id int64 0 190k | prompt stringlengths 21 13.4M | docstring stringlengths 1 12k ⌀ |
|---|---|---|
170,115 | import builtins
import inspect
import operator
import warnings
import textwrap
import re
from functools import reduce
import numpy as np
import numpy.core.umath as umath
import numpy.core.numerictypes as ntypes
from numpy.core import multiarray as mu
from numpy import ndarray, amax, amin, iscomplexobj, bool_, _NoValue
... | Shift the bits of an integer to the right. This is the masked array version of `numpy.right_shift`, for details see that function. See Also -------- numpy.right_shift |
170,116 | import builtins
import inspect
import operator
import warnings
import textwrap
import re
from functools import reduce
import numpy as np
import numpy.core.umath as umath
import numpy.core.numerictypes as ntypes
from numpy.core import multiarray as mu
from numpy import ndarray, amax, amin, iscomplexobj, bool_, _NoValue
... | Changes elements of an array based on conditional and input values. This is the masked array version of `numpy.putmask`, for details see `numpy.putmask`. See Also -------- numpy.putmask Notes ----- Using a masked array as `values` will **not** transform a `ndarray` into a `MaskedArray`. |
170,117 | import builtins
import inspect
import operator
import warnings
import textwrap
import re
from functools import reduce
import numpy as np
import numpy.core.umath as umath
import numpy.core.numerictypes as ntypes
from numpy.core import multiarray as mu
from numpy import ndarray, amax, amin, iscomplexobj, bool_, _NoValue
... | Permute the dimensions of an array. This function is exactly equivalent to `numpy.transpose`. See Also -------- numpy.transpose : Equivalent function in top-level NumPy module. Examples -------- >>> import numpy.ma as ma >>> x = ma.arange(4).reshape((2,2)) >>> x[1, 1] = ma.masked >>> x masked_array( data=[[0, 1], [2, -... |
170,118 | import builtins
import inspect
import operator
import warnings
import textwrap
import re
from functools import reduce
import numpy as np
import numpy.core.umath as umath
import numpy.core.numerictypes as ntypes
from numpy.core import multiarray as mu
from numpy import ndarray, amax, amin, iscomplexobj, bool_, _NoValue
... | Use an index array to construct a new array from a list of choices. Given an array of integers and a list of n choice arrays, this method will create a new array that merges each of the choice arrays. Where a value in `index` is i, the new array will have the value that choices[i] contains in the same place. Parameters... |
170,119 | import builtins
import inspect
import operator
import warnings
import textwrap
import re
from functools import reduce
import numpy as np
import numpy.core.umath as umath
import numpy.core.numerictypes as ntypes
from numpy.core import multiarray as mu
from numpy import ndarray, amax, amin, iscomplexobj, bool_, _NoValue
... | Return a copy of a, rounded to 'decimals' places. When 'decimals' is negative, it specifies the number of positions to the left of the decimal point. The real and imaginary parts of complex numbers are rounded separately. Nothing is done if the array is not of float type and 'decimals' is greater than or equal to 0. Pa... |
170,120 | import builtins
import inspect
import operator
import warnings
import textwrap
import re
from functools import reduce
import numpy as np
import numpy.core.umath as umath
import numpy.core.numerictypes as ntypes
from numpy.core import multiarray as mu
from numpy import ndarray, amax, amin, iscomplexobj, bool_, _NoValue
... | Returns the inner product of a and b for arrays of floating point types. Like the generic NumPy equivalent the product sum is over the last dimension of a and b. The first argument is not conjugated. |
170,121 | import builtins
import inspect
import operator
import warnings
import textwrap
import re
from functools import reduce
import numpy as np
import numpy.core.umath as umath
import numpy.core.numerictypes as ntypes
from numpy.core import multiarray as mu
from numpy import ndarray, amax, amin, iscomplexobj, bool_, _NoValue
... | Cross-correlation of two 1-dimensional sequences. Parameters ---------- a, v : array_like Input sequences. mode : {'valid', 'same', 'full'}, optional Refer to the `np.convolve` docstring. Note that the default is 'valid', unlike `convolve`, which uses 'full'. propagate_mask : bool If True, then a result element is mask... |
170,122 | import builtins
import inspect
import operator
import warnings
import textwrap
import re
from functools import reduce
import numpy as np
import numpy.core.umath as umath
import numpy.core.numerictypes as ntypes
from numpy.core import multiarray as mu
from numpy import ndarray, amax, amin, iscomplexobj, bool_, _NoValue
... | Returns the discrete, linear convolution of two one-dimensional sequences. Parameters ---------- a, v : array_like Input sequences. mode : {'valid', 'same', 'full'}, optional Refer to the `np.convolve` docstring. propagate_mask : bool If True, then if any masked element is included in the sum for a result element, then... |
170,123 | import builtins
import inspect
import operator
import warnings
import textwrap
import re
from functools import reduce
import numpy as np
import numpy.core.umath as umath
import numpy.core.numerictypes as ntypes
from numpy.core import multiarray as mu
from numpy import ndarray, amax, amin, iscomplexobj, bool_, _NoValue
... | Return True if all entries of a and b are equal, using fill_value as a truth value where either or both are masked. Parameters ---------- a, b : array_like Input arrays to compare. fill_value : bool, optional Whether masked values in a or b are considered equal (True) or not (False). Returns ------- y : bool Returns Tr... |
170,124 | import builtins
import inspect
import operator
import warnings
import textwrap
import re
from functools import reduce
import numpy as np
import numpy.core.umath as umath
import numpy.core.numerictypes as ntypes
from numpy.core import multiarray as mu
from numpy import ndarray, amax, amin, iscomplexobj, bool_, _NoValue
... | Returns True if two arrays are element-wise equal within a tolerance. This function is equivalent to `allclose` except that masked values are treated as equal (default) or unequal, depending on the `masked_equal` argument. Parameters ---------- a, b : array_like Input arrays to compare. masked_equal : bool, optional Wh... |
