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All modules for which code is available

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Source code for pybop

-#
-# Root of the pybop module.
-# Provides access to all shared functionality (models, solvers, etc.).
-#
-# This file is adapted from Pints
-# (see https://github.com/pints-team/pints)
-#
-
-import sys
-from os import path
-
-#
-# Version info
-#
-from pybop.version import __version__
-
-#
-# Constants
-#
-# Float format: a float can be converted to a 17 digit decimal and back without
-# loss of information
-

-[docs]
-FLOAT_FORMAT = "{: .17e}"

-
-# Absolute path to the pybop repo
-

-[docs]
-script_path = path.dirname(__file__)

-
-
-#
-# Cost function class
-#
-from ._costs import BaseCost, RootMeanSquaredError, SumSquaredError
-
-#
-# Dataset class
-#
-from ._dataset import Dataset
-
-#
-# Model classes
-#
-from .models.base_model import BaseModel
-from .models import lithium_ion
-from .models import empirical
-
-#
-# Main optimisation class
-#
-from .optimisation import Optimisation
-
-#
-# Optimiser class
-#
-from .optimisers.base_optimiser import BaseOptimiser
-from .optimisers.nlopt_optimize import NLoptOptimize
-from .optimisers.scipy_optimisers import SciPyMinimize, SciPyDifferentialEvolution
-from .optimisers.pints_optimisers import (
-    GradientDescent,
-    Adam,
-    CMAES,
-    IRPropMin,
-    PSO,
-    SNES,
-    XNES,
-)
-
-#
-# Parameter classes
-#
-from .parameters.parameter import Parameter
-from .parameters.parameter_set import ParameterSet
-from .parameters.priors import Gaussian, Uniform, Exponential
-
-#
-# Problem class
-#
-from ._problem import FittingProblem, DesignProblem
-
-#
-# Plotting class
-#
-from .plotting.plot_cost2d import plot_cost2d
-from .plotting.quick_plot import StandardPlot, quick_plot
-from .plotting.plot_convergence import plot_convergence
-from .plotting.plot_parameters import plot_parameters
-from .plotting.plotly_manager import PlotlyManager
-
-#
-# Remove any imported modules, so we don't expose them as part of pybop
-#
-del sys
-
- -
- - - - - -
- - - - -
-
- -
- -
-
-
- - - - - -
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- -
- -
- -

- - © Copyright 2023, The PyBOP Team. -
- -

-
- -
- -

- Created using Sphinx 7.2.6. -
-

-
- -
- - - -
- -
-

- Built with the PyData Sphinx Theme 0.14.4. -

- -
- -
- -
- - \ No newline at end of file diff --git a/_modules/pybop/_costs.html b/_modules/pybop/_costs.html deleted file mode 100644 index 596524919..000000000 --- a/_modules/pybop/_costs.html +++ /dev/null @@ -1,720 +0,0 @@ - - - - - - - - - - pybop._costs — PyBOP Documentation - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
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Source code for pybop._costs

-import numpy as np
-
-
-

-[docs]
-class BaseCost:
-    """
-    Base class for defining cost functions.
-
-    This class is intended to be subclassed to create specific cost functions
-    for evaluating model predictions against a set of data. The cost function
-    quantifies the goodness-of-fit between the model predictions and the
-    observed data, with a lower cost value indicating a better fit.
-
-    Parameters
-    ----------
-    problem : object
-        A problem instance containing the data and functions necessary for
-        evaluating the cost function.
-    _target : array-like
-        An array containing the target data to fit.
-    x0 : array-like
-        The initial guess for the model parameters.
-    bounds : tuple
-        The bounds for the model parameters.
-    n_parameters : int
-        The number of parameters in the model.
-    """
-
-    def __init__(self, problem):
-        self.problem = problem
-        if problem is not None:
-            self._target = problem._target
-            self.x0 = problem.x0
-            self.bounds = problem.bounds
-            self.n_parameters = problem.n_parameters
-
-

-[docs]
-    def __call__(self, x, grad=None):
-        """
-        Calculate the cost function value for a given set of parameters.
-
-        This method must be implemented by subclasses.
-
-        Parameters
-        ----------
-        x : array-like
-            The parameters for which to evaluate the cost.
-        grad : array-like, optional
-            An array to store the gradient of the cost function with respect
-            to the parameters.
-
-        Returns
-        -------
-        float
-            The calculated cost function value.
-
-        Raises
-        ------
-        NotImplementedError
-            If the method has not been implemented by the subclass.
-        """
-
-        raise NotImplementedError

-

-
-
-
-

-[docs]
-class RootMeanSquaredError(BaseCost):
-    """
-    Root mean square error cost function.
-
-    Computes the root mean square error between model predictions and the target
-    data, providing a measure of the differences between predicted values and
-    observed values.
-
-    Inherits all parameters and attributes from ``BaseCost``.
-
-    """
-
-    def __init__(self, problem):
-        super(RootMeanSquaredError, self).__init__(problem)
-
-

-[docs]
-    def __call__(self, x, grad=None):
-        """
-        Calculate the root mean square error for a given set of parameters.
-
-        Parameters
-        ----------
-        x : array-like
-            The parameters for which to evaluate the cost.
-        grad : array-like, optional
-            An array to store the gradient of the cost function with respect
-            to the parameters.
-
-        Returns
-        -------
-        float
-            The root mean square error.
-
-        Raises
-        ------
-        ValueError
-            If an error occurs during the calculation of the cost.
-        """
-
-        try:
-            prediction = self.problem.evaluate(x)
-
-            if len(prediction) < len(self._target):
-                return np.float64(np.inf)  # simulation stopped early
-            else:
-                return np.sqrt(np.mean((prediction - self._target) ** 2))
-
-        except Exception as e:
-            raise ValueError(f"Error in cost calculation: {e}")

-

-
-
-
-

-[docs]
-class SumSquaredError(BaseCost):
-    """
-    Sum of squared errors cost function.
-
-    Computes the sum of the squares of the differences between model predictions
-    and target data, which serves as a measure of the total error between the
-    predicted and observed values.
-
-    Inherits all parameters and attributes from ``BaseCost``.
-
-    Additional Attributes
-    ---------------------
-    _de : float
-        The gradient of the cost function to use if an error occurs during
-        evaluation. Defaults to 1.0.
-
-    """
-
-    def __init__(self, problem):
-        super(SumSquaredError, self).__init__(problem)
-
-        # Default fail gradient
-        self._de = 1.0
-
-

-[docs]
-    def __call__(self, x, grad=None):
-        """
-        Calculate the sum of squared errors for a given set of parameters.
-
-        Parameters
-        ----------
-        x : array-like
-            The parameters for which to evaluate the cost.
-        grad : array-like, optional
-            An array to store the gradient of the cost function with respect
-            to the parameters.
-
-        Returns
-        -------
-        float
-            The sum of squared errors.
-
-        Raises
-        ------
-        ValueError
-            If an error occurs during the calculation of the cost.
-        """
-        try:
-            prediction = self.problem.evaluate(x)
-
-            if len(prediction) < len(self._target):
-                return np.float64(np.inf)  # simulation stopped early
-            else:
-                return np.sum(
-                    (np.sum(((prediction - self._target) ** 2), axis=0)),
-                    axis=0,
-                )
-
-        except Exception as e:
-            raise ValueError(f"Error in cost calculation: {e}")

-
-
-

-[docs]
-    def evaluateS1(self, x):
-        """
-        Compute the cost and its gradient with respect to the parameters.
-
-        Parameters
-        ----------
-        x : array-like
-            The parameters for which to compute the cost and gradient.
-
-        Returns
-        -------
-        tuple
-            A tuple containing the cost and the gradient. The cost is a float,
-            and the gradient is an array-like of the same length as `x`.
-
-        Raises
-        ------
-        ValueError
-            If an error occurs during the calculation of the cost or gradient.
-        """
-        try:
-            y, dy = self.problem.evaluateS1(x)
-            if len(y) < len(self._target):
-                e = np.float64(np.inf)
-                de = self._de * np.ones(self.problem.n_parameters)
-            else:
-                dy = dy.reshape(
-                    (
-                        self.problem.n_time_data,
-                        self.problem.n_outputs,
-                        self.problem.n_parameters,
-                    )
-                )
-                r = y - self._target
-                e = np.sum(np.sum(r**2, axis=0), axis=0)
-                de = 2 * np.sum(np.sum((r.T * dy.T), axis=2), axis=1)
-
-            return e, de
-
-        except Exception as e:
-            raise ValueError(f"Error in cost calculation: {e}")

-
-
-

-[docs]
-    def set_fail_gradient(self, de):
-        """
-        Set the fail gradient to a specified value.
-
-        The fail gradient is used if an error occurs during the calculation
-        of the gradient. This method allows updating the default gradient value.
-
-        Parameters
-        ----------
-        de : float
-            The new fail gradient value to be used.
-        """
-        de = float(de)
-        self._de = de

-

-
-
- -
- - - - - -
- - - - -
-
- -
- -
-
-
- - - - - -
-
- -
- -
- -

- - © Copyright 2023, The PyBOP Team. -
- -

-
- -
- -

- Created using Sphinx 7.2.6. -
-

-
- -
- - - -
- -
-

- Built with the PyData Sphinx Theme 0.14.4. -

- -
- -
- -
- - \ No newline at end of file diff --git a/_modules/pybop/_dataset.html b/_modules/pybop/_dataset.html deleted file mode 100644 index 3159c5b52..000000000 --- a/_modules/pybop/_dataset.html +++ /dev/null @@ -1,540 +0,0 @@ - - - - - - - - - - pybop._dataset — PyBOP Documentation - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
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Source code for pybop._dataset

-import pybamm
-
-
-

-[docs]
-class Dataset:
-    """
-    Represents a collection of experimental observations.
-
-    This class provides a structured way to store and work with experimental data,
-    which may include applying operations such as interpolation.
-
-    Parameters
-    ----------
-    name : str
-        The name of the dataset, providing a label for identification.
-    data : array-like
-        The actual experimental data, typically in a structured form such as
-        a NumPy array or a pandas DataFrame.
-
-    """
-
-    def __init__(self, name, data):
-        """
-        Initialize a Dataset instance with a name and data.
-
-        Parameters
-        ----------
-        name : str
-            The name for the dataset.
-        data : array-like
-            The experimental data to store within the dataset.
-        """
-
-        self.name = name
-        self.data = data
-
-

-[docs]
-    def __repr__(self):
-        """
-        Return a string representation of the Dataset instance.
-
-        Returns
-        -------
-        str
-            A string that includes the name and data of the dataset.
-        """
-        return f"Dataset: {self.name} \n Data: {self.data}"

-
-
-

-[docs]
-    def Interpolant(self):
-        """
-        Create an interpolation function of the dataset based on the independent variable.
-
-        Currently, only time-based interpolation is supported. This method modifies
-        the instance's Interpolant attribute to be an interpolation function that
-        can be evaluated at different points in time.
-
-        Raises
-        ------
-        NotImplementedError
-            If the independent variable for interpolation is not supported.
-        """
-
-        if self.variable == "time":
-            self.Interpolant = pybamm.Interpolant(self.x, self.y, pybamm.t)
-        else:
-            NotImplementedError("Only time interpolation is supported")

-

-
-
- -
- - - - - -
- - - - -
-
- -
- -
-
-
- - - - - -
-
- -
- -
- -

- - © Copyright 2023, The PyBOP Team. -
- -

-
- -
- -

- Created using Sphinx 7.2.6. -
-

-
- -
- - - -
- -
-

- Built with the PyData Sphinx Theme 0.14.4. -

- -
- -
- -
- - \ No newline at end of file diff --git a/_modules/pybop/_problem.html b/_modules/pybop/_problem.html deleted file mode 100644 index d14a0cded..000000000 --- a/_modules/pybop/_problem.html +++ /dev/null @@ -1,775 +0,0 @@ - - - - - - - - - - pybop._problem — PyBOP Documentation - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
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Source code for pybop._problem

-import numpy as np
-
-
-

-[docs]
-class BaseProblem:
-    """
-    Base class for defining a problem within the PyBOP framework, compatible with PINTS.
-
-    Parameters
-    ----------
-    parameters : list
-        List of parameters for the problem.
-    model : object, optional
-        The model to be used for the problem (default: None).
-    check_model : bool, optional
-        Flag to indicate if the model should be checked (default: True).
-    init_soc : float, optional
-        Initial state of charge (default: None).
-    x0 : np.ndarray, optional
-        Initial parameter values (default: None).
-    """
-
-    def __init__(
-        self,
-        parameters,
-        model=None,
-        check_model=True,
-        init_soc=None,
-        x0=None,
-    ):
-        self._model = model
-        self.check_model = check_model
-        self.parameters = parameters
-        self.init_soc = init_soc
-        self.x0 = x0
-        self.n_parameters = len(self.parameters)
-
-        # Set bounds
-        self.bounds = dict(
-            lower=[param.bounds[0] for param in self.parameters],
-            upper=[param.bounds[1] for param in self.parameters],
-        )
-
-        # Sample from prior for x0
-        if x0 is None:
-            self.x0 = np.zeros(self.n_parameters)
-            for i, param in enumerate(self.parameters):
-                self.x0[i] = param.rvs(1)
-        elif len(x0) != self.n_parameters:
-            raise ValueError("x0 dimensions do not match number of parameters")
-
-        # Add the initial values to the parameter definitions
-        for i, param in enumerate(self.parameters):
-            param.update(value=self.x0[i])
-
-

-[docs]
-    def evaluate(self, x):
-        """
-        Evaluate the model with the given parameters and return the signal.
-
-        Parameters
-        ----------
-        x : np.ndarray
-            Parameter values to evaluate the model at.
-
-        Raises
-        ------
-        NotImplementedError
-            This method must be implemented by subclasses.
-        """
-        raise NotImplementedError

-
-
-

-[docs]
-    def evaluateS1(self, x):
-        """
-        Evaluate the model with the given parameters and return the signal and its derivatives.
-
-        Parameters
-        ----------
-        x : np.ndarray
-            Parameter values to evaluate the model at.
-
-        Raises
-        ------
-        NotImplementedError
-            This method must be implemented by subclasses.
-        """
-        raise NotImplementedError

-

-
-
-
-

-[docs]
-class FittingProblem(BaseProblem):
-    """
-    Problem class for fitting (parameter estimation) problems.
-
-    Extends `BaseProblem` with specifics for fitting a model to a dataset.
-
-    Parameters
-    ----------
-    model : object
-        The model to fit.
-    parameters : list
-        List of parameters for the problem.
-    dataset : list
-        List of data objects to fit the model to.
-    signal : str, optional
-        The signal to fit (default: "Voltage [V]").
-    """
-
-    def __init__(
-        self,
-        model,
-        parameters,
-        dataset,
-        signal="Voltage [V]",
-        check_model=True,
-        init_soc=None,
-        x0=None,
-    ):
-        super().__init__(parameters, model, check_model, init_soc, x0)
-        if model is not None:
-            self._model.signal = signal
-        self.signal = signal
-        self._dataset = {o.name: o for o in dataset}
-        self.n_outputs = len([self.signal])
-
-        # Check that the dataset contains time and current
-        for name in ["Time [s]", "Current function [A]", signal]:
-            if name not in self._dataset:
-                raise ValueError(f"expected {name} in list of dataset")
-
-        self._time_data = self._dataset["Time [s]"].data
-        self.n_time_data = len(self._time_data)
-        self._target = self._dataset[signal].data
-
-        if np.any(self._time_data < 0):
-            raise ValueError("Times can not be negative.")
-        if np.any(self._time_data[:-1] >= self._time_data[1:]):
-            raise ValueError("Times must be increasing.")
-
-        if len(self._target) != len(self._time_data):
-            raise ValueError("Time data and signal data must be the same length.")
-
-        # Build the model
-        if self._model._built_model is None:
-            self._model.build(
-                dataset=self._dataset,
-                parameters=self.parameters,
-                check_model=self.check_model,
-                init_soc=self.init_soc,
-            )
-
-

-[docs]
-    def evaluate(self, x):
-        """
-        Evaluate the model with the given parameters and return the signal.
-
-        Parameters
-        ----------
-        x : np.ndarray
-            Parameter values to evaluate the model at.
-        """
-
-        y = np.asarray(self._model.simulate(inputs=x, t_eval=self._time_data))
-
-        return y

-
-
-

-[docs]
-    def evaluateS1(self, x):
-        """
-        Evaluate the model with the given parameters and return the signal and its derivatives.
-
-        Parameters
-        ----------
-        x : np.ndarray
-            Parameter values to evaluate the model at.
-        """
-
-        y, dy = self._model.simulateS1(
-            inputs=x,
-            t_eval=self._time_data,
-        )
-
-        return (np.asarray(y), np.asarray(dy))

-
-
-

-[docs]
-    def target(self):
-        """
-        Return the target dataset.
-
-        Returns
-        -------
-        np.ndarray
-            The target dataset array.
-        """
-        return self._target

-

-
-
-
-

-[docs]
-class DesignProblem(BaseProblem):
-    """
-    Problem class for design optimization problems.
-
-    Extends `BaseProblem` with specifics for applying a model to an experimental design.
-
-    Parameters
-    ----------
-    model : object
-        The model to apply the design to.
-    parameters : list
-        List of parameters for the problem.
-    experiment : object
-        The experimental setup to apply the model to.
-    """
-
-    def __init__(
-        self,
-        model,
-        parameters,
-        experiment,
-        check_model=True,
-        init_soc=None,
-        x0=None,
-    ):
-        super().__init__(parameters, model, check_model, init_soc, x0)
-        self.experiment = experiment
-        self._target = None
-
-        # Build the model if required
-        if experiment is not None:
-            # Leave the build until later to apply the experiment
-            self._model.parameters = self.parameters
-            if self.parameters is not None:
-                self._model.fit_keys = [param.name for param in self.parameters]
-
-        elif self._model._built_model is None:
-            self._model.build(
-                experiment=self.experiment,
-                parameters=self.parameters,
-                check_model=self.check_model,
-                init_soc=self.init_soc,
-            )
-
-

-[docs]
-    def evaluate(self, x):
-        """
-        Evaluate the model with the given parameters and return the signal.
-
-        Parameters
-        ----------
-        x : np.ndarray
-            Parameter values to evaluate the model at.
-        """
-
-        y = np.asarray(self._model.simulate(inputs=x, t_eval=self._time_data))
-
-        return y

-
-
-

-[docs]
-    def evaluateS1(self, x):
-        """
-        Evaluate the model with the given parameters and return the signal and its derivatives.
-
-        Parameters
-        ----------
-        x : np.ndarray
-            Parameter values to evaluate the model at.
-        """
-
-        y, dy = self._model.simulateS1(
-            inputs=x,
-            t_eval=self._time_data,
-        )
-
-        return (np.asarray(y), np.asarray(dy))

-
-
-

-[docs]
-    def target(self):
-        """
-        Return the target dataset (not applicable for design problems).
-
-        Returns
-        -------
-        None
-        """
-        return self._target

-

-
-
- -
- - - - - -
- - - - -
-
- -
- -
-
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- - - - - -
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- - © Copyright 2023, The PyBOP Team. -
- -

-
- -
- -

- Created using Sphinx 7.2.6. -
-

-
- -
- - - -
- -
-

- Built with the PyData Sphinx Theme 0.14.4. -

- -
- -
- -
- - \ No newline at end of file diff --git a/_modules/pybop/models/base_model.html b/_modules/pybop/models/base_model.html deleted file mode 100644 index eff68781a..000000000 --- a/_modules/pybop/models/base_model.html +++ /dev/null @@ -1,871 +0,0 @@ - - - - - - - - - - pybop.models.base_model — PyBOP Documentation - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
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Source code for pybop.models.base_model

-import pybamm
-import numpy as np
-
-
-

-[docs]
-class BaseModel:
-    """
-    A base class for constructing and simulating models using PyBaMM.
-
-    This class serves as a foundation for building specific models in PyBaMM.
-    It provides methods to set up the model, define parameters, and perform
-    simulations. The class is designed to be subclassed for creating models
-    with custom behavior.
-
-    Methods
-    -------
-    build(dataset=None, parameters=None, check_model=True, init_soc=None)
-        Construct the PyBaMM model if not already built.
-    set_init_soc(init_soc)
-        Set the initial state of charge for the battery model.
-    set_params()
-        Assign the parameters to the model.
-    simulate(inputs, t_eval)
-        Execute the forward model simulation and return the result.
-    simulateS1(inputs, t_eval)
-        Perform the forward model simulation with sensitivities.
-    predict(inputs=None, t_eval=None, parameter_set=None, experiment=None, init_soc=None)
-        Solve the model using PyBaMM's simulation framework and return the solution.
-    """
-
-    def __init__(self, name="Base Model"):
-        """
-        Initialize the BaseModel with an optional name.
-
-        Parameters
-        ----------
-        name : str, optional
-            The name given to the model instance.
-        """
-        self.name = name
-        self.pybamm_model = None
-        self.parameters = None
-        self.dataset = None
-        self.signal = None
-
-

-[docs]
-    def build(
-        self,
-        dataset=None,
-        parameters=None,
-        check_model=True,
-        init_soc=None,
-    ):
-        """
-        Construct the PyBaMM model if not already built, and set parameters.
-
-        This method initializes the model components, applies the given parameters,
-        sets up the mesh and discretization if needed, and prepares the model
-        for simulations.
-
-        Parameters
-        ----------
-        dataset : pybamm.Dataset, optional
-            The dataset to be used in the model construction.
-        parameters : dict, optional
-            A dictionary containing parameter values to apply to the model.
-        check_model : bool, optional
-            If True, the model will be checked for correctness after construction.
-        init_soc : float, optional
-            The initial state of charge to be used in simulations.
-        """
-        self.dataset = dataset
-        self.parameters = parameters
-        if self.parameters is not None:
-            self.fit_keys = [param.name for param in self.parameters]
-
-        if init_soc is not None:
-            self.set_init_soc(init_soc)
-
-        if self._built_model:
-            return
-
-        elif self.pybamm_model.is_discretised:
-            self._model_with_set_params = self.pybamm_model
-            self._built_model = self.pybamm_model
-        else:
-            self.set_params()
-            self._mesh = pybamm.Mesh(self.geometry, self.submesh_types, self.var_pts)
-            self._disc = pybamm.Discretisation(self.mesh, self.spatial_methods)
-            self._built_model = self._disc.process_model(
-                self._model_with_set_params, inplace=False, check_model=check_model
-            )
-
-            # Clear solver
-            self._solver._model_set_up = {}

-
-
-

-[docs]
-    def set_init_soc(self, init_soc):
-        """
-        Set the initial state of charge for the battery model.
-
-        Parameters
-        ----------
-        init_soc : float
-            The initial state of charge to be used in the model.
-        """
-        if self._built_initial_soc != init_soc:
-            # reset
-            self._model_with_set_params = None
-            self._built_model = None
-            self.op_conds_to_built_models = None
-            self.op_conds_to_built_solvers = None
-
-        param = self.pybamm_model.param
-        self._parameter_set = (
-            self._unprocessed_parameter_set.set_initial_stoichiometries(
-                init_soc, param=param, inplace=False
-            )
-        )
-        # Save solved initial SOC in case we need to rebuild the model
-        self._built_initial_soc = init_soc

-
-
-

-[docs]
-    def set_params(self):
-        """
-        Assign the parameters to the model.
-
-        This method processes the model with the given parameters, sets up
-        the geometry, and updates the model instance.
-        """
-        if self.model_with_set_params:
-            return
-
-        # Mark any simulation inputs in the parameter set
-        if self.parameters is not None:
-            for i in self.fit_keys:
-                self._parameter_set[i] = "[input]"
-
-        if self.dataset is not None and self.parameters is not None:
-            if "Current function [A]" not in self.fit_keys:
-                self.parameter_set["Current function [A]"] = pybamm.Interpolant(
-                    self.dataset["Time [s]"].data,
-                    self.dataset["Current function [A]"].data,
-                    pybamm.t,
-                )
-                # Set t_eval
-                self.time_data = self._parameter_set["Current function [A]"].x[0]
-
-        self._model_with_set_params = self._parameter_set.process_model(
-            self._unprocessed_model, inplace=False
-        )
-        self._parameter_set.process_geometry(self.geometry)
-        self.pybamm_model = self._model_with_set_params

-
-
-

-[docs]
-    def simulate(self, inputs, t_eval):
-        """
-        Execute the forward model simulation and return the result.
-
-        Parameters
-        ----------
-        inputs : dict or array-like
-            The input parameters for the simulation. If array-like, it will be
-            converted to a dictionary using the model's fit keys.
-        t_eval : array-like
-            An array of time points at which to evaluate the solution.
-
-        Returns
-        -------
-        array-like
-            The simulation result corresponding to the specified signal.
-
-        Raises
-        ------
-        ValueError
-            If the model has not been built before simulation.
-        """
-
-        if self._built_model is None:
-            raise ValueError("Model must be built before calling simulate")
-        else:
-            if not isinstance(inputs, dict):
-                inputs = {key: inputs[i] for i, key in enumerate(self.fit_keys)}
-
-            return self.solver.solve(self.built_model, inputs=inputs, t_eval=t_eval)[
-                self.signal
-            ].data

-
-
-

-[docs]
-    def simulateS1(self, inputs, t_eval):
-        """
-        Perform the forward model simulation with sensitivities.
-
-        Parameters
-        ----------
-        inputs : dict or array-like
-            The input parameters for the simulation. If array-like, it will be
-            converted to a dictionary using the model's fit keys.
-        t_eval : array-like
-            An array of time points at which to evaluate the solution and its
-            sensitivities.
-
-        Returns
-        -------
-        tuple
-            A tuple containing the simulation result and the sensitivities.
-
-        Raises
-        ------
-        ValueError
-            If the model has not been built before simulation.
-        """
-
-        if self._built_model is None:
-            raise ValueError("Model must be built before calling simulate")
-        else:
-            if not isinstance(inputs, dict):
-                inputs = {key: inputs[i] for i, key in enumerate(self.fit_keys)}
-
-            sol = self.solver.solve(
-                self.built_model,
-                inputs=inputs,
-                t_eval=t_eval,
-                calculate_sensitivities=True,
-            )
-
-            return (
-                sol[self.signal].data,
-                np.asarray(
-                    [
-                        sol[self.signal].sensitivities[key].toarray()
-                        for key in self.fit_keys
-                    ]
-                ).T,
-            )

-
-
-

-[docs]
-    def predict(
-        self,
-        inputs=None,
-        t_eval=None,
-        parameter_set=None,
-        experiment=None,
-        init_soc=None,
-    ):
-        """
-        Solve the model using PyBaMM's simulation framework and return the solution.
-
-        This method sets up a PyBaMM simulation by configuring the model, parameters, experiment
-        (if any), and initial state of charge (if provided). It then solves the simulation and
-        returns the resulting solution object.
-
-        Parameters
-        ----------
-        inputs : dict or array-like, optional
-            Input parameters for the simulation. If the input is array-like, it is converted
-            to a dictionary using the model's fitting keys. Defaults to None, indicating
-            that the default parameters should be used.
-        t_eval : array-like, optional
-            An array of time points at which to evaluate the solution. Defaults to None,
-            which means the time points need to be specified within experiment or elsewhere.
-        parameter_set : pybamm.ParameterValues, optional
-            A PyBaMM ParameterValues object or a dictionary containing the parameter values
-            to use for the simulation. Defaults to the model's current ParameterValues if None.
-        experiment : pybamm.Experiment, optional
-            A PyBaMM Experiment object specifying the experimental conditions under which
-            the simulation should be run. Defaults to None, indicating no experiment.
-        init_soc : float, optional
-            The initial state of charge for the simulation, as a fraction (between 0 and 1).
-            Defaults to None.
-
-        Returns
-        -------
-        pybamm.Solution
-            The solution object returned after solving the simulation.
-
-        Raises
-        ------
-        ValueError
-            If the model has not been configured properly before calling this method or
-            if PyBaMM models are not supported by the current simulation method.
-
-        """
-        parameter_set = parameter_set or self._parameter_set
-        if inputs is not None:
-            if not isinstance(inputs, dict):
-                inputs = {key: inputs[i] for i, key in enumerate(self.fit_keys)}
-            parameter_set.update(inputs)
-
-        if self._unprocessed_model is not None:
-            if experiment is None:
-                return pybamm.Simulation(
-                    self._unprocessed_model,
-                    parameter_values=parameter_set,
-                ).solve(t_eval=t_eval, initial_soc=init_soc)
-            else:
-                return pybamm.Simulation(
-                    self._unprocessed_model,
-                    experiment=experiment,
-                    parameter_values=parameter_set,
-                ).solve(initial_soc=init_soc)
-        else:
-            raise ValueError("This sim method currently only supports PyBaMM models")

-
-
-    @property
-

-[docs]
-    def built_model(self):
-        return self._built_model

-
-
-    @property
-

-[docs]
-    def parameter_set(self):
-        return self._parameter_set

-
-
-    @parameter_set.setter
-    def parameter_set(self, parameter_set):
-        self._parameter_set = parameter_set.copy()
-
-    @property
-

-[docs]
-    def model_with_set_params(self):
-        return self._model_with_set_params

-
-
-    @property
-

-[docs]
-    def geometry(self):
-        return self._geometry

-
-
-    @geometry.setter
-    def geometry(self, geometry):
-        self._geometry = geometry.copy()
-
-    @property
-

-[docs]
-    def submesh_types(self):
-        return self._submesh_types

-
-
-    @submesh_types.setter
-    def submesh_types(self, submesh_types):
-        self._submesh_types = submesh_types.copy()
-
-    @property
-

-[docs]
-    def mesh(self):
-        return self._mesh

-
-
-    @property
-

-[docs]
-    def var_pts(self):
-        return self._var_pts

-
-
-    @var_pts.setter
-    def var_pts(self, var_pts):
-        self._var_pts = var_pts.copy()
-
-    @property
-

-[docs]
-    def spatial_methods(self):
-        return self._spatial_methods

-
-
-    @spatial_methods.setter
-    def spatial_methods(self, spatial_methods):
-        self._spatial_methods = spatial_methods.copy()
-
-    @property
-

-[docs]
-    def solver(self):
-        return self._solver

-
-
-    @solver.setter
-    def solver(self, solver):
-        self._solver = solver.copy()

-
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- - © Copyright 2023, The PyBOP Team. -
- -

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- Built with the PyData Sphinx Theme 0.14.4. -

- -
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- - \ No newline at end of file diff --git a/_modules/pybop/models/empirical/ecm.html b/_modules/pybop/models/empirical/ecm.html deleted file mode 100644 index e64763717..000000000 --- a/_modules/pybop/models/empirical/ecm.html +++ /dev/null @@ -1,547 +0,0 @@ - - - - - - - - - - pybop.models.empirical.ecm — PyBOP Documentation - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
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Source code for pybop.models.empirical.ecm

-import pybamm
-from ..base_model import BaseModel
-
-
-

-[docs]
-class Thevenin(BaseModel):
-    """
-    The Thevenin class represents an equivalent circuit model based on the Thevenin model in PyBaMM.
-
-    This class encapsulates the PyBaMM equivalent circuit Thevenin model, providing an interface
-    to define the parameters, geometry, submesh types, variable points, spatial methods, and solver
-    to be used for simulations.
-
-    Parameters
-    ----------
-    name : str, optional
-        A name for the model instance. Defaults to "Equivalent Circuit Thevenin Model".
-    parameter_set : dict or None, optional
-        A dictionary of parameters to be used for the model. If None, the default parameters from PyBaMM are used.
-    geometry : dict or None, optional
-        The geometry definitions for the model. If None, the default geometry from PyBaMM is used.
-    submesh_types : dict or None, optional
-        The types of submeshes to use. If None, the default submesh types from PyBaMM are used.
-    var_pts : dict or None, optional
-        The number of points for each variable in the model to define the discretization. If None, the default is used.
-    spatial_methods : dict or None, optional
-        The spatial methods to be used for discretization. If None, the default spatial methods from PyBaMM are used.
-    solver : pybamm.Solver or None, optional
-        The solver to use for simulating the model. If None, the default solver from PyBaMM is used.
-    options : dict or None, optional
-        A dictionary of options to pass to the PyBaMM Thevenin model.
-    **kwargs :
-        Additional arguments passed to the PyBaMM Thevenin model constructor.
-    """
-
-    def __init__(
-        self,
-        name="Equivalent Circuit Thevenin Model",
-        parameter_set=None,
-        geometry=None,
-        submesh_types=None,
-        var_pts=None,
-        spatial_methods=None,
-        solver=None,
-        options=None,
-        **kwargs,
-    ):
-        super().__init__()
-        self.pybamm_model = pybamm.equivalent_circuit.Thevenin(
-            options=options, **kwargs
-        )
-        self._unprocessed_model = self.pybamm_model
-        self.name = name
-
-        if isinstance(parameter_set, dict):
-            self.default_parameter_values = pybamm.ParameterValues(parameter_set)
-            self._parameter_set = self.default_parameter_values
-        else:
-            self.default_parameter_values = self.pybamm_model.default_parameter_values
-            self._parameter_set = (
-                parameter_set or self.pybamm_model.default_parameter_values
-            )
-
-        self._unprocessed_parameter_set = self._parameter_set
-
-        self.geometry = geometry or self.pybamm_model.default_geometry
-        self.submesh_types = submesh_types or self.pybamm_model.default_submesh_types
-        self.var_pts = var_pts or self.pybamm_model.default_var_pts
-        self.spatial_methods = (
-            spatial_methods or self.pybamm_model.default_spatial_methods
-        )
-        self.solver = solver or self.pybamm_model.default_solver
-
-        self._model_with_set_params = None
-        self._built_model = None
-        self._built_initial_soc = None
-        self._mesh = None
-        self._disc = None

-
-
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-
- -
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- -

- - © Copyright 2023, The PyBOP Team. -
- -

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- Built with the PyData Sphinx Theme 0.14.4. -

- -
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- - \ No newline at end of file diff --git a/_modules/pybop/models/lithium_ion/echem.html b/_modules/pybop/models/lithium_ion/echem.html deleted file mode 100644 index f3d053a71..000000000 --- a/_modules/pybop/models/lithium_ion/echem.html +++ /dev/null @@ -1,611 +0,0 @@ - - - - - - - - - - pybop.models.lithium_ion.echem — PyBOP Documentation - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
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Source code for pybop.models.lithium_ion.echem

-import pybamm
-from ..base_model import BaseModel
-
-
-

-[docs]
-class SPM(BaseModel):
-    """
-    Wraps the Single Particle Model (SPM) for simulating lithium-ion batteries, as implemented in PyBaMM.
-
-    The SPM is a simplified physics-based model that represents a lithium-ion cell using a single
-    spherical particle to simulate the behavior of the negative and positive electrodes.
-
-    Parameters
-    ----------
-    name : str, optional
-        The name for the model instance, defaulting to "Single Particle Model".
-    parameter_set : pybamm.ParameterValues or dict, optional
-        The parameters for the model. If None, default parameters provided by PyBaMM are used.
-    geometry : dict, optional
-        The geometry definitions for the model. If None, default geometry from PyBaMM is used.
-    submesh_types : dict, optional
-        The types of submeshes to use. If None, default submesh types from PyBaMM are used.
-    var_pts : dict, optional
-        The discretization points for each variable in the model. If None, default points from PyBaMM are used.
-    spatial_methods : dict, optional
-        The spatial methods used for discretization. If None, default spatial methods from PyBaMM are used.
-    solver : pybamm.Solver, optional
-        The solver to use for simulating the model. If None, the default solver from PyBaMM is used.
-    options : dict, optional
-        A dictionary of options to customize the behavior of the PyBaMM model.
-    """
-
-    def __init__(
-        self,
-        name="Single Particle Model",
-        parameter_set=None,
-        geometry=None,
-        submesh_types=None,
-        var_pts=None,
-        spatial_methods=None,
-        solver=None,
-        options=None,
-    ):
-        super().__init__()
-        self.pybamm_model = pybamm.lithium_ion.SPM(options=options)
-        self._unprocessed_model = self.pybamm_model
-        self.name = name
-
-        # Set parameters, using either the provided ones or the default
-        self.default_parameter_values = self.pybamm_model.default_parameter_values
-        self._parameter_set = (
-            parameter_set or self.pybamm_model.default_parameter_values
-        )
-        self._unprocessed_parameter_set = self._parameter_set
-
-        # Define model geometry and discretization
-        self.geometry = geometry or self.pybamm_model.default_geometry
-        self.submesh_types = submesh_types or self.pybamm_model.default_submesh_types
-        self.var_pts = var_pts or self.pybamm_model.default_var_pts
-        self.spatial_methods = (
-            spatial_methods or self.pybamm_model.default_spatial_methods
-        )
-        self.solver = solver or self.pybamm_model.default_solver
-
-        # Internal attributes for the built model are initialized but not set
-        self._model_with_set_params = None
-        self._built_model = None
-        self._built_initial_soc = None
-        self._mesh = None
-        self._disc = None

-
-
-
-

-[docs]
-class SPMe(BaseModel):
-    """
-    Represents the Single Particle Model with Electrolyte (SPMe) for lithium-ion batteries.
-
-    The SPMe extends the basic Single Particle Model (SPM) by incorporating electrolyte dynamics,
-    making it suitable for simulations where electrolyte effects are non-negligible. This class
-    provides a framework to define the model parameters, geometry, mesh types, discretization
-    points, spatial methods, and numerical solvers for simulation within the PyBaMM ecosystem.
-
-    Parameters
-    ----------
-    name: str, optional
-        A name for the model instance, defaults to "Single Particle Model with Electrolyte".
-    parameter_set: pybamm.ParameterValues or dict, optional
-        A dictionary or a ParameterValues object containing the parameters for the model. If None, the default PyBaMM parameters for SPMe are used.
-    geometry: dict, optional
-        A dictionary defining the model's geometry. If None, the default PyBaMM geometry for SPMe is used.
-    submesh_types: dict, optional
-        A dictionary defining the types of submeshes to use. If None, the default PyBaMM submesh types for SPMe are used.
-    var_pts: dict, optional
-        A dictionary specifying the number of points for each variable for discretization. If None, the default PyBaMM variable points for SPMe are used.
-    spatial_methods: dict, optional
-        A dictionary specifying the spatial methods for discretization. If None, the default PyBaMM spatial methods for SPMe are used.
-    solver: pybamm.Solver, optional
-        The solver to use for simulating the model. If None, the default PyBaMM solver for SPMe is used.
-    options: dict, optional
-        A dictionary of options to customize the behavior of the PyBaMM model.
-    """
-
-    def __init__(
-        self,
-        name="Single Particle Model with Electrolyte",
-        parameter_set=None,
-        geometry=None,
-        submesh_types=None,
-        var_pts=None,
-        spatial_methods=None,
-        solver=None,
-        options=None,
-    ):
-        super().__init__()
-        self.pybamm_model = pybamm.lithium_ion.SPMe(options=options)
-        self._unprocessed_model = self.pybamm_model
-        self.name = name
-
-        # Set parameters, using either the provided ones or the default
-        self.default_parameter_values = self.pybamm_model.default_parameter_values
-        self._parameter_set = (
-            parameter_set or self.pybamm_model.default_parameter_values
-        )
-        self._unprocessed_parameter_set = self._parameter_set
-
-        # Define model geometry and discretization
-        self.geometry = geometry or self.pybamm_model.default_geometry
-        self.submesh_types = submesh_types or self.pybamm_model.default_submesh_types
-        self.var_pts = var_pts or self.pybamm_model.default_var_pts
-        self.spatial_methods = (
-            spatial_methods or self.pybamm_model.default_spatial_methods
-        )
-        self.solver = solver or self.pybamm_model.default_solver
-
-        # Internal attributes for the built model are initialized but not set
-        self._model_with_set_params = None
-        self._built_model = None
-        self._built_initial_soc = None
-        self._mesh = None
-        self._disc = None

-
-
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- - © Copyright 2023, The PyBOP Team. -
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Source code for pybop.optimisation

-import pybop
-import pints
-import numpy as np
-
-
-

-[docs]
-class Optimisation:
-    """
-    A class for conducting optimization using PyBOP or PINTS optimizers.
-
-    Parameters
-    ----------
-    cost : pints.ErrorMeasure or pints.LogPDF
-        An objective function to be optimized, which can be either a PINTS error measure or log PDF.
-    optimiser : pints.Optimiser or subclass of pybop.BaseOptimizer, optional
-        An optimizer from either the PINTS or PyBOP framework to perform the optimization (default: None).
-    sigma0 : float or sequence, optional
-        Initial step size or standard deviation for the optimizer (default: None).
-    verbose : bool, optional
-        If True, the optimization progress is printed (default: False).
-
-    Attributes
-    ----------
-    x0 : numpy.ndarray
-        Initial parameter values for the optimization.
-    bounds : dict
-        Dictionary containing the parameter bounds with keys 'lower' and 'upper'.
-    n_parameters : int
-        Number of parameters in the optimization problem.
-    sigma0 : float or sequence
-        Initial step size or standard deviation for the optimizer.
-    log : list
-        Log of the optimization process.
-    """
-
-    def __init__(
-        self,
-        cost,
-        optimiser=None,
-        sigma0=None,
-        verbose=False,
-    ):
-        self.cost = cost
-        self.optimiser = optimiser
-        self.verbose = verbose
-        self.x0 = cost.x0
-        self.bounds = cost.bounds
-        self.n_parameters = cost.n_parameters
-        self.sigma0 = sigma0
-        self.log = []
-
-        # Convert x0 to pints vector
-        self._x0 = pints.vector(self.x0)
-
-        # PyBOP doesn't currently support the pints transformation class
-        self._transformation = None
-
-        # Check if minimising or maximising
-        self._minimising = not isinstance(cost, pints.LogPDF)
-        if self._minimising:
-            self._function = self.cost
-        else:
-            self._function = pints.ProbabilityBasedError(cost)
-        del cost
-
-        # Construct Optimiser
-        self.pints = True
-
-        if self.optimiser is None:
-            self.optimiser = pybop.CMAES
-        elif issubclass(self.optimiser, pints.Optimiser):
-            pass
-        else:
-            self.pints = False
-
-            if issubclass(self.optimiser, pybop.NLoptOptimize):
-                self.optimiser = self.optimiser(self.n_parameters)
-
-            elif issubclass(
-                self.optimiser, (pybop.SciPyMinimize, pybop.SciPyDifferentialEvolution)
-            ):
-                self.optimiser = self.optimiser()
-
-            else:
-                raise ValueError("Unknown optimiser type")
-
-        if self.pints:
-            self.optimiser = self.optimiser(self.x0, self.sigma0, self.bounds)
-
-        # Check if sensitivities are required
-        self._needs_sensitivities = self.optimiser.needs_sensitivities()
-
-        # Track optimiser's f_best or f_guessed
-        self._use_f_guessed = None
-        self.set_f_guessed_tracking()
-
-        # Parallelisation
-        self._parallel = False
-        self._n_workers = 1
-        self.set_parallel()
-
-        # User callback
-        self._callback = None
-
-        # Define stopping criteria
-        # Maximum iterations
-        self._max_iterations = None
-        self.set_max_iterations()
-
-        # Maximum unchanged iterations
-        self._unchanged_threshold = 1  # smallest significant f change
-        self._unchanged_max_iterations = None
-        self.set_max_unchanged_iterations()
-
-        # Maximum evaluations
-        self._max_evaluations = None
-
-        # Threshold value
-        self._threshold = None
-
-        # Post-run statistics
-        self._evaluations = None
-        self._iterations = None
-
-

-[docs]
-    def run(self):
-        """
-        Run the optimization and return the optimized parameters and final cost.
-
-        Returns
-        -------
-        x : numpy.ndarray
-            The best parameter set found by the optimization.
-        final_cost : float
-            The final cost associated with the best parameters.
-        """
-
-        if self.pints:
-            x, final_cost = self._run_pints()
-        elif not self.pints:
-            x, final_cost = self._run_pybop()
-
-        # Store the optimised parameters
-        if self.cost.problem is not None:
-            self.store_optimised_parameters(x)
-
-        return x, final_cost

-
-
-

-[docs]
-    def _run_pybop(self):
-        """
-        Internal method to run the optimization using a PyBOP optimizer.
-
-        Returns
-        -------
-        x : numpy.ndarray
-            The best parameter set found by the optimization.
-        final_cost : float
-            The final cost associated with the best parameters.
-        """
-        x, final_cost = self.optimiser.optimise(
-            cost_function=self.cost,
-            x0=self.x0,
-            bounds=self.bounds,
-            maxiter=self._max_iterations,
-        )
-        self.log = self.optimiser.log
-
-        return x, final_cost

-
-
-

-[docs]
-    def _run_pints(self):
-        """
-        Internal method to run the optimization using a PINTS optimizer.
-
-        Returns
-        -------
-        x : numpy.ndarray
-            The best parameter set found by the optimization.
-        final_cost : float
-            The final cost associated with the best parameters.
-
-        See Also
-        --------
-        This method is heavily based on the run method in the PINTS.OptimisationController class.
-        """
-
-        # Check stopping criteria
-        has_stopping_criterion = False
-        has_stopping_criterion |= self._max_iterations is not None
-        has_stopping_criterion |= self._unchanged_max_iterations is not None
-        has_stopping_criterion |= self._max_evaluations is not None
-        has_stopping_criterion |= self._threshold is not None
-        if not has_stopping_criterion:
-            raise ValueError("At least one stopping criterion must be set.")
-
-        # Iterations and function evaluations
-        iteration = 0
-        evaluations = 0
-
-        # Unchanged iterations counter
-        unchanged_iterations = 0
-
-        # Choose method to evaluate
-        f = self._function
-        if self._needs_sensitivities:
-            f = f.evaluateS1
-
-        # Create evaluator object
-        if self._parallel:
-            # Get number of workers
-            n_workers = self._n_workers
-
-            # For population based optimisers, don't use more workers than
-            # particles!
-            if isinstance(self._optimiser, pints.PopulationBasedOptimiser):
-                n_workers = min(n_workers, self._optimiser.population_size())
-            evaluator = pints.ParallelEvaluator(f, n_workers=n_workers)
-        else:
-            evaluator = pints.SequentialEvaluator(f)
-
-        # Keep track of current best and best-guess scores.
-        fb = fg = np.inf
-
-        # Internally we always minimise! Keep a 2nd value to show the user.
-        fg_user = (fb, fg) if self._minimising else (-fb, -fg)
-
-        # Keep track of the last significant change
-        f_sig = np.inf
-
-        # Run the ask-and-tell loop
-        running = True
-        try:
-            while running:
-                # Ask optimiser for new points
-                xs = self.optimiser.ask()
-
-                # Evaluate points
-                fs = evaluator.evaluate(xs)
-
-                # Tell optimiser about function values
-                self.optimiser.tell(fs)
-
-                # Update the scores
-                fb = self.optimiser.f_best()
-                fg = self.optimiser.f_guessed()
-                fg_user = (fb, fg) if self._minimising else (-fb, -fg)
-
-                # Check for significant changes
-                f_new = fg if self._use_f_guessed else fb
-                if np.abs(f_new - f_sig) >= self._unchanged_threshold:
-                    unchanged_iterations = 0
-                    f_sig = f_new
-                else:
-                    unchanged_iterations += 1
-
-                # Update counts
-                evaluations += len(fs)
-                iteration += 1
-                self.log.append(xs)
-
-                # Check stopping criteria:
-                # Maximum number of iterations
-                if (
-                    self._max_iterations is not None
-                    and iteration >= self._max_iterations
-                ):
-                    running = False
-                    halt_message = (
-                        "Maximum number of iterations (" + str(iteration) + ") reached."
-                    )
-
-                # Maximum number of iterations without significant change
-                halt = (
-                    self._unchanged_max_iterations is not None
-                    and unchanged_iterations >= self._unchanged_max_iterations
-                )
-                if running and halt:
-                    running = False
-                    halt_message = (
-                        "No significant change for "
-                        + str(unchanged_iterations)
-                        + " iterations."
-                    )
-
-                # Maximum number of evaluations
-                if (
-                    self._max_evaluations is not None
-                    and evaluations >= self._max_evaluations
-                ):
-                    running = False
-                    halt_message = (
-                        "Maximum number of evaluations ("
-                        + str(self._max_evaluations)
-                        + ") reached."
-                    )
-
-                # Threshold value
-                halt = self._threshold is not None and f_new < self._threshold
-                if running and halt:
-                    running = False
-                    halt_message = (
-                        "Objective function crossed threshold: "
-                        + str(self._threshold)
-                        + "."
-                    )
-
-                # Error in optimiser
-                error = self.optimiser.stop()
-                if error:
-                    running = False
-                    halt_message = str(error)
-
-                elif self._callback is not None:
-                    self._callback(iteration - 1, self.optimiser)
-
-        except (Exception, SystemExit, KeyboardInterrupt):
-            # Show last result and exit
-            print("\n" + "-" * 40)
-            print("Unexpected termination.")
-            print("Current score: " + str(fg_user))
-            print("Current position:")
-
-            # Show current parameters
-            x_user = self.optimiser.x_guessed()
-            if self._transformation is not None:
-                x_user = self._transformation.to_model(x_user)
-            for p in x_user:
-                print(pints.strfloat(p))
-            print("-" * 40)
-            raise
-
-        if self.verbose:
-            print("Halt: " + halt_message)
-
-        # Save post-run statistics
-        self._evaluations = evaluations
-        self._iterations = iteration
-
-        # Get best parameters
-        if self._use_f_guessed:
-            x = self.optimiser.x_guessed()
-            f = self.optimiser.f_guessed()
-        else:
-            x = self.optimiser.x_best()
-            f = self.optimiser.f_best()
-
-        # Inverse transform search parameters
-        if self._transformation is not None:
-            x = self._transformation.to_model(x)
-
-        # Return best position and score
-        return x, f if self._minimising else -f

-
-
-

-[docs]
-    def f_guessed_tracking(self):
-        """
-        Check if f_guessed instead of f_best is being tracked.
-        Credit: PINTS
-
-        Returns
-        -------
-        bool
-            True if f_guessed is being tracked, False otherwise.
-        """
-        return self._use_f_guessed

-
-
-

-[docs]
-    def set_f_guessed_tracking(self, use_f_guessed=False):
-        """
-        Set the method used to track the optimizer progress.
-        Credit: PINTS
-
-        Parameters
-        ----------
-        use_f_guessed : bool, optional
-            If True, track f_guessed; otherwise, track f_best (default: False).
-        """
-        self._use_f_guessed = bool(use_f_guessed)

-
-
-

-[docs]
-    def set_max_evaluations(self, evaluations=None):
-        """
-        Set a maximum number of evaluations stopping criterion.
-        Credit: PINTS
-
-        Parameters
-        ----------
-        evaluations : int, optional
-            The maximum number of evaluations after which to stop the optimization (default: None).
-        """
-        if evaluations is not None:
-            evaluations = int(evaluations)
-            if evaluations < 0:
-                raise ValueError("Maximum number of evaluations cannot be negative.")
-        self._max_evaluations = evaluations

-
-
-

-[docs]
-    def set_parallel(self, parallel=False):
-        """
-        Enable or disable parallel evaluation.
-        Credit: PINTS
-
-        Parameters
-        ----------
-        parallel : bool or int, optional
-            If True, use as many worker processes as there are CPU cores. If an integer, use that many workers.
-            If False or 0, disable parallelism (default: False).
-        """
-        if parallel is True:
-            self._parallel = True
-            self._n_workers = pints.ParallelEvaluator.cpu_count()
-        elif parallel >= 1:
-            self._parallel = True
-            self._n_workers = int(parallel)
-        else:
-            self._parallel = False
-            self._n_workers = 1

-
-
-

-[docs]
-    def set_max_iterations(self, iterations=1000):
-        """
-        Set the maximum number of iterations as a stopping criterion.
-        Credit: PINTS
-
-        Parameters
-        ----------
-        iterations : int, optional
-            The maximum number of iterations to run (default is 1000).
-            Set to `None` to remove this stopping criterion.
-        """
-        if iterations is not None:
-            iterations = int(iterations)
-            if iterations < 0:
-                raise ValueError("Maximum number of iterations cannot be negative.")
-        self._max_iterations = iterations

-
-
-

-[docs]
-    def set_max_unchanged_iterations(self, iterations=25, threshold=1e-5):
-        """
-        Set the maximum number of iterations without significant change as a stopping criterion.
-        Credit: PINTS
-
-        Parameters
-        ----------
-        iterations : int, optional
-            The maximum number of unchanged iterations to run (default is 25).
-            Set to `None` to remove this stopping criterion.
-        threshold : float, optional
-            The minimum significant change in the objective function value that resets the unchanged iteration counter (default is 1e-5).
-        """
-        if iterations is not None:
-            iterations = int(iterations)
-            if iterations < 0:
-                raise ValueError("Maximum number of iterations cannot be negative.")
-
-        threshold = float(threshold)
-        if threshold < 0:
-            raise ValueError("Minimum significant change cannot be negative.")
-
-        self._unchanged_max_iterations = iterations
-        self._unchanged_threshold = threshold

-
-
-

-[docs]
-    def store_optimised_parameters(self, x):
-        """
-        Update the problem parameters with optimized values.
-
-        The optimized parameter values are stored within the associated PyBOP parameter class.
-
-        Parameters
-        ----------
-        x : array-like
-            Optimized parameter values.
-        """
-        for i, param in enumerate(self.cost.problem.parameters):
-            param.update(value=x[i])

-

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- - - - -
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- - © Copyright 2023, The PyBOP Team. -
- -

-
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- -

- Created using Sphinx 7.2.6. -
-

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- Built with the PyData Sphinx Theme 0.14.4. -

- -
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- -
- - \ No newline at end of file diff --git a/_modules/pybop/optimisers/base_optimiser.html b/_modules/pybop/optimisers/base_optimiser.html deleted file mode 100644 index af752bb2c..000000000 --- a/_modules/pybop/optimisers/base_optimiser.html +++ /dev/null @@ -1,567 +0,0 @@ - - - - - - - - - - pybop.optimisers.base_optimiser — PyBOP Documentation - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
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Source code for pybop.optimisers.base_optimiser

-

-[docs]
-class BaseOptimiser:
-    """
-    A base class for defining optimisation methods.
-
-    This class serves as a template for creating optimisers. It provides a basic structure for
-    an optimisation algorithm, including the initial setup and a method stub for performing
-    the optimisation process. Child classes should override the optimise and _runoptimise
-    methods with specific algorithms.
-
-    Methods
-    -------
-    optimise(cost_function, x0=None, bounds=None, maxiter=None)
-        Initiates the optimisation process. This is a stub and should be implemented in child classes.
-    _runoptimise(cost_function, x0=None, bounds=None)
-        Contains the logic for the optimisation algorithm. This is a stub and should be implemented in child classes.
-    name()
-        Returns the name of the optimiser.
-    """
-
-    def __init__(self):
-        """
-        Initializes the BaseOptimiser.
-        """
-        pass
-
-

-[docs]
-    def optimise(self, cost_function, x0=None, bounds=None, maxiter=None):
-        """
-        Initiates the optimisation process.
-
-        This method should be overridden by child classes with the specific optimisation algorithm.
-
-        Parameters
-        ----------
-        cost_function : callable
-            The cost function to be minimised by the optimiser.
-        x0 : ndarray, optional
-            Initial guess for the parameters. Default is None.
-        bounds : sequence or Bounds, optional
-            Bounds on the parameters. Default is None.
-        maxiter : int, optional
-            Maximum number of iterations to perform. Default is None.
-
-        Returns
-        -------
-        The result of the optimisation process. The specific type of this result will depend on the child implementation.
-        """
-        self.cost_function = cost_function
-        self.x0 = x0
-        self.bounds = bounds
-        self.maxiter = maxiter
-
-        # Run optimisation
-        result = self._runoptimise(self.cost_function, x0=self.x0, bounds=self.bounds)
-
-        return result

-
-
-

-[docs]
-    def _runoptimise(self, cost_function, x0=None, bounds=None):
-        """
-        Contains the logic for the optimisation algorithm.
-
-        This method should be implemented by child classes to perform the actual optimisation.
-
-        Parameters
-        ----------
-        cost_function : callable
-            The cost function to be minimised by the optimiser.
-        x0 : ndarray, optional
-            Initial guess for the parameters. Default is None.
-        bounds : sequence or Bounds, optional
-            Bounds on the parameters. Default is None.
-
-        Returns
-        -------
-        This method is expected to return the result of the optimisation, the format of which
-        will be determined by the child class implementation.
-        """
-        pass

-
-
-

-[docs]
-    def name(self):
-        """
-        Returns the name of the optimiser.
-
-        Returns
-        -------
-        str
-            The name of the optimiser, which is "BaseOptimiser" for this base class.
-        """
-        return "BaseOptimiser"

-

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- - © Copyright 2023, The PyBOP Team. -
- -

-
- -
- -

- Created using Sphinx 7.2.6. -
-

-
- -
- - - -
- -
-

- Built with the PyData Sphinx Theme 0.14.4. -

- -
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- -
- - \ No newline at end of file diff --git a/_modules/pybop/optimisers/nlopt_optimize.html b/_modules/pybop/optimisers/nlopt_optimize.html deleted file mode 100644 index 2dfe4d56b..000000000 --- a/_modules/pybop/optimisers/nlopt_optimize.html +++ /dev/null @@ -1,592 +0,0 @@ - - - - - - - - - - pybop.optimisers.nlopt_optimize — PyBOP Documentation - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
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Source code for pybop.optimisers.nlopt_optimize

-import nlopt
-from .base_optimiser import BaseOptimiser
-import numpy as np
-
-
-

-[docs]
-class NLoptOptimize(BaseOptimiser):
-    """
-    Extends BaseOptimiser to utilize the NLopt library for nonlinear optimization.
-
-    This class serves as an interface to the NLopt optimization algorithms. It allows the user to
-    define an optimization problem with bounds, initial guesses, and to select an optimization method
-    provided by NLopt.
-
-    Parameters
-    ----------
-    n_param : int
-        Number of parameters to optimize.
-    xtol : float, optional
-        The relative tolerance for optimization (stopping criteria). If not provided, a default of 1e-5 is used.
-    method : nlopt.algorithm, optional
-        The NLopt algorithm to use for optimization. If not provided, LN_BOBYQA is used by default.
-    maxiter : int, optional
-        The maximum number of iterations to perform during optimization. If not provided, NLopt's default is used.
-
-    Methods
-    -------
-    _runoptimise(cost_function, x0, bounds)
-        Performs the optimization using the NLopt library.
-    needs_sensitivities()
-        Indicates whether the optimizer requires gradient information.
-    name()
-        Returns the name of the optimizer.
-    """
-
-    def __init__(self, n_param, xtol=None, method=None, maxiter=None):
-        super().__init__()
-        self.n_param = n_param
-        self.maxiter = maxiter
-
-        if method is not None:
-            self.optim = nlopt.opt(method, self.n_param)
-        else:
-            self.optim = nlopt.opt(nlopt.LN_BOBYQA, self.n_param)
-
-        if xtol is not None:
-            self.optim.set_xtol_rel(xtol)
-        else:
-            self.optim.set_xtol_rel(1e-5)
-
-

-[docs]
-    def _runoptimise(self, cost_function, x0, bounds):
-        """
-        Runs the optimization process using the NLopt library.
-
-        Parameters
-        ----------
-        cost_function : callable
-            The objective function to minimize. It should take an array of parameter values and return the scalar cost.
-        x0 : array_like
-            The initial guess for the parameters.
-        bounds : dict
-            A dictionary containing the 'lower' and 'upper' bounds arrays for the parameters.
-
-        Returns
-        -------
-        tuple
-            A tuple containing the optimized parameter values and the final cost.
-        """
-
-        # Add callback storing history of parameter values
-        self.log = [[x0]]
-
-        def cost_wrapper(x, grad):
-            self.log.append([np.array(x)])
-            return cost_function(x, grad)
-
-        # Pass settings to the optimiser
-        self.optim.set_min_objective(cost_wrapper)
-        self.optim.set_lower_bounds(bounds["lower"])
-        self.optim.set_upper_bounds(bounds["upper"])
-
-        # Set max iterations
-        if self.maxiter is not None:
-            self.optim.set_maxeval(self.maxiter)
-
-        # Run the optimser
-        x = self.optim.optimize(x0)
-
-        # Get performance statistics
-        final_cost = self.optim.last_optimum_value()
-
-        return x, final_cost

-
-
-

-[docs]
-    def needs_sensitivities(self):
-        """
-        Indicates if the optimizer requires gradient information for the cost function.
-
-        Returns
-        -------
-        bool
-            False, as the default NLopt algorithms do not require gradient information.
-        """
-        return False

-
-
-

-[docs]
-    def name(self):
-        """
-        Returns the name of this optimizer instance.
-
-        Returns
-        -------
-        str
-            The name 'NLoptOptimize' representing this NLopt optimization class.
-        """
-        return "NLoptOptimize"

-

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- - © Copyright 2023, The PyBOP Team. -
- -

-
- -
- -

- Created using Sphinx 7.2.6. -
-

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- -
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- Built with the PyData Sphinx Theme 0.14.4. -

- -
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- - \ No newline at end of file diff --git a/_modules/pybop/optimisers/pints_optimisers.html b/_modules/pybop/optimisers/pints_optimisers.html deleted file mode 100644 index 85a935888..000000000 --- a/_modules/pybop/optimisers/pints_optimisers.html +++ /dev/null @@ -1,708 +0,0 @@ - - - - - - - - - - pybop.optimisers.pints_optimisers — PyBOP Documentation - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
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Source code for pybop.optimisers.pints_optimisers

-import pints
-
-
-

-[docs]
-class GradientDescent(pints.GradientDescent):
-    """
-    Implements a simple gradient descent optimization algorithm.
-
-    This class extends the gradient descent optimizer from the PINTS library, designed
-    to minimize a scalar function of one or more variables. Note that this optimizer
-    does not support boundary constraints.
-
-    Parameters
-    ----------
-    x0 : array_like
-        Initial position from which optimization will start.
-    sigma0 : float, optional
-        Initial step size (default is 0.1).
-    bounds : sequence or ``Bounds``, optional
-        Ignored by this optimizer, provided for API consistency.
-
-    See Also
-    --------
-    pints.GradientDescent : The PINTS implementation this class is based on.
-    """
-
-    def __init__(self, x0, sigma0=0.1, bounds=None):
-        if bounds is not None:
-            print("NOTE: Boundaries ignored by Gradient Descent")
-
-        self.boundaries = None  # Bounds ignored in pints.GradDesc
-        super().__init__(x0, sigma0, self.boundaries)

-
-
-
-

-[docs]
-class Adam(pints.Adam):
-    """
-    Implements the Adam optimization algorithm.
-
-    This class extends the Adam optimizer from the PINTS library, which combines
-    ideas from RMSProp and Stochastic Gradient Descent with momentum. Note that
-    this optimizer does not support boundary constraints.
-
-    Parameters
-    ----------
-    x0 : array_like
-        Initial position from which optimization will start.
-    sigma0 : float, optional
-        Initial step size (default is 0.1).
-    bounds : sequence or ``Bounds``, optional
-        Ignored by this optimizer, provided for API consistency.
-
-    See Also
-    --------
-    pints.Adam : The PINTS implementation this class is based on.
-    """
-
-    def __init__(self, x0, sigma0=0.1, bounds=None):
-        if bounds is not None:
-            print("NOTE: Boundaries ignored by Adam")
-
-        self.boundaries = None  # Bounds ignored in pints.Adam
-        super().__init__(x0, sigma0, self.boundaries)

-
-
-
-

-[docs]
-class IRPropMin(pints.IRPropMin):
-    """
-    Implements the iRpropMin optimization algorithm.
-
-    This class inherits from the PINTS IRPropMin class, which is an optimizer that
-    uses resilient backpropagation with weight-backtracking. It is designed to handle
-    problems with large plateaus, noisy gradients, and local minima.
-
-    Parameters
-    ----------
-    x0 : array_like
-        Initial position from which optimization will start.
-    sigma0 : float, optional
-        Initial step size (default is 0.1).
-    bounds : dict, optional
-        Lower and upper bounds for each optimization parameter.
-
-    See Also
-    --------
-    pints.IRPropMin : The PINTS implementation this class is based on.
-    """
-
-    def __init__(self, x0, sigma0=0.1, bounds=None):
-        if bounds is not None:
-            self.boundaries = pints.RectangularBoundaries(
-                bounds["lower"], bounds["upper"]
-            )
-        else:
-            self.boundaries = None
-        super().__init__(x0, sigma0, self.boundaries)

