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- numpy.ma.power
...NumPy reference NumPy’s module structure Masked array operations numpy.ma.power...
- numpy.emath.power (Python function, in numpy.emath.power)
- numpy.lib.scimath.power (Python function, in numpy.lib.scimath.power)
- numpy.ma.power (Python function, in numpy.ma.power)
numpy.polynomial...nomial A sub-package for efficiently dealing with polynomials. Within the documentation for this sub-package, a “finite power series,” i.e., a polynomial (also referred to simply as a “series”) is represented by a 1-D numpy array of the pol...
- Array creation
...vander(x, n) defines a Vandermonde matrix as a 2D NumPy array. Each column of the Vandermonde matrix is a decreasing power of the input 1D array or list or tuple, x where the highest polynomial order is n-1. This array creation routine i...
- Array iterator API
...uffersize is zero, a default buffer size is used, otherwise it specifies how big of a buffer to use. Buffers which are powers of 2 such as 4096 or 8192 are recommended. Returns NULL if there is an error, otherwise returns the allocated ite...
- Constants of the
numpy.mamodule...f, value). MaskedArray.__rdivmod__(value, /) Return divmod(value, self). MaskedArray.__pow__(other) Raise self to the power other, masking the potential NaNs/Infs MaskedArray.__rpow__(other) Raise other to the power self, masking the pot...
- CPU build options
...tures. I’m facing the same case above but with ppc64 architecture Then raise the ceiling of the baseline features to Power8: python -m build --wheel -Csetup-args=-Dcpu-baseline="vsx2" Having issues with AVX512 features? You may have...
- Data types
...c types may cause overflow errors when a value requires more memory than available in the data type. For example, numpy.power evaluates 100 ** 9 correctly for 64-bit integers, but gives -1486618624 (incorrect) for a 32-bit integer. >>> np.p...
- Discrete Fourier Transform (
numpy.fft)...t. When the input a is a time-domain signal and A = fft(a), np.abs(A) is its amplitude spectrum and np.abs(A)**2 is its power spectrum. The phase spectrum is obtained by np.angle(A). The inverse DFT is defined as \[a_m = \frac{1}{n}\sum_{k...
- How to contribute to the NumPy documentation
...urce is a community effort. Do your best – we’ll help fix issues. Images and real-life data make text more engaging and powerful, but be sure what you use is appropriately licensed and available. Here again, even a rough idea for artwork ca...
- Interoperability with NumPy
...ns on array-structured data and a concrete implementation of the API based on strided in-RAM storage. While this API is powerful and fairly general, its concrete implementation has limitations. As datasets grow and NumPy becomes used in a v...
- NumPy 1.10.0 Release Notes
...omization. np.cbrt to compute cube root for real floats np.cbrt wraps the C99 cube root function cbrt. Compared to np.power(x, 1./3.) it is well defined for negative real floats and a bit faster. numpy.distutils now allows parallel comp...
- NumPy 1.10.2 Release Notes
...is_fortran(a), that was using PyArray_ISFORTRAN to check for Fortran contiguity instead of PyArray_IS_F_CONTIGUOUS. You may want to regenerate swigged files using the updated numpy.i Deprecate views changing dimensions in fortran order Th...
- NumPy 1.10.4 Release Notes
...dows binaries. Compatibility notes The trace function now calls the trace method on subclasses of ndarray, except for matrix, for which the current behavior is preserved. This is to help with the units package of AstroPy and hopefully wil...
- NumPy 1.11.0 Release Notes
...2 - 3.5 and contains a number of enhancements and improvements. Note also the build system changes listed below as they may have subtle effects. No Windows (TM) binaries are provided for this release due to a broken toolchain. One of the pr...
- NumPy 1.11.1 Release Notes
...several build related improvements. Wheels for Linux, Windows, and OSX can be found on PyPI. Fixes Merged #7506 BUG: Make sure numpy imports on python 2.6 when nose is unavailable. #7530 BUG: Floating exception with invalid axis in np.le...
