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searchindex.js
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Search.setIndex({"alltitles": {"1D plotting": [[161, null]], "2D plotting": [[162, null]], "3D Plots": [[157, "d-plots"]], "3D images": [[231, null]], "3D plotting": [[131, null], [132, null]], "3D plotting vignette": [[149, null]], "A 2D image plot of the function": [[177, "a-2d-image-plot-of-the-function"]], "A 3D surface plot of the function": [[177, "a-3d-surface-plot-of-the-function"]], "A Few Notes on Preconditioning": [[65, "a-few-notes-on-preconditioning"]], "A Note on Facial Recognition": [[238, "a-note-on-facial-recognition"]], "A Simple Example: the Iris Dataset": [[251, "a-simple-example-the-iris-dataset"]], "A correct approach: Using a validation set": [[251, "a-correct-approach-using-a-validation-set"]], "A demo of 1D interpolation": [[184, null]], "A example of plotting not quite right": [[140, null]], "A function to do it: scipy.signal.fftconvolve()": [[198, "a-function-to-do-it-scipy-signal-fftconvolve"]], "A last word of caution: separate validation and test set": [[251, "a-last-word-of-caution-separate-validation-and-test-set"]], "A plugin registration system": [[9, "a-plugin-registration-system"]], "A quick look at the data": [[251, "a-quick-look-at-the-data"]], "A quick test on the K-neighbors classifier": [[251, "a-quick-test-on-the-k-neighbors-classifier"]], "A recap on Scikit-learn\u2019s estimator interface": [[251, "a-recap-on-scikit-learn-s-estimator-interface"]], "A review of the different optimizers": [[53, "a-review-of-the-different-optimizers"]], "A shooting method: the Powell algorithm": [[53, "a-shooting-method-the-powell-algorithm"]], "A simple example": [[68, null]], "A simple linear regression": [[242, null], [265, "a-simple-linear-regression"]], "A simple plotting example": [[121, null]], "A simple regression analysis on the California housing data": [[235, null]], "A simple, good-looking plot": [[124, null]], "A type-as-go spell-checker like integration": [[10, "a-type-as-go-spell-checker-like-integration"]], "A while-loop removing decorator": [[9, "a-while-loop-removing-decorator"]], "About the Scientific Python Lectures": [[267, null]], "Acknowledgements": [[251, null]], "Adaptive step gradient descent": [[53, "id8"]], "Adding a dimension": [[175, "adding-a-dimension"]], "Adding a legend": [[157, "adding-a-legend"]], "Additional Contributions": [[0, "additional-contributions"], [267, "additional-contributions"]], "Additional Links": [[54, "additional-links"]], "Admonitions": [[70, "admonitions"]], "Advanced NumPy": [[8, null]], "Advanced Python Constructs": [[9, null]], "Advanced iteration": [[78, "advanced-iteration"]], "Advanced operations": [[158, null]], "Advanced topics": [[38, null]], "Affine transform": [[224, null]], "Air fares before and after 9/11": [[253, null]], "Algebraic manipulations": [[266, "algebraic-manipulations"]], "Algorithmic optimization": [[54, "algorithmic-optimization"]], "Aliased versus anti-aliased": [[101, null], [103, null]], "Alpha: transparency": [[102, null]], "Alternating optimization": [[47, null]], "Analysis of Iris petal and sepal sizes": [[254, null]], "Annotate some points": [[157, "annotate-some-points"]], "Array interface protocol": [[8, "array-interface-protocol"]], "Array manipulations": [[172, "array-manipulations"]], "Array shape manipulation": [[175, "array-shape-manipulation"]], "Array siblings: chararray, maskedarray": [[8, "array-siblings-chararray-maskedarray"]], "Assignment operator": [[77, "assignment-operator"]], "Authors": [[0, null], [267, "authors"]], "Automatically Performing Grid Search": [[251, "automatically-performing-grid-search"]], "Avoiding bugs": [[10, "avoiding-bugs"]], "Axes": [[120, null], [157, "axes"]], "Bar Plots": [[157, "bar-plots"]], "Bar plot advanced": [[142, null]], "Bar plots": [[122, null]], "Basic Hyperparameter Optimization": [[251, "basic-hyperparameter-optimization"]], "Basic data types": [[159, "basic-data-types"]], "Basic manipulations": [[37, "basic-manipulations"]], "Basic operations": [[175, "basic-operations"]], "Basic