SciPy: Difference between revisions
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* [[Python_for_Data_Analysis#Overview|Python for Data Analysis]] | * [[Python_for_Data_Analysis#Overview|Python for Data Analysis]] | ||
=Overview= | |||
SciPy is a collection of packages addressing a number of foundational problems in scientific computing. | |||
=Modules= | |||
==<tt>scipy.integrate</tt>== | |||
Numerical integration routines and differential equation solvers. | |||
==<tt>scipy.linalg</tt>== | |||
Linear algebra routines and matrix decomposition extending beyond those provided by <code>numpy.linalg</code>. | |||
==<tt>scipy.optimize</tt>== | |||
Function optimizers (minimizers) and root finding algorithms. | |||
==<tt>scipy.signal</tt>== | |||
Signal processing tools. | |||
==<tt>scipy.sparse</tt>== | |||
Sparse matrices and sparse linear system solvers. | |||
==<tt>scipy.special</tt>== | |||
==<tt>scipy.stats</tt>== | |||
Standard continuous and discrete probability distributions (density functions, samplers, continuous distribution functions), various statistical tests and more descriptive statistics. | |||
Latest revision as of 23:44, 14 May 2024
External
Internal
Overview
SciPy is a collection of packages addressing a number of foundational problems in scientific computing.
Modules
scipy.integrate
Numerical integration routines and differential equation solvers.
scipy.linalg
Linear algebra routines and matrix decomposition extending beyond those provided by numpy.linalg.
scipy.optimize
Function optimizers (minimizers) and root finding algorithms.
scipy.signal
Signal processing tools.
scipy.sparse
Sparse matrices and sparse linear system solvers.
scipy.special
scipy.stats
Standard continuous and discrete probability distributions (density functions, samplers, continuous distribution functions), various statistical tests and more descriptive statistics.