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• numpy.ma.MaskedArray.diagonal

  ...Array objects Masked arrays Constants of the numpy.ma module numpy.ma.MaskedArray.diagonal...

• numpy.ma.MaskedArray.diagonal (Python method, in numpy.ma.MaskedArray.diagonal)
• Constants of the numpy.ma module

  ...ray from a set of choices. MaskedArray.compress(condition[, axis, out]) Return a where condition is True. MaskedArray.diagonal([offset, axis1, axis2]) Return specified diagonals. MaskedArray.fill(value) Fill the array with a scalar value...

• NumPy 1.10.0 Release Notes

  ...ises IndexError Using axis != 0 has raised a DeprecationWarning since NumPy 1.7, it now raises an error. np.ravel, np.diagonal and np.diag now preserve subtypes There was inconsistent behavior between x.ravel() and np.ravel(x), as well as...

• NumPy 1.11.0 Release Notes

  ...be used in all cases. np.trace now respects array subclasses This behaviour mimics that of other functions such as np.diagonal and ensures, e.g., that for masked arrays np.trace(ma) and ma.trace() give the same result. np.dot now raises...

• 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 1.12.1 Release Notes

  ...and OSX can be found on PyPI, Bugs Fixed BUG: Fix wrong future nat warning and equiv type logic error… BUG: Fix wrong masked median for some special cases DOC: Place np.average in inline code TST: Work around isfinite inconsistency on i38...

• NumPy 1.13.0 Release Notes

  ...viside function. New np.isin function, improves on in1d. New np.block function for creating blocked arrays. New PyArray_MapIterArrayCopyIfOverlap added to NumPy C-API. See below for details. Deprecations Calling np.fix, np.isposinf, and...

• 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 1.15.0 Release Notes

  ...NumPy 1.15.0 Release Notes NumPy 1.15.0 is a release with an unusual number of cleanups, many deprecations of old functions, and improvements to many existing functions. Please read the detailed descriptions b...

• 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 1.24 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 1.25.0 Release Notes

  ...are now MUSL wheels. Support the Fujitsu C/C++ compiler. Object arrays are now supported in einsum Support for inplace matrix multiplication (@=). We will be releasing a NumPy 1.26 when Python 3.12 comes out. That is needed because distut...

• 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

  ...k because, e.g., ‘1.9’ > ‘1.10’ is True. A NumpyVersion class has been added that can be used for such comparisons. The diagonal and diag functions will return writeable views in 1.10.0 The S and/or a dtypes may be changed to represent Pyth...

• NumPy 2.0.0 Release Notes

  ...perate on unicode or byte strings and are used in np.char. They operate similar to str.find and str.rfind. (gh-24868) diagonal and trace for numpy.linalg numpy.linalg.diagonal and numpy.linalg.trace have been added, which are array API st...

• 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.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.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.ma.append

  ...NumPy reference NumPy’s module structure Masked array operations numpy.ma.append...

• numpy.ma.arange

  ...NumPy reference NumPy’s module structure Masked array operations numpy.ma.arange...

• numpy.ma.argsort

  ...NumPy reference NumPy’s module structure Masked array operations numpy.ma.argsort...

• 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.average

  ...NumPy reference NumPy’s module structure Masked array operations numpy.ma.average...

• numpy.ma.clip

  ...NumPy reference NumPy’s module structure Masked array operations numpy.ma.clip...

• numpy.ma.common_fill_value

  ...NumPy reference NumPy’s module structure Masked array operations numpy.ma.common_fill_value...

• numpy.ma.compress_cols

  ...NumPy reference NumPy’s module structure Masked array operations numpy.ma.compress_cols...

• numpy.ma.compress_nd

  ...NumPy reference NumPy’s module structure Masked array operations numpy.ma.compress_nd...

• numpy.ma.compress_rowcols

  ...NumPy reference NumPy’s module structure Masked array operations numpy.ma.compress_rowcols...

