/
usr
/
lib64
/
python2.6
/
site-packages
/
numpy
/
/usr/lib64/python2.6/site-packages/numpy
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compat/
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core/
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distutils/
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doc/
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fft/
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lib/
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linalg/
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ma/
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matrixlib/
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numarray/
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oldnumeric/
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polynomial/
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random/
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testing/
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tests/
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add_newdocs.py
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ctypeslib.py
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ctypeslib.pyc
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dual.py
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dual.pyc
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dual.pyo
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matlib.py
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setup.py
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setupscons.pyc
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version.py
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version.pyc
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_import_tools.py
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_import_tools.pyc
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__config__.py
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__config__.pyc
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__init__.py
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Edit:
/usr/lib64/python2.6/site-packages/numpy/__init__.py
(4875B)
""" NumPy ===== Provides 1. An array object of arbitrary homogeneous items 2. Fast mathematical operations over arrays 3. Linear Algebra, Fourier Transforms, Random Number Generation How to use the documentation ---------------------------- Documentation is available in two forms: docstrings provided with the code, and a loose standing reference guide, available from `the NumPy homepage <http://www.scipy.org>`_. We recommend exploring the docstrings using `IPython <http://ipython.scipy.org>`_, an advanced Python shell with TAB-completion and introspection capabilities. See below for further instructions. The docstring examples assume that `numpy` has been imported as `np`:: >>> import numpy as np Code snippets are indicated by three greater-than signs:: >>> x = x + 1 Use the built-in ``help`` function to view a function's docstring:: >>> help(np.sort) For some objects, ``np.info(obj)`` may provide additional help. This is particularly true if you see the line "Help on ufunc object:" at the top of the help() page. Ufuncs are implemented in C, not Python, for speed. The native Python help() does not know how to view their help, but our np.info() function does. To search for documents containing a keyword, do:: >>> np.lookfor('keyword') General-purpose documents like a glossary and help on the basic concepts of numpy are available under the ``doc`` sub-module:: >>> from numpy import doc >>> help(doc) Available subpackages --------------------- doc Topical documentation on broadcasting, indexing, etc. lib Basic functions used by several sub-packages. random Core Random Tools linalg Core Linear Algebra Tools fft Core FFT routines polynomial Polynomial tools testing Numpy testing tools f2py Fortran to Python Interface Generator. distutils Enhancements to distutils with support for Fortran compilers support and more. Utilities --------- test Run numpy unittests show_config Show numpy build configuration dual Overwrite certain functions with high-performance Scipy tools matlib Make everything matrices. __version__ Numpy version string Viewing documentation using IPython ----------------------------------- Start IPython with the NumPy profile (``ipython -p numpy``), which will import `numpy` under the alias `np`. Then, use the ``cpaste`` command to paste examples into the shell. To see which functions are available in `numpy`, type ``np.<TAB>`` (where ``<TAB>`` refers to the TAB key), or use ``np.*cos*?<ENTER>`` (where ``<ENTER>`` refers to the ENTER key) to narrow down the list. To view the docstring for a function, use ``np.cos?<ENTER>`` (to view the docstring) and ``np.cos??<ENTER>`` (to view the source code). Copies vs. in-place operation ----------------------------- Most of the functions in `numpy` return a copy of the array argument (e.g., `np.sort`). In-place versions of these functions are often available as array methods, i.e. ``x = np.array([1,2,3]); x.sort()``. Exceptions to this rule are documented. """ # We first need to detect if we're being called as part of the numpy setup # procedure itself in a reliable manner. try: __NUMPY_SETUP__ except NameError: __NUMPY_SETUP__ = False if __NUMPY_SETUP__: import sys as _sys print >> _sys.stderr, 'Running from numpy source directory.' del _sys else: try: from numpy.__config__ import show as show_config except ImportError, e: msg = """Error importing numpy: you should not try to import numpy from its source directory; please exit the numpy source tree, and relaunch your python intepreter from there.""" raise ImportError(msg) from version import version as __version__ from _import_tools import PackageLoader def pkgload(*packages, **options): loader = PackageLoader(infunc=True) return loader(*packages, **options) import add_newdocs __all__ = ['add_newdocs'] pkgload.__doc__ = PackageLoader.__call__.__doc__ from testing import Tester test = Tester().test bench = Tester().bench import core from core import * import compat import lib from lib import * import linalg import fft import polynomial import random import ctypeslib import ma import matrixlib as _mat from matrixlib import * # Make these accessible from numpy name-space # but not imported in from numpy import * from __builtin__ import bool, int, long, float, complex, \ object, unicode, str from core import round, abs, max, min __all__.extend(['__version__', 'pkgload', 'PackageLoader', 'show_config']) __all__.extend(core.__all__) __all__.extend(_mat.__all__) __all__.extend(lib.__all__) __all__.extend(['linalg', 'fft', 'random', 'ctypeslib', 'ma'])
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