• Scipy Cookbook
  • Introduction
  • 1. SciPy Cookbook
  • 2. Compiling Extensions
    • 2.1. Compiling Extension Modules on Windows using mingw
  • 3. Graphics
    • 3.1. Line Integral Convolution
    • 3.2. Mayavi
    • 3.3. Vtk volume rendering
    • 3.4. Input Output
    • 3.5. Data Acquisition with NIDAQmx
    • 3.6. Data acquisition with PyUL
    • 3.7. Fortran I/O Formats
  • 4. Input and output
    • 4.1. LAS reader
    • 4.2. Reading SPE file from CCD camera
    • 4.3. Reading mat files
    • 4.4. hdf5 in Matlab
  • 5. Matplotlib / 3D Plotting
    • 5.1. Matplotlib VTK integration
    • 5.2. Matplotlib: mplot3d
  • 6. Matplotlib / Embedding Plots in Apps
    • 6.1. Embedding In Wx
    • 6.2. Matplotlib: pyside
    • 6.3. Matplotlib: scrolling plot
  • 7. Matplotlib / Misc
    • 7.1. Load image
    • 7.2. Matplotlib: adjusting image size
    • 7.3. Matplotlib: compiling matplotlib on solaris10
    • 7.4. Matplotlib: deleting an existing data series
    • 7.5. Matplotlib: django
    • 7.6. Matplotlib: interactive plotting
    • 7.7. Matplotlib: matplotlib and zope
    • 7.8. Matplotlib: multiple subplots with one axis label
    • 7.9. Matplotlib: qt with ipython and designer
    • 7.10. Matplotlib: using matplotlib in a CGI script
  • 8. Matplotlib / Pseudo Color Plots
    • 8.1. Matplotlib: colormap transformations
    • 8.2. Matplotlib: converting a matrix to a raster image
    • 8.3. Matplotlib: gridding irregularly spaced data
    • 8.4. Matplotlib: loading a colormap dynamically
    • 8.5. Matplotlib: plotting images with special values
    • 8.6. Matplotlib: show colormaps
  • 9. Matplotlib / Simple Plotting
    • 9.1. Matplotlib: animations
    • 9.2. Matplotlib: arrows
    • 9.3. Matplotlib: bar charts
    • 9.4. Matplotlib: custom log labels
    • 9.5. Matplotlib: hint on diagrams
    • 9.6. Matplotlib: legend
    • 9.7. Matplotlib: maps
    • 9.8. Matplotlib: multicolored line
    • 9.9. Matplotlib: multiline plots
    • 9.10. Matplotlib: plotting values with masked arrays
    • 9.11. Matplotlib: shaded regions
    • 9.12. Matplotlib: sigmoidal functions
    • 9.13. Matplotlib: thick axes
    • 9.14. Matplotlib: transformations
    • 9.15. Matplotlib: unfilled histograms
  • 10. Matplotlib / Typesetting
    • 10.1. Matplotlib: latex examples
    • 10.2. Matplotlib: using tex
    • 10.3. Mayavi
    • 10.4. Mayavi surf
    • 10.5. Mayavi tips
    • 10.6. Mayavi: running mayavi 2
    • 10.7. Scripting Mayavi 2
  • 11. Mayavi / TVTK
    • 11.1. Mayabi: mlab
    • 11.2. Mayavi tvtk
  • 12. Numpy & Scipy / Advanced topics
    • 12.1. Views versus copies in NumPy
  • 13. Numpy & Scipy / Interpolation
    • 13.1. Interpolation
    • 13.2. Using radial basis functions for smoothing/interpolation
  • 14. Numpy & Scipy / Linear Algebra
    • 14.1. Rank and nullspace of a matrix
  • 15. Numpy & Scipy / Matplotlib
    • 15.1. Histograms
  • 16. Numpy & Scipy / Optimization and fitting techniques
    • 16.1. Fitting data
    • 16.2. Large-scale bundle adjustment in scipy
    • 16.3. Least squares circle
    • 16.4. Linear regression
    • 16.5. OLS
    • 16.6. Optimization and fit demo
    • 16.7. Optimization demo
    • 16.8. RANSAC
    • 16.9. Robust nonlinear regression in scipy
    • 16.10. Solving a discrete boundary-value problem in scipy
