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- numpy.ndarray.transpose
...Array objects The N-dimensional array (ndarray) numpy.ndarray numpy.ndarray.transpose...
- numpy.ndarray.transpose (Python method, in numpy.ndarray.transpose)
- Constants of the
numpy.mamodule - How to contribute to the NumPy documentation
...hich raises the bar. Test the waters by first presenting the fix as an issue. Some functions/objects like numpy.ndarray.transpose, numpy.array etc. defined in C-extension modules have their docstrings defined separately in _add_newdocs.py...
- Indexing on
ndarrays...nambiguous place to drop in the indexing subspace, thus it is tacked-on to the beginning. It is always possible to use .transpose() to move the subspace anywhere desired. Note that this example cannot be replicated using take. Example Slici...
- Internal organization of NumPy arrays
..., etc) but shares the same data bytes. Many operations in NumPy do just this such as slicing. Other operations, such as transpose, don’t move data elements around in the array, but rather change the information about the shape and strides s...
- NumPy 1.11.0 Release Notes
...viously, gemm BLAS operations were used for all matrix products. Now, if the matrix product is between a matrix and its transpose, it will use syrk BLAS operations for a performance boost. This optimization has been extended to @, numpy.dot...
- NumPy 1.24 Release Notes
...ctions. See below for the details, This release supports Python versions 3.8-3.11. Deprecations Deprecate fastCopyAndTranspose and PyArray_CopyAndTranspose The numpy.fastCopyAndTranspose function has been deprecated. Use the correspondin...
- NumPy 2.0.0 Release Notes
...enums, expired members and functions have been removed from the main namespace, such as: ERR_*, SHIFT_*, np.fastCopyAndTranspose, np.kernel_version, np.numarray, np.oldnumeric and np.set_numeric_ops. (gh-24316) Replaced from ... import *...
- NumPy C code explanations
...array but needs some care during setup. Deciding what case applies, checking broadcasting, and determining the kind of transposition needed are all done in PyArray_MapIterNew. After setting up, there are two cases. If there is no subarray...
- NumPy for MATLAB users
...with rows in reverse order a([1:end 1],:) a[np.r_[:len(a),0]] a with copy of the first row appended to the end a.' a.transpose() or a.T transpose of a a' a.conj().transpose() or a.conj().T conjugate transpose of a a * b a @ b matrix mu...
- NumPy quickstart
...ner, invert, lexsort, max, maximum, mean, median, min, minimum, nonzero, outer, prod, re, round, sort, std, sum, trace, transpose, var, vdot, vectorize, where Indexing, slicing and iterating One-dimensional arrays can be indexed, sliced...
- numpy.argwhere
...where N is the number of non-zero items. See also where, nonzero Notes np.argwhere(a) is almost the same as np.transpose(np.nonzero(a)), but produces a result of the correct shape for a 0D array. The output of argwhere is not suita...
- numpy.char.chararray.strides
...offset=sum(y.strides * np.array((1,1,1))) >>> offset/y.itemsize 17 >>> x = np.reshape(np.arange(5*6*7*8), (5,6,7,8)).transpose(2,3,1,0) >>> x.strides (32, 4, 224, 1344) >>> i = np.array([3,5,2,2]) >>> offset = sum(i * x.strides) >>> x[3,...
- numpy.char.chararray.transpose
...Legacy fixed-width string functionality numpy.char.chararray numpy.char.chararray.transpose...
- numpy.char.chararray.view
...', 'i1')]) Views that change the dtype size (bytes per entry) should normally be avoided on arrays defined by slices, transposes, fortran-ordering, etc.: >>> x = np.array([[1, 2, 3], [4, 5, 6]], dtype=np.int16) >>> y = x[:, ::2] >>> y arr...
- numpy.corrcoef
...s True (default), then each row represents a variable, with observations in the columns. Otherwise, the relationship is transposed: each column represents a variable, while the rows contain observations. bias_NoValue, optionalHas no effect...
