doc_content stringlengths 1 386k | doc_id stringlengths 5 188 |
|---|---|
numpy.record.argsort method record.argsort()
Scalar method identical to the corresponding array attribute. Please see ndarray.argsort. | numpy.reference.generated.numpy.record.argsort |
numpy.record.astype method record.astype()
Scalar method identical to the corresponding array attribute. Please see ndarray.astype. | numpy.reference.generated.numpy.record.astype |
numpy.record.base attribute record.base
base object | numpy.reference.generated.numpy.record.base |
numpy.record.byteswap method record.byteswap()
Scalar method identical to the corresponding array attribute. Please see ndarray.byteswap. | numpy.reference.generated.numpy.record.byteswap |
numpy.record.choose method record.choose()
Scalar method identical to the corresponding array attribute. Please see ndarray.choose. | numpy.reference.generated.numpy.record.choose |
numpy.record.clip method record.clip()
Scalar method identical to the corresponding array attribute. Please see ndarray.clip. | numpy.reference.generated.numpy.record.clip |
numpy.record.compress method record.compress()
Scalar method identical to the corresponding array attribute. Please see ndarray.compress. | numpy.reference.generated.numpy.record.compress |
numpy.record.conjugate method record.conjugate()
Scalar method identical to the corresponding array attribute. Please see ndarray.conjugate. | numpy.reference.generated.numpy.record.conjugate |
numpy.record.copy method record.copy()
Scalar method identical to the corresponding array attribute. Please see ndarray.copy. | numpy.reference.generated.numpy.record.copy |
numpy.record.cumprod method record.cumprod()
Scalar method identical to the corresponding array attribute. Please see ndarray.cumprod. | numpy.reference.generated.numpy.record.cumprod |
numpy.record.cumsum method record.cumsum()
Scalar method identical to the corresponding array attribute. Please see ndarray.cumsum. | numpy.reference.generated.numpy.record.cumsum |
numpy.record.data attribute record.data
Pointer to start of data. | numpy.reference.generated.numpy.record.data |
numpy.record.diagonal method record.diagonal()
Scalar method identical to the corresponding array attribute. Please see ndarray.diagonal. | numpy.reference.generated.numpy.record.diagonal |
numpy.record.dump method record.dump()
Scalar method identical to the corresponding array attribute. Please see ndarray.dump. | numpy.reference.generated.numpy.record.dump |
numpy.record.dumps method record.dumps()
Scalar method identical to the corresponding array attribute. Please see ndarray.dumps. | numpy.reference.generated.numpy.record.dumps |
numpy.record.fill method record.fill()
Scalar method identical to the corresponding array attribute. Please see ndarray.fill. | numpy.reference.generated.numpy.record.fill |
numpy.record.flags attribute record.flags
integer value of flags | numpy.reference.generated.numpy.record.flags |
numpy.record.flat attribute record.flat
A 1-D view of the scalar. | numpy.reference.generated.numpy.record.flat |
numpy.record.flatten method record.flatten()
Scalar method identical to the corresponding array attribute. Please see ndarray.flatten. | numpy.reference.generated.numpy.record.flatten |
numpy.record.getfield method record.getfield()
Scalar method identical to the corresponding array attribute. Please see ndarray.getfield. | numpy.reference.generated.numpy.record.getfield |
numpy.record.item method record.item()
Scalar method identical to the corresponding array attribute. Please see ndarray.item. | numpy.reference.generated.numpy.record.item |
numpy.record.itemset method record.itemset()
Scalar method identical to the corresponding array attribute. Please see ndarray.itemset. | numpy.reference.generated.numpy.record.itemset |
numpy.record.itemsize attribute record.itemsize
The length of one element in bytes. | numpy.reference.generated.numpy.record.itemsize |
numpy.record.max method record.max()
Scalar method identical to the corresponding array attribute. Please see ndarray.max. | numpy.reference.generated.numpy.record.max |
numpy.record.mean method record.mean()
Scalar method identical to the corresponding array attribute. Please see ndarray.mean. | numpy.reference.generated.numpy.record.mean |
numpy.record.min method record.min()
Scalar method identical to the corresponding array attribute. Please see ndarray.min. | numpy.reference.generated.numpy.record.min |
numpy.record.nbytes attribute record.nbytes
The length of the scalar in bytes. | numpy.reference.generated.numpy.record.nbytes |