principles of machine learning with scikit-learn": [[251, "basic-principles-of-machine-learning-with-scikit-learn"]], "Basic reductions": [[175, "basic-reductions"]], "Basic types": [[77, null]], "Basic visualization": [[159, "basic-visualization"]], "Before starting: Installing a working environment": [[76, "before-starting-installing-a-working-environment"]], "Beyond this tutorial": [[157, "beyond-this-tutorial"]], "Bias and variance of polynomial fit": [[234, null]], "Bias-variance trade-off: illustration on a simple regression problem": [[251, "bias-variance-trade-off-illustration-on-a-simple-regression-problem"]], "Bidirectional communication": [[9, "bidirectional-communication"]], "Binary segmentation: foreground + background": [[231, "binary-segmentation-foreground-background"]], "Block Compressed Row Format (BSR)": [[55, null]], "Block of memory": [[8, "block-of-memory"]], "Blurring of images": [[14, null]], "Blurring/smoothing": [[37, "blurring-smoothing"]], "Box bounds": [[53, "box-bounds"]], "Boxplot with matplotlib": [[143, null]], "Boxplots and paired differences": [[255, null]], "Brent\u2019s method": [[41, null]], "Brent\u2019s method on a non-convex function: note that\n the fact that the optimizer avoided the local minimum\n is a matter of luck.": [[53, "id6"]], "Brent\u2019s method on a quadratic function: it\n converges in 3 iterations, as the quadratic\n approximation is then exact.": [[53, "id5"]], "Brian Kernighan": [[10, null]], "Broadcasting": [[8, "broadcasting"], [175, "broadcasting"]], "Brute force: a grid search": [[53, "brute-force-a-grid-search"]], "Building instructions": [[2, "building-instructions"], [267, "building-instructions"]], "Built-in Hyperparameter Search": [[251, "built-in-hyperparameter-search"]], "C and Fortran order": [[8, "c-and-fortran-order"]], "CPU cache effects": [[8, "cpu-cache-effects"]], "Calculus": [[266, "calculus"]], "Casting": [[8, "casting"], [171, "casting"]], "Casting and re-interpretation/views": [[8, "casting-and-re-interpretation-views"]], "Catching exceptions": [[9, "catching-exceptions"], [79, "catching-exceptions"]], "Categorical variables: comparing groups or multiple categories": [[265, "categorical-variables-comparing-groups-or-multiple-categories"]], "Chaining generators": [[9, "chaining-generators"]], "Changing colors and line widths": [[157, "changing-colors-and-line-widths"]], "Chapter authors": [[0, "chapter-authors"], [267, "chapter-authors"]], "Chapter contents": [[8, "chapter-contents"], [9, "chapter-contents"], [10, "chapter-contents"], [157, "chapter-contents"]], "Chapter, section, subsection, paragraph": [[70, "chapter-section-subsection-paragraph"]], "Chapters contents": [[37, "chapters-contents"], [39, "chapters-contents"], [53, "chapters-contents"], [54, "chapters-contents"], [70, "chapters-contents"], [202, "chapters-contents"], [231, "chapters-contents"], [251, "chapters-contents"], [266, "chapters-contents"]], "Choosing a method": [[53, "choosing-a-method"]], "Classify with Gaussian naive Bayes": [[237, "classify-with-gaussian-naive-bayes"]], "Cleaning segmentation with mathematical morphology": [[15, null]], "Clearing floats": [[70, "clearing-floats"]], "Code and notebook": [[251, null], [251, null], [251, null]], "Code documentation": [[157, "code-documentation"]], "Code for the chapter\u2019s exercises": [[87, null], [99, "code-for-the-chapter-s-exercises"], [157, "code-for-the-chapter-s-exercises"]], "Code generating the summary figures with a title": [[99, "code-generating-the-summary-figures-with-a-title"], [141, null], [157, "code-generating-the-summary-figures-with-a-title"]], "Code samples for Matplotlib": [[99, null], [157, "code-samples-for-matplotlib"]], "Coding best practices to avoid getting in trouble": [[10, "coding-best-practices-to-avoid-getting-in-trouble"]], "Colormaps": [[105, null], [157, "colormaps"]], "Colorspaces": [[231, "colorspaces"]], "Common Methods": [[66, "common-methods"]], "Common Parameters": [[65, "common-parameters"]], "Compare classifiers on the digits data": [[236, null]], "Comparing 2 sets of samples from