SciPy Sub-Module

A SciPy Sub-Module is a python library module within a SciPy library.

• Example(s):
  • scipy.cluster, implements hierarchical clustering, vector quantization, K-means.
  • scipy.fftpack, a Discrete Fourier Transform systems.
  • scipy.integrate, a numerical integration systems.
  • scipy.interpolate, implements interpolation tools.
  • scipy.linalg, implements linear algebra routines.
  • scipy.ndimage, for multi-dimensional image processing.
  • scipy.optimize, implements optimization algorithms including scipy.optimize.leastsq, scipy.optimize.nnls, scipy.optimize.curve_fit, and scipy.optimize.linprog.
  • scipy.signal, a signal processing systems.
  • scipy.sparse, a sparse matrix system.
  • scipy.spatial, for KD-trees, nearest neighbors, distance functions.
  • scipy.stats, implements statistical functions.
  • …
• Counter-Example(s):
  • a numpy Module.
  • a sklearn Module.
• See: Scientific Processing System.

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References

2014

• http://en.wikipedia.org/wiki/SciPy#The_SciPy_Library.2FPackage
  • The SciPy package of key algorithms and functions core to Python's scientific computing capabilities. Available sub-packages include:
    • cluster: hierarchical clustering, vector quantization, K-means
    • fftpack: Discrete Fourier Transform algorithms
    • integrate: numerical integration routines
    • interpolate: interpolation tools
    • io: data input and output
    • lib: Python wrappers to external libraries
    • linalg: linear algebra routines
    • misc: miscellaneous utilities (e.g. image reading/writing)
    • ndimage: various functions for multi-dimensional image processing
    • optimize: optimization algorithms including linear programming
    • signal: signal processing tools
    • sparse: sparse matrix and related algorithms
    • spatial: KD-trees, nearest neighbors, distance functions
    • special: special functions
    • stats: statistical functions
    • weave: tool for writing C/C++ code as Python multiline strings

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