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SciPy: A scientific computing package for Python
Documentation is available in the docstrings and
online at
SciPy imports all the functions from the NumPy namespace, and in
addition provides:
odr --- Orthogonal Distance Regression [*]
misc --- Various utilities that don't have
another home.
cluster --- Vector Quantization / Kmeans [*]
fftpack --- Discrete Fourier Transform algorithms
io --- Data input and output [*]
sparse.linalg.eigen.lobpcg --- Locally Optimal Block Preconditioned
Conjugate Gradient Method (LOBPCG) [*]
special --- Airy Functions [*]
lib.blas --- Wrappers to BLAS library [*]
sparse.linalg.eigen --- Sparse Eigenvalue Solvers [*]
stats --- Statistical Functions [*]
lib --- Python wrappers to external libraries
lib.lapack --- Wrappers to LAPACK library [*]
maxentropy --- Routines for fitting maximum entropy
models [*]
integrate --- Integration routines [*]
ndimage --- n-dimensional image package [*]
linalg --- Linear algebra routines [*]
spatial --- Spatial data structures and algorithms
interpolate --- Interpolation Tools [*]
sparse.linalg --- Sparse Linear Algebra [*]
sparse.linalg.dsolve.umfpack --- :Interface to the UMFPACK library: [*]
sparse.linalg.dsolve --- Linear Solvers [*]
optimize --- Optimization Tools [*]
sparse.linalg.eigen.arpack --- Eigenvalue solver using iterative
methods. [*]
signal --- Signal Processing Tools [*]
sparse --- Sparse Matrices [*]
[*] - using a package requires explicit import
Global symbols from subpackages
misc --> info, factorial, factorial2, factorialk,
comb, who, lena, central_diff_weights,
derivative, pade, source
fftpack --> fft, fftn, fft2, ifft, ifft2, ifftn,
fftshift, ifftshift, fftfreq
stats --> find_repeats
linalg.dsolve.umfpack --> UmfpackContext
Utility tools
test --- Run scipy unittests
show_config --- Show scipy build configuration
show_numpy_config --- Show numpy build configuration
__version__ --- Scipy version string
__numpy_version__ --- Numpy version string
__all__ = ['pkgload','test']
from numpy import show_config as show_numpy_config
if show_numpy_config is None:
raise ImportError("Cannot import scipy when running from numpy source directory.")
from numpy import __version__ as __numpy_version__
# Import numpy symbols to scipy name space
import numpy as _num
from numpy import oldnumeric
from numpy import *
from numpy.random import rand, randn
from numpy.fft import fft, ifft
from numpy.lib.scimath import *
# Emit a warning if numpy is too old
majver, minver = [float(i) for i in _num.version.version.split('.')[:2]]
if majver < 1 or (majver == 1 and minver < 2):
import warnings
warnings.warn("Numpy 1.2.0 or above is recommended for this version of " \
"scipy (detected version %s)" % _num.version.version,
__all__ += ['oldnumeric']+_num.__all__
__all__ += ['randn', 'rand', 'fft', 'ifft']
del _num
# Remove the linalg imported from numpy so that the scipy.linalg package can be
# imported.
del linalg
from scipy.__config__ import show as show_config
except ImportError:
msg = """Error importing scipy: you cannot import scipy while
being in scipy source directory; please exit the scipy source
tree first, and relaunch your python intepreter."""
raise ImportError(msg)
from scipy.version import version as __version__
# Load scipy packages and their global_symbols
from numpy._import_tools import PackageLoader
import os as _os
SCIPY_IMPORT_VERBOSE = int(_os.environ.get('SCIPY_IMPORT_VERBOSE','-1'))
del _os
pkgload = PackageLoader()
from numpy.testing import Tester
test = Tester().test
bench = Tester().bench
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