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• Array iterator API

  ...PY_ITER_OVERLAP_ASSUME_ELEMENTWISE enabled are accessed only in the iterator order. This enables the iterator to reason about data dependency, possibly avoiding unnecessary copies. This flag has effect only if NPY_ITER_COPY_IF_OVERLAP is en...

• Constants of the numpy.ma module

  ...the array with the ctypes module. MaskedArray.dtype Data-type of the array's elements. MaskedArray.flags Information about the memory layout of the array. MaskedArray.itemsize Length of one array element in bytes. MaskedArray.nbytes To...

• Contributing to NumPy

  ...has a different level of experience, also NumPy is a pretty well-established project, so it’s hard to make assumptions about an ideal “first-time-contributor”. So, that’s why we don’t mark issues with the “good-first-issue” label. Instead,...

• CPU build options

  ...build --wheel -Csetup-args=-Dcpu-baseline="vsx2" Having issues with AVX512 features? You may have some reservations about including of AVX512 or any other CPU feature and you want to exclude from the dispatched features: python -m build...

• Data type classes (numpy.dtypes)

  ...py.dtypes) This module is home to specific dtypes related functionality and their classes. For more general information about dtypes, also see numpy.dtype and Data type objects (dtype). Similar to the builtin types module, this submodule de...

• Data type promotion in NumPy

  ...n. This step is referred to as promotion or finding the common dtype. In typical cases, the user does not need to worry about the details of promotion, since the promotion step usually ensures that the result will either match or exceed the...

• Data types

  ..., 3], dtype='d') array([1., 2., 3.], dtype=float64) See Specifying and constructing data types for more information about specifying and constructing data type objects, including how to specify parameters like the byte order. To convert...

• For downstream package authors

  ...is job, either all warnings or otherwise at least DeprecationWarning and FutureWarning. This gives you an early warning about changes in NumPy to adapt your code. If you want to test your own wheel builds against the latest NumPy nightly bu...

• How to contribute to the NumPy documentation

  ...explanations. Reporting defects is another way to contribute. We discuss both. Contributing fixes We’re eager to hear about and fix doc defects. But to attack the biggest problems we end up having to defer or overlook some bug reports. He...

• How to extend NumPy

  ...memory for an ndarray object (or one of it’s sub-classes). The easiest way to do this doesn’t require you to know much about the internals of NumPy. The method is to Ensure you are dealing with a well-behaved array (aligned, in machine by...

• How to write a NumPy how-to

  ...y. Tutorials are warm-fuzzy information; the user wants a feel for some aspect of NumPy (and again, may or may not care about deeper knowledge). We distinguish both tutorials and how-tos from Explanations, which are deep dives intended to g...

• Internal organization of NumPy arrays

  ...Internal organization of NumPy arrays It helps to understand a bit about how NumPy arrays are handled under the covers to help understand NumPy better. This section will not go into great...

• NumPy 1.13.0 Release Notes

  ...C long double floating point information In previous versions of 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 fai...

• NumPy 1.14.0 Release Notes

  ...ur. Compatibility notes The mask of a masked array view is also a view rather than a copy There was a FutureWarning about this change in NumPy 1.11.x. In short, it is now the case that, when changing a view of a masked array, changes to...

• NumPy 1.14.1 Release Notes

  ...issue with unicode input and py2 #10397: BUG: fix error message not formatted in einsum #10398: DOC: add documentation about how to handle new array printing #10403: BUG: Set einsum optimize parameter default to False. #10424: ENH: Fix rep...

• NumPy 1.16.0 Release Notes

  ...planned since numpy 1.7. Operations hitting this path have emitted FutureWarnings since then. Additional FutureWarnings about this change were added in 1.12. To help users update their code to account for these changes, a number of function...

• NumPy 1.17.0 Release Notes

  ...)], [Fraction(1, 3), Fraction(1, 2)]]) b = a @ a Changes median and percentile family of functions no longer warn about nan numpy.median, numpy.percentile, and numpy.quantile used to emit a RuntimeWarning when encountering an nan. Sin...

• NumPy 1.17.3 Release Notes

  ...515: BUG: Fix randint when range is 2**32 #14519: MAINT: remove the entropy c-extension module #14563: DOC: remove note about Pocketfft license file (non-existing here). #14578: BUG: random: Create a legacy implementation of random.binomial...

• NumPy 1.19.0 Release Notes

  ...rove the performance of np.exp with np.float64 input 5-7x faster than before. The _multiarray_umath.so module has grown about 63 KB on linux64. (gh-15648) Ability to disable madvise hugepages On Linux NumPy has previously added support fo...

• NumPy 1.19.2 Release Notes

  ...thon 3.0+ that use NumPy can now set the C macro NPY_NO_DEPRECATED_API=NPY_1_7_API_VERSION to avoid C compiler warnings about deprecated API usage. Contributors A total of 8 people contributed to this release. People with a “+” by their...

• NumPy 1.20.0 Release Notes

  ...generally a good replacement. For float and complex you can use float64 and complex128 if you wish to be more explicit about the precision. For np.int a direct replacement with np.int_ or int is also good and will not change behavior, but...

• NumPy 1.21.3 Release Notes

  ...elease that fixes a few bugs discovered after 1.21.2. It also provides 64 bit Python 3.10.0 wheels. Note a few oddities about Python 3.10: There are no 32 bit wheels for Windows, Mac, or Linux. The Mac Intel builds are only available in un...

• NumPy 1.23.0 Release Notes

  ...y want to convert a known NumPy scalar into a Python one using scalar.item(). (gh-21188) Faster np.kron numpy.kron is about 80% faster as the product is now computed using broadcasting. (gh-21354)...