170,125 | import builtins
import inspect
import operator
import warnings
import textwrap
import re
from functools import reduce
import numpy as np
import numpy.core.umath as umath
import numpy.core.numerictypes as ntypes
from numpy.core import multiarray as mu
from numpy import ndarray, amax, amin, iscomplexobj, bool_, _NoValue
... | null |
170,126 | import builtins
import inspect
import operator
import warnings
import textwrap
import re
from functools import reduce
import numpy as np
import numpy.core.umath as umath
import numpy.core.numerictypes as ntypes
from numpy.core import multiarray as mu
from numpy import ndarray, amax, amin, iscomplexobj, bool_, _NoValue
... | Build a masked array from a suitable flexible-type array. The input array has to have a data-type with ``_data`` and ``_mask`` fields. This type of array is output by `MaskedArray.toflex`. Parameters ---------- fxarray : ndarray The structured input array, containing ``_data`` and ``_mask`` fields. If present, other fi... |
170,127 | import timeit
import numpy
def timer(s, v='', nloop=500, nrep=3):
if __name__ == '__main__':
compare_functions_1v(numpy.sin)
compare_functions_1v(numpy.log)
compare_functions_1v(numpy.sqrt)
compare_functions_2v(numpy.multiply)
compare_functions_2v(numpy.divide)
compare_functions_2v(numpy.power)
... | null |
170,128 | import timeit
import numpy
def timer(s, v='', nloop=500, nrep=3):
units = ["s", "ms", "µs", "ns"]
scaling = [1, 1e3, 1e6, 1e9]
print("%s : %-50s : " % (v, s), end=' ')
varnames = ["%ss,nm%ss,%sl,nm%sl" % tuple(x*4) for x in 'xyz']
setup = 'from __main__ import numpy, ma, %s' % ','.join(varnames)
... | null |
170,129 | import timeit
import numpy
def timer(s, v='', nloop=500, nrep=3):
units = ["s", "ms", "µs", "ns"]
scaling = [1, 1e3, 1e6, 1e9]
print("%s : %-50s : " % (v, s), end=' ')
varnames = ["%ss,nm%ss,%sl,nm%sl" % tuple(x*4) for x in 'xyz']
setup = 'from __main__ import numpy, ma, %s' % ','.join(varnames)
... | null |
170,130 | from numpy.ma import (
MAError, MaskedArray, masked, nomask, masked_array, getdata,
getmaskarray, filled
)
import numpy.ma as ma
import warnings
import numpy as np
from numpy import (
bool_, dtype, ndarray, recarray, array as narray
)
from numpy.core.records import (
fromarrays as recfromarrays, fromrec... | Checks that field names ``descr`` are not reserved keywords. If this is the case, a default 'f%i' is substituted. If the argument `names` is not None, updates the field names to valid names. |
170,131 | from numpy.ma import (
MAError, MaskedArray, masked, nomask, masked_array, getdata,
getmaskarray, filled
)
import numpy.ma as ma
import warnings
import numpy as np
from numpy import (
bool_, dtype, ndarray, recarray, array as narray
)
from numpy.core.records import (
fromarrays as recfromarrays, fromrec... | null |
170,132 | from numpy.ma import (
MAError, MaskedArray, masked, nomask, masked_array, getdata,
getmaskarray, filled
)
import numpy.ma as ma
import warnings
import numpy as np
from numpy import (
bool_, dtype, ndarray, recarray, array as narray
)
from numpy.core.records import (
fromarrays as recfromarrays, fromrec... | Build a new MaskedArray from the information stored in a pickle. |
170,133 | from numpy.ma import (
MAError, MaskedArray, masked, nomask, masked_array, getdata,
getmaskarray, filled
)
import numpy.ma as ma
import warnings
import numpy as np
from numpy import (
bool_, dtype, ndarray, recarray, array as narray
)
from numpy.core.records import (
fromarrays as recfromarrays, fromrec... | Creates a MaskedRecords from a list of records. Parameters ---------- reclist : sequence A list of records. Each element of the sequence is first converted to a masked array if needed. If a 2D array is passed as argument, it is processed line by line dtype : {None, dtype}, optional Data type descriptor. shape : {None,i... |
170,134 | from numpy.ma import (
MAError, MaskedArray, masked, nomask, masked_array, getdata,
getmaskarray, filled
)
import numpy.ma as ma
import warnings
import numpy as np
from numpy import (
bool_, dtype, ndarray, recarray, array as narray
)
from numpy.core.records import (
fromarrays as recfromarrays, fromrec... | Creates a mrecarray from data stored in the file `filename`. Parameters ---------- fname : {file name/handle} Handle of an opened file. delimiter : {None, string}, optional Alphanumeric character used to separate columns in the file. If None, any (group of) white spacestring(s) will be used. commentchar : {'#', string}... |
170,135 | from numpy.ma import (
MAError, MaskedArray, masked, nomask, masked_array, getdata,
getmaskarray, filled
)
import numpy.ma as ma
import warnings
import numpy as np
from numpy import (
bool_, dtype, ndarray, recarray, array as narray
)
from numpy.core.records import (
fromarrays as recfromarrays, fromrec... | Adds a new field to the masked record array Uses `newfield` as data and `newfieldname` as name. If `newfieldname` is None, the new field name is set to 'fi', where `i` is the number of existing fields. |
170,136 |
class Configuration:
_list_keys = ['packages', 'ext_modules', 'data_files', 'include_dirs',
'libraries', 'headers', 'scripts', 'py_modules',
'installed_libraries', 'define_macros']
_dict_keys = ['package_dir', 'installed_pkg_config']
_extra_keys = ['name', 'version']
... | null |
170,184 | import itertools
import warnings
from . import core as ma
from .core import (
MaskedArray, MAError, add, array, asarray, concatenate, filled, count,
getmask, getmaskarray, make_mask_descr, masked, masked_array, mask_or,
nomask, ones, sort, zeros, getdata, get_masked_subclass, dot,
mask_rowcols
)
imp... | Is seq a sequence (ndarray, list or tuple)? |
170,185 | import itertools
import warnings
from . import core as ma
from .core import (
MaskedArray, MAError, add, array, asarray, concatenate, filled, count,
getmask, getmaskarray, make_mask_descr, masked, masked_array, mask_or,
nomask, ones, sort, zeros, getdata, get_masked_subclass, dot,
mask_rowcols
)
imp... | Count the number of masked elements along the given axis. Parameters ---------- arr : array_like An array with (possibly) masked elements. axis : int, optional Axis along which to count. If None (default), a flattened version of the array is used. Returns ------- count : int, ndarray The total number of masked elements... |