Gaussians": [[193, null]], "Compiled languages: C, C++, Fortran\u2026": [[76, "compiled-languages-c-c-fortran"]], "Compressed Sparse Column Format (CSC)": [[57, null]], "Compressed Sparse Row Format (CSR)": [[58, null]], "Computation times": [[7, null], [36, null], [52, null], [69, null], [98, null], [118, null], [155, null], [156, null], [170, null], [194, null], [200, null], [213, null], [230, null], [250, null], [261, null], [264, null], [268, null]], "Computational linear algebra": [[54, null]], "Compute and plot the power": [[181, "compute-and-plot-the-power"]], "Compute and plot the power spectral density (PSD)": [[192, "compute-and-plot-the-power-spectral-density-psd"]], "Compute and plot the spectrogram": [[192, "compute-and-plot-the-spectrogram"]], "Compute the 2d FFT of the input image": [[197, "compute-the-2d-fft-of-the-input-image"]], "Computing gradients": [[53, "computing-gradients"]], "Computing horizontal gradients with the Sobel filter": [[228, null]], "Computing sums": [[175, "computing-sums"]], "Computing the cumulative probabilities": [[216, "computing-the-cumulative-probabilities"]], "Conditional Expressions": [[78, "conditional-expressions"]], "Conjugate gradient descent": [[53, "conjugate-gradient-descent"], [53, "id9"]], "Connected components and measurements on images": [[201, "connected-components-and-measurements-on-images"], [202, "connected-components-and-measurements-on-images"]], "Constraint optimization: visualizing the geometry": [[43, null]], "Constraints": [[53, "constraints"]], "Containers": [[77, "containers"]], "Contents": [[265, "contents"]], "Context managers": [[9, "context-managers"]], "Contour Plots": [[157, "contour-plots"]], "Contributing": [[2, null], [267, "contributing"]], "Contributing features": [[8, "contributing-features"]], "Contributing guide": [[2, "contributing-guide"], [267, "contributing-guide"]], "Contributing to NumPy/SciPy": [[8, "contributing-to-numpy-scipy"]], "Contributing to documentation": [[8, "contributing-to-documentation"]], "Control Flow": [[78, null]], "Convex function": [[44, null]], "Convex versus non-convex optimization": [[53, "convex-versus-non-convex-optimization"]], "Coordinate Format (COO)": [[56, null]], "Copies and views": [[159, "copies-and-views"]], "Copying the docstring and other attributes of the original function": [[9, "copying-the-docstring-and-other-attributes-of-the-original-function"]], "Creating an image": [[222, null]], "Creating arrays": [[159, "creating-arrays"]], "Creating dataframes: reading data files or converting arrays": [[265, "creating-dataframes-reading-data-files-or-converting-arrays"]], "Creating modules": [[85, "creating-modules"]], "Cross-validation": [[251, "cross-validation"]], "Crude integral approximations": [[172, "crude-integral-approximations"]], "Crude periodicity finding": [[199, null]], "Ctypes": [[39, "id3"], [39, "id13"]], "Cumulative wind speed prediction": [[206, null]], "Curve fitting": [[45, null], [53, "curve-fitting"], [179, null], [202, "curve-fitting"]], "Curve fitting: temperature as a function of month of the year": [[196, null]], "Cython": [[39, "cython"], [39, "id15"]], "Dash capstyle": [[106, null]], "Dash join style": [[107, null]], "Data as a table": [[265, "data-as-a-table"]], "Data in scikit-learn": [[251, "data-in-scikit-learn"]], "Data representation and interaction": [[265, "data-representation-and-interaction"]], "Data statistics": [[172, "data-statistics"]], "Data types": [[8, "data-types"], [231, "data-types"]], "Data visualization and interaction": [[231, "data-visualization-and-interaction"]], "Debugger commands and interaction": [[10, "debugger-commands-and-interaction"]], "Debugging code": [[10, null]], "Debugging segmentation faults using gdb": [[10, "debugging-segmentation-faults-using-gdb"]], "Debugging workflow": [[10, "debugging-workflow"]], "Decorators": [[9, "decorators"]], "Decorators implemented as classes and as functions": [[9, "decorators-implemented-as-classes-and-as-functions"]], "Define the function": [[188, "define-the-function"]], "Defining functions": [[81, null]], "Demo PCA in 2D": [[244, null]], "Demo