  • 17. Numpy & Scipy / Ordinary differential equations
    • 17.1. Coupled spring-mass system
    • 17.2. Korteweg de Vries equation
    • 17.3. Matplotlib: lotka volterra tutorial
    • 17.4. Modeling a Zombie Apocalypse
    • 17.5. Theoretical ecology: Hastings and Powell
  • 18. Numpy & Scipy / Other examples
    • 18.1. Applying a FIR filter
    • 18.2. Brownian Motion
    • 18.3. Butterworth Bandpass
    • 18.4. Communication theory
    • 18.5. Correlated Random Samples
    • 18.6. Easy multithreading
    • 18.7. Eye Diagram
    • 18.8. FIR filter
    • 18.9. Filtfilt
    • 18.10. Finding the Convex Hull of a 2-D Dataset
    • 18.11. Finding the minimum point in the convex hull of a finite set of points
    • 18.12. Frequency swept signals
    • 18.13. KDTree example
    • 18.14. Kalman filtering
    • 18.15. Linear classification
    • 18.16. Particle filter
    • 18.17. Rebinning
    • 18.18. Savitzky Golay Filtering
    • 18.19. Smoothing of a 1D signal
    • 18.20. Solving large Markov Chains
    • 18.21. Watershed
  • 19. Numpy & Scipy / Root finding
    • 19.1. Function intersections
    • 19.2. Spherical Bessel Zeros
    • 19.3. Numpy & Scipy / Tips and tricks
    • 19.4. Addressing Array Columns by Name
    • 19.5. Building arrays
    • 19.6. Convolution-like operations
    • 19.7. Indexing numpy arrays
    • 19.8. MetaArray
    • 19.9. Multidot
    • 19.10. Object arrays using record arrays
    • 19.11. Stride tricks for the Game of Life
    • 19.12. accumarray like function
  • 20. Other examples
    • 20.1. C Extensions for Using NumPy Arrays
    • 20.2. Embedding in Traits GUI
    • 20.3. Matplotlib: drag’n’drop text example
    • 20.4. Matplotlib: treemap
    • 20.5. Mayavi: Install python stuff from source
    • 20.6. Mayavi: examples
    • 20.7. Reading custom text files with Pyparsing
    • 20.8. Scripting Mayavi 2: basic modules
    • 20.9. Scripting Mayavi 2: filters
    • 20.10. Scripting Mayavi 2: main modules
  • 21. Performance
    • 21.1. A beginners guide to using Python for performance computing
    • 21.2. Parallel Programming with numpy and scipy
  • 22. Scientific GUIs
    • 22.1. wxPython dialogs
  • 23. Scientific Scripts
    • 23.1. FDTD Algorithm Applied to the Schrödinger Equation
    • 23.2. Using NumPy With Other Languages (Advanced)
    • 23.3. C extensions
    • 23.4. Ctypes
    • 23.5. F2py
    • 23.6. Inline Weave With Basic Array Conversion (no Blitz)
    • 23.7. Pyrex And NumPy
    • 23.8. SWIG Numpy examples
    • 23.9. SWIG and Numpy
    • 23.10. SWIG memory deallocation
    • 23.11. f2py and numpy
  • 24. Outdated
    • 24.1. A numerical agnostic pyrex class
    • 24.2. Array, struct, and Pyrex
    • 24.3. Data Frames
    • 24.4. Python Imaging Library
    • 24.5. Recipes for timeseries
    • 24.6. The FortranFile class
    • 24.7. dbase
    • 24.8. xplt
Powered by GitBook

Scipy Cookbook

Matplotlib / Misc

  • Load image
  • Matplotlib: adjusting image size
  • Matplotlib: compiling matplotlib on solaris10
  • Matplotlib: deleting an existing data series
  • Matplotlib: django
  • Matplotlib: interactive plotting
  • Handling click events while zoomed
  • Matplotlib: matplotlib and zope
  • Matplotlib: multiple subplots with one axis label
  • Matplotlib: qt with ipython and designer
  • Matplotlib: using matplotlib in a CGI script