170,186 | import itertools
import warnings
from . import core as ma
from .core import (
MaskedArray, MAError, add, array, asarray, concatenate, filled, count,
getmask, getmaskarray, make_mask_descr, masked, masked_array, mask_or,
nomask, ones, sort, zeros, getdata, get_masked_subclass, dot,
mask_rowcols
)
imp... | Empty masked array with all elements masked. Return an empty masked array of the given shape and dtype, where all the data are masked. Parameters ---------- shape : int or tuple of ints Shape of the required MaskedArray, e.g., ``(2, 3)`` or ``2``. dtype : dtype, optional Data type of the output. Returns ------- a : Mas... |
170,187 | import itertools
import warnings
from . import core as ma
from .core import (
MaskedArray, MAError, add, array, asarray, concatenate, filled, count,
getmask, getmaskarray, make_mask_descr, masked, masked_array, mask_or,
nomask, ones, sort, zeros, getdata, get_masked_subclass, dot,
mask_rowcols
)
imp... | Empty masked array with the properties of an existing array. Return an empty masked array of the same shape and dtype as the array `arr`, where all the data are masked. Parameters ---------- arr : ndarray An array describing the shape and dtype of the required MaskedArray. Returns ------- a : MaskedArray A masked array... |
170,188 | import itertools
import warnings
from . import core as ma
from .core import (
MaskedArray, MAError, add, array, asarray, concatenate, filled, count,
getmask, getmaskarray, make_mask_descr, masked, masked_array, mask_or,
nomask, ones, sort, zeros, getdata, get_masked_subclass, dot,
mask_rowcols
)
imp... | (This docstring should be overwritten) |
170,189 | import itertools
import warnings
from . import core as ma
from .core import (
MaskedArray, MAError, add, array, asarray, concatenate, filled, count,
getmask, getmaskarray, make_mask_descr, masked, masked_array, mask_or,
nomask, ones, sort, zeros, getdata, get_masked_subclass, dot,
mask_rowcols
)
imp... | (This docstring will be overwritten) |
170,190 | import itertools
import warnings
from . import core as ma
from .core import (
MaskedArray, MAError, add, array, asarray, concatenate, filled, count,
getmask, getmaskarray, make_mask_descr, masked, masked_array, mask_or,
nomask, ones, sort, zeros, getdata, get_masked_subclass, dot,
mask_rowcols
)
imp... | Return the weighted average of array over the given axis. Parameters ---------- a : array_like Data to be averaged. Masked entries are not taken into account in the computation. axis : int, optional Axis along which to average `a`. If None, averaging is done over the flattened array. weights : array_like, optional The ... |
170,191 | import itertools
import warnings
from . import core as ma
from .core import (
MaskedArray, MAError, add, array, asarray, concatenate, filled, count,
getmask, getmaskarray, make_mask_descr, masked, masked_array, mask_or,
nomask, ones, sort, zeros, getdata, get_masked_subclass, dot,
mask_rowcols
)
imp... | Compute the median along the specified axis. Returns the median of the array elements. Parameters ---------- a : array_like Input array or object that can be converted to an array. axis : int, optional Axis along which the medians are computed. The default (None) is to compute the median along a flattened version of th... |
170,192 | import itertools
import warnings
from . import core as ma
from .core import (
MaskedArray, MAError, add, array, asarray, concatenate, filled, count,
getmask, getmaskarray, make_mask_descr, masked, masked_array, mask_or,
nomask, ones, sort, zeros, getdata, get_masked_subclass, dot,
mask_rowcols
)
imp... | Suppress whole rows of a 2-D array that contain masked values. This is equivalent to ``np.ma.compress_rowcols(a, 0)``, see `compress_rowcols` for details. See Also -------- compress_rowcols |
170,193 | import itertools
import warnings
from . import core as ma
from .core import (
MaskedArray, MAError, add, array, asarray, concatenate, filled, count,
getmask, getmaskarray, make_mask_descr, masked, masked_array, mask_or,
nomask, ones, sort, zeros, getdata, get_masked_subclass, dot,
mask_rowcols
)
imp... | Suppress whole columns of a 2-D array that contain masked values. This is equivalent to ``np.ma.compress_rowcols(a, 1)``, see `compress_rowcols` for details. See Also -------- compress_rowcols |
170,194 | import itertools
import warnings
from . import core as ma
from .core import (
MaskedArray, MAError, add, array, asarray, concatenate, filled, count,
getmask, getmaskarray, make_mask_descr, masked, masked_array, mask_or,
nomask, ones, sort, zeros, getdata, get_masked_subclass, dot,
mask_rowcols
)
imp... | Compute the differences between consecutive elements of an array. This function is the equivalent of `numpy.ediff1d` that takes masked values into account, see `numpy.ediff1d` for details. See Also -------- numpy.ediff1d : Equivalent function for ndarrays. |
170,195 | import itertools
import warnings
from . import core as ma
from .core import (
MaskedArray, MAError, add, array, asarray, concatenate, filled, count,
getmask, getmaskarray, make_mask_descr, masked, masked_array, mask_or,
nomask, ones, sort, zeros, getdata, get_masked_subclass, dot,
mask_rowcols
)
imp... | Returns the unique elements common to both arrays. Masked values are considered equal one to the other. The output is always a masked array. See `numpy.intersect1d` for more details. See Also -------- numpy.intersect1d : Equivalent function for ndarrays. Examples -------- >>> x = np.ma.array([1, 3, 3, 3], mask=[0, 0, 0... |
170,196 | import itertools
import warnings
from . import core as ma
from .core import (
MaskedArray, MAError, add, array, asarray, concatenate, filled, count,
getmask, getmaskarray, make_mask_descr, masked, masked_array, mask_or,
nomask, ones, sort, zeros, getdata, get_masked_subclass, dot,
mask_rowcols
)
imp... | Set exclusive-or of 1-D arrays with unique elements. The output is always a masked array. See `numpy.setxor1d` for more details. See Also -------- numpy.setxor1d : Equivalent function for ndarrays. |
170,197 | import itertools
import warnings
from . import core as ma
from .core import (
MaskedArray, MAError, add, array, asarray, concatenate, filled, count,
