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Return the directory that contains the NumPy \*.h header files.
Extension modules that need to compile against NumPy should use this
function to locate the appropriate include directory.
Notes
-----
When using ``distutils``, for example in ``setup.py``::
import numpy as np
...
Extension('extension_name', ...
include_dirs=[np.get_include()])
...
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Decorator class to deprecate old functions.
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See Also
--------
deprecate
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Issues a DeprecationWarning, adds warning to `old_name`'s
docstring, rebinds ``old_name.__name__`` and returns the new
function object.
This function may also be used as a decorator.
Parameters
----------
func : function
The function to be deprecated.
old_name : str, optional
The name of the function to be deprecated. Default is None, in
which case the name of `func` is used.
new_name : str, optional
The new name for the function. Default is None, in which case the
deprecation message is that `old_name` is deprecated. If given, the
deprecation message is that `old_name` is deprecated and `new_name`
should be used instead.
message : str, optional
Additional explanation of the deprecation. Displayed in the
docstring after the warning.
Returns
-------
old_func : function
The deprecated function.
Examples
--------
Note that ``olduint`` returns a value after printing Deprecation
Warning:
>>> olduint = np.deprecate(np.uint)
DeprecationWarning: `uint64` is deprecated! # may vary
>>> olduint(6)
6
r r2 N�r" )r. r? �fnr r r r � s
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Deprecates a function and includes the deprecation in its docstring.
This function is used as a decorator. It returns an object that can be
used to issue a DeprecationWarning, by passing the to-be decorated
function as argument, this adds warning to the to-be decorated function's
docstring and returns the new function object.
See Also
--------
deprecate : Decorate a function such that it issues a `DeprecationWarning`
Parameters
----------
msg : str
Additional explanation of the deprecation. Displayed in the
docstring after the warning.
Returns
-------
obj : object
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Returns pointers to the end-points of an array.
Parameters
----------
a : ndarray
Input array. It must conform to the Python-side of the array
interface.
Returns
-------
(low, high) : tuple of 2 integers
The first integer is the first byte of the array, the second
integer is just past the last byte of the array. If `a` is not
contiguous it will not use every byte between the (`low`, `high`)
values.
Examples
--------
>>> I = np.eye(2, dtype='f'); I.dtype
dtype('float32')
>>> low, high = np.byte_bounds(I)
>>> high - low == I.size*I.itemsize
True
>>> I = np.eye(2); I.dtype
dtype('float64')
>>> low, high = np.byte_bounds(I)
>>> high - low == I.size*I.itemsize
True
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Print the NumPy arrays in the given dictionary.
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namespace).
Parameters
----------
vardict : dict, optional
A dictionary possibly containing ndarrays. Default is globals().
Returns
-------
out : None
Returns 'None'.
Notes
-----
Prints out the name, shape, bytes and type of all of the ndarrays
present in `vardict`.
Examples
--------
>>> a = np.arange(10)
>>> b = np.ones(20)
>>> np.who()
Name Shape Bytes Type
===========================================================
a 10 80 int64
b 20 160 float64
Upper bound on total bytes = 240
>>> d = {'x': np.arange(2.0), 'y': np.arange(3.0), 'txt': 'Some str',
... 'idx':5}
>>> np.who(d)
Name Shape Bytes Type
===========================================================
x 2 16 float64
y 3 24 float64
Upper bound on total bytes = 40
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obj : ndarray
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output
Where printed output goes.
Notes
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Adapted somewhat as only numpy is an option now.
Called by info.
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Get help information for a function, class, or module.
Parameters
----------
object : object or str, optional
Input object or name to get information about. If `object` is a
numpy object, its docstring is given. If it is a string, available
modules are searched for matching objects. If None, information
about `info` itself is returned.
maxwidth : int, optional
Printing width.
output : file like object, optional
File like object that the output is written to, default is
``None``, in which case ``sys.stdout`` will be used.
The object has to be opened in 'w' or 'a' mode.
toplevel : str, optional
Start search at this level.
See Also
--------
source, lookfor
Notes
-----
When used interactively with an object, ``np.info(obj)`` is equivalent
to ``help(obj)`` on the Python prompt or ``obj?`` on the IPython
prompt.
Examples
--------
>>> np.info(np.polyval) # doctest: +SKIP
polyval(p, x)
Evaluate the polynomial p at x.
...
When using a string for `object` it is possible to get multiple results.