connected components": [[178, null]], "Demo mathematical morphology": [[185, null]], "Demo text printing": [[139, null]], "Denoising": [[37, "denoising"]], "Denoising an image with the median filter": [[16, null]], "Deprecation of functions": [[9, "deprecation-of-functions"]], "Detrending a signal": [[180, null]], "Devil is in the details": [[157, "devil-is-in-the-details"]], "Diagonal Format (DIA)": [[59, null]], "Dictionaries": [[77, "dictionaries"]], "Dictionary of Keys Format (DOK)": [[60, null]], "Different data type sizes": [[171, "different-data-type-sizes"]], "Differential Equations": [[266, "differential-equations"]], "Differentiation": [[266, "differentiation"]], "Dimension shuffling": [[175, "dimension-shuffling"]], "Dimensionality Reduction: PCA": [[251, "dimensionality-reduction-pca"]], "Dimensionality of the problem": [[53, null]], "Directory and file manipulation": [[86, "directory-and-file-manipulation"]], "Discovering methods:": [[77, null]], "Display a Raccoon Face": [[17, null]], "Display the contours of a function": [[144, null]], "Displaying a Raccoon Face": [[18, null]], "Displaying a simple image": [[220, null]], "Displaying images": [[37, "displaying-images"]], "Displaying the contours of a function": [[123, null]], "Distances exercise": [[164, null]], "Distribution objects and frozen distributions": [[202, null]], "Docstrings": [[81, "docstrings"]], "Doing the Learning: Support Vector Machines": [[238, "doing-the-learning-support-vector-machines"]], "Domain-aware functions": [[8, "domain-aware-functions"]], "Donald Knuth": [[54, null]], "Download": [[73, null]], "Earlier scikit-image versions": [[231, null]], "Easier and better: scipy.ndimage.gaussian_filter()": [[197, "easier-and-better-scipy-ndimage-gaussian-filter"]], "Easier to ask for forgiveness than for permission": [[79, "easier-to-ask-for-forgiveness-than-for-permission"]], "Edge detection": [[37, "edge-detection"]], "Editors": [[0, "editors"], [267, "editors"]], "Eigenvalue Problem Solvers": [[65, "eigenvalue-problem-solvers"]], "Elaboration of the work in an editor": [[76, "elaboration-of-the-work-in-an-editor"]], "Elementwise operations": [[175, "elementwise-operations"]], "Environment variables:": [[86, "environment-variables"]], "Equalizing the histogram of an image": [[223, null]], "Equation solving": [[266, "equation-solving"]], "Example": [[39, "example"], [39, "id5"], [39, "id8"], [39, "id10"]], "Example chapter": [[2, null], [267, null]], "Example data": [[231, "example-data"]], "Example demoing choices for an option": [[99, "example-demoing-choices-for-an-option"], [100, null], [157, "example-demoing-choices-for-an-option"]], "Example of filters comparison: image denoising": [[231, null]], "Example of linear and non-linear models": [[247, null]], "Example of solution for the image processing exercise: unmolten grains in glass": [[204, null]], "Example of the SVD": [[54, "example-of-the-svd"]], "Example:": [[70, null]], "Example: Masked statistics": [[6, null], [8, null]], "Example: fake dimensions with strides": [[8, "example-fake-dimensions-with-strides"]], "Example: reading .wav files": [[8, "example-reading-wav-files"]], "Examples": [[55, "examples"], [56, "examples"], [57, "examples"], [58, "examples"], [59, "examples"], [60, "examples"], [63, "examples"], [65, "examples"]], "Examples for the advanced NumPy chapter": [[5, null]], "Examples for the contribution guide": [[67, null]], "Examples for the image processing chapter": [[11, null], [37, "examples-for-the-image-processing-chapter"]], "Examples for the mathematical optimization chapter": 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"Exercise 7": [[95, null]], "Exercise 8": [[96, null]], "Exercise 9": [[97, null]], "Exercise other operations": [[175, null]], "Exercise with the Gumbell distribution": [[216, "exercise-with-the-gumbell-distribution"]], "Exercise:": [[251, null]], "Exercise: 2-D minimization": [[202, null]], "Exercise: A locally flat minimum": [[53, null]], "Exercise: A simple (?) quadratic function": [[53, null]], "Exercise: Array creation": [[159, null]], "Exercise: Creating arrays using functions": [[159, null]], "Exercise: Curve fitting of temperature data": [[202, null]], "Exercise: Denoise moon landing image": [[202, null]], "Exercise: Elementwise operations": [[175, null]], "Exercise: Fancy indexing": [[159, null]], "Exercise: Fibonacci sequence": [[81, null]], "Exercise: Gradient Boosting Tree Regression": [[251, null]], "Exercise: Indexing and slicing": [[159, null]], "Exercise: Other dimension reduction of digits": [[251, null]], "Exercise: Probability distributions": [[202, null]], "Exercise: Quicksort": [[81, null]], "Exercise: Reductions": [[175, null]], "Exercise: Shape manipulations": [[175, null]], "Exercise: Simple arrays": [[159, null]], "Exercise: Simple visualizations": [[159, null]], "Exercise: Sorting": [[175, null]], "Exercise: Text data files": [[158, null]], "Exercise: Tiling for array creation": [[159, null]], "Exercise: building an ufunc from scratch": [[8, "exercise-building-an-ufunc-from-scratch"]], "Exercise: denoising": [[37, null]], "Exercises": [[39, "exercises"], [81, "exercises"], [266, null], [266, null], [266, null], [266, null], [266, null]], "Expand": [[266, "expand"]], "Fancy indexing": [[159, "fancy-indexing"]], "Fast Fourier transforms: scipy.fft": [[202, "fast-fourier-transforms-scipy-fft"]], "Feature extraction": [[37, "feature-extraction"]], "Feature extraction for computer vision": [[231, "feature-extraction-for-computer-vision"]], "Fibonacci sequence": [[203, "fibonacci-sequence"]], "Figures": [[157, "figures"]], "Figures and 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202], "zoomed_fac": [183, 201, 202], "zorder": [142, 143, 144, 145, 146, 147, 148, 150, 152, 153, 154, 233, 247], "\u00e7a\u011flayan": [0, 1, 267], "\u00f3scar": [1, 267], "\u2460": 9, "\u2461": 9}, "titles": ["<span class=\"section-number\">4.1.1. </span>Authors", "What\u2019s new", "Contributing", "License", "<span class=\"section-number\">4. </span>About the Scientific Python Lectures", "Examples for the advanced NumPy chapter", "Example: Masked statistics", "Computation times", "<span class=\"section-number\">2.2. </span>Advanced NumPy", "<span class=\"section-number\">2.1. </span>Advanced Python Constructs", "<span class=\"section-number\">2.3. </span>Debugging code", "Examples for the image processing chapter", "<span class=\"section-number\">2.6.8.21. </span>Segmentation with Gaussian mixture models", "<span class=\"section-number\">2.6.8.3. </span>Plot the block mean of an image", "<span class=\"section-number\">2.6.8.8. </span>Blurring of images", "<span class=\"section-number\">2.6.8.20. </span>Cleaning segmentation with mathematical morphology", "<span class=\"section-number\">2.6.8.16. </span>Denoising an image with the median filter", "<span class=\"section-number\">2.6.8.6. </span>Display a Raccoon Face", "<span class=\"section-number\">2.6.8.1. </span>Displaying a Raccoon Face", "<span class=\"section-number\">2.6.8.11. </span>Image denoising", "<span class=\"section-number\">2.6.8.13. </span>Total Variation denoising", "<span class=\"section-number\">2.6.8.19. </span>Finding edges with Sobel filters", "<span class=\"section-number\">2.6.8.15. </span>Find the bounding box of an object", "<span class=\"section-number\">2.6.8.12. </span>Geometrical transformations", "<span class=\"section-number\">2.6.8.23. </span>Granulometry", "<span class=\"section-number\">2.6.8.18. </span>Greyscale dilation", "<span class=\"section-number\">2.6.8.17. </span>Histogram segmentation", "<span class=\"section-number\">2.6.8.2. </span>Image interpolation", "<span class=\"section-number\">2.6.8.14. </span>Measurements from images", "<span class=\"section-number\">2.6.8.4. </span>Image manipulation and NumPy arrays", "<span class=\"section-number\">2.6.8.10. </span>Opening, erosion, and propagation", "<span class=\"section-number\">2.6.8.5. </span>Radial mean", "<span class=\"section-number\">2.6.8.7. </span>Image sharpening", "<span class=\"section-number\">2.6.8.24. </span>Segmentation with spectral clustering", "<span class=\"section-number\">2.6.8.9. </span>Synthetic data", "<span