getmask, getmaskarray, make_mask_descr, masked, masked_array, mask_or,
nomask, ones, sort, zeros, getdata, get_masked_subclass, dot,
mask_rowcols
)
imp... | Calculates `element in test_elements`, broadcasting over `element` only. The output is always a masked array of the same shape as `element`. See `numpy.isin` for more details. See Also -------- in1d : Flattened version of this function. numpy.isin : Equivalent function for ndarrays. Notes ----- .. versionadded:: 1.13.0 |
170,198 | import itertools
import warnings
from . import core as ma
from .core import (
MaskedArray, MAError, add, array, asarray, concatenate, filled, count,
getmask, getmaskarray, make_mask_descr, masked, masked_array, mask_or,
nomask, ones, sort, zeros, getdata, get_masked_subclass, dot,
mask_rowcols
)
imp... | Union of two arrays. The output is always a masked array. See `numpy.union1d` for more details. See Also -------- numpy.union1d : Equivalent function for ndarrays. |
170,199 | import itertools
import warnings
from . import core as ma
from .core import (
MaskedArray, MAError, add, array, asarray, concatenate, filled, count,
getmask, getmaskarray, make_mask_descr, masked, masked_array, mask_or,
nomask, ones, sort, zeros, getdata, get_masked_subclass, dot,
mask_rowcols
)
imp... | Set difference of 1D arrays with unique elements. The output is always a masked array. See `numpy.setdiff1d` for more details. See Also -------- numpy.setdiff1d : Equivalent function for ndarrays. Examples -------- >>> x = np.ma.array([1, 2, 3, 4], mask=[0, 1, 0, 1]) >>> np.ma.setdiff1d(x, [1, 2]) masked_array(data=[3,... |
170,200 | import itertools
import warnings
from . import core as ma
from .core import (
MaskedArray, MAError, add, array, asarray, concatenate, filled, count,
getmask, getmaskarray, make_mask_descr, masked, masked_array, mask_or,
nomask, ones, sort, zeros, getdata, get_masked_subclass, dot,
mask_rowcols
)
imp... | Estimate the covariance matrix. Except for the handling of missing data this function does the same as `numpy.cov`. For more details and examples, see `numpy.cov`. By default, masked values are recognized as such. If `x` and `y` have the same shape, a common mask is allocated: if ``x[i,j]`` is masked, then ``y[i,j]`` w... |
170,201 | import itertools
import warnings
from . import core as ma
from .core import (
MaskedArray, MAError, add, array, asarray, concatenate, filled, count,
getmask, getmaskarray, make_mask_descr, masked, masked_array, mask_or,
nomask, ones, sort, zeros, getdata, get_masked_subclass, dot,
mask_rowcols
)
imp... | Return Pearson product-moment correlation coefficients. Except for the handling of missing data this function does the same as `numpy.corrcoef`. For more details and examples, see `numpy.corrcoef`. Parameters ---------- x : array_like A 1-D or 2-D array containing multiple variables and observations. Each row of `x` re... |
170,202 | import itertools
import warnings
from . import core as ma
from .core import (
MaskedArray, MAError, add, array, asarray, concatenate, filled, count,
getmask, getmaskarray, make_mask_descr, masked, masked_array, mask_or,
nomask, ones, sort, zeros, getdata, get_masked_subclass, dot,
mask_rowcols
)
imp... | Multidimensional index iterator. Return an iterator yielding pairs of array coordinates and values, skipping elements that are masked. With `compressed=False`, `ma.masked` is yielded as the value of masked elements. This behavior differs from that of `numpy.ndenumerate`, which yields the value of the underlying data ar... |
170,203 | import itertools
import warnings
from . import core as ma
from .core import (
MaskedArray, MAError, add, array, asarray, concatenate, filled, count,
getmask, getmaskarray, make_mask_descr, masked, masked_array, mask_or,
nomask, ones, sort, zeros, getdata, get_masked_subclass, dot,
mask_rowcols
)
imp... | Find the indices of the first and last unmasked values along an axis. If all values are masked, return None. Otherwise, return a list of two tuples, corresponding to the indices of the first and last unmasked values respectively. Parameters ---------- a : array_like The input array. axis : int, optional Axis along whic... |
170,204 | import itertools
import warnings
from . import core as ma
from .core import (
MaskedArray, MAError, add, array, asarray, concatenate, filled, count,
getmask, getmaskarray, make_mask_descr, masked, masked_array, mask_or,
nomask, ones, sort, zeros, getdata, get_masked_subclass, dot,
mask_rowcols
)
imp... | Find contiguous unmasked data in a masked array along the given axis. Parameters ---------- a : array_like The input array. axis : int, optional Axis along which to perform the operation. If None (default), applies to a flattened version of the array, and this is the same as `flatnotmasked_contiguous`. Returns ------- ... |
170,205 | import itertools
import warnings
from . import core as ma
from .core import (
MaskedArray, MAError, add, array, asarray, concatenate, filled, count,
getmask, getmaskarray, make_mask_descr, masked, masked_array, mask_or,
nomask, ones, sort, zeros, getdata, get_masked_subclass, dot,
mask_rowcols
)
imp... | Return list of slices corresponding to the unmasked clumps of a 1-D array. (A "clump" is defined as a contiguous region of the array). Parameters ---------- a : ndarray A one-dimensional masked array. Returns ------- slices : list of slice The list of slices, one for each continuous region of unmasked elements in `a`. ... |
170,206 | import itertools
import warnings
from . import core as ma
from .core import (
MaskedArray, MAError, add, array, asarray, concatenate, filled, count,
getmask, getmaskarray, make_mask_descr, masked, masked_array, mask_or,
nomask, ones, sort, zeros, getdata, get_masked_subclass, dot,
mask_rowcols
)
imp... | Returns a list of slices corresponding to the masked clumps of a 1-D array. (A "clump" is defined as a contiguous region of the array). Parameters ---------- a : ndarray A one-dimensional masked array. Returns ------- slices : list of slice The list of slices, one for each continuous region of masked elements in `a`. N... |
170,207 | import itertools
import warnings
from . import core as ma
from .core import (
MaskedArray, MAError, add, array, asarray, concatenate, filled, count,
getmask, getmaskarray, make_mask_descr, masked, masked_array, mask_or,
