All Samples(18) | Call(0) | Derive(0) | Import(18)
Defines a multi-dimensional array and useful procedures for Numerical computation.
Functions
- array - NumPy Array construction
- zeros - Return an array of all zeros
- empty - Return an unitialized array
- shape - Return shape of sequence or array
- rank - Return number of dimensions
- size - Return number of elements in entire array or a
certain dimension
- fromstring - Construct array from (byte) string
- take - Select sub-arrays using sequence of indices
- put - Set sub-arrays using sequence of 1-D indices
- putmask - Set portion of arrays using a mask
- reshape - Return array with new shape
- repeat - Repeat elements of array
- choose - Construct new array from indexed array tuple
- correlate - Correlate two 1-d arrays
- searchsorted - Search for element in 1-d array
- sum - Total sum over a specified dimension
- average - Average, possibly weighted, over axis or array.
- cumsum - Cumulative sum over a specified dimension
- product - Total product over a specified dimension
- cumproduct - Cumulative product over a specified dimension
- alltrue - Logical and over an entire axis
- sometrue - Logical or over an entire axis
- allclose - Tests if sequences are essentially equal
More Functions:
- arange - Return regularly spaced array
- asarray - Guarantee NumPy array
- convolve - Convolve two 1-d arrays
- swapaxes - Exchange axes
- concatenate - Join arrays together
- transpose - Permute axes
- sort - Sort elements of array
- argsort - Indices of sorted array
- argmax - Index of largest value
- argmin - Index of smallest value
- inner - Innerproduct of two arrays
- dot - Dot product (matrix multiplication)
- outer - Outerproduct of two arrays
- resize - Return array with arbitrary new shape
- indices - Tuple of indices
- fromfunction - Construct array from universal function
- diagonal - Return diagonal array
- trace - Trace of array
- dump - Dump array to file object (pickle)
- dumps - Return pickled string representing data
- load - Return array stored in file object
- loads - Return array from pickled string
- ravel - Return array as 1-D
- nonzero - Indices of nonzero elements for 1-D array
- shape - Shape of array
- where - Construct array from binary result
- compress - Elements of array where condition is true
- clip - Clip array between two values
- ones - Array of all ones
- identity - 2-D identity array (matrix)
(Universal) Math Functions
add logical_or exp
subtract logical_xor log
multiply logical_not log10
divide maximum sin
divide_safe minimum sinh
conjugate bitwise_and sqrt
power bitwise_or tan
absolute bitwise_xor tanh
negative invert ceil
greater left_shift fabs
greater_equal right_shift floor
less arccos arctan2
less_equal arcsin fmod
equal arctan hypot
not_equal cos around
logical_and cosh sign
arccosh arcsinh arctanhsrc/n/u/numpy-refactor-HEAD/numpy/lib/utils.py numpy-refactor(Download)
d = os.path.join(os.path.dirname(numpy.__file__), 'core', 'include')
else:
# using installed numpy core headers
import numpy.core as core
d = os.path.join(os.path.dirname(core.__file__), 'include')
return d
src/p/d/pdb2pqr-HEAD/trunk/pdb2pqr/contrib/numpy-1.1.0/numpy/lib/utils.py pdb2pqr(Download)
d = os.path.join(os.path.dirname(numpy.__file__), 'core', 'include')
else:
# using installed numpy core headers
import numpy.core as core
d = os.path.join(os.path.dirname(core.__file__), 'include')
return d
src/n/u/numpy-HEAD/numpy/lib/utils.py numpy(Download)
d = os.path.join(os.path.dirname(numpy.__file__), 'core', 'include')
else:
# using installed numpy core headers
import numpy.core as core
d = os.path.join(os.path.dirname(core.__file__), 'include')
return d
src/p/d/pdb2pqr-HEAD/pdb2pqr/contrib/numpy-1.1.0/numpy/lib/utils.py pdb2pqr(Download)
d = os.path.join(os.path.dirname(numpy.__file__), 'core', 'include')
else:
# using installed numpy core headers
import numpy.core as core
d = os.path.join(os.path.dirname(core.__file__), 'include')
return d
src/n/u/numpy3k-HEAD/numpy/lib/utils.py numpy3k(Download)
d = os.path.join(os.path.dirname(numpy.__file__), 'core', 'include')
else:
# using installed numpy core headers
import numpy.core as core
d = os.path.join(os.path.dirname(core.__file__), 'include')
return d
src/n/u/numpy-1.5.0/numpy/lib/utils.py numpy(Download)
d = os.path.join(os.path.dirname(numpy.__file__), 'core', 'include')
else:
# using installed numpy core headers
import numpy.core as core
d = os.path.join(os.path.dirname(core.__file__), 'include')
return d
src/n/i/NiPy-OLD-HEAD/nipy/io/imageformats/setup.py NiPy-OLD(Download)
import os.path
import numpy.core
def configuration(parent_package='',top_path=None):
from numpy.distutils.misc_util import Configuration
config = Configuration('imageformats', parent_package, top_path)
config.add_subpackage('testing')
src/n/i/NiPy-OLD-HEAD/nipy/algorithms/statistics/setup.py NiPy-OLD(Download)
import os.path
import numpy.core
def configuration(parent_package='',top_path=None):
from numpy.distutils.misc_util import Configuration
config = Configuration('statistics', parent_package, top_path)
src/n/i/NiPy-OLD-HEAD/nipy/algorithms/diagnostics/setup.py NiPy-OLD(Download)
import os.path
import numpy.core
def configuration(parent_package='',top_path=None):
from numpy.distutils.misc_util import Configuration
config = Configuration('diagnostics', parent_package, top_path)
config.add_data_dir('tests')
src/n/i/nipy-HEAD/nipy/io/imageformats/setup.py nipy(Download)
# emacs: -*- mode: python; py-indent-offset: 4; indent-tabs-mode: nil -*-
# vi: set ft=python sts=4 ts=4 sw=4 et:
import os.path
import numpy.core
def configuration(parent_package='',top_path=None):
from numpy.distutils.misc_util import Configuration
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