class=\"section-number\">2.6.8.22. </span>Watershed segmentation", "Computation times", "<span class=\"section-number\">2.6. </span>Image manipulation and processing using NumPy and SciPy", "<span class=\"section-number\">2. </span>Advanced topics", "<span class=\"section-number\">2.8. </span>Interfacing with C", "Examples for the mathematical optimization chapter", "<span class=\"section-number\">2.7.4.7. </span>Brent\u2019s method", "<span class=\"section-number\">2.7.4.10. </span>Plotting the comparison of optimizers", "<span class=\"section-number\">2.7.4.8. </span>Constraint optimization: visualizing the geometry", "<span class=\"section-number\">2.7.4.4. </span>Convex function", "<span class=\"section-number\">2.7.4.3. </span>Curve fitting", "<span class=\"section-number\">2.7.4.5. </span>Finding a minimum in a flat neighborhood", "<span class=\"section-number\">2.7.4.9. </span>Alternating optimization", "<span class=\"section-number\">2.7.4.11. </span>Gradient descent", "<span class=\"section-number\">2.7.4.1. </span>Noisy optimization problem", "<span class=\"section-number\">2.7.4.6. </span>Optimization with constraints", "<span class=\"section-number\">2.7.4.2. </span>Smooth vs non-smooth", "Computation times", "<span class=\"section-number\">2.7. </span>Mathematical optimization: finding minima of functions", "<span class=\"section-number\">2.4. </span>Optimizing code", "Block Compressed Row Format (BSR)", "Coordinate Format (COO)", "Compressed Sparse Column Format (CSC)", "Compressed Sparse Row Format (CSR)", "Diagonal Format (DIA)", "Dictionary of Keys Format (DOK)", "<span class=\"section-number\">2.5. </span>Sparse Arrays in SciPy", "<span class=\"section-number\">2.5.1. </span>Introduction", "List of Lists Format (LIL)", "<span class=\"section-number\">2.5.4. </span>Other Interesting Packages", "<span class=\"section-number\">2.5.3. </span>Linear System Solvers", "<span class=\"section-number\">2.5.2. </span>Storage Schemes", "Examples for the contribution guide", "A simple example", "Computation times", "How to contribute", "<no title>", "<no title>", "Scientific Python Lectures", "<span class=\"section-number\">1.6. </span>Getting help and finding documentation", "<span class=\"section-number\">1. </span>Getting started with Python for science", "<span class=\"section-number\">1.1. </span>Python scientific computing ecosystem", "<span class=\"section-number\">1.2.2. </span>Basic types", "<span class=\"section-number\">1.2.3. </span>Control Flow", "<span class=\"section-number\">1.2.8. </span>Exception handling in Python", "<span class=\"section-number\">1.2.1. </span>First steps", "<span class=\"section-number\">1.2.4. </span>Defining functions", "<span class=\"section-number\">1.2.6. </span>Input and Output", "<span class=\"section-number\">1.2.9. </span>Object-oriented programming (OOP)", "<span class=\"section-number\">1.2. </span>The Python language", "<span class=\"section-number\">1.2.5. </span>Reusing code: scripts and modules", "<span class=\"section-number\">1.2.7. </span>Standard Library", "Code for the chapter\u2019s exercises", "Exercise 1", "Exercise", "Exercise 2", "Exercise 3", "Exercise 4", "Exercise 5", "Exercise 6", "Exercise 7", "Exercise 8", "Exercise 9", "Computation times", "Code samples for Matplotlib", "Example demoing choices for an option", "Aliased versus anti-aliased", "Alpha: transparency", "Aliased versus anti-aliased", "The colors matplotlib line plots", "Colormaps", "Dash capstyle", "Dash join style", "Linestyles", "Linewidth", "Markers", "Marker edge color", "Marker edge width", "Marker face color", "Marker size", "Solid cap style", "Solid joint style", "Locators for tick on axis", "Computation times", "Simple axes example", "Axes", "A simple plotting example", "Bar plots", "Displaying the contours of a function", "A simple, good-looking plot", "Grid", "GridSpec", "Imshow elaborate", "Subplots", "Pie chart", "Plot and filled plots", "3D plotting", "3D plotting", "Plotting in polar coordinates", "Plotting a vector field: quiver", "Plotting a scatter of points", "Subplot grid", "Horizontal arrangement of subplots", "Subplot