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- numpy.ma.masked_array.reshape
...numpy.ma.masked_array.reshape...
- numpy.ma.masked_array.reshape (Python method, in numpy.ma.masked_array.reshape)
- Constants of the
numpy.mamodule...ll_value, order]) Return the array data as a string containing the raw bytes in the array. Shape manipulation For reshape, resize, and transpose, the single tuple argument may be replaced with n integers which will be interpreted as a...
- NumPy 1.11.0 Release Notes
...ple ellipsis will raise IndexError, e.g., a[..., ...]. Non-integers used as index values will raise TypeError, e.g., in reshape, take, and specifying reduce axis. In a future release the following changes will be made. The rand function e...
- NumPy 1.12.0 Release Notes
...ith multiple ellipsis raises IndexError, e.g., a[..., ...]. Non-integers used as index values raise TypeError, e.g., in reshape, take, and specifying reduce axis. FutureWarning to changed behavior np.full now returns an array of the fil...
- NumPy 1.13.0 Release Notes
...). Calling expand_dims when the axis keyword does not satisfy -a.ndim - 1 <= axis <= a.ndim, where a is the array being reshaped, is deprecated. Future Changes Assignment between structured arrays with different field names will change...
- NumPy 1.23.0 Release Notes
...entation, and expire old deprecations. The highlights are: Implementation of loadtxt in C, greatly improving its performance. Exposing DLPack at the Python level for easy data exchange. Changes to the promotion and comparisons of structure...
- NumPy 1.25.0 Release Notes
...now possible to perform inplace matrix multiplication via the @= operator. >>> import numpy as np >>> a = np.arange(6).reshape(3, 2) >>> print(a) [[0 1] [2 3] [4 5]] >>> b = np.ones((2, 2), dtype=int) >>> a @= b >>> print(a) [[1 1] [5...
- NumPy 2.0.0 Release Notes
...construction is always np.take(unique, unique_inverse, axis=axis). When 2.0.0 needs to be supported, add unique_inverse.reshape(-1) to code. (gh-25553, gh-25570) any and all return booleans for object arrays The any and all functions and...
- NumPy 2.1.0 Release Notes
...so occur in code that releases the GIL; disabling the GIL only makes it easier to hit threading bugs. (gh-26157) numpy.reshape and numpy.ndarray.reshape now support shape and copy arguments. (gh-26292) NumPy now supports DLPack v1, suppor...
- numpy.average
...) >>> np.average(data) 2.5 >>> np.average(np.arange(1, 11), weights=np.arange(10, 0, -1)) 4.0 >>> data = np.arange(6).reshape((3, 2)) >>> data array([[0, 1], [2, 3], [4, 5]]) >>> np.average(data, axis=1, weights=[1./4, 3./4]...
- 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.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.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.append
...NumPy reference NumPy’s module structure Masked array operations numpy.ma.append...
- numpy.ma.apply_over_axes
...a function to 1-D slices of an array along the given axis. Examples >>> import numpy as np >>> a = np.ma.arange(24).reshape(2,3,4) >>> a[:,0,1] = np.ma.masked >>> a[:,1,:] = np.ma.masked >>> a masked_array( data=[[[0, --, 2, 3],...
- numpy.ma.argmax
...ape to hold the output. Returns: index_array{integer_array} Examples >>> import numpy as np >>> a = np.arange(6).reshape(2,3) >>> a.argmax() 5 >>> a.argmax(0) array([1, 1, 1]) >>> a.argmax(1) array([2, 2])...
- 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.array
...s np The mask can be initialized with an array of boolean values with the same shape as data. >>> data = np.arange(6).reshape((2, 3)) >>> np.ma.MaskedArray(data, mask=[[False, True, False], ... [False, False,...
- numpy.ma.asanyarray
...asarraySimilar to asanyarray, but does not conserve subclass. Examples >>> import numpy as np >>> x = np.arange(10.).reshape(2, 5) >>> x array([[0., 1., 2., 3., 4.], [5., 6., 7., 8., 9.]]) >>> np.ma.asanyarray(x) masked_array( d...