-
-
-
-

-[docs]
-class PSO(pints.PSO):
-    """
-    Implements a particle swarm optimization (PSO) algorithm.
-
-    This class extends the PSO optimizer from the PINTS library. PSO is a
-    metaheuristic optimization method inspired by the social behavior of birds
-    flocking or fish schooling, suitable for global optimization problems.
-
-    Parameters
-    ----------
-    x0 : array_like
-        Initial positions of particles, which the optimization will use.
-    sigma0 : float, optional
-        Spread of the initial particle positions (default is 0.1).
-    bounds : dict, optional
-        Lower and upper bounds for each optimization parameter.
-
-    See Also
-    --------
-    pints.PSO : The PINTS implementation this class is based on.
-    """
-
-    def __init__(self, x0, sigma0=0.1, bounds=None):
-        if bounds is not None:
-            self.boundaries = pints.RectangularBoundaries(
-                bounds["lower"], bounds["upper"]
-            )
-        else:
-            self.boundaries = None
-        super().__init__(x0, sigma0, self.boundaries)

-
-
-
-

-[docs]
-class SNES(pints.SNES):
-    """
-    Implements the stochastic natural evolution strategy (SNES) optimization algorithm.
-
-    Inheriting from the PINTS SNES class, this optimizer is an evolutionary algorithm
-    that evolves a probability distribution on the parameter space, guiding the search
-    for the optimum based on the natural gradient of expected fitness.
-
-    Parameters
-    ----------
-    x0 : array_like
-        Initial position from which optimization will start.
-    sigma0 : float, optional
-        Initial step size (default is 0.1).
-    bounds : dict, optional
-        Lower and upper bounds for each optimization parameter.
-
-    See Also
-    --------
-    pints.SNES : The PINTS implementation this class is based on.
-    """
-
-    def __init__(self, x0, sigma0=0.1, bounds=None):
-        if bounds is not None:
-            self.boundaries = pints.RectangularBoundaries(
-                bounds["lower"], bounds["upper"]
-            )
-        else:
-            self.boundaries = None
-        super().__init__(x0, sigma0, self.boundaries)

-
-
-
-

-[docs]
-class XNES(pints.XNES):
-    """
-    Implements the Exponential Natural Evolution Strategy (XNES) optimizer from PINTS.
-
-    XNES is an evolutionary algorithm that samples from a multivariate normal distribution, which is updated iteratively to fit the distribution of successful solutions.
-
-    Parameters
-    ----------
-    x0 : array_like
-        The initial parameter vector to optimize.
-    sigma0 : float, optional
-        Initial standard deviation of the sampling distribution, defaults to 0.1.
-    bounds : dict, optional
-        A dictionary with 'lower' and 'upper' keys containing arrays for lower and upper bounds on the parameters. If ``None``, no bounds are enforced.
-
-    See Also
-    --------
-    pints.XNES : PINTS implementation of XNES algorithm.
-    """
-
-    def __init__(self, x0, sigma0=0.1, bounds=None):
-        if bounds is not None:
-            self.boundaries = pints.RectangularBoundaries(
-                bounds["lower"], bounds["upper"]
-            )
-        else:
-            self.boundaries = None
-        super().__init__(x0, sigma0, self.boundaries)

-
-
-
-

-[docs]
-class CMAES(pints.CMAES):
-    """
-    Adapter for the Covariance Matrix Adaptation Evolution Strategy (CMA-ES) optimizer in PINTS.
-
-    CMA-ES is an evolutionary algorithm for difficult non-linear non-convex optimization problems.
-    It adapts the covariance matrix of a multivariate normal distribution to capture the shape of the cost landscape.
-
-    Parameters
-    ----------
-    x0 : array_like
-        The initial parameter vector to optimize.
-    sigma0 : float, optional
-        Initial standard deviation of the sampling distribution, defaults to 0.1.
-    bounds : dict, optional
-        A dictionary with 'lower' and 'upper' keys containing arrays for lower and upper bounds on the parameters.
-        If ``None``, no bounds are enforced.
-
-    See Also
-    --------
-    pints.CMAES : PINTS implementation of CMA-ES algorithm.
-    """
-
-    def __init__(self, x0, sigma0=0.1, bounds=None):
-        if bounds is not None:
-            self.boundaries = pints.RectangularBoundaries(
-                bounds["lower"], bounds["upper"]
-            )
-        else:
-            self.boundaries = None
-
-        super().__init__(x0, sigma0, self.boundaries)

-
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- - - - -
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- - © Copyright 2023, The PyBOP Team. -
- -

-
- -
- -

- Created using Sphinx 7.2.6. -
-

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- Built with the PyData Sphinx Theme 0.14.4. -

- -
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- -
- - \ No newline at end of file diff --git a/_modules/pybop/optimisers/scipy_optimisers.html b/_modules/pybop/optimisers/scipy_optimisers.html deleted file mode 100644 index a8f1b5b2d..000000000 --- a/_modules/pybop/optimisers/scipy_optimisers.html +++ /dev/null @@ -1,693 +0,0 @@ - - - - - - - - - - pybop.optimisers.scipy_optimisers — PyBOP Documentation - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
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Source code for pybop.optimisers.scipy_optimisers

-from scipy.optimize import minimize, differential_evolution
-from .base_optimiser import BaseOptimiser
-
-
-

-[docs]
-class SciPyMinimize(BaseOptimiser):
-    """
-    Adapts SciPy's minimize function for use as an optimization strategy.
-
-    This class provides an interface to various scalar minimization algorithms implemented in SciPy, allowing fine-tuning of the optimization process through method selection and option configuration.
-
-    Parameters
-    ----------
-    method : str, optional
-        The type of solver to use. If not specified, defaults to 'COBYLA'.
-    bounds : sequence or ``Bounds``, optional
-        Bounds for variables as supported by the selected method.
-    maxiter : int, optional
-        Maximum number of iterations to perform.
-    """
-
-    def __init__(self, method=None, bounds=None, maxiter=None):
-        super().__init__()
-        self.method = method
-        self.bounds = bounds
-        self.maxiter = maxiter
-        if self.maxiter is not None:
-            self.options = {"maxiter": self.maxiter}
-        else:
-            self.options = {}
-
-        if self.method is None:
-            self.method = "COBYLA"  # "L-BFGS-B"
-
-

-[docs]
-    def _runoptimise(self, cost_function, x0, bounds):
-        """
-        Executes the optimization process using SciPy's minimize function.
-
-        Parameters
-        ----------
-        cost_function : callable
-            The objective function to minimize.
-        x0 : array_like
-            Initial guess for the parameters.
-        bounds : sequence or `Bounds`
-            Bounds for the variables.
-
-        Returns
-        -------
-        tuple
-            A tuple (x, final_cost) containing the optimized parameters and the value of `cost_function` at the optimum.
-        """
-
-        # Add callback storing history of parameter values
-        self.log = [[x0]]
-
-        def callback(x):
-            self.log.append([x])
-
-        # Reformat bounds
-        if bounds is not None:
-            bounds = (
-                (lower, upper) for lower, upper in zip(bounds["lower"], bounds["upper"])
-            )
-
-        output = minimize(
-            cost_function,
-            x0,
-            method=self.method,
-            bounds=bounds,
-            options=self.options,
-            callback=callback,
-        )
-
-        # Get performance statistics
-        x = output.x
-        final_cost = output.fun
-
-        return x, final_cost

-
-
-

-[docs]
-    def needs_sensitivities(self):
-        """
-        Determines if the optimization algorithm requires gradient information.
-
-        Returns
-        -------
-        bool
-            False, indicating that gradient information is not required.
-        """
-        return False

-
-
-

-[docs]
-    def name(self):
-        """
-        Provides the name of the optimization strategy.
-
-        Returns
-        -------
-        str
-            The name 'SciPyMinimize'.
-        """
-        return "SciPyMinimize"

-

-
-
-
-

-[docs]
-class SciPyDifferentialEvolution(BaseOptimiser):
-    """
-    Adapts SciPy's differential_evolution function for global optimization.
-
-    This class provides a global optimization strategy based on differential evolution, useful for problems involving continuous parameters and potentially multiple local minima.
-
-    Parameters
-    ----------
-    bounds : sequence or ``Bounds``
-        Bounds for variables. Must be provided as it is essential for differential evolution.
-    strategy : str, optional
-        The differential evolution strategy to use. Defaults to 'best1bin'.
-    maxiter : int, optional
-        Maximum number of iterations to perform. Defaults to 1000.
-    popsize : int, optional
-        The number of individuals in the population. Defaults to 15.
-    """
-
-    def __init__(self, bounds=None, strategy="best1bin", maxiter=1000, popsize=15):
-        super().__init__()
-        self.bounds = bounds
-        self.strategy = strategy
-        self.maxiter = maxiter
-        self.popsize = popsize
-
-

-[docs]
-    def _runoptimise(self, cost_function, x0=None, bounds=None):
-        """
-        Executes the optimization process using SciPy's differential_evolution function.
-
-        Parameters
-        ----------
-        cost_function : callable
-            The objective function to minimize.
-        x0 : array_like, optional
-            Ignored parameter, provided for API consistency.
-        bounds : sequence or ``Bounds``
-            Bounds for the variables, required for differential evolution.
-
-        Returns
-        -------
-        tuple
-            A tuple (x, final_cost) containing the optimized parameters and the value of ``cost_function`` at the optimum.
-        """
-
-        if bounds is None:
-            raise ValueError("Bounds must be specified for differential_evolution.")
-
-        if x0 is not None:
-            print(
-                "Ignoring x0. Initial conditions are not used for differential_evolution."
-            )
-
-        # Add callback storing history of parameter values
-        self.log = []
-
-        def callback(x, convergence):
-            self.log.append([x])
-
-        # Reformat bounds if necessary
-        if isinstance(bounds, dict):
-            bounds = [
-                (lower, upper) for lower, upper in zip(bounds["lower"], bounds["upper"])
-            ]
-
-        output = differential_evolution(
-            cost_function,
-            bounds,
-            strategy=self.strategy,
-            maxiter=self.maxiter,
-            popsize=self.popsize,
-            callback=callback,
-        )
-
-        # Get performance statistics
-        x = output.x
-        final_cost = output.fun
-
-        return x, final_cost

-
-
-

-[docs]
-    def needs_sensitivities(self):
-        """
-        Determines if the optimization algorithm requires gradient information.
-
-        Returns
-        -------
-        bool
-            False, indicating that gradient information is not required for differential evolution.
-        """
-        return False

-
-
-

-[docs]
-    def name(self):
-        """
-        Provides the name of the optimization strategy.
-
-        Returns
-        -------
-        str
-            The name 'SciPyDifferentialEvolution'.
-        """
-        return "SciPyDifferentialEvolution"

-

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- - © Copyright 2023, The PyBOP Team. -
- -

-
- -
- -

- Created using Sphinx 7.2.6. -
-

-
- -
- - - -
- -
-

- Built with the PyData Sphinx Theme 0.14.4. -

- -
- -
- -
- - \ No newline at end of file diff --git a/_modules/pybop/parameters/parameter.html b/_modules/pybop/parameters/parameter.html deleted file mode 100644 index 88e125ea1..000000000 --- a/_modules/pybop/parameters/parameter.html +++ /dev/null @@ -1,605 +0,0 @@ - - - - - - - - - - pybop.parameters.parameter — PyBOP Documentation - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
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Source code for pybop.parameters.parameter

-import numpy as np
-
-
-

-[docs]
-class Parameter:
-    """
-    Represents a parameter within the PyBOP framework.
-
-    This class encapsulates the definition of a parameter, including its name, prior
-    distribution, initial value, bounds, and a margin to ensure the parameter stays
-    within feasible limits during optimization or sampling.
-
-    Parameters
-    ----------
-    name : str
-        The name of the parameter.
-    initial_value : float, optional
-        The initial value to be assigned to the parameter. Defaults to None.
-    prior : scipy.stats distribution, optional
-        The prior distribution from which parameter values are drawn. Defaults to None.
-    bounds : tuple, optional
-        A tuple defining the lower and upper bounds for the parameter.
-        Defaults to None.
-
-    Methods
-    -------
-    rvs(n_samples)
-        Draw random samples from the parameter's prior distribution.
-    update(value)
-        Update the parameter's current value.
-    set_margin(margin)
-        Set the margin to a specified positive value less than 1.
-
-    Raises
-    ------
-    ValueError
-        If the lower bound is not strictly less than the upper bound, or if
-        the margin is set outside the interval (0, 1).
-    """
-
-    def __init__(self, name, initial_value=None, prior=None, bounds=None):
-        """
-        Construct the parameter class with a name, initial value, prior, and bounds.
-        """
-        self.name = name
-        self.prior = prior
-        self.initial_value = initial_value
-        self.value = initial_value
-        self.bounds = bounds
-        self.lower_bound = self.bounds[0]
-        self.upper_bound = self.bounds[1]
-        self.margin = 1e-4
-
-        if self.lower_bound >= self.upper_bound:
-            raise ValueError("Lower bound must be less than upper bound")
-
-

-[docs]
-    def rvs(self, n_samples):
-        """
-        Draw random samples from the parameter's prior distribution.
-
-        The samples are constrained to be within the parameter's bounds, excluding
-        a predefined margin at the boundaries.
-
-        Parameters
-        ----------
-        n_samples : int
-            The number of samples to draw.
-
-        Returns
-        -------
-        array-like
-            An array of samples drawn from the prior distribution within the parameter's bounds.
-        """
-        samples = self.prior.rvs(n_samples)
-
-        # Constrain samples to be within bounds
-        offset = self.margin * (self.upper_bound - self.lower_bound)
-        samples = np.clip(samples, self.lower_bound + offset, self.upper_bound - offset)
-
-        return samples

-
-
-

-[docs]
-    def update(self, value):
-        """
-        Update the parameter's current value.
-
-        Parameters
-        ----------
-        value : float
-            The new value to be assigned to the parameter.
-        """
-        self.value = value

-
-
-

-[docs]
-    def __repr__(self):
-        """
-        Return a string representation of the Parameter instance.
-
-        Returns
-        -------
-        str
-            A string including the parameter's name, prior, bounds, and current value.
-        """
-        return f"Parameter: {self.name} \n Prior: {self.prior} \n Bounds: {self.bounds} \n Value: {self.value}"

-
-
-

-[docs]
-    def set_margin(self, margin):
-        """
-        Set the margin to a specified positive value less than 1.
-
-        The margin is used to ensure parameter samples are not drawn exactly at the bounds,
-        which may be problematic in some optimization or sampling algorithms.
-
-        Parameters
-        ----------
-        margin : float
-            The new margin value to be used, which must be in the interval (0, 1).
-
-        Raises
-        ------
-        ValueError
-            If the margin is not between 0 and 1.
-        """
-        if not 0 < margin < 1:
-            raise ValueError("Margin must be between 0 and 1")
-
-        self.margin = margin

-

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- - - - - -
- - - - -
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- -
- -
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- -
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- - © Copyright 2023, The PyBOP Team. -
- -

-
- -
- -

- Created using Sphinx 7.2.6. -
-

-
- -
- - - -
- -
-

- Built with the PyData Sphinx Theme 0.14.4. -

- -
- -
- -
- - \ No newline at end of file diff --git a/_modules/pybop/parameters/parameter_set.html b/_modules/pybop/parameters/parameter_set.html deleted file mode 100644 index 2cc247b1c..000000000 --- a/_modules/pybop/parameters/parameter_set.html +++ /dev/null @@ -1,640 +0,0 @@ - - - - - - - - - - pybop.parameters.parameter_set — PyBOP Documentation - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
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Source code for pybop.parameters.parameter_set

-import json
-import types
-import pybamm
-import pybop
-
-
-

-[docs]
-class ParameterSet:
-    """
-    Handles the import and export of parameter sets for battery models.
-
-    This class provides methods to load parameters from a JSON file and to export them
-    back to a JSON file. It also includes custom logic to handle special cases, such
-    as parameter values that require specific initialization.
-
-    Parameters
-    ----------
-    json_path : str, optional
-        Path to a JSON file containing parameter data. If provided, parameters will be imported from this file during initialization.
-    params_dict : dict, optional
-        A dictionary of parameters to initialize the ParameterSet with. If not provided, an empty dictionary is used.
-    """
-
-    def __init__(self, json_path=None, params_dict=None):
-        self.json_path = json_path
-        self.params = params_dict or {}
-        self.chemistry = None
-
-

-[docs]
-    def import_parameters(self, json_path=None):
-        """
-        Imports parameters from a JSON file specified by the `json_path` attribute.
-
-        If a `json_path` is provided at initialization or as an argument, that JSON file
-        is loaded and the parameters are stored in the `params` attribute. Special cases
-        are handled appropriately.
-
-        Parameters
-        ----------
-        json_path : str, optional
-            Path to the JSON file from which to import parameters. If provided, it overrides the instance's `json_path`.
-
-        Returns
-        -------
-        dict
-            The dictionary containing the imported parameters.
-
-        Raises
-        ------
-        FileNotFoundError
-            If the specified JSON file cannot be found.
-        """
-
-        # Read JSON file
-        if not self.params and self.json_path:
-            with open(self.json_path, "r") as file:
-                self.params = json.load(file)
-                self._handle_special_cases()
-        if self.params["chemistry"] is not None:
-            self.chemistry = self.params["chemistry"]
-        return self.params

-
-
-

-[docs]
-    def _handle_special_cases(self):
-        """
-        Processes special cases for parameter values that require custom handling.
-
-        For example, if the open-circuit voltage is specified as 'default', it will
-        fetch the default value from the PyBaMM empirical Thevenin model.
-        """
-        if (
-            "Open-circuit voltage [V]" in self.params
-            and self.params["Open-circuit voltage [V]"] == "default"
-        ):
-            self.params[
-                "Open-circuit voltage [V]"
-            ] = pybop.empirical.Thevenin().default_parameter_values[
-                "Open-circuit voltage [V]"
-            ]

-
-
-

-[docs]
-    def export_parameters(self, output_json_path, fit_params=None):
-        """
-        Exports parameters to a JSON file specified by `output_json_path`.
-
-        The current state of the `params` attribute is written to the file. If `fit_params`
-        is provided, these parameters are updated before export. Non-serializable values
-        are handled and noted in the output JSON.
-
-        Parameters
-        ----------
-        output_json_path : str
-            The file path where the JSON output will be saved.
-        fit_params : list of fitted parameter objects, optional
-            Parameters that have been fitted and need to be included in the export.
-
-        Raises
-        ------
-        ValueError
-            If there are no parameters to export.
-        """
-        if not self.params:
-            raise ValueError("No parameters to export. Please import parameters first.")
-
-        # Prepare a copy of the params to avoid modifying the original dict
-        exportable_params = {**{"chemistry": self.chemistry}, **self.params.copy()}
-
-        # Update parameter set
-        if fit_params is not None:
-            for i, param in enumerate(fit_params):
-                exportable_params.update({param.name: param.value})
-
-        # Replace non-serializable values
-        for key, value in exportable_params.items():
-            if isinstance(value, types.FunctionType) or not self.is_json_serializable(
-                value
-            ):
-                exportable_params[key] = "Unable to write value to JSON file"
-
-        # Write parameters to JSON file
-        with open(output_json_path, "w") as file:
-            json.dump(exportable_params, file, indent=4)

-
-
-

-[docs]
-    def is_json_serializable(self, value):
-        """
-        Determines if the given `value` can be serialized to JSON format.
-
-        Parameters
-        ----------
-        value : any
-            The value to check for JSON serializability.
-
-        Returns
-        -------
-        bool
-            True if the value is JSON serializable, False otherwise.
-        """
-        try:
-            json.dumps(value)
-            return True
-        except (TypeError, OverflowError):
-            return False

-
-
-    @classmethod
-

-[docs]
-    def pybamm(cls, name):
-        """
-        Retrieves a PyBaMM parameter set by name.
-
-        Parameters
-        ----------
-        name : str
-            The name of the PyBaMM parameter set to retrieve.
-
-        Returns
-        -------
-        pybamm.ParameterValues
-            A PyBaMM parameter set corresponding to the provided name.
-        """
-        return pybamm.ParameterValues(name).copy()

-

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- - © Copyright 2023, The PyBOP Team. -
- -

-
- -
- -

- Created using Sphinx 7.2.6. -
-

-
- -
- - - -
- -
-

- Built with the PyData Sphinx Theme 0.14.4. -

- -
- -
- -
- - \ No newline at end of file diff --git a/_modules/pybop/parameters/priors.html b/_modules/pybop/parameters/priors.html deleted file mode 100644 index 3dffda073..000000000 --- a/_modules/pybop/parameters/priors.html +++ /dev/null @@ -1,761 +0,0 @@ - - - - - - - - - - pybop.parameters.priors — PyBOP Documentation - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
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Source code for pybop.parameters.priors

-import scipy.stats as stats
-
-
-

-[docs]
-class Gaussian:
-    """
-    Represents a Gaussian (normal) distribution with a given mean and standard deviation.
-
-    This class provides methods to calculate the probability density function (pdf),
-    the logarithm of the pdf, and to generate random variates (rvs) from the distribution.
-
-    Parameters
-    ----------
-    mean : float
-        The mean (mu) of the Gaussian distribution.
-    sigma : float
-        The standard deviation (sigma) of the Gaussian distribution.
-    """
-
-    def __init__(self, mean, sigma):
-        self.name = "Gaussian"
-        self.mean = mean
-        self.sigma = sigma
-
-

-[docs]
-    def pdf(self, x):
-        """
-        Calculates the probability density function of the Gaussian distribution at x.
-
-        Parameters
-        ----------
-        x : float
-            The point at which to evaluate the pdf.
-
-        Returns
-        -------
-        float
-            The probability density function value at x.
-        """
-        return stats.norm.pdf(x, loc=self.mean, scale=self.sigma)

-
-
-

-[docs]
-    def logpdf(self, x):
-        """
-        Calculates the logarithm of the probability density function of the Gaussian distribution at x.
-
-        Parameters
-        ----------
-        x : float
-            The point at which to evaluate the log pdf.
-
-        Returns
-        -------
-        float
-            The logarithm of the probability density function value at x.
-        """
-        return stats.norm.logpdf(x, loc=self.mean, scale=self.sigma)

-
-
-

-[docs]
-    def rvs(self, size):
-        """
-        Generates random variates from the Gaussian distribution.
-
-        Parameters
-        ----------
-        size : int
-            The number of random variates to generate.
-
-        Returns
-        -------
-        array_like
-            An array of random variates from the Gaussian distribution.
-
-        Raises
-        ------
-        ValueError
-            If the size parameter is not positive.
-        """
-        if size < 0:
-            raise ValueError("size must be positive")
-        else:
-            return stats.norm.rvs(loc=self.mean, scale=self.sigma, size=size)

-
-
-

-[docs]
-    def __repr__(self):
-        """
-        Returns a string representation of the Gaussian object.
-        """
-        return f"{self.name}, mean: {self.mean}, sigma: {self.sigma}"

-

-
-
-
-

-[docs]
-class Uniform:
-    """
-    Represents a uniform distribution over a specified interval.
-
-    This class provides methods to calculate the pdf, the log pdf, and to generate
-    random variates from the distribution.
-
-    Parameters
-    ----------
-    lower : float
-        The lower bound of the distribution.
-    upper : float
-        The upper bound of the distribution.
-    """
-
-    def __init__(self, lower, upper):
-        self.name = "Uniform"
-        self.lower = lower
-        self.upper = upper
-
-

-[docs]
-    def pdf(self, x):
-        """
-        Calculates the probability density function of the uniform distribution at x.
-
-        Parameters
-        ----------
-        x : float
-            The point at which to evaluate the pdf.
-
-        Returns
-        -------
-        float
-            The probability density function value at x.
-        """
-        return stats.uniform.pdf(x, loc=self.lower, scale=self.upper - self.lower)

-
-
-

-[docs]
-    def logpdf(self, x):
-        """
-        Calculates the logarithm of the pdf of the uniform distribution at x.
-
-        Parameters
-        ----------
-        x : float
-            The point at which to evaluate the log pdf.
-
-        Returns
-        -------
-        float
-            The log of the probability density function value at x.
-        """
-        return stats.uniform.logpdf(x, loc=self.lower, scale=self.upper - self.lower)

-
-
-

-[docs]
-    def rvs(self, size):
-        """
-        Generates random variates from the uniform distribution.
-
-        Parameters
-        ----------
-        size : int
-            The number of random variates to generate.
-
-        Returns
-        -------
-        array_like
-            An array of random variates from the uniform distribution.
-
-        Raises
-        ------
-        ValueError
-            If the size parameter is not positive.
-        """
-        if size < 0:
-            raise ValueError("size must be positive")
-        else:
-            return stats.uniform.rvs(
-                loc=self.lower, scale=self.upper - self.lower, size=size
-            )

-
-
-

-[docs]
-    def __repr__(self):
-        """
-        Returns a string representation of the Uniform object.
-        """
-        return f"{self.name}, lower: {self.lower}, upper: {self.upper}"

-

-
-
-
-

-[docs]
-class Exponential:
-    """
-    Represents an exponential distribution with a specified scale parameter.
-
-    This class provides methods to calculate the pdf, the log pdf, and to generate random
-    variates from the distribution.
-
-    Parameters
-    ----------
-    scale : float
-        The scale parameter (lambda) of the exponential distribution.
-    """
-
-    def __init__(self, scale):
-        self.name = "Exponential"
-        self.scale = scale
-
-

-[docs]
-    def pdf(self, x):
-        """
-        Calculates the probability density function of the exponential distribution at x.
-
-        Parameters
-        ----------
-        x : float
-            The point at which to evaluate the pdf.
-
-        Returns
-        -------
-        float
-            The probability density function value at x.
-        """
-        return stats.expon.pdf(x, scale=self.scale)

-
-
-

-[docs]
-    def logpdf(self, x):
-        """
-        Calculates the logarithm of the pdf of the exponential distribution at x.
-
-        Parameters
-        ----------
-        x : float
-            The point at which to evaluate the log pdf.
-
-        Returns
-        -------
-        float
-            The log of the probability density function value at x.
-        """
-        return stats.expon.logpdf(x, scale=self.scale)

-
-
-

-[docs]
-    def rvs(self, size):
-        """
-        Generates random variates from the exponential distribution.
-
-        Parameters
-        ----------
-        size : int
-            The number of random variates to generate.
-
-        Returns
-        -------
-        array_like
-            An array of random variates from the exponential distribution.
-
-        Raises
-        ------
-        ValueError
-            If the size parameter is not positive.
-        """
-        if size < 0:
-            raise ValueError("size must be positive")
-        else:
-            return stats.expon.rvs(scale=self.scale, size=size)

-
-
-

-[docs]
-    def __repr__(self):
-        """
-        Returns a string representation of the Uniform object.
-        """
-        return f"{self.name}, scale: {self.scale}"

-

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- - - - - -
- - - - -
-
- -
- -
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- -
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- - © Copyright 2023, The PyBOP Team. -
- -

-
- -
- -

- Created using Sphinx 7.2.6. -
-

-
- -
- - - -
- -
-

- Built with the PyData Sphinx Theme 0.14.4. -

- -
- -
- -
- - \ No newline at end of file diff --git a/_modules/pybop/plotting/plot_convergence.html b/_modules/pybop/plotting/plot_convergence.html deleted file mode 100644 index edb3fec02..000000000 --- a/_modules/pybop/plotting/plot_convergence.html +++ /dev/null @@ -1,523 +0,0 @@ - - - - - - - - - - pybop.plotting.plot_convergence — PyBOP Documentation - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
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Source code for pybop.plotting.plot_convergence

-import pybop
-
-
-

-[docs]
-def plot_convergence(
-    optim, xaxis_title="Iteration", yaxis_title="Cost", title="Convergence"
-):
-    """
-    Plot the convergence of the optimisation algorithm.
-
-    Parameters:
-    ----------
-    optim : optimisation object
-        Optimisation object containing the cost function and optimiser.
-    xaxis_title : str, optional
-        Title for the x-axis (default is "Iteration").
-    yaxis_title : str, optional
-        Title for the y-axis (default is "Cost").
-    title : str, optional
-        Title of the plot (default is "Convergence").
-
-    Returns:
-    ----------
-    fig : plotly.graph_objs.Figure
-        The Plotly figure object for the convergence plot.
-    """
-
-    # Extract the cost function from the optimisation object
-    cost_function = optim.cost
-
-    # Compute the minimum cost for each iteration
-    min_cost_per_iteration = [
-        min(cost_function(solution) for solution in log_entry)
-        for log_entry in optim.log
-    ]
-
-    # Generate a list of iteration numbers
-    iteration_numbers = list(range(1, len(min_cost_per_iteration) + 1))
-
-    # Create the convergence plot using the StandardPlot class
-    fig = pybop.StandardPlot(
-        x=iteration_numbers,
-        y=min_cost_per_iteration,
-        cost=cost_function,
-        xaxis_title=xaxis_title,
-        yaxis_title=yaxis_title,
-        title=title,
-        trace_name=optim.optimiser.name(),
-    )()
-
-    # Display the figure
-    fig.show()
-
-    return fig

-
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- - - - - -
- - - - -
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- - © Copyright 2023, The PyBOP Team. -
- -

-
- -
- -

- Created using Sphinx 7.2.6. -
-

-
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- - - -
- -
-

- Built with the PyData Sphinx Theme 0.14.4. -

- -
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- -
- - \ No newline at end of file diff --git a/_modules/pybop/plotting/plot_cost2d.html b/_modules/pybop/plotting/plot_cost2d.html deleted file mode 100644 index fce0025bb..000000000 --- a/_modules/pybop/plotting/plot_cost2d.html +++ /dev/null @@ -1,635 +0,0 @@ - - - - - - - - - - pybop.plotting.plot_cost2d — PyBOP Documentation - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
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Source code for pybop.plotting.plot_cost2d

-import numpy as np
-
-
-

-[docs]
-def plot_cost2d(cost, bounds=None, optim=None, steps=10):
-    """
-    Plot a 2D visualization of a cost landscape using Plotly.
-
-    This function generates a contour plot representing the cost landscape for a provided
-    callable cost function over a grid of parameter values within the specified bounds.
-
-    Parameters
-    ----------
-    cost : callable
-        The cost function to be evaluated. Must accept a list of parameters and return a cost value.
-    bounds : numpy.ndarray, optional
-        A 2x2 array specifying the [min, max] bounds for each parameter. If None, uses `get_param_bounds`.
-    optim : object, optional
-        An optimizer instance which, if provided, overlays its specific trace on the plot.
-    steps : int, optional
-        The number of intervals to divide the parameter space into along each dimension (default is 10).
-
-    Returns
-    -------
-    plotly.graph_objs.Figure
-        The Plotly figure object containing the cost landscape plot.
-
-    Raises
-    ------
-    ValueError
-        If the cost function does not return a valid cost when called with a parameter list.
-    """
-
-    if bounds is None:
-        # Set up parameter bounds
-        bounds = get_param_bounds(cost)
-    else:
-        bounds = bounds
-
-    # Generate grid
-    x = np.linspace(bounds[0, 0], bounds[0, 1], steps)
-    y = np.linspace(bounds[1, 0], bounds[1, 1], steps)
-
-    # Initialize cost matrix
-    costs = np.zeros((len(y), len(x)))
-
-    # Populate cost matrix
-    for i, xi in enumerate(x):
-        for j, yj in enumerate(y):
-            costs[j, i] = cost([xi, yj])
-
-    # Create figure
-    fig = create_figure(x, y, costs, bounds, cost.problem.parameters, optim)
-
-    # Display figure
-    fig.show()
-
-    return fig

-
-
-
-

-[docs]
-def get_param_bounds(cost):
-    """
-    Retrieve parameter bounds from a cost function's associated problem parameters.
-
-    Parameters
-    ----------
-    cost : callable
-        The cost function with an associated 'problem' attribute containing 'parameters'.
-
-    Returns
-    -------
-    numpy.ndarray
-        An array of shape (n_parameters, 2) containing the bounds for each parameter.
-    """
-    bounds = np.empty((len(cost.problem.parameters), 2))
-    for i, param in enumerate(cost.problem.parameters):
-        bounds[i] = param.bounds
-    return bounds

-
-
-
-

-[docs]
-def create_figure(x, y, z, bounds, params, optim):
-    """
-    Create a Plotly figure with a 2D contour plot of the cost landscape.
-
-    Parameters
-    ----------
-    x : numpy.ndarray
-        1D array of x-coordinates for the meshgrid.
-    y : numpy.ndarray
-        1D array of y-coordinates for the meshgrid.
-    z : numpy.ndarray
-        2D array of cost function values corresponding to the meshgrid.
-    bounds : numpy.ndarray
-        A 2x2 array specifying the [min, max] bounds for each parameter.
-    params : iterable
-        An iterable of parameter objects with 'name' attributes for axis labeling.
-    optim : object
-        An optimizer instance with 'log' and 'x0' attributes for plotting traces.
-
-    Returns
-    -------
-    plotly.graph_objs.Figure
-        The Plotly figure object with the contour plot and optimization traces.
-    """
-
-    # Import plotly only when needed
-    import plotly.graph_objects as go
-
-    fig = go.Figure(data=[go.Contour(x=x, y=y, z=z)])
-    if optim is not None:
-        optim_trace = np.array([item for sublist in optim.log for item in sublist])
-        optim_trace = optim_trace.reshape(-1, 2)
-
-        # Plot initial guess
-        fig.add_trace(
-            go.Scatter(
-                x=[optim.x0[0]],
-                y=[optim.x0[1]],
-                mode="markers",
-                marker_symbol="x",
-                marker=dict(
-                    color="red",
-                    line_color="midnightblue",
-                    line_width=1,
-                    size=12,
-                    showscale=False,
-                ),
-                showlegend=False,
-            )
-        )
-
-        # Plot optimisation trace
-        fig.add_trace(
-            go.Scatter(
-                x=optim_trace[:, 0],
-                y=optim_trace[:, 1],
-                mode="markers",
-                marker=dict(
-                    color=[i / len(optim_trace) for i in range(len(optim_trace))],
-                    colorscale="YlOrBr",
-                    showscale=False,
-                ),
-                showlegend=False,
-            )
-        )
-
-    # Set figure properties
-    fig.update_layout(
-        title="Cost Landscape",
-        title_x=0.5,
-        title_y=0.9,
-        xaxis_title=params[0].name,
-        yaxis_title=params[1].name,
-        width=600,
-        height=600,
-        xaxis=dict(range=bounds[0]),
-        yaxis=dict(range=bounds[1]),
-    )
-
-    return fig

-
-
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- - - - - -
- - - - -
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- -
- -
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- -
- -
- -

- - © Copyright 2023, The PyBOP Team. -
- -

-
- -
- -

- Created using Sphinx 7.2.6. -
-

-
- -
- - - -
- -
-

- Built with the PyData Sphinx Theme 0.14.4. -

- -
- -
- -
- - \ No newline at end of file diff --git a/_modules/pybop/plotting/plot_parameters.html b/_modules/pybop/plotting/plot_parameters.html deleted file mode 100644 index 59808270f..000000000 --- a/_modules/pybop/plotting/plot_parameters.html +++ /dev/null @@ -1,634 +0,0 @@ - - - - - - - - - - pybop.plotting.plot_parameters — PyBOP Documentation - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
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Source code for pybop.plotting.plot_parameters

-import pybop
-import math
-
-
-

-[docs]
-def plot_parameters(
-    optim, xaxis_titles="Iteration", yaxis_titles=None, title="Convergence"
-):
-    """
-    Plot the evolution of parameters during the optimization process using Plotly.
-
-    Parameters
-    ----------
-    optim : object
-        The optimization object containing the history of parameter values and associated cost.
-    xaxis_titles : str, optional
-        Title for the x-axis, defaulting to "Iteration".
-    yaxis_titles : list of str, optional
-        Titles for the y-axes, one for each parameter. If None, parameter names are used.
-    title : str, optional
-        Title of the plot, defaulting to "Convergence".
-
-    Returns
-    -------
-    plotly.graph_objs.Figure
-        A Plotly figure object showing the parameter evolution over iterations.
-    """
-
-    # Extract parameters from the optimisation object
-    params = optim.cost.problem.parameters
-
-    # Create the traces from the optimisation log
-    traces = create_traces(params, optim.log)
-
-    # Create the axis titles
-    axis_titles = []
-    for param in params:
-        axis_titles.append(("Function Call", param.name))
-
-    # Create the figure
-    fig = create_subplots_with_traces(traces, axis_titles=axis_titles)
-
-    # Display the figure
-    fig.show()
-
-    return fig

-
-
-
-

-[docs]
-def create_traces(params, trace_data, x_values=None):
-    """
-    Create traces for plotting parameter evolution.
-
-    Parameters
-    ----------
-    params : list
-        List of parameter objects, each having a 'name' attribute used for labeling the trace.
-    trace_data : list of numpy.ndarray
-        A list of arrays representing the historical values of each parameter.
-    x_values : list or numpy.ndarray, optional
-        The x-axis values for plotting. If None, defaults to sequential integers.
-
-    Returns
-    -------
-    list of plotly.graph_objs.Scatter
-        A list of Scatter trace objects, one for each parameter.
-    """
-
-    # Attempt to import plotly when an instance is created
-    go = pybop.PlotlyManager().go
-
-    traces = []
-
-    # If x_values are not provided:
-    if x_values is None:
-        x_values = list(range(len(trace_data[0]) * len(trace_data)))
-
-    # Determine the number of elements in the smallest arrays
-    num_elements = len(trace_data[0][0])
-
-    # Initialize a list of lists to store our columns
-    columns = [[] for _ in range(num_elements)]
-
-    # Loop through each numpy array in trace_data
-    for array in trace_data:
-        # Loop through each item (which is a n-element array) in the numpy array
-        for item in array:
-            # Loop through each element in the item and append to the corresponding column
-            for i in range(num_elements):
-                columns[i].append(item[i])
-
-    # Create a trace for each column
-    for i in range(len(columns)):
-        wrap_param = pybop.StandardPlot.wrap_text(params[i].name, width=50)
-        traces.append(go.Scatter(x=x_values, y=columns[i], name=wrap_param))
-
-    return traces

-
-
-
-

-[docs]
-def create_subplots_with_traces(
-    traces,
-    plot_size=(1024, 576),
-    title="Parameter Convergence",
-    axis_titles=None,
-    **layout_kwargs,
-):
-    """
-    Create a subplot with individual traces for each parameter.
-
-    Parameters
-    ----------
-    traces : list of plotly.graph_objs.Scatter
-        Traces to be plotted, one trace per subplot.
-    plot_size : tuple of int, optional
-        The size of the plot as (width, height), defaulting to (1024, 576).
-    title : str, optional
-        The title of the plot, defaulting to "Parameter Convergence".
-    axis_titles : list of tuple of str, optional
-        A list of (x_title, y_title) pairs for each subplot. If None, titles are omitted.
-    **layout_kwargs : dict
-        Additional keyword arguments to customize the layout.
-
-    Returns
-    -------
-    plotly.graph_objs.Figure
-        A Plotly figure object with subplots for each trace.
-    """
-
-    # Attempt to import plotly when an instance is created
-    make_subplots = pybop.PlotlyManager().make_subplots
-
-    num_traces = len(traces)
-    num_cols = int(math.ceil(math.sqrt(num_traces)))
-    num_rows = int(math.ceil(num_traces / num_cols))
-
-    fig = make_subplots(rows=num_rows, cols=num_cols, start_cell="bottom-left")
-
-    for idx, trace in enumerate(traces):
-        row = (idx // num_cols) + 1
-        col = (idx % num_cols) + 1
-        fig.add_trace(trace, row=row, col=col)
-
-        if axis_titles and idx < len(axis_titles):
-            x_title, y_title = axis_titles[idx]
-            fig.update_xaxes(title_text=x_title, row=row, col=col)
-            fig.update_yaxes(title_text=y_title, row=row, col=col)
-
-    if plot_size:
-        layout_kwargs["width"], layout_kwargs["height"] = plot_size
-
-    if title:
-        layout_kwargs["title_text"] = title
-
-    # Set the legend above the subplots
-    fig.update_layout(
-        legend=dict(orientation="h", yanchor="bottom", y=1.02, xanchor="right", x=1),
-        **layout_kwargs,
-    )
-
-    return fig

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- -
- -
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- - - - - -
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- -
- -
- -

- - © Copyright 2023, The PyBOP Team. -
- -

-
- -
- -

- Created using Sphinx 7.2.6. -
-

-
- -
- - - -
- -
-

- Built with the PyData Sphinx Theme 0.14.4. -

- -
- -
- -
- - \ No newline at end of file diff --git a/_modules/pybop/plotting/plotly_manager.html b/_modules/pybop/plotting/plotly_manager.html deleted file mode 100644 index 73f751b2e..000000000 --- a/_modules/pybop/plotting/plotly_manager.html +++ /dev/null @@ -1,633 +0,0 @@ - - - - - - - - - - pybop.plotting.plotly_manager — PyBOP Documentation - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
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Source code for pybop.plotting.plotly_manager

-import subprocess
-import webbrowser
-import sys
-
-
-

-[docs]
-class PlotlyManager:
-    """
-    Manages the installation and configuration of Plotly for generating visualizations.
-
-    This class ensures that Plotly is installed and properly configured to display
-    plots in a web browser.
-
-    Upon instantiation, it checks for Plotly's presence, installs it if missing,
-    and configures the default renderer and browser settings.
-
-    Attributes
-    ----------
-    go : module
-        The Plotly graph_objects module for creating figures.
-    pio : module
-        The Plotly input/output module for configuring the renderer.
-    make_subplots : function
-        The function from Plotly for creating subplot figures.
-
-    Methods
-    -------
-    ensure_plotly_installed()
-        Verifies if Plotly is installed, importing necessary modules and prompting for installation if missing.
-    prompt_for_plotly_installation()
-        Prompts the user for permission to install Plotly and proceeds with installation if consented.
-    install_plotly()
-        Installs the Plotly package using pip.
-    post_install_setup()
-        Sets up Plotly default renderer after installation.
-    check_renderer_settings()
-        Verifies that the Plotly renderer is correctly set.
-    check_browser_availability()
-        Checks if a web browser is available for rendering plots.
-
-    Examples
-    --------
-    >>> plotly_manager = PlotlyManager()
-    """
-
-    def __init__(self):
-        """
-        Initialize the PlotlyManager, ensuring Plotly is installed and configured.
-        """
-        self.go = None
-        self.pio = None
-        self.make_subplots = None
-        self.ensure_plotly_installed()
-        self.check_renderer_settings()
-        self.check_browser_availability()
-
-

-[docs]
-    def ensure_plotly_installed(self):
-        """
-        Check if Plotly is installed and import necessary modules; prompt for installation if missing.
-        """
-        try:
-            import plotly.graph_objs as go
-            import plotly.io as pio
-            from plotly.subplots import make_subplots
-
-            self.go = go
-            self.pio = pio
-            self.make_subplots = make_subplots
-        except ImportError:
-            self.prompt_for_plotly_installation()

-
-
-

-[docs]
-    def prompt_for_plotly_installation(self):
-        """
-        Prompt the user for Plotly installation and install it upon agreement.
-        """
-        user_input = (
-            input(
-                "Plotly is not installed. To proceed, we need to install plotly. (Y/n)? "
-            )
-            .strip()
-            .lower()
-        )
-        if user_input == "y":
-            self.install_plotly()
-            self.post_install_setup()
-        else:
-            print("Installation cancelled by user.")
-            sys.exit(1)  # Exit if user cancels installation

-
-
-

-[docs]
-    def install_plotly(self):
-        """
-        Install the Plotly package using pip. Exit if installation fails.
-        """
-        try:
-            subprocess.check_call([sys.executable, "-m", "pip", "install", "plotly"])
-        except subprocess.CalledProcessError as e:
-            print(f"Error installing plotly: {e}")
-            sys.exit(1)  # Exit if installation fails

-
-
-

-[docs]
-    def post_install_setup(self):
-        """
-        Import Plotly modules and set the default renderer after installation.
-        """
-        import plotly.graph_objs as go
-        import plotly.io as pio
-        from plotly.subplots import make_subplots
-
-        self.go = go
-        self.pio = pio
-        self.make_subplots = make_subplots
-        if pio.renderers.default == "":
-            pio.renderers.default = "browser"
-            print(
-                'Set default renderer to "browser" as it was empty after installation.'
-            )

-
-
-

-[docs]
-    def check_renderer_settings(self):
-        """
-        Check and provide information on setting the Plotly renderer if it's not already set.
-        """
-        if self.pio and self.pio.renderers.default == "":
-            print(
-                "The Plotly renderer is an empty string. To set the renderer, use:\n"
-                "    pio.renderers\n"
-                '    pio.renderers.default = "browser"\n'
-                "For more information, see: https://plotly.com/python/renderers/#setting-the-default-renderer"
-            )

-
-
-

-[docs]
-    def check_browser_availability(self):
-        """
-        Confirm a web browser is available for Plotly's 'browser' renderer; provide guidance if not.
-        """
-        if self.pio and self.pio.renderers.default == "browser":
-            try:
-                webbrowser.get()
-            except webbrowser.Error:
-                raise Exception(
-                    "\n **Browser Not Found** \nFor Windows users, in order to view figures in the browser using Plotly, "
-                    "you need to set the environment variable BROWSER equal to the "
-                    "path to your chosen browser. To do this, please enter a command like "
-                    "the following to add this to your virtual environment activation file:\n\n"
-                    "echo 'export BROWSER=\"/mnt/c/Program Files/Mozilla Firefox/firefox.exe\"' >> your-env/bin/activate"
-                    "\n\nThen reactivate your virtual environment. Alternatively, you can use a "
-                    "different Plotly renderer. For more information see: "
-                    "https://plotly.com/python/renderers/#setting-the-default-renderer"
-                )

-

-
-
- -
- - - - - -
- - - - -
-
- -
- -
-
-
- - - - - -
-
- -
- -
- -

- - © Copyright 2023, The PyBOP Team. -
- -

-
- -
- -

- Created using Sphinx 7.2.6. -
-

-
- -
- - - -
- -
-

- Built with the PyData Sphinx Theme 0.14.4. -

- -
- -
- -
- - \ No newline at end of file diff --git a/_modules/pybop/plotting/quick_plot.html b/_modules/pybop/plotting/quick_plot.html deleted file mode 100644 index c7127b027..000000000 --- a/_modules/pybop/plotting/quick_plot.html +++ /dev/null @@ -1,720 +0,0 @@ - - - - - - - - - - pybop.plotting.quick_plot — PyBOP Documentation - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
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Source code for pybop.plotting.quick_plot

-import numpy as np
-import textwrap
-import pybop
-
-
-

-[docs]
-class StandardPlot:
-    """
-    A class for creating and displaying Plotly figures for model output comparison.
-
-    Generates interactive plots comparing simulated model output with an optional target dataset and visualizes uncertainty.
-
-    Parameters
-    ----------
-    x : list or np.ndarray
-        X-axis data points.
-    y : list or np.ndarray
-        Primary Y-axis data points for simulated model output.
-    cost : float
-        Cost associated with the model output.
-    y2 : list or np.ndarray, optional
-        Secondary Y-axis data points for the target dataset (default: None).
-    title : str, optional
-        Title of the plot (default: None).
-    xaxis_title : str, optional
-        Title for the x-axis (default: None).
-    yaxis_title : str, optional
-        Title for the y-axis (default: None).
-    trace_name : str, optional
-        Name for the primary trace (default: "Simulated").
-    width : int, optional
-        Width of the figure in pixels (default: 1024).
-    height : int, optional
-        Height of the figure in pixels (default: 576).
-    """
-
-    def __init__(
-        self,
-        x,
-        y,
-        cost,
-        y2=None,
-        title=None,
-        xaxis_title=None,
-        yaxis_title=None,
-        trace_name=None,
-        width=1024,
-        height=576,
-    ):
-        """
-        Initialize the StandardPlot object with simulation and optional target data.
-
-        Parameters
-        ----------
-        x : list or np.ndarray
-            X-axis data points.
-        y : list or np.ndarray
-            Primary Y-axis data points for simulated model output.
-        cost : float
-            Cost associated with the model output.
-        y2 : list or np.ndarray, optional
-            Secondary Y-axis data points for target dataset (default: None).
-        title : str, optional
-            Plot title (default: None).
-        xaxis_title : str, optional
-            X-axis title (default: None).
-        yaxis_title : str, optional
-            Y-axis title (default: None).
-        trace_name : str, optional
-            Name for the primary trace (default: "Simulated").
-        width : int, optional
-            Figure width in pixels (default: 1024).
-        height : int, optional
-            Figure height in pixels (default: 576).
-        """
-        self.x = x if isinstance(x, list) else x.tolist()
-        self.y = y
-        self.y2 = y2
-        self.cost = cost
-        self.width = width
-        self.height = height
-        self.title = title
-        self.xaxis_title = xaxis_title
-        self.yaxis_title = yaxis_title
-        self.trace_name = trace_name or "Simulated"
-
-        if self.y2 is not None:
-            self.sigma = np.std(self.y - self.y2)
-            self.y_upper = (self.y + self.sigma).tolist()
-            self.y_lower = (self.y - self.sigma).tolist()
-
-        # Attempt to import plotly when an instance is created
-        self.go = pybop.PlotlyManager().go
-
-    @staticmethod
-

-[docs]
-    def wrap_text(text, width):
-        """
-        Wrap text to a specified width with HTML line breaks.
-
-        Parameters
-        ----------
-        text : str
-            The text to wrap.
-        width : int
-            The width to wrap the text to.
-
-        Returns
-        -------
-        str
-            The wrapped text.
-        """
-        wrapped_text = textwrap.fill(text, width=width, break_long_words=False)
-        return wrapped_text.replace("\n", "<br>")

-
-
-

-[docs]
-    def create_layout(self):
-        """
-        Create the layout for the Plotly figure.
-
-        Returns
-        -------
-        plotly.graph_objs.Layout
-            The layout for the Plotly figure.
-        """
-        return self.go.Layout(
-            title=self.title,
-            title_x=0.5,
-            xaxis=dict(title=self.xaxis_title, titlefont_size=12, tickfont_size=12),
-            yaxis=dict(title=self.yaxis_title, titlefont_size=12, tickfont_size=12),
-            legend=dict(x=1, y=1, xanchor="right", yanchor="top", font_size=12),
-            showlegend=True,
-            autosize=False,
-            width=self.width,
-            height=self.height,
-            margin=dict(l=10, r=10, b=10, t=75, pad=4),
-        )

-
-
-

-[docs]
-    def create_traces(self):
-        """
-        Create traces for the Plotly figure.
-
-        Returns
-        -------
-        list
-            A list of plotly.graph_objs.Scatter objects to be used as traces.
-        """
-        traces = []
-
-        wrapped_trace_name = self.wrap_text(self.trace_name, width=40)
-        simulated_trace = self.go.Scatter(
-            x=self.x,
-            y=self.y,
-            line=dict(width=4),
-            mode="lines",
-            name=wrapped_trace_name,
-        )
-
-        if self.y2 is not None:
-            target_trace = self.go.Scatter(
-                x=self.x, y=self.y2, mode="markers", name="Target"
-            )
-            fill_trace = self.go.Scatter(
-                x=self.x + self.x[::-1],
-                y=self.y_upper + self.y_lower[::-1],
-                fill="toself",
-                fillcolor="rgba(255,229,204,0.8)",
-                line=dict(color="rgba(255,255,255,0)"),
-                hoverinfo="skip",
-                showlegend=False,
-            )
-            traces.extend([fill_trace, target_trace])
-
-        traces.append(simulated_trace)
-
-        return traces

-
-
-

-[docs]
-    def __call__(self):
-        """
-        Generate the Plotly figure.
-
-        Returns
-        -------
-        plotly.graph_objs.Figure
-            The generated Plotly figure.
-        """
-        layout = self.create_layout()
-        traces = self.create_traces()
-        fig = self.go.Figure(data=traces, layout=layout)
-        return fig

-

-
-
-
-

-[docs]
-def quick_plot(params, cost, title="Scatter Plot", width=1024, height=576):
-    """
-    Quickly plot the target dataset against minimized model output.
-
-    Parameters
-    ----------
-    params : array-like
-        Optimized parameters.
-    cost : object
-        Cost object with problem, dataset, and signal attributes.
-    title : str, optional
-        Title of the plot (default: "Scatter Plot").
-    width : int, optional
-        Width of the figure in pixels (default: 1024).
-    height : int, optional
-        Height of the figure in pixels (default: 576).
-
-    Returns
-    -------
-    plotly.graph_objs.Figure
-        The Plotly figure object for the scatter plot.
-    """
-
-    # Extract the time data and evaluate the model's output and target values
-    time_data = cost.problem._dataset["Time [s]"].data
-    model_output = cost.problem.evaluate(params)
-    target_output = cost.problem.target()
-
-    # Create the figure using the StandardPlot class
-    fig = pybop.StandardPlot(
-        x=time_data,
-        y=model_output,
-        cost=cost,
-        y2=target_output,
-        xaxis_title="Time [s]",
-        yaxis_title=cost.problem.signal,
-        title=title,
-        trace_name="Model",
-        width=width,
-        height=height,
-    )()
-
-    # Display the figure
-    fig.show()
-
-    return fig

-
-
- -
- - - - - -
- - - - -
-
- -
- -
-
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- - - - - -
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- -
- -
- -

- - © Copyright 2023, The PyBOP Team. -
- -

-
- -
- -

- Created using Sphinx 7.2.6. -
-

-
- -
- - - -
- -
-

- Built with the PyData Sphinx Theme 0.14.4. -

- -
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- -
- - \ No newline at end of file diff --git a/_modules/pybop/version.html b/_modules/pybop/version.html deleted file mode 100644 index fd0ab4fa5..000000000 --- a/_modules/pybop/version.html +++ /dev/null @@ -1,471 +0,0 @@ - - - - - - - - - - pybop.version — PyBOP Documentation - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
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Source code for pybop.version

-

-[docs]
-__version__ = "23.11"

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- - - - - -
- - - - -
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- -
- -
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- -
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- - © Copyright 2023, The PyBOP Team. -
- -