nomask, ones, sort, zeros, getdata, get_masked_subclass, dot,
mask_rowcols
)
imp... | Masked values in the input array result in rows of zeros. |
170,208 | import itertools
import warnings
from . import core as ma
from .core import (
MaskedArray, MAError, add, array, asarray, concatenate, filled, count,
getmask, getmaskarray, make_mask_descr, masked, masked_array, mask_or,
nomask, ones, sort, zeros, getdata, get_masked_subclass, dot,
mask_rowcols
)
imp... | Any masked values in x is propagated in y, and vice-versa. |
170,240 | import sys
class Configuration:
_list_keys = ['packages', 'ext_modules', 'data_files', 'include_dirs',
'libraries', 'headers', 'scripts', 'py_modules',
'installed_libraries', 'define_macros']
_dict_keys = ['package_dir', 'installed_pkg_config']
_extra_keys = ['name', 'v... | null |
170,241 | import functools
from numpy.core import asarray, zeros, swapaxes, conjugate, take, sqrt
from . import _pocketfft_internal as pfi
from numpy.core.multiarray import normalize_axis_index
from numpy.core import overrides
def _fft_dispatcher(a, n=None, axis=None, norm=None):
return (a,) | null |
170,242 | import functools
from numpy.core import asarray, zeros, swapaxes, conjugate, take, sqrt
from . import _pocketfft_internal as pfi
from numpy.core.multiarray import normalize_axis_index
from numpy.core import overrides
def _swap_direction(norm):
try:
return _SWAP_DIRECTION_MAP[norm]
except KeyError:
... | Compute the FFT of a signal that has Hermitian symmetry, i.e., a real spectrum. Parameters ---------- a : array_like The input array. n : int, optional Length of the transformed axis of the output. For `n` output points, ``n//2 + 1`` input points are necessary. If the input is longer than this, it is cropped. If it is ... |
170,243 | import functools
from numpy.core import asarray, zeros, swapaxes, conjugate, take, sqrt
from . import _pocketfft_internal as pfi
from numpy.core.multiarray import normalize_axis_index
from numpy.core import overrides
def _swap_direction(norm):
try:
return _SWAP_DIRECTION_MAP[norm]
except KeyError:
... | Compute the inverse FFT of a signal that has Hermitian symmetry. Parameters ---------- a : array_like Input array. n : int, optional Length of the inverse FFT, the number of points along transformation axis in the input to use. If `n` is smaller than the length of the input, the input is cropped. If it is larger, the i... |
170,244 | import functools
from numpy.core import asarray, zeros, swapaxes, conjugate, take, sqrt
from . import _pocketfft_internal as pfi
from numpy.core.multiarray import normalize_axis_index
from numpy.core import overrides
def _fftn_dispatcher(a, s=None, axes=None, norm=None):
return (a,) | null |
170,245 | import functools
from numpy.core import asarray, zeros, swapaxes, conjugate, take, sqrt
from . import _pocketfft_internal as pfi
from numpy.core.multiarray import normalize_axis_index
from numpy.core import overrides
def fft(a, n=None, axis=-1, norm=None):
"""
Compute the one-dimensional discrete Fourier Transf... | Compute the N-dimensional discrete Fourier Transform. This function computes the *N*-dimensional discrete Fourier Transform over any number of axes in an *M*-dimensional array by means of the Fast Fourier Transform (FFT). Parameters ---------- a : array_like Input array, can be complex. s : sequence of ints, optional S... |
170,246 | import functools
from numpy.core import asarray, zeros, swapaxes, conjugate, take, sqrt
from . import _pocketfft_internal as pfi
from numpy.core.multiarray import normalize_axis_index
from numpy.core import overrides
def ifft(a, n=None, axis=-1, norm=None):
"""
Compute the one-dimensional inverse discrete Fouri... | Compute the N-dimensional inverse discrete Fourier Transform. This function computes the inverse of the N-dimensional discrete Fourier Transform over any number of axes in an M-dimensional array by means of the Fast Fourier Transform (FFT). In other words, ``ifftn(fftn(a)) == a`` to within numerical accuracy. For a des... |
170,247 | import functools
from numpy.core import asarray, zeros, swapaxes, conjugate, take, sqrt
from . import _pocketfft_internal as pfi
from numpy.core.multiarray import normalize_axis_index
from numpy.core import overrides
def fft(a, n=None, axis=-1, norm=None):
"""
Compute the one-dimensional discrete Fourier Transf... | Compute the 2-dimensional discrete Fourier Transform. This function computes the *n*-dimensional discrete Fourier Transform over any axes in an *M*-dimensional array by means of the Fast Fourier Transform (FFT). By default, the transform is computed over the last two axes of the input array, i.e., a 2-dimensional FFT. ... |
170,248 | import functools
from numpy.core import asarray, zeros, swapaxes, conjugate, take, sqrt
from . import _pocketfft_internal as pfi
from numpy.core.multiarray import normalize_axis_index
from numpy.core import overrides
def ifft(a, n=None, axis=-1, norm=None):
"""
Compute the one-dimensional inverse discrete Fouri... | Compute the 2-dimensional inverse discrete Fourier Transform. This function computes the inverse of the 2-dimensional discrete Fourier Transform over any number of axes in an M-dimensional array by means of the Fast Fourier Transform (FFT). In other words, ``ifft2(fft2(a)) == a`` to within numerical accuracy. By defaul... |
170,249 | import functools
from numpy.core import asarray, zeros, swapaxes, conjugate, take, sqrt
from . import _pocketfft_internal as pfi
from numpy.core.multiarray import normalize_axis_index
from numpy.core import overrides
def rfftn(a, s=None, axes=None, norm=None):
"""
Compute the N-dimensional discrete Fourier Tran... | Compute the 2-dimensional FFT of a real array. Parameters ---------- a : array Input array, taken to be real. s : sequence of ints, optional Shape of the FFT. axes : sequence of ints, optional Axes over which to compute the FFT. norm : {"backward", "ortho", "forward"}, optional .. versionadded:: 1.10.0 Normalization mo... |
170,250 | import functools
from numpy.core import asarray, zeros, swapaxes, conjugate, take, sqrt
from . import _pocketfft_internal as pfi
from numpy.core.multiarray import normalize_axis_index
from numpy.core import overrides
def irfftn(a, s=None, axes=None, norm=None):
"""
Computes the inverse of `rfftn`.