- NumPy 1.11.2 Release Notes
...ound on PyPI. Pull Requests Merged Fixes overridden by later merges and release notes updates are omitted. #7736 BUG: Many functions silently drop ‘keepdims’ kwarg. #7738 ENH: Add extra kwargs and update doc of many MA methods. #7778 DOC:...
- NumPy 1.12.0 Release Notes
...g if the argument is a subclass of ndarray, as the subclass will be preserved starting in 1.13. (see Future Changes) power and ** raise errors for integer to negative integer powers The previous behavior depended on whether numpy scalar...
- NumPy 1.12.1 Release Notes
...n BUG: Fix undefined behaviour induced by bad __array_wrap__ BUG: Fix MaskedArray.__setitem__ BUG: PPC64el machines are POWER for Fortran in f2py BUG: Look up methods on MaskedArray in _frommethod BUG: Remove extra digit in binary_repr at l...
- NumPy 1.13.0 Release Notes
...f NumPy, the finfo function returned invalid information about the double double format of the longdouble float type on Power PC (PPC). The invalid values resulted from the failure of the NumPy algorithm to deal with the variable number of...
- NumPy 1.14.0 Release Notes
...tains a large number of bug fixes and new features, along with several changes with potential compatibility issues. The major change that users will notice are the stylistic changes in the way numpy arrays and scalars are printed, a change...
- NumPy 1.14.3 Release Notes
...lease. People with a “+” by their names contributed a patch for the first time. Allan Haldane Charles Harris Jonathan March + Malcolm Smith + Matti Picus Pauli Virtanen Pull requests merged A total of 8 pull requests were merged for th...
- NumPy 1.14.6 Release Notes
...fix release for bugs reported following the 1.14.5 release. The most significant fixes are: Fix for behavior change in ma.masked_values(shrink=True) Fix the new cached allocations machinery to be thread safe. The Python versions supported...
- NumPy 1.15.0 Release Notes
...esult is stored in its place, hence the overlap is safe. Avoiding the copy results in faster execution. linalg.matrix_power can now handle stacks of matrices Like other functions in linalg, matrix_power can now deal with arrays of dimensi...
- NumPy 1.16.0 Release Notes
...a ufunc. This provides better performance and allows overriding with __array_ufunc__. Improved support for the ARM and POWER architectures. Improved support for AIX and PyPy. Improved interop with ctypes. Improved support for PEP 3118....
- NumPy 1.18.0 Release Notes
...r numpy.random has been defined and documented. Basic infrastructure for linking with 64 bit BLAS and LAPACK libraries. Many documentation improvements. New functions Multivariate hypergeometric distribution added to numpy.random The me...
- NumPy 1.20.2 Release Notes
...NumPy 1.20.2 Release Notes NumPy 1.20.2 is a bugfix release containing several fixes merged to the main branch after the NumPy 1.20.1 release. Contributors A total of 7 people contributed to this release. People with...
- NumPy 1.22.0 Release Notes
...tes NumPy 1.22.0 is a big release featuring the work of 153 contributors spread over 609 pull requests. There have been many improvements, highlights are: Annotations of the main namespace are essentially complete. Upstream is a moving tar...
- NumPy 1.23.0 Release Notes
...worrying whether ndarray is their superclass or not. The actual call remains a no-op. (gh-20766) Add support for VSX4/Power10 With VSX4/Power10 enablement, the new instructions available in Power ISA 3.1 can be used to accelerate some Num...
- NumPy 1.24 Release Notes
...ired deprecations due to changes in promotion and cleanups. This might be called a deprecation release. Highlights are Many new deprecations, check them out. Many expired deprecations, New F2PY features and fixes. New “dtype” and “casting”...
- NumPy 1.24.1 Release Notes
...NumPy 1.24.1 Release Notes NumPy 1.24.1 is a maintenance release that fixes bugs and regressions discovered after the 1.24.0 release. The Python versions supported b...
- NumPy 1.25.0 Release Notes
...es that it contains no __slots__, ensuring that subclasses can now make use of this feature in Python. (gh-23113) Fix power of complex zero np.power now returns a different result for 0^{non-zero} for complex numbers. Note that the value...
