941 lines
25 KiB
Python
941 lines
25 KiB
Python
|
"""
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|
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NumPy
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||
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|
=====
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|
|
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||
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Provides
|
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1. An array object of arbitrary homogeneous items
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2. Fast mathematical operations over arrays
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3. Linear Algebra, Fourier Transforms, Random Number Generation
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How to use the documentation
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----------------------------
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Documentation is available in two forms: docstrings provided
|
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with the code, and a loose standing reference guide, available from
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`the NumPy homepage <https://numpy.org>`_.
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We recommend exploring the docstrings using
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`IPython <https://ipython.org>`_, an advanced Python shell with
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|
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TAB-completion and introspection capabilities. See below for further
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instructions.
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The docstring examples assume that `numpy` has been imported as ``np``::
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>>> import numpy as np
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Code snippets are indicated by three greater-than signs::
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>>> x = 42
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>>> x = x + 1
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Use the built-in ``help`` function to view a function's docstring::
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>>> help(np.sort)
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... # doctest: +SKIP
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For some objects, ``np.info(obj)`` may provide additional help. This is
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particularly true if you see the line "Help on ufunc object:" at the top
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of the help() page. Ufuncs are implemented in C, not Python, for speed.
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The native Python help() does not know how to view their help, but our
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np.info() function does.
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Available subpackages
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---------------------
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lib
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Basic functions used by several sub-packages.
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random
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Core Random Tools
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linalg
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Core Linear Algebra Tools
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fft
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Core FFT routines
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polynomial
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Polynomial tools
|
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testing
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NumPy testing tools
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distutils
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Enhancements to distutils with support for
|
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Fortran compilers support and more (for Python <= 3.11)
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Utilities
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---------
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test
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Run numpy unittests
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show_config
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Show numpy build configuration
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__version__
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NumPy version string
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Viewing documentation using IPython
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-----------------------------------
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Start IPython and import `numpy` usually under the alias ``np``: `import
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numpy as np`. Then, directly past or use the ``%cpaste`` magic to paste
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examples into the shell. To see which functions are available in `numpy`,
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type ``np.<TAB>`` (where ``<TAB>`` refers to the TAB key), or use
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``np.*cos*?<ENTER>`` (where ``<ENTER>`` refers to the ENTER key) to narrow
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down the list. To view the docstring for a function, use
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``np.cos?<ENTER>`` (to view the docstring) and ``np.cos??<ENTER>`` (to view
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the source code).
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Copies vs. in-place operation
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|
-----------------------------
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Most of the functions in `numpy` return a copy of the array argument
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(e.g., `np.sort`). In-place versions of these functions are often
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available as array methods, i.e. ``x = np.array([1,2,3]); x.sort()``.
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Exceptions to this rule are documented.
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"""
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# start delvewheel patch
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def _delvewheel_patch_1_11_0():
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import os
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if os.path.isdir(libs_dir := os.path.abspath(os.path.join(os.path.dirname(__file__), os.pardir, 'numpy.libs'))):
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os.add_dll_directory(libs_dir)
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_delvewheel_patch_1_11_0()
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del _delvewheel_patch_1_11_0
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# end delvewheel patch
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import os
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import sys
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import warnings
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# If a version with git hash was stored, use that instead
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from . import version
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from ._expired_attrs_2_0 import __expired_attributes__
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from ._globals import _CopyMode, _NoValue
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from .version import __version__
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# We first need to detect if we're being called as part of the numpy setup
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# procedure itself in a reliable manner.
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try:
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__NUMPY_SETUP__ # noqa: B018
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|
except NameError:
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__NUMPY_SETUP__ = False
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||
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if __NUMPY_SETUP__:
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sys.stderr.write('Running from numpy source directory.\n')
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else:
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# Allow distributors to run custom init code before importing numpy._core
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from . import _distributor_init
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try:
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from numpy.__config__ import show_config
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except ImportError as e:
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msg = """Error importing numpy: you should not try to import numpy from
|
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|
its source directory; please exit the numpy source tree, and relaunch
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|
your python interpreter from there."""
