Merge pull request #33 from GeoStat-Framework/update_structure

Minor doc fixes

CHANGELOG.md

@@ -2,6 +2,30 @@
 
 All notable changes to **welltestpy** will be documented in this file.
 
+
+## [1.2.0] - 2023-04
+
+See [#28](https://github.com/GeoStat-Framework/welltestpy/pull/28), [#31](https://github.com/GeoStat-Framework/welltestpy/pull/31) and [#32](https://github.com/GeoStat-Framework/welltestpy/pull/32)
+
+### Enhancements
+
+- added archive support
+- simplify documentation
+- new arguments `val_fit_type` and `val_fit_name` for all estimators to select fitting transformation
+- `val_fit_name` will be incorporated into the generated plots and the header of the estimation result file
+
+### Changes
+
+- move to `src/` based package structure
+- use [hatchling](https://pypi.org/project/hatchling/) as build backend
+- drop py36 support
+- value names for all arguments in the estimators now need to match the call signatures of the used type-curves
+
+### Bugfixes
+
+- minor fixes for the plotting routines and the estimators
+
+
 ## [1.1.0] - 2021-07
 
 ### Enhancements
@@ -112,7 +136,8 @@ All notable changes to **welltestpy** will be documented in this file.
 
 First alpha release of welltespy.
 
-[Unreleased]: https://github.com/GeoStat-Framework/welltestpy/compare/v1.1.0...HEAD
+[Unreleased]: https://github.com/GeoStat-Framework/welltestpy/compare/v1.2.0...HEAD
+[1.2.0]: https://github.com/GeoStat-Framework/welltestpy/compare/v1.1.0...v1.2.0
 [1.1.0]: https://github.com/GeoStat-Framework/welltestpy/compare/v1.0.3...v1.1.0
 [1.0.3]: https://github.com/GeoStat-Framework/welltestpy/compare/v1.0.2...v1.0.3
 [1.0.2]: https://github.com/GeoStat-Framework/welltestpy/compare/v1.0.1...v1.0.2

src/welltestpy/__init__.py

@@ -1,6 +1,5 @@
 """
-Purpose
-=======
+welltestpy - a Python package to handle well-based Field-campaigns.
 
 welltestpy provides a framework to handle and plot data from well based
 field campaigns as well as a parameter estimation module.

src/welltestpy/data/__init__.py

@@ -1,7 +1,6 @@
 """
 welltestpy subpackage providing datastructures.
 