• numpy.ma.compress_rows

  ...NumPy reference NumPy’s module structure Masked array operations numpy.ma.compress_rows...

• numpy.ma.compressed

  ...NumPy reference NumPy’s module structure Masked array operations numpy.ma.compressed...

• numpy.ma.concatenate

  ...NumPy reference NumPy’s module structure Masked array operations numpy.ma.concatenate...

• numpy.ma.convolve

  ...NumPy reference NumPy’s module structure Masked array operations numpy.ma.convolve...

• numpy.ma.correlate

  ...NumPy reference NumPy’s module structure Masked array operations numpy.ma.correlate...

• numpy.ma.count_masked

  ...NumPy reference NumPy’s module structure Masked array operations numpy.ma.count_masked...

• numpy.ma.cumprod

  ...NumPy reference NumPy’s module structure Masked array operations numpy.ma.cumprod...

• numpy.ma.cumsum

  ...NumPy reference NumPy’s module structure Masked array operations numpy.ma.cumsum...

• numpy.ma.diag

  ...numpy.ma.diag ma.diag(v, k=0)[source] Extract a diagonal or construct a diagonal array. This function is the equivalent of numpy.diag that takes masked values into acco...

• numpy.ma.diagflat

  ...diagflat = <numpy.ma.extras._fromnxfunction_single object> Create a two-dimensional array with the flattened input as a diagonal. Parameters: varray_likeInput data, which is flattened and set as the k-th diagonal of the output. kint, opt...

• numpy.ma.diff

  ...NumPy reference NumPy’s module structure Masked array operations numpy.ma.diff...

• numpy.ma.empty

  ...NumPy reference NumPy’s module structure Masked array operations numpy.ma.empty...

• numpy.ma.empty_like

  ...NumPy reference NumPy’s module structure Masked array operations numpy.ma.empty_like...

• numpy.ma.filled

  ...NumPy reference NumPy’s module structure Masked array operations numpy.ma.filled...

• numpy.ma.fix_invalid

  ...NumPy reference NumPy’s module structure Masked array operations numpy.ma.fix_invalid...

• numpy.ma.flatnotmasked_edges

  ...NumPy reference NumPy’s module structure Masked array operations numpy.ma.flatnotmasked_edges...

• numpy.ma.frombuffer

  ...NumPy reference NumPy’s module structure Masked array operations numpy.ma.frombuffer...

• numpy.ma.fromflex

  ...NumPy reference NumPy’s module structure Masked array operations numpy.ma.fromflex...

• numpy.ma.fromfunction

  ...NumPy reference NumPy’s module structure Masked array operations numpy.ma.fromfunction...

• numpy.ma.getdata

  ...NumPy reference NumPy’s module structure Masked array operations numpy.ma.getdata...

• numpy.ma.getmask

  ...NumPy reference NumPy’s module structure Masked array operations numpy.ma.getmask...

• numpy.ma.getmaskarray

  ...NumPy reference NumPy’s module structure Masked array operations numpy.ma.getmaskarray...

• numpy.ma.harden_mask

  ...NumPy reference NumPy’s module structure Masked array operations numpy.ma.harden_mask...

• numpy.ma.identity

  ...numpy.ma.core._convert2ma object> Return the identity array. The identity array is a square array with ones on the main diagonal. Parameters: nintNumber of rows (and columns) in n x n output. dtypedata-type, optionalData-type of the outp...

• numpy.ma.indices

  ...NumPy reference NumPy’s module structure Masked array operations numpy.ma.indices...

• numpy.ma.is_mask

  ...NumPy reference NumPy’s module structure Masked array operations numpy.ma.is_mask...

• numpy.ma.is_masked

  ...NumPy reference NumPy’s module structure Masked array operations numpy.ma.is_masked...

• numpy.ma.isarray

  ...NumPy reference NumPy’s module structure Masked array operations numpy.ma.isarray...

• numpy.ma.isMA

  ...NumPy reference NumPy’s module structure Masked array operations numpy.ma.isMA...