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raise ImportError(msg) from e
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from . import _core
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from ._core import (
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False_,
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ScalarType,
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|
|
True_,
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||
|
|
abs,
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||
|
|
absolute,
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||
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acos,
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acosh,
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add,
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all,
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allclose,
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amax,
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amin,
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any,
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arange,
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arccos,
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arccosh,
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arcsin,
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|
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arcsinh,
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|
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arctan,
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|
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arctan2,
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|
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arctanh,
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|
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argmax,
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|
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argmin,
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argpartition,
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argsort,
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||
|
|
argwhere,
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||
|
|
around,
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||
|
|
array,
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||
|
|
array2string,
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||
|
|
array_equal,
|
||
|
|
array_equiv,
|
||
|
|
array_repr,
|
||
|
|
array_str,
|
||
|
|
asanyarray,
|
||
|
|
asarray,
|
||
|
|
ascontiguousarray,
|
||
|
|
asfortranarray,
|
||
|
|
asin,
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||
|
|
asinh,
|
||
|
|
astype,
|
||
|
|
atan,
|
||
|
|
atan2,
|
||
|
|
atanh,
|
||
|
|
atleast_1d,
|
||
|
|
atleast_2d,
|
||
|
|
atleast_3d,
|
||
|
|
base_repr,
|
||
|
|
binary_repr,
|
||
|
|
bitwise_and,
|
||
|
|
bitwise_count,
|
||
|
|
bitwise_invert,
|
||
|
|
bitwise_left_shift,
|
||
|
|
bitwise_not,
|
||
|
|
bitwise_or,
|
||
|
|
bitwise_right_shift,
|
||
|
|
bitwise_xor,
|
||
|
|
block,
|
||
|
|
bool,
|
||
|
|
bool_,
|
||
|
|
broadcast,
|
||
|
|
busday_count,
|
||
|
|
busday_offset,
|
||
|
|
busdaycalendar,
|
||
|
|
byte,
|
||
|
|
bytes_,
|
||
|
|
can_cast,
|
||
|
|
cbrt,
|
||
|
|
cdouble,
|
||
|
|
ceil,
|
||
|
|
character,
|
||
|
|
choose,
|
||
|
|
clip,
|
||
|
|
clongdouble,
|
||
|
|
complex64,
|
||
|
|
complex128,
|
||
|
|
complexfloating,
|
||
|
|
compress,
|
||
|
|
concat,
|
||
|
|
concatenate,
|
||
|
|
conj,
|
||
|
|
conjugate,
|
||
|
|
convolve,
|
||
|
|
copysign,
|
||
|
|
copyto,
|
||
|
|
correlate,
|
||
|
|
cos,
|
||
|
|
cosh,
|
||
|
|
count_nonzero,
|
||
|
|
cross,
|
||
|
|
csingle,
|
||
|
|
cumprod,
|
||
|
|
cumsum,
|
||
|
|
cumulative_prod,
|
||
|
|
cumulative_sum,
|
||
|
|
datetime64,
|
||
|
|
datetime_as_string,
|
||
|
|
datetime_data,
|
||
|
|
deg2rad,
|
||
|
|
degrees,
|
||
|
|
diagonal,
|
||
|
|
divide,
|
||
|
|
divmod,