plot arrangement vertical", "Demo text printing", "A example of plotting not quite right", "Code generating the summary figures with a title", "Bar plot advanced", "Boxplot with matplotlib", "Display the contours of a function", "Grid elaborate", "Imshow demo", "Multiple plots vignette", "Pie chart vignette", "3D plotting vignette", "Plot example vignette", "Plotting in polar, decorated", "Plotting quiver decorated", "Plot scatter decorated", "Text printing decorated", "Computation times", "Computation times", "<span class=\"section-number\">1.4. </span>Matplotlib: plotting", "<span class=\"section-number\">1.3.4. </span>Advanced operations", "<span class=\"section-number\">1.3.1. </span>The NumPy array object", "Full code examples for the numpy chapter", "1D plotting", "2D plotting", "Fitting in Chebyshev basis", "Distances exercise", "Reading and writing an elephant", "Mandelbrot set", "Fitting to polynomial", "Population exercise", "Random walk exercise", "Computation times", "<span class=\"section-number\">1.3.3. </span>More elaborate arrays", "<span class=\"section-number\">1.3.5. </span>Some exercises", "<span class=\"section-number\">1.3.6. </span>Full code examples", "<span class=\"section-number\">1.3. </span>NumPy: creating and manipulating numerical data", "<span class=\"section-number\">1.3.2. </span>Numerical operations on arrays", "Full code examples for the SciPy chapter", "<span class=\"section-number\">1.5.12.15. </span>Optimization of a two-parameter function", "<span class=\"section-number\">1.5.12.12. </span>Demo connected components", "<span class=\"section-number\">1.5.12.8. </span>Curve fitting", "<span class=\"section-number\">1.5.12.3. </span>Detrending a signal", "<span class=\"section-number\">1.5.12.16. </span>Plotting and manipulating FFTs for filtering", "<span class=\"section-number\">1.5.12.14. </span>Plot filtering on images", "<span class=\"section-number\">1.5.12.11. </span>Plot geometrical transformations on images", "<span class=\"section-number\">1.5.12.17. </span>A demo of 1D interpolation", "<span class=\"section-number\">1.5.12.10. </span>Demo mathematical morphology", "<span class=\"section-number\">1.5.12.5. </span>Normal distribution: histogram and PDF", "<span class=\"section-number\">1.5.12.1. </span>Finding the minimum of a smooth function", "<span class=\"section-number\">1.5.12.13. </span>Minima and roots of a function", "<span class=\"section-number\">1.5.12.2. </span>Resample a signal with scipy.signal.resample", "<span class=\"section-number\">1.5.12.6. </span>Integrate the Damped spring-mass oscillator", "<span class=\"section-number\">1.5.12.4. </span>Integrating a simple ODE", "<span class=\"section-number\">1.5.12.9. </span>Spectrogram, power spectral density", "<span class=\"section-number\">1.5.12.7. </span>Comparing 2 sets of samples from Gaussians", "Computation times", "Solutions of the exercises for SciPy", "Curve fitting: temperature as a function of month of the year", "Image denoising by FFT", "Simple image blur by convolution with a Gaussian kernel", "Crude periodicity finding", "Computation times", "Geometrical transformations on images", "<span class=\"section-number\">1.5. </span>SciPy : high-level scientific computing", "Solutions", "<span class=\"section-number\">1.5.11.4. </span>Example of solution for the image processing exercise: unmolten grains in glass", "Examples for the summary excercices", "Cumulative wind speed prediction", "The Gumbell distribution", "The lidar system, data (2 of 2 datasets)", "The lidar system, data and fit (2 of 2 datasets)", "The lidar system, data (1 of 2 datasets)", "The lidar system, data and fit (1 of 2 datasets)", "The Gumbell distribution, results", "Computation times", "<span class=\"section-number\">1.5.11.3. </span>Image processing application: counting bubbles and unmolten grains", "<span class=\"section-number\">1.5.11.2. </span>Non linear least squares curve fitting: application to point extraction in topographical lidar data", "<span class=\"section-number\">1.5.11.1. </span>Maximum wind speed prediction at the Sprog\u00f8 station", "<span