-
- -
- -

- Created using Sphinx 7.2.6. -
-

-
- -
- - - -
- -
-

- Built with the PyData Sphinx Theme 0.14.4. -

- -
- -
- -
- - \ No newline at end of file diff --git a/_sources/api/index.rst.txt b/_sources/api/index.rst.txt deleted file mode 100644 index 870df405e..000000000 --- a/_sources/api/index.rst.txt +++ /dev/null @@ -1,12 +0,0 @@ -API Reference -============= - -This page contains auto-generated API reference documentation [#f1]_. - -.. toctree:: - :titlesonly: - :maxdepth: 2 - - /api/pybop/index - -.. [#f1] Created with `sphinx-autoapi `_ \ No newline at end of file diff --git a/_sources/api/pybop/_costs/index.rst.txt b/_sources/api/pybop/_costs/index.rst.txt deleted file mode 100644 index 2c0c469ea..000000000 --- a/_sources/api/pybop/_costs/index.rst.txt +++ /dev/null @@ -1,156 +0,0 @@ -:py:mod:`pybop._costs` -====================== - -.. py:module:: pybop._costs - - -Module Contents ---------------- - -Classes -~~~~~~~ - -.. autoapisummary:: - - pybop._costs.BaseCost - pybop._costs.RootMeanSquaredError - pybop._costs.SumSquaredError - - - - -.. py:class:: BaseCost(problem) - - - Base class for defining cost functions. - - This class is intended to be subclassed to create specific cost functions - for evaluating model predictions against a set of data. The cost function - quantifies the goodness-of-fit between the model predictions and the - observed data, with a lower cost value indicating a better fit. - - :param problem: A problem instance containing the data and functions necessary for - evaluating the cost function. - :type problem: object - :param _target: An array containing the target data to fit. - :type _target: array-like - :param x0: The initial guess for the model parameters. - :type x0: array-like - :param bounds: The bounds for the model parameters. - :type bounds: tuple - :param n_parameters: The number of parameters in the model. - :type n_parameters: int - - .. py:method:: __call__(x, grad=None) - :abstractmethod: - - Calculate the cost function value for a given set of parameters. - - This method must be implemented by subclasses. - - :param x: The parameters for which to evaluate the cost. - :type x: array-like - :param grad: An array to store the gradient of the cost function with respect - to the parameters. - :type grad: array-like, optional - - :returns: The calculated cost function value. - :rtype: float - - :raises NotImplementedError: If the method has not been implemented by the subclass. - - - -.. py:class:: RootMeanSquaredError(problem) - - - Bases: :py:obj:`BaseCost` - - Root mean square error cost function. - - Computes the root mean square error between model predictions and the target - data, providing a measure of the differences between predicted values and - observed values. - - Inherits all parameters and attributes from ``BaseCost``. - - - .. py:method:: __call__(x, grad=None) - - Calculate the root mean square error for a given set of parameters. - - :param x: The parameters for which to evaluate the cost. - :type x: array-like - :param grad: An array to store the gradient of the cost function with respect - to the parameters. - :type grad: array-like, optional - - :returns: The root mean square error. - :rtype: float - - :raises ValueError: If an error occurs during the calculation of the cost. - - - -.. py:class:: SumSquaredError(problem) - - - Bases: :py:obj:`BaseCost` - - Sum of squared errors cost function. - - Computes the sum of the squares of the differences between model predictions - and target data, which serves as a measure of the total error between the - predicted and observed values. - - Inherits all parameters and attributes from ``BaseCost``. - - Additional Attributes - --------------------- - _de : float - The gradient of the cost function to use if an error occurs during - evaluation. Defaults to 1.0. - - - .. py:method:: __call__(x, grad=None) - - Calculate the sum of squared errors for a given set of parameters. - - :param x: The parameters for which to evaluate the cost. - :type x: array-like - :param grad: An array to store the gradient of the cost function with respect - to the parameters. - :type grad: array-like, optional - - :returns: The sum of squared errors. - :rtype: float - - :raises ValueError: If an error occurs during the calculation of the cost. - - - .. py:method:: evaluateS1(x) - - Compute the cost and its gradient with respect to the parameters. - - :param x: The parameters for which to compute the cost and gradient. - :type x: array-like - - :returns: A tuple containing the cost and the gradient. The cost is a float, - and the gradient is an array-like of the same length as `x`. - :rtype: tuple - - :raises ValueError: If an error occurs during the calculation of the cost or gradient. - - - .. py:method:: set_fail_gradient(de) - - Set the fail gradient to a specified value. - - The fail gradient is used if an error occurs during the calculation - of the gradient. This method allows updating the default gradient value. - - :param de: The new fail gradient value to be used. - :type de: float - - - diff --git a/_sources/api/pybop/_dataset/index.rst.txt b/_sources/api/pybop/_dataset/index.rst.txt deleted file mode 100644 index b59e8624f..000000000 --- a/_sources/api/pybop/_dataset/index.rst.txt +++ /dev/null @@ -1,53 +0,0 @@ -:py:mod:`pybop._dataset` -======================== - -.. py:module:: pybop._dataset - - -Module Contents ---------------- - -Classes -~~~~~~~ - -.. autoapisummary:: - - pybop._dataset.Dataset - - - - -.. py:class:: Dataset(name, data) - - - Represents a collection of experimental observations. - - This class provides a structured way to store and work with experimental data, - which may include applying operations such as interpolation. - - :param name: The name of the dataset, providing a label for identification. - :type name: str - :param data: The actual experimental data, typically in a structured form such as - a NumPy array or a pandas DataFrame. - :type data: array-like - - .. py:method:: Interpolant() - - Create an interpolation function of the dataset based on the independent variable. - - Currently, only time-based interpolation is supported. This method modifies - the instance's Interpolant attribute to be an interpolation function that - can be evaluated at different points in time. - - :raises NotImplementedError: If the independent variable for interpolation is not supported. - - - .. py:method:: __repr__() - - Return a string representation of the Dataset instance. - - :returns: A string that includes the name and data of the dataset. - :rtype: str - - - diff --git a/_sources/api/pybop/_problem/index.rst.txt b/_sources/api/pybop/_problem/index.rst.txt deleted file mode 100644 index c36de4d61..000000000 --- a/_sources/api/pybop/_problem/index.rst.txt +++ /dev/null @@ -1,143 +0,0 @@ -:py:mod:`pybop._problem` -======================== - -.. py:module:: pybop._problem - - -Module Contents ---------------- - -Classes -~~~~~~~ - -.. autoapisummary:: - - pybop._problem.BaseProblem - pybop._problem.DesignProblem - pybop._problem.FittingProblem - - - - -.. py:class:: BaseProblem(parameters, model=None, check_model=True, init_soc=None, x0=None) - - - Base class for defining a problem within the PyBOP framework, compatible with PINTS. - - :param parameters: List of parameters for the problem. - :type parameters: list - :param model: The model to be used for the problem (default: None). - :type model: object, optional - :param check_model: Flag to indicate if the model should be checked (default: True). - :type check_model: bool, optional - :param init_soc: Initial state of charge (default: None). - :type init_soc: float, optional - :param x0: Initial parameter values (default: None). - :type x0: np.ndarray, optional - - .. py:method:: evaluate(x) - :abstractmethod: - - Evaluate the model with the given parameters and return the signal. - - :param x: Parameter values to evaluate the model at. - :type x: np.ndarray - - :raises NotImplementedError: This method must be implemented by subclasses. - - - .. py:method:: evaluateS1(x) - :abstractmethod: - - Evaluate the model with the given parameters and return the signal and its derivatives. - - :param x: Parameter values to evaluate the model at. - :type x: np.ndarray - - :raises NotImplementedError: This method must be implemented by subclasses. - - - -.. py:class:: DesignProblem(model, parameters, experiment, check_model=True, init_soc=None, x0=None) - - - Bases: :py:obj:`BaseProblem` - - Problem class for design optimization problems. - - Extends `BaseProblem` with specifics for applying a model to an experimental design. - - :param model: The model to apply the design to. - :type model: object - :param parameters: List of parameters for the problem. - :type parameters: list - :param experiment: The experimental setup to apply the model to. - :type experiment: object - - .. py:method:: evaluate(x) - - Evaluate the model with the given parameters and return the signal. - - :param x: Parameter values to evaluate the model at. - :type x: np.ndarray - - - .. py:method:: evaluateS1(x) - - Evaluate the model with the given parameters and return the signal and its derivatives. - - :param x: Parameter values to evaluate the model at. - :type x: np.ndarray - - - .. py:method:: target() - - Return the target dataset (not applicable for design problems). - - :rtype: None - - - -.. py:class:: FittingProblem(model, parameters, dataset, signal='Voltage [V]', check_model=True, init_soc=None, x0=None) - - - Bases: :py:obj:`BaseProblem` - - Problem class for fitting (parameter estimation) problems. - - Extends `BaseProblem` with specifics for fitting a model to a dataset. - - :param model: The model to fit. - :type model: object - :param parameters: List of parameters for the problem. - :type parameters: list - :param dataset: List of data objects to fit the model to. - :type dataset: list - :param signal: The signal to fit (default: "Voltage [V]"). - :type signal: str, optional - - .. py:method:: evaluate(x) - - Evaluate the model with the given parameters and return the signal. - - :param x: Parameter values to evaluate the model at. - :type x: np.ndarray - - - .. py:method:: evaluateS1(x) - - Evaluate the model with the given parameters and return the signal and its derivatives. - - :param x: Parameter values to evaluate the model at. - :type x: np.ndarray - - - .. py:method:: target() - - Return the target dataset. - - :returns: The target dataset array. - :rtype: np.ndarray - - - diff --git a/_sources/api/pybop/index.rst.txt b/_sources/api/pybop/index.rst.txt deleted file mode 100644 index 7df4544a3..000000000 --- a/_sources/api/pybop/index.rst.txt +++ /dev/null @@ -1,1607 +0,0 @@ -:py:mod:`pybop` -=============== - -.. py:module:: pybop - - -Subpackages ------------ -.. toctree:: - :titlesonly: - :maxdepth: 3 - - models/index.rst - optimisers/index.rst - parameters/index.rst - plotting/index.rst - - -Submodules ----------- -.. toctree:: - :titlesonly: - :maxdepth: 1 - - _costs/index.rst - _dataset/index.rst - _problem/index.rst - optimisation/index.rst - version/index.rst - - -Package Contents ----------------- - -Classes -~~~~~~~ - -.. autoapisummary:: - - pybop.Adam - pybop.BaseCost - pybop.BaseModel - pybop.BaseOptimiser - pybop.CMAES - pybop.Dataset - pybop.DesignProblem - pybop.Exponential - pybop.FittingProblem - pybop.Gaussian - pybop.GradientDescent - pybop.IRPropMin - pybop.NLoptOptimize - pybop.Optimisation - pybop.PSO - pybop.Parameter - pybop.ParameterSet - pybop.PlotlyManager - pybop.RootMeanSquaredError - pybop.SNES - pybop.SciPyDifferentialEvolution - pybop.SciPyMinimize - pybop.StandardPlot - pybop.SumSquaredError - pybop.Uniform - pybop.XNES - - - -Functions -~~~~~~~~~ - -.. autoapisummary:: - - pybop.plot_convergence - pybop.plot_cost2d - pybop.plot_parameters - pybop.quick_plot - - - -Attributes -~~~~~~~~~~ - -.. autoapisummary:: - - pybop.FLOAT_FORMAT - pybop.__version__ - pybop.script_path - - -.. py:class:: Adam(x0, sigma0=0.1, bounds=None) - - - Bases: :py:obj:`pints.Adam` - - Implements the Adam optimization algorithm. - - This class extends the Adam optimizer from the PINTS library, which combines - ideas from RMSProp and Stochastic Gradient Descent with momentum. Note that - this optimizer does not support boundary constraints. - - :param x0: Initial position from which optimization will start. - :type x0: array_like - :param sigma0: Initial step size (default is 0.1). - :type sigma0: float, optional - :param bounds: Ignored by this optimizer, provided for API consistency. - :type bounds: sequence or ``Bounds``, optional - - .. seealso:: - - :obj:`pints.Adam` - The PINTS implementation this class is based on. - - -.. py:class:: BaseCost(problem) - - - Base class for defining cost functions. - - This class is intended to be subclassed to create specific cost functions - for evaluating model predictions against a set of data. The cost function - quantifies the goodness-of-fit between the model predictions and the - observed data, with a lower cost value indicating a better fit. - - :param problem: A problem instance containing the data and functions necessary for - evaluating the cost function. - :type problem: object - :param _target: An array containing the target data to fit. - :type _target: array-like - :param x0: The initial guess for the model parameters. - :type x0: array-like - :param bounds: The bounds for the model parameters. - :type bounds: tuple - :param n_parameters: The number of parameters in the model. - :type n_parameters: int - - .. py:method:: __call__(x, grad=None) - :abstractmethod: - - Calculate the cost function value for a given set of parameters. - - This method must be implemented by subclasses. - - :param x: The parameters for which to evaluate the cost. - :type x: array-like - :param grad: An array to store the gradient of the cost function with respect - to the parameters. - :type grad: array-like, optional - - :returns: The calculated cost function value. - :rtype: float - - :raises NotImplementedError: If the method has not been implemented by the subclass. - - - -.. py:class:: BaseModel(name='Base Model') - - - A base class for constructing and simulating models using PyBaMM. - - This class serves as a foundation for building specific models in PyBaMM. - It provides methods to set up the model, define parameters, and perform - simulations. The class is designed to be subclassed for creating models - with custom behavior. - - .. method:: build(dataset=None, parameters=None, check_model=True, init_soc=None) - - Construct the PyBaMM model if not already built. - - .. method:: set_init_soc(init_soc) - - Set the initial state of charge for the battery model. - - .. method:: set_params() - - Assign the parameters to the model. - - .. method:: simulate(inputs, t_eval) - - Execute the forward model simulation and return the result. - - .. method:: simulateS1(inputs, t_eval) - - Perform the forward model simulation with sensitivities. - - .. method:: predict(inputs=None, t_eval=None, parameter_set=None, experiment=None, init_soc=None) - - Solve the model using PyBaMM's simulation framework and return the solution. - - - .. py:property:: built_model - - - .. py:property:: geometry - - - .. py:property:: mesh - - - .. py:property:: model_with_set_params - - - .. py:property:: parameter_set - - - .. py:property:: solver - - - .. py:property:: spatial_methods - - - .. py:property:: submesh_types - - - .. py:property:: var_pts - - - .. py:method:: build(dataset=None, parameters=None, check_model=True, init_soc=None) - - Construct the PyBaMM model if not already built, and set parameters. - - This method initializes the model components, applies the given parameters, - sets up the mesh and discretization if needed, and prepares the model - for simulations. - - :param dataset: The dataset to be used in the model construction. - :type dataset: pybamm.Dataset, optional - :param parameters: A dictionary containing parameter values to apply to the model. - :type parameters: dict, optional - :param check_model: If True, the model will be checked for correctness after construction. - :type check_model: bool, optional - :param init_soc: The initial state of charge to be used in simulations. - :type init_soc: float, optional - - - .. py:method:: predict(inputs=None, t_eval=None, parameter_set=None, experiment=None, init_soc=None) - - Solve the model using PyBaMM's simulation framework and return the solution. - - This method sets up a PyBaMM simulation by configuring the model, parameters, experiment - (if any), and initial state of charge (if provided). It then solves the simulation and - returns the resulting solution object. - - :param inputs: Input parameters for the simulation. If the input is array-like, it is converted - to a dictionary using the model's fitting keys. Defaults to None, indicating - that the default parameters should be used. - :type inputs: dict or array-like, optional - :param t_eval: An array of time points at which to evaluate the solution. Defaults to None, - which means the time points need to be specified within experiment or elsewhere. - :type t_eval: array-like, optional - :param parameter_set: A PyBaMM ParameterValues object or a dictionary containing the parameter values - to use for the simulation. Defaults to the model's current ParameterValues if None. - :type parameter_set: pybamm.ParameterValues, optional - :param experiment: A PyBaMM Experiment object specifying the experimental conditions under which - the simulation should be run. Defaults to None, indicating no experiment. - :type experiment: pybamm.Experiment, optional - :param init_soc: The initial state of charge for the simulation, as a fraction (between 0 and 1). - Defaults to None. - :type init_soc: float, optional - - :returns: The solution object returned after solving the simulation. - :rtype: pybamm.Solution - - :raises ValueError: If the model has not been configured properly before calling this method or - if PyBaMM models are not supported by the current simulation method. - - - .. py:method:: set_init_soc(init_soc) - - Set the initial state of charge for the battery model. - - :param init_soc: The initial state of charge to be used in the model. - :type init_soc: float - - - .. py:method:: set_params() - - Assign the parameters to the model. - - This method processes the model with the given parameters, sets up - the geometry, and updates the model instance. - - - .. py:method:: simulate(inputs, t_eval) - - Execute the forward model simulation and return the result. - - :param inputs: The input parameters for the simulation. If array-like, it will be - converted to a dictionary using the model's fit keys. - :type inputs: dict or array-like - :param t_eval: An array of time points at which to evaluate the solution. - :type t_eval: array-like - - :returns: The simulation result corresponding to the specified signal. - :rtype: array-like - - :raises ValueError: If the model has not been built before simulation. - - - .. py:method:: simulateS1(inputs, t_eval) - - Perform the forward model simulation with sensitivities. - - :param inputs: The input parameters for the simulation. If array-like, it will be - converted to a dictionary using the model's fit keys. - :type inputs: dict or array-like - :param t_eval: An array of time points at which to evaluate the solution and its - sensitivities. - :type t_eval: array-like - - :returns: A tuple containing the simulation result and the sensitivities. - :rtype: tuple - - :raises ValueError: If the model has not been built before simulation. - - - -.. py:class:: BaseOptimiser - - - A base class for defining optimisation methods. - - This class serves as a template for creating optimisers. It provides a basic structure for - an optimisation algorithm, including the initial setup and a method stub for performing - the optimisation process. Child classes should override the optimise and _runoptimise - methods with specific algorithms. - - .. method:: optimise(cost_function, x0=None, bounds=None, maxiter=None) - - Initiates the optimisation process. This is a stub and should be implemented in child classes. - - .. method:: _runoptimise(cost_function, x0=None, bounds=None) - - Contains the logic for the optimisation algorithm. This is a stub and should be implemented in child classes. - - .. method:: name() - - Returns the name of the optimiser. - - - .. py:method:: _runoptimise(cost_function, x0=None, bounds=None) - - Contains the logic for the optimisation algorithm. - - This method should be implemented by child classes to perform the actual optimisation. - - :param cost_function: The cost function to be minimised by the optimiser. - :type cost_function: callable - :param x0: Initial guess for the parameters. Default is None. - :type x0: ndarray, optional - :param bounds: Bounds on the parameters. Default is None. - :type bounds: sequence or Bounds, optional - - :returns: * *This method is expected to return the result of the optimisation, the format of which* - * *will be determined by the child class implementation.* - - - .. py:method:: name() - - Returns the name of the optimiser. - - :returns: The name of the optimiser, which is "BaseOptimiser" for this base class. - :rtype: str - - - .. py:method:: optimise(cost_function, x0=None, bounds=None, maxiter=None) - - Initiates the optimisation process. - - This method should be overridden by child classes with the specific optimisation algorithm. - - :param cost_function: The cost function to be minimised by the optimiser. - :type cost_function: callable - :param x0: Initial guess for the parameters. Default is None. - :type x0: ndarray, optional - :param bounds: Bounds on the parameters. Default is None. - :type bounds: sequence or Bounds, optional - :param maxiter: Maximum number of iterations to perform. Default is None. - :type maxiter: int, optional - - :rtype: The result of the optimisation process. The specific type of this result will depend on the child implementation. - - - -.. py:class:: CMAES(x0, sigma0=0.1, bounds=None) - - - Bases: :py:obj:`pints.CMAES` - - Adapter for the Covariance Matrix Adaptation Evolution Strategy (CMA-ES) optimizer in PINTS. - - CMA-ES is an evolutionary algorithm for difficult non-linear non-convex optimization problems. - It adapts the covariance matrix of a multivariate normal distribution to capture the shape of the cost landscape. - - :param x0: The initial parameter vector to optimize. - :type x0: array_like - :param sigma0: Initial standard deviation of the sampling distribution, defaults to 0.1. - :type sigma0: float, optional - :param bounds: A dictionary with 'lower' and 'upper' keys containing arrays for lower and upper bounds on the parameters. - If ``None``, no bounds are enforced. - :type bounds: dict, optional - - .. seealso:: - - :obj:`pints.CMAES` - PINTS implementation of CMA-ES algorithm. - - -.. py:class:: Dataset(name, data) - - - Represents a collection of experimental observations. - - This class provides a structured way to store and work with experimental data, - which may include applying operations such as interpolation. - - :param name: The name of the dataset, providing a label for identification. - :type name: str - :param data: The actual experimental data, typically in a structured form such as - a NumPy array or a pandas DataFrame. - :type data: array-like - - .. py:method:: Interpolant() - - Create an interpolation function of the dataset based on the independent variable. - - Currently, only time-based interpolation is supported. This method modifies - the instance's Interpolant attribute to be an interpolation function that - can be evaluated at different points in time. - - :raises NotImplementedError: If the independent variable for interpolation is not supported. - - - .. py:method:: __repr__() - - Return a string representation of the Dataset instance. - - :returns: A string that includes the name and data of the dataset. - :rtype: str - - - -.. py:class:: DesignProblem(model, parameters, experiment, check_model=True, init_soc=None, x0=None) - - - Bases: :py:obj:`BaseProblem` - - Problem class for design optimization problems. - - Extends `BaseProblem` with specifics for applying a model to an experimental design. - - :param model: The model to apply the design to. - :type model: object - :param parameters: List of parameters for the problem. - :type parameters: list - :param experiment: The experimental setup to apply the model to. - :type experiment: object - - .. py:method:: evaluate(x) - - Evaluate the model with the given parameters and return the signal. - - :param x: Parameter values to evaluate the model at. - :type x: np.ndarray - - - .. py:method:: evaluateS1(x) - - Evaluate the model with the given parameters and return the signal and its derivatives. - - :param x: Parameter values to evaluate the model at. - :type x: np.ndarray - - - .. py:method:: target() - - Return the target dataset (not applicable for design problems). - - :rtype: None - - - -.. py:class:: Exponential(scale) - - - Represents an exponential distribution with a specified scale parameter. - - This class provides methods to calculate the pdf, the log pdf, and to generate random - variates from the distribution. - - :param scale: The scale parameter (lambda) of the exponential distribution. - :type scale: float - - .. py:method:: __repr__() - - Returns a string representation of the Uniform object. - - - .. py:method:: logpdf(x) - - Calculates the logarithm of the pdf of the exponential distribution at x. - - :param x: The point at which to evaluate the log pdf. - :type x: float - - :returns: The log of the probability density function value at x. - :rtype: float - - - .. py:method:: pdf(x) - - Calculates the probability density function of the exponential distribution at x. - - :param x: The point at which to evaluate the pdf. - :type x: float - - :returns: The probability density function value at x. - :rtype: float - - - .. py:method:: rvs(size) - - Generates random variates from the exponential distribution. - - :param size: The number of random variates to generate. - :type size: int - - :returns: An array of random variates from the exponential distribution. - :rtype: array_like - - :raises ValueError: If the size parameter is not positive. - - - -.. py:class:: FittingProblem(model, parameters, dataset, signal='Voltage [V]', check_model=True, init_soc=None, x0=None) - - - Bases: :py:obj:`BaseProblem` - - Problem class for fitting (parameter estimation) problems. - - Extends `BaseProblem` with specifics for fitting a model to a dataset. - - :param model: The model to fit. - :type model: object - :param parameters: List of parameters for the problem. - :type parameters: list - :param dataset: List of data objects to fit the model to. - :type dataset: list - :param signal: The signal to fit (default: "Voltage [V]"). - :type signal: str, optional - - .. py:method:: evaluate(x) - - Evaluate the model with the given parameters and return the signal. - - :param x: Parameter values to evaluate the model at. - :type x: np.ndarray - - - .. py:method:: evaluateS1(x) - - Evaluate the model with the given parameters and return the signal and its derivatives. - - :param x: Parameter values to evaluate the model at. - :type x: np.ndarray - - - .. py:method:: target() - - Return the target dataset. - - :returns: The target dataset array. - :rtype: np.ndarray - - - -.. py:class:: Gaussian(mean, sigma) - - - Represents a Gaussian (normal) distribution with a given mean and standard deviation. - - This class provides methods to calculate the probability density function (pdf), - the logarithm of the pdf, and to generate random variates (rvs) from the distribution. - - :param mean: The mean (mu) of the Gaussian distribution. - :type mean: float - :param sigma: The standard deviation (sigma) of the Gaussian distribution. - :type sigma: float - - .. py:method:: __repr__() - - Returns a string representation of the Gaussian object. - - - .. py:method:: logpdf(x) - - Calculates the logarithm of the probability density function of the Gaussian distribution at x. - - :param x: The point at which to evaluate the log pdf. - :type x: float - - :returns: The logarithm of the probability density function value at x. - :rtype: float - - - .. py:method:: pdf(x) - - Calculates the probability density function of the Gaussian distribution at x. - - :param x: The point at which to evaluate the pdf. - :type x: float - - :returns: The probability density function value at x. - :rtype: float - - - .. py:method:: rvs(size) - - Generates random variates from the Gaussian distribution. - - :param size: The number of random variates to generate. - :type size: int - - :returns: An array of random variates from the Gaussian distribution. - :rtype: array_like - - :raises ValueError: If the size parameter is not positive. - - - -.. py:class:: GradientDescent(x0, sigma0=0.1, bounds=None) - - - Bases: :py:obj:`pints.GradientDescent` - - Implements a simple gradient descent optimization algorithm. - - This class extends the gradient descent optimizer from the PINTS library, designed - to minimize a scalar function of one or more variables. Note that this optimizer - does not support boundary constraints. - - :param x0: Initial position from which optimization will start. - :type x0: array_like - :param sigma0: Initial step size (default is 0.1). - :type sigma0: float, optional - :param bounds: Ignored by this optimizer, provided for API consistency. - :type bounds: sequence or ``Bounds``, optional - - .. seealso:: - - :obj:`pints.GradientDescent` - The PINTS implementation this class is based on. - - -.. py:class:: IRPropMin(x0, sigma0=0.1, bounds=None) - - - Bases: :py:obj:`pints.IRPropMin` - - Implements the iRpropMin optimization algorithm. - - This class inherits from the PINTS IRPropMin class, which is an optimizer that - uses resilient backpropagation with weight-backtracking. It is designed to handle - problems with large plateaus, noisy gradients, and local minima. - - :param x0: Initial position from which optimization will start. - :type x0: array_like - :param sigma0: Initial step size (default is 0.1). - :type sigma0: float, optional - :param bounds: Lower and upper bounds for each optimization parameter. - :type bounds: dict, optional - - .. seealso:: - - :obj:`pints.IRPropMin` - The PINTS implementation this class is based on. - - -.. py:class:: NLoptOptimize(n_param, xtol=None, method=None, maxiter=None) - - - Bases: :py:obj:`pybop.optimisers.base_optimiser.BaseOptimiser` - - Extends BaseOptimiser to utilize the NLopt library for nonlinear optimization. - - This class serves as an interface to the NLopt optimization algorithms. It allows the user to - define an optimization problem with bounds, initial guesses, and to select an optimization method - provided by NLopt. - - :param n_param: Number of parameters to optimize. - :type n_param: int - :param xtol: The relative tolerance for optimization (stopping criteria). If not provided, a default of 1e-5 is used. - :type xtol: float, optional - :param method: The NLopt algorithm to use for optimization. If not provided, LN_BOBYQA is used by default. - :type method: nlopt.algorithm, optional - :param maxiter: The maximum number of iterations to perform during optimization. If not provided, NLopt's default is used. - :type maxiter: int, optional - - .. method:: _runoptimise(cost_function, x0, bounds) - - Performs the optimization using the NLopt library. - - .. method:: needs_sensitivities() - - Indicates whether the optimizer requires gradient information. - - .. method:: name() - - Returns the name of the optimizer. - - - .. py:method:: _runoptimise(cost_function, x0, bounds) - - Runs the optimization process using the NLopt library. - - :param cost_function: The objective function to minimize. It should take an array of parameter values and return the scalar cost. - :type cost_function: callable - :param x0: The initial guess for the parameters. - :type x0: array_like - :param bounds: A dictionary containing the 'lower' and 'upper' bounds arrays for the parameters. - :type bounds: dict - - :returns: A tuple containing the optimized parameter values and the final cost. - :rtype: tuple - - - .. py:method:: name() - - Returns the name of this optimizer instance. - - :returns: The name 'NLoptOptimize' representing this NLopt optimization class. - :rtype: str - - - .. py:method:: needs_sensitivities() - - Indicates if the optimizer requires gradient information for the cost function. - - :returns: False, as the default NLopt algorithms do not require gradient information. - :rtype: bool - - - -.. py:class:: Optimisation(cost, optimiser=None, sigma0=None, verbose=False) - - - A class for conducting optimization using PyBOP or PINTS optimizers. - - :param cost: An objective function to be optimized, which can be either a PINTS error measure or log PDF. - :type cost: pints.ErrorMeasure or pints.LogPDF - :param optimiser: An optimizer from either the PINTS or PyBOP framework to perform the optimization (default: None). - :type optimiser: pints.Optimiser or subclass of pybop.BaseOptimizer, optional - :param sigma0: Initial step size or standard deviation for the optimizer (default: None). - :type sigma0: float or sequence, optional - :param verbose: If True, the optimization progress is printed (default: False). - :type verbose: bool, optional - - .. attribute:: x0 - - Initial parameter values for the optimization. - - :type: numpy.ndarray - - .. attribute:: bounds - - Dictionary containing the parameter bounds with keys 'lower' and 'upper'. - - :type: dict - - .. attribute:: n_parameters - - Number of parameters in the optimization problem. - - :type: int - - .. attribute:: sigma0 - - Initial step size or standard deviation for the optimizer. - - :type: float or sequence - - .. attribute:: log - - Log of the optimization process. - - :type: list - - .. py:method:: _run_pints() - - Internal method to run the optimization using a PINTS optimizer. - - :returns: * **x** (*numpy.ndarray*) -- The best parameter set found by the optimization. - * **final_cost** (*float*) -- The final cost associated with the best parameters. - - .. seealso:: :obj:`This` - - - .. py:method:: _run_pybop() - - Internal method to run the optimization using a PyBOP optimizer. - - :returns: * **x** (*numpy.ndarray*) -- The best parameter set found by the optimization. - * **final_cost** (*float*) -- The final cost associated with the best parameters. - - - .. py:method:: f_guessed_tracking() - - Check if f_guessed instead of f_best is being tracked. - Credit: PINTS - - :returns: True if f_guessed is being tracked, False otherwise. - :rtype: bool - - - .. py:method:: run() - - Run the optimization and return the optimized parameters and final cost. - - :returns: * **x** (*numpy.ndarray*) -- The best parameter set found by the optimization. - * **final_cost** (*float*) -- The final cost associated with the best parameters. - - - .. py:method:: set_f_guessed_tracking(use_f_guessed=False) - - Set the method used to track the optimizer progress. - Credit: PINTS - - :param use_f_guessed: If True, track f_guessed; otherwise, track f_best (default: False). - :type use_f_guessed: bool, optional - - - .. py:method:: set_max_evaluations(evaluations=None) - - Set a maximum number of evaluations stopping criterion. - Credit: PINTS - - :param evaluations: The maximum number of evaluations after which to stop the optimization (default: None). - :type evaluations: int, optional - - - .. py:method:: set_max_iterations(iterations=1000) - - Set the maximum number of iterations as a stopping criterion. - Credit: PINTS - - :param iterations: The maximum number of iterations to run (default is 1000). - Set to `None` to remove this stopping criterion. - :type iterations: int, optional - - - .. py:method:: set_max_unchanged_iterations(iterations=25, threshold=1e-05) - - Set the maximum number of iterations without significant change as a stopping criterion. - Credit: PINTS - - :param iterations: The maximum number of unchanged iterations to run (default is 25). - Set to `None` to remove this stopping criterion. - :type iterations: int, optional - :param threshold: The minimum significant change in the objective function value that resets the unchanged iteration counter (default is 1e-5). - :type threshold: float, optional - - - .. py:method:: set_parallel(parallel=False) - - Enable or disable parallel evaluation. - Credit: PINTS - - :param parallel: If True, use as many worker processes as there are CPU cores. If an integer, use that many workers. - If False or 0, disable parallelism (default: False). - :type parallel: bool or int, optional - - - .. py:method:: store_optimised_parameters(x) - - Update the problem parameters with optimized values. - - The optimized parameter values are stored within the associated PyBOP parameter class. - - :param x: Optimized parameter values. - :type x: array-like - - - -.. py:class:: PSO(x0, sigma0=0.1, bounds=None) - - - Bases: :py:obj:`pints.PSO` - - Implements a particle swarm optimization (PSO) algorithm. - - This class extends the PSO optimizer from the PINTS library. PSO is a - metaheuristic optimization method inspired by the social behavior of birds - flocking or fish schooling, suitable for global optimization problems. - - :param x0: Initial positions of particles, which the optimization will use. - :type x0: array_like - :param sigma0: Spread of the initial particle positions (default is 0.1). - :type sigma0: float, optional - :param bounds: Lower and upper bounds for each optimization parameter. - :type bounds: dict, optional - - .. seealso:: - - :obj:`pints.PSO` - The PINTS implementation this class is based on. - - -.. py:class:: Parameter(name, initial_value=None, prior=None, bounds=None) - - - Represents a parameter within the PyBOP framework. - - This class encapsulates the definition of a parameter, including its name, prior - distribution, initial value, bounds, and a margin to ensure the parameter stays - within feasible limits during optimization or sampling. - - :param name: The name of the parameter. - :type name: str - :param initial_value: The initial value to be assigned to the parameter. Defaults to None. - :type initial_value: float, optional - :param prior: The prior distribution from which parameter values are drawn. Defaults to None. - :type prior: scipy.stats distribution, optional - :param bounds: A tuple defining the lower and upper bounds for the parameter. - Defaults to None. - :type bounds: tuple, optional - - .. method:: rvs(n_samples) - - Draw random samples from the parameter's prior distribution. - - .. method:: update(value) - - Update the parameter's current value. - - .. method:: set_margin(margin) - - Set the margin to a specified positive value less than 1. - - - :raises ValueError: If the lower bound is not strictly less than the upper bound, or if - the margin is set outside the interval (0, 1). - - .. py:method:: __repr__() - - Return a string representation of the Parameter instance. - - :returns: A string including the parameter's name, prior, bounds, and current value. - :rtype: str - - - .. py:method:: rvs(n_samples) - - Draw random samples from the parameter's prior distribution. - - The samples are constrained to be within the parameter's bounds, excluding - a predefined margin at the boundaries. - - :param n_samples: The number of samples to draw. - :type n_samples: int - - :returns: An array of samples drawn from the prior distribution within the parameter's bounds. - :rtype: array-like - - - .. py:method:: set_margin(margin) - - Set the margin to a specified positive value less than 1. - - The margin is used to ensure parameter samples are not drawn exactly at the bounds, - which may be problematic in some optimization or sampling algorithms. - - :param margin: The new margin value to be used, which must be in the interval (0, 1). - :type margin: float - - :raises ValueError: If the margin is not between 0 and 1. - - - .. py:method:: update(value) - - Update the parameter's current value. - - :param value: The new value to be assigned to the parameter. - :type value: float - - - -.. py:class:: ParameterSet(json_path=None, params_dict=None) - - - Handles the import and export of parameter sets for battery models. - - This class provides methods to load parameters from a JSON file and to export them - back to a JSON file. It also includes custom logic to handle special cases, such - as parameter values that require specific initialization. - - :param json_path: Path to a JSON file containing parameter data. If provided, parameters will be imported from this file during initialization. - :type json_path: str, optional - :param params_dict: A dictionary of parameters to initialize the ParameterSet with. If not provided, an empty dictionary is used. - :type params_dict: dict, optional - - .. py:method:: _handle_special_cases() - - Processes special cases for parameter values that require custom handling. - - For example, if the open-circuit voltage is specified as 'default', it will - fetch the default value from the PyBaMM empirical Thevenin model. - - - .. py:method:: export_parameters(output_json_path, fit_params=None) - - Exports parameters to a JSON file specified by `output_json_path`. - - The current state of the `params` attribute is written to the file. If `fit_params` - is provided, these parameters are updated before export. Non-serializable values - are handled and noted in the output JSON. - - :param output_json_path: The file path where the JSON output will be saved. - :type output_json_path: str - :param fit_params: Parameters that have been fitted and need to be included in the export. - :type fit_params: list of fitted parameter objects, optional - - :raises ValueError: If there are no parameters to export. - - - .. py:method:: import_parameters(json_path=None) - - Imports parameters from a JSON file specified by the `json_path` attribute. - - If a `json_path` is provided at initialization or as an argument, that JSON file - is loaded and the parameters are stored in the `params` attribute. Special cases - are handled appropriately. - - :param json_path: Path to the JSON file from which to import parameters. If provided, it overrides the instance's `json_path`. - :type json_path: str, optional - - :returns: The dictionary containing the imported parameters. - :rtype: dict - - :raises FileNotFoundError: If the specified JSON file cannot be found. - - - .. py:method:: is_json_serializable(value) - - Determines if the given `value` can be serialized to JSON format. - - :param value: The value to check for JSON serializability. - :type value: any - - :returns: True if the value is JSON serializable, False otherwise. - :rtype: bool - - - .. py:method:: pybamm(name) - :classmethod: - - Retrieves a PyBaMM parameter set by name. - - :param name: The name of the PyBaMM parameter set to retrieve. - :type name: str - - :returns: A PyBaMM parameter set corresponding to the provided name. - :rtype: pybamm.ParameterValues - - - -.. py:class:: PlotlyManager - - - Manages the installation and configuration of Plotly for generating visualizations. - - This class ensures that Plotly is installed and properly configured to display - plots in a web browser. - - Upon instantiation, it checks for Plotly's presence, installs it if missing, - and configures the default renderer and browser settings. - - .. attribute:: go - - The Plotly graph_objects module for creating figures. - - :type: module - - .. attribute:: pio - - The Plotly input/output module for configuring the renderer. - - :type: module - - .. attribute:: make_subplots - - The function from Plotly for creating subplot figures. - - :type: function - - .. method:: ensure_plotly_installed() - - Verifies if Plotly is installed, importing necessary modules and prompting for installation if missing. - - .. method:: prompt_for_plotly_installation() - - Prompts the user for permission to install Plotly and proceeds with installation if consented. - - .. method:: install_plotly() - - Installs the Plotly package using pip. - - .. method:: post_install_setup() - - Sets up Plotly default renderer after installation. - - .. method:: check_renderer_settings() - - Verifies that the Plotly renderer is correctly set. - - .. method:: check_browser_availability() - - Checks if a web browser is available for rendering plots. - - - .. rubric:: Examples - - >>> plotly_manager = PlotlyManager() - - .. py:method:: check_browser_availability() - - Confirm a web browser is available for Plotly's 'browser' renderer; provide guidance if not. - - - .. py:method:: check_renderer_settings() - - Check and provide information on setting the Plotly renderer if it's not already set. - - - .. py:method:: ensure_plotly_installed() - - Check if Plotly is installed and import necessary modules; prompt for installation if missing. - - - .. py:method:: install_plotly() - - Install the Plotly package using pip. Exit if installation fails. - - - .. py:method:: post_install_setup() - - Import Plotly modules and set the default renderer after installation. - - - .. py:method:: prompt_for_plotly_installation() - - Prompt the user for Plotly installation and install it upon agreement. - - - -.. py:class:: RootMeanSquaredError(problem) - - - Bases: :py:obj:`BaseCost` - - Root mean square error cost function. - - Computes the root mean square error between model predictions and the target - data, providing a measure of the differences between predicted values and - observed values. - - Inherits all parameters and attributes from ``BaseCost``. - - - .. py:method:: __call__(x, grad=None) - - Calculate the root mean square error for a given set of parameters. - - :param x: The parameters for which to evaluate the cost. - :type x: array-like - :param grad: An array to store the gradient of the cost function with respect - to the parameters. - :type grad: array-like, optional - - :returns: The root mean square error. - :rtype: float - - :raises ValueError: If an error occurs during the calculation of the cost. - - - -.. py:class:: SNES(x0, sigma0=0.1, bounds=None) - - - Bases: :py:obj:`pints.SNES` - - Implements the stochastic natural evolution strategy (SNES) optimization algorithm. - - Inheriting from the PINTS SNES class, this optimizer is an evolutionary algorithm - that evolves a probability distribution on the parameter space, guiding the search - for the optimum based on the natural gradient of expected fitness. - - :param x0: Initial position from which optimization will start. - :type x0: array_like - :param sigma0: Initial step size (default is 0.1). - :type sigma0: float, optional - :param bounds: Lower and upper bounds for each optimization parameter. - :type bounds: dict, optional - - .. seealso:: - - :obj:`pints.SNES` - The PINTS implementation this class is based on. - - -.. py:class:: SciPyDifferentialEvolution(bounds=None, strategy='best1bin', maxiter=1000, popsize=15) - - - Bases: :py:obj:`pybop.optimisers.base_optimiser.BaseOptimiser` - - Adapts SciPy's differential_evolution function for global optimization. - - This class provides a global optimization strategy based on differential evolution, useful for problems involving continuous parameters and potentially multiple local minima. - - :param bounds: Bounds for variables. Must be provided as it is essential for differential evolution. - :type bounds: sequence or ``Bounds`` - :param strategy: The differential evolution strategy to use. Defaults to 'best1bin'. - :type strategy: str, optional - :param maxiter: Maximum number of iterations to perform. Defaults to 1000. - :type maxiter: int, optional - :param popsize: The number of individuals in the population. Defaults to 15. - :type popsize: int, optional - - .. py:method:: _runoptimise(cost_function, x0=None, bounds=None) - - Executes the optimization process using SciPy's differential_evolution function. - - :param cost_function: The objective function to minimize. - :type cost_function: callable - :param x0: Ignored parameter, provided for API consistency. - :type x0: array_like, optional - :param bounds: Bounds for the variables, required for differential evolution. - :type bounds: sequence or ``Bounds`` - - :returns: A tuple (x, final_cost) containing the optimized parameters and the value of ``cost_function`` at the optimum. - :rtype: tuple - - - .. py:method:: name() - - Provides the name of the optimization strategy. - - :returns: The name 'SciPyDifferentialEvolution'. - :rtype: str - - - .. py:method:: needs_sensitivities() - - Determines if the optimization algorithm requires gradient information. - - :returns: False, indicating that gradient information is not required for differential evolution. - :rtype: bool - - - -.. py:class:: SciPyMinimize(method=None, bounds=None, maxiter=None) - - - Bases: :py:obj:`pybop.optimisers.base_optimiser.BaseOptimiser` - - Adapts SciPy's minimize function for use as an optimization strategy. - - This class provides an interface to various scalar minimization algorithms implemented in SciPy, allowing fine-tuning of the optimization process through method selection and option configuration. - - :param method: The type of solver to use. If not specified, defaults to 'COBYLA'. - :type method: str, optional - :param bounds: Bounds for variables as supported by the selected method. - :type bounds: sequence or ``Bounds``, optional - :param maxiter: Maximum number of iterations to perform. - :type maxiter: int, optional - - .. py:method:: _runoptimise(cost_function, x0, bounds) - - Executes the optimization process using SciPy's minimize function. - - :param cost_function: The objective function to minimize. - :type cost_function: callable - :param x0: Initial guess for the parameters. - :type x0: array_like - :param bounds: Bounds for the variables. - :type bounds: sequence or `Bounds` - - :returns: A tuple (x, final_cost) containing the optimized parameters and the value of `cost_function` at the optimum. - :rtype: tuple - - - .. py:method:: name() - - Provides the name of the optimization strategy. - - :returns: The name 'SciPyMinimize'. - :rtype: str - - - .. py:method:: needs_sensitivities() - - Determines if the optimization algorithm requires gradient information. - - :returns: False, indicating that gradient information is not required. - :rtype: bool - - - -.. py:class:: StandardPlot(x, y, cost, y2=None, title=None, xaxis_title=None, yaxis_title=None, trace_name=None, width=1024, height=576) - - - A class for creating and displaying Plotly figures for model output comparison. - - Generates interactive plots comparing simulated model output with an optional target dataset and visualizes uncertainty. - - :param x: X-axis data points. - :type x: list or np.ndarray - :param y: Primary Y-axis data points for simulated model output. - :type y: list or np.ndarray - :param cost: Cost associated with the model output. - :type cost: float - :param y2: Secondary Y-axis data points for the target dataset (default: None). - :type y2: list or np.ndarray, optional - :param title: Title of the plot (default: None). - :type title: str, optional - :param xaxis_title: Title for the x-axis (default: None). - :type xaxis_title: str, optional - :param yaxis_title: Title for the y-axis (default: None). - :type yaxis_title: str, optional - :param trace_name: Name for the primary trace (default: "Simulated"). - :type trace_name: str, optional - :param width: Width of the figure in pixels (default: 1024). - :type width: int, optional - :param height: Height of the figure in pixels (default: 576). - :type height: int, optional - - .. py:method:: __call__() - - Generate the Plotly figure. - - :returns: The generated Plotly figure. - :rtype: plotly.graph_objs.Figure - - - .. py:method:: create_layout() - - Create the layout for the Plotly figure. - - :returns: The layout for the Plotly figure. - :rtype: plotly.graph_objs.Layout - - - .. py:method:: create_traces() - - Create traces for the Plotly figure. - - :returns: A list of plotly.graph_objs.Scatter objects to be used as traces. - :rtype: list - - - .. py:method:: wrap_text(text, width) - :staticmethod: - - Wrap text to a specified width with HTML line breaks. - - :param text: The text to wrap. - :type text: str - :param width: The width to wrap the text to. - :type width: int - - :returns: The wrapped text. - :rtype: str - - - -.. py:class:: SumSquaredError(problem) - - - Bases: :py:obj:`BaseCost` - - Sum of squared errors cost function. - - Computes the sum of the squares of the differences between model predictions - and target data, which serves as a measure of the total error between the - predicted and observed values. - - Inherits all parameters and attributes from ``BaseCost``. - - Additional Attributes - --------------------- - _de : float - The gradient of the cost function to use if an error occurs during - evaluation. Defaults to 1.0. - - - .. py:method:: __call__(x, grad=None) - - Calculate the sum of squared errors for a given set of parameters. - - :param x: The parameters for which to evaluate the cost. - :type x: array-like - :param grad: An array to store the gradient of the cost function with respect - to the parameters. - :type grad: array-like, optional - - :returns: The sum of squared errors. - :rtype: float - - :raises ValueError: If an error occurs during the calculation of the cost. - - - .. py:method:: evaluateS1(x) - - Compute the cost and its gradient with respect to the parameters. - - :param x: The parameters for which to compute the cost and gradient. - :type x: array-like - - :returns: A tuple containing the cost and the gradient. The cost is a float, - and the gradient is an array-like of the same length as `x`. - :rtype: tuple - - :raises ValueError: If an error occurs during the calculation of the cost or gradient. - - - .. py:method:: set_fail_gradient(de) - - Set the fail gradient to a specified value. - - The fail gradient is used if an error occurs during the calculation - of the gradient. This method allows updating the default gradient value. - - :param de: The new fail gradient value to be used. - :type de: float - - - -.. py:class:: Uniform(lower, upper) - - - Represents a uniform distribution over a specified interval. - - This class provides methods to calculate the pdf, the log pdf, and to generate - random variates from the distribution. - - :param lower: The lower bound of the distribution. - :type lower: float - :param upper: The upper bound of the distribution. - :type upper: float - - .. py:method:: __repr__() - - Returns a string representation of the Uniform object. - - - .. py:method:: logpdf(x) - - Calculates the logarithm of the pdf of the uniform distribution at x. - - :param x: The point at which to evaluate the log pdf. - :type x: float - - :returns: The log of the probability density function value at x. - :rtype: float - - - .. py:method:: pdf(x) - - Calculates the probability density function of the uniform distribution at x. - - :param x: The point at which to evaluate the pdf. - :type x: float - - :returns: The probability density function value at x. - :rtype: float - - - .. py:method:: rvs(size) - - Generates random variates from the uniform distribution. - - :param size: The number of random variates to generate. - :type size: int - - :returns: An array of random variates from the uniform distribution. - :rtype: array_like - - :raises ValueError: If the size parameter is not positive. - - - -.. py:class:: XNES(x0, sigma0=0.1, bounds=None) - - - Bases: :py:obj:`pints.XNES` - - Implements the Exponential Natural Evolution Strategy (XNES) optimizer from PINTS. - - XNES is an evolutionary algorithm that samples from a multivariate normal distribution, which is updated iteratively to fit the distribution of successful solutions. - - :param x0: The initial parameter vector to optimize. - :type x0: array_like - :param sigma0: Initial standard deviation of the sampling distribution, defaults to 0.1. - :type sigma0: float, optional - :param bounds: A dictionary with 'lower' and 'upper' keys containing arrays for lower and upper bounds on the parameters. If ``None``, no bounds are enforced. - :type bounds: dict, optional - - .. seealso:: - - :obj:`pints.XNES` - PINTS implementation of XNES algorithm. - - -.. py:function:: plot_convergence(optim, xaxis_title='Iteration', yaxis_title='Cost', title='Convergence') - - Plot the convergence of the optimisation algorithm. - - Parameters: - ---------- - optim : optimisation object - Optimisation object containing the cost function and optimiser. - xaxis_title : str, optional - Title for the x-axis (default is "Iteration"). - yaxis_title : str, optional - Title for the y-axis (default is "Cost"). - title : str, optional - Title of the plot (default is "Convergence"). - - Returns: - ---------- - fig : plotly.graph_objs.Figure - The Plotly figure object for the convergence plot. - - -.. py:function:: plot_cost2d(cost, bounds=None, optim=None, steps=10) - - Plot a 2D visualization of a cost landscape using Plotly. - - This function generates a contour plot representing the cost landscape for a provided - callable cost function over a grid of parameter values within the specified bounds. - - :param cost: The cost function to be evaluated. Must accept a list of parameters and return a cost value. - :type cost: callable - :param bounds: A 2x2 array specifying the [min, max] bounds for each parameter. If None, uses `get_param_bounds`. - :type bounds: numpy.ndarray, optional - :param optim: An optimizer instance which, if provided, overlays its specific trace on the plot. - :type optim: object, optional - :param steps: The number of intervals to divide the parameter space into along each dimension (default is 10). - :type steps: int, optional - - :returns: The Plotly figure object containing the cost landscape plot. - :rtype: plotly.graph_objs.Figure - - :raises ValueError: If the cost function does not return a valid cost when called with a parameter list. - - -.. py:function:: plot_parameters(optim, xaxis_titles='Iteration', yaxis_titles=None, title='Convergence') - - Plot the evolution of parameters during the optimization process using Plotly. - - :param optim: The optimization object containing the history of parameter values and associated cost. - :type optim: object - :param xaxis_titles: Title for the x-axis, defaulting to "Iteration". - :type xaxis_titles: str, optional - :param yaxis_titles: Titles for the y-axes, one for each parameter. If None, parameter names are used. - :type yaxis_titles: list of str, optional - :param title: Title of the plot, defaulting to "Convergence". - :type title: str, optional - - :returns: A Plotly figure object showing the parameter evolution over iterations. - :rtype: plotly.graph_objs.Figure - - -.. py:function:: quick_plot(params, cost, title='Scatter Plot', width=1024, height=576) - - Quickly plot the target dataset against minimized model output. - - :param params: Optimized parameters. - :type params: array-like - :param cost: Cost object with problem, dataset, and signal attributes. - :type cost: object - :param title: Title of the plot (default: "Scatter Plot"). - :type title: str, optional - :param width: Width of the figure in pixels (default: 1024). - :type width: int, optional - :param height: Height of the figure in pixels (default: 576). - :type height: int, optional - - :returns: The Plotly figure object for the scatter plot. - :rtype: plotly.graph_objs.Figure - - -.. py:data:: FLOAT_FORMAT - :value: '{: .17e}' - - - -.. py:data:: __version__ - :value: '23.11' - - - -.. py:data:: script_path - - - diff --git a/_sources/api/pybop/models/base_model/index.rst.txt b/_sources/api/pybop/models/base_model/index.rst.txt deleted file mode 100644 index 28872c8a2..000000000 --- a/_sources/api/pybop/models/base_model/index.rst.txt +++ /dev/null @@ -1,181 +0,0 @@ -:py:mod:`pybop.models.base_model` -================================= - -.. py:module:: pybop.models.base_model - - -Module Contents ---------------- - -Classes -~~~~~~~ - -.. autoapisummary:: - - pybop.models.base_model.BaseModel - - - - -.. py:class:: BaseModel(name='Base Model') - - - A base class for constructing and simulating models using PyBaMM. - - This class serves as a foundation for building specific models in PyBaMM. - It provides methods to set up the model, define parameters, and perform - simulations. The class is designed to be subclassed for creating models - with custom behavior. - - .. method:: build(dataset=None, parameters=None, check_model=True, init_soc=None) - - Construct the PyBaMM model if not already built. - - .. method:: set_init_soc(init_soc) - - Set the initial state of charge for the battery model. - - .. method:: set_params() - - Assign the parameters to the model. - - .. method:: simulate(inputs, t_eval) - - Execute the forward model simulation and return the result. - - .. method:: simulateS1(inputs, t_eval) - - Perform the forward model simulation with sensitivities. - - .. method:: predict(inputs=None, t_eval=None, parameter_set=None, experiment=None, init_soc=None) - - Solve the model using PyBaMM's simulation framework and return the solution. - - - .. py:property:: built_model - - - .. py:property:: geometry - - - .. py:property:: mesh - - - .. py:property:: model_with_set_params - - - .. py:property:: parameter_set - - - .. py:property:: solver - - - .. py:property:: spatial_methods - - - .. py:property:: submesh_types - - - .. py:property:: var_pts - - - .. py:method:: build(dataset=None, parameters=None, check_model=True, init_soc=None) - - Construct the PyBaMM model if not already built, and set parameters. - - This method initializes the model components, applies the given parameters, - sets up the mesh and discretization if needed, and prepares the model - for simulations. - - :param dataset: The dataset to be used in the model construction. - :type dataset: pybamm.Dataset, optional - :param parameters: A dictionary containing parameter values to apply to the model. - :type parameters: dict, optional - :param check_model: If True, the model will be checked for correctness after construction. - :type check_model: bool, optional - :param init_soc: The initial state of charge to be used in simulations. - :type init_soc: float, optional - - - .. py:method:: predict(inputs=None, t_eval=None, parameter_set=None, experiment=None, init_soc=None) - - Solve the model using PyBaMM's simulation framework and return the solution. - - This method sets up a PyBaMM simulation by configuring the model, parameters, experiment - (if any), and initial state of charge (if provided). It then solves the simulation and - returns the resulting solution object. - - :param inputs: Input parameters for the simulation. If the input is array-like, it is converted - to a dictionary using the model's fitting keys. Defaults to None, indicating - that the default parameters should be used. - :type inputs: dict or array-like, optional - :param t_eval: An array of time points at which to evaluate the solution. Defaults to None, - which means the time points need to be specified within experiment or elsewhere. - :type t_eval: array-like, optional - :param parameter_set: A PyBaMM ParameterValues object or a dictionary containing the parameter values - to use for the simulation. Defaults to the model's current ParameterValues if None. - :type parameter_set: pybamm.ParameterValues, optional - :param experiment: A PyBaMM Experiment object specifying the experimental conditions under which - the simulation should be run. Defaults to None, indicating no experiment. - :type experiment: pybamm.Experiment, optional - :param init_soc: The initial state of charge for the simulation, as a fraction (between 0 and 1). - Defaults to None. - :type init_soc: float, optional - - :returns: The solution object returned after solving the simulation. - :rtype: pybamm.Solution - - :raises ValueError: If the model has not been configured properly before calling this method or - if PyBaMM models are not supported by the current simulation method. - - - .. py:method:: set_init_soc(init_soc) - - Set the initial state of charge for the battery model. - - :param init_soc: The initial state of charge to be used in the model. - :type init_soc: float - - - .. py:method:: set_params() - - Assign the parameters to the model. - - This method processes the model with the given parameters, sets up - the geometry, and updates the model instance. - - - .. py:method:: simulate(inputs, t_eval) - - Execute the forward model simulation and return the result. - - :param inputs: The input parameters for the simulation. If array-like, it will be - converted to a dictionary using the model's fit keys. - :type inputs: dict or array-like - :param t_eval: An array of time points at which to evaluate the solution. - :type t_eval: array-like - - :returns: The simulation result corresponding to the specified signal. - :rtype: array-like - - :raises ValueError: If the model has not been built before simulation. - - - .. py:method:: simulateS1(inputs, t_eval) - - Perform the forward model simulation with sensitivities. - - :param inputs: The input parameters for the simulation. If array-like, it will be - converted to a dictionary using the model's fit keys. - :type inputs: dict or array-like - :param t_eval: An array of time points at which to evaluate the solution and its - sensitivities. - :type t_eval: array-like - - :returns: A tuple containing the simulation result and the sensitivities. - :rtype: tuple - - :raises ValueError: If the model has not been built before simulation. - - - diff --git a/_sources/api/pybop/models/empirical/ecm/index.rst.txt b/_sources/api/pybop/models/empirical/ecm/index.rst.txt deleted file mode 100644 index 154000860..000000000 --- a/_sources/api/pybop/models/empirical/ecm/index.rst.txt +++ /dev/null @@ -1,49 +0,0 @@ -:py:mod:`pybop.models.empirical.ecm` -==================================== - -.. py:module:: pybop.models.empirical.ecm - - -Module Contents ---------------- - -Classes -~~~~~~~ - -.. autoapisummary:: - - pybop.models.empirical.ecm.Thevenin - - - - -.. py:class:: Thevenin(name='Equivalent Circuit Thevenin Model', parameter_set=None, geometry=None, submesh_types=None, var_pts=None, spatial_methods=None, solver=None, options=None, **kwargs) - - - Bases: :py:obj:`pybop.models.base_model.BaseModel` - - The Thevenin class represents an equivalent circuit model based on the Thevenin model in PyBaMM. - - This class encapsulates the PyBaMM equivalent circuit Thevenin model, providing an interface - to define the parameters, geometry, submesh types, variable points, spatial methods, and solver - to be used for simulations. - - :param name: A name for the model instance. Defaults to "Equivalent Circuit Thevenin Model". - :type name: str, optional - :param parameter_set: A dictionary of parameters to be used for the model. If None, the default parameters from PyBaMM are used. - :type parameter_set: dict or None, optional - :param geometry: The geometry definitions for the model. If None, the default geometry from PyBaMM is used. - :type geometry: dict or None, optional - :param submesh_types: The types of submeshes to use. If None, the default submesh types from PyBaMM are used. - :type submesh_types: dict or None, optional - :param var_pts: The number of points for each variable in the model to define the discretization. If None, the default is used. - :type var_pts: dict or None, optional - :param spatial_methods: The spatial methods to be used for discretization. If None, the default spatial methods from PyBaMM are used. - :type spatial_methods: dict or None, optional - :param solver: The solver to use for simulating the model. If None, the default solver from PyBaMM is used. - :type solver: pybamm.Solver or None, optional - :param options: A dictionary of options to pass to the PyBaMM Thevenin model. - :type options: dict or None, optional - :param \*\*kwargs: Additional arguments passed to the PyBaMM Thevenin model constructor. - - diff --git a/_sources/api/pybop/models/empirical/index.rst.txt b/_sources/api/pybop/models/empirical/index.rst.txt deleted file mode 100644 index 002c41791..000000000 --- a/_sources/api/pybop/models/empirical/index.rst.txt +++ /dev/null @@ -1,58 +0,0 @@ -:py:mod:`pybop.models.empirical` -================================ - -.. py:module:: pybop.models.empirical - - -Submodules ----------- -.. toctree:: - :titlesonly: - :maxdepth: 1 - - ecm/index.rst - - -Package Contents ----------------- - -Classes -~~~~~~~ - -.. autoapisummary:: - - pybop.models.empirical.Thevenin - - - - -.. py:class:: Thevenin(name='Equivalent Circuit Thevenin Model', parameter_set=None, geometry=None, submesh_types=None, var_pts=None, spatial_methods=None, solver=None, options=None, **kwargs) - - - Bases: :py:obj:`pybop.models.base_model.BaseModel` - - The Thevenin class represents an equivalent circuit model based on the Thevenin model in PyBaMM. - - This class encapsulates the PyBaMM equivalent circuit Thevenin model, providing an interface - to define the parameters, geometry, submesh types, variable points, spatial methods, and solver - to be used for simulations. - - :param name: A name for the model instance. Defaults to "Equivalent Circuit Thevenin Model". - :type name: str, optional - :param parameter_set: A dictionary of parameters to be used for the model. If None, the default parameters from PyBaMM are used. - :type parameter_set: dict or None, optional - :param geometry: The geometry definitions for the model. If None, the default geometry from PyBaMM is used. - :type geometry: dict or None, optional - :param submesh_types: The types of submeshes to use. If None, the default submesh types from PyBaMM are used. - :type submesh_types: dict or None, optional - :param var_pts: The number of points for each variable in the model to define the discretization. If None, the default is used. - :type var_pts: dict or None, optional - :param spatial_methods: The spatial methods to be used for discretization. If None, the default spatial methods from PyBaMM are used. - :type spatial_methods: dict or None, optional - :param solver: The solver to use for simulating the model. If None, the default solver from PyBaMM is used. - :type solver: pybamm.Solver or None, optional - :param options: A dictionary of options to pass to the PyBaMM Thevenin model. - :type options: dict or None, optional - :param \*\*kwargs: Additional arguments passed to the PyBaMM Thevenin model constructor. - - diff --git a/_sources/api/pybop/models/index.rst.txt b/_sources/api/pybop/models/index.rst.txt deleted file mode 100644 index 665808348..000000000 --- a/_sources/api/pybop/models/index.rst.txt +++ /dev/null @@ -1,25 +0,0 @@ -:py:mod:`pybop.models` -====================== - -.. py:module:: pybop.models - - -Subpackages ------------ -.. toctree:: - :titlesonly: - :maxdepth: 3 - - empirical/index.rst - lithium_ion/index.rst - - -Submodules ----------- -.. toctree:: - :titlesonly: - :maxdepth: 1 - - base_model/index.rst - - diff --git a/_sources/api/pybop/models/lithium_ion/echem/index.rst.txt b/_sources/api/pybop/models/lithium_ion/echem/index.rst.txt deleted file mode 100644 index 09df238b5..000000000 --- a/_sources/api/pybop/models/lithium_ion/echem/index.rst.txt +++ /dev/null @@ -1,78 +0,0 @@ -:py:mod:`pybop.models.lithium_ion.echem` -======================================== - -.. py:module:: pybop.models.lithium_ion.echem - - -Module Contents ---------------- - -Classes -~~~~~~~ - -.. autoapisummary:: - - pybop.models.lithium_ion.echem.SPM - pybop.models.lithium_ion.echem.SPMe - - - - -.. py:class:: SPM(name='Single Particle Model', parameter_set=None, geometry=None, submesh_types=None, var_pts=None, spatial_methods=None, solver=None, options=None) - - - Bases: :py:obj:`pybop.models.base_model.BaseModel` - - Wraps the Single Particle Model (SPM) for simulating lithium-ion batteries, as implemented in PyBaMM. - - The SPM is a simplified physics-based model that represents a lithium-ion cell using a single - spherical particle to simulate the behavior of the negative and positive electrodes. - - :param name: The name for the model instance, defaulting to "Single Particle Model". - :type name: str, optional - :param parameter_set: The parameters for the model. If None, default parameters provided by PyBaMM are used. - :type parameter_set: pybamm.ParameterValues or dict, optional - :param geometry: The geometry definitions for the model. If None, default geometry from PyBaMM is used. - :type geometry: dict, optional - :param submesh_types: The types of submeshes to use. If None, default submesh types from PyBaMM are used. - :type submesh_types: dict, optional - :param var_pts: The discretization points for each variable in the model. If None, default points from PyBaMM are used. - :type var_pts: dict, optional - :param spatial_methods: The spatial methods used for discretization. If None, default spatial methods from PyBaMM are used. - :type spatial_methods: dict, optional - :param solver: The solver to use for simulating the model. If None, the default solver from PyBaMM is used. - :type solver: pybamm.Solver, optional - :param options: A dictionary of options to customize the behavior of the PyBaMM model. - :type options: dict, optional - - -.. py:class:: SPMe(name='Single Particle Model with Electrolyte', parameter_set=None, geometry=None, submesh_types=None, var_pts=None, spatial_methods=None, solver=None, options=None) - - - Bases: :py:obj:`pybop.models.base_model.BaseModel` - - Represents the Single Particle Model with Electrolyte (SPMe) for lithium-ion batteries. - - The SPMe extends the basic Single Particle Model (SPM) by incorporating electrolyte dynamics, - making it suitable for simulations where electrolyte effects are non-negligible. This class - provides a framework to define the model parameters, geometry, mesh types, discretization - points, spatial methods, and numerical solvers for simulation within the PyBaMM ecosystem. - - :param name: A name for the model instance, defaults to "Single Particle Model with Electrolyte". - :type name: str, optional - :param parameter_set: A dictionary or a ParameterValues object containing the parameters for the model. If None, the default PyBaMM parameters for SPMe are used. - :type parameter_set: pybamm.ParameterValues or dict, optional - :param geometry: A dictionary defining the model's geometry. If None, the default PyBaMM geometry for SPMe is used. - :type geometry: dict, optional - :param submesh_types: A dictionary defining the types of submeshes to use. If None, the default PyBaMM submesh types for SPMe are used. - :type submesh_types: dict, optional - :param var_pts: A dictionary specifying the number of points for each variable for discretization. If None, the default PyBaMM variable points for SPMe are used. - :type var_pts: dict, optional - :param spatial_methods: A dictionary specifying the spatial methods for discretization. If None, the default PyBaMM spatial methods for SPMe are used. - :type spatial_methods: dict, optional - :param solver: The solver to use for simulating the model. If None, the default PyBaMM solver for SPMe is used. - :type solver: pybamm.Solver, optional - :param options: A dictionary of options to customize the behavior of the PyBaMM model. - :type options: dict, optional - - diff --git a/_sources/api/pybop/models/lithium_ion/index.rst.txt b/_sources/api/pybop/models/lithium_ion/index.rst.txt deleted file mode 100644 index 5180306ae..000000000 --- a/_sources/api/pybop/models/lithium_ion/index.rst.txt +++ /dev/null @@ -1,87 +0,0 @@ -:py:mod:`pybop.models.lithium_ion` -================================== - -.. py:module:: pybop.models.lithium_ion - - -Submodules ----------- -.. toctree:: - :titlesonly: - :maxdepth: 1 - - echem/index.rst - - -Package Contents ----------------- - -Classes -~~~~~~~ - -.. autoapisummary:: - - pybop.models.lithium_ion.SPM - pybop.models.lithium_ion.SPMe - - - - -.. py:class:: SPM(name='Single Particle Model', parameter_set=None, geometry=None, submesh_types=None, var_pts=None, spatial_methods=None, solver=None, options=None) - - - Bases: :py:obj:`pybop.models.base_model.BaseModel` - - Wraps the Single Particle Model (SPM) for simulating lithium-ion batteries, as implemented in PyBaMM. - - The SPM is a simplified physics-based model that represents a lithium-ion cell using a single - spherical particle to simulate the behavior of the negative and positive electrodes. - - :param name: The name for the model instance, defaulting to "Single Particle Model". - :type name: str, optional - :param parameter_set: The parameters for the model. If None, default parameters provided by PyBaMM are used. - :type parameter_set: pybamm.ParameterValues or dict, optional - :param geometry: The geometry definitions for the model. If None, default geometry from PyBaMM is used. - :type geometry: dict, optional - :param submesh_types: The types of submeshes to use. If None, default submesh types from PyBaMM are used. - :type submesh_types: dict, optional - :param var_pts: The discretization points for each variable in the model. If None, default points from PyBaMM are used. - :type var_pts: dict, optional - :param spatial_methods: The spatial methods used for discretization. If None, default spatial methods from PyBaMM are used. - :type spatial_methods: dict, optional - :param solver: The solver to use for simulating the model. If None, the default solver from PyBaMM is used. - :type solver: pybamm.Solver, optional - :param options: A dictionary of options to customize the behavior of the PyBaMM model. - :type options: dict, optional - - -.. py:class:: SPMe(name='Single Particle Model with Electrolyte', parameter_set=None, geometry=None, submesh_types=None, var_pts=None, spatial_methods=None, solver=None, options=None) - - - Bases: :py:obj:`pybop.models.base_model.BaseModel` - - Represents the Single Particle Model with Electrolyte (SPMe) for lithium-ion batteries. - - The SPMe extends the basic Single Particle Model (SPM) by incorporating electrolyte dynamics, - making it suitable for simulations where electrolyte effects are non-negligible. This class - provides a framework to define the model parameters, geometry, mesh types, discretization - points, spatial methods, and numerical solvers for simulation within the PyBaMM ecosystem. - - :param name: A name for the model instance, defaults to "Single Particle Model with Electrolyte". - :type name: str, optional - :param parameter_set: A dictionary or a ParameterValues object containing the parameters for the model. If None, the default PyBaMM parameters for SPMe are used. - :type parameter_set: pybamm.ParameterValues or dict, optional - :param geometry: A dictionary defining the model's geometry. If None, the default PyBaMM geometry for SPMe is used. - :type geometry: dict, optional - :param submesh_types: A dictionary defining the types of submeshes to use. If None, the default PyBaMM submesh types for SPMe are used. - :type submesh_types: dict, optional - :param var_pts: A dictionary specifying the number of points for each variable for discretization. If None, the default PyBaMM variable points for SPMe are used. - :type var_pts: dict, optional - :param spatial_methods: A dictionary specifying the spatial methods for discretization. If None, the default PyBaMM spatial methods for SPMe are used. - :type spatial_methods: dict, optional - :param solver: The solver to use for simulating the model. If None, the default PyBaMM solver for SPMe is used. - :type solver: pybamm.Solver, optional - :param options: A dictionary of options to customize the behavior of the PyBaMM model. - :type options: dict, optional - - diff --git a/_sources/api/pybop/optimisation/index.rst.txt b/_sources/api/pybop/optimisation/index.rst.txt deleted file mode 100644 index 25cd20a74..000000000 --- a/_sources/api/pybop/optimisation/index.rst.txt +++ /dev/null @@ -1,159 +0,0 @@ -:py:mod:`pybop.optimisation` -============================ - -.. py:module:: pybop.optimisation - - -Module Contents ---------------- - -Classes -~~~~~~~ - -.. autoapisummary:: - - pybop.optimisation.Optimisation - - - - -.. py:class:: Optimisation(cost, optimiser=None, sigma0=None, verbose=False) - - - A class for conducting optimization using PyBOP or PINTS optimizers. - - :param cost: An objective function to be optimized, which can be either a PINTS error measure or log PDF. - :type cost: pints.ErrorMeasure or pints.LogPDF - :param optimiser: An optimizer from either the PINTS or PyBOP framework to perform the optimization (default: None). - :type optimiser: pints.Optimiser or subclass of pybop.BaseOptimizer, optional - :param sigma0: Initial step size or standard deviation for the optimizer (default: None). - :type sigma0: float or sequence, optional - :param verbose: If True, the optimization progress is printed (default: False). - :type verbose: bool, optional - - .. attribute:: x0 - - Initial parameter values for the optimization. - - :type: numpy.ndarray - - .. attribute:: bounds - - Dictionary containing the parameter bounds with keys 'lower' and 'upper'. - - :type: dict - - .. attribute:: n_parameters - - Number of parameters in the optimization problem. - - :type: int - - .. attribute:: sigma0 - - Initial step size or standard deviation for the optimizer. - - :type: float or sequence - - .. attribute:: log - - Log of the optimization process. - - :type: list - - .. py:method:: _run_pints() - - Internal method to run the optimization using a PINTS optimizer. - - :returns: * **x** (*numpy.ndarray*) -- The best parameter set found by the optimization. - * **final_cost** (*float*) -- The final cost associated with the best parameters. - - .. seealso:: :obj:`This` - - - .. py:method:: _run_pybop() - - Internal method to run the optimization using a PyBOP optimizer. - - :returns: * **x** (*numpy.ndarray*) -- The best parameter set found by the optimization. - * **final_cost** (*float*) -- The final cost associated with the best parameters. - - - .. py:method:: f_guessed_tracking() - - Check if f_guessed instead of f_best is being tracked. - Credit: PINTS - - :returns: True if f_guessed is being tracked, False otherwise. - :rtype: bool - - - .. py:method:: run() - - Run the optimization and return the optimized parameters and final cost. - - :returns: * **x** (*numpy.ndarray*) -- The best parameter set found by the optimization. - * **final_cost** (*float*) -- The final cost associated with the best parameters. - - - .. py:method:: set_f_guessed_tracking(use_f_guessed=False) - - Set the method used to track the optimizer progress. - Credit: PINTS - - :param use_f_guessed: If True, track f_guessed; otherwise, track f_best (default: False). - :type use_f_guessed: bool, optional - - - .. py:method:: set_max_evaluations(evaluations=None) - - Set a maximum number of evaluations stopping criterion. - Credit: PINTS - - :param evaluations: The maximum number of evaluations after which to stop the optimization (default: None). - :type evaluations: int, optional - - - .. py:method:: set_max_iterations(iterations=1000) - - Set the maximum number of iterations as a stopping criterion. - Credit: PINTS - - :param iterations: The maximum number of iterations to run (default is 1000). - Set to `None` to remove this stopping criterion. - :type iterations: int, optional - - - .. py:method:: set_max_unchanged_iterations(iterations=25, threshold=1e-05) - - Set the maximum number of iterations without significant change as a stopping criterion. - Credit: PINTS - - :param iterations: The maximum number of unchanged iterations to run (default is 25). - Set to `None` to remove this stopping criterion. - :type iterations: int, optional - :param threshold: The minimum significant change in the objective function value that resets the unchanged iteration counter (default is 1e-5). - :type threshold: float, optional - - - .. py:method:: set_parallel(parallel=False) - - Enable or disable parallel evaluation. - Credit: PINTS - - :param parallel: If True, use as many worker processes as there are CPU cores. If an integer, use that many workers. - If False or 0, disable parallelism (default: False). - :type parallel: bool or int, optional - - - .. py:method:: store_optimised_parameters(x) - - Update the problem parameters with optimized values. - - The optimized parameter values are stored within the associated PyBOP parameter class. - - :param x: Optimized parameter values. - :type x: array-like - - - diff --git a/_sources/api/pybop/optimisers/base_optimiser/index.rst.txt b/_sources/api/pybop/optimisers/base_optimiser/index.rst.txt deleted file mode 100644 index d69b4b7b9..000000000 --- a/_sources/api/pybop/optimisers/base_optimiser/index.rst.txt +++ /dev/null @@ -1,86 +0,0 @@ -:py:mod:`pybop.optimisers.base_optimiser` -========================================= - -.. py:module:: pybop.optimisers.base_optimiser - - -Module Contents ---------------- - -Classes -~~~~~~~ - -.. autoapisummary:: - - pybop.optimisers.base_optimiser.BaseOptimiser - - - - -.. py:class:: BaseOptimiser - - - A base class for defining optimisation methods. - - This class serves as a template for creating optimisers. It provides a basic structure for - an optimisation algorithm, including the initial setup and a method stub for performing - the optimisation process. Child classes should override the optimise and _runoptimise - methods with specific algorithms. - - .. method:: optimise(cost_function, x0=None, bounds=None, maxiter=None) - - Initiates the optimisation process. This is a stub and should be implemented in child classes. - - .. method:: _runoptimise(cost_function, x0=None, bounds=None) - - Contains the logic for the optimisation algorithm. This is a stub and should be implemented in child classes. - - .. method:: name() - - Returns the name of the optimiser. - - - .. py:method:: _runoptimise(cost_function, x0=None, bounds=None) - - Contains the logic for the optimisation algorithm. - - This method should be implemented by child classes to perform the actual optimisation. - - :param cost_function: The cost function to be minimised by the optimiser. - :type cost_function: callable - :param x0: Initial guess for the parameters. Default is None. - :type x0: ndarray, optional - :param bounds: Bounds on the parameters. Default is None. - :type bounds: sequence or Bounds, optional - - :returns: * *This method is expected to return the result of the optimisation, the format of which* - * *will be determined by the child class implementation.* - - - .. py:method:: name() - - Returns the name of the optimiser. - - :returns: The name of the optimiser, which is "BaseOptimiser" for this base class. - :rtype: str - - - .. py:method:: optimise(cost_function, x0=None, bounds=None, maxiter=None) - - Initiates the optimisation process. - - This method should be overridden by child classes with the specific optimisation algorithm. - - :param cost_function: The cost function to be minimised by the optimiser. - :type cost_function: callable - :param x0: Initial guess for the parameters. Default is None. - :type x0: ndarray, optional - :param bounds: Bounds on the parameters. Default is None. - :type bounds: sequence or Bounds, optional - :param maxiter: Maximum number of iterations to perform. Default is None. - :type maxiter: int, optional - - :rtype: The result of the optimisation process. The specific type of this result will depend on the child implementation. - - - diff --git a/_sources/api/pybop/optimisers/index.rst.txt b/_sources/api/pybop/optimisers/index.rst.txt deleted file mode 100644 index 11519d8e7..000000000 --- a/_sources/api/pybop/optimisers/index.rst.txt +++ /dev/null @@ -1,18 +0,0 @@ -:py:mod:`pybop.optimisers` -========================== - -.. py:module:: pybop.optimisers - - -Submodules ----------- -.. toctree:: - :titlesonly: - :maxdepth: 1 - - base_optimiser/index.rst - nlopt_optimize/index.rst - pints_optimisers/index.rst - scipy_optimisers/index.rst - - diff --git a/_sources/api/pybop/optimisers/nlopt_optimize/index.rst.txt b/_sources/api/pybop/optimisers/nlopt_optimize/index.rst.txt deleted file mode 100644 index 2faa2abc5..000000000 --- a/_sources/api/pybop/optimisers/nlopt_optimize/index.rst.txt +++ /dev/null @@ -1,84 +0,0 @@ -:py:mod:`pybop.optimisers.nlopt_optimize` -========================================= - -.. py:module:: pybop.optimisers.nlopt_optimize - - -Module Contents ---------------- - -Classes -~~~~~~~ - -.. autoapisummary:: - - pybop.optimisers.nlopt_optimize.NLoptOptimize - - - - -.. py:class:: NLoptOptimize(n_param, xtol=None, method=None, maxiter=None) - - - Bases: :py:obj:`pybop.optimisers.base_optimiser.BaseOptimiser` - - Extends BaseOptimiser to utilize the NLopt library for nonlinear optimization. - - This class serves as an interface to the NLopt optimization algorithms. It allows the user to - define an optimization problem with bounds, initial guesses, and to select an optimization method - provided by NLopt. - - :param n_param: Number of parameters to optimize. - :type n_param: int - :param xtol: The relative tolerance for optimization (stopping criteria). If not provided, a default of 1e-5 is used. - :type xtol: float, optional - :param method: The NLopt algorithm to use for optimization. If not provided, LN_BOBYQA is used by default. - :type method: nlopt.algorithm, optional - :param maxiter: The maximum number of iterations to perform during optimization. If not provided, NLopt's default is used. - :type maxiter: int, optional - - .. method:: _runoptimise(cost_function, x0, bounds) - - Performs the optimization using the NLopt library. - - .. method:: needs_sensitivities() - - Indicates whether the optimizer requires gradient information. - - .. method:: name() - - Returns the name of the optimizer. - - - .. py:method:: _runoptimise(cost_function, x0, bounds) - - Runs the optimization process using the NLopt library. - - :param cost_function: The objective function to minimize. It should take an array of parameter values and return the scalar cost. - :type cost_function: callable - :param x0: The initial guess for the parameters. - :type x0: array_like - :param bounds: A dictionary containing the 'lower' and 'upper' bounds arrays for the parameters. - :type bounds: dict - - :returns: A tuple containing the optimized parameter values and the final cost. - :rtype: tuple - - - .. py:method:: name() - - Returns the name of this optimizer instance. - - :returns: The name 'NLoptOptimize' representing this NLopt optimization class. - :rtype: str - - - .. py:method:: needs_sensitivities() - - Indicates if the optimizer requires gradient information for the cost function. - - :returns: False, as the default NLopt algorithms do not require gradient information. - :rtype: bool - - - diff --git a/_sources/api/pybop/optimisers/pints_optimisers/index.rst.txt b/_sources/api/pybop/optimisers/pints_optimisers/index.rst.txt deleted file mode 100644 index a38fea790..000000000 --- a/_sources/api/pybop/optimisers/pints_optimisers/index.rst.txt +++ /dev/null @@ -1,191 +0,0 @@ -:py:mod:`pybop.optimisers.pints_optimisers` -=========================================== - -.. py:module:: pybop.optimisers.pints_optimisers - - -Module Contents ---------------- - -Classes -~~~~~~~ - -.. autoapisummary:: - - pybop.optimisers.pints_optimisers.Adam - pybop.optimisers.pints_optimisers.CMAES - pybop.optimisers.pints_optimisers.GradientDescent - pybop.optimisers.pints_optimisers.IRPropMin - pybop.optimisers.pints_optimisers.PSO - pybop.optimisers.pints_optimisers.SNES - pybop.optimisers.pints_optimisers.XNES - - - - -.. py:class:: Adam(x0, sigma0=0.1, bounds=None) - - - Bases: :py:obj:`pints.Adam` - - Implements the Adam optimization algorithm. - - This class extends the Adam optimizer from the PINTS library, which combines - ideas from RMSProp and Stochastic Gradient Descent with momentum. Note that - this optimizer does not support boundary constraints. - - :param x0: Initial position from which optimization will start. - :type x0: array_like - :param sigma0: Initial step size (default is 0.1). - :type sigma0: float, optional - :param bounds: Ignored by this optimizer, provided for API consistency. - :type bounds: sequence or ``Bounds``, optional - - .. seealso:: - - :obj:`pints.Adam` - The PINTS implementation this class is based on. - - -.. py:class:: CMAES(x0, sigma0=0.1, bounds=None) - - - Bases: :py:obj:`pints.CMAES` - - Adapter for the Covariance Matrix Adaptation Evolution Strategy (CMA-ES) optimizer in PINTS. - - CMA-ES is an evolutionary algorithm for difficult non-linear non-convex optimization problems. - It adapts the covariance matrix of a multivariate normal distribution to capture the shape of the cost landscape. - - :param x0: The initial parameter vector to optimize. - :type x0: array_like - :param sigma0: Initial standard deviation of the sampling distribution, defaults to 0.1. - :type sigma0: float, optional - :param bounds: A dictionary with 'lower' and 'upper' keys containing arrays for lower and upper bounds on the parameters. - If ``None``, no bounds are enforced. - :type bounds: dict, optional - - .. seealso:: - - :obj:`pints.CMAES` - PINTS implementation of CMA-ES algorithm. - - -.. py:class:: GradientDescent(x0, sigma0=0.1, bounds=None) - - - Bases: :py:obj:`pints.GradientDescent` - - Implements a simple gradient descent optimization algorithm. - - This class extends the gradient descent optimizer from the PINTS library, designed - to minimize a scalar function of one or more variables. Note that this optimizer - does not support boundary constraints. - - :param x0: Initial position from which optimization will start. - :type x0: array_like - :param sigma0: Initial step size (default is 0.1). - :type sigma0: float, optional - :param bounds: Ignored by this optimizer, provided for API consistency. - :type bounds: sequence or ``Bounds``, optional - - .. seealso:: - - :obj:`pints.GradientDescent` - The PINTS implementation this class is based on. - - -.. py:class:: IRPropMin(x0, sigma0=0.1, bounds=None) - - - Bases: :py:obj:`pints.IRPropMin` - - Implements the iRpropMin optimization algorithm. - - This class inherits from the PINTS IRPropMin class, which is an optimizer that - uses resilient backpropagation with weight-backtracking. It is designed to handle - problems with large plateaus, noisy gradients, and local minima. - - :param x0: Initial position from which optimization will start. - :type x0: array_like - :param sigma0: Initial step size (default is 0.1). - :type sigma0: float, optional - :param bounds: Lower and upper bounds for each optimization parameter. - :type bounds: dict, optional - - .. seealso:: - - :obj:`pints.IRPropMin` - The PINTS implementation this class is based on. - - -.. py:class:: PSO(x0, sigma0=0.1, bounds=None) - - - Bases: :py:obj:`pints.PSO` - - Implements a particle swarm optimization (PSO) algorithm. - - This class extends the PSO optimizer from the PINTS library. PSO is a - metaheuristic optimization method inspired by the social behavior of birds - flocking or fish schooling, suitable for global optimization problems. - - :param x0: Initial positions of particles, which the optimization will use. - :type x0: array_like - :param sigma0: Spread of the initial particle positions (default is 0.1). - :type sigma0: float, optional - :param bounds: Lower and upper bounds for each optimization parameter. - :type bounds: dict, optional - - .. seealso:: - - :obj:`pints.PSO` - The PINTS implementation this class is based on. - - -.. py:class:: SNES(x0, sigma0=0.1, bounds=None) - - - Bases: :py:obj:`pints.SNES` - - Implements the stochastic natural evolution strategy (SNES) optimization algorithm. - - Inheriting from the PINTS SNES class, this optimizer is an evolutionary algorithm - that evolves a probability distribution on the parameter space, guiding the search - for the optimum based on the natural gradient of expected fitness. - - :param x0: Initial position from which optimization will start. - :type x0: array_like - :param sigma0: Initial step size (default is 0.1). - :type sigma0: float, optional - :param bounds: Lower and upper bounds for each optimization parameter. - :type bounds: dict, optional - - .. seealso:: - - :obj:`pints.SNES` - The PINTS implementation this class is based on. - - -.. py:class:: XNES(x0, sigma0=0.1, bounds=None) - - - Bases: :py:obj:`pints.XNES` - - Implements the Exponential Natural Evolution Strategy (XNES) optimizer from PINTS. - - XNES is an evolutionary algorithm that samples from a multivariate normal distribution, which is updated iteratively to fit the distribution of successful solutions. - - :param x0: The initial parameter vector to optimize. - :type x0: array_like - :param sigma0: Initial standard deviation of the sampling distribution, defaults to 0.1. - :type sigma0: float, optional - :param bounds: A dictionary with 'lower' and 'upper' keys containing arrays for lower and upper bounds on the parameters. If ``None``, no bounds are enforced. - :type bounds: dict, optional - - .. seealso:: - - :obj:`pints.XNES` - PINTS implementation of XNES algorithm. - - diff --git a/_sources/api/pybop/optimisers/scipy_optimisers/index.rst.txt b/_sources/api/pybop/optimisers/scipy_optimisers/index.rst.txt deleted file mode 100644 index 3c3506780..000000000 --- a/_sources/api/pybop/optimisers/scipy_optimisers/index.rst.txt +++ /dev/null @@ -1,118 +0,0 @@ -:py:mod:`pybop.optimisers.scipy_optimisers` -=========================================== - -.. py:module:: pybop.optimisers.scipy_optimisers - - -Module Contents ---------------- - -Classes -~~~~~~~ - -.. autoapisummary:: - - pybop.optimisers.scipy_optimisers.SciPyDifferentialEvolution - pybop.optimisers.scipy_optimisers.SciPyMinimize - - - - -.. py:class:: SciPyDifferentialEvolution(bounds=None, strategy='best1bin', maxiter=1000, popsize=15) - - - Bases: :py:obj:`pybop.optimisers.base_optimiser.BaseOptimiser` - - Adapts SciPy's differential_evolution function for global optimization. - - This class provides a global optimization strategy based on differential evolution, useful for problems involving continuous parameters and potentially multiple local minima. - - :param bounds: Bounds for variables. Must be provided as it is essential for differential evolution. - :type bounds: sequence or ``Bounds`` - :param strategy: The differential evolution strategy to use. Defaults to 'best1bin'. - :type strategy: str, optional - :param maxiter: Maximum number of iterations to perform. Defaults to 1000. - :type maxiter: int, optional - :param popsize: The number of individuals in the population. Defaults to 15. - :type popsize: int, optional - - .. py:method:: _runoptimise(cost_function, x0=None, bounds=None) - - Executes the optimization process using SciPy's differential_evolution function. - - :param cost_function: The objective function to minimize. - :type cost_function: callable - :param x0: Ignored parameter, provided for API consistency. - :type x0: array_like, optional - :param bounds: Bounds for the variables, required for differential evolution. - :type bounds: sequence or ``Bounds`` - - :returns: A tuple (x, final_cost) containing the optimized parameters and the value of ``cost_function`` at the optimum. - :rtype: tuple - - - .. py:method:: name() - - Provides the name of the optimization strategy. - - :returns: The name 'SciPyDifferentialEvolution'. - :rtype: str - - - .. py:method:: needs_sensitivities() - - Determines if the optimization algorithm requires gradient information. - - :returns: False, indicating that gradient information is not required for differential evolution. - :rtype: bool - - - -.. py:class:: SciPyMinimize(method=None, bounds=None, maxiter=None) - - - Bases: :py:obj:`pybop.optimisers.base_optimiser.BaseOptimiser` - - Adapts SciPy's minimize function for use as an optimization strategy. - - This class provides an interface to various scalar minimization algorithms implemented in SciPy, allowing fine-tuning of the optimization process through method selection and option configuration. - - :param method: The type of solver to use. If not specified, defaults to 'COBYLA'. - :type method: str, optional - :param bounds: Bounds for variables as supported by the selected method. - :type bounds: sequence or ``Bounds``, optional - :param maxiter: Maximum number of iterations to perform. - :type maxiter: int, optional - - .. py:method:: _runoptimise(cost_function, x0, bounds) - - Executes the optimization process using SciPy's minimize function. - - :param cost_function: The objective function to minimize. - :type cost_function: callable - :param x0: Initial guess for the parameters. - :type x0: array_like - :param bounds: Bounds for the variables. - :type bounds: sequence or `Bounds` - - :returns: A tuple (x, final_cost) containing the optimized parameters and the value of `cost_function` at the optimum. - :rtype: tuple - - - .. py:method:: name() - - Provides the name of the optimization strategy. - - :returns: The name 'SciPyMinimize'. - :rtype: str - - - .. py:method:: needs_sensitivities() - - Determines if the optimization algorithm requires gradient information. - - :returns: False, indicating that gradient information is not required. - :rtype: bool - - - diff --git a/_sources/api/pybop/parameters/index.rst.txt b/_sources/api/pybop/parameters/index.rst.txt deleted file mode 100644 index 926eaea60..000000000 --- a/_sources/api/pybop/parameters/index.rst.txt +++ /dev/null @@ -1,17 +0,0 @@ -:py:mod:`pybop.parameters` -========================== - -.. py:module:: pybop.parameters - - -Submodules ----------- -.. toctree:: - :titlesonly: - :maxdepth: 1 - - parameter/index.rst - parameter_set/index.rst - priors/index.rst - - diff --git a/_sources/api/pybop/parameters/parameter/index.rst.txt b/_sources/api/pybop/parameters/parameter/index.rst.txt deleted file mode 100644 index 29eead0bd..000000000 --- a/_sources/api/pybop/parameters/parameter/index.rst.txt +++ /dev/null @@ -1,98 +0,0 @@ -:py:mod:`pybop.parameters.parameter` -==================================== - -.. py:module:: pybop.parameters.parameter - - -Module Contents ---------------- - -Classes -~~~~~~~ - -.. autoapisummary:: - - pybop.parameters.parameter.Parameter - - - - -.. py:class:: Parameter(name, initial_value=None, prior=None, bounds=None) - - - Represents a parameter within the PyBOP framework. - - This class encapsulates the definition of a parameter, including its name, prior - distribution, initial value, bounds, and a margin to ensure the parameter stays - within feasible limits during optimization or sampling. - - :param name: The name of the parameter. - :type name: str - :param initial_value: The initial value to be assigned to the parameter. Defaults to None. - :type initial_value: float, optional - :param prior: The prior distribution from which parameter values are drawn. Defaults to None. - :type prior: scipy.stats distribution, optional - :param bounds: A tuple defining the lower and upper bounds for the parameter. - Defaults to None. - :type bounds: tuple, optional - - .. method:: rvs(n_samples) - - Draw random samples from the parameter's prior distribution. - - .. method:: update(value) - - Update the parameter's current value. - - .. method:: set_margin(margin) - - Set the margin to a specified positive value less than 1. - - - :raises ValueError: If the lower bound is not strictly less than the upper bound, or if - the margin is set outside the interval (0, 1). - - .. py:method:: __repr__() - - Return a string representation of the Parameter instance. - - :returns: A string including the parameter's name, prior, bounds, and current value. - :rtype: str - - - .. py:method:: rvs(n_samples) - - Draw random samples from the parameter's prior distribution. - - The samples are constrained to be within the parameter's bounds, excluding - a predefined margin at the boundaries. - - :param n_samples: The number of samples to draw. - :type n_samples: int - - :returns: An array of samples drawn from the prior distribution within the parameter's bounds. - :rtype: array-like - - - .. py:method:: set_margin(margin) - - Set the margin to a specified positive value less than 1. - - The margin is used to ensure parameter samples are not drawn exactly at the bounds, - which may be problematic in some optimization or sampling algorithms. - - :param margin: The new margin value to be used, which must be in the interval (0, 1). - :type margin: float - - :raises ValueError: If the margin is not between 0 and 1. - - - .. py:method:: update(value) - - Update the parameter's current value. - - :param value: The new value to be assigned to the parameter. - :type value: float - - - diff --git a/_sources/api/pybop/parameters/parameter_set/index.rst.txt b/_sources/api/pybop/parameters/parameter_set/index.rst.txt deleted file mode 100644 index d24c6070f..000000000 --- a/_sources/api/pybop/parameters/parameter_set/index.rst.txt +++ /dev/null @@ -1,98 +0,0 @@ -:py:mod:`pybop.parameters.parameter_set` -======================================== - -.. py:module:: pybop.parameters.parameter_set - - -Module Contents ---------------- - -Classes -~~~~~~~ - -.. autoapisummary:: - - pybop.parameters.parameter_set.ParameterSet - - - - -.. py:class:: ParameterSet(json_path=None, params_dict=None) - - - Handles the import and export of parameter sets for battery models. - - This class provides methods to load parameters from a JSON file and to export them - back to a JSON file. It also includes custom logic to handle special cases, such - as parameter values that require specific initialization. - - :param json_path: Path to a JSON file containing parameter data. If provided, parameters will be imported from this file during initialization. - :type json_path: str, optional - :param params_dict: A dictionary of parameters to initialize the ParameterSet with. If not provided, an empty dictionary is used. - :type params_dict: dict, optional - - .. py:method:: _handle_special_cases() - - Processes special cases for parameter values that require custom handling. - - For example, if the open-circuit voltage is specified as 'default', it will - fetch the default value from the PyBaMM empirical Thevenin model. - - - .. py:method:: export_parameters(output_json_path, fit_params=None) - - Exports parameters to a JSON file specified by `output_json_path`. - - The current state of the `params` attribute is written to the file. If `fit_params` - is provided, these parameters are updated before export. Non-serializable values - are handled and noted in the output JSON. - - :param output_json_path: The file path where the JSON output will be saved. - :type output_json_path: str - :param fit_params: Parameters that have been fitted and need to be included in the export. - :type fit_params: list of fitted parameter objects, optional - - :raises ValueError: If there are no parameters to export. - - - .. py:method:: import_parameters(json_path=None) - - Imports parameters from a JSON file specified by the `json_path` attribute. - - If a `json_path` is provided at initialization or as an argument, that JSON file - is loaded and the parameters are stored in the `params` attribute. Special cases - are handled appropriately. - - :param json_path: Path to the JSON file from which to import parameters. If provided, it overrides the instance's `json_path`. - :type json_path: str, optional - - :returns: The dictionary containing the imported parameters. - :rtype: dict - - :raises FileNotFoundError: If the specified JSON file cannot be found. - - - .. py:method:: is_json_serializable(value) - - Determines if the given `value` can be serialized to JSON format. - - :param value: The value to check for JSON serializability. - :type value: any - - :returns: True if the value is JSON serializable, False otherwise. - :rtype: bool - - - .. py:method:: pybamm(name) - :classmethod: - - Retrieves a PyBaMM parameter set by name. - - :param name: The name of the PyBaMM parameter set to retrieve. - :type name: str - - :returns: A PyBaMM parameter set corresponding to the provided name. - :rtype: pybamm.ParameterValues - - - diff --git a/_sources/api/pybop/parameters/priors/index.rst.txt b/_sources/api/pybop/parameters/priors/index.rst.txt deleted file mode 100644 index ed5503b30..000000000 --- a/_sources/api/pybop/parameters/priors/index.rst.txt +++ /dev/null @@ -1,181 +0,0 @@ -:py:mod:`pybop.parameters.priors` -================================= - -.. py:module:: pybop.parameters.priors - - -Module Contents ---------------- - -Classes -~~~~~~~ - -.. autoapisummary:: - - pybop.parameters.priors.Exponential - pybop.parameters.priors.Gaussian - pybop.parameters.priors.Uniform - - - - -.. py:class:: Exponential(scale) - - - Represents an exponential distribution with a specified scale parameter. - - This class provides methods to calculate the pdf, the log pdf, and to generate random - variates from the distribution. - - :param scale: The scale parameter (lambda) of the exponential distribution. - :type scale: float - - .. py:method:: __repr__() - - Returns a string representation of the Uniform object. - - - .. py:method:: logpdf(x) - - Calculates the logarithm of the pdf of the exponential distribution at x. - - :param x: The point at which to evaluate the log pdf. - :type x: float - - :returns: The log of the probability density function value at x. - :rtype: float - - - .. py:method:: pdf(x) - - Calculates the probability density function of the exponential distribution at x. - - :param x: The point at which to evaluate the pdf. - :type x: float - - :returns: The probability density function value at x. - :rtype: float - - - .. py:method:: rvs(size) - - Generates random variates from the exponential distribution. - - :param size: The number of random variates to generate. - :type size: int - - :returns: An array of random variates from the exponential distribution. - :rtype: array_like - - :raises ValueError: If the size parameter is not positive. - - - -.. py:class:: Gaussian(mean, sigma) - - - Represents a Gaussian (normal) distribution with a given mean and standard deviation. - - This class provides methods to calculate the probability density function (pdf), - the logarithm of the pdf, and to generate random variates (rvs) from the distribution. - - :param mean: The mean (mu) of the Gaussian distribution. - :type mean: float - :param sigma: The standard deviation (sigma) of the Gaussian distribution. - :type sigma: float - - .. py:method:: __repr__() - - Returns a string representation of the Gaussian object. - - - .. py:method:: logpdf(x) - - Calculates the logarithm of the probability density function of the Gaussian distribution at x. - - :param x: The point at which to evaluate the log pdf. - :type x: float - - :returns: The logarithm of the probability density function value at x. - :rtype: float - - - .. py:method:: pdf(x) - - Calculates the probability density function of the Gaussian distribution at x. - - :param x: The point at which to evaluate the pdf. - :type x: float - - :returns: The probability density function value at x. - :rtype: float - - - .. py:method:: rvs(size) - - Generates random variates from the Gaussian distribution. - - :param size: The number of random variates to generate. - :type size: int - - :returns: An array of random variates from the Gaussian distribution. - :rtype: array_like - - :raises ValueError: If the size parameter is not positive. - - - -.. py:class:: Uniform(lower, upper) - - - Represents a uniform distribution over a specified interval. - - This class provides methods to calculate the pdf, the log pdf, and to generate - random variates from the distribution. - - :param lower: The lower bound of the distribution. - :type lower: float - :param upper: The upper bound of the distribution. - :type upper: float - - .. py:method:: __repr__() - - Returns a string representation of the Uniform object. - - - .. py:method:: logpdf(x) - - Calculates the logarithm of the pdf of the uniform distribution at x. - - :param x: The point at which to evaluate the log pdf. - :type x: float - - :returns: The log of the probability density function value at x. - :rtype: float - - - .. py:method:: pdf(x) - - Calculates the probability density function of the uniform distribution at x. - - :param x: The point at which to evaluate the pdf. - :type x: float - - :returns: The probability density function value at x. - :rtype: float - - - .. py:method:: rvs(size) - - Generates random variates from the uniform distribution. - - :param size: The number of random variates to generate. - :type size: int - - :returns: An array of random variates from the uniform distribution. - :rtype: array_like - - :raises ValueError: If the size parameter is not positive. - - - diff --git a/_sources/api/pybop/plotting/index.rst.txt b/_sources/api/pybop/plotting/index.rst.txt deleted file mode 100644 index 362e48e40..000000000 --- a/_sources/api/pybop/plotting/index.rst.txt +++ /dev/null @@ -1,19 +0,0 @@ -:py:mod:`pybop.plotting` -======================== - -.. py:module:: pybop.plotting - - -Submodules ----------- -.. toctree:: - :titlesonly: - :maxdepth: 1 - - plot_convergence/index.rst - plot_cost2d/index.rst - plot_parameters/index.rst - plotly_manager/index.rst - quick_plot/index.rst - - diff --git a/_sources/api/pybop/plotting/plot_convergence/index.rst.txt b/_sources/api/pybop/plotting/plot_convergence/index.rst.txt deleted file mode 100644 index 0ee1d10fb..000000000 --- a/_sources/api/pybop/plotting/plot_convergence/index.rst.txt +++ /dev/null @@ -1,40 +0,0 @@ -:py:mod:`pybop.plotting.plot_convergence` -========================================= - -.. py:module:: pybop.plotting.plot_convergence - - -Module Contents ---------------- - - -Functions -~~~~~~~~~ - -.. autoapisummary:: - - pybop.plotting.plot_convergence.plot_convergence - - - -.. py:function:: plot_convergence(optim, xaxis_title='Iteration', yaxis_title='Cost', title='Convergence') - - Plot the convergence of the optimisation algorithm. - - Parameters: - ---------- - optim : optimisation object - Optimisation object containing the cost function and optimiser. - xaxis_title : str, optional - Title for the x-axis (default is "Iteration"). - yaxis_title : str, optional - Title for the y-axis (default is "Cost"). - title : str, optional - Title of the plot (default is "Convergence"). - - Returns: - ---------- - fig : plotly.graph_objs.Figure - The Plotly figure object for the convergence plot. - - diff --git a/_sources/api/pybop/plotting/plot_cost2d/index.rst.txt b/_sources/api/pybop/plotting/plot_cost2d/index.rst.txt deleted file mode 100644 index aec28587d..000000000 --- a/_sources/api/pybop/plotting/plot_cost2d/index.rst.txt +++ /dev/null @@ -1,75 +0,0 @@ -:py:mod:`pybop.plotting.plot_cost2d` -==================================== - -.. py:module:: pybop.plotting.plot_cost2d - - -Module Contents ---------------- - - -Functions -~~~~~~~~~ - -.. autoapisummary:: - - pybop.plotting.plot_cost2d.create_figure - pybop.plotting.plot_cost2d.get_param_bounds - pybop.plotting.plot_cost2d.plot_cost2d - - - -.. py:function:: create_figure(x, y, z, bounds, params, optim) - - Create a Plotly figure with a 2D contour plot of the cost landscape. - - :param x: 1D array of x-coordinates for the meshgrid. - :type x: numpy.ndarray - :param y: 1D array of y-coordinates for the meshgrid. - :type y: numpy.ndarray - :param z: 2D array of cost function values corresponding to the meshgrid. - :type z: numpy.ndarray - :param bounds: A 2x2 array specifying the [min, max] bounds for each parameter. - :type bounds: numpy.ndarray - :param params: An iterable of parameter objects with 'name' attributes for axis labeling. - :type params: iterable - :param optim: An optimizer instance with 'log' and 'x0' attributes for plotting traces. - :type optim: object - - :returns: The Plotly figure object with the contour plot and optimization traces. - :rtype: plotly.graph_objs.Figure - - -.. py:function:: get_param_bounds(cost) - - Retrieve parameter bounds from a cost function's associated problem parameters. - - :param cost: The cost function with an associated 'problem' attribute containing 'parameters'. - :type cost: callable - - :returns: An array of shape (n_parameters, 2) containing the bounds for each parameter. - :rtype: numpy.ndarray - - -.. py:function:: plot_cost2d(cost, bounds=None, optim=None, steps=10) - - Plot a 2D visualization of a cost landscape using Plotly. - - This function generates a contour plot representing the cost landscape for a provided - callable cost function over a grid of parameter values within the specified bounds. - - :param cost: The cost function to be evaluated. Must accept a list of parameters and return a cost value. - :type cost: callable - :param bounds: A 2x2 array specifying the [min, max] bounds for each parameter. If None, uses `get_param_bounds`. - :type bounds: numpy.ndarray, optional - :param optim: An optimizer instance which, if provided, overlays its specific trace on the plot. - :type optim: object, optional - :param steps: The number of intervals to divide the parameter space into along each dimension (default is 10). - :type steps: int, optional - - :returns: The Plotly figure object containing the cost landscape plot. - :rtype: plotly.graph_objs.Figure - - :raises ValueError: If the cost function does not return a valid cost when called with a parameter list. - - diff --git a/_sources/api/pybop/plotting/plot_parameters/index.rst.txt b/_sources/api/pybop/plotting/plot_parameters/index.rst.txt deleted file mode 100644 index 2e377a04a..000000000 --- a/_sources/api/pybop/plotting/plot_parameters/index.rst.txt +++ /dev/null @@ -1,72 +0,0 @@ -:py:mod:`pybop.plotting.plot_parameters` -======================================== - -.. py:module:: pybop.plotting.plot_parameters - - -Module Contents ---------------- - - -Functions -~~~~~~~~~ - -.. autoapisummary:: - - pybop.plotting.plot_parameters.create_subplots_with_traces - pybop.plotting.plot_parameters.create_traces - pybop.plotting.plot_parameters.plot_parameters - - - -.. py:function:: create_subplots_with_traces(traces, plot_size=(1024, 576), title='Parameter Convergence', axis_titles=None, **layout_kwargs) - - Create a subplot with individual traces for each parameter. - - :param traces: Traces to be plotted, one trace per subplot. - :type traces: list of plotly.graph_objs.Scatter - :param plot_size: The size of the plot as (width, height), defaulting to (1024, 576). - :type plot_size: tuple of int, optional - :param title: The title of the plot, defaulting to "Parameter Convergence". - :type title: str, optional - :param axis_titles: A list of (x_title, y_title) pairs for each subplot. If None, titles are omitted. - :type axis_titles: list of tuple of str, optional - :param \*\*layout_kwargs: Additional keyword arguments to customize the layout. - :type \*\*layout_kwargs: dict - - :returns: A Plotly figure object with subplots for each trace. - :rtype: plotly.graph_objs.Figure - - -.. py:function:: create_traces(params, trace_data, x_values=None) - - Create traces for plotting parameter evolution. - - :param params: List of parameter objects, each having a 'name' attribute used for labeling the trace. - :type params: list - :param trace_data: A list of arrays representing the historical values of each parameter. - :type trace_data: list of numpy.ndarray - :param x_values: The x-axis values for plotting. If None, defaults to sequential integers. - :type x_values: list or numpy.ndarray, optional - - :returns: A list of Scatter trace objects, one for each parameter. - :rtype: list of plotly.graph_objs.Scatter - - -.. py:function:: plot_parameters(optim, xaxis_titles='Iteration', yaxis_titles=None, title='Convergence') - - Plot the evolution of parameters during the optimization process using Plotly. - - :param optim: The optimization object containing the history of parameter values and associated cost. - :type optim: object - :param xaxis_titles: Title for the x-axis, defaulting to "Iteration". - :type xaxis_titles: str, optional - :param yaxis_titles: Titles for the y-axes, one for each parameter. If None, parameter names are used. - :type yaxis_titles: list of str, optional - :param title: Title of the plot, defaulting to "Convergence". - :type title: str, optional - - :returns: A Plotly figure object showing the parameter evolution over iterations. - :rtype: plotly.graph_objs.Figure - - diff --git a/_sources/api/pybop/plotting/plotly_manager/index.rst.txt b/_sources/api/pybop/plotting/plotly_manager/index.rst.txt deleted file mode 100644 index 839180342..000000000 --- a/_sources/api/pybop/plotting/plotly_manager/index.rst.txt +++ /dev/null @@ -1,108 +0,0 @@ -:py:mod:`pybop.plotting.plotly_manager` -======================================= - -.. py:module:: pybop.plotting.plotly_manager - - -Module Contents ---------------- - -Classes -~~~~~~~ - -.. autoapisummary:: - - pybop.plotting.plotly_manager.PlotlyManager - - - - -.. py:class:: PlotlyManager - - - Manages the installation and configuration of Plotly for generating visualizations. - - This class ensures that Plotly is installed and properly configured to display - plots in a web browser. - - Upon instantiation, it checks for Plotly's presence, installs it if missing, - and configures the default renderer and browser settings. - - .. attribute:: go - - The Plotly graph_objects module for creating figures. - - :type: module - - .. attribute:: pio - - The Plotly input/output module for configuring the renderer. - - :type: module - - .. attribute:: make_subplots - - The function from Plotly for creating subplot figures. - - :type: function - - .. method:: ensure_plotly_installed() - - Verifies if Plotly is installed, importing necessary modules and prompting for installation if missing. - - .. method:: prompt_for_plotly_installation() - - Prompts the user for permission to install Plotly and proceeds with installation if consented. - - .. method:: install_plotly() - - Installs the Plotly package using pip. - - .. method:: post_install_setup() - - Sets up Plotly default renderer after installation. - - .. method:: check_renderer_settings() - - Verifies that the Plotly renderer is correctly set. - - .. method:: check_browser_availability() - - Checks if a web browser is available for rendering plots. - - - .. rubric:: Examples - - >>> plotly_manager = PlotlyManager() - - .. py:method:: check_browser_availability() - - Confirm a web browser is available for Plotly's 'browser' renderer; provide guidance if not. - - - .. py:method:: check_renderer_settings() - - Check and provide information on setting the Plotly renderer if it's not already set. - - - .. py:method:: ensure_plotly_installed() - - Check if Plotly is installed and import necessary modules; prompt for installation if missing. - - - .. py:method:: install_plotly() - - Install the Plotly package using pip. Exit if installation fails. - - - .. py:method:: post_install_setup() - - Import Plotly modules and set the default renderer after installation. - - - .. py:method:: prompt_for_plotly_installation() - - Prompt the user for Plotly installation and install it upon agreement. - - - diff --git a/_sources/api/pybop/plotting/quick_plot/index.rst.txt b/_sources/api/pybop/plotting/quick_plot/index.rst.txt deleted file mode 100644 index b34038623..000000000 --- a/_sources/api/pybop/plotting/quick_plot/index.rst.txt +++ /dev/null @@ -1,113 +0,0 @@ -:py:mod:`pybop.plotting.quick_plot` -=================================== - -.. py:module:: pybop.plotting.quick_plot - - -Module Contents ---------------- - -Classes -~~~~~~~ - -.. autoapisummary:: - - pybop.plotting.quick_plot.StandardPlot - - - -Functions -~~~~~~~~~ - -.. autoapisummary:: - - pybop.plotting.quick_plot.quick_plot - - - -.. py:class:: StandardPlot(x, y, cost, y2=None, title=None, xaxis_title=None, yaxis_title=None, trace_name=None, width=1024, height=576) - - - A class for creating and displaying Plotly figures for model output comparison. - - Generates interactive plots comparing simulated model output with an optional target dataset and visualizes uncertainty. - - :param x: X-axis data points. - :type x: list or np.ndarray - :param y: Primary Y-axis data points for simulated model output. - :type y: list or np.ndarray - :param cost: Cost associated with the model output. - :type cost: float - :param y2: Secondary Y-axis data points for the target dataset (default: None). - :type y2: list or np.ndarray, optional - :param title: Title of the plot (default: None). - :type title: str, optional - :param xaxis_title: Title for the x-axis (default: None). - :type xaxis_title: str, optional - :param yaxis_title: Title for the y-axis (default: None). - :type yaxis_title: str, optional - :param trace_name: Name for the primary trace (default: "Simulated"). - :type trace_name: str, optional - :param width: Width of the figure in pixels (default: 1024). - :type width: int, optional - :param height: Height of the figure in pixels (default: 576). - :type height: int, optional - - .. py:method:: __call__() - - Generate the Plotly figure. - - :returns: The generated Plotly figure. - :rtype: plotly.graph_objs.Figure - - - .. py:method:: create_layout() - - Create the layout for the Plotly figure. - - :returns: The layout for the Plotly figure. - :rtype: plotly.graph_objs.Layout - - - .. py:method:: create_traces() - - Create traces for the Plotly figure. - - :returns: A list of plotly.graph_objs.Scatter objects to be used as traces. - :rtype: list - - - .. py:method:: wrap_text(text, width) - :staticmethod: - - Wrap text to a specified width with HTML line breaks. - - :param text: The text to wrap. - :type text: str - :param width: The width to wrap the text to. - :type width: int - - :returns: The wrapped text. - :rtype: str - - - -.. py:function:: quick_plot(params, cost, title='Scatter Plot', width=1024, height=576) - - Quickly plot the target dataset against minimized model output. - - :param params: Optimized parameters. - :type params: array-like - :param cost: Cost object with problem, dataset, and signal attributes. - :type cost: object - :param title: Title of the plot (default: "Scatter Plot"). - :type title: str, optional - :param width: Width of the figure in pixels (default: 1024). - :type width: int, optional - :param height: Height of the figure in pixels (default: 576). - :type height: int, optional - - :returns: The Plotly figure object for the scatter plot. - :rtype: plotly.graph_objs.Figure - - diff --git a/_sources/api/pybop/version/index.rst.txt b/_sources/api/pybop/version/index.rst.txt deleted file mode 100644 index 3eb8d0df9..000000000 --- a/_sources/api/pybop/version/index.rst.txt +++ /dev/null @@ -1,14 +0,0 @@ -:py:mod:`pybop.version` -======================= - -.. py:module:: pybop.version - - -Module Contents ---------------- - -.. py:data:: __version__ - :value: '23.11' - - - diff --git a/_sources/contributing.md.txt b/_sources/contributing.md.txt deleted file mode 100644 index 78caf34e3..000000000 --- a/_sources/contributing.md.txt +++ /dev/null @@ -1,2 +0,0 @@ -```{include} ../CONTRIBUTING.md -``` diff --git a/_sources/index.md.txt b/_sources/index.md.txt deleted file mode 100644 index 622dd79df..000000000 --- a/_sources/index.md.txt +++ /dev/null @@ -1,38 +0,0 @@ ---- -myst: - html_meta: - "description lang=en": | - High-level documentation for PyBOP, and corresponding links to the site. -html_theme.sidebar_secondary.remove: true ---- - -# PyBOP: Optimise and Parameterise Battery Models - -Welcome to PyBOP, a Python package dedicated to the optimization and parameterization of battery models. PyBOP is designed to streamline your workflow, whether you are conducting academic research, working in industry, or simply interested in battery technology and modelling. - -**Version: v23.11** - -```{gallery-grid} -:grid-columns: 1 2 2 2 - -- header: "{fab}`bootstrap;pst-color-primary` API Documentation" - content: "Get detailed information on functions, classes, and modules that allow you to fully leverage the power of PyBOP in your own projects." - link: "api/index.html" -- header: "{fas}`bolt;pst-color-primary` Installation" - content: "Setting up PyBOP is straightforward. Follow our step-by-step guide to install PyBOP on your system." - link: "user_guide/installation.html" -- header: "{fas}`circle-half-stroke;pst-color-primary` Usage" - content: "Discover how to use PyBOP effectively with our usage examples. From basic tasks to advanced features, learn how to solve real-world problems with PyBOP." - link: "user_guide/index.html" -- header: "{fab}`python;pst-color-primary` Contributing" - content: "Contribute to the PyBOP project and become a part of our growing community." - link: "contributing.html" -``` - -```{toctree} -:maxdepth: 2 -:hidden: - -user_guide/index -contributing -``` diff --git a/_sources/user_guide/index.md.txt b/_sources/user_guide/index.md.txt deleted file mode 100644 index 0a5496f40..000000000 --- a/_sources/user_guide/index.md.txt +++ /dev/null @@ -1,22 +0,0 @@ ---- -myst: - html_meta: - "description lang=en": | - Documentation for PyBOP users. ---- - -# User Guide - -```{toctree} -:caption: Installation - -installation - -``` - -```{toctree} -:caption: Usage - -usage - -``` diff --git a/_sources/user_guide/installation.rst.txt b/_sources/user_guide/installation.rst.txt deleted file mode 100644 index 1204d7251..000000000 --- a/_sources/user_guide/installation.rst.txt +++ /dev/null @@ -1,66 +0,0 @@ -Installation Guide for PyBOP -***************************** - -PyBOP is a versatile Python package designed for optimization and parameterization of battery models. Follow the instructions below to install PyBOP and set up your environment to begin utilizing its capabilities. - -Installing PyBOP with pip -------------------------- - -The simplest method to install PyBOP is using pip. Run the following command in your terminal: - -.. code-block:: console - - $ pip install pybop - -This command will download and install the latest stable version of PyBOP. If you want to install a specific version, you can specify the version number using the following command: - -.. code-block:: console - - $ pip install pybop==23.11 - -Installing the Development Version ----------------------------------- - -If you're interested in the cutting-edge features and want to try out the latest enhancements, you can install the development version directly from the ``develop`` branch on GitHub: - -.. code-block:: console - - $ pip install git+https://github.com/pybop-team/PyBOP.git@develop - -Please note that the development version may be less stable than the official releases. - -Local Installation from Source ------------------------------- - -For those who prefer to install PyBOP from a local clone of the repository or wish to modify the source code, you can use pip to install the package in "editable" mode. Replace "path/to/pybop" with the actual path to your local PyBOP directory: - -.. code-block:: console - - $ pip install -e "path/to/pybop" - -In editable mode, changes you make to the source code will immediately affect the PyBOP installation without the need for reinstallation. - -Verifying Installation ----------------------- - -To verify that PyBOP has been installed successfully, try running one of the provided example scripts included in the documentation or repository. If the example executes without any errors, PyBOP is ready to use. - -For Developers --------------- - -If you are installing PyBOP for development purposes, such as contributing to the project, please ensure that you follow the guidelines outlined in the contributing guide. It includes additional steps that might be necessary for setting up a development environment, including the installation of dependencies and setup of pre-commit hooks. - -`Contributing Guide <../contributing.html>`_ - -Further Assistance ------------------- - -If you encounter any issues during the installation process or have any questions regarding the use of PyBOP, feel free to reach out to the community via the `PyBOP GitHub Discussions `_. - -Next Steps ----------- - -After installing PyBOP, you might want to: - -* Explore the `Quick Start Guide `_ to begin using PyBOP. -* Check out the `API Reference <../api/index.html>`_ for detailed information on PyBOP's programming interface. diff --git a/_sources/user_guide/usage.rst.txt b/_sources/user_guide/usage.rst.txt deleted file mode 100644 index 4e2b2418e..000000000 --- a/_sources/user_guide/usage.rst.txt +++ /dev/null @@ -1,61 +0,0 @@ -Quick Start Guide for PyBOP -**************************** - -Welcome to the Quick Start Guide for PyBOP. This guide will help you get up and running with PyBOP. If you're new to PyBOP, we recommend you start here to learn the basics and get a feel for the package. - -Getting Started with PyBOP --------------------------- - -PyBOP is equipped with a series of robust tools that can help you optimize various parameters within your battery models to better match empirical data or to explore the effects of different parameters on battery behavior. - -To begin using PyBOP: - -1. Install the package using pip: - - .. code-block:: console - - $ pip install pybop - - For detailed installation instructions, including how to install specific versions or from source, see the :ref:`installation` section. - -2. Once PyBOP is installed, you can import it in your Python scripts or Jupyter notebooks: - - .. code-block:: python - - import pybop - - Now you're ready to utilize PyBOP's functionality in your projects! - -Exploring Examples ------------------- - -To help you get acquainted with PyBOP's capabilities, we provide a collection of examples that demonstrate common use cases and features of the package: - -- **Jupyter Notebooks**: Interactive notebooks that include detailed explanations alongside the live code, visualizations, and results. These are an excellent resource for learning and can be easily modified and executed to suit your needs. - -- **Python Scripts**: For those who prefer working in a text editor, IDE, or for integrating into larger projects, we provide equivalent examples in plain Python script format. - -You can find these resources in the ``examples`` folder of the PyBOP repository. To access the examples, navigate to the following path after cloning or downloading the repository: - -.. code-block:: console - - path/to/pybop/examples - -These examples are also available on our `GitHub repository `_. - -Next Steps ----------- - -Once you're comfortable with the basics demonstrated in the examples, you can dive deeper into the functionality of PyBOP by: - -- Exploring the :ref:`user-guide` for a comprehensive overview of features. -- Delving into the :ref:`api-reference` for detailed API documentation. -- Checking out the :ref:`advanced-topics` for in-depth discussions on specific PyBOP features and how to customize them for complex scenarios. - -Support and Contributions -------------------------- - -If you encounter any issues or have questions as you start using PyBOP, don't hesitate to reach out to our community: - -- **Support**: Visit our :ref:`support` page for FAQs and contact information. -- **Contributions**: Interested in contributing to PyBOP? Check out our :ref:`contributing-guide` for guidelines on how to contribute. diff --git a/_sphinx_design_static/design-style.1e8bd061cd6da7fc9cf755528e8ffc24.min.css b/_sphinx_design_static/design-style.1e8bd061cd6da7fc9cf755528e8ffc24.min.css deleted file mode 100644 index eb19f698a..000000000 --- a/_sphinx_design_static/design-style.1e8bd061cd6da7fc9cf755528e8ffc24.min.css +++ /dev/null @@ -1 +0,0 @@ -.sd-bg-primary{background-color:var(--sd-color-primary) !important}.sd-bg-text-primary{color:var(--sd-color-primary-text) !important}button.sd-bg-primary:focus,button.sd-bg-primary:hover{background-color:var(--sd-color-primary-highlight) !important}a.sd-bg-primary:focus,a.sd-bg-primary:hover{background-color:var(--sd-color-primary-highlight) !important}.sd-bg-secondary{background-color:var(--sd-color-secondary) !important}.sd-bg-text-secondary{color:var(--sd-color-secondary-text) 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p:last-of-type { - margin-bottom: 0em; -} -aside.footnote > p:last-of-type:after, -div.citation > p:last-of-type:after { - content: ""; - clear: both; -} - -dl.field-list { - display: grid; - grid-template-columns: fit-content(30%) auto; -} - -dl.field-list > dt { - font-weight: bold; - word-break: break-word; - padding-left: 0.5em; - padding-right: 5px; -} - -dl.field-list > dd { - padding-left: 0.5em; - margin-top: 0em; - margin-left: 0em; - margin-bottom: 0em; -} - -dl { - margin-bottom: 15px; -} - -dd > :first-child { - margin-top: 0px; -} - -dd ul, dd table { - margin-bottom: 10px; -} - -dd { - margin-top: 3px; - margin-bottom: 10px; - margin-left: 30px; -} - -.sig dd { - margin-top: 0px; - margin-bottom: 0px; -} - -.sig dl { - margin-top: 0px; - margin-bottom: 0px; -} - -dl > dd:last-child, -dl > dd:last-child > :last-child { - margin-bottom: 0; -} - -dt:target, span.highlighted { - background-color: #fbe54e; -} - -rect.highlighted { - fill: #fbe54e; -} - -dl.glossary dt { - font-weight: bold; - font-size: 1.1em; -} - -.versionmodified { - font-style: italic; -} - -.system-message { - background-color: #fda; - padding: 5px; - border: 3px solid red; -} - -.footnote:target { - background-color: #ffa; -} - -.line-block { - display: block; - margin-top: 1em; - margin-bottom: 1em; -} - -.line-block .line-block { - margin-top: 0; - margin-bottom: 0; - margin-left: 1.5em; -} - -.guilabel, .menuselection { - font-family: sans-serif; -} - -.accelerator { - text-decoration: underline; -} - -.classifier { - font-style: oblique; -} - -.classifier:before { - font-style: normal; - margin: 0 0.5em; - content: ":"; - display: inline-block; -} - -abbr, acronym { - border-bottom: dotted 1px; - cursor: help; -} - -.translated { - background-color: rgba(207, 255, 207, 0.2) -} - -.untranslated { - background-color: rgba(255, 207, 207, 0.2) -} - -/* -- code displays --------------------------------------------------------- */ - -pre { - overflow: auto; - overflow-y: hidden; /* fixes display issues on Chrome browsers */ -} - -pre, div[class*="highlight-"] { - clear: both; -} - -span.pre { - -moz-hyphens: none; - -ms-hyphens: none; - -webkit-hyphens: none; - hyphens: none; - white-space: nowrap; -} - -div[class*="highlight-"] { - margin: 1em 0; -} - -td.linenos pre { - border: 0; - background-color: transparent; - color: #aaa; -} - -table.highlighttable { - display: block; -} - -table.highlighttable tbody { - display: block; -} - -table.highlighttable tr { - display: flex; -} - -table.highlighttable td { - margin: 0; - padding: 0; -} - -table.highlighttable td.linenos { - padding-right: 0.5em; -} - -table.highlighttable td.code { - flex: 1; - overflow: hidden; -} - -.highlight .hll { - display: block; -} - -div.highlight pre, -table.highlighttable pre { - margin: 0; -} - -div.code-block-caption + div { - margin-top: 0; -} - -div.code-block-caption { - margin-top: 1em; - padding: 2px 5px; - font-size: small; -} - -div.code-block-caption code { - background-color: transparent; -} - -table.highlighttable td.linenos, -span.linenos, -div.highlight span.gp { /* gp: Generic.Prompt */ - user-select: none; - -webkit-user-select: text; /* Safari fallback only */ - -webkit-user-select: none; /* Chrome/Safari */ - -moz-user-select: none; /* Firefox */ - -ms-user-select: none; /* IE10+ */ -} - -div.code-block-caption span.caption-number { - padding: 0.1em 0.3em; - font-style: italic; -} - -div.code-block-caption span.caption-text { -} - -div.literal-block-wrapper { - margin: 1em 0; -} - -code.xref, a code { - background-color: transparent; - font-weight: bold; -} - -h1 code, h2 code, h3 code, h4 code, h5 code, h6 code { - background-color: transparent; -} - -.viewcode-link { - float: right; -} - -.viewcode-back { - float: right; - font-family: sans-serif; -} - -div.viewcode-block:target { - margin: -1px -10px; - padding: 0 10px; -} - -/* -- math display ---------------------------------------------------------- */ - -img.math { - vertical-align: middle; -} - -div.body div.math p { - text-align: center; -} - -span.eqno { - float: right; -} - -span.eqno a.headerlink { - position: absolute; - z-index: 1; -} - -div.math:hover a.headerlink { - visibility: visible; -} - -/* -- printout stylesheet --------------------------------------------------- */ - -@media print { - div.document, - div.documentwrapper, - div.bodywrapper { - margin: 0 !important; - width: 100%; - } - - div.sphinxsidebar, - div.related, - div.footer, - #top-link { - display: none; - } -} \ No newline at end of file diff --git a/_static/check-solid.svg b/_static/check-solid.svg deleted file mode 100644 index 92fad4b5c..000000000 --- a/_static/check-solid.svg +++ /dev/null @@ -1,4 +0,0 @@ - - - - diff --git a/_static/clipboard.min.js b/_static/clipboard.min.js deleted file mode 100644 index 54b3c4638..000000000 --- a/_static/clipboard.min.js +++ /dev/null @@ -1,7 +0,0 @@ -/*! - * clipboard.js v2.0.8 - * https://clipboardjs.com/ - * - * Licensed MIT © Zeno Rocha - */ -!function(t,e){"object"==typeof exports&&"object"==typeof module?module.exports=e():"function"==typeof define&&define.amd?define([],e):"object"==typeof exports?exports.ClipboardJS=e():t.ClipboardJS=e()}(this,function(){return n={686:function(t,e,n){"use strict";n.d(e,{default:function(){return o}});var e=n(279),i=n.n(e),e=n(370),u=n.n(e),e=n(817),c=n.n(e);function a(t){try{return document.execCommand(t)}catch(t){return}}var f=function(t){t=c()(t);return a("cut"),t};var l=function(t){var e,n,o,r=1 - - - - diff --git a/_static/copybutton.css b/_static/copybutton.css deleted file mode 100644 index f1916ec7d..000000000 --- a/_static/copybutton.css +++ /dev/null @@ -1,94 +0,0 @@ -/* Copy buttons */ -button.copybtn { - position: absolute; - display: flex; - top: .3em; - right: .3em; - width: 1.7em; - height: 1.7em; - opacity: 0; - transition: opacity 0.3s, border .3s, background-color .3s; - user-select: none; - padding: 0; - border: none; - outline: none; - border-radius: 0.4em; - /* The colors that GitHub uses */ - border: #1b1f2426 1px solid; - background-color: #f6f8fa; - color: #57606a; -} - -button.copybtn.success { - border-color: #22863a; - color: #22863a; -} - -button.copybtn svg { - stroke: currentColor; - width: 1.5em; - height: 1.5em; - padding: 0.1em; -} - -div.highlight { - position: relative; -} - -/* Show the copybutton */ -.highlight:hover button.copybtn, button.copybtn.success { - opacity: 1; -} - -.highlight button.copybtn:hover { - background-color: rgb(235, 235, 235); -} - -.highlight button.copybtn:active { - background-color: rgb(187, 187, 187); -} - -/** - * A minimal CSS-only tooltip copied from: - * https://codepen.io/mildrenben/pen/rVBrpK - * - * To use, write HTML like the following: - * - *