numpy.record.ndim attribute record.ndim
The number of array dimensions. | numpy.reference.generated.numpy.record.ndim |
numpy.record.newbyteorder method record.newbyteorder(new_order='S', /)
Return a new dtype with a different byte order. Changes are also made in all fields and sub-arrays of the data type. The new_order code can be any from the following: ‘S’ - swap dtype from current to opposite endian {‘<’, ‘little’} - little end... | numpy.reference.generated.numpy.record.newbyteorder |
numpy.record.nonzero method record.nonzero()
Scalar method identical to the corresponding array attribute. Please see ndarray.nonzero. | numpy.reference.generated.numpy.record.nonzero |
numpy.record.pprint method record.pprint()[source]
Pretty-print all fields. | numpy.reference.generated.numpy.record.pprint |
numpy.record.prod method record.prod()
Scalar method identical to the corresponding array attribute. Please see ndarray.prod. | numpy.reference.generated.numpy.record.prod |
numpy.record.ptp method record.ptp()
Scalar method identical to the corresponding array attribute. Please see ndarray.ptp. | numpy.reference.generated.numpy.record.ptp |
numpy.record.put method record.put()
Scalar method identical to the corresponding array attribute. Please see ndarray.put. | numpy.reference.generated.numpy.record.put |
numpy.record.ravel method record.ravel()
Scalar method identical to the corresponding array attribute. Please see ndarray.ravel. | numpy.reference.generated.numpy.record.ravel |
numpy.record.repeat method record.repeat()
Scalar method identical to the corresponding array attribute. Please see ndarray.repeat. | numpy.reference.generated.numpy.record.repeat |
numpy.record.reshape method record.reshape()
Scalar method identical to the corresponding array attribute. Please see ndarray.reshape. | numpy.reference.generated.numpy.record.reshape |
numpy.record.resize method record.resize()
Scalar method identical to the corresponding array attribute. Please see ndarray.resize. | numpy.reference.generated.numpy.record.resize |
numpy.record.round method record.round()
Scalar method identical to the corresponding array attribute. Please see ndarray.round. | numpy.reference.generated.numpy.record.round |
numpy.record.searchsorted method record.searchsorted()
Scalar method identical to the corresponding array attribute. Please see ndarray.searchsorted. | numpy.reference.generated.numpy.record.searchsorted |
numpy.record.setfield method record.setfield()
Scalar method identical to the corresponding array attribute. Please see ndarray.setfield. | numpy.reference.generated.numpy.record.setfield |
numpy.record.setflags method record.setflags()
Scalar method identical to the corresponding array attribute. Please see ndarray.setflags. | numpy.reference.generated.numpy.record.setflags |
numpy.record.size attribute record.size
The number of elements in the gentype. | numpy.reference.generated.numpy.record.size |
numpy.record.sort method record.sort()
Scalar method identical to the corresponding array attribute. Please see ndarray.sort. | numpy.reference.generated.numpy.record.sort |
numpy.record.squeeze method record.squeeze()
Scalar method identical to the corresponding array attribute. Please see ndarray.squeeze. | numpy.reference.generated.numpy.record.squeeze |
numpy.record.std method record.std()
Scalar method identical to the corresponding array attribute. Please see ndarray.std. | numpy.reference.generated.numpy.record.std |
numpy.record.strides attribute record.strides
Tuple of bytes steps in each dimension. | numpy.reference.generated.numpy.record.strides |
numpy.record.sum method record.sum()
Scalar method identical to the corresponding array attribute. Please see ndarray.sum. | numpy.reference.generated.numpy.record.sum |
numpy.record.swapaxes method record.swapaxes()
Scalar method identical to the corresponding array attribute. Please see ndarray.swapaxes. | numpy.reference.generated.numpy.record.swapaxes |
numpy.record.T attribute record.T
Scalar attribute identical to the corresponding array attribute. Please see ndarray.T. | numpy.reference.generated.numpy.record.t |
numpy.record.take method record.take()
Scalar method identical to the corresponding array attribute. Please see ndarray.take. | numpy.reference.generated.numpy.record.take |
numpy.record.tofile method record.tofile()
Scalar method identical to the corresponding array attribute. Please see ndarray.tofile. | numpy.reference.generated.numpy.record.tofile |
numpy.record.tolist method record.tolist()