class=\"section-number\">3. </span>Packages and applications", "Examples for the scikit-image chapter", "<span class=\"section-number\">3.3.11.6. </span>Segmentation contours", "<span class=\"section-number\">3.3.11.2. </span>Displaying a simple image", "<span class=\"section-number\">3.3.11.3. </span>Integers can overflow", "<span class=\"section-number\">3.3.11.1. </span>Creating an image", "<span class=\"section-number\">3.3.11.4. </span>Equalizing the histogram of an image", "<span class=\"section-number\">3.3.11.8. </span>Affine transform", "<span class=\"section-number\">3.3.11.10. </span>Various denoising filters", "<span class=\"section-number\">3.3.11.9. </span>Labelling connected components of an image", "<span class=\"section-number\">3.3.11.11. </span>Watershed and random walker for segmentation", "<span class=\"section-number\">3.3.11.5. </span>Computing horizontal gradients with the Sobel filter", "<span class=\"section-number\">3.3.11.7. </span>Otsu thresholding", "Computation times", "<span class=\"section-number\">3.3. </span><code class=\"docutils literal notranslate\"><span class=\"pre\">scikit-image</span></code>: image processing", "Examples for the scikit-learn chapter", "<span class=\"section-number\">3.4.8.17. </span>Tutorial Diagrams", "<span class=\"section-number\">3.4.8.16. </span>Bias and variance of polynomial fit", "<span class=\"section-number\">3.4.8.11. </span>A simple regression analysis on the California housing data", "<span class=\"section-number\">3.4.8.9. </span>Compare classifiers on the digits data", "<span class=\"section-number\">3.4.8.13. </span>Simple visualization and classification of the digits dataset", "<span class=\"section-number\">3.4.8.14. </span>The eigenfaces example: chaining PCA and SVMs", "<span class=\"section-number\">3.4.8.12. </span>Nearest-neighbor prediction on iris", "<span class=\"section-number\">3.4.8.4. </span>Plot 2D views of the iris dataset", "<span class=\"section-number\">3.4.8.6. </span>Use the RidgeCV and LassoCV to set the regularization parameter", "<span class=\"section-number\">3.4.8.3. </span>A simple linear regression", "<span class=\"section-number\">3.4.8.2. </span>Measuring Decision Tree performance", "<span class=\"section-number\">3.4.8.1. </span>Demo PCA in 2D", "<span class=\"section-number\">3.4.8.10. </span>Plot fitting a 9th order polynomial", "<span class=\"section-number\">3.4.8.8. </span>Simple picture of the formal problem of machine learning", "<span class=\"section-number\">3.4.8.15. </span>Example of linear and non-linear models", "<span class=\"section-number\">3.4.8.5. </span>tSNE to visualize digits", "<span class=\"section-number\">3.4.8.7. </span>Plot variance and regularization in linear models", "Computation times", "<span class=\"section-number\">3.4. </span>scikit-learn: machine learning in Python", "Full code for the figures", "<span class=\"section-number\">3.1.6.8. </span>Air fares before and after 9/11", "<span class=\"section-number\">3.1.6.3. </span>Analysis of Iris petal and sepal sizes", "<span class=\"section-number\">3.1.6.1. </span>Boxplots and paired differences", "<span class=\"section-number\">3.1.6.2. </span>Plotting simple quantities of a pandas dataframe", "<span class=\"section-number\">3.1.6.4. </span>Simple Regression", "<span class=\"section-number\">3.1.6.5. </span>Multiple Regression", "<span class=\"section-number\">3.1.6.7. </span>Visualizing factors influencing wages", "<span class=\"section-number\">3.1.6.6. </span>Test for an education/gender interaction in wages", "Computation times", "<span class=\"section-number\">3.1.7.1. </span>Solutions to this chapter\u2019s exercises", "Relating Gender and IQ", "Computation times", "<span class=\"section-number\">3.1. </span>Statistics in Python", "<span class=\"section-number\">3.2. </span>Sympy : Symbolic Mathematics in Python", "About the Scientific Python Lectures", "Computation times"], "titleterms": {"": [1, 8, 41, 53, 76, 87, 99, 157, 158, 251, 252, 262, 265, 267], "0": [1, 267], "1": [1, 88, 210, 211, 267], 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