• numpy.ma.isMaskedArray

  ...NumPy reference NumPy’s module structure Masked array operations numpy.ma.isMaskedArray...

• numpy.ma.mask_rowcols

  ...NumPy reference NumPy’s module structure Masked array operations numpy.ma.mask_rowcols...

• numpy.ma.masked_all

  ...NumPy reference NumPy’s module structure Masked array operations numpy.ma.masked_all...

• numpy.ma.masked_all_like

  ...NumPy reference NumPy’s module structure Masked array operations numpy.ma.masked_all_like...

• numpy.ma.masked_array

  ...NumPy reference NumPy’s module structure Masked array operations numpy.ma.masked_array...

• numpy.ma.masked_array.argsort

  ...numpy.ma.masked_array.argsort...

• numpy.ma.masked_array.compress

  ...numpy.ma.masked_array.compress...

• numpy.ma.masked_array.compressed

  ...numpy.ma.masked_array.compressed...

• numpy.ma.masked_array.cumprod

  ...numpy.ma.masked_array.cumprod...

• numpy.ma.masked_array.cumsum

  ...numpy.ma.masked_array.cumsum...

• numpy.ma.masked_array.diagonal
• numpy.ma.masked_array.filled

  ...numpy.ma.masked_array.filled...

• numpy.ma.masked_array.get_imag

  ...numpy.ma.masked_array.get_imag...

• numpy.ma.masked_array.get_real

  ...numpy.ma.masked_array.get_real...