|
||
|
|
dot,
|
||
|
|
double,
|
||
|
|
dtype,
|
||
|
|
e,
|
||
|
|
einsum,
|
||
|
|
einsum_path,
|
||
|
|
empty,
|
||
|
|
empty_like,
|
||
|
|
equal,
|
||
|
|
errstate,
|
||
|
|
euler_gamma,
|
||
|
|
exp,
|
||
|
|
exp2,
|
||
|
|
expm1,
|
||
|
|
fabs,
|
||
|
|
finfo,
|
||
|
|
flatiter,
|
||
|
|
flatnonzero,
|
||
|
|
flexible,
|
||
|
|
float16,
|
||
|
|
float32,
|
||
|
|
float64,
|
||
|
|
float_power,
|
||
|
|
floating,
|
||
|
|
floor,
|
||
|
|
floor_divide,
|
||
|
|
fmax,
|
||
|
|
fmin,
|
||
|
|
fmod,
|
||
|
|
format_float_positional,
|
||
|
|
format_float_scientific,
|
||
|
|
frexp,
|
||
|
|
from_dlpack,
|
||
|
|
frombuffer,
|
||
|
|
fromfile,
|
||
|
|
fromfunction,
|
||
|
|
fromiter,
|
||
|
|
frompyfunc,
|
||
|
|
fromstring,
|
||
|
|
full,
|
||
|
|
full_like,
|
||
|
|
gcd,
|
||
|
|
generic,
|
||
|
|
geomspace,
|
||
|
|
get_printoptions,
|
||
|
|
getbufsize,
|
||
|
|
geterr,
|
||
|
|
geterrcall,
|
||
|
|
greater,
|
||
|
|
greater_equal,
|
||
|
|
half,
|
||
|
|
heaviside,
|
||
|
|
hstack,
|
||
|
|
hypot,
|
||
|
|
identity,
|
||
|
|
iinfo,
|
||
|
|
indices,
|
||
|
|
inexact,
|
||
|
|
inf,
|
||
|
|
inner,
|
||
|
|
int8,
|
||
|
|
int16,
|
||
|
|
int32,
|
||
|
|
int64,
|
||
|
|
int_,
|
||
|
|
intc,
|
||
|
|
integer,
|
||
|
|
intp,
|
||
|
|
invert,
|
||
|
|
is_busday,
|
||
|
|
isclose,
|
||
|
|
isdtype,
|
||
|
|
isfinite,
|
||
|
|
isfortran,
|
||
|
|
isinf,
|
||
|
|
isnan,
|
||
|
|
isnat,
|
||
|
|
isscalar,
|
||
|
|
issubdtype,
|
||
|
|
lcm,
|
||
|
|
ldexp,
|
||
|
|
left_shift,
|
||
|
|
less,
|
||
|
|
less_equal,
|
||
|
|
lexsort,
|
||
|
|
linspace,
|
||
|
|
little_endian,
|
||
|
|
log,
|
||
|
|
log1p,
|
||
|
|
log2,
|
||
|
|
log10,
|
||
|
|
logaddexp,
|
||
|
|
logaddexp2,
|
||
|
|
logical_and,
|
||
|
|
logical_not,
|
||
|
|
logical_or,
|
||
|
|
logical_xor,
|
||
|
|
logspace,
|
||
|
|
long,
|
||
|
|
longdouble,
|
||
|
|
longlong,
|
||
|
|
matmul,
|
||
|
|
matrix_transpose,
|
||
|
|
matvec,
|
||
|
|
max,
|
||
|
|
maximum,
|
||
|
|
may_share_memory,
|
||
|
|
mean,
|
||
|
|
memmap,
|
||
|
|
min,
|
||
|
|
min_scalar_type,
|
||
|
|
minimum,
|
||
|
|
mod,
|
||
|
|
modf,
|
||
|
|
moveaxis,
|
||
|
|
multiply,
|
||
|
|
nan,
|
||
|
|
ndarray,
|
||
|
|
ndim,
|
||
|
|
nditer,
|
||
|
|
negative,
|
||
|
|
nested_iters,
|
||
|
|
newaxis,
|
||
|
|
nextafter,
|
||
|
|
nonzero,
|
||
|
|
not_equal,
|
||
|
|
number,
|
||
|
|
object_,
|
||
|
|
ones,
|
||
|
|
ones_like,
|
||
|
|
outer,
|
||
|
|
partition,
|
||
|
|
permute_dims,
|
||
|
|
pi,
|
||
|
|
positive,
|
||
|
|
pow,
|
||
|
|
power,
|
||
|
|
printoptions,
|
||
|
|
prod,
|
||
|
|
promote_types,
|
||
|
|
ptp,
|
||
|
|
put,
|
||
|
|
putmask,
|
||
|
|
rad2deg,
|
||
|
|
radians,
|
||
|
|
ravel,
|
||
|
|
recarray,
|
||
|
|
reciprocal,
|
||
|
|
record,
|
||
|
|
remainder,
|
||
|
|
repeat,
|
||
|
|
require,
|
||
|
|
reshape,
|
||
|
|
resize,
|
||
|
|
result_type,
|
||
|
|
right_shift,
|
||
|
|
rint,
|
||
|
|
roll,
|
||
|
|
rollaxis,
|
||
|
|
round,
|
||
|
|
sctypeDict,
|
||
|
|
searchsorted,
|
||
|
|
set_printoptions,
|
||
|
|
setbufsize,
|
||
|
|
seterr,
|
||
|
|
seterrcall,
|
||
|
|
shape,
|
||
|
|
shares_memory,
|
||
|
|
short,
|
||
|
|
sign,
|
||
|
|
signbit,
|
||
|
|
signedinteger,
|
||
|
|
sin,
|
||
|
|
single,
|
||
|
|
sinh,
|
||
|
|
size,
|
||
|
|
sort,
|
||
|
|
spacing,
|
||
|
|
sqrt,
|
||
|
|
square,
|
||
|
|
squeeze,
|
||
|
|
stack,
|
||
|
|
std,
|
||
|
|
str_,
|
||
|
|
subtract,
|
||
|
|
sum,
|
||
|
|
swapaxes,
|
||
|
|
take,
|
||
|
|
tan,
|
||
|
|
tanh,
|
||
|
|
tensordot,
|
||
|
|
timedelta64,
|
||
|
|
trace,
|
||
|
|
transpose,
|
||
|
|
true_divide,
|
||
|
|
trunc,
|
||
|
|
typecodes,
|
||
|
|
ubyte,
|
||
|
|
ufunc,
|
||
|
|
uint,
|
||
|
|
uint8,
|
||
|
|
uint16,
|
||
|
|
uint32,
|
||
|
|
uint64,
|
||
|
|
uintc,
|
||
|
|
uintp,
|
||
|
|
ulong,
|
||
|
|
ulonglong,
|
||
|
|
unsignedinteger,
|
||
|
|
unstack,
|
||
|
|
ushort,
|
||
|
|
var,
|
||
|
|
vdot,
|
||
|
|
vecdot,
|
||
|
|
vecmat,
|
||
|
|
void,
|
||
|
|
vstack,
|
||
|
|
where,
|
||
|
|
zeros,
|
||
|
|
zeros_like,
|
||
|
|
)