- NumPy 1.4.0 Release Notes
...e new chebyshev module. The most noticeable difference to most will be that coefficients are specified from low to high power, that the low level functions do not work with the Chebyshev and Polynomial classes as arguments, and that the Che...
- NumPy 1.6.0 Release Notes
...time dtype support to deal with dates in arrays. A new 16-bit floating point type. A new iterator, which improves performance of many functions. New features New 16-bit floating point type This release adds support for the IEEE 754-2008...
- NumPy 1.7.2 Release Notes
...umber of array elements gh-2485: Fix for astype(‘S’) string truncate issue gh-3312: bug in count_nonzero gh-2684: numpy.ma.average casts complex to float under certain conditions gh-2403: masked array with named components does not behave a...
- NumPy 1.9.0 Release Notes
...NumPy 1.9.0 Release Notes This release supports Python 2.6 - 2.7 and 3.2 - 3.4. Highlights Numerous performance improvements in various areas, most notably indexing and operations on small arrays are significantly faster. Inde...
- NumPy 1.9.2 Release Notes
...elease in the 1.9.x series. Issues fixed #5316: fix too large dtype alignment of strings and complex types #5424: fix ma.median when used on ndarrays #5481: Fix astype for structured array fields of different byte order #5354: fix segfaul...
- NumPy 2.0.0 Release Notes
...NumPy 2.0.0 Release Notes NumPy 2.0.0 is the first major release since 2006. It is the result of 11 months of development since the last feature release and is the work of...
- NumPy 2.0.1 Release Notes
...NumPy 2.0.1 Release Notes NumPy 2.0.1 is a maintenance release that fixes bugs and regressions discovered after the 2.0.0 release. NumPy 2.0.1 is the last planned...
- NumPy 2.1.0 Release Notes
...opt-out of this change. If you are experiencing problems due to an upstream header including NumPy, the solution is to make sure you #include "numpy/ndarrayobject.h" before their header and import NumPy yourself based on including-the-c-a...
- NumPy project governance and decision-making
...rs with all other Contributors and the Community. In these everyday activities, Council Members do not have any special power or privilege through their membership on the Council. However, it is expected that because of the quality and quan...
- numpy.arange
....arange produces numpy.int32 or numpy.int64 numbers. This may result in incorrect results for large integer values: >>> power = 40 >>> modulo = 10000 >>> x1 = [(n ** power) % modulo for n in range(8)] >>> x2 = [(n ** power) % modulo for n i...
- numpy.array_repr
...numpy.array_repr numpy.array_repr(arr, max_line_width=None, precision=None, suppress_small=None)[source] Return the string representation of an array. Paramet...
- numpy.average
...ption, the result will broadcast correctly against the original a. Note: keepdims will not work with instances of numpy.matrix or other classes whose methods do not support keepdims. New in version 1.23.0. Returns: retval, [sum_of_wei...
- numpy.blackman
...t as good (by some measures) as the kaiser window. References Blackman, R.B. and Tukey, J.W., (1958) The measurement of power spectra, Dover Publications, New York. Oppenheim, A.V., and R.W. Schafer. Discrete-Time Signal Processing. Upper S...
- numpy.concat
...NumPy reference Routines and objects by topic Array manipulation routines numpy.concat...
- numpy.concatenate
...NumPy reference Routines and objects by topic Array manipulation routines numpy.concatenate...
- numpy.emath.power
...NumPy’s module structure Mathematical functions with automatic domain numpy.emath.power...
- numpy.exp2
.... **kwargsFor other keyword-only arguments, see the ufunc docs. Returns: outndarray or scalarElement-wise 2 to the power x. This is a scalar if x is a scalar. See also power Examples >>> import numpy as np >>> np.exp2([2, 3]) a...
- numpy.fft.fft
...(DFT) can be calculated efficiently, by using symmetries in the calculated terms. The symmetry is highest when n is a power of 2, and the transform is therefore most efficient for these sizes. The DFT is defined, with the conventions used...
