done
This commit is contained in:
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lib/python3.11/site-packages/numpy/__init__.py
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|
||||
"""
|
||||
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 <https://numpy.org>`_.
|
||||
|
||||
We recommend exploring the docstrings using
|
||||
`IPython <https://ipython.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 = 42
|
||||
>>> x = x + 1
|
||||
|
||||
Use the built-in ``help`` function to view a function's docstring::
|
||||
|
||||
>>> help(np.sort)
|
||||
... # doctest: +SKIP
|
||||
|
||||
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.
|
||||
|
||||
Available subpackages
|
||||
---------------------
|
||||
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
|
||||
distutils
|
||||
Enhancements to distutils with support for
|
||||
Fortran compilers support and more (for Python <= 3.11)
|
||||
|
||||
Utilities
|
||||
---------
|
||||
test
|
||||
Run numpy unittests
|
||||
show_config
|
||||
Show numpy build configuration
|
||||
__version__
|
||||
NumPy version string
|
||||
|
||||
Viewing documentation using IPython
|
||||
-----------------------------------
|
||||
|
||||
Start IPython and import `numpy` usually under the alias ``np``: `import
|
||||
numpy as np`. Then, directly past or use the ``%cpaste`` magic 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.
|
||||
|
||||
"""
|
||||
import os
|
||||
import sys
|
||||
import warnings
|
||||
|
||||
# If a version with git hash was stored, use that instead
|
||||
from . import version
|
||||
from ._expired_attrs_2_0 import __expired_attributes__
|
||||
from ._globals import _CopyMode, _NoValue
|
||||
from .version import __version__
|
||||
|
||||
# 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__ # noqa: B018
|
||||
except NameError:
|
||||
__NUMPY_SETUP__ = False
|
||||
|
||||
if __NUMPY_SETUP__:
|
||||
sys.stderr.write('Running from numpy source directory.\n')
|
||||
else:
|
||||
# Allow distributors to run custom init code before importing numpy._core
|
||||
from . import _distributor_init
|
||||
|
||||
try:
|
||||
from numpy.__config__ import show_config
|
||||
except ImportError as 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 interpreter from there."""
|
||||
raise ImportError(msg) from e
|
||||
|
||||
from . import _core
|
||||
from ._core import (
|
||||
False_,
|
||||
ScalarType,
|
||||
True_,
|
||||
abs,
|
||||
absolute,
|
||||
acos,
|
||||
acosh,
|
||||
add,
|
||||
all,
|
||||
allclose,
|
||||
amax,
|
||||
amin,
|
||||
any,
|
||||
arange,
|
||||
arccos,
|
||||
arccosh,
|
||||
arcsin,
|
||||
arcsinh,
|
||||
arctan,
|
||||
arctan2,
|
||||
arctanh,
|
||||
argmax,
|
||||
argmin,
|
||||
argpartition,
|
||||
argsort,
|
||||
argwhere,
|
||||
around,
|
||||
array,
|
||||
array2string,
|
||||
array_equal,
|
||||
array_equiv,
|
||||
array_repr,
|
||||
array_str,
|
||||
asanyarray,
|
||||
asarray,
|
||||
ascontiguousarray,
|
||||
asfortranarray,
|
||||
asin,
|
||||
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
|
||||
Reference in New Issue
Block a user