Short

- */ - .o-tooltip--left { - position: relative; - } - - .o-tooltip--left:after { - opacity: 0; - visibility: hidden; - position: absolute; - content: attr(data-tooltip); - padding: .2em; - font-size: .8em; - left: -.2em; - background: grey; - color: white; - white-space: nowrap; - z-index: 2; - border-radius: 2px; - transform: translateX(-102%) translateY(0); - transition: opacity 0.2s cubic-bezier(0.64, 0.09, 0.08, 1), transform 0.2s cubic-bezier(0.64, 0.09, 0.08, 1); -} - -.o-tooltip--left:hover:after { - display: block; - opacity: 1; - visibility: visible; - transform: translateX(-100%) translateY(0); - transition: opacity 0.2s cubic-bezier(0.64, 0.09, 0.08, 1), transform 0.2s cubic-bezier(0.64, 0.09, 0.08, 1); - transition-delay: .5s; -} - -/* By default the copy button shouldn't show up when printing a page */ -@media print { - button.copybtn { - display: none; - } -} diff --git a/_static/copybutton.js b/_static/copybutton.js deleted file mode 100644 index 2ea7ff3e2..000000000 --- a/_static/copybutton.js +++ /dev/null @@ -1,248 +0,0 @@ -// Localization support -const messages = { - 'en': { - 'copy': 'Copy', - 'copy_to_clipboard': 'Copy to clipboard', - 'copy_success': 'Copied!', - 'copy_failure': 'Failed to copy', - }, - 'es' : { - 'copy': 'Copiar', - 'copy_to_clipboard': 'Copiar al portapapeles', - 'copy_success': '¡Copiado!', - 'copy_failure': 'Error al copiar', - }, - 'de' : { - 'copy': 'Kopieren', - 'copy_to_clipboard': 'In die Zwischenablage kopieren', - 'copy_success': 'Kopiert!', - 'copy_failure': 'Fehler beim Kopieren', - }, - 'fr' : { - 'copy': 'Copier', - 'copy_to_clipboard': 'Copier dans le presse-papier', - 'copy_success': 'Copié !', - 'copy_failure': 'Échec de la copie', - }, - 'ru': { - 'copy': 'Скопировать', - 'copy_to_clipboard': 'Скопировать в буфер', - 'copy_success': 'Скопировано!', - 'copy_failure': 'Не удалось скопировать', - }, - 'zh-CN': { - 'copy': '复制', - 'copy_to_clipboard': '复制到剪贴板', - 'copy_success': '复制成功!', - 'copy_failure': '复制失败', - }, - 'it' : { - 'copy': 'Copiare', - 'copy_to_clipboard': 'Copiato negli appunti', - 'copy_success': 'Copiato!', - 'copy_failure': 'Errore durante la copia', - } -} - -let locale = 'en' -if( document.documentElement.lang !== undefined - && messages[document.documentElement.lang] !== undefined ) { - locale = document.documentElement.lang -} - -let doc_url_root = DOCUMENTATION_OPTIONS.URL_ROOT; -if (doc_url_root == '#') { - doc_url_root = ''; -} - -/** - * SVG files for our copy buttons - */ -let iconCheck = ` - ${messages[locale]['copy_success']} - - -` - -// If the user specified their own SVG use that, otherwise use the default -let iconCopy = ``; -if (!iconCopy) { - iconCopy = ` - ${messages[locale]['copy_to_clipboard']} - - - -` -} - -/** - * Set up copy/paste for code blocks - */ - -const runWhenDOMLoaded = cb => { - if (document.readyState != 'loading') { - cb() - } else if (document.addEventListener) { - document.addEventListener('DOMContentLoaded', cb) - } else { - document.attachEvent('onreadystatechange', function() { - if (document.readyState == 'complete') cb() - }) - } -} - -const codeCellId = index => `codecell${index}` - -// Clears selected text since ClipboardJS will select the text when copying -const clearSelection = () => { - if (window.getSelection) { - window.getSelection().removeAllRanges() - } else if (document.selection) { - document.selection.empty() - } -} - -// Changes tooltip text for a moment, then changes it back -// We want the timeout of our `success` class to be a bit shorter than the -// tooltip and icon change, so that we can hide the icon before changing back. -var timeoutIcon = 2000; -var timeoutSuccessClass = 1500; - -const temporarilyChangeTooltip = (el, oldText, newText) => { - el.setAttribute('data-tooltip', newText) - el.classList.add('success') - // Remove success a little bit sooner than we change the tooltip - // So that we can use CSS to hide the copybutton first - setTimeout(() => el.classList.remove('success'), timeoutSuccessClass) - setTimeout(() => el.setAttribute('data-tooltip', oldText), timeoutIcon) -} - -// Changes the copy button icon for two seconds, then changes it back -const temporarilyChangeIcon = (el) => { - el.innerHTML = iconCheck; - setTimeout(() => {el.innerHTML = iconCopy}, timeoutIcon) -} - -const addCopyButtonToCodeCells = () => { - // If ClipboardJS hasn't loaded, wait a bit and try again. This - // happens because we load ClipboardJS asynchronously. - if (window.ClipboardJS === undefined) { - setTimeout(addCopyButtonToCodeCells, 250) - return - } - - // Add copybuttons to all of our code cells - const COPYBUTTON_SELECTOR = 'div.highlight pre'; - const codeCells = document.querySelectorAll(COPYBUTTON_SELECTOR) - codeCells.forEach((codeCell, index) => { - const id = codeCellId(index) - codeCell.setAttribute('id', id) - - const clipboardButton = id => - `` - codeCell.insertAdjacentHTML('afterend', clipboardButton(id)) - }) - -function escapeRegExp(string) { - return string.replace(/[.*+?^${}()|[\]\\]/g, '\\$&'); // $& means the whole matched string -} - -/** - * Removes excluded text from a Node. - * - * @param {Node} target Node to filter. - * @param {string} exclude CSS selector of nodes to exclude. - * @returns {DOMString} Text from `target` with text removed. - */ -function filterText(target, exclude) { - const clone = target.cloneNode(true); // clone as to not modify the live DOM - if (exclude) { - // remove excluded nodes - clone.querySelectorAll(exclude).forEach(node => node.remove()); - } - return clone.innerText; -} - -// Callback when a copy button is clicked. Will be passed the node that was clicked -// should then grab the text and replace pieces of text that shouldn't be used in output -function formatCopyText(textContent, copybuttonPromptText, isRegexp = false, onlyCopyPromptLines = true, removePrompts = true, copyEmptyLines = true, lineContinuationChar = "", hereDocDelim = "") { - var regexp; - var match; - - // Do we check for line continuation characters and "HERE-documents"? - var useLineCont = !!lineContinuationChar - var useHereDoc = !!hereDocDelim - - // create regexp to capture prompt and remaining line - if (isRegexp) { - regexp = new RegExp('^(' + copybuttonPromptText + ')(.*)') - } else { - regexp = new RegExp('^(' + escapeRegExp(copybuttonPromptText) + ')(.*)') - } - - const outputLines = []; - var promptFound = false; - var gotLineCont = false; - var gotHereDoc = false; - const lineGotPrompt = []; - for (const line of textContent.split('\n')) { - match = line.match(regexp) - if (match || gotLineCont || gotHereDoc) { - promptFound = regexp.test(line) - lineGotPrompt.push(promptFound) - if (removePrompts && promptFound) { - outputLines.push(match[2]) - } else { - outputLines.push(line) - } - gotLineCont = line.endsWith(lineContinuationChar) & useLineCont - if (line.includes(hereDocDelim) & useHereDoc) - gotHereDoc = !gotHereDoc - } else if (!onlyCopyPromptLines) { - outputLines.push(line) - } else if (copyEmptyLines && line.trim() === '') { - outputLines.push(line) - } - } - - // If no lines with the prompt were found then just use original lines - if (lineGotPrompt.some(v => v === true)) { - textContent = outputLines.join('\n'); - } - - // Remove a trailing newline to avoid auto-running when pasting - if (textContent.endsWith("\n")) { - textContent = textContent.slice(0, -1) - } - return textContent -} - - -var copyTargetText = (trigger) => { - var target = document.querySelector(trigger.attributes['data-clipboard-target'].value); - - // get filtered text - let exclude = '.linenos'; - - let text = filterText(target, exclude); - return formatCopyText(text, '', false, true, true, true, '', '') -} - - // Initialize with a callback so we can modify the text before copy - const clipboard = new ClipboardJS('.copybtn', {text: copyTargetText}) - - // Update UI with error/success messages - clipboard.on('success', event => { - clearSelection() - temporarilyChangeTooltip(event.trigger, messages[locale]['copy'], messages[locale]['copy_success']) - temporarilyChangeIcon(event.trigger) - }) - - clipboard.on('error', event => { - temporarilyChangeTooltip(event.trigger, messages[locale]['copy'], messages[locale]['copy_failure']) - }) -} - -runWhenDOMLoaded(addCopyButtonToCodeCells) \ No newline at end of file diff --git a/_static/copybutton_funcs.js b/_static/copybutton_funcs.js deleted file mode 100644 index dbe1aaad7..000000000 --- a/_static/copybutton_funcs.js +++ /dev/null @@ -1,73 +0,0 @@ -function escapeRegExp(string) { - return string.replace(/[.*+?^${}()|[\]\\]/g, '\\$&'); // $& means the whole matched string -} - -/** - * Removes excluded text from a Node. - * - * @param {Node} target Node to filter. - * @param {string} exclude CSS selector of nodes to exclude. - * @returns {DOMString} Text from `target` with text removed. - */ -export function filterText(target, exclude) { - const clone = target.cloneNode(true); // clone as to not modify the live DOM - if (exclude) { - // remove excluded nodes - clone.querySelectorAll(exclude).forEach(node => node.remove()); - } - return clone.innerText; -} - -// Callback when a copy button is clicked. Will be passed the node that was clicked -// should then grab the text and replace pieces of text that shouldn't be used in output -export function formatCopyText(textContent, copybuttonPromptText, isRegexp = false, onlyCopyPromptLines = true, removePrompts = true, copyEmptyLines = true, lineContinuationChar = "", hereDocDelim = "") { - var regexp; - var match; - - // Do we check for line continuation characters and "HERE-documents"? - var useLineCont = !!lineContinuationChar - var useHereDoc = !!hereDocDelim - - // create regexp to capture prompt and remaining line - if (isRegexp) { - regexp = new RegExp('^(' + copybuttonPromptText + ')(.*)') - } else { - regexp = new RegExp('^(' + escapeRegExp(copybuttonPromptText) + ')(.*)') - } - - const outputLines = []; - var promptFound = false; - var gotLineCont = false; - var gotHereDoc = false; - const lineGotPrompt = []; - for (const line of textContent.split('\n')) { - match = line.match(regexp) - if (match || gotLineCont || gotHereDoc) { - promptFound = regexp.test(line) - lineGotPrompt.push(promptFound) - if (removePrompts && promptFound) { - outputLines.push(match[2]) - } else { - outputLines.push(line) - } - gotLineCont = line.endsWith(lineContinuationChar) & useLineCont - if (line.includes(hereDocDelim) & useHereDoc) - gotHereDoc = !gotHereDoc - } else if (!onlyCopyPromptLines) { - outputLines.push(line) - } else if (copyEmptyLines && line.trim() === '') { - outputLines.push(line) - } - } - - // If no lines with the prompt were found then just use original lines - if (lineGotPrompt.some(v => v === true)) { - textContent = outputLines.join('\n'); - } - - // Remove a trailing newline to avoid auto-running when pasting - if (textContent.endsWith("\n")) { - textContent = textContent.slice(0, -1) - } - return textContent -} diff --git a/_static/custom-icon.js b/_static/custom-icon.js deleted file mode 100644 index ac9c6c91e..000000000 --- a/_static/custom-icon.js +++ /dev/null @@ -1,17 +0,0 @@ -/******************************************************************************* - * Set a custom icon for pypi as it's not available in the fa built-in brands - * Taken from: https://github.com/pydata/pydata-sphinx-theme/blob/main/docs/_static/custom-icon.js - */ -FontAwesome.library.add( - (faListOldStyle = { - prefix: "fa-custom", - iconName: "pypi", - icon: [ - 17.313, // viewBox width - 19.807, // viewBox height - [], // ligature - "e001", // unicode codepoint - private use area - "m10.383 0.2-3.239 1.1769 3.1883 1.1614 3.239-1.1798zm-3.4152 1.2411-3.2362 1.1769 3.1855 1.1614 3.2369-1.1769zm6.7177 0.00281-3.2947 1.2009v3.8254l3.2947-1.1988zm-3.4145 1.2439-3.2926 1.1981v3.8254l0.17548-0.064132 3.1171-1.1347zm-6.6564 0.018325v3.8247l3.244 1.1805v-3.8254zm10.191 0.20931v2.3137l3.1777-1.1558zm3.2947 1.2425-3.2947 1.1988v3.8254l3.2947-1.1988zm-8.7058 0.45739c0.00929-1.931e-4 0.018327-2.977e-4 0.027485 0 0.25633 0.00851 0.4263 0.20713 0.42638 0.49826 1.953e-4 0.38532-0.29327 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(nextLink && nextLink.href) { - window.location.href = nextLink.href; - event.preventDefault(); - } - break; - } - } - - // some keyboard layouts may need Shift to get / - switch (event.key) { - case "/": - if (!DOCUMENTATION_OPTIONS.ENABLE_SEARCH_SHORTCUTS) break; - Documentation.focusSearchBar(); - event.preventDefault(); - } - }); - }, -}; - -// quick alias for translations -const _ = Documentation.gettext; - -_ready(Documentation.init); diff --git a/_static/documentation_options.js b/_static/documentation_options.js deleted file mode 100644 index 3e2db2d9b..000000000 --- a/_static/documentation_options.js +++ /dev/null @@ -1,13 +0,0 @@ -const DOCUMENTATION_OPTIONS = { - VERSION: 'v23.11', - LANGUAGE: 'en', - COLLAPSE_INDEX: false, - BUILDER: 'html', - FILE_SUFFIX: '.html', - LINK_SUFFIX: '.html', - HAS_SOURCE: true, - SOURCELINK_SUFFIX: '.txt', - NAVIGATION_WITH_KEYS: false, - SHOW_SEARCH_SUMMARY: true, - ENABLE_SEARCH_SHORTCUTS: true, -}; \ No newline at end of file diff --git a/_static/file.png b/_static/file.png deleted file mode 100644 index a858a410e4faa62ce324d814e4b816fff83a6fb3..0000000000000000000000000000000000000000 GIT binary patch literal 0 HcmV?d00001 literal 286 zcmV+(0pb3MP)s`hMrGg#P~ix$^RISR_I47Y|r1 z_CyJOe}D1){SET-^Amu_i71Lt6eYfZjRyw@I6OQAIXXHDfiX^GbOlHe=Ae4>0m)d(f|Me07*qoM6N<$f}vM^LjV8( diff --git a/_static/graphviz.css b/_static/graphviz.css deleted file mode 100644 index 8d81c02ed..000000000 --- a/_static/graphviz.css +++ /dev/null @@ -1,19 +0,0 @@ -/* - * graphviz.css - * ~~~~~~~~~~~~ - * - * Sphinx stylesheet -- graphviz extension. - * - * :copyright: Copyright 2007-2023 by the Sphinx team, see AUTHORS. - * :license: BSD, see LICENSE for details. - * - */ - -img.graphviz { - border: 0; - max-width: 100%; -} - -object.graphviz { - max-width: 100%; -} diff --git a/_static/language_data.js b/_static/language_data.js deleted file mode 100644 index 250f5665f..000000000 --- a/_static/language_data.js +++ /dev/null @@ -1,199 +0,0 @@ -/* - * language_data.js - * ~~~~~~~~~~~~~~~~ - * - * This script contains the language-specific data used by searchtools.js, - * namely the list of stopwords, stemmer, scorer and splitter. - * - * :copyright: Copyright 2007-2023 by the Sphinx team, see AUTHORS. - * :license: BSD, see LICENSE for details. - * - */ - -var stopwords = ["a", "and", "are", "as", "at", "be", "but", "by", "for", "if", "in", "into", "is", "it", "near", "no", "not", "of", "on", "or", "such", "that", "the", "their", "then", "there", "these", "they", "this", "to", "was", "will", "with"]; - - -/* Non-minified version is copied as a separate JS file, is available */ - -/** - * Porter Stemmer - */ -var Stemmer = function() { - - var step2list = { - ational: 'ate', - tional: 'tion', - enci: 'ence', - anci: 'ance', - izer: 'ize', - bli: 'ble', - alli: 'al', - entli: 'ent', - eli: 'e', - ousli: 'ous', - ization: 'ize', - ation: 'ate', - ator: 'ate', - alism: 'al', - iveness: 'ive', - fulness: 'ful', - ousness: 'ous', - aliti: 'al', - iviti: 'ive', - biliti: 'ble', - logi: 'log' - }; - - var step3list = { - icate: 'ic', - ative: '', - alize: 'al', - iciti: 'ic', - ical: 'ic', - ful: '', - ness: '' - }; - - var c = "[^aeiou]"; // consonant - var v = "[aeiouy]"; // vowel - var C = c + "[^aeiouy]*"; // consonant sequence - var V = v + "[aeiou]*"; // vowel sequence - - var mgr0 = "^(" + C + ")?" + V + C; // [C]VC... is m>0 - var meq1 = "^(" + C + ")?" + V + C + "(" + V + ")?$"; // [C]VC[V] is m=1 - var mgr1 = "^(" + C + ")?" + V + C + V + C; // [C]VCVC... is m>1 - var s_v = "^(" + C + ")?" + v; // vowel in stem - - this.stemWord = function (w) { - var stem; - var suffix; - var firstch; - var origword = w; - - if (w.length < 3) - return w; - - var re; - var re2; - var re3; - var re4; - - firstch = w.substr(0,1); - if (firstch == "y") - w = firstch.toUpperCase() + w.substr(1); - - // Step 1a - re = /^(.+?)(ss|i)es$/; - re2 = /^(.+?)([^s])s$/; - - if (re.test(w)) - w = w.replace(re,"$1$2"); - else if (re2.test(w)) - w = w.replace(re2,"$1$2"); - - // Step 1b - re = /^(.+?)eed$/; - re2 = /^(.+?)(ed|ing)$/; - if (re.test(w)) { - var fp = re.exec(w); - re = new RegExp(mgr0); - if (re.test(fp[1])) { - re = /.$/; - w = w.replace(re,""); - } - } - else if (re2.test(w)) { - var fp = re2.exec(w); - stem = fp[1]; - re2 = new RegExp(s_v); - if (re2.test(stem)) { - w = stem; - re2 = /(at|bl|iz)$/; - re3 = new RegExp("([^aeiouylsz])\\1$"); - re4 = new RegExp("^" + C + v + "[^aeiouwxy]$"); - if (re2.test(w)) - w = w + "e"; - else if (re3.test(w)) { - re = /.$/; - w = w.replace(re,""); - } - else if (re4.test(w)) - w = w + "e"; - } - } - - // Step 1c - re = /^(.+?)y$/; - if (re.test(w)) { - var fp = re.exec(w); - stem = fp[1]; - re = new RegExp(s_v); - if (re.test(stem)) - w = stem + "i"; - } - - // Step 2 - re = /^(.+?)(ational|tional|enci|anci|izer|bli|alli|entli|eli|ousli|ization|ation|ator|alism|iveness|fulness|ousness|aliti|iviti|biliti|logi)$/; - if (re.test(w)) { - var fp = re.exec(w); - stem = fp[1]; - suffix = fp[2]; - re = new RegExp(mgr0); - if (re.test(stem)) - w = stem + step2list[suffix]; - } - - // Step 3 - re = /^(.+?)(icate|ative|alize|iciti|ical|ful|ness)$/; - if (re.test(w)) { - var fp = re.exec(w); - stem = fp[1]; - suffix = fp[2]; - re = new RegExp(mgr0); - if (re.test(stem)) - w = stem + step3list[suffix]; - } - - // Step 4 - re = /^(.+?)(al|ance|ence|er|ic|able|ible|ant|ement|ment|ent|ou|ism|ate|iti|ous|ive|ize)$/; - re2 = /^(.+?)(s|t)(ion)$/; - if (re.test(w)) { - var fp = re.exec(w); - stem = fp[1]; - re = new RegExp(mgr1); - if (re.test(stem)) - w = stem; - } - else if (re2.test(w)) { - var fp = re2.exec(w); - stem = fp[1] + fp[2]; - re2 = new RegExp(mgr1); - if (re2.test(stem)) - w = stem; - } - - // Step 5 - re = /^(.+?)e$/; - if (re.test(w)) { - var fp = re.exec(w); - stem = fp[1]; - re = new RegExp(mgr1); - re2 = new RegExp(meq1); - re3 = new RegExp("^" + C + v + "[^aeiouwxy]$"); - if (re.test(stem) || (re2.test(stem) && !(re3.test(stem)))) - w = stem; - } - re 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l=n?"carousel-item-start":"carousel-item-end",c=n?"carousel-item-next":"carousel-item-prev";s.classList.add(c),Rt(s),i.classList.add(l),s.classList.add(l),this._queueCallback((()=>{s.classList.remove(l,c),s.classList.add(Je),i.classList.remove(Je,c,l),this._isSliding=!1,r(qe)}),i,this._isAnimated()),a&&this.cycle()}_isAnimated(){return this._element.classList.contains("slide")}_getActive(){return ye.findOne(ei,this._element)}_getItems(){return ye.find(ti,this._element)}_clearInterval(){this._interval&&(clearInterval(this._interval),this._interval=null)}_directionToOrder(t){return Yt()?t===We?Be:He:t===We?He:Be}_orderToDirection(t){return Yt()?t===Be?We:ze:t===Be?ze:We}static jQueryInterface(t){return this.each((function(){const e=oi.getOrCreateInstance(this,t);if("number"!=typeof t){if("string"==typeof t){if(void 0===e[t]||t.startsWith("_")||"constructor"===t)throw new TypeError(`No method named "${t}"`);e[t]()}}else e.to(t)}))}}ue.on(document,Ue,"[data-bs-slide], 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e=ye.getSelectorFromElement(t),i=ye.find(e).filter((t=>t===this._element));null!==e&&i.length&&this._triggerArray.push(t)}this._initializeChildren(),this._config.parent||this._addAriaAndCollapsedClass(this._triggerArray,this._isShown()),this._config.toggle&&this.toggle()}static get Default(){return _i}static get DefaultType(){return bi}static get NAME(){return"collapse"}toggle(){this._isShown()?this.hide():this.show()}show(){if(this._isTransitioning||this._isShown())return;let t=[];if(this._config.parent&&(t=this._getFirstLevelChildren(".collapse.show, .collapse.collapsing").filter((t=>t!==this._element)).map((t=>vi.getOrCreateInstance(t,{toggle:!1})))),t.length&&t[0]._isTransitioning)return;if(ue.trigger(this._element,ai).defaultPrevented)return;for(const e of t)e.hide();const e=this._getDimension();this._element.classList.remove(fi),this._element.classList.add(pi),this._element.style[e]=0,this._addAriaAndCollapsedClass(this._triggerArray,!0),this._isTransitioning=!0;const i=`scroll${e[0].toUpperCase()+e.slice(1)}`;this._queueCallback((()=>{this._isTransitioning=!1,this._element.classList.remove(pi),this._element.classList.add(fi,ui),this._element.style[e]="",ue.trigger(this._element,li)}),this._element,!0),this._element.style[e]=`${this._element[i]}px`}hide(){if(this._isTransitioning||!this._isShown())return;if(ue.trigger(this._element,ci).defaultPrevented)return;const t=this._getDimension();this._element.style[t]=`${this._element.getBoundingClientRect()[t]}px`,Rt(this._element),this._element.classList.add(pi),this._element.classList.remove(fi,ui);for(const t of this._triggerArray){const e=ye.getElementFromSelector(t);e&&!this._isShown(e)&&this._addAriaAndCollapsedClass([t],!1)}this._isTransitioning=!0,this._element.style[t]="",this._queueCallback((()=>{this._isTransitioning=!1,this._element.classList.remove(pi),this._element.classList.add(fi),ue.trigger(this._element,hi)}),this._element,!0)}_isShown(t=this._element){return t.classList.contains(ui)}_configAfterMerge(t){return t.toggle=Boolean(t.toggle),t.parent=Ft(t.parent),t}_getDimension(){return this._element.classList.contains("collapse-horizontal")?"width":"height"}_initializeChildren(){if(!this._config.parent)return;const t=this._getFirstLevelChildren(gi);for(const e of t){const t=ye.getElementFromSelector(e);t&&this._addAriaAndCollapsedClass([e],this._isShown(t))}}_getFirstLevelChildren(t){const e=ye.find(mi,this._config.parent);return ye.find(t,this._config.parent).filter((t=>!e.includes(t)))}_addAriaAndCollapsedClass(t,e){if(t.length)for(const i of t)i.classList.toggle("collapsed",!e),i.setAttribute("aria-expanded",e)}static jQueryInterface(t){const e={};return"string"==typeof t&&/show|hide/.test(t)&&(e.toggle=!1),this.each((function(){const i=vi.getOrCreateInstance(this,e);if("string"==typeof t){if(void 0===i[t])throw new TypeError(`No method named "${t}"`);i[t]()}}))}}ue.on(document,di,gi,(function(t){("A"===t.target.tagName||t.delegateTarget&&"A"===t.delegateTarget.tagName)&&t.preventDefault();for(const t of ye.getMultipleElementsFromSelector(this))vi.getOrCreateInstance(t,{toggle:!1}).toggle()})),Kt(vi);const yi="dropdown",wi=".bs.dropdown",Ei=".data-api",Ai="ArrowUp",Ti="ArrowDown",Ci=`hide${wi}`,Oi=`hidden${wi}`,xi=`show${wi}`,ki=`shown${wi}`,Li=`click${wi}${Ei}`,Si=`keydown${wi}${Ei}`,Di=`keyup${wi}${Ei}`,$i="show",Ii='[data-bs-toggle="dropdown"]:not(.disabled):not(:disabled)',Ni=`${Ii}.${$i}`,Pi=".dropdown-menu",Mi=Yt()?"top-end":"top-start",ji=Yt()?"top-start":"top-end",Fi=Yt()?"bottom-end":"bottom-start",Hi=Yt()?"bottom-start":"bottom-end",Bi=Yt()?"left-start":"right-start",Wi=Yt()?"right-start":"left-start",zi={autoClose:!0,boundary:"clippingParents",display:"dynamic",offset:[0,2],popperConfig:null,reference:"toggle"},Ri={autoClose:"(boolean|string)",boundary:"(string|element)",display:"string",offset:"(array|string|function)",popperConfig:"(null|object|function)",reference:"(string|element|object)"};class qi extends be{constructor(t,e){super(t,e),this._popper=null,this._parent=this._element.parentNode,this._menu=ye.next(this._element,Pi)[0]||ye.prev(this._element,Pi)[0]||ye.findOne(Pi,this._parent),this._inNavbar=this._detectNavbar()}static get Default(){return zi}static get DefaultType(){return Ri}static get NAME(){return yi}toggle(){return this._isShown()?this.hide():this.show()}show(){if(Bt(this._element)||this._isShown())return;const t={relatedTarget:this._element};if(!ue.trigger(this._element,xi,t).defaultPrevented){if(this._createPopper(),"ontouchstart"in document.documentElement&&!this._parent.closest(".navbar-nav"))for(const t of[].concat(...document.body.children))ue.on(t,"mouseover",zt);this._element.focus(),this._element.setAttribute("aria-expanded",!0),this._menu.classList.add($i),this._element.classList.add($i),ue.trigger(this._element,ki,t)}}hide(){if(Bt(this._element)||!this._isShown())return;const t={relatedTarget:this._element};this._completeHide(t)}dispose(){this._popper&&this._popper.destroy(),super.dispose()}update(){this._inNavbar=this._detectNavbar(),this._popper&&this._popper.update()}_completeHide(t){if(!ue.trigger(this._element,Ci,t).defaultPrevented){if("ontouchstart"in document.documentElement)for(const t of[].concat(...document.body.children))ue.off(t,"mouseover",zt);this._popper&&this._popper.destroy(),this._menu.classList.remove($i),this._element.classList.remove($i),this._element.setAttribute("aria-expanded","false"),ge.removeDataAttribute(this._menu,"popper"),ue.trigger(this._element,Oi,t)}}_getConfig(t){if("object"==typeof(t=super._getConfig(t)).reference&&!jt(t.reference)&&"function"!=typeof t.reference.getBoundingClientRect)throw new TypeError(`${yi.toUpperCase()}: Option "reference" provided type "object" without a required "getBoundingClientRect" method.`);return t}_createPopper(){if(void 0===e)throw new TypeError("Bootstrap's dropdowns require Popper (https://popper.js.org)");let t=this._element;"parent"===this._config.reference?t=this._parent:jt(this._config.reference)?t=Ft(this._config.reference):"object"==typeof this._config.reference&&(t=this._config.reference);const i=this._getPopperConfig();this._popper=St(t,this._menu,i)}_isShown(){return this._menu.classList.contains($i)}_getPlacement(){const t=this._parent;if(t.classList.contains("dropend"))return Bi;if(t.classList.contains("dropstart"))return Wi;if(t.classList.contains("dropup-center"))return"top";if(t.classList.contains("dropdown-center"))return"bottom";const e="end"===getComputedStyle(this._menu).getPropertyValue("--bs-position").trim();return t.classList.contains("dropup")?e?ji:Mi:e?Hi:Fi}_detectNavbar(){return null!==this._element.closest(".navbar")}_getOffset(){const{offset:t}=this._config;return"string"==typeof t?t.split(",").map((t=>Number.parseInt(t,10))):"function"==typeof t?e=>t(e,this._element):t}_getPopperConfig(){const t={placement:this._getPlacement(),modifiers:[{name:"preventOverflow",options:{boundary:this._config.boundary}},{name:"offset",options:{offset:this._getOffset()}}]};return(this._inNavbar||"static"===this._config.display)&&(ge.setDataAttribute(this._menu,"popper","static"),t.modifiers=[{name:"applyStyles",enabled:!1}]),{...t,...Qt(this._config.popperConfig,[t])}}_selectMenuItem({key:t,target:e}){const i=ye.find(".dropdown-menu .dropdown-item:not(.disabled):not(:disabled)",this._menu).filter((t=>Ht(t)));i.length&&Ut(i,e,t===Ti,!i.includes(e)).focus()}static jQueryInterface(t){return this.each((function(){const e=qi.getOrCreateInstance(this,t);if("string"==typeof t){if(void 0===e[t])throw new TypeError(`No method named "${t}"`);e[t]()}}))}static clearMenus(t){if(2===t.button||"keyup"===t.type&&"Tab"!==t.key)return;const e=ye.find(Ni);for(const i of e){const e=qi.getInstance(i);if(!e||!1===e._config.autoClose)continue;const n=t.composedPath(),s=n.includes(e._menu);if(n.includes(e._element)||"inside"===e._config.autoClose&&!s||"outside"===e._config.autoClose&&s)continue;if(e._menu.contains(t.target)&&("keyup"===t.type&&"Tab"===t.key||/input|select|option|textarea|form/i.test(t.target.tagName)))continue;const o={relatedTarget:e._element};"click"===t.type&&(o.clickEvent=t),e._completeHide(o)}}static dataApiKeydownHandler(t){const e=/input|textarea/i.test(t.target.tagName),i="Escape"===t.key,n=[Ai,Ti].includes(t.key);if(!n&&!i)return;if(e&&!i)return;t.preventDefault();const s=this.matches(Ii)?this:ye.prev(this,Ii)[0]||ye.next(this,Ii)[0]||ye.findOne(Ii,t.delegateTarget.parentNode),o=qi.getOrCreateInstance(s);if(n)return t.stopPropagation(),o.show(),void o._selectMenuItem(t);o._isShown()&&(t.stopPropagation(),o.hide(),s.focus())}}ue.on(document,Si,Ii,qi.dataApiKeydownHandler),ue.on(document,Si,Pi,qi.dataApiKeydownHandler),ue.on(document,Li,qi.clearMenus),ue.on(document,Di,qi.clearMenus),ue.on(document,Li,Ii,(function(t){t.preventDefault(),qi.getOrCreateInstance(this).toggle()})),Kt(qi);const Vi="backdrop",Yi="show",Ki=`mousedown.bs.${Vi}`,Qi={className:"modal-backdrop",clickCallback:null,isAnimated:!1,isVisible:!0,rootElement:"body"},Xi={className:"string",clickCallback:"(function|null)",isAnimated:"boolean",isVisible:"boolean",rootElement:"(element|string)"};class Ui extends _e{constructor(t){super(),this._config=this._getConfig(t),this._isAppended=!1,this._element=null}static get Default(){return Qi}static get DefaultType(){return Xi}static get NAME(){return Vi}show(t){if(!this._config.isVisible)return void Qt(t);this._append();const e=this._getElement();this._config.isAnimated&&Rt(e),e.classList.add(Yi),this._emulateAnimation((()=>{Qt(t)}))}hide(t){this._config.isVisible?(this._getElement().classList.remove(Yi),this._emulateAnimation((()=>{this.dispose(),Qt(t)}))):Qt(t)}dispose(){this._isAppended&&(ue.off(this._element,Ki),this._element.remove(),this._isAppended=!1)}_getElement(){if(!this._element){const t=document.createElement("div");t.className=this._config.className,this._config.isAnimated&&t.classList.add("fade"),this._element=t}return this._element}_configAfterMerge(t){return t.rootElement=Ft(t.rootElement),t}_append(){if(this._isAppended)return;const t=this._getElement();this._config.rootElement.append(t),ue.on(t,Ki,(()=>{Qt(this._config.clickCallback)})),this._isAppended=!0}_emulateAnimation(t){Xt(t,this._getElement(),this._config.isAnimated)}}const Gi=".bs.focustrap",Ji=`focusin${Gi}`,Zi=`keydown.tab${Gi}`,tn="backward",en={autofocus:!0,trapElement:null},nn={autofocus:"boolean",trapElement:"element"};class sn extends _e{constructor(t){super(),this._config=this._getConfig(t),this._isActive=!1,this._lastTabNavDirection=null}static get Default(){return en}static get DefaultType(){return nn}static get NAME(){return"focustrap"}activate(){this._isActive||(this._config.autofocus&&this._config.trapElement.focus(),ue.off(document,Gi),ue.on(document,Ji,(t=>this._handleFocusin(t))),ue.on(document,Zi,(t=>this._handleKeydown(t))),this._isActive=!0)}deactivate(){this._isActive&&(this._isActive=!1,ue.off(document,Gi))}_handleFocusin(t){const{trapElement:e}=this._config;if(t.target===document||t.target===e||e.contains(t.target))return;const i=ye.focusableChildren(e);0===i.length?e.focus():this._lastTabNavDirection===tn?i[i.length-1].focus():i[0].focus()}_handleKeydown(t){"Tab"===t.key&&(this._lastTabNavDirection=t.shiftKey?tn:"forward")}}const on=".fixed-top, .fixed-bottom, .is-fixed, .sticky-top",rn=".sticky-top",an="padding-right",ln="margin-right";class cn{constructor(){this._element=document.body}getWidth(){const t=document.documentElement.clientWidth;return Math.abs(window.innerWidth-t)}hide(){const t=this.getWidth();this._disableOverFlow(),this._setElementAttributes(this._element,an,(e=>e+t)),this._setElementAttributes(on,an,(e=>e+t)),this._setElementAttributes(rn,ln,(e=>e-t))}reset(){this._resetElementAttributes(this._element,"overflow"),this._resetElementAttributes(this._element,an),this._resetElementAttributes(on,an),this._resetElementAttributes(rn,ln)}isOverflowing(){return this.getWidth()>0}_disableOverFlow(){this._saveInitialAttribute(this._element,"overflow"),this._element.style.overflow="hidden"}_setElementAttributes(t,e,i){const n=this.getWidth();this._applyManipulationCallback(t,(t=>{if(t!==this._element&&window.innerWidth>t.clientWidth+n)return;this._saveInitialAttribute(t,e);const s=window.getComputedStyle(t).getPropertyValue(e);t.style.setProperty(e,`${i(Number.parseFloat(s))}px`)}))}_saveInitialAttribute(t,e){const i=t.style.getPropertyValue(e);i&&ge.setDataAttribute(t,e,i)}_resetElementAttributes(t,e){this._applyManipulationCallback(t,(t=>{const i=ge.getDataAttribute(t,e);null!==i?(ge.removeDataAttribute(t,e),t.style.setProperty(e,i)):t.style.removeProperty(e)}))}_applyManipulationCallback(t,e){if(jt(t))e(t);else for(const i of ye.find(t,this._element))e(i)}}const hn=".bs.modal",dn=`hide${hn}`,un=`hidePrevented${hn}`,fn=`hidden${hn}`,pn=`show${hn}`,mn=`shown${hn}`,gn=`resize${hn}`,_n=`click.dismiss${hn}`,bn=`mousedown.dismiss${hn}`,vn=`keydown.dismiss${hn}`,yn=`click${hn}.data-api`,wn="modal-open",En="show",An="modal-static",Tn={backdrop:!0,focus:!0,keyboard:!0},Cn={backdrop:"(boolean|string)",focus:"boolean",keyboard:"boolean"};class On extends be{constructor(t,e){super(t,e),this._dialog=ye.findOne(".modal-dialog",this._element),this._backdrop=this._initializeBackDrop(),this._focustrap=this._initializeFocusTrap(),this._isShown=!1,this._isTransitioning=!1,this._scrollBar=new cn,this._addEventListeners()}static get Default(){return Tn}static get DefaultType(){return Cn}static get NAME(){return"modal"}toggle(t){return this._isShown?this.hide():this.show(t)}show(t){this._isShown||this._isTransitioning||ue.trigger(this._element,pn,{relatedTarget:t}).defaultPrevented||(this._isShown=!0,this._isTransitioning=!0,this._scrollBar.hide(),document.body.classList.add(wn),this._adjustDialog(),this._backdrop.show((()=>this._showElement(t))))}hide(){this._isShown&&!this._isTransitioning&&(ue.trigger(this._element,dn).defaultPrevented||(this._isShown=!1,this._isTransitioning=!0,this._focustrap.deactivate(),this._element.classList.remove(En),this._queueCallback((()=>this._hideModal()),this._element,this._isAnimated())))}dispose(){ue.off(window,hn),ue.off(this._dialog,hn),this._backdrop.dispose(),this._focustrap.deactivate(),super.dispose()}handleUpdate(){this._adjustDialog()}_initializeBackDrop(){return new Ui({isVisible:Boolean(this._config.backdrop),isAnimated:this._isAnimated()})}_initializeFocusTrap(){return new sn({trapElement:this._element})}_showElement(t){document.body.contains(this._element)||document.body.append(this._element),this._element.style.display="block",this._element.removeAttribute("aria-hidden"),this._element.setAttribute("aria-modal",!0),this._element.setAttribute("role","dialog"),this._element.scrollTop=0;const e=ye.findOne(".modal-body",this._dialog);e&&(e.scrollTop=0),Rt(this._element),this._element.classList.add(En),this._queueCallback((()=>{this._config.focus&&this._focustrap.activate(),this._isTransitioning=!1,ue.trigger(this._element,mn,{relatedTarget:t})}),this._dialog,this._isAnimated())}_addEventListeners(){ue.on(this._element,vn,(t=>{"Escape"===t.key&&(this._config.keyboard?this.hide():this._triggerBackdropTransition())})),ue.on(window,gn,(()=>{this._isShown&&!this._isTransitioning&&this._adjustDialog()})),ue.on(this._element,bn,(t=>{ue.one(this._element,_n,(e=>{this._element===t.target&&this._element===e.target&&("static"!==this._config.backdrop?this._config.backdrop&&this.hide():this._triggerBackdropTransition())}))}))}_hideModal(){this._element.style.display="none",this._element.setAttribute("aria-hidden",!0),this._element.removeAttribute("aria-modal"),this._element.removeAttribute("role"),this._isTransitioning=!1,this._backdrop.hide((()=>{document.body.classList.remove(wn),this._resetAdjustments(),this._scrollBar.reset(),ue.trigger(this._element,fn)}))}_isAnimated(){return this._element.classList.contains("fade")}_triggerBackdropTransition(){if(ue.trigger(this._element,un).defaultPrevented)return;const t=this._element.scrollHeight>document.documentElement.clientHeight,e=this._element.style.overflowY;"hidden"===e||this._element.classList.contains(An)||(t||(this._element.style.overflowY="hidden"),this._element.classList.add(An),this._queueCallback((()=>{this._element.classList.remove(An),this._queueCallback((()=>{this._element.style.overflowY=e}),this._dialog)}),this._dialog),this._element.focus())}_adjustDialog(){const t=this._element.scrollHeight>document.documentElement.clientHeight,e=this._scrollBar.getWidth(),i=e>0;if(i&&!t){const t=Yt()?"paddingLeft":"paddingRight";this._element.style[t]=`${e}px`}if(!i&&t){const t=Yt()?"paddingRight":"paddingLeft";this._element.style[t]=`${e}px`}}_resetAdjustments(){this._element.style.paddingLeft="",this._element.style.paddingRight=""}static jQueryInterface(t,e){return this.each((function(){const i=On.getOrCreateInstance(this,t);if("string"==typeof t){if(void 0===i[t])throw new TypeError(`No method named "${t}"`);i[t](e)}}))}}ue.on(document,yn,'[data-bs-toggle="modal"]',(function(t){const e=ye.getElementFromSelector(this);["A","AREA"].includes(this.tagName)&&t.preventDefault(),ue.one(e,pn,(t=>{t.defaultPrevented||ue.one(e,fn,(()=>{Ht(this)&&this.focus()}))}));const i=ye.findOne(".modal.show");i&&On.getInstance(i).hide(),On.getOrCreateInstance(e).toggle(this)})),we(On),Kt(On);const xn=".bs.offcanvas",kn=".data-api",Ln=`load${xn}${kn}`,Sn="show",Dn="showing",$n="hiding",In=".offcanvas.show",Nn=`show${xn}`,Pn=`shown${xn}`,Mn=`hide${xn}`,jn=`hidePrevented${xn}`,Fn=`hidden${xn}`,Hn=`resize${xn}`,Bn=`click${xn}${kn}`,Wn=`keydown.dismiss${xn}`,zn={backdrop:!0,keyboard:!0,scroll:!1},Rn={backdrop:"(boolean|string)",keyboard:"boolean",scroll:"boolean"};class qn extends be{constructor(t,e){super(t,e),this._isShown=!1,this._backdrop=this._initializeBackDrop(),this._focustrap=this._initializeFocusTrap(),this._addEventListeners()}static get Default(){return zn}static get DefaultType(){return Rn}static get NAME(){return"offcanvas"}toggle(t){return this._isShown?this.hide():this.show(t)}show(t){this._isShown||ue.trigger(this._element,Nn,{relatedTarget:t}).defaultPrevented||(this._isShown=!0,this._backdrop.show(),this._config.scroll||(new cn).hide(),this._element.setAttribute("aria-modal",!0),this._element.setAttribute("role","dialog"),this._element.classList.add(Dn),this._queueCallback((()=>{this._config.scroll&&!this._config.backdrop||this._focustrap.activate(),this._element.classList.add(Sn),this._element.classList.remove(Dn),ue.trigger(this._element,Pn,{relatedTarget:t})}),this._element,!0))}hide(){this._isShown&&(ue.trigger(this._element,Mn).defaultPrevented||(this._focustrap.deactivate(),this._element.blur(),this._isShown=!1,this._element.classList.add($n),this._backdrop.hide(),this._queueCallback((()=>{this._element.classList.remove(Sn,$n),this._element.removeAttribute("aria-modal"),this._element.removeAttribute("role"),this._config.scroll||(new cn).reset(),ue.trigger(this._element,Fn)}),this._element,!0)))}dispose(){this._backdrop.dispose(),this._focustrap.deactivate(),super.dispose()}_initializeBackDrop(){const t=Boolean(this._config.backdrop);return new Ui({className:"offcanvas-backdrop",isVisible:t,isAnimated:!0,rootElement:this._element.parentNode,clickCallback:t?()=>{"static"!==this._config.backdrop?this.hide():ue.trigger(this._element,jn)}:null})}_initializeFocusTrap(){return new sn({trapElement:this._element})}_addEventListeners(){ue.on(this._element,Wn,(t=>{"Escape"===t.key&&(this._config.keyboard?this.hide():ue.trigger(this._element,jn))}))}static jQueryInterface(t){return this.each((function(){const e=qn.getOrCreateInstance(this,t);if("string"==typeof t){if(void 0===e[t]||t.startsWith("_")||"constructor"===t)throw new TypeError(`No method named "${t}"`);e[t](this)}}))}}ue.on(document,Bn,'[data-bs-toggle="offcanvas"]',(function(t){const e=ye.getElementFromSelector(this);if(["A","AREA"].includes(this.tagName)&&t.preventDefault(),Bt(this))return;ue.one(e,Fn,(()=>{Ht(this)&&this.focus()}));const i=ye.findOne(In);i&&i!==e&&qn.getInstance(i).hide(),qn.getOrCreateInstance(e).toggle(this)})),ue.on(window,Ln,(()=>{for(const t of ye.find(In))qn.getOrCreateInstance(t).show()})),ue.on(window,Hn,(()=>{for(const t of ye.find("[aria-modal][class*=show][class*=offcanvas-]"))"fixed"!==getComputedStyle(t).position&&qn.getOrCreateInstance(t).hide()})),we(qn),Kt(qn);const Vn={"*":["class","dir","id","lang","role",/^aria-[\w-]*$/i],a:["target","href","title","rel"],area:[],b:[],br:[],col:[],code:[],div:[],em:[],hr:[],h1:[],h2:[],h3:[],h4:[],h5:[],h6:[],i:[],img:["src","srcset","alt","title","width","height"],li:[],ol:[],p:[],pre:[],s:[],small:[],span:[],sub:[],sup:[],strong:[],u:[],ul:[]},Yn=new Set(["background","cite","href","itemtype","longdesc","poster","src","xlink:href"]),Kn=/^(?!javascript:)(?:[a-z0-9+.-]+:|[^&:/?#]*(?:[/?#]|$))/i,Qn=(t,e)=>{const i=t.nodeName.toLowerCase();return e.includes(i)?!Yn.has(i)||Boolean(Kn.test(t.nodeValue)):e.filter((t=>t instanceof RegExp)).some((t=>t.test(i)))},Xn={allowList:Vn,content:{},extraClass:"",html:!1,sanitize:!0,sanitizeFn:null,template:"
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")),e}_typeCheckConfig(t){super._typeCheckConfig(t),this._checkContent(t.content)}_checkContent(t){for(const[e,i]of Object.entries(t))super._typeCheckConfig({selector:e,entry:i},Gn)}_setContent(t,e,i){const n=ye.findOne(i,t);n&&((e=this._resolvePossibleFunction(e))?jt(e)?this._putElementInTemplate(Ft(e),n):this._config.html?n.innerHTML=this._maybeSanitize(e):n.textContent=e:n.remove())}_maybeSanitize(t){return this._config.sanitize?function(t,e,i){if(!t.length)return t;if(i&&"function"==typeof i)return i(t);const n=(new window.DOMParser).parseFromString(t,"text/html"),s=[].concat(...n.body.querySelectorAll("*"));for(const t of s){const i=t.nodeName.toLowerCase();if(!Object.keys(e).includes(i)){t.remove();continue}const n=[].concat(...t.attributes),s=[].concat(e["*"]||[],e[i]||[]);for(const e of n)Qn(e,s)||t.removeAttribute(e.nodeName)}return n.body.innerHTML}(t,this._config.allowList,this._config.sanitizeFn):t}_resolvePossibleFunction(t){return Qt(t,[this])}_putElementInTemplate(t,e){if(this._config.html)return e.innerHTML="",void e.append(t);e.textContent=t.textContent}}const Zn=new Set(["sanitize","allowList","sanitizeFn"]),ts="fade",es="show",is=".modal",ns="hide.bs.modal",ss="hover",os="focus",rs={AUTO:"auto",TOP:"top",RIGHT:Yt()?"left":"right",BOTTOM:"bottom",LEFT:Yt()?"right":"left"},as={allowList:Vn,animation:!0,boundary:"clippingParents",container:!1,customClass:"",delay:0,fallbackPlacements:["top","right","bottom","left"],html:!1,offset:[0,6],placement:"top",popperConfig:null,sanitize:!0,sanitizeFn:null,selector:!1,template:'',title:"",trigger:"hover focus"},ls={allowList:"object",animation:"boolean",boundary:"(string|element)",container:"(string|element|boolean)",customClass:"(string|function)",delay:"(number|object)",fallbackPlacements:"array",html:"boolean",offset:"(array|string|function)",placement:"(string|function)",popperConfig:"(null|object|function)",sanitize:"boolean",sanitizeFn:"(null|function)",selector:"(string|boolean)",template:"string",title:"(string|element|function)",trigger:"string"};class cs extends be{constructor(t,i){if(void 0===e)throw new TypeError("Bootstrap's tooltips require Popper (https://popper.js.org)");super(t,i),this._isEnabled=!0,this._timeout=0,this._isHovered=null,this._activeTrigger={},this._popper=null,this._templateFactory=null,this._newContent=null,this.tip=null,this._setListeners(),this._config.selector||this._fixTitle()}static get Default(){return as}static get DefaultType(){return ls}static get 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i=this._getTipElement();this._element.setAttribute("aria-describedby",i.getAttribute("id"));const{container:n}=this._config;if(this._element.ownerDocument.documentElement.contains(this.tip)||(n.append(i),ue.trigger(this._element,this.constructor.eventName("inserted"))),this._popper=this._createPopper(i),i.classList.add(es),"ontouchstart"in document.documentElement)for(const t of[].concat(...document.body.children))ue.on(t,"mouseover",zt);this._queueCallback((()=>{ue.trigger(this._element,this.constructor.eventName("shown")),!1===this._isHovered&&this._leave(),this._isHovered=!1}),this.tip,this._isAnimated())}hide(){if(this._isShown()&&!ue.trigger(this._element,this.constructor.eventName("hide")).defaultPrevented){if(this._getTipElement().classList.remove(es),"ontouchstart"in document.documentElement)for(const t of[].concat(...document.body.children))ue.off(t,"mouseover",zt);this._activeTrigger.click=!1,this._activeTrigger[os]=!1,this._activeTrigger[ss]=!1,this._isHovered=null,this._queueCallback((()=>{this._isWithActiveTrigger()||(this._isHovered||this._disposePopper(),this._element.removeAttribute("aria-describedby"),ue.trigger(this._element,this.constructor.eventName("hidden")))}),this.tip,this._isAnimated())}}update(){this._popper&&this._popper.update()}_isWithContent(){return Boolean(this._getTitle())}_getTipElement(){return this.tip||(this.tip=this._createTipElement(this._newContent||this._getContentForTemplate())),this.tip}_createTipElement(t){const e=this._getTemplateFactory(t).toHtml();if(!e)return null;e.classList.remove(ts,es),e.classList.add(`bs-${this.constructor.NAME}-auto`);const i=(t=>{do{t+=Math.floor(1e6*Math.random())}while(document.getElementById(t));return t})(this.constructor.NAME).toString();return e.setAttribute("id",i),this._isAnimated()&&e.classList.add(ts),e}setContent(t){this._newContent=t,this._isShown()&&(this._disposePopper(),this.show())}_getTemplateFactory(t){return this._templateFactory?this._templateFactory.changeContent(t):this._templateFactory=new Jn({...this._config,content:t,extraClass:this._resolvePossibleFunction(this._config.customClass)}),this._templateFactory}_getContentForTemplate(){return{".tooltip-inner":this._getTitle()}}_getTitle(){return this._resolvePossibleFunction(this._config.title)||this._element.getAttribute("data-bs-original-title")}_initializeOnDelegatedTarget(t){return this.constructor.getOrCreateInstance(t.delegateTarget,this._getDelegateConfig())}_isAnimated(){return this._config.animation||this.tip&&this.tip.classList.contains(ts)}_isShown(){return this.tip&&this.tip.classList.contains(es)}_createPopper(t){const e=Qt(this._config.placement,[this,t,this._element]),i=rs[e.toUpperCase()];return St(this._element,t,this._getPopperConfig(i))}_getOffset(){const{offset:t}=this._config;return"string"==typeof t?t.split(",").map((t=>Number.parseInt(t,10))):"function"==typeof t?e=>t(e,this._element):t}_resolvePossibleFunction(t){return Qt(t,[this._element])}_getPopperConfig(t){const e={placement:t,modifiers:[{name:"flip",options:{fallbackPlacements:this._config.fallbackPlacements}},{name:"offset",options:{offset:this._getOffset()}},{name:"preventOverflow",options:{boundary:this._config.boundary}},{name:"arrow",options:{element:`.${this.constructor.NAME}-arrow`}},{name:"preSetPlacement",enabled:!0,phase:"beforeMain",fn:t=>{this._getTipElement().setAttribute("data-popper-placement",t.state.placement)}}]};return{...e,...Qt(this._config.popperConfig,[e])}}_setListeners(){const t=this._config.trigger.split(" ");for(const e of t)if("click"===e)ue.on(this._element,this.constructor.eventName("click"),this._config.selector,(t=>{this._initializeOnDelegatedTarget(t).toggle()}));else if("manual"!==e){const t=e===ss?this.constructor.eventName("mouseenter"):this.constructor.eventName("focusin"),i=e===ss?this.constructor.eventName("mouseleave"):this.constructor.eventName("focusout");ue.on(this._element,t,this._config.selector,(t=>{const e=this._initializeOnDelegatedTarget(t);e._activeTrigger["focusin"===t.type?os:ss]=!0,e._enter()})),ue.on(this._element,i,this._config.selector,(t=>{const e=this._initializeOnDelegatedTarget(t);e._activeTrigger["focusout"===t.type?os:ss]=e._element.contains(t.relatedTarget),e._leave()}))}this._hideModalHandler=()=>{this._element&&this.hide()},ue.on(this._element.closest(is),ns,this._hideModalHandler)}_fixTitle(){const t=this._element.getAttribute("title");t&&(this._element.getAttribute("aria-label")||this._element.textContent.trim()||this._element.setAttribute("aria-label",t),this._element.setAttribute("data-bs-original-title",t),this._element.removeAttribute("title"))}_enter(){this._isShown()||this._isHovered?this._isHovered=!0:(this._isHovered=!0,this._setTimeout((()=>{this._isHovered&&this.show()}),this._config.delay.show))}_leave(){this._isWithActiveTrigger()||(this._isHovered=!1,this._setTimeout((()=>{this._isHovered||this.hide()}),this._config.delay.hide))}_setTimeout(t,e){clearTimeout(this._timeout),this._timeout=setTimeout(t,e)}_isWithActiveTrigger(){return Object.values(this._activeTrigger).includes(!0)}_getConfig(t){const e=ge.getDataAttributes(this._element);for(const t of Object.keys(e))Zn.has(t)&&delete e[t];return t={...e,..."object"==typeof t&&t?t:{}},t=this._mergeConfigObj(t),t=this._configAfterMerge(t),this._typeCheckConfig(t),t}_configAfterMerge(t){return t.container=!1===t.container?document.body:Ft(t.container),"number"==typeof t.delay&&(t.delay={show:t.delay,hide:t.delay}),"number"==typeof t.title&&(t.title=t.title.toString()),"number"==typeof t.content&&(t.content=t.content.toString()),t}_getDelegateConfig(){const t={};for(const[e,i]of Object.entries(this._config))this.constructor.Default[e]!==i&&(t[e]=i);return t.selector=!1,t.trigger="manual",t}_disposePopper(){this._popper&&(this._popper.destroy(),this._popper=null),this.tip&&(this.tip.remove(),this.tip=null)}static jQueryInterface(t){return this.each((function(){const e=cs.getOrCreateInstance(this,t);if("string"==typeof t){if(void 0===e[t])throw new TypeError(`No method named "${t}"`);e[t]()}}))}}Kt(cs);const hs={...cs.Default,content:"",offset:[0,8],placement:"right",template:'',trigger:"click"},ds={...cs.DefaultType,content:"(null|string|element|function)"};class us extends cs{static get Default(){return hs}static get DefaultType(){return ds}static get NAME(){return"popover"}_isWithContent(){return this._getTitle()||this._getContent()}_getContentForTemplate(){return{".popover-header":this._getTitle(),".popover-body":this._getContent()}}_getContent(){return this._resolvePossibleFunction(this._config.content)}static jQueryInterface(t){return this.each((function(){const e=us.getOrCreateInstance(this,t);if("string"==typeof t){if(void 0===e[t])throw new TypeError(`No method named "${t}"`);e[t]()}}))}}Kt(us);const fs=".bs.scrollspy",ps=`activate${fs}`,ms=`click${fs}`,gs=`load${fs}.data-api`,_s="active",bs="[href]",vs=".nav-link",ys=`${vs}, .nav-item > ${vs}, .list-group-item`,ws={offset:null,rootMargin:"0px 0px -25%",smoothScroll:!1,target:null,threshold:[.1,.5,1]},Es={offset:"(number|null)",rootMargin:"string",smoothScroll:"boolean",target:"element",threshold:"array"};class As extends be{constructor(t,e){super(t,e),this._targetLinks=new Map,this._observableSections=new 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e=this._observableSections.get(t.target.hash);if(e){t.preventDefault();const i=this._rootElement||window,n=e.offsetTop-this._element.offsetTop;if(i.scrollTo)return void i.scrollTo({top:n,behavior:"smooth"});i.scrollTop=n}})))}_getNewObserver(){const t={root:this._rootElement,threshold:this._config.threshold,rootMargin:this._config.rootMargin};return new IntersectionObserver((t=>this._observerCallback(t)),t)}_observerCallback(t){const e=t=>this._targetLinks.get(`#${t.target.id}`),i=t=>{this._previousScrollData.visibleEntryTop=t.target.offsetTop,this._process(e(t))},n=(this._rootElement||document.documentElement).scrollTop,s=n>=this._previousScrollData.parentScrollTop;this._previousScrollData.parentScrollTop=n;for(const o of t){if(!o.isIntersecting){this._activeTarget=null,this._clearActiveClass(e(o));continue}const t=o.target.offsetTop>=this._previousScrollData.visibleEntryTop;if(s&&t){if(i(o),!n)return}else s||t||i(o)}}_initializeTargetsAndObservables(){this._targetLinks=new Map,this._observableSections=new Map;const t=ye.find(bs,this._config.target);for(const e of t){if(!e.hash||Bt(e))continue;const t=ye.findOne(decodeURI(e.hash),this._element);Ht(t)&&(this._targetLinks.set(decodeURI(e.hash),e),this._observableSections.set(e.hash,t))}}_process(t){this._activeTarget!==t&&(this._clearActiveClass(this._config.target),this._activeTarget=t,t.classList.add(_s),this._activateParents(t),ue.trigger(this._element,ps,{relatedTarget:t}))}_activateParents(t){if(t.classList.contains("dropdown-item"))ye.findOne(".dropdown-toggle",t.closest(".dropdown")).classList.add(_s);else for(const e of ye.parents(t,".nav, .list-group"))for(const t of ye.prev(e,ys))t.classList.add(_s)}_clearActiveClass(t){t.classList.remove(_s);const e=ye.find(`${bs}.${_s}`,t);for(const t of e)t.classList.remove(_s)}static jQueryInterface(t){return this.each((function(){const e=As.getOrCreateInstance(this,t);if("string"==typeof t){if(void 0===e[t]||t.startsWith("_")||"constructor"===t)throw new TypeError(`No method named "${t}"`);e[t]()}}))}}ue.on(window,gs,(()=>{for(const t of ye.find('[data-bs-spy="scroll"]'))As.getOrCreateInstance(t)})),Kt(As);const Ts=".bs.tab",Cs=`hide${Ts}`,Os=`hidden${Ts}`,xs=`show${Ts}`,ks=`shown${Ts}`,Ls=`click${Ts}`,Ss=`keydown${Ts}`,Ds=`load${Ts}`,$s="ArrowLeft",Is="ArrowRight",Ns="ArrowUp",Ps="ArrowDown",Ms="Home",js="End",Fs="active",Hs="fade",Bs="show",Ws=".dropdown-toggle",zs=`:not(${Ws})`,Rs='[data-bs-toggle="tab"], [data-bs-toggle="pill"], [data-bs-toggle="list"]',qs=`.nav-link${zs}, .list-group-item${zs}, [role="tab"]${zs}, ${Rs}`,Vs=`.${Fs}[data-bs-toggle="tab"], .${Fs}[data-bs-toggle="pill"], .${Fs}[data-bs-toggle="list"]`;class Ys extends be{constructor(t){super(t),this._parent=this._element.closest('.list-group, .nav, [role="tablist"]'),this._parent&&(this._setInitialAttributes(this._parent,this._getChildren()),ue.on(this._element,Ss,(t=>this._keydown(t))))}static get NAME(){return"tab"}show(){const t=this._element;if(this._elemIsActive(t))return;const e=this._getActiveElem(),i=e?ue.trigger(e,Cs,{relatedTarget:t}):null;ue.trigger(t,xs,{relatedTarget:e}).defaultPrevented||i&&i.defaultPrevented||(this._deactivate(e,t),this._activate(t,e))}_activate(t,e){t&&(t.classList.add(Fs),this._activate(ye.getElementFromSelector(t)),this._queueCallback((()=>{"tab"===t.getAttribute("role")?(t.removeAttribute("tabindex"),t.setAttribute("aria-selected",!0),this._toggleDropDown(t,!0),ue.trigger(t,ks,{relatedTarget:e})):t.classList.add(Bs)}),t,t.classList.contains(Hs)))}_deactivate(t,e){t&&(t.classList.remove(Fs),t.blur(),this._deactivate(ye.getElementFromSelector(t)),this._queueCallback((()=>{"tab"===t.getAttribute("role")?(t.setAttribute("aria-selected",!1),t.setAttribute("tabindex","-1"),this._toggleDropDown(t,!1),ue.trigger(t,Os,{relatedTarget:e})):t.classList.remove(Bs)}),t,t.classList.contains(Hs)))}_keydown(t){if(![$s,Is,Ns,Ps,Ms,js].includes(t.key))return;t.stopPropagation(),t.preventDefault();const e=this._getChildren().filter((t=>!Bt(t)));let i;if([Ms,js].includes(t.key))i=e[t.key===Ms?0:e.length-1];else{const n=[Is,Ps].includes(t.key);i=Ut(e,t.target,n,!0)}i&&(i.focus({preventScroll:!0}),Ys.getOrCreateInstance(i).show())}_getChildren(){return ye.find(qs,this._parent)}_getActiveElem(){return this._getChildren().find((t=>this._elemIsActive(t)))||null}_setInitialAttributes(t,e){this._setAttributeIfNotExists(t,"role","tablist");for(const t of e)this._setInitialAttributesOnChild(t)}_setInitialAttributesOnChild(t){t=this._getInnerElement(t);const e=this._elemIsActive(t),i=this._getOuterElement(t);t.setAttribute("aria-selected",e),i!==t&&this._setAttributeIfNotExists(i,"role","presentation"),e||t.setAttribute("tabindex","-1"),this._setAttributeIfNotExists(t,"role","tab"),this._setInitialAttributesOnTargetPanel(t)}_setInitialAttributesOnTargetPanel(t){const e=ye.getElementFromSelector(t);e&&(this._setAttributeIfNotExists(e,"role","tabpanel"),t.id&&this._setAttributeIfNotExists(e,"aria-labelledby",`${t.id}`))}_toggleDropDown(t,e){const i=this._getOuterElement(t);if(!i.classList.contains("dropdown"))return;const n=(t,n)=>{const s=ye.findOne(t,i);s&&s.classList.toggle(n,e)};n(Ws,Fs),n(".dropdown-menu",Bs),i.setAttribute("aria-expanded",e)}_setAttributeIfNotExists(t,e,i){t.hasAttribute(e)||t.setAttribute(e,i)}_elemIsActive(t){return t.classList.contains(Fs)}_getInnerElement(t){return t.matches(qs)?t:ye.findOne(qs,t)}_getOuterElement(t){return t.closest(".nav-item, .list-group-item")||t}static jQueryInterface(t){return this.each((function(){const e=Ys.getOrCreateInstance(this);if("string"==typeof t){if(void 0===e[t]||t.startsWith("_")||"constructor"===t)throw new TypeError(`No method named "${t}"`);e[t]()}}))}}ue.on(document,Ls,Rs,(function(t){["A","AREA"].includes(this.tagName)&&t.preventDefault(),Bt(this)||Ys.getOrCreateInstance(this).show()})),ue.on(window,Ds,(()=>{for(const t of ye.find(Vs))Ys.getOrCreateInstance(t)})),Kt(Ys);const Ks=".bs.toast",Qs=`mouseover${Ks}`,Xs=`mouseout${Ks}`,Us=`focusin${Ks}`,Gs=`focusout${Ks}`,Js=`hide${Ks}`,Zs=`hidden${Ks}`,to=`show${Ks}`,eo=`shown${Ks}`,io="hide",no="show",so="showing",oo={animation:"boolean",autohide:"boolean",delay:"number"},ro={animation:!0,autohide:!0,delay:5e3};class ao extends be{constructor(t,e){super(t,e),this._timeout=null,this._hasMouseInteraction=!1,this._hasKeyboardInteraction=!1,this._setListeners()}static get Default(){return ro}static get DefaultType(){return oo}static get NAME(){return"toast"}show(){ue.trigger(this._element,to).defaultPrevented||(this._clearTimeout(),this._config.animation&&this._element.classList.add("fade"),this._element.classList.remove(io),Rt(this._element),this._element.classList.add(no,so),this._queueCallback((()=>{this._element.classList.remove(so),ue.trigger(this._element,eo),this._maybeScheduleHide()}),this._element,this._config.animation))}hide(){this.isShown()&&(ue.trigger(this._element,Js).defaultPrevented||(this._element.classList.add(so),this._queueCallback((()=>{this._element.classList.add(io),this._element.classList.remove(so,no),ue.trigger(this._element,Zs)}),this._element,this._config.animation)))}dispose(){this._clearTimeout(),this.isShown()&&this._element.classList.remove(no),super.dispose()}isShown(){return 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(element.nodeName || '').toLowerCase() : null;\n}","export default function getWindow(node) {\n if (node == null) {\n return window;\n }\n\n if (node.toString() !== '[object Window]') {\n var ownerDocument = node.ownerDocument;\n return ownerDocument ? ownerDocument.defaultView || window : window;\n }\n\n return node;\n}","import getWindow from \"./getWindow.js\";\n\nfunction isElement(node) {\n var OwnElement = getWindow(node).Element;\n return node instanceof OwnElement || node instanceof Element;\n}\n\nfunction isHTMLElement(node) {\n var OwnElement = getWindow(node).HTMLElement;\n return node instanceof OwnElement || node instanceof HTMLElement;\n}\n\nfunction isShadowRoot(node) {\n // IE 11 has no ShadowRoot\n if (typeof ShadowRoot === 'undefined') {\n return false;\n }\n\n var OwnElement = getWindow(node).ShadowRoot;\n return node instanceof OwnElement || node instanceof ShadowRoot;\n}\n\nexport { isElement, isHTMLElement, isShadowRoot };","import getNodeName from \"../dom-utils/getNodeName.js\";\nimport { isHTMLElement } from \"../dom-utils/instanceOf.js\"; // This modifier takes the styles prepared by the `computeStyles` modifier\n// and applies them to the HTMLElements such as popper and arrow\n\nfunction applyStyles(_ref) {\n var state = _ref.state;\n Object.keys(state.elements).forEach(function (name) {\n var style = state.styles[name] || {};\n var attributes = state.attributes[name] || {};\n var element = state.elements[name]; // arrow is optional + virtual elements\n\n if (!isHTMLElement(element) || !getNodeName(element)) {\n return;\n } // Flow doesn't support to extend this property, but it's the most\n // effective way to apply styles to an HTMLElement\n // $FlowFixMe[cannot-write]\n\n\n Object.assign(element.style, style);\n Object.keys(attributes).forEach(function (name) {\n var value = attributes[name];\n\n if (value === false) {\n element.removeAttribute(name);\n } else {\n element.setAttribute(name, value === true ? '' : value);\n }\n });\n });\n}\n\nfunction effect(_ref2) {\n var state = _ref2.state;\n var initialStyles = {\n popper: {\n position: state.options.strategy,\n left: '0',\n top: '0',\n margin: '0'\n },\n arrow: {\n position: 'absolute'\n },\n reference: {}\n };\n Object.assign(state.elements.popper.style, initialStyles.popper);\n state.styles = initialStyles;\n\n if (state.elements.arrow) {\n Object.assign(state.elements.arrow.style, initialStyles.arrow);\n }\n\n return function () {\n Object.keys(state.elements).forEach(function (name) {\n var element = state.elements[name];\n var attributes = state.attributes[name] || {};\n var styleProperties = Object.keys(state.styles.hasOwnProperty(name) ? state.styles[name] : initialStyles[name]); // Set all values to an empty string to unset them\n\n var style = styleProperties.reduce(function (style, property) {\n style[property] = '';\n return style;\n }, {}); // arrow is optional + virtual elements\n\n if (!isHTMLElement(element) || !getNodeName(element)) {\n return;\n }\n\n Object.assign(element.style, style);\n Object.keys(attributes).forEach(function (attribute) {\n element.removeAttribute(attribute);\n });\n });\n };\n} // eslint-disable-next-line import/no-unused-modules\n\n\nexport default {\n name: 'applyStyles',\n enabled: true,\n phase: 'write',\n fn: applyStyles,\n effect: effect,\n requires: ['computeStyles']\n};","import { auto } from \"../enums.js\";\nexport default function getBasePlacement(placement) {\n return placement.split('-')[0];\n}","export var max = Math.max;\nexport var min = Math.min;\nexport var round = Math.round;","export default function getUAString() {\n var uaData = navigator.userAgentData;\n\n if (uaData != null && uaData.brands && Array.isArray(uaData.brands)) {\n return uaData.brands.map(function (item) {\n return item.brand + \"/\" + item.version;\n }).join(' ');\n }\n\n return navigator.userAgent;\n}","import getUAString from \"../utils/userAgent.js\";\nexport default function isLayoutViewport() {\n return !/^((?!chrome|android).)*safari/i.test(getUAString());\n}","import { isElement, isHTMLElement } from \"./instanceOf.js\";\nimport { round } from \"../utils/math.js\";\nimport getWindow from \"./getWindow.js\";\nimport isLayoutViewport from \"./isLayoutViewport.js\";\nexport default function getBoundingClientRect(element, includeScale, isFixedStrategy) {\n if (includeScale === void 0) {\n includeScale = false;\n }\n\n if (isFixedStrategy === void 0) {\n isFixedStrategy = false;\n }\n\n var clientRect = element.getBoundingClientRect();\n var scaleX = 1;\n var scaleY = 1;\n\n if (includeScale && isHTMLElement(element)) {\n scaleX = element.offsetWidth > 0 ? round(clientRect.width) / element.offsetWidth || 1 : 1;\n scaleY = element.offsetHeight > 0 ? round(clientRect.height) / element.offsetHeight || 1 : 1;\n }\n\n var _ref = isElement(element) ? getWindow(element) : window,\n visualViewport = _ref.visualViewport;\n\n var addVisualOffsets = !isLayoutViewport() && isFixedStrategy;\n var x = (clientRect.left + (addVisualOffsets && visualViewport ? visualViewport.offsetLeft : 0)) / scaleX;\n var y = (clientRect.top + (addVisualOffsets && visualViewport ? visualViewport.offsetTop : 0)) / scaleY;\n var width = clientRect.width / scaleX;\n var height = clientRect.height / scaleY;\n return {\n width: width,\n height: height,\n top: y,\n right: x + width,\n bottom: y + height,\n left: x,\n x: x,\n y: y\n };\n}","import getBoundingClientRect from \"./getBoundingClientRect.js\"; // Returns the layout rect of an element relative to its offsetParent. Layout\n// means it doesn't take into account transforms.\n\nexport default function getLayoutRect(element) {\n var clientRect = getBoundingClientRect(element); // Use the clientRect sizes if it's not been transformed.\n // Fixes https://github.com/popperjs/popper-core/issues/1223\n\n var width = element.offsetWidth;\n var height = element.offsetHeight;\n\n if (Math.abs(clientRect.width - width) <= 1) {\n width = clientRect.width;\n }\n\n if (Math.abs(clientRect.height - height) <= 1) {\n height = clientRect.height;\n }\n\n return {\n x: element.offsetLeft,\n y: element.offsetTop,\n width: width,\n height: height\n };\n}","import { isShadowRoot } from \"./instanceOf.js\";\nexport default function contains(parent, child) {\n var rootNode = child.getRootNode && child.getRootNode(); // First, attempt with faster native method\n\n if (parent.contains(child)) {\n return true;\n } // then fallback to custom implementation with Shadow DOM support\n else if (rootNode && isShadowRoot(rootNode)) {\n var next = child;\n\n do {\n if (next && parent.isSameNode(next)) {\n return true;\n } // $FlowFixMe[prop-missing]: need a better way to handle this...\n\n\n next = next.parentNode || next.host;\n } while (next);\n } // Give up, the result is false\n\n\n return false;\n}","import getWindow from \"./getWindow.js\";\nexport default function getComputedStyle(element) {\n return getWindow(element).getComputedStyle(element);\n}","import getNodeName from \"./getNodeName.js\";\nexport default function isTableElement(element) {\n return ['table', 'td', 'th'].indexOf(getNodeName(element)) >= 0;\n}","import { isElement } from \"./instanceOf.js\";\nexport default function getDocumentElement(element) {\n // $FlowFixMe[incompatible-return]: assume body is always available\n return ((isElement(element) ? element.ownerDocument : // $FlowFixMe[prop-missing]\n element.document) || window.document).documentElement;\n}","import getNodeName from \"./getNodeName.js\";\nimport getDocumentElement from \"./getDocumentElement.js\";\nimport { isShadowRoot } from \"./instanceOf.js\";\nexport default function getParentNode(element) {\n if (getNodeName(element) === 'html') {\n return element;\n }\n\n return (// this is a quicker (but less type safe) way to save quite some bytes from the bundle\n // $FlowFixMe[incompatible-return]\n // $FlowFixMe[prop-missing]\n element.assignedSlot || // step into the shadow DOM of the parent of a slotted node\n element.parentNode || ( // DOM Element detected\n isShadowRoot(element) ? element.host : null) || // ShadowRoot detected\n // $FlowFixMe[incompatible-call]: HTMLElement is a Node\n getDocumentElement(element) // fallback\n\n );\n}","import getWindow from \"./getWindow.js\";\nimport getNodeName from \"./getNodeName.js\";\nimport getComputedStyle from \"./getComputedStyle.js\";\nimport { isHTMLElement, isShadowRoot } from \"./instanceOf.js\";\nimport isTableElement from \"./isTableElement.js\";\nimport getParentNode from \"./getParentNode.js\";\nimport getUAString from \"../utils/userAgent.js\";\n\nfunction getTrueOffsetParent(element) {\n if (!isHTMLElement(element) || // https://github.com/popperjs/popper-core/issues/837\n getComputedStyle(element).position === 'fixed') {\n return null;\n }\n\n return element.offsetParent;\n} // `.offsetParent` reports `null` for fixed elements, while absolute elements\n// return the containing block\n\n\nfunction getContainingBlock(element) {\n var isFirefox = /firefox/i.test(getUAString());\n var isIE = /Trident/i.test(getUAString());\n\n if (isIE && isHTMLElement(element)) {\n // In IE 9, 10 and 11 fixed elements containing block is always established by the viewport\n var elementCss = getComputedStyle(element);\n\n if (elementCss.position === 'fixed') {\n return null;\n }\n }\n\n var currentNode = getParentNode(element);\n\n if (isShadowRoot(currentNode)) {\n currentNode = currentNode.host;\n }\n\n while (isHTMLElement(currentNode) && ['html', 'body'].indexOf(getNodeName(currentNode)) < 0) {\n var css = getComputedStyle(currentNode); // This is non-exhaustive but covers the most common CSS properties that\n // create a containing block.\n // https://developer.mozilla.org/en-US/docs/Web/CSS/Containing_block#identifying_the_containing_block\n\n if (css.transform !== 'none' || css.perspective !== 'none' || css.contain === 'paint' || ['transform', 'perspective'].indexOf(css.willChange) !== -1 || isFirefox && css.willChange === 'filter' || isFirefox && css.filter && css.filter !== 'none') {\n return currentNode;\n } else {\n currentNode = currentNode.parentNode;\n }\n }\n\n return null;\n} // Gets the closest ancestor positioned element. Handles some edge cases,\n// such as table ancestors and cross browser bugs.\n\n\nexport default function getOffsetParent(element) {\n var window = getWindow(element);\n var offsetParent = getTrueOffsetParent(element);\n\n while (offsetParent && isTableElement(offsetParent) && getComputedStyle(offsetParent).position === 'static') {\n offsetParent = getTrueOffsetParent(offsetParent);\n }\n\n if (offsetParent && (getNodeName(offsetParent) === 'html' || getNodeName(offsetParent) === 'body' && getComputedStyle(offsetParent).position === 'static')) {\n return window;\n }\n\n return offsetParent || getContainingBlock(element) || window;\n}","export default function getMainAxisFromPlacement(placement) {\n return ['top', 'bottom'].indexOf(placement) >= 0 ? 'x' : 'y';\n}","import { max as mathMax, min as mathMin } from \"./math.js\";\nexport function within(min, value, max) {\n return mathMax(min, mathMin(value, max));\n}\nexport function withinMaxClamp(min, value, max) {\n var v = within(min, value, max);\n return v > max ? max : v;\n}","import getFreshSideObject from \"./getFreshSideObject.js\";\nexport default function mergePaddingObject(paddingObject) {\n return Object.assign({}, getFreshSideObject(), paddingObject);\n}","export default function getFreshSideObject() {\n return {\n top: 0,\n right: 0,\n bottom: 0,\n left: 0\n };\n}","export default function expandToHashMap(value, keys) {\n return keys.reduce(function (hashMap, key) {\n hashMap[key] = value;\n return hashMap;\n }, {});\n}","import getBasePlacement from \"../utils/getBasePlacement.js\";\nimport getLayoutRect from \"../dom-utils/getLayoutRect.js\";\nimport contains from \"../dom-utils/contains.js\";\nimport getOffsetParent from \"../dom-utils/getOffsetParent.js\";\nimport getMainAxisFromPlacement from \"../utils/getMainAxisFromPlacement.js\";\nimport { within } from \"../utils/within.js\";\nimport mergePaddingObject from \"../utils/mergePaddingObject.js\";\nimport expandToHashMap from \"../utils/expandToHashMap.js\";\nimport { left, right, basePlacements, top, bottom } from \"../enums.js\"; // eslint-disable-next-line import/no-unused-modules\n\nvar toPaddingObject = function toPaddingObject(padding, state) {\n padding = typeof padding === 'function' ? padding(Object.assign({}, state.rects, {\n placement: state.placement\n })) : padding;\n return mergePaddingObject(typeof padding !== 'number' ? padding : expandToHashMap(padding, basePlacements));\n};\n\nfunction arrow(_ref) {\n var _state$modifiersData$;\n\n var state = _ref.state,\n name = _ref.name,\n options = _ref.options;\n var arrowElement = state.elements.arrow;\n var popperOffsets = state.modifiersData.popperOffsets;\n var basePlacement = getBasePlacement(state.placement);\n var axis = getMainAxisFromPlacement(basePlacement);\n var isVertical = [left, right].indexOf(basePlacement) >= 0;\n var len = isVertical ? 'height' : 'width';\n\n if (!arrowElement || !popperOffsets) {\n return;\n }\n\n var paddingObject = toPaddingObject(options.padding, state);\n var arrowRect = getLayoutRect(arrowElement);\n var minProp = axis === 'y' ? top : left;\n var maxProp = axis === 'y' ? bottom : right;\n var endDiff = state.rects.reference[len] + state.rects.reference[axis] - popperOffsets[axis] - state.rects.popper[len];\n var startDiff = popperOffsets[axis] - state.rects.reference[axis];\n var arrowOffsetParent = getOffsetParent(arrowElement);\n var clientSize = arrowOffsetParent ? axis === 'y' ? arrowOffsetParent.clientHeight || 0 : arrowOffsetParent.clientWidth || 0 : 0;\n var centerToReference = endDiff / 2 - startDiff / 2; // Make sure the arrow doesn't overflow the popper if the center point is\n // outside of the popper bounds\n\n var min = paddingObject[minProp];\n var max = clientSize - arrowRect[len] - paddingObject[maxProp];\n var center = clientSize / 2 - arrowRect[len] / 2 + centerToReference;\n var offset = within(min, center, max); // Prevents breaking syntax highlighting...\n\n var axisProp = axis;\n state.modifiersData[name] = (_state$modifiersData$ = {}, _state$modifiersData$[axisProp] = offset, _state$modifiersData$.centerOffset = offset - center, _state$modifiersData$);\n}\n\nfunction effect(_ref2) {\n var state = _ref2.state,\n options = _ref2.options;\n var _options$element = options.element,\n arrowElement = _options$element === void 0 ? '[data-popper-arrow]' : _options$element;\n\n if (arrowElement == null) {\n return;\n } // CSS selector\n\n\n if (typeof arrowElement === 'string') {\n arrowElement = state.elements.popper.querySelector(arrowElement);\n\n if (!arrowElement) {\n return;\n }\n }\n\n if (!contains(state.elements.popper, arrowElement)) {\n return;\n }\n\n state.elements.arrow = arrowElement;\n} // eslint-disable-next-line import/no-unused-modules\n\n\nexport default {\n name: 'arrow',\n enabled: true,\n phase: 'main',\n fn: arrow,\n effect: effect,\n requires: ['popperOffsets'],\n requiresIfExists: ['preventOverflow']\n};","export default function getVariation(placement) {\n return placement.split('-')[1];\n}","import { top, left, right, bottom, end } from \"../enums.js\";\nimport getOffsetParent from \"../dom-utils/getOffsetParent.js\";\nimport getWindow from \"../dom-utils/getWindow.js\";\nimport getDocumentElement from \"../dom-utils/getDocumentElement.js\";\nimport getComputedStyle from \"../dom-utils/getComputedStyle.js\";\nimport getBasePlacement from \"../utils/getBasePlacement.js\";\nimport getVariation from \"../utils/getVariation.js\";\nimport { round } from \"../utils/math.js\"; // eslint-disable-next-line import/no-unused-modules\n\nvar unsetSides = {\n top: 'auto',\n right: 'auto',\n bottom: 'auto',\n left: 'auto'\n}; // Round the offsets to the nearest suitable subpixel based on the DPR.\n// Zooming can change the DPR, but it seems to report a value that will\n// cleanly divide the values into the appropriate subpixels.\n\nfunction roundOffsetsByDPR(_ref, win) {\n var x = _ref.x,\n y = _ref.y;\n var dpr = win.devicePixelRatio || 1;\n return {\n x: round(x * dpr) / dpr || 0,\n y: round(y * dpr) / dpr || 0\n };\n}\n\nexport function mapToStyles(_ref2) {\n var _Object$assign2;\n\n var popper = _ref2.popper,\n popperRect = _ref2.popperRect,\n placement = _ref2.placement,\n variation = _ref2.variation,\n offsets = _ref2.offsets,\n position = _ref2.position,\n gpuAcceleration = _ref2.gpuAcceleration,\n adaptive = _ref2.adaptive,\n roundOffsets = _ref2.roundOffsets,\n isFixed = _ref2.isFixed;\n var _offsets$x = offsets.x,\n x = _offsets$x === void 0 ? 0 : _offsets$x,\n _offsets$y = offsets.y,\n y = _offsets$y === void 0 ? 0 : _offsets$y;\n\n var _ref3 = typeof roundOffsets === 'function' ? roundOffsets({\n x: x,\n y: y\n }) : {\n x: x,\n y: y\n };\n\n x = _ref3.x;\n y = _ref3.y;\n var hasX = offsets.hasOwnProperty('x');\n var hasY = offsets.hasOwnProperty('y');\n var sideX = left;\n var sideY = top;\n var win = window;\n\n if (adaptive) {\n var offsetParent = getOffsetParent(popper);\n var heightProp = 'clientHeight';\n var widthProp = 'clientWidth';\n\n if (offsetParent === getWindow(popper)) {\n offsetParent = getDocumentElement(popper);\n\n if (getComputedStyle(offsetParent).position !== 'static' && position === 'absolute') {\n heightProp = 'scrollHeight';\n widthProp = 'scrollWidth';\n }\n } // $FlowFixMe[incompatible-cast]: force type refinement, we compare offsetParent with window above, but Flow doesn't detect it\n\n\n offsetParent = offsetParent;\n\n if (placement === top || (placement === left || placement === right) && variation === end) {\n sideY = bottom;\n var offsetY = isFixed && offsetParent === win && win.visualViewport ? win.visualViewport.height : // $FlowFixMe[prop-missing]\n offsetParent[heightProp];\n y -= offsetY - popperRect.height;\n y *= gpuAcceleration ? 1 : -1;\n }\n\n if (placement === left || (placement === top || placement === bottom) && variation === end) {\n sideX = right;\n var offsetX = isFixed && offsetParent === win && win.visualViewport ? win.visualViewport.width : // $FlowFixMe[prop-missing]\n offsetParent[widthProp];\n x -= offsetX - popperRect.width;\n x *= gpuAcceleration ? 