- numpy.ma.asarray
...also asanyarraySimilar to asarray, but conserves subclasses. Examples >>> import numpy as np >>> x = np.arange(10.).reshape(2, 5) >>> x array([[0., 1., 2., 3., 4.], [5., 6., 7., 8., 9.]]) >>> np.ma.asarray(x) masked_array( data...
- numpy.ma.atleast_1d
...data and the _mask, if any. Examples >>> import numpy as np >>> np.atleast_1d(1.0) array([1.]) >>> x = np.arange(9.0).reshape(3,3) >>> np.atleast_1d(x) array([[0., 1., 2.], [3., 4., 5.], [6., 7., 8.]]) >>> np.atleast_1d(x) i...
- numpy.ma.atleast_3d
...atleast_3d(3.0) array([[[3.]]]) >>> x = np.arange(3.0) >>> np.atleast_3d(x).shape (1, 3, 1) >>> x = np.arange(12.0).reshape(4,3) >>> np.atleast_3d(x).shape (4, 3, 1) >>> np.atleast_3d(x).base is x.base # x is a reshape, so not base its...
- numpy.ma.average
...., 3., 4.], mask=[False, False, True, True]) >>> np.ma.average(a, weights=[3, 1, 0, 0]) 1.25 >>> x = np.ma.arange(6.).reshape(3, 2) >>> x masked_array( data=[[0., 1.], [2., 3.], [4., 5.]], mask=False, fill_value=1e+2...
- numpy.ma.choose
...NumPy reference NumPy’s module structure Masked array operations numpy.ma.choose...
- numpy.ma.clump_masked
...NumPy reference NumPy’s module structure Masked array operations numpy.ma.clump_masked...
- numpy.ma.clump_unmasked
...NumPy reference NumPy’s module structure Masked array operations numpy.ma.clump_unmasked...
- numpy.ma.compress_cols
...he compressed array. See also compress_rowcols Examples >>> import numpy as np >>> a = np.ma.array(np.arange(9).reshape(3, 3), mask=[[1, 0, 0], ... [1, 0, 0], ......
- numpy.ma.compress_rowcols
...rns: compressed_arrayndarrayThe compressed array. Examples >>> import numpy as np >>> x = np.ma.array(np.arange(9).reshape(3, 3), mask=[[1, 0, 0], ... [1, 0, 0], ......
- numpy.ma.compress_rows
...he compressed array. See also compress_rowcols Examples >>> import numpy as np >>> a = np.ma.array(np.arange(9).reshape(3, 3), mask=[[1, 0, 0], ... [1, 0, 0], ......
- 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.corrcoef
...NumPy reference NumPy’s module structure Masked array operations numpy.ma.corrcoef...
- numpy.ma.correlate
...NumPy reference NumPy’s module structure Masked array operations numpy.ma.correlate...
- numpy.ma.count
..._maskedCount masked elements in array or along a given axis. Examples >>> import numpy.ma as ma >>> a = ma.arange(6).reshape((2, 3)) >>> a[1, :] = ma.masked >>> a masked_array( data=[[0, 1, 2], [--, --, --]], mask=[[False, Fa...
- numpy.ma.count_masked
...xis. See also MaskedArray.countCount non-masked elements. Examples >>> import numpy as np >>> a = np.arange(9).reshape((3,3)) >>> a = np.ma.array(a) >>> a[1, 0] = np.ma.masked >>> a[1, 2] = np.ma.masked >>> a[2, 1] = np.ma.masked >...
- numpy.ma.cov
...NumPy reference NumPy’s module structure Masked array operations numpy.ma.cov...
- numpy.ma.cumsum
...NumPy reference NumPy’s module structure Masked array operations numpy.ma.cumsum...
- numpy.ma.diag
...NumPy reference NumPy’s module structure Masked array operations numpy.ma.diag...
- numpy.ma.diff
...NumPy reference NumPy’s module structure Masked array operations numpy.ma.diff...
- numpy.ma.dot
...NumPy reference NumPy’s module structure Masked array operations numpy.ma.dot...