• NumPy 1.24.1 Release Notes

  ...in delimiter in… #22848: BUG, SIMD: Fix the bitmask of the boolean comparison #22857: BLD: Help raspian arm + clang 13 about __builtin_mul_overflow #22858: API: Ensure a full mask is returned for masked_invalid #22866: BUG: Polynomials now...

• NumPy 1.25.0 Release Notes

  ...in behavior in this case, is when the array types are signed integers and scalar types are unsigned. If you are unsure about how to replace a use of scalar_types or when non-numeric dtypes are likely, please do not hesitate to open a NumPy...

• NumPy 1.6.2 Release Notes

  ...ke unique() return consistent index #1138: allow creating arrays from empty buffers or empty slices #1446: correct note about correspondence vstack and concatenate #1149: make argmin() work for datetime #1672: fix allclose() to work for sca...

• NumPy 1.7.0 Release Notes

  ...n optimized to use a different, optimized code path. This code path should produce the same results, but any feedback about changes to your code would be appreciated. Attempting to write to a read-only array (one with arr.flags.writeable...

• NumPy 1.8.0 Release Notes

  ...d simplifies numpy’s code internally. However, it may also break third-party libraries that make too-strong assumptions about the stride values of C- and F-contiguous arrays. (It is also currently known that this breaks Cython code using me...

• NumPy 2.0 migration guide
• NumPy 2.0.0 Release Notes

  ...s for macOS >=14, with significant performance improvements for linear algebra operations on macOS, and wheels that are about 3 times smaller, numpy.char fixed-length string operations have been accelerated by implementing ufuncs that also...

• NumPy 2.1.0 Release Notes

  ...as the first argument of bincount is now deprecated, because such inputs are silently cast to integers with no warning about loss of precision. (gh-27076) Expired deprecations Scalars and 0D arrays are disallowed for numpy.nonzero and...

• NumPy C code explanations
• NumPy for MATLAB users

  ...mport io, integrate, linalg, signal from scipy.sparse.linalg import cg, eigs Also assume below that if the Notes talk about “matrix” that the arguments are two-dimensional entities. General purpose equivalents MATLAB NumPy Notes hel...

• NumPy project governance and decision-making

  ...ofit entities. Summary NumPy is a community-owned and community-run project. To the maximum extent possible, decisions about project direction are made by community consensus (but note that “consensus” here has a somewhat technical meaning...

• NumPy security

  ...esource and its notes apply also to NumPy. NumPy’s maintainers are not security experts. However, we are conscientious about security and experts of both the NumPy codebase and how it’s used. Please do notify us before creating security ad...

• numpy.ascontiguousarray
• numpy.asfortranarray
• numpy.binary_repr
• numpy.broadcast_shapes
• numpy.char.chararray
• numpy.char.chararray.flags
• numpy.char.chararray.setflags
• numpy.datetime_data
• numpy.distutils.ccompiler_opt.CCompilerOpt.dist_info
• numpy.expm1
• numpy.fft.ifft
• numpy.finfo
• numpy.i: a SWIG interface file for NumPy
• numpy.iinfo
• numpy.info
• numpy.isreal
• numpy.lib.format
• numpy.lib.format.drop_metadata
• numpy.linalg.eig
• numpy.linalg.matrix_rank
• numpy.ma.masked_array.flags
• numpy.ma.masked_array.setflags
• numpy.ma.masked_array.tobytes
• numpy.ma.masked_array.var
• numpy.ma.MaskedArray.flags
• numpy.ma.MaskedArray.tobytes
• numpy.ma.MaskedArray.var
• numpy.ma.polyfit
• numpy.ma.var
• numpy.matrix
• numpy.matrix.flags
• numpy.matrix.setflags
• numpy.memmap.flags
• numpy.memmap.setflags
• numpy.ndarray
• numpy.ndarray.flags
• numpy.ndarray.setflags
• numpy.pad
• numpy.polyfit
• numpy.polynomial.chebyshev.chebfit
• numpy.polynomial.chebyshev.Chebyshev.fit
• numpy.polynomial.hermite.hermfit
• numpy.polynomial.hermite.Hermite.fit
• numpy.polynomial.hermite_e.hermefit
• numpy.polynomial.hermite_e.HermiteE.fit
• numpy.polynomial.laguerre.lagfit
• numpy.polynomial.laguerre.Laguerre.fit
• numpy.polynomial.legendre.Legendre.fit
• numpy.polynomial.legendre.legfit
• numpy.polynomial.polynomial.polyfit
• numpy.polynomial.polynomial.Polynomial.fit
• numpy.promote_types
• numpy.random.f
• numpy.random.Generator.f
• numpy.random.Generator.standard_t
• numpy.random.RandomState.f
• numpy.random.RandomState.set_state
• numpy.random.RandomState.standard_t
• numpy.random.set_state
• numpy.random.standard_t
• numpy.recarray
• numpy.recarray.flags
• numpy.recarray.setflags
• numpy.require
• numpy.show_runtime
• numpy.std
• numpy.var
• NumPy: the absolute basics for beginners
• Python types and C-structures
• Random Generator
• Releasing a version
• Standard array subclasses
• Status of numpy.distutils and migration advice
• Testing guidelines
• The numpy.ma module
• Typing (numpy.typing)
• Understanding Meson
• Using F2PY
• What is NumPy?
• Advanced debugging tools
• Array API
• Beyond the basics
• Bit generators
• Compatibility policy
• Compiler selection and customizing a build
• Copies and views
• Data type objects (dtype)
• Development workflow
• F2PY examples
• Indexing on ndarrays
• Iterating over arrays
• NpyString API