>>> np.info('fft') # doctest: +SKIP
*** Found in numpy ***
Core FFT routines
...
*** Found in numpy.fft ***
fft(a, n=None, axis=-1)
...
*** Repeat reference found in numpy.fft.fftpack ***
*** Total of 3 references found. ***
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Print or write to a file the source code for a NumPy object.
The source code is only returned for objects written in Python. Many
functions and classes are defined in C and will therefore not return
useful information.
Parameters
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object : numpy object
Input object. This can be any object (function, class, module,
...).
output : file object, optional
If `output` not supplied then source code is printed to screen
(sys.stdout). File object must be created with either write 'w' or
append 'a' modes.
See Also
--------
lookfor, info
Examples
--------
>>> np.source(np.interp) #doctest: +SKIP
In file: /usr/lib/python2.6/dist-packages/numpy/lib/function_base.py
def interp(x, xp, fp, left=None, right=None):
""".... (full docstring printed)"""
if isinstance(x, (float, int, number)):
return compiled_interp([x], xp, fp, left, right).item()
else:
return compiled_interp(x, xp, fp, left, right)
The source code is only returned for objects written in Python.
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Not available for this object.
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Do a keyword search on docstrings.
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docstring for it to be returned as a result, but the order does
not matter.
Parameters
----------
what : str
String containing words to look for.
module : str or list, optional
Name of module(s) whose docstrings to go through.
import_modules : bool, optional
Whether to import sub-modules in packages. Default is True.
regenerate : bool, optional
Whether to re-generate the docstring cache. Default is False.
output : file-like, optional
File-like object to write the output to. If omitted, use a pager.
See Also
--------
source, info
Notes
-----
Relevance is determined only roughly, by checking if the keywords occur
in the function name, at the start of a docstring, etc.
Examples
--------
>>> np.lookfor('binary representation') # doctest: +SKIP
Search results for 'binary representation'
------------------------------------------
numpy.binary_repr
Return the binary representation of the input number as a string.
numpy.core.setup_common.long_double_representation
Given a binary dump as given by GNU od -b, look for long double
numpy.base_repr
Return a string representation of a number in the given base system.
...
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Generate docstring cache for given module.
Parameters
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module : str, None, module
Module for which to generate docstring cache
import_modules : bool
Whether to import sub-modules in packages.
regenerate : bool
Re-generate the docstring cache
Returns
-------
cache : dict {obj_full_name: (docstring, kind, index), ...}
Docstring cache for the module, either cached one (regenerate=False)
or newly generated.
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Protected string evaluation.
Evaluate a string containing a Python literal expression without
allowing the execution of arbitrary non-literal code.
.. warning::
This function is identical to :py:meth:`ast.literal_eval` and
has the same security implications. It may not always be safe
to evaluate large input strings.
Parameters
----------
source : str
The string to evaluate.
Returns
-------
obj : object
The result of evaluating `source`.
Raises
------
SyntaxError
If the code has invalid Python syntax, or if it contains
non-literal code.
Examples
--------
>>> np.safe_eval('1')
1
>>> np.safe_eval('[1, 2, 3]')
[1, 2, 3]
>>> np.safe_eval('{"foo": ("bar", 10.0)}')
{'foo': ('bar', 10.0)}
>>> np.safe_eval('import os')
Traceback (most recent call last):
...
SyntaxError: invalid syntax
>>> np.safe_eval('open("/home/user/.ssh/id_dsa").read()')
Traceback (most recent call last):
...
ValueError: malformed node or string: <_ast.Call object at 0x...>
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Utility function to check median result from data for NaN values at the end
and return NaN in that case. Input result can also be a MaskedArray.
Parameters
----------
data : array
Sorted input data to median function
result : Array or MaskedArray
Result of median function.
axis : int
Axis along which the median was computed.
Returns
-------
result : scalar or ndarray
Median or NaN in axes which contained NaN in the input. If the input
was an array, NaN will be inserted in-place. If a scalar, either the
input itself or a scalar NaN.
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Returns a string contains the supported CPU features by the current build.
The string format can be explained as follows:
- dispatched features that are supported by the running machine
end with `*`.
- dispatched features that are "not" supported by the running machine
end with `?`.
- remained features are representing the baseline.
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r� )N)r )N)Nr� Nr )NTFN)-r rG r; rw �rer+ Znumpy.core.numerictypesr r r Znumpy.core.overridesr r r r r r r� r� r r! r" r8 r r
r r rr r� r� r| r� r r� r
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