Scalar method identical to the corresponding array attribute. Please see ndarray.tolist. | numpy.reference.generated.numpy.record.tolist |
numpy.record.tostring method record.tostring()
Scalar method identical to the corresponding array attribute. Please see ndarray.tostring. | numpy.reference.generated.numpy.record.tostring |
numpy.record.trace method record.trace()
Scalar method identical to the corresponding array attribute. Please see ndarray.trace. | numpy.reference.generated.numpy.record.trace |
numpy.record.transpose method record.transpose()
Scalar method identical to the corresponding array attribute. Please see ndarray.transpose. | numpy.reference.generated.numpy.record.transpose |
numpy.record.var method record.var()
Scalar method identical to the corresponding array attribute. Please see ndarray.var. | numpy.reference.generated.numpy.record.var |
numpy.record.view method record.view()
Scalar method identical to the corresponding array attribute. Please see ndarray.view. | numpy.reference.generated.numpy.record.view |
NumPy Reference Release
1.22 Date
December 31, 2021 This reference manual details functions, modules, and objects included in NumPy, describing what they are and what they do. For learning how to use NumPy, see the complete documentation.
Array objects The N-dimensional array (ndarray) Scalars Data type objects... | numpy.reference.index |
Routines In this chapter routine docstrings are presented, grouped by functionality. Many docstrings contain example code, which demonstrates basic usage of the routine. The examples assume that NumPy is imported with: >>> import numpy as np
A convenient way to execute examples is the %doctest_mode mode of IPython, wh... | numpy.reference.routines |
Testing the numpy.i Typemaps Introduction Writing tests for the numpy.i SWIG interface file is a combinatorial headache. At present, 12 different data types are supported, each with 74 different argument signatures, for a total of 888 typemaps supported “out of the box”. Each of these typemaps, in turn, might require ... | numpy.reference.swig.testing |
setup.py #!/usr/bin/env python3
"""
Build the Cython demonstrations of low-level access to NumPy random
Usage: python setup.py build_ext -i
"""
import setuptools # triggers monkeypatching distutils
from distutils.core import setup
from os.path import dirname, join, abspath
import numpy as np
from Cython.Build import... | numpy.reference.random.examples.cython.setup.py |
Statistics Order statistics
ptp(a[, axis, out, keepdims]) Range of values (maximum - minimum) along an axis.
percentile(a, q[, axis, out, ...]) Compute the q-th percentile of the data along the specified axis.
nanpercentile(a, q[, axis, out, ...]) Compute the qth percentile of the data along the specified axis, ... | numpy.reference.routines.statistics |
numpy.testing.assert_allclose testing.assert_allclose(actual, desired, rtol=1e-07, atol=0, equal_nan=True, err_msg='', verbose=True)[source]
Raises an AssertionError if two objects are not equal up to desired tolerance. The test is equivalent to allclose(actual, desired, rtol, atol) (note that allclose has differen... | numpy.reference.generated.numpy.testing.assert_allclose |
numpy.testing.assert_almost_equal testing.assert_almost_equal(actual, desired, decimal=7, err_msg='', verbose=True)[source]
Raises an AssertionError if two items are not equal up to desired precision. Note It is recommended to use one of assert_allclose, assert_array_almost_equal_nulp or assert_array_max_ulp inste... | numpy.reference.generated.numpy.testing.assert_almost_equal |
numpy.testing.assert_approx_equal testing.assert_approx_equal(actual, desired, significant=7, err_msg='', verbose=True)[source]
Raises an AssertionError if two items are not equal up to significant digits. Note It is recommended to use one of assert_allclose, assert_array_almost_equal_nulp or assert_array_max_ulp ... | numpy.reference.generated.numpy.testing.assert_approx_equal |
numpy.testing.assert_array_almost_equal testing.assert_array_almost_equal(x, y, decimal=6, err_msg='', verbose=True)[source]
Raises an AssertionError if two objects are not equal up to desired precision. Note It is recommended to use one of assert_allclose, assert_array_almost_equal_nulp or assert_array_max_ulp in... | numpy.reference.generated.numpy.testing.assert_array_almost_equal |
numpy.testing.assert_array_almost_equal_nulp testing.assert_array_almost_equal_nulp(x, y, nulp=1)[source]
Compare two arrays relatively to their spacing. This is a relatively robust method to compare two arrays whose amplitude is variable. Parameters
x, yarray_like
Input arrays.
