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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","&lt;no title&gt;","&lt;no title&gt;","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 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