- numpy.ma.dstack
...(along third axis). This is equivalent to concatenation along the third axis after 2-D arrays of shape (M,N) have been reshaped to (M,N,1) and 1-D arrays of shape (N,) have been reshaped to (1,N,1). Rebuilds arrays divided by dsplit. This...
- numpy.ma.ediff1d
...NumPy reference NumPy’s module structure Masked array operations numpy.ma.ediff1d...
- numpy.ma.expand_dims
...a with the number of dimensions increased. See also squeezeThe inverse operation, removing singleton dimensions reshapeInsert, remove, and combine dimensions, and resize existing ones atleast_1d, atleast_2d, atleast_3d Examples >...
- numpy.ma.filled
...ay. See also compressed Examples >>> import numpy as np >>> import numpy.ma as ma >>> x = ma.array(np.arange(9).reshape(3, 3), mask=[[1, 0, 0], ... [1, 0, 0], ......
- numpy.ma.fix_invalid
...NumPy reference NumPy’s module structure Masked array operations numpy.ma.fix_invalid...
- numpy.ma.fromflex
...lexBuild a flexible-type array from a masked array. Examples >>> import numpy as np >>> x = np.ma.array(np.arange(9).reshape(3, 3), mask=[0] + [1, 0] * 4) >>> rec = x.toflex() >>> rec array([[(0, False), (1, True), (2, False)], [...
- 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.hsplit
...he function is applied to both the _data and the _mask, if any. Examples >>> import numpy as np >>> x = np.arange(16.0).reshape(4, 4) >>> x array([[ 0., 1., 2., 3.], [ 4., 5., 6., 7.], [ 8., 9., 10., 11.],...
- numpy.ma.in1d
...NumPy reference NumPy’s module structure Masked array operations numpy.ma.in1d...
- numpy.ma.indices
...indices array([[0, 1, 2], [0, 1, 2]]) The indices can be used as an index into an array. >>> x = np.arange(20).reshape(5, 4) >>> row, col = np.indices((2, 3)) >>> x[row, col] array([[0, 1, 2], [4, 5, 6]]) Note that it woul...
- numpy.ma.inner
...p.array([1,2,3]) >>> b = np.array([0,1,0]) >>> np.inner(a, b) 2 Some multidimensional examples: >>> a = np.arange(24).reshape((2,3,4)) >>> b = np.arange(4) >>> c = np.inner(a, b) >>> c.shape (2, 3) >>> c array([[ 14, 38, 62], [ 8...
- numpy.ma.innerproduct
...p.array([1,2,3]) >>> b = np.array([0,1,0]) >>> np.inner(a, b) 2 Some multidimensional examples: >>> a = np.arange(24).reshape((2,3,4)) >>> b = np.arange(4) >>> c = np.inner(a, b) >>> c.shape (2, 3) >>> c array([[ 14, 38, 62], [ 8...
- numpy.ma.intersect1d
...NumPy reference NumPy’s module structure Masked array operations numpy.ma.intersect1d...
- 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.isin
...NumPy reference NumPy’s module structure Masked array operations numpy.ma.isin...
- 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.left_shift
...NumPy reference NumPy’s module structure Masked array operations numpy.ma.left_shift...
- numpy.ma.mask_cols
...NumPy reference NumPy’s module structure Masked array operations numpy.ma.mask_cols...
- numpy.ma.mask_rowcols
...NumPy reference NumPy’s module structure Masked array operations numpy.ma.mask_rowcols...
- numpy.ma.mask_rows
...NumPy reference NumPy’s module structure Masked array operations numpy.ma.mask_rows...
- 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.all
...numpy.ma.masked_array.all...
- numpy.ma.masked_array.anom
...numpy.ma.masked_array.anom...
- numpy.ma.masked_array.any
...numpy.ma.masked_array.any...
- numpy.ma.masked_array.argmax
...ape to hold the output. Returns: index_array{integer_array} Examples >>> import numpy as np >>> a = np.arange(6).reshape(2,3) >>> a.argmax() 5 >>> a.argmax(0) array([1, 1, 1]) >>> a.argmax(1) array([2, 2])...