- numpy.finfo
...eps. maxfloating point number of the appropriate typeThe largest representable number. maxexpintThe smallest positive power of the base (2) that causes overflow. minfloating point number of the appropriate typeThe smallest representable...
- numpy.float_power
...NumPy reference Routines and objects by topic Mathematical functions numpy.float_power...
- numpy.hamming
...of the sampled signal) or tapering function. References [1] Blackman, R.B. and Tukey, J.W., (1958) The measurement of power spectra, Dover Publications, New York. [2] E.R. Kanasewich, “Time Sequence Analysis in Geophysics”, The Universi...
- numpy.hanning
...of the sampled signal) or tapering function. References [1] Blackman, R.B. and Tukey, J.W., (1958) The measurement of power spectra, Dover Publications, New York. [2] E.R. Kanasewich, “Time Sequence Analysis in Geophysics”, The Universi...
- numpy.i: a SWIG interface file for NumPy
...numpy.i: a SWIG interface file for NumPy Introduction The Simple Wrapper and Interface Generator (or SWIG) is a powerful tool for generating wrapper code for interfacing to a wide variety of scripting languages. SWIG can parse heade...
- numpy.lib.scimath
...plane: >>> import math >>> np.emath.log(-math.exp(1)) == (1+1j*math.pi) True Similarly, sqrt, other base logarithms, power and trig functions are correctly handled. See their respective docstrings for specific examples. Functions arcc...
- numpy.lib.scimath.power
...umPy’s module structure Lib module (numpy.lib) numpy.lib.scimath numpy.lib.scimath.power...
- numpy.linalg.matrix_power
...ference NumPy’s module structure Linear algebra (numpy.linalg) numpy.linalg.matrix_power...
- numpy.logspace
...source] Return numbers spaced evenly on a log scale. In linear space, the sequence starts at base ** start (base to the power of start) and ends with base ** stop (see endpoint below). Changed in version 1.25.0: Non-scalar ‘base` is now su...
- numpy.ma.all
...NumPy reference NumPy’s module structure Masked array operations numpy.ma.all...
- numpy.ma.allclose
...NumPy reference NumPy’s module structure Masked array operations numpy.ma.allclose...
- numpy.ma.allequal
...NumPy reference NumPy’s module structure Masked array operations numpy.ma.allequal...
- numpy.ma.amax
...NumPy reference NumPy’s module structure Masked array operations numpy.ma.amax...
- numpy.ma.amin
...NumPy reference NumPy’s module structure Masked array operations numpy.ma.amin...
- numpy.ma.anom
...NumPy reference NumPy’s module structure Masked array operations numpy.ma.anom...
- numpy.ma.anomalies
...NumPy reference NumPy’s module structure Masked array operations numpy.ma.anomalies...
- numpy.ma.any
...NumPy reference NumPy’s module structure Masked array operations numpy.ma.any...
- numpy.ma.append
...NumPy reference NumPy’s module structure Masked array operations numpy.ma.append...
- numpy.ma.apply_along_axis
...NumPy reference NumPy’s module structure Masked array operations numpy.ma.apply_along_axis...
- numpy.ma.apply_over_axes
...NumPy reference NumPy’s module structure Masked array operations numpy.ma.apply_over_axes...
- numpy.ma.arange
....arange produces numpy.int32 or numpy.int64 numbers. This may result in incorrect results for large integer values: >>> power = 40 >>> modulo = 10000 >>> x1 = [(n ** power) % modulo for n in range(8)] >>> x2 = [(n ** power) % modulo for n i...
- numpy.ma.argmax
...NumPy reference NumPy’s module structure Masked array operations numpy.ma.argmax...
- numpy.ma.argmin
...NumPy reference NumPy’s module structure Masked array operations numpy.ma.argmin...
- numpy.ma.argsort
...NumPy reference NumPy’s module structure Masked array operations numpy.ma.argsort...
- numpy.ma.around
...NumPy reference NumPy’s module structure Masked array operations numpy.ma.around...