|
||
|
|
|
||
|
|
# NOTE: It's still under discussion whether these aliases
|
||
|
|
# should be removed.
|
||
|
|
for ta in ["float96", "float128", "complex192", "complex256"]:
|
||
|
|
try:
|
||
|
|
globals()[ta] = getattr(_core, ta)
|
||
|
|
except AttributeError:
|
||
|
|
pass
|
||
|
|
del ta
|
||
|
|
|
||
|
|
from . import lib
|
||
|
|
from . import matrixlib as _mat
|
||
|
|
from .lib import scimath as emath
|
||
|
|
from .lib._arraypad_impl import pad
|
||
|
|
from .lib._arraysetops_impl import (
|
||
|
|
ediff1d,
|
||
|
|
in1d,
|
||
|
|
intersect1d,
|
||
|
|
isin,
|
||
|
|
setdiff1d,
|
||
|
|
setxor1d,
|
||
|
|
union1d,
|
||
|
|
unique,
|
||
|
|
unique_all,
|
||
|
|
unique_counts,
|
||
|
|
unique_inverse,
|
||
|
|
unique_values,
|
||
|
|
)
|
||
|
|
from .lib._function_base_impl import (
|
||
|
|
angle,
|
||
|
|
append,
|
||
|
|
asarray_chkfinite,
|
||
|
|
average,
|
||
|
|
bartlett,
|
||
|
|
bincount,
|
||
|
|
blackman,
|
||
|
|
copy,
|
||
|
|
corrcoef,
|
||
|
|
cov,
|
||
|
|
delete,
|
||
|
|
diff,
|
||
|
|
digitize,
|
||
|
|
extract,
|
||
|
|
flip,
|
||
|
|
gradient,
|
||
|
|
hamming,
|
||
|
|
hanning,
|
||
|
|
i0,
|
||
|
|
insert,
|
||
|
|
interp,
|
||
|
|
iterable,
|
||
|
|
kaiser,
|
||
|
|
median,
|
||
|
|
meshgrid,
|
||
|
|
percentile,
|
||
|
|
piecewise,
|
||
|
|
place,
|
||
|
|
quantile,
|
||
|
|
rot90,
|
||
|
|
select,
|
||
|
|
sinc,
|
||
|
|
sort_complex,
|
||
|
|
trapezoid,
|
||
|
|
trapz,
|
||
|
|
trim_zeros,
|
||
|
|
unwrap,
|
||
|
|
vectorize,
|
||
|
|
)
|
||
|
|
from .lib._histograms_impl import histogram, histogram_bin_edges, histogramdd
|
||
|
|
from .lib._index_tricks_impl import (
|
||
|
|
c_,
|
||
|
|
diag_indices,
|
||
|
|
diag_indices_from,
|
||
|
|
fill_diagonal,
|
||
|
|
index_exp,
|
||
|
|
ix_,
|
||
|
|
mgrid,
|
||
|
|
ndenumerate,
|
||
|
|
ndindex,
|
||
|
|
ogrid,
|
||
|
|
r_,
|
||
|
|
ravel_multi_index,
|
||
|
|
s_,
|
||
|
|
unravel_index,
|
||
|
|
)
|
||
|
|
from .lib._nanfunctions_impl import (
|
||
|
|
nanargmax,
|
||
|
|
nanargmin,
|
||
|
|
nancumprod,
|
||
|
|
nancumsum,
|
||
|
|
nanmax,
|
||
|
|
nanmean,
|
||
|
|
nanmedian,
|
||
|
|
nanmin,
|
||
|
|
nanpercentile,
|
||
|
|
nanprod,
|
||
|
|
nanquantile,
|
||
|
|
nanstd,
|
||
|
|
nansum,
|
||
|
|
nanvar,
|
||
|
|
)
|
||
|
|
from .lib._npyio_impl import (
|
||
|
|
fromregex,
|
||
|
|
genfromtxt,
|
||
|
|
load,
|
||
|
|
loadtxt,
|
||
|
|
packbits,
|
||
|
|
save,
|
||
|
|
savetxt,
|
||
|
|
savez,
|
||
|
|
savez_compressed,
|
||
|
|
unpackbits,
|
||
|
|
)
|
||
|
|
from .lib._polynomial_impl import (
|
||
|
|
poly,
|
||
|
|
poly1d,
|
||
|
|
polyadd,
|
||
|
|
polyder,
|
||
|
|
polydiv,
|
||
|
|
polyfit,
|
||
|
|
polyint,
|
||
|
|
polymul,
|
||
|
|
polysub,
|
||
|
|
polyval,
|
||
|
|
roots,
|
||
|
|
)
|
||
|
|
from .lib._shape_base_impl import (
|
||
|
|
apply_along_axis,
|
||
|
|
apply_over_axes,