nulpint, optional
The maxi... | numpy.reference.generated.numpy.testing.assert_array_almost_equal_nulp |
numpy.testing.assert_array_equal testing.assert_array_equal(x, y, err_msg='', verbose=True)[source]
Raises an AssertionError if two array_like objects are not equal. Given two array_like objects, check that the shape is equal and all elements of these objects are equal (but see the Notes for the special handling of... | numpy.reference.generated.numpy.testing.assert_array_equal |
numpy.testing.assert_array_less testing.assert_array_less(x, y, err_msg='', verbose=True)[source]
Raises an AssertionError if two array_like objects are not ordered by less than. Given two array_like objects, check that the shape is equal and all elements of the first object are strictly smaller than those of the s... | numpy.reference.generated.numpy.testing.assert_array_less |
numpy.testing.assert_array_max_ulp testing.assert_array_max_ulp(a, b, maxulp=1, dtype=None)[source]
Check that all items of arrays differ in at most N Units in the Last Place. Parameters
a, barray_like
Input arrays to be compared.
maxulpint, optional
The maximum number of units in the last place that elem... | numpy.reference.generated.numpy.testing.assert_array_max_ulp |
numpy.testing.assert_equal testing.assert_equal(actual, desired, err_msg='', verbose=True)[source]
Raises an AssertionError if two objects are not equal. Given two objects (scalars, lists, tuples, dictionaries or numpy arrays), check that all elements of these objects are equal. An exception is raised at the first ... | numpy.reference.generated.numpy.testing.assert_equal |
numpy.testing.assert_raises testing.assert_raises(exception_class, callable, *args, **kwargs) assert_raises(exception_class)[source]
testing.assert_raises(exception_class) → None
Fail unless an exception of class exception_class is thrown by callable when invoked with arguments args and keyword arguments kwargs. ... | numpy.reference.generated.numpy.testing.assert_raises |
numpy.testing.assert_raises_regex testing.assert_raises_regex(exception_class, expected_regexp, callable, *args, **kwargs) assert_raises_regex(exception_class, expected_regexp)[source]
Fail unless an exception of class exception_class and with message that matches expected_regexp is thrown by callable when invoked ... | numpy.reference.generated.numpy.testing.assert_raises_regex |
numpy.testing.assert_string_equal testing.assert_string_equal(actual, desired)[source]
Test if two strings are equal. If the given strings are equal, assert_string_equal does nothing. If they are not equal, an AssertionError is raised, and the diff between the strings is shown. Parameters
actualstr
The string... | numpy.reference.generated.numpy.testing.assert_string_equal |
numpy.testing.assert_warns testing.assert_warns(warning_class, *args, **kwargs)[source]
Fail unless the given callable throws the specified warning. A warning of class warning_class should be thrown by the callable when invoked with arguments args and keyword arguments kwargs. If a different type of warning is thro... | numpy.reference.generated.numpy.testing.assert_warns |
numpy.testing.dec.deprecated testing.dec.deprecated(conditional=True)[source]
Deprecated since version 1.21: This decorator is retained for compatibility with the nose testing framework, which is being phased out. Please use the nose2 or pytest frameworks instead. Filter deprecation warnings while running the tes... | numpy.reference.generated.numpy.testing.dec.deprecated |
numpy.testing.dec.knownfailureif testing.dec.knownfailureif(fail_condition, msg=None)[source]
Deprecated since version 1.21: This decorator is retained for compatibility with the nose testing framework, which is being phased out. Please use the nose2 or pytest frameworks instead. Make function raise KnownFailureE... | numpy.reference.generated.numpy.testing.dec.knownfailureif |