- numpy.ma.masked_array.argmin
...numpy.ma.masked_array.argmin...
- numpy.ma.masked_array.argpartition
...numpy.ma.masked_array.argpartition...
- numpy.ma.masked_array.argsort
...numpy.ma.masked_array.argsort...
- numpy.ma.masked_array.astype
...numpy.ma.masked_array.astype...
- numpy.ma.masked_array.base
...numpy.ma.masked_array.base...
- numpy.ma.masked_array.baseclass
...numpy.ma.masked_array.baseclass...
- numpy.ma.masked_array.byteswap
...numpy.ma.masked_array.byteswap...
- numpy.ma.masked_array.choose
...numpy.ma.masked_array.choose...
- numpy.ma.masked_array.clip
...numpy.ma.masked_array.clip...
- numpy.ma.masked_array.compress
...numpy.ma.masked_array.compress...
- numpy.ma.masked_array.compressed
...numpy.ma.masked_array.compressed...
- numpy.ma.masked_array.conj
...numpy.ma.masked_array.conj...
- numpy.ma.masked_array.conjugate
...numpy.ma.masked_array.conjugate...
- numpy.ma.masked_array.copy
...numpy.ma.masked_array.copy...
- numpy.ma.masked_array.count
..._maskedCount masked elements in array or along a given axis. Examples >>> import numpy.ma as ma >>> a = ma.arange(6).reshape((2, 3)) >>> a[1, :] = ma.masked >>> a masked_array( data=[[0, 1, 2], [--, --, --]], mask=[[False, Fa...
- numpy.ma.masked_array.ctypes
...numpy.ma.masked_array.ctypes...
- numpy.ma.masked_array.cumprod
...numpy.ma.masked_array.cumprod...
- numpy.ma.masked_array.cumsum
...numpy.ma.masked_array.cumsum...
- numpy.ma.masked_array.data
...numpy.ma.masked_array.data...
- numpy.ma.masked_array.device
...numpy.ma.masked_array.device...
- numpy.ma.masked_array.diagonal
...numpy.ma.masked_array.diagonal...
- numpy.ma.masked_array.dot
...numpy.ma.masked_array.dot...
- numpy.ma.masked_array.dtype
- numpy.ma.masked_array.dump
- numpy.ma.masked_array.dumps
- numpy.ma.masked_array.fill
- numpy.ma.masked_array.fill_value
- numpy.ma.masked_array.filled
- numpy.ma.masked_array.flags
- numpy.ma.masked_array.flat
- numpy.ma.masked_array.flatten
- numpy.ma.masked_array.get_fill_value
- numpy.ma.masked_array.get_imag
- numpy.ma.masked_array.get_real
- numpy.ma.masked_array.getfield
- numpy.ma.masked_array.harden_mask
- numpy.ma.masked_array.hardmask
- numpy.ma.masked_array.ids
- numpy.ma.masked_array.imag
- numpy.ma.masked_array.iscontiguous
- numpy.ma.masked_array.item
- numpy.ma.masked_array.itemset
- numpy.ma.masked_array.itemsize
- numpy.ma.masked_array.mask
- numpy.ma.masked_array.max
- numpy.ma.masked_array.mean
- numpy.ma.masked_array.min
- numpy.ma.masked_array.mT
- numpy.ma.masked_array.nbytes
- numpy.ma.masked_array.ndim
- numpy.ma.masked_array.newbyteorder
- numpy.ma.masked_array.nonzero
- numpy.ma.masked_array.partition
- numpy.ma.masked_array.prod
- numpy.ma.masked_array.product
- numpy.ma.masked_array.ptp
- numpy.ma.masked_array.put
- numpy.ma.masked_array.ravel
- numpy.ma.masked_array.real
- numpy.ma.masked_array.recordmask