|
||
|
|
array_split,
|
||
|
|
column_stack,
|
||
|
|
dsplit,
|
||
|
|
dstack,
|
||
|
|
expand_dims,
|
||
|
|
hsplit,
|
||
|
|
kron,
|
||
|
|
put_along_axis,
|
||
|
|
row_stack,
|
||
|
|
split,
|
||
|
|
take_along_axis,
|
||
|
|
tile,
|
||
|
|
vsplit,
|
||
|
|
)
|
||
|
|
from .lib._stride_tricks_impl import (
|
||
|
|
broadcast_arrays,
|
||
|
|
broadcast_shapes,
|
||
|
|
broadcast_to,
|
||
|
|
)
|
||
|
|
from .lib._twodim_base_impl import (
|
||
|
|
diag,
|
||
|
|
diagflat,
|
||
|
|
eye,
|
||
|
|
fliplr,
|
||
|
|
flipud,
|
||
|
|
histogram2d,
|
||
|
|
mask_indices,
|
||
|
|
tri,
|
||
|
|
tril,
|
||
|
|
tril_indices,
|
||
|
|
tril_indices_from,
|
||
|
|
triu,
|
||
|
|
triu_indices,
|
||
|
|
triu_indices_from,
|
||
|
|
vander,
|
||
|
|
)
|
||
|
|
from .lib._type_check_impl import (
|
||
|
|
common_type,
|
||
|
|
imag,
|
||
|
|
iscomplex,
|
||
|
|
iscomplexobj,
|
||
|
|
isreal,
|
||
|
|
isrealobj,
|
||
|
|
mintypecode,
|
||
|
|
nan_to_num,
|
||
|
|
real,
|
||
|
|
real_if_close,
|
||
|
|
typename,
|
||
|
|
)
|
||
|
|
from .lib._ufunclike_impl import fix, isneginf, isposinf
|
||
|
|
from .lib._utils_impl import get_include, info, show_runtime
|
||
|
|
from .matrixlib import asmatrix, bmat, matrix
|
||
|
|
|
||
|
|
# public submodules are imported lazily, therefore are accessible from
|
||
|
|
# __getattr__. Note that `distutils` (deprecated) and `array_api`
|
||
|
|
# (experimental label) are not added here, because `from numpy import *`
|
||
|
|
# must not raise any warnings - that's too disruptive.
|
||
|
|
__numpy_submodules__ = {
|
||
|
|
"linalg", "fft", "dtypes", "random", "polynomial", "ma",
|
||
|
|
"exceptions", "lib", "ctypeslib", "testing", "typing",
|
||
|
|
"f2py", "test", "rec", "char", "core", "strings",
|
||
|
|
}
|
||
|
|
|
||
|
|
# We build warning messages for former attributes
|
||
|
|
_msg = (
|
||
|
|
"module 'numpy' has no attribute '{n}'.\n"
|
||
|
|
"`np.{n}` was a deprecated alias for the builtin `{n}`. "
|
||
|
|
"To avoid this error in existing code, use `{n}` by itself. "
|
||
|
|
"Doing this will not modify any behavior and is safe. {extended_msg}\n"
|
||
|
|
"The aliases was originally deprecated in NumPy 1.20; for more "
|
||
|
|
"details and guidance see the original release note at:\n"
|
||
|
|
" https://numpy.org/devdocs/release/1.20.0-notes.html#deprecations")
|
||
|
|
|
||
|
|
_specific_msg = (
|
||
|
|
"If you specifically wanted the numpy scalar type, use `np.{}` here.")
|
||
|
|
|
||
|
|
_int_extended_msg = (
|
||
|
|
"When replacing `np.{}`, you may wish to use e.g. `np.int64` "
|
||
|
|
"or `np.int32` to specify the precision. If you wish to review "
|
||
|
|
"your current use, check the release note link for "
|
||
|
|
"additional information.")
|
||
|
|
|
||
|
|
_type_info = [
|
||
|
|
("object", ""), # The NumPy scalar only exists by name.