numpy.testing.dec.setastest testing.dec.setastest(tf=True)[source]
Deprecated since version 1.21: This decorator is retained for compatibility with the nose testing framework, which is being phased out. Please use the nose2 or pytest frameworks instead. Signals to nose that this function is or is not a test. Par... | numpy.reference.generated.numpy.testing.dec.setastest |
numpy.testing.dec.skipif testing.dec.skipif(skip_condition, msg=None)[source]
Deprecated since version 1.21: This decorator is retained for compatibility with the nose testing framework, which is being phased out. Please use the nose2 or pytest frameworks instead. Make function raise SkipTest exception if a given... | numpy.reference.generated.numpy.testing.dec.skipif |
numpy.testing.dec.slow testing.dec.slow(t)[source]
Deprecated since version 1.21: This decorator is retained for compatibility with the nose testing framework, which is being phased out. Please use the nose2 or pytest frameworks instead. Label a test as ‘slow’. The exact definition of a slow test is obviously bot... | numpy.reference.generated.numpy.testing.dec.slow |
numpy.testing.decorate_methods testing.decorate_methods(cls, decorator, testmatch=None)[source]
Apply a decorator to all methods in a class matching a regular expression. The given decorator is applied to all public methods of cls that are matched by the regular expression testmatch (testmatch.search(methodname)). ... | numpy.reference.generated.numpy.testing.decorate_methods |
numpy.testing.run_module_suite testing.run_module_suite(file_to_run=None, argv=None)[source]
Run a test module. Equivalent to calling $ nosetests <argv> <file_to_run> from the command line Parameters
file_to_runstr, optional
Path to test module, or None. By default, run the module from which this function is ... | numpy.reference.generated.numpy.testing.run_module_suite |
numpy.testing.rundocs testing.rundocs(filename=None, raise_on_error=True)[source]
Run doctests found in the given file. By default rundocs raises an AssertionError on failure. Parameters
filenamestr
The path to the file for which the doctests are run.
raise_on_errorbool
Whether to raise an AssertionError ... | numpy.reference.generated.numpy.testing.rundocs |
numpy.testing.suppress_warnings.__call__ method testing.suppress_warnings.__call__(func)[source]
Function decorator to apply certain suppressions to a whole function. | numpy.reference.generated.numpy.testing.suppress_warnings.__call__ |
numpy.testing.suppress_warnings.filter method testing.suppress_warnings.filter(category=<class 'Warning'>, message='', module=None)[source]
Add a new suppressing filter or apply it if the state is entered. Parameters
categoryclass, optional
Warning class to filter
messagestring, optional
Regular expressio... | numpy.reference.generated.numpy.testing.suppress_warnings.filter |
numpy.testing.suppress_warnings.record method testing.suppress_warnings.record(category=<class 'Warning'>, message='', module=None)[source]
Append a new recording filter or apply it if the state is entered. All warnings matching will be appended to the log attribute. Parameters
categoryclass, optional
Warning... | numpy.reference.generated.numpy.testing.suppress_warnings.record |
numpy.ufunc.__call__ method ufunc.__call__(*args, **kwargs)
Call self as a function. | numpy.reference.generated.numpy.ufunc.__call__ |
numpy.ufunc.accumulate method ufunc.accumulate(array, axis=0, dtype=None, out=None)
Accumulate the result of applying the operator to all elements. For a one-dimensional array, accumulate produces results equivalent to: r = np.empty(len(A))
t = op.identity # op = the ufunc being applied to A's elements
for ... | numpy.reference.generated.numpy.ufunc.accumulate |
numpy.ufunc.at method ufunc.at(a, indices, b=None, /)