1 : -1;\n }\n }\n\n var commonStyles = Object.assign({\n position: position\n }, adaptive && unsetSides);\n\n var _ref4 = roundOffsets === true ? roundOffsetsByDPR({\n x: x,\n y: y\n }, getWindow(popper)) : {\n x: x,\n y: y\n };\n\n x = _ref4.x;\n y = _ref4.y;\n\n if (gpuAcceleration) {\n var _Object$assign;\n\n return Object.assign({}, commonStyles, (_Object$assign = {}, _Object$assign[sideY] = hasY ? '0' : '', _Object$assign[sideX] = hasX ? '0' : '', _Object$assign.transform = (win.devicePixelRatio || 1) <= 1 ? \"translate(\" + x + \"px, \" + y + \"px)\" : \"translate3d(\" + x + \"px, \" + y + \"px, 0)\", _Object$assign));\n }\n\n return Object.assign({}, commonStyles, (_Object$assign2 = {}, _Object$assign2[sideY] = hasY ? y + \"px\" : '', _Object$assign2[sideX] = hasX ? x + \"px\" : '', _Object$assign2.transform = '', _Object$assign2));\n}\n\nfunction computeStyles(_ref5) {\n var state = _ref5.state,\n options = _ref5.options;\n var _options$gpuAccelerat = options.gpuAcceleration,\n gpuAcceleration = _options$gpuAccelerat === void 0 ? true : _options$gpuAccelerat,\n _options$adaptive = options.adaptive,\n adaptive = _options$adaptive === void 0 ? true : _options$adaptive,\n _options$roundOffsets = options.roundOffsets,\n roundOffsets = _options$roundOffsets === void 0 ? true : _options$roundOffsets;\n var commonStyles = {\n placement: getBasePlacement(state.placement),\n variation: getVariation(state.placement),\n popper: state.elements.popper,\n popperRect: state.rects.popper,\n gpuAcceleration: gpuAcceleration,\n isFixed: state.options.strategy === 'fixed'\n };\n\n if (state.modifiersData.popperOffsets != null) {\n state.styles.popper = Object.assign({}, state.styles.popper, mapToStyles(Object.assign({}, commonStyles, {\n offsets: state.modifiersData.popperOffsets,\n position: state.options.strategy,\n adaptive: adaptive,\n roundOffsets: roundOffsets\n })));\n }\n\n if (state.modifiersData.arrow != null) {\n state.styles.arrow = Object.assign({}, state.styles.arrow, mapToStyles(Object.assign({}, commonStyles, {\n offsets: state.modifiersData.arrow,\n position: 'absolute',\n adaptive: false,\n roundOffsets: roundOffsets\n })));\n }\n\n state.attributes.popper = Object.assign({}, state.attributes.popper, {\n 'data-popper-placement': state.placement\n });\n} // eslint-disable-next-line import/no-unused-modules\n\n\nexport default {\n name: 'computeStyles',\n enabled: true,\n phase: 'beforeWrite',\n fn: computeStyles,\n data: {}\n};","import getWindow from \"../dom-utils/getWindow.js\"; // eslint-disable-next-line import/no-unused-modules\n\nvar passive = {\n passive: true\n};\n\nfunction effect(_ref) {\n var state = _ref.state,\n instance = _ref.instance,\n options = _ref.options;\n var _options$scroll = options.scroll,\n scroll = _options$scroll === void 0 ? true : _options$scroll,\n _options$resize = options.resize,\n resize = _options$resize === void 0 ? true : _options$resize;\n var window = getWindow(state.elements.popper);\n var scrollParents = [].concat(state.scrollParents.reference, state.scrollParents.popper);\n\n if (scroll) {\n scrollParents.forEach(function (scrollParent) {\n scrollParent.addEventListener('scroll', instance.update, passive);\n });\n }\n\n if (resize) {\n window.addEventListener('resize', instance.update, passive);\n }\n\n return function () {\n if (scroll) {\n scrollParents.forEach(function (scrollParent) {\n scrollParent.removeEventListener('scroll', instance.update, passive);\n });\n }\n\n if (resize) {\n window.removeEventListener('resize', instance.update, passive);\n }\n };\n} // eslint-disable-next-line import/no-unused-modules\n\n\nexport default {\n name: 'eventListeners',\n enabled: true,\n phase: 'write',\n fn: function fn() {},\n effect: effect,\n data: {}\n};","var hash = {\n left: 'right',\n right: 'left',\n bottom: 'top',\n top: 'bottom'\n};\nexport default function getOppositePlacement(placement) {\n return placement.replace(/left|right|bottom|top/g, function (matched) {\n return hash[matched];\n });\n}","var hash = {\n start: 'end',\n end: 'start'\n};\nexport default function getOppositeVariationPlacement(placement) {\n return placement.replace(/start|end/g, function (matched) {\n return hash[matched];\n });\n}","import getWindow from \"./getWindow.js\";\nexport default function getWindowScroll(node) {\n var win = getWindow(node);\n var scrollLeft = win.pageXOffset;\n var scrollTop = win.pageYOffset;\n return {\n scrollLeft: scrollLeft,\n scrollTop: scrollTop\n };\n}","import getBoundingClientRect from \"./getBoundingClientRect.js\";\nimport getDocumentElement from \"./getDocumentElement.js\";\nimport getWindowScroll from \"./getWindowScroll.js\";\nexport default function getWindowScrollBarX(element) {\n // If has a CSS width greater than the viewport, then this will be\n // incorrect for RTL.\n // Popper 1 is broken in this case and never had a bug report so let's assume\n // it's not an issue. I don't think anyone ever specifies width on \n // anyway.\n // Browsers where the left scrollbar doesn't cause an issue report `0` for\n // this (e.g. Edge 2019, IE11, Safari)\n return getBoundingClientRect(getDocumentElement(element)).left + getWindowScroll(element).scrollLeft;\n}","import getComputedStyle from \"./getComputedStyle.js\";\nexport default function isScrollParent(element) {\n // Firefox wants us to check `-x` and `-y` variations as well\n var _getComputedStyle = getComputedStyle(element),\n overflow = _getComputedStyle.overflow,\n overflowX = _getComputedStyle.overflowX,\n overflowY = _getComputedStyle.overflowY;\n\n return /auto|scroll|overlay|hidden/.test(overflow + overflowY + overflowX);\n}","import getParentNode from \"./getParentNode.js\";\nimport isScrollParent from \"./isScrollParent.js\";\nimport getNodeName from \"./getNodeName.js\";\nimport { isHTMLElement } from \"./instanceOf.js\";\nexport default function getScrollParent(node) {\n if (['html', 'body', '#document'].indexOf(getNodeName(node)) >= 0) {\n // $FlowFixMe[incompatible-return]: assume body is always available\n return node.ownerDocument.body;\n }\n\n if (isHTMLElement(node) && isScrollParent(node)) {\n return node;\n }\n\n return getScrollParent(getParentNode(node));\n}","import getScrollParent from \"./getScrollParent.js\";\nimport getParentNode from \"./getParentNode.js\";\nimport getWindow from \"./getWindow.js\";\nimport isScrollParent from \"./isScrollParent.js\";\n/*\ngiven a DOM element, return the list of all scroll parents, up the list of ancesors\nuntil we get to the top window object. This list is what we attach scroll listeners\nto, because if any of these parent elements scroll, we'll need to re-calculate the\nreference element's position.\n*/\n\nexport default function listScrollParents(element, list) {\n var _element$ownerDocumen;\n\n if (list === void 0) {\n list = [];\n }\n\n var scrollParent = getScrollParent(element);\n var isBody = scrollParent === ((_element$ownerDocumen = element.ownerDocument) == null ? void 0 : _element$ownerDocumen.body);\n var win = getWindow(scrollParent);\n var target = isBody ? [win].concat(win.visualViewport || [], isScrollParent(scrollParent) ? scrollParent : []) : scrollParent;\n var updatedList = list.concat(target);\n return isBody ? updatedList : // $FlowFixMe[incompatible-call]: isBody tells us target will be an HTMLElement here\n updatedList.concat(listScrollParents(getParentNode(target)));\n}","export default function rectToClientRect(rect) {\n return Object.assign({}, rect, {\n left: rect.x,\n top: rect.y,\n right: rect.x + rect.width,\n bottom: rect.y + rect.height\n });\n}","import { viewport } from \"../enums.js\";\nimport getViewportRect from \"./getViewportRect.js\";\nimport getDocumentRect from \"./getDocumentRect.js\";\nimport listScrollParents from \"./listScrollParents.js\";\nimport getOffsetParent from \"./getOffsetParent.js\";\nimport getDocumentElement from \"./getDocumentElement.js\";\nimport getComputedStyle from \"./getComputedStyle.js\";\nimport { isElement, isHTMLElement } from \"./instanceOf.js\";\nimport getBoundingClientRect from \"./getBoundingClientRect.js\";\nimport getParentNode from \"./getParentNode.js\";\nimport contains from \"./contains.js\";\nimport getNodeName from \"./getNodeName.js\";\nimport rectToClientRect from \"../utils/rectToClientRect.js\";\nimport { max, min } from \"../utils/math.js\";\n\nfunction getInnerBoundingClientRect(element, strategy) {\n var rect = getBoundingClientRect(element, false, strategy === 'fixed');\n rect.top = rect.top + element.clientTop;\n rect.left = rect.left + element.clientLeft;\n rect.bottom = rect.top + element.clientHeight;\n rect.right = rect.left + element.clientWidth;\n rect.width = element.clientWidth;\n rect.height = element.clientHeight;\n rect.x = rect.left;\n rect.y = rect.top;\n return rect;\n}\n\nfunction getClientRectFromMixedType(element, clippingParent, strategy) {\n return clippingParent === viewport ? rectToClientRect(getViewportRect(element, strategy)) : isElement(clippingParent) ? getInnerBoundingClientRect(clippingParent, strategy) : rectToClientRect(getDocumentRect(getDocumentElement(element)));\n} // A \"clipping parent\" is an overflowable container with the characteristic of\n// clipping (or hiding) overflowing elements with a position different from\n// `initial`\n\n\nfunction getClippingParents(element) {\n var clippingParents = listScrollParents(getParentNode(element));\n var canEscapeClipping = ['absolute', 'fixed'].indexOf(getComputedStyle(element).position) >= 0;\n var clipperElement = canEscapeClipping && isHTMLElement(element) ? getOffsetParent(element) : element;\n\n if (!isElement(clipperElement)) {\n return [];\n } // $FlowFixMe[incompatible-return]: https://github.com/facebook/flow/issues/1414\n\n\n return clippingParents.filter(function (clippingParent) {\n return isElement(clippingParent) && contains(clippingParent, clipperElement) && getNodeName(clippingParent) !== 'body';\n });\n} // Gets the maximum area that the element is visible in due to any number of\n// clipping parents\n\n\nexport default function getClippingRect(element, boundary, rootBoundary, strategy) {\n var mainClippingParents = boundary === 'clippingParents' ? getClippingParents(element) : [].concat(boundary);\n var clippingParents = [].concat(mainClippingParents, [rootBoundary]);\n var firstClippingParent = clippingParents[0];\n var clippingRect = clippingParents.reduce(function (accRect, clippingParent) {\n var rect = getClientRectFromMixedType(element, clippingParent, strategy);\n accRect.top = max(rect.top, accRect.top);\n accRect.right = min(rect.right, accRect.right);\n accRect.bottom = min(rect.bottom, accRect.bottom);\n accRect.left = max(rect.left, accRect.left);\n return accRect;\n }, getClientRectFromMixedType(element, firstClippingParent, strategy));\n clippingRect.width = clippingRect.right - clippingRect.left;\n clippingRect.height = clippingRect.bottom - clippingRect.top;\n clippingRect.x = clippingRect.left;\n clippingRect.y = clippingRect.top;\n return clippingRect;\n}","import getWindow from \"./getWindow.js\";\nimport getDocumentElement from \"./getDocumentElement.js\";\nimport getWindowScrollBarX from \"./getWindowScrollBarX.js\";\nimport isLayoutViewport from \"./isLayoutViewport.js\";\nexport default function getViewportRect(element, strategy) {\n var win = getWindow(element);\n var html = getDocumentElement(element);\n var visualViewport = win.visualViewport;\n var width = html.clientWidth;\n var height = html.clientHeight;\n var x = 0;\n var y = 0;\n\n if (visualViewport) {\n width = visualViewport.width;\n height = visualViewport.height;\n var layoutViewport = isLayoutViewport();\n\n if (layoutViewport || !layoutViewport && strategy === 'fixed') {\n x = visualViewport.offsetLeft;\n y = visualViewport.offsetTop;\n }\n }\n\n return {\n width: width,\n height: height,\n x: x + getWindowScrollBarX(element),\n y: y\n };\n}","import getDocumentElement from \"./getDocumentElement.js\";\nimport getComputedStyle from \"./getComputedStyle.js\";\nimport getWindowScrollBarX from \"./getWindowScrollBarX.js\";\nimport getWindowScroll from \"./getWindowScroll.js\";\nimport { max } from \"../utils/math.js\"; // Gets the entire size of the scrollable document area, even extending outside\n// of the `` and `` rect bounds if horizontally scrollable\n\nexport default function getDocumentRect(element) {\n var _element$ownerDocumen;\n\n var html = getDocumentElement(element);\n var winScroll = getWindowScroll(element);\n var body = (_element$ownerDocumen = element.ownerDocument) == null ? void 0 : _element$ownerDocumen.body;\n var width = max(html.scrollWidth, html.clientWidth, body ? body.scrollWidth : 0, body ? body.clientWidth : 0);\n var height = max(html.scrollHeight, html.clientHeight, body ? body.scrollHeight : 0, body ? body.clientHeight : 0);\n var x = -winScroll.scrollLeft + getWindowScrollBarX(element);\n var y = -winScroll.scrollTop;\n\n if (getComputedStyle(body || html).direction === 'rtl') {\n x += max(html.clientWidth, body ? body.clientWidth : 0) - width;\n }\n\n return {\n width: width,\n height: height,\n x: x,\n y: y\n };\n}","import getBasePlacement from \"./getBasePlacement.js\";\nimport getVariation from \"./getVariation.js\";\nimport getMainAxisFromPlacement from \"./getMainAxisFromPlacement.js\";\nimport { top, right, bottom, left, start, end } from \"../enums.js\";\nexport default function computeOffsets(_ref) {\n var reference = _ref.reference,\n element = _ref.element,\n placement = _ref.placement;\n var basePlacement = placement ? getBasePlacement(placement) : null;\n var variation = placement ? getVariation(placement) : null;\n var commonX = reference.x + reference.width / 2 - element.width / 2;\n var commonY = reference.y + reference.height / 2 - element.height / 2;\n var offsets;\n\n switch (basePlacement) {\n case top:\n offsets = {\n x: commonX,\n y: reference.y - element.height\n };\n break;\n\n case bottom:\n offsets = {\n x: commonX,\n y: reference.y + reference.height\n };\n break;\n\n case right:\n offsets = {\n x: reference.x + reference.width,\n y: commonY\n };\n break;\n\n case left:\n offsets = {\n x: reference.x - element.width,\n y: commonY\n };\n break;\n\n default:\n offsets = {\n x: reference.x,\n y: reference.y\n };\n }\n\n var mainAxis = basePlacement ? getMainAxisFromPlacement(basePlacement) : null;\n\n if (mainAxis != null) {\n var len = mainAxis === 'y' ? 'height' : 'width';\n\n switch (variation) {\n case start:\n offsets[mainAxis] = offsets[mainAxis] - (reference[len] / 2 - element[len] / 2);\n break;\n\n case end:\n offsets[mainAxis] = offsets[mainAxis] + (reference[len] / 2 - element[len] / 2);\n break;\n\n default:\n }\n }\n\n return offsets;\n}","import getClippingRect from \"../dom-utils/getClippingRect.js\";\nimport getDocumentElement from \"../dom-utils/getDocumentElement.js\";\nimport getBoundingClientRect from \"../dom-utils/getBoundingClientRect.js\";\nimport computeOffsets from \"./computeOffsets.js\";\nimport rectToClientRect from \"./rectToClientRect.js\";\nimport { clippingParents, reference, popper, bottom, top, right, basePlacements, viewport } from \"../enums.js\";\nimport { isElement } from \"../dom-utils/instanceOf.js\";\nimport mergePaddingObject from \"./mergePaddingObject.js\";\nimport expandToHashMap from \"./expandToHashMap.js\"; // eslint-disable-next-line import/no-unused-modules\n\nexport default function detectOverflow(state, options) {\n if (options === void 0) {\n options = {};\n }\n\n var _options = options,\n _options$placement = _options.placement,\n placement = _options$placement === void 0 ? state.placement : _options$placement,\n _options$strategy = _options.strategy,\n strategy = _options$strategy === void 0 ? state.strategy : _options$strategy,\n _options$boundary = _options.boundary,\n boundary = _options$boundary === void 0 ? clippingParents : _options$boundary,\n _options$rootBoundary = _options.rootBoundary,\n rootBoundary = _options$rootBoundary === void 0 ? viewport : _options$rootBoundary,\n _options$elementConte = _options.elementContext,\n elementContext = _options$elementConte === void 0 ? popper : _options$elementConte,\n _options$altBoundary = _options.altBoundary,\n altBoundary = _options$altBoundary === void 0 ? false : _options$altBoundary,\n _options$padding = _options.padding,\n padding = _options$padding === void 0 ? 0 : _options$padding;\n var paddingObject = mergePaddingObject(typeof padding !== 'number' ? padding : expandToHashMap(padding, basePlacements));\n var altContext = elementContext === popper ? reference : popper;\n var popperRect = state.rects.popper;\n var element = state.elements[altBoundary ? altContext : elementContext];\n var clippingClientRect = getClippingRect(isElement(element) ? element : element.contextElement || getDocumentElement(state.elements.popper), boundary, rootBoundary, strategy);\n var referenceClientRect = getBoundingClientRect(state.elements.reference);\n var popperOffsets = computeOffsets({\n reference: referenceClientRect,\n element: popperRect,\n strategy: 'absolute',\n placement: placement\n });\n var popperClientRect = rectToClientRect(Object.assign({}, popperRect, popperOffsets));\n var elementClientRect = elementContext === popper ? popperClientRect : referenceClientRect; // positive = overflowing the clipping rect\n // 0 or negative = within the clipping rect\n\n var overflowOffsets = {\n top: clippingClientRect.top - elementClientRect.top + paddingObject.top,\n bottom: elementClientRect.bottom - clippingClientRect.bottom + paddingObject.bottom,\n left: clippingClientRect.left - elementClientRect.left + paddingObject.left,\n right: elementClientRect.right - clippingClientRect.right + paddingObject.right\n };\n var offsetData = state.modifiersData.offset; // Offsets can be applied only to the popper element\n\n if (elementContext === popper && offsetData) {\n var offset = offsetData[placement];\n Object.keys(overflowOffsets).forEach(function (key) {\n var multiply = [right, bottom].indexOf(key) >= 0 ? 1 : -1;\n var axis = [top, bottom].indexOf(key) >= 0 ? 'y' : 'x';\n overflowOffsets[key] += offset[axis] * multiply;\n });\n }\n\n return overflowOffsets;\n}","import getOppositePlacement from \"../utils/getOppositePlacement.js\";\nimport getBasePlacement from \"../utils/getBasePlacement.js\";\nimport getOppositeVariationPlacement from \"../utils/getOppositeVariationPlacement.js\";\nimport detectOverflow from \"../utils/detectOverflow.js\";\nimport computeAutoPlacement from \"../utils/computeAutoPlacement.js\";\nimport { bottom, top, start, right, left, auto } from \"../enums.js\";\nimport getVariation from \"../utils/getVariation.js\"; // eslint-disable-next-line import/no-unused-modules\n\nfunction getExpandedFallbackPlacements(placement) {\n if (getBasePlacement(placement) === auto) {\n return [];\n }\n\n var oppositePlacement = getOppositePlacement(placement);\n return [getOppositeVariationPlacement(placement), oppositePlacement, getOppositeVariationPlacement(oppositePlacement)];\n}\n\nfunction flip(_ref) {\n var state = _ref.state,\n options = _ref.options,\n name = _ref.name;\n\n if (state.modifiersData[name]._skip) {\n return;\n }\n\n var _options$mainAxis = options.mainAxis,\n checkMainAxis = _options$mainAxis === void 0 ? true : _options$mainAxis,\n _options$altAxis = options.altAxis,\n checkAltAxis = _options$altAxis === void 0 ? true : _options$altAxis,\n specifiedFallbackPlacements = options.fallbackPlacements,\n padding = options.padding,\n boundary = options.boundary,\n rootBoundary = options.rootBoundary,\n altBoundary = options.altBoundary,\n _options$flipVariatio = options.flipVariations,\n flipVariations = _options$flipVariatio === void 0 ? true : _options$flipVariatio,\n allowedAutoPlacements = options.allowedAutoPlacements;\n var preferredPlacement = state.options.placement;\n var basePlacement = getBasePlacement(preferredPlacement);\n var isBasePlacement = basePlacement === preferredPlacement;\n var fallbackPlacements = specifiedFallbackPlacements || (isBasePlacement || !flipVariations ? [getOppositePlacement(preferredPlacement)] : getExpandedFallbackPlacements(preferredPlacement));\n var placements = [preferredPlacement].concat(fallbackPlacements).reduce(function (acc, placement) {\n return acc.concat(getBasePlacement(placement) === auto ? computeAutoPlacement(state, {\n placement: placement,\n boundary: boundary,\n rootBoundary: rootBoundary,\n padding: padding,\n flipVariations: flipVariations,\n allowedAutoPlacements: allowedAutoPlacements\n }) : placement);\n }, []);\n var referenceRect = state.rects.reference;\n var popperRect = state.rects.popper;\n var checksMap = new Map();\n var makeFallbackChecks = true;\n var firstFittingPlacement = placements[0];\n\n for (var i = 0; i < placements.length; i++) {\n var placement = placements[i];\n\n var _basePlacement = getBasePlacement(placement);\n\n var isStartVariation = getVariation(placement) === start;\n var isVertical = [top, bottom].indexOf(_basePlacement) >= 0;\n var len = isVertical ? 'width' : 'height';\n var overflow = detectOverflow(state, {\n placement: placement,\n boundary: boundary,\n rootBoundary: rootBoundary,\n altBoundary: altBoundary,\n padding: padding\n });\n var mainVariationSide = isVertical ? isStartVariation ? right : left : isStartVariation ? bottom : top;\n\n if (referenceRect[len] > popperRect[len]) {\n mainVariationSide = getOppositePlacement(mainVariationSide);\n }\n\n var altVariationSide = getOppositePlacement(mainVariationSide);\n var checks = [];\n\n if (checkMainAxis) {\n checks.push(overflow[_basePlacement] <= 0);\n }\n\n if (checkAltAxis) {\n checks.push(overflow[mainVariationSide] <= 0, overflow[altVariationSide] <= 0);\n }\n\n if (checks.every(function (check) {\n return check;\n })) {\n firstFittingPlacement = placement;\n makeFallbackChecks = false;\n break;\n }\n\n checksMap.set(placement, checks);\n }\n\n if (makeFallbackChecks) {\n // `2` may be desired in some cases – research later\n var numberOfChecks = flipVariations ? 3 : 1;\n\n var _loop = function _loop(_i) {\n var fittingPlacement = placements.find(function (placement) {\n var checks = checksMap.get(placement);\n\n if (checks) {\n return checks.slice(0, _i).every(function (check) {\n return check;\n });\n }\n });\n\n if (fittingPlacement) {\n firstFittingPlacement = fittingPlacement;\n return \"break\";\n }\n };\n\n for (var _i = numberOfChecks; _i > 0; _i--) {\n var _ret = _loop(_i);\n\n if (_ret === \"break\") break;\n }\n }\n\n if (state.placement !== firstFittingPlacement) {\n state.modifiersData[name]._skip = true;\n state.placement = firstFittingPlacement;\n state.reset = true;\n }\n} // eslint-disable-next-line import/no-unused-modules\n\n\nexport default {\n name: 'flip',\n enabled: true,\n phase: 'main',\n fn: flip,\n requiresIfExists: ['offset'],\n data: {\n _skip: false\n }\n};","import getVariation from \"./getVariation.js\";\nimport { variationPlacements, basePlacements, placements as allPlacements } from \"../enums.js\";\nimport detectOverflow from \"./detectOverflow.js\";\nimport getBasePlacement from \"./getBasePlacement.js\";\nexport default function computeAutoPlacement(state, options) {\n if (options === void 0) {\n options = {};\n }\n\n var _options = options,\n placement = _options.placement,\n boundary = _options.boundary,\n rootBoundary = _options.rootBoundary,\n padding = _options.padding,\n flipVariations = _options.flipVariations,\n _options$allowedAutoP = _options.allowedAutoPlacements,\n allowedAutoPlacements = _options$allowedAutoP === void 0 ? allPlacements : _options$allowedAutoP;\n var variation = getVariation(placement);\n var placements = variation ? flipVariations ? variationPlacements : variationPlacements.filter(function (placement) {\n return getVariation(placement) === variation;\n }) : basePlacements;\n var allowedPlacements = placements.filter(function (placement) {\n return allowedAutoPlacements.indexOf(placement) >= 0;\n });\n\n if (allowedPlacements.length === 0) {\n allowedPlacements = placements;\n } // $FlowFixMe[incompatible-type]: Flow seems to have problems with two array unions...\n\n\n var overflows = allowedPlacements.reduce(function (acc, placement) {\n acc[placement] = detectOverflow(state, {\n placement: placement,\n boundary: boundary,\n rootBoundary: rootBoundary,\n padding: padding\n })[getBasePlacement(placement)];\n return acc;\n }, {});\n return Object.keys(overflows).sort(function (a, b) {\n return overflows[a] - overflows[b];\n });\n}","import { top, bottom, left, right } from \"../enums.js\";\nimport detectOverflow from \"../utils/detectOverflow.js\";\n\nfunction getSideOffsets(overflow, rect, preventedOffsets) {\n if (preventedOffsets === void 0) {\n preventedOffsets = {\n x: 0,\n y: 0\n };\n }\n\n return {\n top: overflow.top - rect.height - preventedOffsets.y,\n right: overflow.right - rect.width + preventedOffsets.x,\n bottom: overflow.bottom - rect.height + preventedOffsets.y,\n left: overflow.left - rect.width - preventedOffsets.x\n };\n}\n\nfunction isAnySideFullyClipped(overflow) {\n return [top, right, bottom, left].some(function (side) {\n return overflow[side] >= 0;\n });\n}\n\nfunction hide(_ref) {\n var state = _ref.state,\n name = _ref.name;\n var referenceRect = state.rects.reference;\n var popperRect = state.rects.popper;\n var preventedOffsets = state.modifiersData.preventOverflow;\n var referenceOverflow = detectOverflow(state, {\n elementContext: 'reference'\n });\n var popperAltOverflow = detectOverflow(state, {\n altBoundary: true\n });\n var referenceClippingOffsets = getSideOffsets(referenceOverflow, referenceRect);\n var popperEscapeOffsets = getSideOffsets(popperAltOverflow, popperRect, preventedOffsets);\n var isReferenceHidden = isAnySideFullyClipped(referenceClippingOffsets);\n var hasPopperEscaped = isAnySideFullyClipped(popperEscapeOffsets);\n state.modifiersData[name] = {\n referenceClippingOffsets: referenceClippingOffsets,\n popperEscapeOffsets: popperEscapeOffsets,\n isReferenceHidden: isReferenceHidden,\n hasPopperEscaped: hasPopperEscaped\n };\n state.attributes.popper = Object.assign({}, state.attributes.popper, {\n 'data-popper-reference-hidden': isReferenceHidden,\n 'data-popper-escaped': hasPopperEscaped\n });\n} // eslint-disable-next-line import/no-unused-modules\n\n\nexport default {\n name: 'hide',\n enabled: true,\n phase: 'main',\n requiresIfExists: ['preventOverflow'],\n fn: hide\n};","import getBasePlacement from \"../utils/getBasePlacement.js\";\nimport { top, left, right, placements } from \"../enums.js\"; // eslint-disable-next-line import/no-unused-modules\n\nexport function distanceAndSkiddingToXY(placement, rects, offset) {\n var basePlacement = getBasePlacement(placement);\n var invertDistance = [left, top].indexOf(basePlacement) >= 0 ? -1 : 1;\n\n var _ref = typeof offset === 'function' ? offset(Object.assign({}, rects, {\n placement: placement\n })) : offset,\n skidding = _ref[0],\n distance = _ref[1];\n\n skidding = skidding || 0;\n distance = (distance || 0) * invertDistance;\n return [left, right].indexOf(basePlacement) >= 0 ? {\n x: distance,\n y: skidding\n } : {\n x: skidding,\n y: distance\n };\n}\n\nfunction offset(_ref2) {\n var state = _ref2.state,\n options = _ref2.options,\n name = _ref2.name;\n var _options$offset = options.offset,\n offset = _options$offset === void 0 ? [0, 0] : _options$offset;\n var data = placements.reduce(function (acc, placement) {\n acc[placement] = distanceAndSkiddingToXY(placement, state.rects, offset);\n return acc;\n }, {});\n var _data$state$placement = data[state.placement],\n x = _data$state$placement.x,\n y = _data$state$placement.y;\n\n if (state.modifiersData.popperOffsets != null) {\n state.modifiersData.popperOffsets.x += x;\n state.modifiersData.popperOffsets.y += y;\n }\n\n state.modifiersData[name] = data;\n} // eslint-disable-next-line import/no-unused-modules\n\n\nexport default {\n name: 'offset',\n enabled: true,\n phase: 'main',\n requires: ['popperOffsets'],\n fn: offset\n};","import computeOffsets from \"../utils/computeOffsets.js\";\n\nfunction popperOffsets(_ref) {\n var state = _ref.state,\n name = _ref.name;\n // Offsets are the actual position the popper needs to have to be\n // properly positioned near its reference element\n // This is the most basic placement, and will be adjusted by\n // the modifiers in the next step\n state.modifiersData[name] = computeOffsets({\n reference: state.rects.reference,\n element: state.rects.popper,\n strategy: 'absolute',\n placement: state.placement\n });\n} // eslint-disable-next-line import/no-unused-modules\n\n\nexport default {\n name: 'popperOffsets',\n enabled: true,\n phase: 'read',\n fn: popperOffsets,\n data: {}\n};","import { top, left, right, bottom, start } from \"../enums.js\";\nimport getBasePlacement from \"../utils/getBasePlacement.js\";\nimport getMainAxisFromPlacement from \"../utils/getMainAxisFromPlacement.js\";\nimport getAltAxis from \"../utils/getAltAxis.js\";\nimport { within, withinMaxClamp } from \"../utils/within.js\";\nimport getLayoutRect from \"../dom-utils/getLayoutRect.js\";\nimport getOffsetParent from \"../dom-utils/getOffsetParent.js\";\nimport detectOverflow from \"../utils/detectOverflow.js\";\nimport getVariation from \"../utils/getVariation.js\";\nimport getFreshSideObject from \"../utils/getFreshSideObject.js\";\nimport { min as mathMin, max as mathMax } from \"../utils/math.js\";\n\nfunction preventOverflow(_ref) {\n var state = _ref.state,\n options = _ref.options,\n name = _ref.name;\n var _options$mainAxis = options.mainAxis,\n checkMainAxis = _options$mainAxis === void 0 ? true : _options$mainAxis,\n _options$altAxis = options.altAxis,\n checkAltAxis = _options$altAxis === void 0 ? false : _options$altAxis,\n boundary = options.boundary,\n rootBoundary = options.rootBoundary,\n altBoundary = options.altBoundary,\n padding = options.padding,\n _options$tether = options.tether,\n tether = _options$tether === void 0 ? true : _options$tether,\n _options$tetherOffset = options.tetherOffset,\n tetherOffset = _options$tetherOffset === void 0 ? 0 : _options$tetherOffset;\n var overflow = detectOverflow(state, {\n boundary: boundary,\n rootBoundary: rootBoundary,\n padding: padding,\n altBoundary: altBoundary\n });\n var basePlacement = getBasePlacement(state.placement);\n var variation = getVariation(state.placement);\n var isBasePlacement = !variation;\n var mainAxis = getMainAxisFromPlacement(basePlacement);\n var altAxis = getAltAxis(mainAxis);\n var popperOffsets = state.modifiersData.popperOffsets;\n var referenceRect = state.rects.reference;\n var popperRect = state.rects.popper;\n var tetherOffsetValue = typeof tetherOffset === 'function' ? tetherOffset(Object.assign({}, state.rects, {\n placement: state.placement\n })) : tetherOffset;\n var normalizedTetherOffsetValue = typeof tetherOffsetValue === 'number' ? {\n mainAxis: tetherOffsetValue,\n altAxis: tetherOffsetValue\n } : Object.assign({\n mainAxis: 0,\n altAxis: 0\n }, tetherOffsetValue);\n var offsetModifierState = state.modifiersData.offset ? state.modifiersData.offset[state.placement] : null;\n var data = {\n x: 0,\n y: 0\n };\n\n if (!popperOffsets) {\n return;\n }\n\n if (checkMainAxis) {\n var _offsetModifierState$;\n\n var mainSide = mainAxis === 'y' ? top : left;\n var altSide = mainAxis === 'y' ? bottom : right;\n var len = mainAxis === 'y' ? 'height' : 'width';\n var offset = popperOffsets[mainAxis];\n var min = offset + overflow[mainSide];\n var max = offset - overflow[altSide];\n var additive = tether ? -popperRect[len] / 2 : 0;\n var minLen = variation === start ? referenceRect[len] : popperRect[len];\n var maxLen = variation === start ? -popperRect[len] : -referenceRect[len]; // We need to include the arrow in the calculation so the arrow doesn't go\n // outside the reference bounds\n\n var arrowElement = state.elements.arrow;\n var arrowRect = tether && arrowElement ? getLayoutRect(arrowElement) : {\n width: 0,\n height: 0\n };\n var arrowPaddingObject = state.modifiersData['arrow#persistent'] ? state.modifiersData['arrow#persistent'].padding : getFreshSideObject();\n var arrowPaddingMin = arrowPaddingObject[mainSide];\n var arrowPaddingMax = arrowPaddingObject[altSide]; // If the reference length is smaller than the arrow length, we don't want\n // to include its full size in the calculation. If the reference is small\n // and near the edge of a boundary, the popper can overflow even if the\n // reference is not overflowing as well (e.g. virtual elements with no\n // width or height)\n\n var arrowLen = within(0, referenceRect[len], arrowRect[len]);\n var minOffset = isBasePlacement ? referenceRect[len] / 2 - additive - arrowLen - arrowPaddingMin - normalizedTetherOffsetValue.mainAxis : minLen - arrowLen - arrowPaddingMin - normalizedTetherOffsetValue.mainAxis;\n var maxOffset = isBasePlacement ? -referenceRect[len] / 2 + additive + arrowLen + arrowPaddingMax + normalizedTetherOffsetValue.mainAxis : maxLen + arrowLen + arrowPaddingMax + normalizedTetherOffsetValue.mainAxis;\n var arrowOffsetParent = state.elements.arrow && getOffsetParent(state.elements.arrow);\n var clientOffset = arrowOffsetParent ? mainAxis === 'y' ? arrowOffsetParent.clientTop || 0 : arrowOffsetParent.clientLeft || 0 : 0;\n var offsetModifierValue = (_offsetModifierState$ = offsetModifierState == null ? void 0 : offsetModifierState[mainAxis]) != null ? _offsetModifierState$ : 0;\n var tetherMin = offset + minOffset - offsetModifierValue - clientOffset;\n var tetherMax = offset + maxOffset - offsetModifierValue;\n var preventedOffset = within(tether ? mathMin(min, tetherMin) : min, offset, tether ? mathMax(max, tetherMax) : max);\n popperOffsets[mainAxis] = preventedOffset;\n data[mainAxis] = preventedOffset - offset;\n }\n\n if (checkAltAxis) {\n var _offsetModifierState$2;\n\n var _mainSide = mainAxis === 'x' ? top : left;\n\n var _altSide = mainAxis === 'x' ? bottom : right;\n\n var _offset = popperOffsets[altAxis];\n\n var _len = altAxis === 'y' ? 'height' : 'width';\n\n var _min = _offset + overflow[_mainSide];\n\n var _max = _offset - overflow[_altSide];\n\n var isOriginSide = [top, left].indexOf(basePlacement) !== -1;\n\n var _offsetModifierValue = (_offsetModifierState$2 = offsetModifierState == null ? void 0 : offsetModifierState[altAxis]) != null ? _offsetModifierState$2 : 0;\n\n var _tetherMin = isOriginSide ? _min : _offset - referenceRect[_len] - popperRect[_len] - _offsetModifierValue + normalizedTetherOffsetValue.altAxis;\n\n var _tetherMax = isOriginSide ? _offset + referenceRect[_len] + popperRect[_len] - _offsetModifierValue - normalizedTetherOffsetValue.altAxis : _max;\n\n var _preventedOffset = tether && isOriginSide ? withinMaxClamp(_tetherMin, _offset, _tetherMax) : within(tether ? _tetherMin : _min, _offset, tether ? _tetherMax : _max);\n\n popperOffsets[altAxis] = _preventedOffset;\n data[altAxis] = _preventedOffset - _offset;\n }\n\n state.modifiersData[name] = data;\n} // eslint-disable-next-line import/no-unused-modules\n\n\nexport default {\n name: 'preventOverflow',\n enabled: true,\n phase: 'main',\n fn: preventOverflow,\n requiresIfExists: ['offset']\n};","export default function getAltAxis(axis) {\n return axis === 'x' ? 'y' : 'x';\n}","import getBoundingClientRect from \"./getBoundingClientRect.js\";\nimport getNodeScroll from \"./getNodeScroll.js\";\nimport getNodeName from \"./getNodeName.js\";\nimport { isHTMLElement } from \"./instanceOf.js\";\nimport getWindowScrollBarX from \"./getWindowScrollBarX.js\";\nimport getDocumentElement from \"./getDocumentElement.js\";\nimport isScrollParent from \"./isScrollParent.js\";\nimport { round } from \"../utils/math.js\";\n\nfunction isElementScaled(element) {\n var rect = element.getBoundingClientRect();\n var scaleX = round(rect.width) / element.offsetWidth || 1;\n var scaleY = round(rect.height) / element.offsetHeight || 1;\n return scaleX !== 1 || scaleY !== 1;\n} // Returns the composite rect of an element relative to its offsetParent.\n// Composite means it takes into account transforms as well as layout.\n\n\nexport default function getCompositeRect(elementOrVirtualElement, offsetParent, isFixed) {\n if (isFixed === void 0) {\n isFixed = false;\n }\n\n var isOffsetParentAnElement = isHTMLElement(offsetParent);\n var offsetParentIsScaled = isHTMLElement(offsetParent) && isElementScaled(offsetParent);\n var documentElement = getDocumentElement(offsetParent);\n var rect = getBoundingClientRect(elementOrVirtualElement, offsetParentIsScaled, isFixed);\n var scroll = {\n scrollLeft: 0,\n scrollTop: 0\n };\n var offsets = {\n x: 0,\n y: 0\n };\n\n if (isOffsetParentAnElement || !isOffsetParentAnElement && !isFixed) {\n if (getNodeName(offsetParent) !== 'body' || // https://github.com/popperjs/popper-core/issues/1078\n isScrollParent(documentElement)) {\n scroll = getNodeScroll(offsetParent);\n }\n\n if (isHTMLElement(offsetParent)) {\n offsets = getBoundingClientRect(offsetParent, true);\n offsets.x += offsetParent.clientLeft;\n offsets.y += offsetParent.clientTop;\n } else if (documentElement) {\n offsets.x = getWindowScrollBarX(documentElement);\n }\n }\n\n return {\n x: rect.left + scroll.scrollLeft - offsets.x,\n y: rect.top + scroll.scrollTop - offsets.y,\n width: rect.width,\n height: rect.height\n };\n}","import getWindowScroll from \"./getWindowScroll.js\";\nimport getWindow from \"./getWindow.js\";\nimport { isHTMLElement } from \"./instanceOf.js\";\nimport getHTMLElementScroll from \"./getHTMLElementScroll.js\";\nexport default function getNodeScroll(node) {\n if (node === getWindow(node) || !isHTMLElement(node)) {\n return getWindowScroll(node);\n } else {\n return getHTMLElementScroll(node);\n }\n}","export default function getHTMLElementScroll(element) {\n return {\n scrollLeft: element.scrollLeft,\n scrollTop: element.scrollTop\n };\n}","import { modifierPhases } from \"../enums.js\"; // source: https://stackoverflow.com/questions/49875255\n\nfunction order(modifiers) {\n var map = new Map();\n var visited = new Set();\n var result = [];\n modifiers.forEach(function (modifier) {\n map.set(modifier.name, modifier);\n }); // On visiting object, check for its dependencies and visit them recursively\n\n function sort(modifier) {\n visited.add(modifier.name);\n var requires = [].concat(modifier.requires || [], modifier.requiresIfExists || []);\n requires.forEach(function (dep) {\n if (!visited.has(dep)) {\n var depModifier = map.get(dep);\n\n if (depModifier) {\n sort(depModifier);\n }\n }\n });\n result.push(modifier);\n }\n\n modifiers.forEach(function (modifier) {\n if (!visited.has(modifier.name)) {\n // check for visited object\n sort(modifier);\n }\n });\n return result;\n}\n\nexport default function orderModifiers(modifiers) {\n // order based on dependencies\n var orderedModifiers = order(modifiers); // order based on phase\n\n return modifierPhases.reduce(function (acc, phase) {\n return acc.concat(orderedModifiers.filter(function (modifier) {\n return modifier.phase === phase;\n }));\n }, []);\n}","import getCompositeRect from \"./dom-utils/getCompositeRect.js\";\nimport getLayoutRect from \"./dom-utils/getLayoutRect.js\";\nimport listScrollParents from \"./dom-utils/listScrollParents.js\";\nimport getOffsetParent from \"./dom-utils/getOffsetParent.js\";\nimport orderModifiers from \"./utils/orderModifiers.js\";\nimport debounce from \"./utils/debounce.js\";\nimport mergeByName from \"./utils/mergeByName.js\";\nimport detectOverflow from \"./utils/detectOverflow.js\";\nimport { isElement } from \"./dom-utils/instanceOf.js\";\nvar DEFAULT_OPTIONS = {\n placement: 'bottom',\n modifiers: [],\n strategy: 'absolute'\n};\n\nfunction areValidElements() {\n for (var _len = arguments.length, args = new Array(_len), _key = 0; _key < _len; _key++) {\n args[_key] = arguments[_key];\n }\n\n return !args.some(function (element) {\n return !(element && typeof element.getBoundingClientRect === 'function');\n });\n}\n\nexport function popperGenerator(generatorOptions) {\n if (generatorOptions === void 0) {\n generatorOptions = {};\n }\n\n var _generatorOptions = generatorOptions,\n _generatorOptions$def = _generatorOptions.defaultModifiers,\n defaultModifiers = _generatorOptions$def === void 0 ? [] : _generatorOptions$def,\n _generatorOptions$def2 = _generatorOptions.defaultOptions,\n defaultOptions = _generatorOptions$def2 === void 0 ? DEFAULT_OPTIONS : _generatorOptions$def2;\n return function createPopper(reference, popper, options) {\n if (options === void 0) {\n options = defaultOptions;\n }\n\n var state = {\n placement: 'bottom',\n orderedModifiers: [],\n options: Object.assign({}, DEFAULT_OPTIONS, defaultOptions),\n modifiersData: {},\n elements: {\n reference: reference,\n popper: popper\n },\n attributes: {},\n styles: {}\n };\n var effectCleanupFns = [];\n var isDestroyed = false;\n var instance = {\n state: state,\n setOptions: function setOptions(setOptionsAction) {\n var options = typeof setOptionsAction === 'function' ? setOptionsAction(state.options) : setOptionsAction;\n cleanupModifierEffects();\n state.options = Object.assign({}, defaultOptions, state.options, options);\n state.scrollParents = {\n reference: isElement(reference) ? listScrollParents(reference) : reference.contextElement ? listScrollParents(reference.contextElement) : [],\n popper: listScrollParents(popper)\n }; // Orders the modifiers based on their dependencies and `phase`\n // properties\n\n var orderedModifiers = orderModifiers(mergeByName([].concat(defaultModifiers, state.options.modifiers))); // Strip out disabled modifiers\n\n state.orderedModifiers = orderedModifiers.filter(function (m) {\n return m.enabled;\n });\n runModifierEffects();\n return instance.update();\n },\n // Sync update – it will always be executed, even if not necessary. This\n // is useful for low frequency updates where sync behavior simplifies the\n // logic.\n // For high frequency updates (e.g. `resize` and `scroll` events), always\n // prefer the async Popper#update method\n forceUpdate: function forceUpdate() {\n if (isDestroyed) {\n return;\n }\n\n var _state$elements = state.elements,\n reference = _state$elements.reference,\n popper = _state$elements.popper; // Don't proceed if `reference` or `popper` are not valid elements\n // anymore\n\n if (!areValidElements(reference, popper)) {\n return;\n } // Store the reference and popper rects to be read by modifiers\n\n\n state.rects = {\n reference: getCompositeRect(reference, getOffsetParent(popper), state.options.strategy === 'fixed'),\n popper: getLayoutRect(popper)\n }; // Modifiers have the ability to reset the current update cycle. The\n // most common use case for this is the `flip` modifier changing the\n // placement, which then needs to re-run all the modifiers, because the\n // logic was previously ran for the previous placement and is therefore\n // stale/incorrect\n\n state.reset = false;\n state.placement = state.options.placement; // On each update cycle, the `modifiersData` property for each modifier\n // is filled with the initial data specified by the modifier. This means\n // it doesn't persist and is fresh on each update.\n // To ensure persistent data, use `${name}#persistent`\n\n state.orderedModifiers.forEach(function (modifier) {\n return state.modifiersData[modifier.name] = Object.assign({}, modifier.data);\n });\n\n for (var index = 0; index < state.orderedModifiers.length; index++) {\n if (state.reset === true) {\n state.reset = false;\n index = -1;\n continue;\n }\n\n var _state$orderedModifie = state.orderedModifiers[index],\n fn = _state$orderedModifie.fn,\n _state$orderedModifie2 = _state$orderedModifie.options,\n _options = _state$orderedModifie2 === void 0 ? {} : _state$orderedModifie2,\n name = _state$orderedModifie.name;\n\n if (typeof fn === 'function') {\n state = fn({\n state: state,\n options: _options,\n name: name,\n instance: instance\n }) || state;\n }\n }\n },\n // Async and optimistically optimized update – it will not be executed if\n // not necessary (debounced to run at most once-per-tick)\n update: debounce(function () {\n return new Promise(function (resolve) {\n instance.forceUpdate();\n resolve(state);\n });\n }),\n destroy: function destroy() {\n cleanupModifierEffects();\n isDestroyed = true;\n }\n };\n\n if (!areValidElements(reference, popper)) {\n return instance;\n }\n\n instance.setOptions(options).then(function (state) {\n if (!isDestroyed && options.onFirstUpdate) {\n options.onFirstUpdate(state);\n }\n }); // Modifiers have the ability to execute arbitrary code before the first\n // update cycle runs. They will be executed in the same order as the update\n // cycle. This is useful when a modifier adds some persistent data that\n // other modifiers need to use, but the modifier is run after the dependent\n // one.\n\n function runModifierEffects() {\n state.orderedModifiers.forEach(function (_ref) {\n var name = _ref.name,\n _ref$options = _ref.options,\n options = _ref$options === void 0 ? {} : _ref$options,\n effect = _ref.effect;\n\n if (typeof effect === 'function') {\n var cleanupFn = effect({\n state: state,\n name: name,\n instance: instance,\n options: options\n });\n\n var noopFn = function noopFn() {};\n\n effectCleanupFns.push(cleanupFn || noopFn);\n }\n });\n }\n\n function cleanupModifierEffects() {\n effectCleanupFns.forEach(function (fn) {\n return fn();\n });\n effectCleanupFns = [];\n }\n\n return instance;\n };\n}\nexport var createPopper = /*#__PURE__*/popperGenerator(); // eslint-disable-next-line import/no-unused-modules\n\nexport { detectOverflow };","export default function debounce(fn) {\n var pending;\n return function () {\n if (!pending) {\n pending = new Promise(function (resolve) {\n Promise.resolve().then(function () {\n pending = undefined;\n resolve(fn());\n });\n });\n }\n\n return pending;\n };\n}","export default function mergeByName(modifiers) {\n var merged = modifiers.reduce(function (merged, current) {\n var existing = merged[current.name];\n merged[current.name] = existing ? Object.assign({}, existing, current, {\n options: Object.assign({}, existing.options, current.options),\n data: Object.assign({}, existing.data, current.data)\n }) : current;\n return merged;\n }, {}); // IE11 does not support Object.values\n\n return Object.keys(merged).map(function (key) {\n return merged[key];\n });\n}","import { popperGenerator, detectOverflow } from \"./createPopper.js\";\nimport eventListeners from \"./modifiers/eventListeners.js\";\nimport popperOffsets from \"./modifiers/popperOffsets.js\";\nimport computeStyles from \"./modifiers/computeStyles.js\";\nimport applyStyles from \"./modifiers/applyStyles.js\";\nimport offset from \"./modifiers/offset.js\";\nimport flip from \"./modifiers/flip.js\";\nimport preventOverflow from \"./modifiers/preventOverflow.js\";\nimport arrow from \"./modifiers/arrow.js\";\nimport hide from \"./modifiers/hide.js\";\nvar defaultModifiers = [eventListeners, popperOffsets, computeStyles, applyStyles, offset, flip, preventOverflow, arrow, hide];\nvar createPopper = /*#__PURE__*/popperGenerator({\n defaultModifiers: defaultModifiers\n}); // eslint-disable-next-line import/no-unused-modules\n\nexport { createPopper, popperGenerator, defaultModifiers, detectOverflow }; // eslint-disable-next-line import/no-unused-modules\n\nexport { createPopper as createPopperLite } from \"./popper-lite.js\"; // eslint-disable-next-line import/no-unused-modules\n\nexport * from \"./modifiers/index.js\";","import { popperGenerator, detectOverflow } from \"./createPopper.js\";\nimport eventListeners from \"./modifiers/eventListeners.js\";\nimport popperOffsets from \"./modifiers/popperOffsets.js\";\nimport computeStyles from \"./modifiers/computeStyles.js\";\nimport applyStyles from \"./modifiers/applyStyles.js\";\nvar defaultModifiers = [eventListeners, popperOffsets, computeStyles, applyStyles];\nvar createPopper = /*#__PURE__*/popperGenerator({\n defaultModifiers: defaultModifiers\n}); // eslint-disable-next-line import/no-unused-modules\n\nexport { createPopper, popperGenerator, defaultModifiers, detectOverflow };","/*!\n * Bootstrap v5.3.2 (https://getbootstrap.com/)\n * Copyright 2011-2023 The Bootstrap Authors (https://github.com/twbs/bootstrap/graphs/contributors)\n * Licensed under MIT (https://github.com/twbs/bootstrap/blob/main/LICENSE)\n */\nimport * as Popper from '@popperjs/core';\n\n/**\n * --------------------------------------------------------------------------\n * Bootstrap dom/data.js\n * Licensed under MIT (https://github.com/twbs/bootstrap/blob/main/LICENSE)\n * --------------------------------------------------------------------------\n */\n\n/**\n * Constants\n */\n\nconst elementMap = new Map();\nconst Data = {\n set(element, key, instance) {\n if (!elementMap.has(element)) {\n elementMap.set(element, new Map());\n }\n const instanceMap = elementMap.get(element);\n\n // make it clear we only want one instance per element\n // can be removed later when multiple key/instances are fine to be used\n if (!instanceMap.has(key) && instanceMap.size !== 0) {\n // eslint-disable-next-line no-console\n console.error(`Bootstrap doesn't allow more than one instance per element. Bound instance: ${Array.from(instanceMap.keys())[0]}.`);\n return;\n }\n instanceMap.set(key, instance);\n },\n get(element, key) {\n if (elementMap.has(element)) {\n return elementMap.get(element).get(key) || null;\n }\n return null;\n },\n remove(element, key) {\n if (!elementMap.has(element)) {\n return;\n }\n const instanceMap = elementMap.get(element);\n instanceMap.delete(key);\n\n // free up element references if there are no instances left for an element\n if (instanceMap.size === 0) {\n elementMap.delete(element);\n }\n }\n};\n\n/**\n * --------------------------------------------------------------------------\n * Bootstrap util/index.js\n * Licensed under MIT (https://github.com/twbs/bootstrap/blob/main/LICENSE)\n * --------------------------------------------------------------------------\n */\n\nconst MAX_UID = 1000000;\nconst MILLISECONDS_MULTIPLIER = 1000;\nconst TRANSITION_END = 'transitionend';\n\n/**\n * Properly escape IDs selectors to handle weird IDs\n * @param {string} selector\n * @returns {string}\n */\nconst parseSelector = selector => {\n if (selector && window.CSS && window.CSS.escape) {\n // document.querySelector needs escaping to handle IDs (html5+) containing for instance /\n selector = selector.replace(/#([^\\s\"#']+)/g, (match, id) => `#${CSS.escape(id)}`);\n }\n return selector;\n};\n\n// Shout-out Angus Croll (https://goo.gl/pxwQGp)\nconst toType = object => {\n if (object === null || object === undefined) {\n return `${object}`;\n }\n return Object.prototype.toString.call(object).match(/\\s([a-z]+)/i)[1].toLowerCase();\n};\n\n/**\n * Public Util API\n */\n\nconst getUID = prefix => {\n do {\n prefix += Math.floor(Math.random() * MAX_UID);\n } while (document.getElementById(prefix));\n return prefix;\n};\nconst getTransitionDurationFromElement = element => {\n if (!element) {\n return 0;\n }\n\n // Get transition-duration of the element\n let {\n transitionDuration,\n transitionDelay\n } = window.getComputedStyle(element);\n const floatTransitionDuration = Number.parseFloat(transitionDuration);\n const floatTransitionDelay = Number.parseFloat(transitionDelay);\n\n // Return 0 if element or transition duration is not found\n if (!floatTransitionDuration && !floatTransitionDelay) {\n return 0;\n }\n\n // If multiple durations are defined, take the first\n transitionDuration = transitionDuration.split(',')[0];\n transitionDelay = transitionDelay.split(',')[0];\n return (Number.parseFloat(transitionDuration) + Number.parseFloat(transitionDelay)) * MILLISECONDS_MULTIPLIER;\n};\nconst triggerTransitionEnd = element => {\n element.dispatchEvent(new Event(TRANSITION_END));\n};\nconst isElement = object => {\n if (!object || typeof object !== 'object') {\n return false;\n }\n if (typeof object.jquery !== 'undefined') {\n object = object[0];\n }\n return typeof object.nodeType !== 'undefined';\n};\nconst getElement = object => {\n // it's a jQuery object or a node element\n if (isElement(object)) {\n return object.jquery ? object[0] : object;\n }\n if (typeof object === 'string' && object.length > 0) {\n return document.querySelector(parseSelector(object));\n }\n return null;\n};\nconst isVisible = element => {\n if (!isElement(element) || element.getClientRects().length === 0) {\n return false;\n }\n const elementIsVisible = getComputedStyle(element).getPropertyValue('visibility') === 'visible';\n // Handle `details` element as its content may falsie appear visible when it is closed\n const closedDetails = element.closest('details:not([open])');\n if (!closedDetails) {\n return elementIsVisible;\n }\n if (closedDetails !== element) {\n const summary = element.closest('summary');\n if (summary && summary.parentNode !== closedDetails) {\n return false;\n }\n if (summary === null) {\n return false;\n }\n }\n return elementIsVisible;\n};\nconst isDisabled = element => {\n if (!element || element.nodeType !== Node.ELEMENT_NODE) {\n return true;\n }\n if (element.classList.contains('disabled')) {\n return true;\n }\n if (typeof element.disabled !== 'undefined') {\n return element.disabled;\n }\n return element.hasAttribute('disabled') && element.getAttribute('disabled') !== 'false';\n};\nconst findShadowRoot = element => {\n if (!document.documentElement.attachShadow) {\n return null;\n }\n\n // Can find the shadow root otherwise it'll return the document\n if (typeof element.getRootNode === 'function') {\n const root = element.getRootNode();\n return root instanceof ShadowRoot ? root : null;\n }\n if (element instanceof ShadowRoot) {\n return element;\n }\n\n // when we don't find a shadow root\n if (!element.parentNode) {\n return null;\n }\n return findShadowRoot(element.parentNode);\n};\nconst noop = () => {};\n\n/**\n * Trick to restart an element's animation\n *\n * @param {HTMLElement} element\n * @return void\n *\n * @see https://www.charistheo.io/blog/2021/02/restart-a-css-animation-with-javascript/#restarting-a-css-animation\n */\nconst reflow = element => {\n element.offsetHeight; // eslint-disable-line no-unused-expressions\n};\n\nconst getjQuery = () => {\n if (window.jQuery && !document.body.hasAttribute('data-bs-no-jquery')) {\n return window.jQuery;\n }\n return null;\n};\nconst DOMContentLoadedCallbacks = [];\nconst onDOMContentLoaded = callback => {\n if (document.readyState === 'loading') {\n // add listener on the first call when the document is in loading state\n if (!DOMContentLoadedCallbacks.length) {\n document.addEventListener('DOMContentLoaded', () => {\n for (const callback of DOMContentLoadedCallbacks) {\n callback();\n }\n });\n }\n DOMContentLoadedCallbacks.push(callback);\n } else {\n callback();\n }\n};\nconst isRTL = () => document.documentElement.dir === 'rtl';\nconst defineJQueryPlugin = plugin => {\n onDOMContentLoaded(() => {\n const $ = getjQuery();\n /* istanbul ignore if */\n if ($) {\n const name = plugin.NAME;\n const JQUERY_NO_CONFLICT = $.fn[name];\n $.fn[name] = plugin.jQueryInterface;\n $.fn[name].Constructor = plugin;\n $.fn[name].noConflict = () => {\n $.fn[name] = JQUERY_NO_CONFLICT;\n return plugin.jQueryInterface;\n };\n }\n });\n};\nconst execute = (possibleCallback, args = [], defaultValue = possibleCallback) => {\n return typeof possibleCallback === 'function' ? possibleCallback(...args) : defaultValue;\n};\nconst executeAfterTransition = (callback, transitionElement, waitForTransition = true) => {\n if (!waitForTransition) {\n execute(callback);\n return;\n }\n const durationPadding = 5;\n const emulatedDuration = getTransitionDurationFromElement(transitionElement) + durationPadding;\n let called = false;\n const handler = ({\n target\n }) => {\n if (target !== transitionElement) {\n return;\n }\n called = true;\n transitionElement.removeEventListener(TRANSITION_END, handler);\n execute(callback);\n };\n transitionElement.addEventListener(TRANSITION_END, handler);\n setTimeout(() => {\n if (!called) {\n triggerTransitionEnd(transitionElement);\n }\n }, emulatedDuration);\n};\n\n/**\n * Return the previous/next element of a list.\n *\n * @param {array} list The list of elements\n * @param activeElement The active element\n * @param shouldGetNext Choose to get next or previous element\n * @param isCycleAllowed\n * @return {Element|elem} The proper element\n */\nconst getNextActiveElement = (list, activeElement, shouldGetNext, isCycleAllowed) => {\n const listLength = list.length;\n let index = list.indexOf(activeElement);\n\n // if the element does not exist in the list return an element\n // depending on the direction and if cycle is allowed\n if (index === -1) {\n return !shouldGetNext && isCycleAllowed ? list[listLength - 1] : list[0];\n }\n index += shouldGetNext ? 1 : -1;\n if (isCycleAllowed) {\n index = (index + listLength) % listLength;\n }\n return list[Math.max(0, Math.min(index, listLength - 1))];\n};\n\n/**\n * --------------------------------------------------------------------------\n * Bootstrap dom/event-handler.js\n * Licensed under MIT (https://github.com/twbs/bootstrap/blob/main/LICENSE)\n * --------------------------------------------------------------------------\n */\n\n\n/**\n * Constants\n */\n\nconst namespaceRegex = /[^.]*(?=\\..*)\\.|.*/;\nconst stripNameRegex = /\\..*/;\nconst stripUidRegex = /::\\d+$/;\nconst eventRegistry = {}; // Events storage\nlet uidEvent = 1;\nconst customEvents = {\n mouseenter: 'mouseover',\n mouseleave: 'mouseout'\n};\nconst nativeEvents = new Set(['click', 'dblclick', 'mouseup', 'mousedown', 'contextmenu', 'mousewheel', 'DOMMouseScroll', 'mouseover', 'mouseout', 'mousemove', 'selectstart', 'selectend', 'keydown', 'keypress', 'keyup', 'orientationchange', 'touchstart', 'touchmove', 'touchend', 'touchcancel', 'pointerdown', 'pointermove', 'pointerup', 'pointerleave', 'pointercancel', 'gesturestart', 'gesturechange', 'gestureend', 'focus', 'blur', 'change', 'reset', 'select', 'submit', 'focusin', 'focusout', 'load', 'unload', 'beforeunload', 'resize', 'move', 'DOMContentLoaded', 'readystatechange', 'error', 'abort', 'scroll']);\n\n/**\n * Private methods\n */\n\nfunction makeEventUid(element, uid) {\n return uid && `${uid}::${uidEvent++}` || element.uidEvent || uidEvent++;\n}\nfunction getElementEvents(element) {\n const uid = makeEventUid(element);\n element.uidEvent = uid;\n eventRegistry[uid] = eventRegistry[uid] || {};\n return eventRegistry[uid];\n}\nfunction bootstrapHandler(element, fn) {\n return function handler(event) {\n hydrateObj(event, {\n delegateTarget: element\n });\n if (handler.oneOff) {\n EventHandler.off(element, event.type, fn);\n }\n return fn.apply(element, [event]);\n };\n}\nfunction bootstrapDelegationHandler(element, selector, fn) {\n return function handler(event) {\n const domElements = element.querySelectorAll(selector);\n for (let {\n target\n } = event; target && target !== this; target = target.parentNode) {\n for (const domElement of domElements) {\n if (domElement !== target) {\n continue;\n }\n hydrateObj(event, {\n delegateTarget: target\n });\n if (handler.oneOff) {\n EventHandler.off(element, event.type, selector, fn);\n }\n return fn.apply(target, [event]);\n }\n }\n };\n}\nfunction findHandler(events, callable, delegationSelector = null) {\n return Object.values(events).find(event => event.callable === callable && event.delegationSelector === delegationSelector);\n}\nfunction normalizeParameters(originalTypeEvent, handler, delegationFunction) {\n const isDelegated = typeof handler === 'string';\n // TODO: tooltip passes `false` instead of selector, so we need to check\n const callable = isDelegated ? delegationFunction : handler || delegationFunction;\n let typeEvent = getTypeEvent(originalTypeEvent);\n if (!nativeEvents.has(typeEvent)) {\n typeEvent = originalTypeEvent;\n }\n return [isDelegated, callable, typeEvent];\n}\nfunction addHandler(element, originalTypeEvent, handler, delegationFunction, oneOff) {\n if (typeof originalTypeEvent !== 'string' || !element) {\n return;\n }\n let [isDelegated, callable, typeEvent] = normalizeParameters(originalTypeEvent, handler, delegationFunction);\n\n // in case of mouseenter or mouseleave wrap the handler within a function that checks for its DOM position\n // this prevents the handler from being dispatched the same way as mouseover or mouseout does\n if (originalTypeEvent in customEvents) {\n const wrapFunction = fn => {\n return function (event) {\n if (!event.relatedTarget || event.relatedTarget !== event.delegateTarget && !event.delegateTarget.contains(event.relatedTarget)) {\n return fn.call(this, event);\n }\n };\n };\n callable = wrapFunction(callable);\n }\n const events = getElementEvents(element);\n const handlers = events[typeEvent] || (events[typeEvent] = {});\n const previousFunction = findHandler(handlers, callable, isDelegated ? handler : null);\n if (previousFunction) {\n previousFunction.oneOff = previousFunction.oneOff && oneOff;\n return;\n }\n const uid = makeEventUid(callable, originalTypeEvent.replace(namespaceRegex, ''));\n const fn = isDelegated ? bootstrapDelegationHandler(element, handler, callable) : bootstrapHandler(element, callable);\n fn.delegationSelector = isDelegated ? handler : null;\n fn.callable = callable;\n fn.oneOff = oneOff;\n fn.uidEvent = uid;\n handlers[uid] = fn;\n element.addEventListener(typeEvent, fn, isDelegated);\n}\nfunction removeHandler(element, events, typeEvent, handler, delegationSelector) {\n const fn = findHandler(events[typeEvent], handler, delegationSelector);\n if (!fn) {\n return;\n }\n element.removeEventListener(typeEvent, fn, Boolean(delegationSelector));\n delete events[typeEvent][fn.uidEvent];\n}\nfunction removeNamespacedHandlers(element, events, typeEvent, namespace) {\n const storeElementEvent = events[typeEvent] || {};\n for (const [handlerKey, event] of Object.entries(storeElementEvent)) {\n if (handlerKey.includes(namespace)) {\n removeHandler(element, events, typeEvent, event.callable, event.delegationSelector);\n }\n }\n}\nfunction getTypeEvent(event) {\n // allow to get the native events from namespaced events ('click.bs.button' --> 'click')\n event = event.replace(stripNameRegex, '');\n return customEvents[event] || event;\n}\nconst EventHandler = {\n on(element, event, handler, delegationFunction) {\n addHandler(element, event, handler, delegationFunction, false);\n },\n one(element, event, handler, delegationFunction) {\n addHandler(element, event, handler, delegationFunction, true);\n },\n off(element, originalTypeEvent, handler, delegationFunction) {\n if (typeof originalTypeEvent !== 'string' || !element) {\n return;\n }\n const [isDelegated, callable, typeEvent] = normalizeParameters(originalTypeEvent, handler, delegationFunction);\n const inNamespace = typeEvent !== originalTypeEvent;\n const events = getElementEvents(element);\n const storeElementEvent = events[typeEvent] || {};\n const isNamespace = originalTypeEvent.startsWith('.');\n if (typeof callable !== 'undefined') {\n // Simplest case: handler is passed, remove that listener ONLY.\n if (!Object.keys(storeElementEvent).length) {\n return;\n }\n removeHandler(element, events, typeEvent, callable, isDelegated ? handler : null);\n return;\n }\n if (isNamespace) {\n for (const elementEvent of Object.keys(events)) {\n removeNamespacedHandlers(element, events, elementEvent, originalTypeEvent.slice(1));\n }\n }\n for (const [keyHandlers, event] of Object.entries(storeElementEvent)) {\n const handlerKey = keyHandlers.replace(stripUidRegex, '');\n if (!inNamespace || originalTypeEvent.includes(handlerKey)) {\n removeHandler(element, events, typeEvent, event.callable, event.delegationSelector);\n }\n }\n },\n trigger(element, event, args) {\n if (typeof event !== 'string' || !element) {\n return null;\n }\n const $ = getjQuery();\n const typeEvent = getTypeEvent(event);\n const inNamespace = event !== typeEvent;\n let jQueryEvent = null;\n let bubbles = true;\n let nativeDispatch = true;\n let defaultPrevented = false;\n if (inNamespace && $) {\n jQueryEvent = $.Event(event, args);\n $(element).trigger(jQueryEvent);\n bubbles = !jQueryEvent.isPropagationStopped();\n nativeDispatch = !jQueryEvent.isImmediatePropagationStopped();\n defaultPrevented = jQueryEvent.isDefaultPrevented();\n }\n const evt = hydrateObj(new Event(event, {\n bubbles,\n cancelable: true\n }), args);\n if (defaultPrevented) {\n evt.preventDefault();\n }\n if (nativeDispatch) {\n element.dispatchEvent(evt);\n }\n if (evt.defaultPrevented && jQueryEvent) {\n jQueryEvent.preventDefault();\n }\n return evt;\n }\n};\nfunction hydrateObj(obj, meta = {}) {\n for (const [key, value] of Object.entries(meta)) {\n try {\n obj[key] = value;\n } catch (_unused) {\n Object.defineProperty(obj, key, {\n configurable: true,\n get() {\n return value;\n }\n });\n }\n }\n return obj;\n}\n\n/**\n * --------------------------------------------------------------------------\n * Bootstrap dom/manipulator.js\n * Licensed under MIT (https://github.com/twbs/bootstrap/blob/main/LICENSE)\n * --------------------------------------------------------------------------\n */\n\nfunction normalizeData(value) {\n if (value === 'true') {\n return true;\n }\n if (value === 'false') {\n return false;\n }\n if (value === Number(value).toString()) {\n return Number(value);\n }\n if (value === '' || value === 'null') {\n return null;\n }\n if (typeof value !== 'string') {\n return value;\n }\n try {\n return JSON.parse(decodeURIComponent(value));\n } catch (_unused) {\n return value;\n }\n}\nfunction normalizeDataKey(key) {\n return key.replace(/[A-Z]/g, chr => `-${chr.toLowerCase()}`);\n}\nconst Manipulator = {\n setDataAttribute(element, key, value) {\n element.setAttribute(`data-bs-${normalizeDataKey(key)}`, value);\n },\n removeDataAttribute(element, key) {\n element.removeAttribute(`data-bs-${normalizeDataKey(key)}`);\n },\n getDataAttributes(element) {\n if (!element) {\n return {};\n }\n const attributes = {};\n const bsKeys = Object.keys(element.dataset).filter(key => key.startsWith('bs') && !key.startsWith('bsConfig'));\n for (const key of bsKeys) {\n let pureKey = key.replace(/^bs/, '');\n pureKey = pureKey.charAt(0).toLowerCase() + pureKey.slice(1, pureKey.length);\n attributes[pureKey] = normalizeData(element.dataset[key]);\n }\n return attributes;\n },\n getDataAttribute(element, key) {\n return normalizeData(element.getAttribute(`data-bs-${normalizeDataKey(key)}`));\n }\n};\n\n/**\n * --------------------------------------------------------------------------\n * Bootstrap util/config.js\n * Licensed under MIT (https://github.com/twbs/bootstrap/blob/main/LICENSE)\n * --------------------------------------------------------------------------\n */\n\n\n/**\n * Class definition\n */\n\nclass Config {\n // Getters\n static get Default() {\n return {};\n }\n static get DefaultType() {\n return {};\n }\n static get NAME() {\n throw new Error('You have to implement the static method \"NAME\", for each component!');\n }\n _getConfig(config) {\n config = this._mergeConfigObj(config);\n config = this._configAfterMerge(config);\n this._typeCheckConfig(config);\n return config;\n }\n _configAfterMerge(config) {\n return config;\n }\n _mergeConfigObj(config, element) {\n const jsonConfig = isElement(element) ? Manipulator.getDataAttribute(element, 'config') : {}; // try to parse\n\n return {\n ...this.constructor.Default,\n ...(typeof jsonConfig === 'object' ? jsonConfig : {}),\n ...(isElement(element) ? Manipulator.getDataAttributes(element) : {}),\n ...(typeof config === 'object' ? config : {})\n };\n }\n _typeCheckConfig(config, configTypes = this.constructor.DefaultType) {\n for (const [property, expectedTypes] of Object.entries(configTypes)) {\n const value = config[property];\n const valueType = isElement(value) ? 'element' : toType(value);\n if (!new RegExp(expectedTypes).test(valueType)) {\n throw new TypeError(`${this.constructor.NAME.toUpperCase()}: Option \"${property}\" provided type \"${valueType}\" but expected type \"${expectedTypes}\".`);\n }\n }\n }\n}\n\n/**\n * --------------------------------------------------------------------------\n * Bootstrap base-component.js\n * Licensed under MIT (https://github.com/twbs/bootstrap/blob/main/LICENSE)\n * --------------------------------------------------------------------------\n */\n\n\n/**\n * Constants\n */\n\nconst VERSION = '5.3.2';\n\n/**\n * Class definition\n */\n\nclass BaseComponent extends Config {\n constructor(element, config) {\n super();\n element = getElement(element);\n if (!element) {\n return;\n }\n this._element = element;\n this._config = this._getConfig(config);\n Data.set(this._element, this.constructor.DATA_KEY, this);\n }\n\n // Public\n dispose() {\n Data.remove(this._element, this.constructor.DATA_KEY);\n EventHandler.off(this._element, this.constructor.EVENT_KEY);\n for (const propertyName of Object.getOwnPropertyNames(this)) {\n this[propertyName] = null;\n }\n }\n _queueCallback(callback, element, isAnimated = true) {\n executeAfterTransition(callback, element, isAnimated);\n }\n _getConfig(config) {\n config = this._mergeConfigObj(config, this._element);\n config = this._configAfterMerge(config);\n this._typeCheckConfig(config);\n return config;\n }\n\n // Static\n static getInstance(element) {\n return Data.get(getElement(element), this.DATA_KEY);\n }\n static getOrCreateInstance(element, config = {}) {\n return this.getInstance(element) || new this(element, typeof config === 'object' ? config : null);\n }\n static get VERSION() {\n return VERSION;\n }\n static get DATA_KEY() {\n return `bs.${this.NAME}`;\n }\n static get EVENT_KEY() {\n return `.${this.DATA_KEY}`;\n }\n static eventName(name) {\n return `${name}${this.EVENT_KEY}`;\n }\n}\n\n/**\n * --------------------------------------------------------------------------\n * Bootstrap dom/selector-engine.js\n * Licensed under MIT (https://github.com/twbs/bootstrap/blob/main/LICENSE)\n * --------------------------------------------------------------------------\n */\n\nconst getSelector = element => {\n let selector = element.getAttribute('data-bs-target');\n if (!selector || selector === '#') {\n let hrefAttribute = element.getAttribute('href');\n\n // The only valid content that could double as a selector are IDs or classes,\n // so everything starting with `#` or `.`. If a \"real\" URL is used as the selector,\n // `document.querySelector` will rightfully complain it is invalid.\n // See https://github.com/twbs/bootstrap/issues/32273\n if (!hrefAttribute || !hrefAttribute.includes('#') && !hrefAttribute.startsWith('.')) {\n return null;\n }\n\n // Just in case some CMS puts out a full URL with the anchor appended\n if (hrefAttribute.includes('#') && !hrefAttribute.startsWith('#')) {\n hrefAttribute = `#${hrefAttribute.split('#')[1]}`;\n }\n selector = hrefAttribute && hrefAttribute !== '#' ? parseSelector(hrefAttribute.trim()) : null;\n }\n return selector;\n};\nconst SelectorEngine = {\n find(selector, element = document.documentElement) {\n return [].concat(...Element.prototype.querySelectorAll.call(element, selector));\n },\n findOne(selector, element = document.documentElement) {\n return Element.prototype.querySelector.call(element, selector);\n },\n children(element, selector) {\n return [].concat(...element.children).filter(child => child.matches(selector));\n },\n parents(element, selector) {\n const parents = [];\n let ancestor = element.parentNode.closest(selector);\n while (ancestor) {\n parents.push(ancestor);\n ancestor = ancestor.parentNode.closest(selector);\n }\n return parents;\n },\n prev(element, selector) {\n let previous = element.previousElementSibling;\n while (previous) {\n if (previous.matches(selector)) {\n return [previous];\n }\n previous = previous.previousElementSibling;\n }\n return [];\n },\n // TODO: this is now unused; remove later along with prev()\n next(element, selector) {\n let next = element.nextElementSibling;\n while (next) {\n if (next.matches(selector)) {\n return [next];\n }\n next = next.nextElementSibling;\n }\n return [];\n },\n focusableChildren(element) {\n const focusables = ['a', 'button', 'input', 'textarea', 'select', 'details', '[tabindex]', '[contenteditable=\"true\"]'].map(selector => `${selector}:not([tabindex^=\"-\"])`).join(',');\n return this.find(focusables, element).filter(el => !isDisabled(el) && isVisible(el));\n },\n getSelectorFromElement(element) {\n const selector = getSelector(element);\n if (selector) {\n return SelectorEngine.findOne(selector) ? selector : null;\n }\n return null;\n },\n getElementFromSelector(element) {\n const selector = getSelector(element);\n return selector ? SelectorEngine.findOne(selector) : null;\n },\n getMultipleElementsFromSelector(element) {\n const selector = getSelector(element);\n return selector ? SelectorEngine.find(selector) : [];\n }\n};\n\n/**\n * --------------------------------------------------------------------------\n * Bootstrap util/component-functions.js\n * Licensed under MIT (https://github.com/twbs/bootstrap/blob/main/LICENSE)\n * --------------------------------------------------------------------------\n */\n\nconst enableDismissTrigger = (component, method = 'hide') => {\n const clickEvent = `click.dismiss${component.EVENT_KEY}`;\n const name = component.NAME;\n EventHandler.on(document, clickEvent, `[data-bs-dismiss=\"${name}\"]`, function (event) {\n if (['A', 'AREA'].includes(this.tagName)) {\n event.preventDefault();\n }\n if (isDisabled(this)) {\n return;\n }\n const target = SelectorEngine.getElementFromSelector(this) || this.closest(`.${name}`);\n const instance = component.getOrCreateInstance(target);\n\n // Method argument is left, for Alert and only, as it doesn't implement the 'hide' method\n instance[method]();\n });\n};\n\n/**\n * --------------------------------------------------------------------------\n * Bootstrap alert.js\n * Licensed under MIT (https://github.com/twbs/bootstrap/blob/main/LICENSE)\n * --------------------------------------------------------------------------\n */\n\n\n/**\n * Constants\n */\n\nconst NAME$f = 'alert';\nconst DATA_KEY$a = 'bs.alert';\nconst EVENT_KEY$b = `.${DATA_KEY$a}`;\nconst EVENT_CLOSE = `close${EVENT_KEY$b}`;\nconst EVENT_CLOSED = `closed${EVENT_KEY$b}`;\nconst CLASS_NAME_FADE$5 = 'fade';\nconst CLASS_NAME_SHOW$8 = 'show';\n\n/**\n * Class definition\n */\n\nclass Alert extends BaseComponent {\n // Getters\n static get NAME() {\n return NAME$f;\n }\n\n // Public\n close() {\n const closeEvent = EventHandler.trigger(this._element, EVENT_CLOSE);\n if (closeEvent.defaultPrevented) {\n return;\n }\n this._element.classList.remove(CLASS_NAME_SHOW$8);\n const isAnimated = this._element.classList.contains(CLASS_NAME_FADE$5);\n this._queueCallback(() => this._destroyElement(), this._element, isAnimated);\n }\n\n // Private\n _destroyElement() {\n this._element.remove();\n EventHandler.trigger(this._element, EVENT_CLOSED);\n this.dispose();\n }\n\n // Static\n static jQueryInterface(config) {\n return this.each(function () {\n const data = Alert.getOrCreateInstance(this);\n if (typeof config !== 'string') {\n return;\n }\n if (data[config] === undefined || config.startsWith('_') || config === 'constructor') {\n throw new TypeError(`No method named \"${config}\"`);\n }\n data[config](this);\n });\n }\n}\n\n/**\n * Data API implementation\n */\n\nenableDismissTrigger(Alert, 'close');\n\n/**\n * jQuery\n */\n\ndefineJQueryPlugin(Alert);\n\n/**\n * --------------------------------------------------------------------------\n * Bootstrap button.js\n * Licensed under MIT (https://github.com/twbs/bootstrap/blob/main/LICENSE)\n * --------------------------------------------------------------------------\n */\n\n\n/**\n * Constants\n */\n\nconst NAME$e = 'button';\nconst DATA_KEY$9 = 'bs.button';\nconst EVENT_KEY$a = `.${DATA_KEY$9}`;\nconst DATA_API_KEY$6 = '.data-api';\nconst CLASS_NAME_ACTIVE$3 = 'active';\nconst SELECTOR_DATA_TOGGLE$5 = '[data-bs-toggle=\"button\"]';\nconst EVENT_CLICK_DATA_API$6 = `click${EVENT_KEY$a}${DATA_API_KEY$6}`;\n\n/**\n * Class definition\n */\n\nclass Button extends BaseComponent {\n // Getters\n static get NAME() {\n return NAME$e;\n }\n\n // Public\n toggle() {\n // Toggle class and sync the `aria-pressed` attribute with the return value of the `.toggle()` method\n this._element.setAttribute('aria-pressed', this._element.classList.toggle(CLASS_NAME_ACTIVE$3));\n }\n\n // Static\n static jQueryInterface(config) {\n return this.each(function () {\n const data = Button.getOrCreateInstance(this);\n if (config === 'toggle') {\n data[config]();\n }\n });\n }\n}\n\n/**\n * Data API implementation\n */\n\nEventHandler.on(document, EVENT_CLICK_DATA_API$6, SELECTOR_DATA_TOGGLE$5, event => {\n event.preventDefault();\n const button = event.target.closest(SELECTOR_DATA_TOGGLE$5);\n const data = Button.getOrCreateInstance(button);\n data.toggle();\n});\n\n/**\n * jQuery\n */\n\ndefineJQueryPlugin(Button);\n\n/**\n * --------------------------------------------------------------------------\n * Bootstrap util/swipe.js\n * Licensed under MIT (https://github.com/twbs/bootstrap/blob/main/LICENSE)\n * --------------------------------------------------------------------------\n */\n\n\n/**\n * Constants\n */\n\nconst NAME$d = 'swipe';\nconst EVENT_KEY$9 = '.bs.swipe';\nconst EVENT_TOUCHSTART = `touchstart${EVENT_KEY$9}`;\nconst EVENT_TOUCHMOVE = `touchmove${EVENT_KEY$9}`;\nconst EVENT_TOUCHEND = `touchend${EVENT_KEY$9}`;\nconst EVENT_POINTERDOWN = `pointerdown${EVENT_KEY$9}`;\nconst EVENT_POINTERUP = `pointerup${EVENT_KEY$9}`;\nconst POINTER_TYPE_TOUCH = 'touch';\nconst POINTER_TYPE_PEN = 'pen';\nconst CLASS_NAME_POINTER_EVENT = 'pointer-event';\nconst SWIPE_THRESHOLD = 40;\nconst Default$c = {\n endCallback: null,\n leftCallback: null,\n rightCallback: null\n};\nconst DefaultType$c = {\n endCallback: '(function|null)',\n leftCallback: '(function|null)',\n rightCallback: '(function|null)'\n};\n\n/**\n * Class definition\n */\n\nclass Swipe extends Config {\n constructor(element, config) {\n super();\n this._element = element;\n if (!element || !Swipe.isSupported()) {\n return;\n }\n this._config = this._getConfig(config);\n this._deltaX = 0;\n this._supportPointerEvents = Boolean(window.PointerEvent);\n this._initEvents();\n }\n\n // Getters\n static get Default() {\n return Default$c;\n }\n static get DefaultType() {\n return DefaultType$c;\n }\n static get NAME() {\n return NAME$d;\n }\n\n // Public\n dispose() {\n EventHandler.off(this._element, EVENT_KEY$9);\n }\n\n // Private\n _start(event) {\n if (!this._supportPointerEvents) {\n this._deltaX = event.touches[0].clientX;\n return;\n }\n if (this._eventIsPointerPenTouch(event)) {\n this._deltaX = event.clientX;\n }\n }\n _end(event) {\n if (this._eventIsPointerPenTouch(event)) {\n this._deltaX = event.clientX - this._deltaX;\n }\n this._handleSwipe();\n execute(this._config.endCallback);\n }\n _move(event) {\n this._deltaX = event.touches && event.touches.length > 1 ? 