|
||
|
|
("float", _specific_msg.format("float64")),
|
||
|
|
("complex", _specific_msg.format("complex128")),
|
||
|
|
("str", _specific_msg.format("str_")),
|
||
|
|
("int", _int_extended_msg.format("int"))]
|
||
|
|
|
||
|
|
__former_attrs__ = {
|
||
|
|
n: _msg.format(n=n, extended_msg=extended_msg)
|
||
|
|
for n, extended_msg in _type_info
|
||
|
|
}
|
||
|
|
|
||
|
|
# Some of these could be defined right away, but most were aliases to
|
||
|
|
# the Python objects and only removed in NumPy 1.24. Defining them should
|
||
|
|
# probably wait for NumPy 1.26 or 2.0.
|
||
|
|
# When defined, these should possibly not be added to `__all__` to avoid
|
||
|
|
# import with `from numpy import *`.
|
||
|
|
__future_scalars__ = {"str", "bytes", "object"}
|
||
|
|
|
||
|
|
__array_api_version__ = "2024.12"
|
||
|
|
|
||
|
|
from ._array_api_info import __array_namespace_info__
|
||
|
|
|
||
|
|
# now that numpy core module is imported, can initialize limits
|
||
|
|
_core.getlimits._register_known_types()
|
||
|
|
|
||
|
|
__all__ = list(
|
||
|
|
__numpy_submodules__ |
|
||
|
|
set(_core.__all__) |
|
||
|
|
set(_mat.__all__) |
|
||
|
|
set(lib._histograms_impl.__all__) |
|
||
|
|
set(lib._nanfunctions_impl.__all__) |
|
||
|
|
set(lib._function_base_impl.__all__) |
|
||
|
|
set(lib._twodim_base_impl.__all__) |
|
||
|
|
set(lib._shape_base_impl.__all__) |
|
||
|
|
set(lib._type_check_impl.__all__) |
|
||
|
|
set(lib._arraysetops_impl.__all__) |
|
||
|
|
set(lib._ufunclike_impl.__all__) |
|
||
|
|
set(lib._arraypad_impl.__all__) |
|
||
|
|
set(lib._utils_impl.__all__) |
|
||
|
|
set(lib._stride_tricks_impl.__all__) |
|
||
|
|
set(lib._polynomial_impl.__all__) |
|
||
|
|
set(lib._npyio_impl.__all__) |
|
||
|
|
set(lib._index_tricks_impl.__all__) |
|
||
|
|
{"emath", "show_config", "__version__", "__array_namespace_info__"}
|
||
|
|
)
|
||
|
|
|
||
|
|
# Filter out Cython harmless warnings
|
||
|
|
warnings.filterwarnings("ignore", message="numpy.dtype size changed")
|
||
|
|
warnings.filterwarnings("ignore", message="numpy.ufunc size changed")
|
||
|
|
warnings.filterwarnings("ignore", message="numpy.ndarray size changed")
|
||
|
|
|
||
|
|
def __getattr__(attr):
|
||
|
|
# Warn for expired attributes
|
||
|
|
import warnings
|
||
|
|
|
||
|
|
if attr == "linalg":
|
||
|
|
import numpy.linalg as linalg
|
||
|
|
return linalg
|
||
|
|
elif attr == "fft":
|
||
|
|
import numpy.fft as fft
|
||
|
|
return fft
|
||
|
|
elif attr == "dtypes":
|
||
|
|
import numpy.dtypes as dtypes
|
||
|
|
return dtypes
|
||
|
|
elif attr == "random":
|
||
|
|
import numpy.random as random
|
||
|
|
return random
|
||
|
|
elif attr == "polynomial":
|
||
|
|
import numpy.polynomial as polynomial
|
||
|
|
return polynomial
|
||
|
|
elif attr == "ma":
|
||
|
|
import numpy.ma as ma
|
||
|
|
return ma
|
||
|
|
elif attr == "ctypeslib":
|
||
|
|
import numpy.ctypeslib as ctypeslib
|
||
|
|
return ctypeslib
|
||
|
|
elif attr == "exceptions":
|
||
|
|
import numpy.exceptions as exceptions
|
||
|
|
return exceptions
|
||
|
|
elif attr == "testing":
|
||
|
|
import numpy.testing as testing
|
||
|
|
return testing
|
||
|
|
elif attr == "matlib":
|
||
|
|
import numpy.matlib as matlib
|
||
|
|
return matlib
|
||
|
|
elif attr == "f2py":
|
||
|
|
import numpy.f2py as f2py
|
||
|
|
return f2py
|
||
|
|
elif attr == "typing":
|
||
|
|
import numpy.typing as typing
|
||
|
|
return typing
|
||
|
|
elif attr == "rec":
|
||
|
|
import numpy.rec as rec
|
||
|
|
return rec
|
||
|
|
elif attr == "char":