- numpy.cov
...s True (default), then each row represents a variable, with observations in the columns. Otherwise, the relationship is transposed: each column represents a variable, while the rows contain observations. biasbool, optionalDefault normaliza...
- numpy.einsum
...dot, linalg.multi_dot einsumSimilar verbose interface is provided by the einops package to cover additional operations: transpose, reshape/flatten, repeat/tile, squeeze/unsqueeze and reductions. The opt_einsum optimizes contraction order fo...
- numpy.genfromtxt
...to upper case. If ‘lower’, field names are converted to lower case. unpackbool, optionalIf True, the returned array is transposed, so that arguments may be unpacked using x, y, z = genfromtxt(...). When used with a structured data-type, a...
- numpy.histogram2d
...togram2d(x, y, bins=(xedges, yedges)) >>> # Histogram does not follow Cartesian convention (see Notes), >>> # therefore transpose H for visualization purposes. >>> H = H.T imshow can only display square bins: >>> fig = plt.figure(figsize=...
- numpy.isfortran
...= np.array([[1, 2, 3], [4, 5, 6]], order='F') >>> b array([[1, 2, 3], [4, 5, 6]]) >>> np.isfortran(b) True The transpose of a C-ordered array is a FORTRAN-ordered array. >>> a = np.array([[1, 2, 3], [4, 5, 6]], order='C') >>> a arr...
- numpy.lib.stride_tricks.as_strided
- numpy.linalg.cholesky
- numpy.linalg.eigvals
- numpy.linalg.matrix_transpose
- numpy.linalg.qr
...arlier versions of numpy both it and the old default ‘full’ can be omitted. Note that array h returned in ‘raw’ mode is transposed for calling Fortran. The ‘economic’ mode is deprecated. The modes ‘full’ and ‘economic’ may be passed using...
- numpy.linalg.svd
- numpy.loadtxt
- numpy.ma.masked_array.mT
- numpy.ma.masked_array.nonzero
- numpy.ma.masked_array.strides
- numpy.ma.masked_array.transpose
- numpy.ma.masked_array.view
- numpy.ma.MaskedArray.nonzero
- numpy.ma.MaskedArray.strides
- numpy.ma.MaskedArray.transpose
- numpy.ma.MaskedArray.view
- numpy.ma.MaskType.transpose
- numpy.ma.nonzero
- numpy.matrix
- numpy.matrix.strides
- numpy.matrix.transpose
- numpy.matrix.view
- numpy.matrix_transpose
- numpy.memmap.strides
- numpy.memmap.transpose
- numpy.memmap.view
- numpy.moveaxis
- numpy.ndarray
- numpy.ndarray.mT
- numpy.ndarray.strides
- numpy.ndarray.T
- numpy.ndarray.transpose
- numpy.ndarray.view
- numpy.nonzero
- numpy.permute_dims
- numpy.polynomial.chebyshev.chebdomain
- numpy.polynomial.chebyshev.chebone
- numpy.polynomial.chebyshev.chebx
- numpy.polynomial.chebyshev.chebzero
- numpy.polynomial.hermite.hermdomain
- numpy.polynomial.hermite.hermone
- numpy.polynomial.hermite.hermx
- numpy.polynomial.hermite.hermzero
- numpy.polynomial.hermite_e.hermedomain
- numpy.polynomial.hermite_e.hermeone
- numpy.polynomial.hermite_e.hermex
- numpy.polynomial.hermite_e.hermezero
- numpy.polynomial.laguerre.lagdomain
- numpy.polynomial.laguerre.lagone
- numpy.polynomial.laguerre.lagx
- numpy.polynomial.laguerre.lagzero
- numpy.polynomial.legendre.legdomain
- numpy.polynomial.legendre.legone
- numpy.polynomial.legendre.legx
- numpy.polynomial.legendre.legzero
- numpy.polynomial.polynomial.polydomain