This func... | Computes the inverse of `rfft2`. Parameters ---------- a : array_like The input array s : sequence of ints, optional Shape of the real output to the inverse FFT. axes : sequence of ints, optional The axes over which to compute the inverse fft. Default is the last two axes. norm : {"backward", "ortho", "forward"}, optio... |
170,251 | from numpy.core import integer, empty, arange, asarray, roll
from numpy.core.overrides import array_function_dispatch, set_module
def _fftshift_dispatcher(x, axes=None):
return (x,) | null |
170,252 | from numpy.core import integer, empty, arange, asarray, roll
from numpy.core.overrides import array_function_dispatch, set_module
integer_types = (int, integer)
The provided code snippet includes necessary dependencies for implementing the `fftshift` function. Write a Python function `def fftshift(x, axes=None)` to so... | Shift the zero-frequency component to the center of the spectrum. This function swaps half-spaces for all axes listed (defaults to all). Note that ``y[0]`` is the Nyquist component only if ``len(x)`` is even. Parameters ---------- x : array_like Input array. axes : int or shape tuple, optional Axes over which to shift.... |
170,253 | from numpy.core import integer, empty, arange, asarray, roll
from numpy.core.overrides import array_function_dispatch, set_module
integer_types = (int, integer)
The provided code snippet includes necessary dependencies for implementing the `ifftshift` function. Write a Python function `def ifftshift(x, axes=None)` to ... | The inverse of `fftshift`. Although identical for even-length `x`, the functions differ by one sample for odd-length `x`. Parameters ---------- x : array_like Input array. axes : int or shape tuple, optional Axes over which to calculate. Defaults to None, which shifts all axes. Returns ------- y : ndarray The shifted a... |
170,254 | from numpy.core import integer, empty, arange, asarray, roll
from numpy.core.overrides import array_function_dispatch, set_module
integer_types = (int, integer)
The provided code snippet includes necessary dependencies for implementing the `fftfreq` function. Write a Python function `def fftfreq(n, d=1.0)` to solve th... | Return the Discrete Fourier Transform sample frequencies. The returned float array `f` contains the frequency bin centers in cycles per unit of the sample spacing (with zero at the start). For instance, if the sample spacing is in seconds, then the frequency unit is cycles/second. Given a window length `n` and a sample... |
170,255 | from numpy.core import integer, empty, arange, asarray, roll
from numpy.core.overrides import array_function_dispatch, set_module
integer_types = (int, integer)
The provided code snippet includes necessary dependencies for implementing the `rfftfreq` function. Write a Python function `def rfftfreq(n, d=1.0)` to solve ... | Return the Discrete Fourier Transform sample frequencies (for usage with rfft, irfft). The returned float array `f` contains the frequency bin centers in cycles per unit of the sample spacing (with zero at the start). For instance, if the sample spacing is in seconds, then the frequency unit is cycles/second. Given a w... |
170,271 |
class Configuration:
def __init__(self,
package_name=None,
parent_name=None,
top_path=None,
package_path=None,
caller_level=1,
setup_name='setup.py',
**attrs):
d... | null |
170,272 | import os
import sys
import re
def process_str(allstr):
newstr = allstr
writestr = ''
struct = parse_structure(newstr)
oldend = 0
names = {}
names.update(_special_names)
for sub in struct:
cleanedstr, defs = find_and_remove_repl_patterns(newstr[oldend:sub[0]])
writestr += cle... | null |
170,273 | import os
import re
import sys
import shlex
import time
import subprocess
from copy import copy
from distutils import ccompiler
from distutils.ccompiler import (
compiler_class, gen_lib_options, get_default_compiler, new_compiler,
CCompiler
)
from distutils.errors import (
DistutilsExecError, DistutilsModul... | null |
170,274 | import os
import re
import sys
import shlex
import time
import subprocess
from copy import copy
from distutils import ccompiler
from distutils.ccompiler import (
compiler_class, gen_lib_options, get_default_compiler, new_compiler,
CCompiler
)
from distutils.errors import (
DistutilsExecError, DistutilsModul... | Does nothing here, but is called by the get_version method and can be overridden by subclasses. In particular it is redefined in the `FCompiler` class where more documentation can be found. |
170,275 | import os
import re
import sys
import shlex
import time
import subprocess
from copy import copy
from distutils import ccompiler
from distutils.ccompiler import (
compiler_class, gen_lib_options, get_default_compiler, new_compiler,
CCompiler
)
from distutils.errors import (
DistutilsExecError, DistutilsModul... | Execute a command in a sub-process. Parameters ---------- cmd : str The command to execute. display : str or sequence of str, optional The text to add to the log file kept by `numpy.distutils`. If not given, `display` is equal to `cmd`. env : a dictionary for environment variables, optional Returns ------- None Raises ... |
170,276 | import os
import re
import sys
import shlex
import time
import subprocess
from copy import copy
from distutils import ccompiler
from distutils.ccompiler import (
compiler_class, gen_lib_options, get_default_compiler, new_compiler,
CCompiler
)
from distutils.errors import (
DistutilsExecError, DistutilsModul... | Return the name of the object files for the given source files. Parameters ---------- source_filenames : list of str The list of paths to source files. Paths can be either relative or absolute, this is handled transparently. strip_dir : bool, optional Whether to strip the directory from the returned paths. If True, the... |
170,277 | import os
import re
import sys
import shlex
import time
import subprocess
from copy import copy
from distutils import ccompiler
from distutils.ccompiler import (
compiler_class, gen_lib_options, get_default_compiler, new_compiler,
CCompiler
)
from distutils.errors import (