|
||
|
|
import numpy.char as char
|
||
|
|
return char
|
||
|
|
elif attr == "array_api":
|
||
|
|
raise AttributeError("`numpy.array_api` is not available from "
|
||
|
|
"numpy 2.0 onwards", name=None)
|
||
|
|
elif attr == "core":
|
||
|
|
import numpy.core as core
|
||
|
|
return core
|
||
|
|
elif attr == "strings":
|
||
|
|
import numpy.strings as strings
|
||
|
|
return strings
|
||
|
|
elif attr == "distutils":
|
||
|
|
if 'distutils' in __numpy_submodules__:
|
||
|
|
import numpy.distutils as distutils
|
||
|
|
return distutils
|
||
|
|
else:
|
||
|
|
raise AttributeError("`numpy.distutils` is not available from "
|
||
|
|
"Python 3.12 onwards", name=None)
|
||
|
|
|
||
|
|
if attr in __future_scalars__:
|
||
|
|
# And future warnings for those that will change, but also give
|
||
|
|
# the AttributeError
|
||
|
|
warnings.warn(
|
||
|
|
f"In the future `np.{attr}` will be defined as the "
|
||
|
|
"corresponding NumPy scalar.", FutureWarning, stacklevel=2)
|
||
|
|
|
||
|
|
if attr in __former_attrs__:
|
||
|
|
raise AttributeError(__former_attrs__[attr], name=None)
|
||
|
|
|
||
|
|
if attr in __expired_attributes__:
|
||
|
|
raise AttributeError(
|
||
|
|
f"`np.{attr}` was removed in the NumPy 2.0 release. "
|
||
|
|
f"{__expired_attributes__[attr]}",
|
||
|
|
name=None
|
||
|
|
)
|
||
|
|
|
||
|
|
if attr == "chararray":
|
||
|
|
warnings.warn(
|
||
|
|
"`np.chararray` is deprecated and will be removed from "
|
||
|
|
"the main namespace in the future. Use an array with a string "
|
||
|
|
"or bytes dtype instead.", DeprecationWarning, stacklevel=2)
|
||
|
|
import numpy.char as char
|
||
|
|
return char.chararray
|
||
|
|
|
||
|
|
raise AttributeError(f"module {__name__!r} has no attribute {attr!r}")
|
||
|
|
|
||
|
|
def __dir__():
|
||
|
|
public_symbols = (
|
||
|
|
globals().keys() | __numpy_submodules__
|
||
|
|
)
|
||
|
|
public_symbols -= {
|
||
|
|
"matrixlib", "matlib", "tests", "conftest", "version",
|
||
|
|
"distutils", "array_api"
|
||
|
|
}
|
||
|
|
return list(public_symbols)
|
||
|
|
|
||
|
|
# Pytest testing
|
||
|
|
from numpy._pytesttester import PytestTester
|
||
|
|
test = PytestTester(__name__)
|
||
|
|
del PytestTester
|
||
|
|
|
||
|
|
def _sanity_check():
|
||
|
|
"""
|
||
|
|
Quick sanity checks for common bugs caused by environment.
|
||
|
|
There are some cases e.g. with wrong BLAS ABI that cause wrong
|
||
|
|
results under specific runtime conditions that are not necessarily
|
||
|
|
achieved during test suite runs, and it is useful to catch those early.
|
||
|
|
|
||
|
|
See https://github.com/numpy/numpy/issues/8577 and other
|
||
|
|
similar bug reports.
|
||
|
|
|
||
|
|
"""
|
||
|
|
try:
|
||
|
|
x = ones(2, dtype=float32)
|
||
|
|
if not abs(x.dot(x) - float32(2.0)) < 1e-5:
|
||
|
|
raise AssertionError
|
||
|
|
except AssertionError:
|
||
|
|
msg = ("The current Numpy installation ({!r}) fails to "
|
||
|
|
"pass simple sanity checks. This can be caused for example "
|
||
|
|
"by incorrect BLAS library being linked in, or by mixing "
|
||
|
|
"package managers (pip, conda, apt, ...). Search closed "
|
||
|
|
"numpy issues for similar problems.")
|
||
|
|
raise RuntimeError(msg.format(__file__)) from None
|
||
|
|
|
||
|
|
_sanity_check()
|
||
|
|
del _sanity_check
|
||
|
|
|
||
|
|
def _mac_os_check():
|
||
|
|
"""
|
||
|
|
Quick Sanity check for Mac OS look for accelerate build bugs.
|
||
|
|
Testing numpy polyfit calls init_dgelsd(LAPACK)
|
||
|
|
"""
|
||
|
|
try:
|
||
|
|
c = array([3., 2., 1.])