0 : event.touches[0].clientX - this._deltaX;\n }\n _handleSwipe() {\n const absDeltaX = Math.abs(this._deltaX);\n if (absDeltaX <= SWIPE_THRESHOLD) {\n return;\n }\n const direction = absDeltaX / this._deltaX;\n this._deltaX = 0;\n if (!direction) {\n return;\n }\n execute(direction > 0 ? this._config.rightCallback : this._config.leftCallback);\n }\n _initEvents() {\n if (this._supportPointerEvents) {\n EventHandler.on(this._element, EVENT_POINTERDOWN, event => this._start(event));\n EventHandler.on(this._element, EVENT_POINTERUP, event => this._end(event));\n this._element.classList.add(CLASS_NAME_POINTER_EVENT);\n } else {\n EventHandler.on(this._element, EVENT_TOUCHSTART, event => this._start(event));\n EventHandler.on(this._element, EVENT_TOUCHMOVE, event => this._move(event));\n EventHandler.on(this._element, EVENT_TOUCHEND, event => this._end(event));\n }\n }\n _eventIsPointerPenTouch(event) {\n return this._supportPointerEvents && (event.pointerType === POINTER_TYPE_PEN || event.pointerType === POINTER_TYPE_TOUCH);\n }\n\n // Static\n static isSupported() {\n return 'ontouchstart' in document.documentElement || navigator.maxTouchPoints > 0;\n }\n}\n\n/**\n * --------------------------------------------------------------------------\n * Bootstrap carousel.js\n * Licensed under MIT (https://github.com/twbs/bootstrap/blob/main/LICENSE)\n * --------------------------------------------------------------------------\n */\n\n\n/**\n * Constants\n */\n\nconst NAME$c = 'carousel';\nconst DATA_KEY$8 = 'bs.carousel';\nconst EVENT_KEY$8 = `.${DATA_KEY$8}`;\nconst DATA_API_KEY$5 = '.data-api';\nconst ARROW_LEFT_KEY$1 = 'ArrowLeft';\nconst ARROW_RIGHT_KEY$1 = 'ArrowRight';\nconst TOUCHEVENT_COMPAT_WAIT = 500; // Time for mouse compat events to fire after touch\n\nconst ORDER_NEXT = 'next';\nconst ORDER_PREV = 'prev';\nconst DIRECTION_LEFT = 'left';\nconst DIRECTION_RIGHT = 'right';\nconst EVENT_SLIDE = `slide${EVENT_KEY$8}`;\nconst EVENT_SLID = `slid${EVENT_KEY$8}`;\nconst EVENT_KEYDOWN$1 = `keydown${EVENT_KEY$8}`;\nconst EVENT_MOUSEENTER$1 = `mouseenter${EVENT_KEY$8}`;\nconst EVENT_MOUSELEAVE$1 = `mouseleave${EVENT_KEY$8}`;\nconst EVENT_DRAG_START = `dragstart${EVENT_KEY$8}`;\nconst EVENT_LOAD_DATA_API$3 = `load${EVENT_KEY$8}${DATA_API_KEY$5}`;\nconst EVENT_CLICK_DATA_API$5 = `click${EVENT_KEY$8}${DATA_API_KEY$5}`;\nconst CLASS_NAME_CAROUSEL = 'carousel';\nconst CLASS_NAME_ACTIVE$2 = 'active';\nconst CLASS_NAME_SLIDE = 'slide';\nconst CLASS_NAME_END = 'carousel-item-end';\nconst CLASS_NAME_START = 'carousel-item-start';\nconst CLASS_NAME_NEXT = 'carousel-item-next';\nconst CLASS_NAME_PREV = 'carousel-item-prev';\nconst SELECTOR_ACTIVE = '.active';\nconst SELECTOR_ITEM = '.carousel-item';\nconst SELECTOR_ACTIVE_ITEM = SELECTOR_ACTIVE + SELECTOR_ITEM;\nconst SELECTOR_ITEM_IMG = '.carousel-item img';\nconst SELECTOR_INDICATORS = '.carousel-indicators';\nconst SELECTOR_DATA_SLIDE = '[data-bs-slide], [data-bs-slide-to]';\nconst SELECTOR_DATA_RIDE = '[data-bs-ride=\"carousel\"]';\nconst KEY_TO_DIRECTION = {\n [ARROW_LEFT_KEY$1]: DIRECTION_RIGHT,\n [ARROW_RIGHT_KEY$1]: DIRECTION_LEFT\n};\nconst Default$b = {\n interval: 5000,\n keyboard: true,\n pause: 'hover',\n ride: false,\n touch: true,\n wrap: true\n};\nconst DefaultType$b = {\n interval: '(number|boolean)',\n // TODO:v6 remove boolean support\n keyboard: 'boolean',\n pause: '(string|boolean)',\n ride: '(boolean|string)',\n touch: 'boolean',\n wrap: 'boolean'\n};\n\n/**\n * Class definition\n */\n\nclass Carousel extends BaseComponent {\n constructor(element, config) {\n super(element, config);\n this._interval = null;\n this._activeElement = null;\n this._isSliding = false;\n this.touchTimeout = null;\n this._swipeHelper = null;\n this._indicatorsElement = SelectorEngine.findOne(SELECTOR_INDICATORS, this._element);\n this._addEventListeners();\n if (this._config.ride === CLASS_NAME_CAROUSEL) {\n this.cycle();\n }\n }\n\n // Getters\n static get Default() {\n return Default$b;\n }\n static get DefaultType() {\n return DefaultType$b;\n }\n static get NAME() {\n return NAME$c;\n }\n\n // Public\n next() {\n this._slide(ORDER_NEXT);\n }\n nextWhenVisible() {\n // FIXME TODO use `document.visibilityState`\n // Don't call next when the page isn't visible\n // or the carousel or its parent isn't visible\n if (!document.hidden && isVisible(this._element)) {\n this.next();\n }\n }\n prev() {\n this._slide(ORDER_PREV);\n }\n pause() {\n if (this._isSliding) {\n triggerTransitionEnd(this._element);\n }\n this._clearInterval();\n }\n cycle() {\n this._clearInterval();\n this._updateInterval();\n this._interval = setInterval(() => this.nextWhenVisible(), this._config.interval);\n }\n _maybeEnableCycle() {\n if (!this._config.ride) {\n return;\n }\n if (this._isSliding) {\n EventHandler.one(this._element, EVENT_SLID, () => this.cycle());\n return;\n }\n this.cycle();\n }\n to(index) {\n const items = this._getItems();\n if (index > items.length - 1 || index < 0) {\n return;\n }\n if (this._isSliding) {\n EventHandler.one(this._element, EVENT_SLID, () => this.to(index));\n return;\n }\n const activeIndex = this._getItemIndex(this._getActive());\n if (activeIndex === index) {\n return;\n }\n const order = index > activeIndex ? ORDER_NEXT : ORDER_PREV;\n this._slide(order, items[index]);\n }\n dispose() {\n if (this._swipeHelper) {\n this._swipeHelper.dispose();\n }\n super.dispose();\n }\n\n // Private\n _configAfterMerge(config) {\n config.defaultInterval = config.interval;\n return config;\n }\n _addEventListeners() {\n if (this._config.keyboard) {\n EventHandler.on(this._element, EVENT_KEYDOWN$1, event => this._keydown(event));\n }\n if (this._config.pause === 'hover') {\n EventHandler.on(this._element, EVENT_MOUSEENTER$1, () => this.pause());\n EventHandler.on(this._element, EVENT_MOUSELEAVE$1, () => this._maybeEnableCycle());\n }\n if (this._config.touch && Swipe.isSupported()) {\n this._addTouchEventListeners();\n }\n }\n _addTouchEventListeners() {\n for (const img of SelectorEngine.find(SELECTOR_ITEM_IMG, this._element)) {\n EventHandler.on(img, EVENT_DRAG_START, event => event.preventDefault());\n }\n const endCallBack = () => {\n if (this._config.pause !== 'hover') {\n return;\n }\n\n // If it's a touch-enabled device, mouseenter/leave are fired as\n // part of the mouse compatibility events on first tap - the carousel\n // would stop cycling until user tapped out of it;\n // here, we listen for touchend, explicitly pause the carousel\n // (as if it's the second time we tap on it, mouseenter compat event\n // is NOT fired) and after a timeout (to allow for mouse compatibility\n // events to fire) we explicitly restart cycling\n\n this.pause();\n if (this.touchTimeout) {\n clearTimeout(this.touchTimeout);\n }\n this.touchTimeout = setTimeout(() => this._maybeEnableCycle(), TOUCHEVENT_COMPAT_WAIT + this._config.interval);\n };\n const swipeConfig = {\n leftCallback: () => this._slide(this._directionToOrder(DIRECTION_LEFT)),\n rightCallback: () => this._slide(this._directionToOrder(DIRECTION_RIGHT)),\n endCallback: endCallBack\n };\n this._swipeHelper = new Swipe(this._element, swipeConfig);\n }\n _keydown(event) {\n if (/input|textarea/i.test(event.target.tagName)) {\n return;\n }\n const direction = KEY_TO_DIRECTION[event.key];\n if (direction) {\n event.preventDefault();\n this._slide(this._directionToOrder(direction));\n }\n }\n _getItemIndex(element) {\n return this._getItems().indexOf(element);\n }\n _setActiveIndicatorElement(index) {\n if (!this._indicatorsElement) {\n return;\n }\n const activeIndicator = SelectorEngine.findOne(SELECTOR_ACTIVE, this._indicatorsElement);\n activeIndicator.classList.remove(CLASS_NAME_ACTIVE$2);\n activeIndicator.removeAttribute('aria-current');\n const newActiveIndicator = SelectorEngine.findOne(`[data-bs-slide-to=\"${index}\"]`, this._indicatorsElement);\n if (newActiveIndicator) {\n newActiveIndicator.classList.add(CLASS_NAME_ACTIVE$2);\n newActiveIndicator.setAttribute('aria-current', 'true');\n }\n }\n _updateInterval() {\n const element = this._activeElement || this._getActive();\n if (!element) {\n return;\n }\n const elementInterval = Number.parseInt(element.getAttribute('data-bs-interval'), 10);\n this._config.interval = elementInterval || this._config.defaultInterval;\n }\n _slide(order, element = null) {\n if (this._isSliding) {\n return;\n }\n const activeElement = this._getActive();\n const isNext = order === ORDER_NEXT;\n const nextElement = element || getNextActiveElement(this._getItems(), activeElement, isNext, this._config.wrap);\n if (nextElement === activeElement) {\n return;\n }\n const nextElementIndex = this._getItemIndex(nextElement);\n const triggerEvent = eventName => {\n return EventHandler.trigger(this._element, eventName, {\n relatedTarget: nextElement,\n direction: this._orderToDirection(order),\n from: this._getItemIndex(activeElement),\n to: nextElementIndex\n });\n };\n const slideEvent = triggerEvent(EVENT_SLIDE);\n if (slideEvent.defaultPrevented) {\n return;\n }\n if (!activeElement || !nextElement) {\n // Some weirdness is happening, so we bail\n // TODO: change tests that use empty divs to avoid this check\n return;\n }\n const isCycling = Boolean(this._interval);\n this.pause();\n this._isSliding = true;\n this._setActiveIndicatorElement(nextElementIndex);\n this._activeElement = nextElement;\n const directionalClassName = isNext ? CLASS_NAME_START : CLASS_NAME_END;\n const orderClassName = isNext ? CLASS_NAME_NEXT : CLASS_NAME_PREV;\n nextElement.classList.add(orderClassName);\n reflow(nextElement);\n activeElement.classList.add(directionalClassName);\n nextElement.classList.add(directionalClassName);\n const completeCallBack = () => {\n nextElement.classList.remove(directionalClassName, orderClassName);\n nextElement.classList.add(CLASS_NAME_ACTIVE$2);\n activeElement.classList.remove(CLASS_NAME_ACTIVE$2, orderClassName, directionalClassName);\n this._isSliding = false;\n triggerEvent(EVENT_SLID);\n };\n this._queueCallback(completeCallBack, activeElement, this._isAnimated());\n if (isCycling) {\n this.cycle();\n }\n }\n _isAnimated() {\n return this._element.classList.contains(CLASS_NAME_SLIDE);\n }\n _getActive() {\n return SelectorEngine.findOne(SELECTOR_ACTIVE_ITEM, this._element);\n }\n _getItems() {\n return SelectorEngine.find(SELECTOR_ITEM, this._element);\n }\n _clearInterval() {\n if (this._interval) {\n clearInterval(this._interval);\n this._interval = null;\n }\n }\n _directionToOrder(direction) {\n if (isRTL()) {\n return direction === DIRECTION_LEFT ? ORDER_PREV : ORDER_NEXT;\n }\n return direction === DIRECTION_LEFT ? ORDER_NEXT : ORDER_PREV;\n }\n _orderToDirection(order) {\n if (isRTL()) {\n return order === ORDER_PREV ? DIRECTION_LEFT : DIRECTION_RIGHT;\n }\n return order === ORDER_PREV ? DIRECTION_RIGHT : DIRECTION_LEFT;\n }\n\n // Static\n static jQueryInterface(config) {\n return this.each(function () {\n const data = Carousel.getOrCreateInstance(this, config);\n if (typeof config === 'number') {\n data.to(config);\n return;\n }\n if (typeof config === 'string') {\n if (data[config] === undefined || config.startsWith('_') || config === 'constructor') {\n throw new TypeError(`No method named \"${config}\"`);\n }\n data[config]();\n }\n });\n }\n}\n\n/**\n * Data API implementation\n */\n\nEventHandler.on(document, EVENT_CLICK_DATA_API$5, SELECTOR_DATA_SLIDE, function (event) {\n const target = SelectorEngine.getElementFromSelector(this);\n if (!target || !target.classList.contains(CLASS_NAME_CAROUSEL)) {\n return;\n }\n event.preventDefault();\n const carousel = Carousel.getOrCreateInstance(target);\n const slideIndex = this.getAttribute('data-bs-slide-to');\n if (slideIndex) {\n carousel.to(slideIndex);\n carousel._maybeEnableCycle();\n return;\n }\n if (Manipulator.getDataAttribute(this, 'slide') === 'next') {\n carousel.next();\n carousel._maybeEnableCycle();\n return;\n }\n carousel.prev();\n carousel._maybeEnableCycle();\n});\nEventHandler.on(window, EVENT_LOAD_DATA_API$3, () => {\n const carousels = SelectorEngine.find(SELECTOR_DATA_RIDE);\n for (const carousel of carousels) {\n Carousel.getOrCreateInstance(carousel);\n }\n});\n\n/**\n * jQuery\n */\n\ndefineJQueryPlugin(Carousel);\n\n/**\n * --------------------------------------------------------------------------\n * Bootstrap collapse.js\n * Licensed under MIT (https://github.com/twbs/bootstrap/blob/main/LICENSE)\n * --------------------------------------------------------------------------\n */\n\n\n/**\n * Constants\n */\n\nconst NAME$b = 'collapse';\nconst DATA_KEY$7 = 'bs.collapse';\nconst EVENT_KEY$7 = `.${DATA_KEY$7}`;\nconst DATA_API_KEY$4 = '.data-api';\nconst EVENT_SHOW$6 = `show${EVENT_KEY$7}`;\nconst EVENT_SHOWN$6 = `shown${EVENT_KEY$7}`;\nconst EVENT_HIDE$6 = `hide${EVENT_KEY$7}`;\nconst EVENT_HIDDEN$6 = `hidden${EVENT_KEY$7}`;\nconst EVENT_CLICK_DATA_API$4 = `click${EVENT_KEY$7}${DATA_API_KEY$4}`;\nconst CLASS_NAME_SHOW$7 = 'show';\nconst CLASS_NAME_COLLAPSE = 'collapse';\nconst CLASS_NAME_COLLAPSING = 'collapsing';\nconst CLASS_NAME_COLLAPSED = 'collapsed';\nconst CLASS_NAME_DEEPER_CHILDREN = `:scope .${CLASS_NAME_COLLAPSE} .${CLASS_NAME_COLLAPSE}`;\nconst CLASS_NAME_HORIZONTAL = 'collapse-horizontal';\nconst WIDTH = 'width';\nconst HEIGHT = 'height';\nconst SELECTOR_ACTIVES = '.collapse.show, .collapse.collapsing';\nconst SELECTOR_DATA_TOGGLE$4 = '[data-bs-toggle=\"collapse\"]';\nconst Default$a = {\n parent: null,\n toggle: true\n};\nconst DefaultType$a = {\n parent: '(null|element)',\n toggle: 'boolean'\n};\n\n/**\n * Class definition\n */\n\nclass Collapse extends BaseComponent {\n constructor(element, config) {\n super(element, config);\n this._isTransitioning = false;\n this._triggerArray = [];\n const toggleList = SelectorEngine.find(SELECTOR_DATA_TOGGLE$4);\n for (const elem of toggleList) {\n const selector = SelectorEngine.getSelectorFromElement(elem);\n const filterElement = SelectorEngine.find(selector).filter(foundElement => foundElement === this._element);\n if (selector !== null && filterElement.length) {\n this._triggerArray.push(elem);\n }\n }\n this._initializeChildren();\n if (!this._config.parent) {\n this._addAriaAndCollapsedClass(this._triggerArray, this._isShown());\n }\n if (this._config.toggle) {\n this.toggle();\n }\n }\n\n // Getters\n static get Default() {\n return Default$a;\n }\n static get DefaultType() {\n return DefaultType$a;\n }\n static get NAME() {\n return NAME$b;\n }\n\n // Public\n toggle() {\n if (this._isShown()) {\n this.hide();\n } else {\n this.show();\n }\n }\n show() {\n if (this._isTransitioning || this._isShown()) {\n return;\n }\n let activeChildren = [];\n\n // find active children\n if (this._config.parent) {\n activeChildren = this._getFirstLevelChildren(SELECTOR_ACTIVES).filter(element => element !== this._element).map(element => Collapse.getOrCreateInstance(element, {\n toggle: false\n }));\n }\n if (activeChildren.length && activeChildren[0]._isTransitioning) {\n return;\n }\n const startEvent = EventHandler.trigger(this._element, EVENT_SHOW$6);\n if (startEvent.defaultPrevented) {\n return;\n }\n for (const activeInstance of activeChildren) {\n activeInstance.hide();\n }\n const dimension = this._getDimension();\n this._element.classList.remove(CLASS_NAME_COLLAPSE);\n this._element.classList.add(CLASS_NAME_COLLAPSING);\n this._element.style[dimension] = 0;\n this._addAriaAndCollapsedClass(this._triggerArray, true);\n this._isTransitioning = true;\n const complete = () => {\n this._isTransitioning = false;\n this._element.classList.remove(CLASS_NAME_COLLAPSING);\n this._element.classList.add(CLASS_NAME_COLLAPSE, CLASS_NAME_SHOW$7);\n this._element.style[dimension] = '';\n EventHandler.trigger(this._element, EVENT_SHOWN$6);\n };\n const capitalizedDimension = dimension[0].toUpperCase() + dimension.slice(1);\n const scrollSize = `scroll${capitalizedDimension}`;\n this._queueCallback(complete, this._element, true);\n this._element.style[dimension] = `${this._element[scrollSize]}px`;\n }\n hide() {\n if (this._isTransitioning || !this._isShown()) {\n return;\n }\n const startEvent = EventHandler.trigger(this._element, EVENT_HIDE$6);\n if (startEvent.defaultPrevented) {\n return;\n }\n const dimension = this._getDimension();\n this._element.style[dimension] = `${this._element.getBoundingClientRect()[dimension]}px`;\n reflow(this._element);\n this._element.classList.add(CLASS_NAME_COLLAPSING);\n this._element.classList.remove(CLASS_NAME_COLLAPSE, CLASS_NAME_SHOW$7);\n for (const trigger of this._triggerArray) {\n const element = SelectorEngine.getElementFromSelector(trigger);\n if (element && !this._isShown(element)) {\n this._addAriaAndCollapsedClass([trigger], false);\n }\n }\n this._isTransitioning = true;\n const complete = () => {\n this._isTransitioning = false;\n this._element.classList.remove(CLASS_NAME_COLLAPSING);\n this._element.classList.add(CLASS_NAME_COLLAPSE);\n EventHandler.trigger(this._element, EVENT_HIDDEN$6);\n };\n this._element.style[dimension] = '';\n this._queueCallback(complete, this._element, true);\n }\n _isShown(element = this._element) {\n return element.classList.contains(CLASS_NAME_SHOW$7);\n }\n\n // Private\n _configAfterMerge(config) {\n config.toggle = Boolean(config.toggle); // Coerce string values\n config.parent = getElement(config.parent);\n return config;\n }\n _getDimension() {\n return this._element.classList.contains(CLASS_NAME_HORIZONTAL) ? WIDTH : HEIGHT;\n }\n _initializeChildren() {\n if (!this._config.parent) {\n return;\n }\n const children = this._getFirstLevelChildren(SELECTOR_DATA_TOGGLE$4);\n for (const element of children) {\n const selected = SelectorEngine.getElementFromSelector(element);\n if (selected) {\n this._addAriaAndCollapsedClass([element], this._isShown(selected));\n }\n }\n }\n _getFirstLevelChildren(selector) {\n const children = SelectorEngine.find(CLASS_NAME_DEEPER_CHILDREN, this._config.parent);\n // remove children if greater depth\n return SelectorEngine.find(selector, this._config.parent).filter(element => !children.includes(element));\n }\n _addAriaAndCollapsedClass(triggerArray, isOpen) {\n if (!triggerArray.length) {\n return;\n }\n for (const element of triggerArray) {\n element.classList.toggle(CLASS_NAME_COLLAPSED, !isOpen);\n element.setAttribute('aria-expanded', isOpen);\n }\n }\n\n // Static\n static jQueryInterface(config) {\n const _config = {};\n if (typeof config === 'string' && /show|hide/.test(config)) {\n _config.toggle = false;\n }\n return this.each(function () {\n const data = Collapse.getOrCreateInstance(this, _config);\n if (typeof config === 'string') {\n if (typeof data[config] === 'undefined') {\n throw new TypeError(`No method named \"${config}\"`);\n }\n data[config]();\n }\n });\n }\n}\n\n/**\n * Data API implementation\n */\n\nEventHandler.on(document, EVENT_CLICK_DATA_API$4, SELECTOR_DATA_TOGGLE$4, function (event) {\n // preventDefault only for elements (which change the URL) not inside the collapsible element\n if (event.target.tagName === 'A' || event.delegateTarget && event.delegateTarget.tagName === 'A') {\n event.preventDefault();\n }\n for (const element of SelectorEngine.getMultipleElementsFromSelector(this)) {\n Collapse.getOrCreateInstance(element, {\n toggle: false\n }).toggle();\n }\n});\n\n/**\n * jQuery\n */\n\ndefineJQueryPlugin(Collapse);\n\n/**\n * --------------------------------------------------------------------------\n * Bootstrap dropdown.js\n * Licensed under MIT (https://github.com/twbs/bootstrap/blob/main/LICENSE)\n * --------------------------------------------------------------------------\n */\n\n\n/**\n * Constants\n */\n\nconst NAME$a = 'dropdown';\nconst DATA_KEY$6 = 'bs.dropdown';\nconst EVENT_KEY$6 = `.${DATA_KEY$6}`;\nconst DATA_API_KEY$3 = '.data-api';\nconst ESCAPE_KEY$2 = 'Escape';\nconst TAB_KEY$1 = 'Tab';\nconst ARROW_UP_KEY$1 = 'ArrowUp';\nconst ARROW_DOWN_KEY$1 = 'ArrowDown';\nconst RIGHT_MOUSE_BUTTON = 2; // MouseEvent.button value for the secondary button, usually the right button\n\nconst EVENT_HIDE$5 = `hide${EVENT_KEY$6}`;\nconst EVENT_HIDDEN$5 = `hidden${EVENT_KEY$6}`;\nconst EVENT_SHOW$5 = `show${EVENT_KEY$6}`;\nconst EVENT_SHOWN$5 = `shown${EVENT_KEY$6}`;\nconst EVENT_CLICK_DATA_API$3 = `click${EVENT_KEY$6}${DATA_API_KEY$3}`;\nconst EVENT_KEYDOWN_DATA_API = `keydown${EVENT_KEY$6}${DATA_API_KEY$3}`;\nconst EVENT_KEYUP_DATA_API = `keyup${EVENT_KEY$6}${DATA_API_KEY$3}`;\nconst CLASS_NAME_SHOW$6 = 'show';\nconst CLASS_NAME_DROPUP = 'dropup';\nconst CLASS_NAME_DROPEND = 'dropend';\nconst CLASS_NAME_DROPSTART = 'dropstart';\nconst CLASS_NAME_DROPUP_CENTER = 'dropup-center';\nconst CLASS_NAME_DROPDOWN_CENTER = 'dropdown-center';\nconst SELECTOR_DATA_TOGGLE$3 = '[data-bs-toggle=\"dropdown\"]:not(.disabled):not(:disabled)';\nconst SELECTOR_DATA_TOGGLE_SHOWN = `${SELECTOR_DATA_TOGGLE$3}.${CLASS_NAME_SHOW$6}`;\nconst SELECTOR_MENU = '.dropdown-menu';\nconst SELECTOR_NAVBAR = '.navbar';\nconst SELECTOR_NAVBAR_NAV = '.navbar-nav';\nconst SELECTOR_VISIBLE_ITEMS = '.dropdown-menu .dropdown-item:not(.disabled):not(:disabled)';\nconst PLACEMENT_TOP = isRTL() ? 'top-end' : 'top-start';\nconst PLACEMENT_TOPEND = isRTL() ? 'top-start' : 'top-end';\nconst PLACEMENT_BOTTOM = isRTL() ? 'bottom-end' : 'bottom-start';\nconst PLACEMENT_BOTTOMEND = isRTL() ? 'bottom-start' : 'bottom-end';\nconst PLACEMENT_RIGHT = isRTL() ? 'left-start' : 'right-start';\nconst PLACEMENT_LEFT = isRTL() ? 'right-start' : 'left-start';\nconst PLACEMENT_TOPCENTER = 'top';\nconst PLACEMENT_BOTTOMCENTER = 'bottom';\nconst Default$9 = {\n autoClose: true,\n boundary: 'clippingParents',\n display: 'dynamic',\n offset: [0, 2],\n popperConfig: null,\n reference: 'toggle'\n};\nconst DefaultType$9 = {\n autoClose: '(boolean|string)',\n boundary: '(string|element)',\n display: 'string',\n offset: '(array|string|function)',\n popperConfig: '(null|object|function)',\n reference: '(string|element|object)'\n};\n\n/**\n * Class definition\n */\n\nclass Dropdown extends BaseComponent {\n constructor(element, config) {\n super(element, config);\n this._popper = null;\n this._parent = this._element.parentNode; // dropdown wrapper\n // TODO: v6 revert #37011 & change markup https://getbootstrap.com/docs/5.3/forms/input-group/\n this._menu = SelectorEngine.next(this._element, SELECTOR_MENU)[0] || SelectorEngine.prev(this._element, SELECTOR_MENU)[0] || SelectorEngine.findOne(SELECTOR_MENU, this._parent);\n this._inNavbar = this._detectNavbar();\n }\n\n // Getters\n static get Default() {\n return Default$9;\n }\n static get DefaultType() {\n return DefaultType$9;\n }\n static get NAME() {\n return NAME$a;\n }\n\n // Public\n toggle() {\n return this._isShown() ? this.hide() : this.show();\n }\n show() {\n if (isDisabled(this._element) || this._isShown()) {\n return;\n }\n const relatedTarget = {\n relatedTarget: this._element\n };\n const showEvent = EventHandler.trigger(this._element, EVENT_SHOW$5, relatedTarget);\n if (showEvent.defaultPrevented) {\n return;\n }\n this._createPopper();\n\n // If this is a touch-enabled device we add extra\n // empty mouseover listeners to the body's immediate children;\n // only needed because of broken event delegation on iOS\n // https://www.quirksmode.org/blog/archives/2014/02/mouse_event_bub.html\n if ('ontouchstart' in document.documentElement && !this._parent.closest(SELECTOR_NAVBAR_NAV)) {\n for (const element of [].concat(...document.body.children)) {\n EventHandler.on(element, 'mouseover', noop);\n }\n }\n this._element.focus();\n this._element.setAttribute('aria-expanded', true);\n this._menu.classList.add(CLASS_NAME_SHOW$6);\n this._element.classList.add(CLASS_NAME_SHOW$6);\n EventHandler.trigger(this._element, EVENT_SHOWN$5, relatedTarget);\n }\n hide() {\n if (isDisabled(this._element) || !this._isShown()) {\n return;\n }\n const relatedTarget = {\n relatedTarget: this._element\n };\n this._completeHide(relatedTarget);\n }\n dispose() {\n if (this._popper) {\n this._popper.destroy();\n }\n super.dispose();\n }\n update() {\n this._inNavbar = this._detectNavbar();\n if (this._popper) {\n this._popper.update();\n }\n }\n\n // Private\n _completeHide(relatedTarget) {\n const hideEvent = EventHandler.trigger(this._element, EVENT_HIDE$5, relatedTarget);\n if (hideEvent.defaultPrevented) {\n return;\n }\n\n // If this is a touch-enabled device we remove the extra\n // empty mouseover listeners we added for iOS support\n if ('ontouchstart' in document.documentElement) {\n for (const element of [].concat(...document.body.children)) {\n EventHandler.off(element, 'mouseover', noop);\n }\n }\n if (this._popper) {\n this._popper.destroy();\n }\n this._menu.classList.remove(CLASS_NAME_SHOW$6);\n this._element.classList.remove(CLASS_NAME_SHOW$6);\n this._element.setAttribute('aria-expanded', 'false');\n Manipulator.removeDataAttribute(this._menu, 'popper');\n EventHandler.trigger(this._element, EVENT_HIDDEN$5, relatedTarget);\n }\n _getConfig(config) {\n config = super._getConfig(config);\n if (typeof config.reference === 'object' && !isElement(config.reference) && typeof config.reference.getBoundingClientRect !== 'function') {\n // Popper virtual elements require a getBoundingClientRect method\n throw new TypeError(`${NAME$a.toUpperCase()}: Option \"reference\" provided type \"object\" without a required \"getBoundingClientRect\" method.`);\n }\n return config;\n }\n _createPopper() {\n if (typeof Popper === 'undefined') {\n throw new TypeError('Bootstrap\\'s dropdowns require Popper (https://popper.js.org)');\n }\n let referenceElement = this._element;\n if (this._config.reference === 'parent') {\n referenceElement = this._parent;\n } else if (isElement(this._config.reference)) {\n referenceElement = getElement(this._config.reference);\n } else if (typeof this._config.reference === 'object') {\n referenceElement = this._config.reference;\n }\n const popperConfig = this._getPopperConfig();\n this._popper = Popper.createPopper(referenceElement, this._menu, popperConfig);\n }\n _isShown() {\n return this._menu.classList.contains(CLASS_NAME_SHOW$6);\n }\n _getPlacement() {\n const parentDropdown = this._parent;\n if (parentDropdown.classList.contains(CLASS_NAME_DROPEND)) {\n return PLACEMENT_RIGHT;\n }\n if (parentDropdown.classList.contains(CLASS_NAME_DROPSTART)) {\n return PLACEMENT_LEFT;\n }\n if (parentDropdown.classList.contains(CLASS_NAME_DROPUP_CENTER)) {\n return PLACEMENT_TOPCENTER;\n }\n if (parentDropdown.classList.contains(CLASS_NAME_DROPDOWN_CENTER)) {\n return PLACEMENT_BOTTOMCENTER;\n }\n\n // We need to trim the value because custom properties can also include spaces\n const isEnd = getComputedStyle(this._menu).getPropertyValue('--bs-position').trim() === 'end';\n if (parentDropdown.classList.contains(CLASS_NAME_DROPUP)) {\n return isEnd ? PLACEMENT_TOPEND : PLACEMENT_TOP;\n }\n return isEnd ? PLACEMENT_BOTTOMEND : PLACEMENT_BOTTOM;\n }\n _detectNavbar() {\n return this._element.closest(SELECTOR_NAVBAR) !== null;\n }\n _getOffset() {\n const {\n offset\n } = this._config;\n if (typeof offset === 'string') {\n return offset.split(',').map(value => Number.parseInt(value, 10));\n }\n if (typeof offset === 'function') {\n return popperData => offset(popperData, this._element);\n }\n return offset;\n }\n _getPopperConfig() {\n const defaultBsPopperConfig = {\n placement: this._getPlacement(),\n modifiers: [{\n name: 'preventOverflow',\n options: {\n boundary: this._config.boundary\n }\n }, {\n name: 'offset',\n options: {\n offset: this._getOffset()\n }\n }]\n };\n\n // Disable Popper if we have a static display or Dropdown is in Navbar\n if (this._inNavbar || this._config.display === 'static') {\n Manipulator.setDataAttribute(this._menu, 'popper', 'static'); // TODO: v6 remove\n defaultBsPopperConfig.modifiers = [{\n name: 'applyStyles',\n enabled: false\n }];\n }\n return {\n ...defaultBsPopperConfig,\n ...execute(this._config.popperConfig, [defaultBsPopperConfig])\n };\n }\n _selectMenuItem({\n key,\n target\n }) {\n const items = SelectorEngine.find(SELECTOR_VISIBLE_ITEMS, this._menu).filter(element => isVisible(element));\n if (!items.length) {\n return;\n }\n\n // if target isn't included in items (e.g. when expanding the dropdown)\n // allow cycling to get the last item in case key equals ARROW_UP_KEY\n getNextActiveElement(items, target, key === ARROW_DOWN_KEY$1, !items.includes(target)).focus();\n }\n\n // Static\n static jQueryInterface(config) {\n return this.each(function () {\n const data = Dropdown.getOrCreateInstance(this, config);\n if (typeof config !== 'string') {\n return;\n }\n if (typeof data[config] === 'undefined') {\n throw new TypeError(`No method named \"${config}\"`);\n }\n data[config]();\n });\n }\n static clearMenus(event) {\n if (event.button === RIGHT_MOUSE_BUTTON || event.type === 'keyup' && event.key !== TAB_KEY$1) {\n return;\n }\n const openToggles = SelectorEngine.find(SELECTOR_DATA_TOGGLE_SHOWN);\n for (const toggle of openToggles) {\n const context = Dropdown.getInstance(toggle);\n if (!context || context._config.autoClose === false) {\n continue;\n }\n const composedPath = event.composedPath();\n const isMenuTarget = composedPath.includes(context._menu);\n if (composedPath.includes(context._element) || context._config.autoClose === 'inside' && !isMenuTarget || context._config.autoClose === 'outside' && isMenuTarget) {\n continue;\n }\n\n // Tab navigation through the dropdown menu or events from contained inputs shouldn't close the menu\n if (context._menu.contains(event.target) && (event.type === 'keyup' && event.key === TAB_KEY$1 || /input|select|option|textarea|form/i.test(event.target.tagName))) {\n continue;\n }\n const relatedTarget = {\n relatedTarget: context._element\n };\n if (event.type === 'click') {\n relatedTarget.clickEvent = event;\n }\n context._completeHide(relatedTarget);\n }\n }\n static dataApiKeydownHandler(event) {\n // If not an UP | DOWN | ESCAPE key => not a dropdown command\n // If input/textarea && if key is other than ESCAPE => not a dropdown command\n\n const isInput = /input|textarea/i.test(event.target.tagName);\n const isEscapeEvent = event.key === ESCAPE_KEY$2;\n const isUpOrDownEvent = [ARROW_UP_KEY$1, ARROW_DOWN_KEY$1].includes(event.key);\n if (!isUpOrDownEvent && !isEscapeEvent) {\n return;\n }\n if (isInput && !isEscapeEvent) {\n return;\n }\n event.preventDefault();\n\n // TODO: v6 revert #37011 & change markup https://getbootstrap.com/docs/5.3/forms/input-group/\n const getToggleButton = this.matches(SELECTOR_DATA_TOGGLE$3) ? this : SelectorEngine.prev(this, SELECTOR_DATA_TOGGLE$3)[0] || SelectorEngine.next(this, SELECTOR_DATA_TOGGLE$3)[0] || SelectorEngine.findOne(SELECTOR_DATA_TOGGLE$3, event.delegateTarget.parentNode);\n const instance = Dropdown.getOrCreateInstance(getToggleButton);\n if (isUpOrDownEvent) {\n event.stopPropagation();\n instance.show();\n instance._selectMenuItem(event);\n return;\n }\n if (instance._isShown()) {\n // else is escape and we check if it is shown\n event.stopPropagation();\n instance.hide();\n getToggleButton.focus();\n }\n }\n}\n\n/**\n * Data API implementation\n */\n\nEventHandler.on(document, EVENT_KEYDOWN_DATA_API, SELECTOR_DATA_TOGGLE$3, Dropdown.dataApiKeydownHandler);\nEventHandler.on(document, EVENT_KEYDOWN_DATA_API, SELECTOR_MENU, Dropdown.dataApiKeydownHandler);\nEventHandler.on(document, EVENT_CLICK_DATA_API$3, Dropdown.clearMenus);\nEventHandler.on(document, EVENT_KEYUP_DATA_API, Dropdown.clearMenus);\nEventHandler.on(document, EVENT_CLICK_DATA_API$3, SELECTOR_DATA_TOGGLE$3, function (event) {\n event.preventDefault();\n Dropdown.getOrCreateInstance(this).toggle();\n});\n\n/**\n * jQuery\n */\n\ndefineJQueryPlugin(Dropdown);\n\n/**\n * --------------------------------------------------------------------------\n * Bootstrap util/backdrop.js\n * Licensed under MIT (https://github.com/twbs/bootstrap/blob/main/LICENSE)\n * --------------------------------------------------------------------------\n */\n\n\n/**\n * Constants\n */\n\nconst NAME$9 = 'backdrop';\nconst CLASS_NAME_FADE$4 = 'fade';\nconst CLASS_NAME_SHOW$5 = 'show';\nconst EVENT_MOUSEDOWN = `mousedown.bs.${NAME$9}`;\nconst Default$8 = {\n className: 'modal-backdrop',\n clickCallback: null,\n isAnimated: false,\n isVisible: true,\n // if false, we use the backdrop helper without adding any element to the dom\n rootElement: 'body' // give the choice to place backdrop under different elements\n};\n\nconst DefaultType$8 = {\n className: 'string',\n clickCallback: '(function|null)',\n isAnimated: 'boolean',\n isVisible: 'boolean',\n rootElement: '(element|string)'\n};\n\n/**\n * Class definition\n */\n\nclass Backdrop extends Config {\n constructor(config) {\n super();\n this._config = this._getConfig(config);\n this._isAppended = false;\n this._element = null;\n }\n\n // Getters\n static get Default() {\n return Default$8;\n }\n static get DefaultType() {\n return DefaultType$8;\n }\n static get NAME() {\n return NAME$9;\n }\n\n // Public\n show(callback) {\n if (!this._config.isVisible) {\n execute(callback);\n return;\n }\n this._append();\n const element = this._getElement();\n if (this._config.isAnimated) {\n reflow(element);\n }\n element.classList.add(CLASS_NAME_SHOW$5);\n this._emulateAnimation(() => {\n execute(callback);\n });\n }\n hide(callback) {\n if (!this._config.isVisible) {\n execute(callback);\n return;\n }\n this._getElement().classList.remove(CLASS_NAME_SHOW$5);\n this._emulateAnimation(() => {\n this.dispose();\n execute(callback);\n });\n }\n dispose() {\n if (!this._isAppended) {\n return;\n }\n EventHandler.off(this._element, EVENT_MOUSEDOWN);\n this._element.remove();\n this._isAppended = false;\n }\n\n // Private\n _getElement() {\n if (!this._element) {\n const backdrop = document.createElement('div');\n backdrop.className = this._config.className;\n if (this._config.isAnimated) {\n backdrop.classList.add(CLASS_NAME_FADE$4);\n }\n this._element = backdrop;\n }\n return this._element;\n }\n _configAfterMerge(config) {\n // use getElement() with the default \"body\" to get a fresh Element on each instantiation\n config.rootElement = getElement(config.rootElement);\n return config;\n }\n _append() {\n if (this._isAppended) {\n return;\n }\n const element = this._getElement();\n this._config.rootElement.append(element);\n EventHandler.on(element, EVENT_MOUSEDOWN, () => {\n execute(this._config.clickCallback);\n });\n this._isAppended = true;\n }\n _emulateAnimation(callback) {\n executeAfterTransition(callback, this._getElement(), this._config.isAnimated);\n }\n}\n\n/**\n * --------------------------------------------------------------------------\n * Bootstrap util/focustrap.js\n * Licensed under MIT (https://github.com/twbs/bootstrap/blob/main/LICENSE)\n * --------------------------------------------------------------------------\n */\n\n\n/**\n * Constants\n */\n\nconst NAME$8 = 'focustrap';\nconst DATA_KEY$5 = 'bs.focustrap';\nconst EVENT_KEY$5 = `.${DATA_KEY$5}`;\nconst EVENT_FOCUSIN$2 = `focusin${EVENT_KEY$5}`;\nconst EVENT_KEYDOWN_TAB = `keydown.tab${EVENT_KEY$5}`;\nconst TAB_KEY = 'Tab';\nconst TAB_NAV_FORWARD = 'forward';\nconst TAB_NAV_BACKWARD = 'backward';\nconst Default$7 = {\n autofocus: true,\n trapElement: null // The element to trap focus inside of\n};\n\nconst DefaultType$7 = {\n autofocus: 'boolean',\n trapElement: 'element'\n};\n\n/**\n * Class definition\n */\n\nclass FocusTrap extends Config {\n constructor(config) {\n super();\n this._config = this._getConfig(config);\n this._isActive = false;\n this._lastTabNavDirection = null;\n }\n\n // Getters\n static get Default() {\n return Default$7;\n }\n static get DefaultType() {\n return DefaultType$7;\n }\n static get NAME() {\n return NAME$8;\n }\n\n // Public\n activate() {\n if (this._isActive) {\n return;\n }\n if (this._config.autofocus) {\n this._config.trapElement.focus();\n }\n EventHandler.off(document, EVENT_KEY$5); // guard against infinite focus loop\n EventHandler.on(document, EVENT_FOCUSIN$2, event => this._handleFocusin(event));\n EventHandler.on(document, EVENT_KEYDOWN_TAB, event => this._handleKeydown(event));\n this._isActive = true;\n }\n deactivate() {\n if (!this._isActive) {\n return;\n }\n this._isActive = false;\n EventHandler.off(document, EVENT_KEY$5);\n }\n\n // Private\n _handleFocusin(event) {\n const {\n trapElement\n } = this._config;\n if (event.target === document || event.target === trapElement || trapElement.contains(event.target)) {\n return;\n }\n const elements = SelectorEngine.focusableChildren(trapElement);\n if (elements.length === 0) {\n trapElement.focus();\n } else if (this._lastTabNavDirection === TAB_NAV_BACKWARD) {\n elements[elements.length - 1].focus();\n } else {\n elements[0].focus();\n }\n }\n _handleKeydown(event) {\n if (event.key !== TAB_KEY) {\n return;\n }\n this._lastTabNavDirection = event.shiftKey ? TAB_NAV_BACKWARD : TAB_NAV_FORWARD;\n }\n}\n\n/**\n * --------------------------------------------------------------------------\n * Bootstrap util/scrollBar.js\n * Licensed under MIT (https://github.com/twbs/bootstrap/blob/main/LICENSE)\n * --------------------------------------------------------------------------\n */\n\n\n/**\n * Constants\n */\n\nconst SELECTOR_FIXED_CONTENT = '.fixed-top, .fixed-bottom, .is-fixed, .sticky-top';\nconst SELECTOR_STICKY_CONTENT = '.sticky-top';\nconst PROPERTY_PADDING = 'padding-right';\nconst PROPERTY_MARGIN = 'margin-right';\n\n/**\n * Class definition\n */\n\nclass ScrollBarHelper {\n constructor() {\n this._element = document.body;\n }\n\n // Public\n getWidth() {\n // https://developer.mozilla.org/en-US/docs/Web/API/Window/innerWidth#usage_notes\n const documentWidth = document.documentElement.clientWidth;\n return Math.abs(window.innerWidth - documentWidth);\n }\n hide() {\n const width = this.getWidth();\n this._disableOverFlow();\n // give padding to element to balance the hidden scrollbar width\n this._setElementAttributes(this._element, PROPERTY_PADDING, calculatedValue => calculatedValue + width);\n // trick: We adjust positive paddingRight and negative marginRight to sticky-top elements to keep showing fullwidth\n this._setElementAttributes(SELECTOR_FIXED_CONTENT, PROPERTY_PADDING, calculatedValue => calculatedValue + width);\n this._setElementAttributes(SELECTOR_STICKY_CONTENT, PROPERTY_MARGIN, calculatedValue => calculatedValue - width);\n }\n reset() {\n this._resetElementAttributes(this._element, 'overflow');\n this._resetElementAttributes(this._element, PROPERTY_PADDING);\n this._resetElementAttributes(SELECTOR_FIXED_CONTENT, PROPERTY_PADDING);\n this._resetElementAttributes(SELECTOR_STICKY_CONTENT, PROPERTY_MARGIN);\n }\n isOverflowing() {\n return this.getWidth() > 0;\n }\n\n // Private\n _disableOverFlow() {\n this._saveInitialAttribute(this._element, 'overflow');\n this._element.style.overflow = 'hidden';\n }\n _setElementAttributes(selector, styleProperty, callback) {\n const scrollbarWidth = this.getWidth();\n const manipulationCallBack = element => {\n if (element !== this._element && window.innerWidth > element.clientWidth + scrollbarWidth) {\n return;\n }\n this._saveInitialAttribute(element, styleProperty);\n const calculatedValue = window.getComputedStyle(element).getPropertyValue(styleProperty);\n element.style.setProperty(styleProperty, `${callback(Number.parseFloat(calculatedValue))}px`);\n };\n this._applyManipulationCallback(selector, manipulationCallBack);\n }\n _saveInitialAttribute(element, styleProperty) {\n const actualValue = element.style.getPropertyValue(styleProperty);\n if (actualValue) {\n Manipulator.setDataAttribute(element, styleProperty, actualValue);\n }\n }\n _resetElementAttributes(selector, styleProperty) {\n const manipulationCallBack = element => {\n const value = Manipulator.getDataAttribute(element, styleProperty);\n // We only want to remove the property if the value is `null`; the value can also be zero\n if (value === null) {\n element.style.removeProperty(styleProperty);\n return;\n }\n Manipulator.removeDataAttribute(element, styleProperty);\n element.style.setProperty(styleProperty, value);\n };\n this._applyManipulationCallback(selector, manipulationCallBack);\n }\n _applyManipulationCallback(selector, callBack) {\n if (isElement(selector)) {\n callBack(selector);\n return;\n }\n for (const sel of SelectorEngine.find(selector, this._element)) {\n callBack(sel);\n }\n }\n}\n\n/**\n * --------------------------------------------------------------------------\n * Bootstrap modal.js\n * Licensed under MIT (https://github.com/twbs/bootstrap/blob/main/LICENSE)\n * --------------------------------------------------------------------------\n */\n\n\n/**\n * Constants\n */\n\nconst NAME$7 = 'modal';\nconst DATA_KEY$4 = 'bs.modal';\nconst EVENT_KEY$4 = `.${DATA_KEY$4}`;\nconst DATA_API_KEY$2 = '.data-api';\nconst ESCAPE_KEY$1 = 'Escape';\nconst EVENT_HIDE$4 = `hide${EVENT_KEY$4}`;\nconst EVENT_HIDE_PREVENTED$1 = `hidePrevented${EVENT_KEY$4}`;\nconst EVENT_HIDDEN$4 = `hidden${EVENT_KEY$4}`;\nconst EVENT_SHOW$4 = `show${EVENT_KEY$4}`;\nconst EVENT_SHOWN$4 = `shown${EVENT_KEY$4}`;\nconst EVENT_RESIZE$1 = `resize${EVENT_KEY$4}`;\nconst EVENT_CLICK_DISMISS = `click.dismiss${EVENT_KEY$4}`;\nconst EVENT_MOUSEDOWN_DISMISS = `mousedown.dismiss${EVENT_KEY$4}`;\nconst EVENT_KEYDOWN_DISMISS$1 = `keydown.dismiss${EVENT_KEY$4}`;\nconst EVENT_CLICK_DATA_API$2 = `click${EVENT_KEY$4}${DATA_API_KEY$2}`;\nconst CLASS_NAME_OPEN = 'modal-open';\nconst CLASS_NAME_FADE$3 = 'fade';\nconst CLASS_NAME_SHOW$4 = 'show';\nconst CLASS_NAME_STATIC = 'modal-static';\nconst OPEN_SELECTOR$1 = '.modal.show';\nconst SELECTOR_DIALOG = '.modal-dialog';\nconst SELECTOR_MODAL_BODY = '.modal-body';\nconst SELECTOR_DATA_TOGGLE$2 = '[data-bs-toggle=\"modal\"]';\nconst Default$6 = {\n backdrop: true,\n focus: true,\n keyboard: true\n};\nconst DefaultType$6 = {\n backdrop: '(boolean|string)',\n focus: 'boolean',\n keyboard: 'boolean'\n};\n\n/**\n * Class definition\n */\n\nclass Modal extends BaseComponent {\n constructor(element, config) {\n super(element, config);\n this._dialog = SelectorEngine.findOne(SELECTOR_DIALOG, this._element);\n this._backdrop = this._initializeBackDrop();\n this._focustrap = this._initializeFocusTrap();\n this._isShown = false;\n this._isTransitioning = false;\n this._scrollBar = new ScrollBarHelper();\n this._addEventListeners();\n }\n\n // Getters\n static get Default() {\n return Default$6;\n }\n static get DefaultType() {\n return DefaultType$6;\n }\n static get NAME() {\n return NAME$7;\n }\n\n // Public\n toggle(relatedTarget) {\n return this._isShown ? this.hide() : this.show(relatedTarget);\n }\n show(relatedTarget) {\n if (this._isShown || this._isTransitioning) {\n return;\n }\n const showEvent = EventHandler.trigger(this._element, EVENT_SHOW$4, {\n relatedTarget\n });\n if (showEvent.defaultPrevented) {\n return;\n }\n this._isShown = true;\n this._isTransitioning = true;\n this._scrollBar.hide();\n document.body.classList.add(CLASS_NAME_OPEN);\n this._adjustDialog();\n this._backdrop.show(() => this._showElement(relatedTarget));\n }\n hide() {\n if (!this._isShown || this._isTransitioning) {\n return;\n }\n const hideEvent = EventHandler.trigger(this._element, EVENT_HIDE$4);\n if (hideEvent.defaultPrevented) {\n return;\n }\n this._isShown = false;\n this._isTransitioning = true;\n this._focustrap.deactivate();\n this._element.classList.remove(CLASS_NAME_SHOW$4);\n this._queueCallback(() => this._hideModal(), this._element, this._isAnimated());\n }\n dispose() {\n EventHandler.off(window, EVENT_KEY$4);\n EventHandler.off(this._dialog, EVENT_KEY$4);\n this._backdrop.dispose();\n this._focustrap.deactivate();\n super.dispose();\n }\n handleUpdate() {\n this._adjustDialog();\n }\n\n // Private\n _initializeBackDrop() {\n return new Backdrop({\n isVisible: Boolean(this._config.backdrop),\n // 'static' option will be translated to true, and booleans will keep their value,\n isAnimated: this._isAnimated()\n });\n }\n _initializeFocusTrap() {\n return new FocusTrap({\n trapElement: this._element\n });\n }\n _showElement(relatedTarget) {\n // try to append dynamic modal\n if (!document.body.contains(this._element)) {\n document.body.append(this._element);\n }\n this._element.style.display = 'block';\n this._element.removeAttribute('aria-hidden');\n this._element.setAttribute('aria-modal', true);\n this._element.setAttribute('role', 'dialog');\n this._element.scrollTop = 0;\n const modalBody = SelectorEngine.findOne(SELECTOR_MODAL_BODY, this._dialog);\n if (modalBody) {\n modalBody.scrollTop = 0;\n }\n reflow(this._element);\n this._element.classList.add(CLASS_NAME_SHOW$4);\n const transitionComplete = () => {\n if (this._config.focus) {\n this._focustrap.activate();\n }\n this._isTransitioning = false;\n EventHandler.trigger(this._element, EVENT_SHOWN$4, {\n relatedTarget\n });\n };\n this._queueCallback(transitionComplete, this._dialog, this._isAnimated());\n }\n _addEventListeners() {\n EventHandler.on(this._element, EVENT_KEYDOWN_DISMISS$1, event => {\n if (event.key !== ESCAPE_KEY$1) {\n return;\n }\n if (this._config.keyboard) {\n this.hide();\n return;\n }\n this._triggerBackdropTransition();\n });\n EventHandler.on(window, EVENT_RESIZE$1, () => {\n if (this._isShown && !this._isTransitioning) {\n this._adjustDialog();\n }\n });\n EventHandler.on(this._element, EVENT_MOUSEDOWN_DISMISS, event => {\n // a bad trick to segregate clicks that may start inside dialog but end outside, and avoid listen to scrollbar clicks\n EventHandler.one(this._element, EVENT_CLICK_DISMISS, event2 => {\n if (this._element !== event.target || this._element !== event2.target) {\n return;\n }\n if (this._config.backdrop === 'static') {\n this._triggerBackdropTransition();\n return;\n }\n if (this._config.backdrop) {\n this.hide();\n }\n });\n });\n }\n _hideModal() {\n this._element.style.display = 'none';\n this._element.setAttribute('aria-hidden', true);\n this._element.removeAttribute('aria-modal');\n this._element.removeAttribute('role');\n this._isTransitioning = false;\n this._backdrop.hide(() => {\n document.body.classList.remove(CLASS_NAME_OPEN);\n this._resetAdjustments();\n this._scrollBar.reset();\n EventHandler.trigger(this._element, EVENT_HIDDEN$4);\n });\n }\n _isAnimated() {\n return this._element.classList.contains(CLASS_NAME_FADE$3);\n }\n _triggerBackdropTransition() {\n const hideEvent = EventHandler.trigger(this._element, EVENT_HIDE_PREVENTED$1);\n if (hideEvent.defaultPrevented) {\n return;\n }\n const isModalOverflowing = this._element.scrollHeight > document.documentElement.clientHeight;\n const initialOverflowY = this._element.style.overflowY;\n // return if the following background transition hasn't yet completed\n if (initialOverflowY === 'hidden' || this._element.classList.contains(CLASS_NAME_STATIC)) {\n return;\n }\n if (!isModalOverflowing) {\n this._element.style.overflowY = 'hidden';\n }\n this._element.classList.add(CLASS_NAME_STATIC);\n this._queueCallback(() => {\n this._element.classList.remove(CLASS_NAME_STATIC);\n this._queueCallback(() => {\n this._element.style.overflowY = initialOverflowY;\n }, this._dialog);\n }, this._dialog);\n this._element.focus();\n }\n\n /**\n * The following methods are used to handle overflowing modals\n */\n\n _adjustDialog() {\n const isModalOverflowing = this._element.scrollHeight > document.documentElement.clientHeight;\n const scrollbarWidth = this._scrollBar.getWidth();\n const isBodyOverflowing = scrollbarWidth > 0;\n if (isBodyOverflowing && !isModalOverflowing) {\n const property = isRTL() ? 'paddingLeft' : 'paddingRight';\n this._element.style[property] = `${scrollbarWidth}px`;\n }\n if (!isBodyOverflowing && isModalOverflowing) {\n const property = isRTL() ? 'paddingRight' : 'paddingLeft';\n this._element.style[property] = `${scrollbarWidth}px`;\n }\n }\n _resetAdjustments() {\n this._element.style.paddingLeft = '';\n this._element.style.paddingRight = '';\n }\n\n // Static\n static jQueryInterface(config, relatedTarget) {\n return this.each(function () {\n const data = Modal.getOrCreateInstance(this, config);\n if (typeof config !== 'string') {\n return;\n }\n if (typeof data[config] === 'undefined') {\n throw new TypeError(`No method named \"${config}\"`);\n }\n data[config](relatedTarget);\n });\n }\n}\n\n/**\n * Data API implementation\n */\n\nEventHandler.on(document, EVENT_CLICK_DATA_API$2, SELECTOR_DATA_TOGGLE$2, function (event) {\n const target = SelectorEngine.getElementFromSelector(this);\n if (['A', 'AREA'].includes(this.tagName)) {\n event.preventDefault();\n }\n EventHandler.one(target, EVENT_SHOW$4, showEvent => {\n if (showEvent.defaultPrevented) {\n // only register focus restorer if modal will actually get shown\n return;\n }\n EventHandler.one(target, EVENT_HIDDEN$4, () => {\n if (isVisible(this)) {\n this.focus();\n }\n });\n });\n\n // avoid conflict when clicking modal toggler while another one is open\n const alreadyOpen = SelectorEngine.findOne(OPEN_SELECTOR$1);\n if (alreadyOpen) {\n Modal.getInstance(alreadyOpen).hide();\n }\n const data = Modal.getOrCreateInstance(target);\n data.toggle(this);\n});\nenableDismissTrigger(Modal);\n\n/**\n * jQuery\n */\n\ndefineJQueryPlugin(Modal);\n\n/**\n * --------------------------------------------------------------------------\n * Bootstrap offcanvas.js\n * Licensed under MIT (https://github.com/twbs/bootstrap/blob/main/LICENSE)\n * --------------------------------------------------------------------------\n */\n\n\n/**\n * Constants\n */\n\nconst NAME$6 = 'offcanvas';\nconst DATA_KEY$3 = 'bs.offcanvas';\nconst EVENT_KEY$3 = `.${DATA_KEY$3}`;\nconst DATA_API_KEY$1 = '.data-api';\nconst EVENT_LOAD_DATA_API$2 = `load${EVENT_KEY$3}${DATA_API_KEY$1}`;\nconst ESCAPE_KEY = 'Escape';\nconst CLASS_NAME_SHOW$3 = 'show';\nconst CLASS_NAME_SHOWING$1 = 'showing';\nconst CLASS_NAME_HIDING = 'hiding';\nconst CLASS_NAME_BACKDROP = 'offcanvas-backdrop';\nconst OPEN_SELECTOR = '.offcanvas.show';\nconst EVENT_SHOW$3 = `show${EVENT_KEY$3}`;\nconst EVENT_SHOWN$3 = `shown${EVENT_KEY$3}`;\nconst EVENT_HIDE$3 = `hide${EVENT_KEY$3}`;\nconst EVENT_HIDE_PREVENTED = `hidePrevented${EVENT_KEY$3}`;\nconst EVENT_HIDDEN$3 = `hidden${EVENT_KEY$3}`;\nconst EVENT_RESIZE = `resize${EVENT_KEY$3}`;\nconst EVENT_CLICK_DATA_API$1 = `click${EVENT_KEY$3}${DATA_API_KEY$1}`;\nconst EVENT_KEYDOWN_DISMISS = `keydown.dismiss${EVENT_KEY$3}`;\nconst SELECTOR_DATA_TOGGLE$1 = '[data-bs-toggle=\"offcanvas\"]';\nconst Default$5 = {\n backdrop: true,\n keyboard: true,\n scroll: false\n};\nconst DefaultType$5 = {\n backdrop: '(boolean|string)',\n keyboard: 'boolean',\n scroll: 'boolean'\n};\n\n/**\n * Class definition\n */\n\nclass Offcanvas extends BaseComponent {\n constructor(element, config) {\n super(element, config);\n this._isShown = false;\n this._backdrop = this._initializeBackDrop();\n this._focustrap = this._initializeFocusTrap();\n this._addEventListeners();\n }\n\n // Getters\n static get Default() {\n return Default$5;\n }\n static get DefaultType() {\n return DefaultType$5;\n }\n static get NAME() {\n return NAME$6;\n }\n\n // Public\n toggle(relatedTarget) {\n return this._isShown ? this.hide() : this.show(relatedTarget);\n }\n show(relatedTarget) {\n if (this._isShown) {\n return;\n }\n const showEvent = EventHandler.trigger(this._element, EVENT_SHOW$3, {\n relatedTarget\n });\n if (showEvent.defaultPrevented) {\n return;\n }\n this._isShown = true;\n this._backdrop.show();\n if (!this._config.scroll) {\n new ScrollBarHelper().hide();\n }\n this._element.setAttribute('aria-modal', true);\n this._element.setAttribute('role', 'dialog');\n this._element.classList.add(CLASS_NAME_SHOWING$1);\n const completeCallBack = () => {\n if (!this._config.scroll || this._config.backdrop) {\n this._focustrap.activate();\n }\n this._element.classList.add(CLASS_NAME_SHOW$3);\n this._element.classList.remove(CLASS_NAME_SHOWING$1);\n EventHandler.trigger(this._element, EVENT_SHOWN$3, {\n relatedTarget\n });\n };\n this._queueCallback(completeCallBack, this._element, true);\n }\n hide() {\n if (!this._isShown) {\n return;\n }\n const hideEvent = EventHandler.trigger(this._element, EVENT_HIDE$3);\n if (hideEvent.defaultPrevented) {\n return;\n }\n this._focustrap.deactivate();\n this._element.blur();\n this._isShown = false;\n this._element.classList.add(CLASS_NAME_HIDING);\n this._backdrop.hide();\n const completeCallback = () => {\n this._element.classList.remove(CLASS_NAME_SHOW$3, CLASS_NAME_HIDING);\n this._element.removeAttribute('aria-modal');\n this._element.removeAttribute('role');\n if (!this._config.scroll) {\n new ScrollBarHelper().reset();\n }\n EventHandler.trigger(this._element, EVENT_HIDDEN$3);\n };\n this._queueCallback(completeCallback, this._element, true);\n }\n dispose() {\n this._backdrop.dispose();\n this._focustrap.deactivate();\n super.dispose();\n }\n\n // Private\n _initializeBackDrop() {\n const clickCallback = () => {\n if (this._config.backdrop === 'static') {\n EventHandler.trigger(this._element, EVENT_HIDE_PREVENTED);\n return;\n }\n this.hide();\n };\n\n // 'static' option will be translated to true, and booleans will keep their value\n const isVisible = Boolean(this._config.backdrop);\n return new Backdrop({\n className: CLASS_NAME_BACKDROP,\n isVisible,\n isAnimated: true,\n rootElement: this._element.parentNode,\n clickCallback: isVisible ? clickCallback : null\n });\n }\n _initializeFocusTrap() {\n return new FocusTrap({\n trapElement: this._element\n });\n }\n _addEventListeners() {\n EventHandler.on(this._element, EVENT_KEYDOWN_DISMISS, event => {\n if (event.key !== ESCAPE_KEY) {\n return;\n }\n if (this._config.keyboard) {\n this.hide();\n return;\n }\n EventHandler.trigger(this._element, EVENT_HIDE_PREVENTED);\n });\n }\n\n // Static\n static jQueryInterface(config) {\n return this.each(function () {\n const data = Offcanvas.getOrCreateInstance(this, config);\n if (typeof config !== 'string') {\n return;\n }\n if (data[config] === undefined || config.startsWith('_') || config === 'constructor') {\n throw new TypeError(`No method named \"${config}\"`);\n }\n data[config](this);\n });\n }\n}\n\n/**\n * Data API implementation\n */\n\nEventHandler.on(document, EVENT_CLICK_DATA_API$1, SELECTOR_DATA_TOGGLE$1, function (event) {\n const target = SelectorEngine.getElementFromSelector(this);\n if (['A', 'AREA'].includes(this.tagName)) {\n event.preventDefault();\n }\n if (isDisabled(this)) {\n return;\n }\n EventHandler.one(target, EVENT_HIDDEN$3, () => {\n // focus on trigger when it is closed\n if (isVisible(this)) {\n this.focus();\n }\n });\n\n // avoid conflict when clicking a toggler of an offcanvas, while another is open\n const alreadyOpen = SelectorEngine.findOne(OPEN_SELECTOR);\n if (alreadyOpen && alreadyOpen !== target) {\n Offcanvas.getInstance(alreadyOpen).hide();\n }\n const data = Offcanvas.getOrCreateInstance(target);\n data.toggle(this);\n});\nEventHandler.on(window, EVENT_LOAD_DATA_API$2, () => {\n for (const selector of SelectorEngine.find(OPEN_SELECTOR)) {\n Offcanvas.getOrCreateInstance(selector).show();\n }\n});\nEventHandler.on(window, EVENT_RESIZE, () => {\n for (const element of SelectorEngine.find('[aria-modal][class*=show][class*=offcanvas-]')) {\n if (getComputedStyle(element).position !== 'fixed') {\n Offcanvas.getOrCreateInstance(element).hide();\n }\n }\n});\nenableDismissTrigger(Offcanvas);\n\n/**\n * jQuery\n */\n\ndefineJQueryPlugin(Offcanvas);\n\n/**\n * --------------------------------------------------------------------------\n * Bootstrap util/sanitizer.js\n * Licensed under MIT (https://github.com/twbs/bootstrap/blob/main/LICENSE)\n * --------------------------------------------------------------------------\n */\n\n// js-docs-start allow-list\nconst ARIA_ATTRIBUTE_PATTERN = /^aria-[\\w-]*$/i;\nconst DefaultAllowlist = {\n // Global attributes allowed on any supplied element below.\n '*': ['class', 'dir', 'id', 'lang', 'role', ARIA_ATTRIBUTE_PATTERN],\n a: ['target', 'href', 'title', 'rel'],\n area: [],\n b: [],\n br: [],\n col: [],\n code: [],\n div: [],\n em: [],\n hr: [],\n h1: [],\n h2: [],\n h3: [],\n h4: [],\n h5: [],\n h6: [],\n i: [],\n img: ['src', 'srcset', 'alt', 'title', 'width', 'height'],\n li: [],\n ol: [],\n p: [],\n pre: [],\n s: [],\n small: [],\n span: [],\n sub: [],\n sup: [],\n strong: [],\n u: [],\n ul: []\n};\n// js-docs-end allow-list\n\nconst uriAttributes = new Set(['background', 'cite', 'href', 'itemtype', 'longdesc', 'poster', 'src', 'xlink:href']);\n\n/**\n * A pattern that recognizes URLs that are safe wrt. XSS in URL navigation\n * contexts.\n *\n * Shout-out to Angular https://github.com/angular/angular/blob/15.2.8/packages/core/src/sanitization/url_sanitizer.ts#L38\n */\n// eslint-disable-next-line unicorn/better-regex\nconst SAFE_URL_PATTERN = /^(?!javascript:)(?:[a-z0-9+.-]+:|[^&:/?#]*(?:[/?#]|$))/i;\nconst allowedAttribute = (attribute, allowedAttributeList) => {\n const attributeName = attribute.nodeName.toLowerCase();\n if (allowedAttributeList.includes(attributeName)) {\n if (uriAttributes.has(attributeName)) {\n return Boolean(SAFE_URL_PATTERN.test(attribute.nodeValue));\n }\n return true;\n }\n\n // Check if a regular expression validates the attribute.\n return allowedAttributeList.filter(attributeRegex => attributeRegex instanceof RegExp).some(regex => regex.test(attributeName));\n};\nfunction sanitizeHtml(unsafeHtml, allowList, sanitizeFunction) {\n if (!unsafeHtml.length) {\n return unsafeHtml;\n }\n if (sanitizeFunction && typeof sanitizeFunction === 'function') {\n return sanitizeFunction(unsafeHtml);\n }\n const domParser = new window.DOMParser();\n const createdDocument = domParser.parseFromString(unsafeHtml, 'text/html');\n const elements = [].concat(...createdDocument.body.querySelectorAll('*'));\n for (const element of elements) {\n const elementName = element.nodeName.toLowerCase();\n if (!Object.keys(allowList).includes(elementName)) {\n element.remove();\n continue;\n }\n const attributeList = [].concat(...element.attributes);\n const allowedAttributes = [].concat(allowList['*'] || [], allowList[elementName] || []);\n for (const attribute of attributeList) {\n if (!allowedAttribute(attribute, allowedAttributes)) {\n element.removeAttribute(attribute.nodeName);\n }\n }\n }\n return createdDocument.body.innerHTML;\n}\n\n/**\n * --------------------------------------------------------------------------\n * Bootstrap util/template-factory.js\n * Licensed under MIT (https://github.com/twbs/bootstrap/blob/main/LICENSE)\n * --------------------------------------------------------------------------\n */\n\n\n/**\n * Constants\n */\n\nconst NAME$5 = 'TemplateFactory';\nconst Default$4 = {\n allowList: DefaultAllowlist,\n content: {},\n // { selector : text , selector2 : text2 , }\n extraClass: '',\n html: false,\n sanitize: true,\n sanitizeFn: null,\n template: '
'\n};\nconst DefaultType$4 = {\n allowList: 'object',\n content: 'object',\n extraClass: '(string|function)',\n html: 'boolean',\n sanitize: 'boolean',\n sanitizeFn: '(null|function)',\n template: 'string'\n};\nconst DefaultContentType = {\n entry: '(string|element|function|null)',\n selector: '(string|element)'\n};\n\n/**\n * Class definition\n */\n\nclass TemplateFactory extends Config {\n constructor(config) {\n super();\n this._config = this._getConfig(config);\n }\n\n // Getters\n static get Default() {\n return Default$4;\n }\n static get DefaultType() {\n return DefaultType$4;\n }\n static get NAME() {\n return NAME$5;\n }\n\n // Public\n getContent() {\n return Object.values(this._config.content).map(config => this._resolvePossibleFunction(config)).filter(Boolean);\n }\n hasContent() {\n return this.getContent().length > 0;\n }\n changeContent(content) {\n this._checkContent(content);\n this._config.content = {\n ...this._config.content,\n ...content\n };\n return this;\n }\n toHtml() {\n const templateWrapper = document.createElement('div');\n templateWrapper.innerHTML = this._maybeSanitize(this._config.template);\n for (const [selector, text] of Object.entries(this._config.content)) {\n this._setContent(templateWrapper, text, selector);\n }\n const template = templateWrapper.children[0];\n const extraClass = this._resolvePossibleFunction(this._config.extraClass);\n if (extraClass) {\n template.classList.add(...extraClass.split(' '));\n }\n return template;\n }\n\n // Private\n _typeCheckConfig(config) {\n super._typeCheckConfig(config);\n this._checkContent(config.content);\n }\n _checkContent(arg) {\n for (const [selector, content] of Object.entries(arg)) {\n super._typeCheckConfig({\n selector,\n entry: content\n }, DefaultContentType);\n }\n }\n _setContent(template, content, selector) {\n const templateElement = SelectorEngine.findOne(selector, template);\n if (!templateElement) {\n return;\n }\n content = this._resolvePossibleFunction(content);\n if (!content) {\n templateElement.remove();\n return;\n }\n if (isElement(content)) {\n this._putElementInTemplate(getElement(content), templateElement);\n return;\n }\n if (this._config.html) {\n templateElement.innerHTML = this._maybeSanitize(content);\n return;\n }\n templateElement.textContent = content;\n }\n _maybeSanitize(arg) {\n return this._config.sanitize ? sanitizeHtml(arg, this._config.allowList, this._config.sanitizeFn) : arg;\n }\n _resolvePossibleFunction(arg) {\n return execute(arg, [this]);\n }\n _putElementInTemplate(element, templateElement) {\n if (this._config.html) {\n templateElement.innerHTML = '';\n templateElement.append(element);\n return;\n }\n templateElement.textContent = element.textContent;\n }\n}\n\n/**\n * --------------------------------------------------------------------------\n * Bootstrap tooltip.js\n * Licensed under MIT (https://github.com/twbs/bootstrap/blob/main/LICENSE)\n * --------------------------------------------------------------------------\n */\n\n\n/**\n * Constants\n */\n\nconst NAME$4 = 'tooltip';\nconst DISALLOWED_ATTRIBUTES = new Set(['sanitize', 'allowList', 'sanitizeFn']);\nconst CLASS_NAME_FADE$2 = 'fade';\nconst CLASS_NAME_MODAL = 'modal';\nconst CLASS_NAME_SHOW$2 = 'show';\nconst SELECTOR_TOOLTIP_INNER = '.tooltip-inner';\nconst SELECTOR_MODAL = `.${CLASS_NAME_MODAL}`;\nconst EVENT_MODAL_HIDE = 'hide.bs.modal';\nconst TRIGGER_HOVER = 'hover';\nconst TRIGGER_FOCUS = 'focus';\nconst TRIGGER_CLICK = 'click';\nconst TRIGGER_MANUAL = 'manual';\nconst EVENT_HIDE$2 = 'hide';\nconst EVENT_HIDDEN$2 = 'hidden';\nconst EVENT_SHOW$2 = 'show';\nconst EVENT_SHOWN$2 = 'shown';\nconst EVENT_INSERTED = 'inserted';\nconst EVENT_CLICK$1 = 'click';\nconst EVENT_FOCUSIN$1 = 'focusin';\nconst EVENT_FOCUSOUT$1 = 'focusout';\nconst EVENT_MOUSEENTER = 'mouseenter';\nconst EVENT_MOUSELEAVE = 'mouseleave';\nconst AttachmentMap = {\n AUTO: 'auto',\n TOP: 'top',\n RIGHT: isRTL() ? 'left' : 'right',\n BOTTOM: 'bottom',\n LEFT: isRTL() ? 'right' : 'left'\n};\nconst Default$3 = {\n allowList: DefaultAllowlist,\n animation: true,\n boundary: 'clippingParents',\n container: false,\n customClass: '',\n delay: 0,\n fallbackPlacements: ['top', 'right', 'bottom', 'left'],\n html: false,\n offset: [0, 6],\n placement: 'top',\n popperConfig: null,\n sanitize: true,\n sanitizeFn: null,\n selector: false,\n template: '
' + '
' + '
' + '
',\n title: '',\n trigger: 'hover focus'\n};\nconst DefaultType$3 = {\n allowList: 'object',\n animation: 'boolean',\n boundary: '(string|element)',\n container: '(string|element|boolean)',\n customClass: '(string|function)',\n delay: '(number|object)',\n fallbackPlacements: 'array',\n html: 'boolean',\n offset: '(array|string|function)',\n placement: '(string|function)',\n popperConfig: '(null|object|function)',\n sanitize: 'boolean',\n sanitizeFn: '(null|function)',\n selector: '(string|boolean)',\n template: 'string',\n title: '(string|element|function)',\n trigger: 'string'\n};\n\n/**\n * Class definition\n */\n\nclass Tooltip extends BaseComponent {\n constructor(element, config) {\n if (typeof Popper === 'undefined') {\n throw new TypeError('Bootstrap\\'s tooltips require Popper (https://popper.js.org)');\n }\n super(element, config);\n\n // Private\n this._isEnabled = true;\n this._timeout = 0;\n this._isHovered = null;\n this._activeTrigger = {};\n this._popper = null;\n this._templateFactory = null;\n this._newContent = null;\n\n // Protected\n this.tip = null;\n this._setListeners();\n if (!this._config.selector) {\n this._fixTitle();\n }\n }\n\n // Getters\n static get Default() {\n return Default$3;\n }\n static get DefaultType() {\n return DefaultType$3;\n }\n static get NAME() {\n return NAME$4;\n }\n\n // Public\n enable() {\n this._isEnabled = true;\n }\n disable() {\n this._isEnabled = false;\n }\n toggleEnabled() {\n this._isEnabled = !this._isEnabled;\n }\n toggle() {\n if (!this._isEnabled) {\n return;\n }\n this._activeTrigger.click = !this._activeTrigger.click;\n if (this._isShown()) {\n this._leave();\n return;\n }\n this._enter();\n }\n dispose() {\n clearTimeout(this._timeout);\n EventHandler.off(this._element.closest(SELECTOR_MODAL), EVENT_MODAL_HIDE, this._hideModalHandler);\n if (this._element.getAttribute('data-bs-original-title')) {\n this._element.setAttribute('title', this._element.getAttribute('data-bs-original-title'));\n }\n this._disposePopper();\n super.dispose();\n }\n show() {\n if (this._element.style.display === 'none') {\n throw new Error('Please use show on visible elements');\n }\n if (!(this._isWithContent() && this._isEnabled)) {\n return;\n }\n const showEvent = EventHandler.trigger(this._element, this.constructor.eventName(EVENT_SHOW$2));\n const shadowRoot = findShadowRoot(this._element);\n const isInTheDom = (shadowRoot || this._element.ownerDocument.documentElement).contains(this._element);\n if (showEvent.defaultPrevented || !isInTheDom) {\n return;\n }\n\n // TODO: v6 remove this or make it optional\n this._disposePopper();\n const tip = this._getTipElement();\n this._element.setAttribute('aria-describedby', tip.getAttribute('id'));\n const {\n container\n } = this._config;\n if (!this._element.ownerDocument.documentElement.contains(this.tip)) {\n container.append(tip);\n EventHandler.trigger(this._element, this.constructor.eventName(EVENT_INSERTED));\n }\n this._popper = this._createPopper(tip);\n tip.classList.add(CLASS_NAME_SHOW$2);\n\n // If this is a touch-enabled device we add extra\n // empty mouseover listeners to the body's immediate children;\n // only needed because of broken event delegation on iOS\n // https://www.quirksmode.org/blog/archives/2014/02/mouse_event_bub.html\n if ('ontouchstart' in document.documentElement) {\n for (const element of [].concat(...document.body.children)) {\n EventHandler.on(element, 'mouseover', noop);\n }\n }\n const complete = () => {\n EventHandler.trigger(this._element, this.constructor.eventName(EVENT_SHOWN$2));\n if (this._isHovered === false) {\n this._leave();\n }\n this._isHovered = false;\n };\n this._queueCallback(complete, this.tip, this._isAnimated());\n }\n hide() {\n if (!this._isShown()) {\n return;\n }\n const hideEvent = EventHandler.trigger(this._element, this.constructor.eventName(EVENT_HIDE$2));\n if (hideEvent.defaultPrevented) {\n return;\n }\n const tip = this._getTipElement();\n tip.classList.remove(CLASS_NAME_SHOW$2);\n\n // If this is a touch-enabled device we remove the extra\n // empty mouseover listeners we added for iOS support\n if ('ontouchstart' in document.documentElement) {\n for (const element of [].concat(...document.body.children)) {\n EventHandler.off(element, 'mouseover', noop);\n }\n }\n this._activeTrigger[TRIGGER_CLICK] = false;\n this._activeTrigger[TRIGGER_FOCUS] = false;\n this._activeTrigger[TRIGGER_HOVER] = false;\n this._isHovered = null; // it is a trick to support manual triggering\n\n const complete = () => {\n if (this._isWithActiveTrigger()) {\n return;\n }\n if (!this._isHovered) {\n this._disposePopper();\n }\n this._element.removeAttribute('aria-describedby');\n EventHandler.trigger(this._element, this.constructor.eventName(EVENT_HIDDEN$2));\n };\n this._queueCallback(complete, this.tip, this._isAnimated());\n }\n update() {\n if (this._popper) {\n this._popper.update();\n }\n }\n\n // Protected\n _isWithContent() {\n return Boolean(this._getTitle());\n }\n _getTipElement() {\n if (!this.tip) {\n this.tip = this._createTipElement(this._newContent || this._getContentForTemplate());\n }\n return this.tip;\n }\n _createTipElement(content) {\n const tip = this._getTemplateFactory(content).toHtml();\n\n // TODO: remove this check in v6\n if (!tip) {\n return null;\n }\n tip.classList.remove(CLASS_NAME_FADE$2, CLASS_NAME_SHOW$2);\n // TODO: v6 the following can be achieved with CSS only\n tip.classList.add(`bs-${this.constructor.NAME}-auto`);\n const tipId = getUID(this.constructor.NAME).toString();\n tip.setAttribute('id', tipId);\n if (this._isAnimated()) {\n tip.classList.add(CLASS_NAME_FADE$2);\n }\n return tip;\n }\n setContent(content) {\n this._newContent = content;\n if (this._isShown()) {\n this._disposePopper();\n this.show();\n }\n }\n _getTemplateFactory(content) {\n if (this._templateFactory) {\n this._templateFactory.changeContent(content);\n } else {\n this._templateFactory = new TemplateFactory({\n ...this._config,\n // the `content` var has to be after `this._config`\n // to override config.content in case of popover\n content,\n extraClass: this._resolvePossibleFunction(this._config.customClass)\n });\n }\n return this._templateFactory;\n }\n _getContentForTemplate() {\n return {\n [SELECTOR_TOOLTIP_INNER]: this._getTitle()\n };\n }\n _getTitle() {\n return this._resolvePossibleFunction(this._config.title) || this._element.getAttribute('data-bs-original-title');\n }\n\n // Private\n _initializeOnDelegatedTarget(event) {\n return this.constructor.getOrCreateInstance(event.delegateTarget, this._getDelegateConfig());\n }\n _isAnimated() {\n return this._config.animation || this.tip && this.tip.classList.contains(CLASS_NAME_FADE$2);\n }\n _isShown() {\n return this.tip && this.tip.classList.contains(CLASS_NAME_SHOW$2);\n }\n _createPopper(tip) {\n const placement = execute(this._config.placement, [this, tip, this._element]);\n const attachment = AttachmentMap[placement.toUpperCase()];\n return Popper.createPopper(this._element, tip, this._getPopperConfig(attachment));\n }\n _getOffset() {\n const {\n offset\n } = this._config;\n if (typeof offset === 'string') {\n return offset.split(',').map(value => Number.parseInt(value, 10));\n }\n if (typeof offset === 'function') {\n return popperData => offset(popperData, this._element);\n }\n return offset;\n }\n _resolvePossibleFunction(arg) {\n return execute(arg, [this._element]);\n }\n _getPopperConfig(attachment) {\n const defaultBsPopperConfig = {\n placement: attachment,\n modifiers: [{\n name: 'flip',\n options: {\n fallbackPlacements: this._config.fallbackPlacements\n }\n }, {\n name: 'offset',\n options: {\n offset: this._getOffset()\n }\n }, {\n name: 'preventOverflow',\n options: {\n boundary: this._config.boundary\n }\n }, {\n name: 'arrow',\n options: {\n element: `.${this.constructor.NAME}-arrow`\n }\n }, {\n name: 'preSetPlacement',\n enabled: true,\n phase: 'beforeMain',\n fn: data => {\n // Pre-set Popper's placement attribute in order to read the arrow sizes properly.\n // Otherwise, Popper mixes up the width and height dimensions since the initial arrow style is for top placement\n this._getTipElement().setAttribute('data-popper-placement', data.state.placement);\n }\n }]\n };\n return {\n ...defaultBsPopperConfig,\n ...execute(this._config.popperConfig, [defaultBsPopperConfig])\n };\n }\n _setListeners() {\n const triggers = this._config.trigger.split(' ');\n for (const trigger of triggers) {\n if (trigger === 'click') {\n EventHandler.on(this._element, this.constructor.eventName(EVENT_CLICK$1), this._config.selector, event => {\n const context = this._initializeOnDelegatedTarget(event);\n context.toggle();\n });\n } else if (trigger !== TRIGGER_MANUAL) {\n const eventIn = trigger === TRIGGER_HOVER ? this.constructor.eventName(EVENT_MOUSEENTER) : this.constructor.eventName(EVENT_FOCUSIN$1);\n const eventOut = trigger === TRIGGER_HOVER ? this.constructor.eventName(EVENT_MOUSELEAVE) : this.constructor.eventName(EVENT_FOCUSOUT$1);\n EventHandler.on(this._element, eventIn, this._config.selector, event => {\n const context = this._initializeOnDelegatedTarget(event);\n context._activeTrigger[event.type === 'focusin' ? TRIGGER_FOCUS : TRIGGER_HOVER] = true;\n context._enter();\n });\n EventHandler.on(this._element, eventOut, this._config.selector, event => {\n const context = this._initializeOnDelegatedTarget(event);\n context._activeTrigger[event.type === 'focusout' ? TRIGGER_FOCUS : TRIGGER_HOVER] = context._element.contains(event.relatedTarget);\n context._leave();\n });\n }\n }\n this._hideModalHandler = () => {\n if (this._element) {\n this.hide();\n }\n };\n EventHandler.on(this._element.closest(SELECTOR_MODAL), EVENT_MODAL_HIDE, this._hideModalHandler);\n }\n _fixTitle() {\n const title = this._element.getAttribute('title');\n if (!title) {\n return;\n }\n if (!this._element.getAttribute('aria-label') && !this._element.textContent.trim()) {\n this._element.setAttribute('aria-label', title);\n }\n this._element.setAttribute('data-bs-original-title', title); // DO NOT USE IT. Is only for backwards compatibility\n this._element.removeAttribute('title');\n }\n _enter() {\n if (this._isShown() || this._isHovered) {\n this._isHovered = true;\n return;\n }\n this._isHovered = true;\n this._setTimeout(() => {\n if (this._isHovered) {\n this.show();\n }\n }, this._config.delay.show);\n }\n _leave() {\n if (this._isWithActiveTrigger()) {\n return;\n }\n this._isHovered = false;\n this._setTimeout(() => {\n if (!this._isHovered) {\n this.hide();\n }\n }, this._config.delay.hide);\n }\n _setTimeout(handler, timeout) {\n clearTimeout(this._timeout);\n this._timeout = setTimeout(handler, timeout);\n }\n _isWithActiveTrigger() {\n return Object.values(this._activeTrigger).includes(true);\n }\n _getConfig(config) {\n const dataAttributes = Manipulator.getDataAttributes(this._element);\n for (const dataAttribute of Object.keys(dataAttributes)) {\n if (DISALLOWED_ATTRIBUTES.has(dataAttribute)) {\n delete dataAttributes[dataAttribute];\n }\n }\n config = {\n ...dataAttributes,\n ...(typeof config === 'object' && config ? config : {})\n };\n config = this._mergeConfigObj(config);\n config = this._configAfterMerge(config);\n this._typeCheckConfig(config);\n return config;\n }\n _configAfterMerge(config) {\n config.container = config.container === false ? document.body : getElement(config.container);\n if (typeof config.delay === 'number') {\n config.delay = {\n show: config.delay,\n hide: config.delay\n };\n }\n if (typeof config.title === 'number') {\n config.title = config.title.toString();\n }\n if (typeof config.content === 'number') {\n config.content = config.content.toString();\n }\n return config;\n }\n _getDelegateConfig() {\n const config = {};\n for (const [key, value] of Object.entries(this._config)) {\n if (this.constructor.Default[key] !== value) {\n config[key] = value;\n }\n }\n config.selector = false;\n config.trigger = 'manual';\n\n // In the future can be replaced with:\n // const keysWithDifferentValues = Object.entries(this._config).filter(entry => this.constructor.Default[entry[0]] !== this._config[entry[0]])\n // `Object.fromEntries(keysWithDifferentValues)`\n return config;\n }\n _disposePopper() {\n if (this._popper) {\n this._popper.destroy();\n this._popper = null;\n }\n if (this.tip) {\n this.tip.remove();\n this.tip = null;\n }\n }\n\n // Static\n static jQueryInterface(config) {\n return this.each(function () {\n const data = Tooltip.getOrCreateInstance(this, config);\n if (typeof config !== 'string') {\n return;\n }\n if (typeof data[config] === 'undefined') {\n throw new TypeError(`No method named \"${config}\"`);\n }\n data[config]();\n });\n }\n}\n\n/**\n * jQuery\n */\n\ndefineJQueryPlugin(Tooltip);\n\n/**\n * --------------------------------------------------------------------------\n * Bootstrap popover.js\n * Licensed under MIT (https://github.com/twbs/bootstrap/blob/main/LICENSE)\n * --------------------------------------------------------------------------\n */\n\n\n/**\n * Constants\n */\n\nconst NAME$3 = 'popover';\nconst SELECTOR_TITLE = '.popover-header';\nconst SELECTOR_CONTENT = '.popover-body';\nconst Default$2 = {\n ...Tooltip.Default,\n content: '',\n offset: [0, 8],\n placement: 'right',\n template: '
' + '
' + '