DistutilsExecError, DistutilsModul... | Compile one or more source files. Please refer to the Python distutils API reference for more details. Parameters ---------- sources : list of str A list of filenames output_dir : str, optional Path to the output directory. macros : list of tuples A list of macro definitions. include_dirs : list of str, optional The di... |
170,278 | import os
import re
import sys
import shlex
import time
import subprocess
from copy import copy
from distutils import ccompiler
from distutils.ccompiler import (
compiler_class, gen_lib_options, get_default_compiler, new_compiler,
CCompiler
)
from distutils.errors import (
DistutilsExecError, DistutilsModul... | Customize compiler using distutils command. Parameters ---------- cmd : class instance An instance inheriting from `distutils.cmd.Command`. ignore : sequence of str, optional List of `CCompiler` commands (without ``'set_'``) that should not be altered. Strings that are checked for are: ``('include_dirs', 'define', 'und... |
170,279 | import os
import re
import sys
import shlex
import time
import subprocess
from copy import copy
from distutils import ccompiler
from distutils.ccompiler import (
compiler_class, gen_lib_options, get_default_compiler, new_compiler,
CCompiler
)
from distutils.errors import (
DistutilsExecError, DistutilsModul... | Print the compiler customizations to stdout. Parameters ---------- None Returns ------- None Notes ----- Printing is only done if the distutils log threshold is < 2. |
170,280 | import os
import re
import sys
import shlex
import time
import subprocess
from copy import copy
from distutils import ccompiler
from distutils.ccompiler import (
compiler_class, gen_lib_options, get_default_compiler, new_compiler,
CCompiler
)
from distutils.errors import (
DistutilsExecError, DistutilsModul... | Do any platform-specific customization of a compiler instance. This method calls `distutils.sysconfig.customize_compiler` for platform-specific customization, as well as optionally remove a flag to suppress spurious warnings in case C++ code is being compiled. Parameters ---------- dist : object This parameter is not u... |
170,281 | import os
import re
import sys
import shlex
import time
import subprocess
from copy import copy
from distutils import ccompiler
from distutils.ccompiler import (
compiler_class, gen_lib_options, get_default_compiler, new_compiler,
CCompiler
)
from distutils.errors import (
DistutilsExecError, DistutilsModul... | Return compiler version, or None if compiler is not available. Parameters ---------- force : bool, optional If True, force a new determination of the version, even if the compiler already has a version attribute. Default is False. ok_status : list of int, optional The list of status values returned by the version look-... |
170,282 | import os
import re
import sys
import shlex
import time
import subprocess
from copy import copy
from distutils import ccompiler
from distutils.ccompiler import (
compiler_class, gen_lib_options, get_default_compiler, new_compiler,
CCompiler
)
from distutils.errors import (
DistutilsExecError, DistutilsModul... | Return the C++ compiler. Parameters ---------- None Returns ------- cxx : class instance The C++ compiler, as a `CCompiler` instance. |
170,283 | import os
import re
import sys
import shlex
import time
import subprocess
from copy import copy
from distutils import ccompiler
from distutils.ccompiler import (
compiler_class, gen_lib_options, get_default_compiler, new_compiler,
CCompiler
)
from distutils.errors import (
DistutilsExecError, DistutilsModul... | null |
170,284 | import os
import re
import sys
import shlex
import time
import subprocess
from copy import copy
from distutils import ccompiler
from distutils.ccompiler import (
compiler_class, gen_lib_options, get_default_compiler, new_compiler,
CCompiler
)
from distutils.errors import (
DistutilsExecError, DistutilsModul... | null |
170,285 | import os
import re
import sys
import copy
import glob
import atexit
import tempfile
import subprocess
import shutil
import multiprocessing
import textwrap
import importlib.util
from threading import local as tlocal
from functools import reduce
import distutils
from distutils.errors import DistutilsError
_tmpdirs = []
... | null |
170,286 | import os
import re
import sys
import copy
import glob
import atexit
import tempfile
import subprocess
import shutil
import multiprocessing
import textwrap
import importlib.util
from threading import local as tlocal
from functools import reduce
import distutils
from distutils.errors import DistutilsError
import warnin... | Quote list of arguments. .. deprecated:: 1.22. |
170,287 | import os
import re
import sys
import copy
import glob
import atexit
import tempfile
import subprocess
import shutil
import multiprocessing
import textwrap
import importlib.util
from threading import local as tlocal
from functools import reduce
import distutils
from distutils.errors import DistutilsError
The provided ... | Convert a /-separated pathname to one using the OS's path separator. |
170,288 | import os
import re
import sys
import copy
import glob
import atexit
import tempfile
import subprocess
import shutil
import multiprocessing
import textwrap
import importlib.util
from threading import local as tlocal
from functools import reduce
import distutils
from distutils.errors import DistutilsError
def rel_path(p... | Return path of the module given a frame object from the call stack. Returned path is relative to parent_path when given, otherwise it is absolute path. |
170,289 | import os
import re
import sys
import copy
import glob
import atexit
import tempfile
import subprocess
import shutil
import multiprocessing
import textwrap
import importlib.util
from threading import local as tlocal
from functools import reduce
import distutils
from distutils.errors import DistutilsError
def _fix_paths... | Apply glob to paths and prepend local_path if needed. |
170,290 | import os
import re
import sys
import copy
import glob
import atexit
import tempfile
import subprocess
import shutil
import multiprocessing
import textwrap
import importlib.util
from threading import local as tlocal
from functools import reduce
import distutils
from distutils.errors import DistutilsError
def terminal_... | null |
170,291 | import os
