To XOR a given scalar value with every element of a masked array, use the ma.MaskedArray.__rxor__() method in Python Numpy. A masked array is the combination of a standard numpy.ndarray and a mask. A mask is either nomask, indicating that no value of the associated array is invalid, or an array of booleans that determines for each element of the associated array whether the value is valid or not.NumPy offers comprehensive mathematical functions, random number generators, linear algebra routines, Fourier transforms, and more. It supports a wide range of hardware and computing platforms, and plays well with distributed, GPU, and ... Read More

To XOR every element of a masked array by a given scalar value, use the ma.MaskedArray.__xor__() method in Python Numpy. A masked array is the combination of a standard numpy.ndarray and a mask. A mask is either nomask, indicating that no value of the associated array is invalid, or an array of booleans that determines for each element of the associated array whether the value is valid or not.NumPy offers comprehensive mathematical functions, random number generators, linear algebra routines, Fourier transforms, and more. It supports a wide range of hardware and computing platforms, and plays well with distributed, GPU, and ... Read More

To return a masked array containing the same data, but with a new shape, use the ma.MaskedArray.reshape() method in Numpy. Give a new shape to the array without changing its data. The new shape should be compatible with the original shape. If an integer is supplied, then the result will be a 1-D array of that length.The order determines whether the array data should be viewed as in C (row-major) or FORTRAN (column-major) order. Returns a masked array containing the same data, but with a new shape. The result is a view on the original array; if this is not ... Read More

To return a 1D version of self as a view, use the ma.MaskedArray.ravel() method in Numpy. The order is set using the "order" parameter, to read the elements using the index order. The ‘K’ means to read the elements in the order they occur in memory, except for reversing the data when strides are negative.The elements of a are read using this index order. ‘C’ means to index the elements in C-like order, with the last axis index changing fastest, back to the first axis index changing slowest. ‘F’ means to index the elements in Fortran-like index order, with the ... Read More

To return a 1D version of self as a view, use the ma.MaskedArray.ravel() method in Numpy. The order is set using the "order" parameter, to read the elements using the index order. The ‘F’ means to index the elements in Fortran-like index order.The elements of a are read using this index order. ‘C’ means to index the elements in C-like order, with the last axis index changing fastest, back to the first axis index changing slowest. ‘F’ means to index the elements in Fortran-like index order, with the first index changing fastest, and the last index changing slowest.The ‘C’ and ... Read More

To return a 1D version of self as a view, use the ma.MaskedArray.ravel() method in Numpy. The order is set using the "order" parameter, to read the elements using the index order. The‘C’ means to index the elements in C-like order, with the last axis index changing fastest, back to the first axis index changing slowest.The elements of a are read using this index order. ‘C’ means to index the elements in C-like order, with the last axis index changing fastest, back to the first axis index changing slowest. ‘F’ means to index the elements in Fortran-like index order, with ... Read More

To return a 1D version of self as a view in Python, use the ma.MaskedArray.ravel() method in Numpy.The elements of a are read using this index order. ‘C’ means to index the elements in C-like order, with the last axis index changing fastest, back to the first axis index changing slowest. ‘F’ means to index the elements in Fortran-like index order, with the first index changing fastest, and the last index changing slowest.The ‘C’ and ‘F’ options take no account of the memory layout of the underlying array, and only refer to the order of axis indexing. ‘A’ means to ... Read More

To return a copy of the array collapsed into one dimension, use the ma.MaskedArray.flatten() method in Numpy. The "order" parameter is used to flatter in order. The ‘K’ order means to flatten in the order the elements occur in memory. The order ‘C’ means to flatten in row-major (C-style) order. ‘F’ means to flatten in column-major (Fortran- style) order. ‘A’ means to flatten in column-major order if a is Fortran contiguous in memory, row-major order otherwise. ‘K’ means to flatten a in the order the elements occur in memory. The default is ‘C’.A masked array is the combination of a ... Read More

To return a copy of the array collapsed into one dimension, use the ma.MaskedArray.flatten() method in Numpy. The "order" parameter is used to flatter in order. The ‘F’ order means to flatten in column-major (Fortan-style) order.The order ‘C’ means to flatten in row-major (C-style) order. ‘F’ means to flatten in column-major (Fortran- style) order. ‘A’ means to flatten in column-major order if a is Fortran contiguous in memory, row-major order otherwise. ‘K’ means to flatten a in the order the elements occur in memory. The default is ‘C’.A masked array is the combination of a standard numpy.ndarray and a mask. ... Read More

To return a copy of the array collapsed into one dimension, use the ma.MaskedArray.flatten() method in Numpy. The "order" parameter is used to flatter in order. The ‘C’ order means to flatten in row-major (C-style) order.The order ‘C’ means to flatten in row-major (C-style) order. ‘F’ means to flatten in column-major (Fortran- style) order. ‘A’ means to flatten in column-major order if a is Fortran contiguous in memory, row-major order otherwise. ‘K’ means to flatten a in the order the elements occur in memory. The default is ‘C’.A masked array is the combination of a standard numpy.ndarray and a mask. ... Read More