-
 Campaign classes
 ~~~~~~~~~~~~~~~~
 

src/welltestpy/estimate/estimators.py

@@ -24,11 +24,12 @@ class ExtTheis3D(transient_lib.TransientPumping):
     function and an anisotropy ratio 0 < e <= 1.
 
     Available values for fitting:
-    - ``cond_gmean``: geometric mean conductivity
-    - ``var``: variance of log-conductivity
-    - ``len_scale``: correlation length scale of log-conductivity
-    - ``anis``: anisotropy between horizontal and vertical correlation length
-    - ``storage``: storage
+
+    * ``cond_gmean``: geometric mean conductivity
+    * ``var``: variance of log-conductivity
+    * ``len_scale``: correlation length scale of log-conductivity
+    * ``anis``: anisotropy between horizontal and vertical correlation length
+    * ``storage``: storage
 
     Parameters
     ----------
@@ -129,10 +130,11 @@ class ExtTheis2D(transient_lib.TransientPumping):
     function.
 
     Available values for fitting:
-    - ``trans_gmean``: geometric mean transmissivity
-    - ``var``: variance of log-transmissivity
-    - ``len_scale``: correlation length scale of log-transmissivity
-    - ``storage``: storage
+
+    * ``trans_gmean``: geometric mean transmissivity
+    * ``var``: variance of log-transmissivity
+    * ``len_scale``: correlation length scale of log-transmissivity
+    * ``storage``: storage
 
     Parameters
     ----------
@@ -229,10 +231,11 @@ class Neuman2004(transient_lib.TransientPumping):
     with an exponential correlation function.
 
     Available values for fitting:
-    - ``trans_gmean``: geometric mean transmissivity
-    - ``var``: variance of log-transmissivity
-    - ``len_scale``: correlation length scale of log-transmissivity
-    - ``storage``: storage
+
+    * ``trans_gmean``: geometric mean transmissivity
+    * ``var``: variance of log-transmissivity
+    * ``len_scale``: correlation length scale of log-transmissivity
+    * ``storage``: storage
 
     Parameters
     ----------
@@ -327,8 +330,9 @@ class Theis(transient_lib.TransientPumping):
     parameters. It utilizes the Theis solution.
 
     Available values for fitting:
-    - ``transmissivity``: transmissivity
-    - ``storage``: storage
+
+    * ``transmissivity``: transmissivity
+    * ``storage``: storage
 
     Parameters
     ----------
@@ -414,10 +418,11 @@ class ExtThiem3D(steady_lib.SteadyPumping):
     function and an anisotropy ratio 0 < e <= 1.
 
     Available values for fitting:
-    - ``cond_gmean``: geometric mean conductivity
-    - ``var``: variance of log-conductivity
-    - ``len_scale``: correlation length scale of log-conductivity
-    - ``anis``: anisotropy between horizontal and vertical correlation length
+
+    * ``cond_gmean``: geometric mean conductivity
+    * ``var``: variance of log-conductivity
+    * ``len_scale``: correlation length scale of log-conductivity
+    * ``anis``: anisotropy between horizontal and vertical correlation length
 
     Parameters
     ----------
@@ -521,9 +526,10 @@ class ExtThiem2D(steady_lib.SteadyPumping):
     function.
 
     Available values for fitting:
-    - ``trans_gmean``: geometric mean transmissivity
-    - ``var``: variance of log-transmissivity
-    - ``len_scale``: correlation length scale of log-transmissivity
+
+    * ``trans_gmean``: geometric mean transmissivity
+    * ``var``: variance of log-transmissivity
+    * ``len_scale``: correlation length scale of log-transmissivity
 
     Parameters
     ----------
@@ -624,9 +630,10 @@ class Neuman2004Steady(steady_lib.SteadyPumping):
     with an exponential correlation function.
 
     Available values for fitting:
-    - ``trans_gmean``: geometric mean transmissivity
-    - ``var``: variance of log-transmissivity
-    - ``len_scale``: correlation length scale of log-transmissivity
+
+    * ``trans_gmean``: geometric mean transmissivity
+    * ``var``: variance of log-transmissivity
+    * ``len_scale``: correlation length scale of log-transmissivity
 
     Parameters
     ----------
@@ -724,7 +731,8 @@ class Thiem(steady_lib.SteadyPumping):
     parameters. It utilizes the Thiem solution.
 
     Available values for fitting:
-    - ``transmissivity``: transmissivity
+
+    * ``transmissivity``: transmissivity
 
     Parameters
     ----------

src/welltestpy/estimate/spotpylib.py

@@ -190,7 +190,7 @@ def simulation(self, vector):
         return self.sim(**self.sim_kwargs).reshape(-1)
 
     def evaluation(self):
-        """Accesses the observation data."""
+        """Access the observation data."""
         return self.data
 
     def objectivefunction(self, simulation, evaluation):

src/welltestpy/process/processlib.py

@@ -238,7 +238,8 @@ def filterdrawdown(observation, tout=None, dxscale=2):
 
 
 def cooper_jacob_correction(observation, sat_thickness):
-    """correction method for observed drawdown for unconfined aquifers.
+    """
+    Correction method for observed drawdown for unconfined aquifers.
 
     Parameters
     ----------

src/welltestpy/tools/diagnostic_plots.py

@@ -18,7 +18,8 @@ def diagnostic_plot_pump_test(
     plotname=None,
     style="WTP",
 ):
-    """plot the derivative with the original data.
+    """
+    Plot the derivative with the original data.
 
     Parameters
     ----------
@@ -48,9 +49,9 @@ def diagnostic_plot_pump_test(
         Plot style.
         Default: "WTP".
 
-     Returns
-     -------
-     Diagnostic plot
+    Returns
+    -------
+    Diagnostic plot
     """
     head, time = observation()
     head = np.array(head, dtype=float).reshape(-1)