import re
import sys
import copy
import glob
import atexit
import tempfile
import subprocess
import shutil
import multiprocessing
import textwrap
import importlib.util
from threading import local as tlocal
from functools import reduce
import distutils
from distutils.errors import DistutilsError
if terminal_ha... | null |
170,292 | import os
import re
import sys
import copy
import glob
import atexit
import tempfile
import subprocess
import shutil
import multiprocessing
import textwrap
import importlib.util
from threading import local as tlocal
from functools import reduce
import distutils
from distutils.errors import DistutilsError
if terminal_ha... | null |
170,293 | import os
import re
import sys
import copy
import glob
import atexit
import tempfile
import subprocess
import shutil
import multiprocessing
import textwrap
import importlib.util
from threading import local as tlocal
from functools import reduce
import distutils
from distutils.errors import DistutilsError
if terminal_ha... | null |
170,294 | import os
import re
import sys
import copy
import glob
import atexit
import tempfile
import subprocess
import shutil
import multiprocessing
import textwrap
import importlib.util
from threading import local as tlocal
from functools import reduce
import distutils
from distutils.errors import DistutilsError
if terminal_ha... | null |
170,295 | import os
import re
import sys
import copy
import glob
import atexit
import tempfile
import subprocess
import shutil
import multiprocessing
import textwrap
import importlib.util
from threading import local as tlocal
from functools import reduce
import distutils
from distutils.errors import DistutilsError
if terminal_ha... | null |
170,296 | import os
import re
import sys
import copy
import glob
import atexit
import tempfile
import subprocess
import shutil
import multiprocessing
import textwrap
import importlib.util
from threading import local as tlocal
from functools import reduce
import distutils
from distutils.errors import DistutilsError
if terminal_ha... | null |
170,297 | import os
import re
import sys
import copy
import glob
import atexit
import tempfile
import subprocess
import shutil
import multiprocessing
import textwrap
import importlib.util
from threading import local as tlocal
from functools import reduce
import distutils
from distutils.errors import DistutilsError
def is_string(... | Return True if all items in lst are string objects. |
170,298 | import os
import re
import sys
import copy
import glob
import atexit
import tempfile
import subprocess
import shutil
import multiprocessing
import textwrap
import importlib.util
from threading import local as tlocal
from functools import reduce
import distutils
from distutils.errors import DistutilsError
def is_string(... | null |
170,299 | import os
import re
import sys
import copy
import glob
import atexit
import tempfile
import subprocess
import shutil
import multiprocessing
import textwrap
import importlib.util
from threading import local as tlocal
from functools import reduce
import distutils
from distutils.errors import DistutilsError
def is_sequenc... | null |
170,300 | import os
import re
import sys
import copy
import glob
import atexit
import tempfile
import subprocess
import shutil
import multiprocessing
import textwrap
import importlib.util
from threading import local as tlocal
from functools import reduce
import distutils
from distutils.errors import DistutilsError
fortran_ext_ma... | Determine language value (c,f77,f90) from sources |
170,301 | import os
import re
import sys
import copy
import glob
import atexit
import tempfile
import subprocess
import shutil
import multiprocessing
import textwrap
import importlib.util
from threading import local as tlocal
from functools import reduce
import distutils
from distutils.errors import DistutilsError
fortran_ext_ma... | Return True if sources contains Fortran files |
170,302 | import os
import re
import sys
import copy
import glob
import atexit
import tempfile
import subprocess
import shutil
import multiprocessing
import textwrap
import importlib.util
from threading import local as tlocal
from functools import reduce
import distutils
from distutils.errors import DistutilsError
cxx_ext_match ... | Return True if sources contains C++ files |
170,303 | import os
import re
import sys
import copy
import glob
import atexit
import tempfile
import subprocess
import shutil
import multiprocessing
import textwrap
import importlib.util
from threading import local as tlocal
from functools import reduce
import distutils
from distutils.errors import DistutilsError
cxx_ext_match ... | Return four lists of filenames containing C, C++, Fortran, and Fortran 90 module sources, respectively. |
170,304 | import os
import re
import sys
import copy
import glob
import atexit
import tempfile
import subprocess
import shutil
import multiprocessing
import textwrap
import importlib.util
from threading import local as tlocal
from functools import reduce
import distutils
from distutils.errors import DistutilsError
def rel_path(p... | Return a directory name relative to top_path and files contained. |
170,305 | import os
import re
import sys
import copy
import glob
import atexit
import tempfile
import subprocess
import shutil
import multiprocessing
import textwrap
import importlib.util
from threading import local as tlocal
from functools import reduce
import distutils
from distutils.errors import DistutilsError
def is_string(... | null |
170,306 | import os
import re
import sys
import copy
import glob
import atexit
import tempfile
import subprocess
import shutil
import multiprocessing
import textwrap
import importlib.util
from threading import local as tlocal
from functools import reduce
import distutils
from distutils.errors import DistutilsError
def is_string(... | null |
170,307 | import os
import re
import sys
import copy
import glob
import atexit
import tempfile
import subprocess
import shutil
import multiprocessing
import textwrap
import importlib.util
from threading import local as tlocal
from functools import reduce
import distutils
from distutils.errors import DistutilsError
def is_string(... | null |
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