Performs unbuffered in place operation on operand ‘a’ for elements specified by ‘indices’. For addition ufunc, this method is equivalent to a[indices] += b, except that results are accumulated for elements that are indexed more than once. For example, a[[0,0]] +... | numpy.reference.generated.numpy.ufunc.at |
numpy.ufunc.identity attribute ufunc.identity
The identity value. Data attribute containing the identity element for the ufunc, if it has one. If it does not, the attribute value is None. Examples >>> np.add.identity
0
>>> np.multiply.identity
1
>>> np.power.identity
1
>>> print(np.exp.identity)
None | numpy.reference.generated.numpy.ufunc.identity |
numpy.ufunc.nargs attribute ufunc.nargs
The number of arguments. Data attribute containing the number of arguments the ufunc takes, including optional ones. Notes Typically this value will be one more than what you might expect because all ufuncs take the optional “out” argument. Examples >>> np.add.nargs
3
>>> np.... | numpy.reference.generated.numpy.ufunc.nargs |
numpy.ufunc.nin attribute ufunc.nin
The number of inputs. Data attribute containing the number of arguments the ufunc treats as input. Examples >>> np.add.nin
2
>>> np.multiply.nin
2
>>> np.power.nin
2
>>> np.exp.nin
1 | numpy.reference.generated.numpy.ufunc.nin |
numpy.ufunc.nout attribute ufunc.nout
The number of outputs. Data attribute containing the number of arguments the ufunc treats as output. Notes Since all ufuncs can take output arguments, this will always be (at least) 1. Examples >>> np.add.nout
1
>>> np.multiply.nout
1
>>> np.power.nout
1
>>> np.exp.nout
1 | numpy.reference.generated.numpy.ufunc.nout |
numpy.ufunc.ntypes attribute ufunc.ntypes
The number of types. The number of numerical NumPy types - of which there are 18 total - on which the ufunc can operate. See also numpy.ufunc.types
Examples >>> np.add.ntypes
18
>>> np.multiply.ntypes
18
>>> np.power.ntypes
17
>>> np.exp.ntypes
7
>>> np.remainder.ntypes... | numpy.reference.generated.numpy.ufunc.ntypes |
numpy.ufunc.outer method ufunc.outer(A, B, /, **kwargs)
Apply the ufunc op to all pairs (a, b) with a in A and b in B. Let M = A.ndim, N = B.ndim. Then the result, C, of op.outer(A, B) is an array of dimension M + N such that: \[C[i_0, ..., i_{M-1}, j_0, ..., j_{N-1}] = op(A[i_0, ..., i_{M-1}], B[j_0, ..., j_{N-1}... | numpy.reference.generated.numpy.ufunc.outer |
numpy.ufunc.reduce method ufunc.reduce(array, axis=0, dtype=None, out=None, keepdims=False, initial=<no value>, where=True)
Reduces array’s dimension by one, by applying ufunc along one axis. Let \(array.shape = (N_0, ..., N_i, ..., N_{M-1})\). Then \(ufunc.reduce(array, axis=i)[k_0, ..,k_{i-1}, k_{i+1}, .., k_{M-1... | numpy.reference.generated.numpy.ufunc.reduce |
numpy.ufunc.reduceat method ufunc.reduceat(array, indices, axis=0, dtype=None, out=None)
Performs a (local) reduce with specified slices over a single axis. For i in range(len(indices)), reduceat computes ufunc.reduce(array[indices[i]:indices[i+1]]), which becomes the i-th generalized “row” parallel to axis in the ... | numpy.reference.generated.numpy.ufunc.reduceat |
numpy.ufunc.signature attribute ufunc.signature
Definition of the core elements a generalized ufunc operates on. The signature determines how the dimensions of each input/output array are split into core and loop dimensions: Each dimension in the signature is matched to a dimension of the corresponding passed-in a... | numpy.reference.generated.numpy.ufunc.signature |
numpy.ufunc.types attribute ufunc.types
Returns a list with types grouped input->output. Data attribute listing the data-type “Domain-Range” groupings the ufunc can deliver. The data-types are given using the character codes. See also numpy.ufunc.ntypes
Examples >>> np.add.types
['??->?', 'bb->b', 'BB->B', 'hh-... | numpy.reference.generated.numpy.ufunc.types |
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