- numpy.ma.array
...NumPy reference NumPy’s module structure Masked array operations numpy.ma.array...
- numpy.ma.asanyarray
...NumPy reference NumPy’s module structure Masked array operations numpy.ma.asanyarray...
- numpy.ma.asarray
...NumPy reference NumPy’s module structure Masked array operations numpy.ma.asarray...
- numpy.ma.atleast_1d
...NumPy reference NumPy’s module structure Masked array operations numpy.ma.atleast_1d...
- numpy.ma.atleast_2d
...NumPy reference NumPy’s module structure Masked array operations numpy.ma.atleast_2d...
- numpy.ma.atleast_3d
...NumPy reference NumPy’s module structure Masked array operations numpy.ma.atleast_3d...
- numpy.ma.average
...NumPy reference NumPy’s module structure Masked array operations numpy.ma.average...
- numpy.ma.choose
- numpy.ma.clip
...NumPy reference NumPy’s module structure Masked array operations numpy.ma.clip...
- numpy.ma.clump_masked
- numpy.ma.clump_unmasked
- numpy.ma.column_stack
- numpy.ma.common_fill_value
- numpy.ma.compress_cols
- numpy.ma.compress_nd
- numpy.ma.compress_rowcols
- numpy.ma.compress_rows
- numpy.ma.compressed
- numpy.ma.concatenate
- numpy.ma.conjugate
- numpy.ma.convolve
- numpy.ma.copy
- numpy.ma.corrcoef
- numpy.ma.correlate
- numpy.ma.count
- numpy.ma.count_masked
- numpy.ma.cov
- numpy.ma.cumprod
- numpy.ma.cumsum
- numpy.ma.default_fill_value
- numpy.ma.diag
- numpy.ma.diagflat
- numpy.ma.diff
- numpy.ma.dot
- numpy.ma.dstack
- numpy.ma.ediff1d
- numpy.ma.empty
- numpy.ma.empty_like
- numpy.ma.expand_dims
- numpy.ma.filled
- numpy.ma.fix_invalid
- numpy.ma.flatnotmasked_contiguous
- numpy.ma.flatnotmasked_edges
- numpy.ma.flatten_mask
- numpy.ma.flatten_structured_array
- numpy.ma.frombuffer
- numpy.ma.fromflex
- numpy.ma.fromfunction
- numpy.ma.getdata
- numpy.ma.getmask
- numpy.ma.getmaskarray
- numpy.ma.harden_mask
- numpy.ma.hsplit
- numpy.ma.hstack
- numpy.ma.identity
- numpy.ma.in1d
- numpy.ma.indices
- numpy.ma.inner
- numpy.ma.innerproduct
- numpy.ma.intersect1d
- numpy.ma.is_mask
- numpy.ma.is_masked
- numpy.ma.isarray
- numpy.ma.isin
- numpy.ma.isMA
- numpy.ma.isMaskedArray
- numpy.ma.left_shift
- numpy.ma.make_mask
- numpy.ma.make_mask_descr
- numpy.ma.make_mask_none
- numpy.ma.mask_cols
- numpy.ma.mask_or
- numpy.ma.mask_rowcols
- numpy.ma.mask_rows
- numpy.ma.masked_all
- numpy.ma.masked_all_like
- numpy.ma.masked_array
- numpy.ma.masked_array.all
- numpy.ma.masked_array.anom
- numpy.ma.masked_array.any
- numpy.ma.masked_array.argmax
- numpy.ma.masked_array.argmin
- numpy.ma.masked_array.argpartition
- numpy.ma.masked_array.argsort
- numpy.ma.masked_array.astype
- numpy.ma.masked_array.base
- numpy.ma.masked_array.baseclass
- numpy.ma.masked_array.byteswap
- numpy.ma.masked_array.choose
- numpy.ma.masked_array.clip
- numpy.ma.masked_array.compress
- numpy.ma.masked_array.compressed
- numpy.ma.masked_array.conj
- numpy.ma.masked_array.conjugate