- numpy.ma.masked_array.repeat
- numpy.ma.masked_array.reshape
- numpy.ma.masked_array.resize
- numpy.ma.masked_array.round
- numpy.ma.masked_array.searchsorted
- numpy.ma.masked_array.set_fill_value
- numpy.ma.masked_array.setfield
- numpy.ma.masked_array.setflags
- numpy.ma.masked_array.shape
- numpy.ma.masked_array.sharedmask
- numpy.ma.masked_array.shrink_mask
- numpy.ma.masked_array.size
- numpy.ma.masked_array.soften_mask
- numpy.ma.masked_array.sort
- numpy.ma.masked_array.squeeze
- numpy.ma.masked_array.std
- numpy.ma.masked_array.strides
- numpy.ma.masked_array.sum
- numpy.ma.masked_array.swapaxes
- numpy.ma.masked_array.T
- numpy.ma.masked_array.take
- numpy.ma.masked_array.to_device
- numpy.ma.masked_array.tobytes
- numpy.ma.masked_array.tofile
- numpy.ma.masked_array.toflex
- numpy.ma.masked_array.tolist
- numpy.ma.masked_array.torecords
- numpy.ma.masked_array.tostring
- numpy.ma.masked_array.trace
- numpy.ma.masked_array.transpose
- numpy.ma.masked_array.unshare_mask
- numpy.ma.masked_array.var
- numpy.ma.masked_array.view
- numpy.ma.masked_equal
- numpy.ma.masked_greater
- numpy.ma.masked_greater_equal
- numpy.ma.masked_inside
- numpy.ma.masked_invalid
- numpy.ma.masked_less
- numpy.ma.masked_less_equal
- numpy.ma.masked_not_equal
- numpy.ma.masked_object
- numpy.ma.masked_outside
- numpy.ma.masked_values
- numpy.ma.masked_where
- numpy.ma.MaskedArray.anom
- numpy.ma.MaskedArray.argmax
- numpy.ma.MaskedArray.argmin
- numpy.ma.MaskedArray.argsort
- numpy.ma.MaskedArray.compress
- numpy.ma.MaskedArray.count
- numpy.ma.MaskedArray.cumsum
- numpy.ma.MaskedArray.imag
- numpy.ma.MaskedArray.max
- numpy.ma.MaskedArray.mean
- numpy.ma.MaskedArray.min
- numpy.ma.MaskedArray.nonzero
- numpy.ma.MaskedArray.ptp
- numpy.ma.MaskedArray.put
- numpy.ma.MaskedArray.ravel
- numpy.ma.MaskedArray.real
- numpy.ma.MaskedArray.reshape
- numpy.ma.MaskedArray.round
- numpy.ma.MaskedArray.shape
- numpy.ma.MaskedArray.shrink_mask
- numpy.ma.MaskedArray.sort
- numpy.ma.MaskedArray.strides
- numpy.ma.MaskedArray.sum
- numpy.ma.MaskedArray.take
- numpy.ma.MaskedArray.toflex
- numpy.ma.MaskedArray.torecords
- numpy.ma.MaskedArray.transpose
- numpy.ma.MaskType.reshape
- numpy.ma.max
- numpy.ma.mean
- numpy.ma.median
- numpy.ma.min
- numpy.ma.mr_
- numpy.ma.ndenumerate
- numpy.ma.nonzero
- numpy.ma.notmasked_contiguous
- numpy.ma.notmasked_edges
- numpy.ma.ones_like
- numpy.ma.power
- numpy.ma.ptp
- numpy.ma.put
- numpy.ma.putmask
- numpy.ma.ravel
- numpy.ma.reshape
- numpy.ma.resize
- numpy.ma.right_shift
- numpy.ma.round
- numpy.ma.round_
- numpy.ma.set_fill_value
- numpy.ma.setdiff1d
- numpy.ma.setxor1d
- numpy.ma.sort
- numpy.ma.squeeze
- numpy.ma.sum
- numpy.ma.transpose
- numpy.ma.union1d
- numpy.ma.unique
- numpy.ma.vstack
- numpy.ma.where
- numpy.ma.zeros_like
- Standard array subclasses
- The
numpy.mamodule - Glossary
- Structured arrays