|
||
|
|
x = linspace(0, 2, 5)
|
||
|
|
y = polyval(c, x)
|
||
|
|
_ = polyfit(x, y, 2, cov=True)
|
||
|
|
except ValueError:
|
||
|
|
pass
|
||
|
|
|
||
|
|
if sys.platform == "darwin":
|
||
|
|
from . import exceptions
|
||
|
|
with warnings.catch_warnings(record=True) as w:
|
||
|
|
_mac_os_check()
|
||
|
|
# Throw runtime error, if the test failed
|
||
|
|
# Check for warning and report the error_message
|
||
|
|
if len(w) > 0:
|
||
|
|
for _wn in w:
|
||
|
|
if _wn.category is exceptions.RankWarning:
|
||
|
|
# Ignore other warnings, they may not be relevant (see gh-25433)
|
||
|
|
error_message = (
|
||
|
|
f"{_wn.category.__name__}: {_wn.message}"
|
||
|
|
)
|
||
|
|
msg = (
|
||
|
|
"Polyfit sanity test emitted a warning, most likely due "
|
||
|
|
"to using a buggy Accelerate backend."
|
||
|
|
"\nIf you compiled yourself, more information is available at:" # noqa: E501
|
||
|
|
"\nhttps://numpy.org/devdocs/building/index.html"
|
||
|
|
"\nOtherwise report this to the vendor "
|
||
|
|
f"that provided NumPy.\n\n{error_message}\n")
|
||
|
|
raise RuntimeError(msg)
|
||
|
|
del _wn
|
||
|
|
del w
|
||
|
|
del _mac_os_check
|
||
|
|
|
||
|
|
def hugepage_setup():
|
||
|
|
"""
|
||
|
|
We usually use madvise hugepages support, but on some old kernels it
|
||
|
|
is slow and thus better avoided. Specifically kernel version 4.6
|
||
|
|
had a bug fix which probably fixed this:
|
||
|
|
https://github.com/torvalds/linux/commit/7cf91a98e607c2f935dbcc177d70011e95b8faff
|
||
|
|
"""
|
||
|
|
use_hugepage = os.environ.get("NUMPY_MADVISE_HUGEPAGE", None)
|
||
|
|
if sys.platform == "linux" and use_hugepage is None:
|
||
|
|
# If there is an issue with parsing the kernel version,
|
||
|
|
# set use_hugepage to 0. Usage of LooseVersion will handle
|
||
|
|
# the kernel version parsing better, but avoided since it
|
||
|
|
# will increase the import time.
|
||
|
|
# See: #16679 for related discussion.
|
||
|
|
try:
|
||
|
|
use_hugepage = 1
|
||
|
|
kernel_version = os.uname().release.split(".")[:2]
|
||
|
|
kernel_version = tuple(int(v) for v in kernel_version)
|
||
|
|
if kernel_version < (4, 6):
|
||
|
|
use_hugepage = 0
|
||
|
|
except ValueError:
|
||
|
|
use_hugepage = 0
|
||
|
|
elif use_hugepage is None:
|
||
|
|
# This is not Linux, so it should not matter, just enable anyway
|
||
|
|
use_hugepage = 1
|
||
|
|
else:
|
||
|
|
use_hugepage = int(use_hugepage)
|
||
|
|
return use_hugepage
|
||
|
|
|
||
|
|
# Note that this will currently only make a difference on Linux
|
||
|
|
_core.multiarray._set_madvise_hugepage(hugepage_setup())
|
||
|
|
del hugepage_setup
|
||
|
|
|
||
|
|
# Give a warning if NumPy is reloaded or imported on a sub-interpreter
|
||
|
|
# We do this from python, since the C-module may not be reloaded and
|
||
|
|
# it is tidier organized.
|
||
|
|
_core.multiarray._multiarray_umath._reload_guard()
|
||
|
|
|
||
|
|
# TODO: Remove the environment variable entirely now that it is "weak"
|
||
|
|
if (os.environ.get("NPY_PROMOTION_STATE", "weak") != "weak"):
|
||
|
|
warnings.warn(
|
||
|
|
"NPY_PROMOTION_STATE was a temporary feature for NumPy 2.0 "
|
||
|
|
"transition and is ignored after NumPy 2.2.",
|
||
|
|
UserWarning, stacklevel=2)
|
||
|
|
|
||
|
|
# Tell PyInstaller where to find hook-numpy.py
|
||
|
|
def _pyinstaller_hooks_dir():
|
||
|
|
from pathlib import Path
|
||
|
|
return [str(Path(__file__).with_name("_pyinstaller").resolve())]
|
||
|
|
|
||
|
|
|
||
|
|
# Remove symbols imported for internal use
|
||
|
|
del os, sys, warnings
|