' + '
' + '
',\n trigger: 'click'\n};\nconst DefaultType$2 = {\n ...Tooltip.DefaultType,\n content: '(null|string|element|function)'\n};\n\n/**\n * Class definition\n */\n\nclass Popover extends Tooltip {\n // Getters\n static get Default() {\n return Default$2;\n }\n static get DefaultType() {\n return DefaultType$2;\n }\n static get NAME() {\n return NAME$3;\n }\n\n // Overrides\n _isWithContent() {\n return this._getTitle() || this._getContent();\n }\n\n // Private\n _getContentForTemplate() {\n return {\n [SELECTOR_TITLE]: this._getTitle(),\n [SELECTOR_CONTENT]: this._getContent()\n };\n }\n _getContent() {\n return this._resolvePossibleFunction(this._config.content);\n }\n\n // Static\n static jQueryInterface(config) {\n return this.each(function () {\n const data = Popover.getOrCreateInstance(this, config);\n if (typeof config !== 'string') {\n return;\n }\n if (typeof data[config] === 'undefined') {\n throw new TypeError(`No method named \"${config}\"`);\n }\n data[config]();\n });\n }\n}\n\n/**\n * jQuery\n */\n\ndefineJQueryPlugin(Popover);\n\n/**\n * --------------------------------------------------------------------------\n * Bootstrap scrollspy.js\n * Licensed under MIT (https://github.com/twbs/bootstrap/blob/main/LICENSE)\n * --------------------------------------------------------------------------\n */\n\n\n/**\n * Constants\n */\n\nconst NAME$2 = 'scrollspy';\nconst DATA_KEY$2 = 'bs.scrollspy';\nconst EVENT_KEY$2 = `.${DATA_KEY$2}`;\nconst DATA_API_KEY = '.data-api';\nconst EVENT_ACTIVATE = `activate${EVENT_KEY$2}`;\nconst EVENT_CLICK = `click${EVENT_KEY$2}`;\nconst EVENT_LOAD_DATA_API$1 = `load${EVENT_KEY$2}${DATA_API_KEY}`;\nconst CLASS_NAME_DROPDOWN_ITEM = 'dropdown-item';\nconst CLASS_NAME_ACTIVE$1 = 'active';\nconst SELECTOR_DATA_SPY = '[data-bs-spy=\"scroll\"]';\nconst SELECTOR_TARGET_LINKS = '[href]';\nconst SELECTOR_NAV_LIST_GROUP = '.nav, .list-group';\nconst SELECTOR_NAV_LINKS = '.nav-link';\nconst SELECTOR_NAV_ITEMS = '.nav-item';\nconst SELECTOR_LIST_ITEMS = '.list-group-item';\nconst SELECTOR_LINK_ITEMS = `${SELECTOR_NAV_LINKS}, ${SELECTOR_NAV_ITEMS} > ${SELECTOR_NAV_LINKS}, ${SELECTOR_LIST_ITEMS}`;\nconst SELECTOR_DROPDOWN = '.dropdown';\nconst SELECTOR_DROPDOWN_TOGGLE$1 = '.dropdown-toggle';\nconst Default$1 = {\n offset: null,\n // TODO: v6 @deprecated, keep it for backwards compatibility reasons\n rootMargin: '0px 0px -25%',\n smoothScroll: false,\n target: null,\n threshold: [0.1, 0.5, 1]\n};\nconst DefaultType$1 = {\n offset: '(number|null)',\n // TODO v6 @deprecated, keep it for backwards compatibility reasons\n rootMargin: 'string',\n smoothScroll: 'boolean',\n target: 'element',\n threshold: 'array'\n};\n\n/**\n * Class definition\n */\n\nclass ScrollSpy extends BaseComponent {\n constructor(element, config) {\n super(element, config);\n\n // this._element is the observablesContainer and config.target the menu links wrapper\n this._targetLinks = new Map();\n this._observableSections = new Map();\n this._rootElement = getComputedStyle(this._element).overflowY === 'visible' ? null : this._element;\n this._activeTarget = null;\n this._observer = null;\n this._previousScrollData = {\n visibleEntryTop: 0,\n parentScrollTop: 0\n };\n this.refresh(); // initialize\n }\n\n // Getters\n static get Default() {\n return Default$1;\n }\n static get DefaultType() {\n return DefaultType$1;\n }\n static get NAME() {\n return NAME$2;\n }\n\n // Public\n refresh() {\n this._initializeTargetsAndObservables();\n this._maybeEnableSmoothScroll();\n if (this._observer) {\n this._observer.disconnect();\n } else {\n this._observer = this._getNewObserver();\n }\n for (const section of this._observableSections.values()) {\n this._observer.observe(section);\n }\n }\n dispose() {\n this._observer.disconnect();\n super.dispose();\n }\n\n // Private\n _configAfterMerge(config) {\n // TODO: on v6 target should be given explicitly & remove the {target: 'ss-target'} case\n config.target = getElement(config.target) || document.body;\n\n // TODO: v6 Only for backwards compatibility reasons. Use rootMargin only\n config.rootMargin = config.offset ? `${config.offset}px 0px -30%` : config.rootMargin;\n if (typeof config.threshold === 'string') {\n config.threshold = config.threshold.split(',').map(value => Number.parseFloat(value));\n }\n return config;\n }\n _maybeEnableSmoothScroll() {\n if (!this._config.smoothScroll) {\n return;\n }\n\n // unregister any previous listeners\n EventHandler.off(this._config.target, EVENT_CLICK);\n EventHandler.on(this._config.target, EVENT_CLICK, SELECTOR_TARGET_LINKS, event => {\n const observableSection = this._observableSections.get(event.target.hash);\n if (observableSection) {\n event.preventDefault();\n const root = this._rootElement || window;\n const height = observableSection.offsetTop - this._element.offsetTop;\n if (root.scrollTo) {\n root.scrollTo({\n top: height,\n behavior: 'smooth'\n });\n return;\n }\n\n // Chrome 60 doesn't support `scrollTo`\n root.scrollTop = height;\n }\n });\n }\n _getNewObserver() {\n const options = {\n root: this._rootElement,\n threshold: this._config.threshold,\n rootMargin: this._config.rootMargin\n };\n return new IntersectionObserver(entries => this._observerCallback(entries), options);\n }\n\n // The logic of selection\n _observerCallback(entries) {\n const targetElement = entry => this._targetLinks.get(`#${entry.target.id}`);\n const activate = entry => {\n this._previousScrollData.visibleEntryTop = entry.target.offsetTop;\n this._process(targetElement(entry));\n };\n const parentScrollTop = (this._rootElement || document.documentElement).scrollTop;\n const userScrollsDown = parentScrollTop >= this._previousScrollData.parentScrollTop;\n this._previousScrollData.parentScrollTop = parentScrollTop;\n for (const entry of entries) {\n if (!entry.isIntersecting) {\n this._activeTarget = null;\n this._clearActiveClass(targetElement(entry));\n continue;\n }\n const entryIsLowerThanPrevious = entry.target.offsetTop >= this._previousScrollData.visibleEntryTop;\n // if we are scrolling down, pick the bigger offsetTop\n if (userScrollsDown && entryIsLowerThanPrevious) {\n activate(entry);\n // if parent isn't scrolled, let's keep the first visible item, breaking the iteration\n if (!parentScrollTop) {\n return;\n }\n continue;\n }\n\n // if we are scrolling up, pick the smallest offsetTop\n if (!userScrollsDown && !entryIsLowerThanPrevious) {\n activate(entry);\n }\n }\n }\n _initializeTargetsAndObservables() {\n this._targetLinks = new Map();\n this._observableSections = new Map();\n const targetLinks = SelectorEngine.find(SELECTOR_TARGET_LINKS, this._config.target);\n for (const anchor of targetLinks) {\n // ensure that the anchor has an id and is not disabled\n if (!anchor.hash || isDisabled(anchor)) {\n continue;\n }\n const observableSection = SelectorEngine.findOne(decodeURI(anchor.hash), this._element);\n\n // ensure that the observableSection exists & is visible\n if (isVisible(observableSection)) {\n this._targetLinks.set(decodeURI(anchor.hash), anchor);\n this._observableSections.set(anchor.hash, observableSection);\n }\n }\n }\n _process(target) {\n if (this._activeTarget === target) {\n return;\n }\n this._clearActiveClass(this._config.target);\n this._activeTarget = target;\n target.classList.add(CLASS_NAME_ACTIVE$1);\n this._activateParents(target);\n EventHandler.trigger(this._element, EVENT_ACTIVATE, {\n relatedTarget: target\n });\n }\n _activateParents(target) {\n // Activate dropdown parents\n if (target.classList.contains(CLASS_NAME_DROPDOWN_ITEM)) {\n SelectorEngine.findOne(SELECTOR_DROPDOWN_TOGGLE$1, target.closest(SELECTOR_DROPDOWN)).classList.add(CLASS_NAME_ACTIVE$1);\n return;\n }\n for (const listGroup of SelectorEngine.parents(target, SELECTOR_NAV_LIST_GROUP)) {\n // Set triggered links parents as active\n // With both