• numpy.ma.masked_array.harden_mask
• numpy.ma.masked_array.hardmask
• numpy.ma.masked_array.imag
• numpy.ma.masked_array.mT
• numpy.ma.masked_array.ptp
• numpy.ma.masked_array.ravel
• numpy.ma.masked_array.real
• numpy.ma.masked_array.soften_mask
• numpy.ma.masked_array.take
• numpy.ma.masked_array.tobytes
• numpy.ma.masked_array.trace
• numpy.ma.masked_array.view
• numpy.ma.masked_equal
• numpy.ma.masked_object
• numpy.ma.masked_values
• numpy.ma.masked_where
• numpy.ma.MaskedArray.__abs__
• numpy.ma.MaskedArray.__add__
• numpy.ma.MaskedArray.__and__
• numpy.ma.MaskedArray.__array__
• numpy.ma.MaskedArray.__array_priority__
• numpy.ma.MaskedArray.__array_wrap__
• numpy.ma.MaskedArray.__bool__
• numpy.ma.MaskedArray.__contains__
• numpy.ma.MaskedArray.__copy__
• numpy.ma.MaskedArray.__deepcopy__
• numpy.ma.MaskedArray.__delitem__
• numpy.ma.MaskedArray.__div__
• numpy.ma.MaskedArray.__divmod__
• numpy.ma.MaskedArray.__eq__
• numpy.ma.MaskedArray.__float__
• numpy.ma.MaskedArray.__floordiv__
• numpy.ma.MaskedArray.__ge__
• numpy.ma.MaskedArray.__getitem__
• numpy.ma.MaskedArray.__getstate__
• numpy.ma.MaskedArray.__gt__
• numpy.ma.MaskedArray.__iadd__
• numpy.ma.MaskedArray.__iand__
• numpy.ma.MaskedArray.__idiv__
• numpy.ma.MaskedArray.__ifloordiv__
• numpy.ma.MaskedArray.__ilshift__
• numpy.ma.MaskedArray.__imod__
• numpy.ma.MaskedArray.__imul__
• numpy.ma.MaskedArray.__int__
• numpy.ma.MaskedArray.__ior__
• numpy.ma.MaskedArray.__ipow__
• numpy.ma.MaskedArray.__irshift__
• numpy.ma.MaskedArray.__isub__
• numpy.ma.MaskedArray.__itruediv__
• numpy.ma.MaskedArray.__ixor__
• numpy.ma.MaskedArray.__le__
• numpy.ma.MaskedArray.__len__
• numpy.ma.MaskedArray.__lshift__
• numpy.ma.MaskedArray.__lt__
• numpy.ma.MaskedArray.__mod__
• numpy.ma.MaskedArray.__mul__
• numpy.ma.MaskedArray.__ne__
• numpy.ma.MaskedArray.__new__
• numpy.ma.MaskedArray.__or__
• numpy.ma.MaskedArray.__pow__
• numpy.ma.MaskedArray.__radd__
• numpy.ma.MaskedArray.__rand__
• numpy.ma.MaskedArray.__rdivmod__
• numpy.ma.MaskedArray.__reduce__
• numpy.ma.MaskedArray.__repr__
• numpy.ma.MaskedArray.__rfloordiv__
• numpy.ma.MaskedArray.__rlshift__
• numpy.ma.MaskedArray.__rmod__
• numpy.ma.MaskedArray.__rmul__
• numpy.ma.MaskedArray.__ror__
• numpy.ma.MaskedArray.__rpow__
• numpy.ma.MaskedArray.__rrshift__
• numpy.ma.MaskedArray.__rshift__
• numpy.ma.MaskedArray.__rsub__
• numpy.ma.MaskedArray.__rtruediv__
• numpy.ma.MaskedArray.__rxor__
• numpy.ma.MaskedArray.__setitem__
• numpy.ma.MaskedArray.__setmask__
• numpy.ma.MaskedArray.__setstate__
• numpy.ma.MaskedArray.__str__
• numpy.ma.MaskedArray.__sub__
• numpy.ma.MaskedArray.__truediv__
• numpy.ma.MaskedArray.__xor__
• numpy.ma.MaskedArray.all
• numpy.ma.MaskedArray.anom
• numpy.ma.MaskedArray.any
• numpy.ma.MaskedArray.argmax
• numpy.ma.MaskedArray.argmin
• numpy.ma.MaskedArray.argsort
• numpy.ma.MaskedArray.astype
• numpy.ma.MaskedArray.base
• numpy.ma.MaskedArray.byteswap
• numpy.ma.MaskedArray.choose
• numpy.ma.MaskedArray.clip
• numpy.ma.MaskedArray.compress
• numpy.ma.MaskedArray.compressed
• numpy.ma.MaskedArray.conj
• numpy.ma.MaskedArray.conjugate
• numpy.ma.MaskedArray.copy
• numpy.ma.MaskedArray.count
• numpy.ma.MaskedArray.ctypes
• numpy.ma.MaskedArray.cumprod
• numpy.ma.MaskedArray.cumsum
• numpy.ma.MaskedArray.diagonal
• numpy.ma.MaskedArray.dtype
• numpy.ma.MaskedArray.dump
• numpy.ma.MaskedArray.dumps
• numpy.ma.MaskedArray.fill
• numpy.ma.MaskedArray.filled
• numpy.ma.MaskedArray.flags
• numpy.ma.MaskedArray.flat
• numpy.ma.MaskedArray.flatten
• numpy.ma.MaskedArray.get_fill_value
• numpy.ma.MaskedArray.harden_mask
• numpy.ma.MaskedArray.ids
• numpy.ma.MaskedArray.imag
• numpy.ma.MaskedArray.iscontiguous
• numpy.ma.MaskedArray.item
• numpy.ma.MaskedArray.itemsize
• numpy.ma.MaskedArray.max
• numpy.ma.MaskedArray.mean
• numpy.ma.MaskedArray.min
• numpy.ma.MaskedArray.nbytes
• numpy.ma.MaskedArray.ndim
• numpy.ma.MaskedArray.nonzero
• numpy.ma.MaskedArray.prod
• numpy.ma.MaskedArray.product
• numpy.ma.MaskedArray.ptp
• numpy.ma.MaskedArray.put
• numpy.ma.MaskedArray.ravel