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set_module) get_includeinfo show_runtimenumpyc ddl m } ddlm}m}m} t
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Print information about various resources in the system
including available intrinsic support and BLAS/LAPACK library
in use
.. versionadded:: 1.24.0
See Also
--------
show_config : Show libraries in the system on which NumPy was built.
Notes
-----
1. Information is derived with the help of `threadpoolctl `_
library if available.
2. SIMD related information is derived from ``__cpu_features__``,
``__cpu_baseline__`` and ``__cpu_dispatch__``
r )pprint__cpu_baseline____cpu_dispatch____cpu_features__)
numpy_versionpythonunamesimd_extensions)baselinefound not_found&ignore_floating_point_errors_in_matmulN)threadpool_infozWARNING: `threadpoolctl` not found in system! Install it by `pip install threadpoolctl`. Once installed, try `np.show_runtime` again for more detailed build information)r
numpy._core._multiarray_umathr r
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Return the directory that contains the NumPy \*.h header files.
Extension modules that need to compile against NumPy may need to use this
function to locate the appropriate include directory.
Notes
-----
When using ``setuptools``, for example in ``setup.py``::
import numpy as np
...
Extension('extension_name', ...
include_dirs=[np.get_include()])
...
Note that a CLI tool ``numpy-config`` was introduced in NumPy 2.0, using
that is likely preferred for build systems other than ``setuptools``::
$ numpy-config --cflags
-I/path/to/site-packages/numpy/_core/include
# Or rely on pkg-config:
$ export PKG_CONFIG_PATH=$(numpy-config --pkgconfigdir)
$ pkg-config --cflags
-I/path/to/site-packages/numpy/_core/include
Examples
--------
>>> np.get_include()
'.../site-packages/numpy/core/include' # may vary
r Nr include) r show_configospathjoindirname__file__ numpy._corer )r dr s r* r r M sq F GGLL 8'9 M
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Determines the leading whitespace that could be removed from all the lines.
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j }t d|| t d| j | t d || t d
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j | | d} nP|dk( r&t | d| | t
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j dk7 } t d || | t d| j | y)aO Provide information about ndarray obj.
Parameters
----------
obj : ndarray
Must be ndarray, not checked.
output
Where printed output goes.
Notes
-----
Copied over from the numarray module prior to its removal.
Adapted somewhat as only numpy is an option now.
Called by info.
rA c | S N )ra s r* z_info.. s 1 r5 __class__rU Nzclass: filezshape: z strides: z
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}|d dk7 s | }}|r^t! d| |D ]K }t= | |d }|'|j? |j5 | xs d \ }}t! d| d | M yyt | d r t! |j5 | | yy# t$ $ r Y w xY w# t. $ r d} Y w xY w# t. $ r d} Y }w xY wc c}w ) a
Get help information for an array, function, class, or module.
Parameters
----------
object : object or str, optional
Input object or name to get information about. If `object` is
an `ndarray` instance, information about the array is printed.
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.
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. ***
When the argument is an array, information about the array is printed.
>>> a = np.array([[1 + 2j, 3, -4], [-5j, 6, 0]], dtype=np.complex64)
>>> np.info(a)
class: ndarray
shape: (2, 3)
strides: (24, 8)
itemsize: 8
aligned: True
contiguous: True
fortran: False
data pointer: 0x562b6e0d2860 # may vary
byteorder: little
byteswap: False
type: complex64
r N_ppimport_importer_ppimport_module_ppimport_attr)r z$
*** Repeat reference found in z *** rk z *** Found in z ***-rB z Help for z not found.z
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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.
r )axisF)where) sizetaker isnanma
isMaskedArrayfilledanyrY genericcopyto)dataresultr potential_nansns r* _median_nancheckr s * yyA~
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Returns a string containing the CPU features supported
by the current build.
The format of the string can be explained as follows:
- Dispatched features supported by the running machine end with `*`.
- Dispatched features not supported by the running machine
end with `?`.
- Remaining features represent the baseline.
Returns:
str: A formatted string indicating the supported CPU features.
r r rA rC *?)r r r
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Returns the dtype unchanged if it contained no metadata or a copy of the
dtype if it (or any of its structure dtypes) contained metadata.
This utility is used by `np.save` and `np.savez` to drop metadata before
saving.
.. note::
Due to its limitation this function may move to a more appropriate
home or change in the future and is considered semi-public API only.
.. warning::
This function does not preserve more strange things like record dtypes
and user dtypes may simply return the wrong thing. If you need to be
sure about the latter, check the result with:
``np.can_cast(new_dtype, dtype, casting="no")``.
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