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Page 2083 of 2547
XOR a given scalar value with every element of a masked array in Python
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 MoreXOR every element of a masked array by a given scalar value in Python
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 MoreReturn a masked array containing the same data but with a new shape in Numpy
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 MoreReturn a 1D version of self as a view in Numpy
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 MoreReturn a copy of the masked array collapsed into one dimension in the order the elements occur in memory in Numpy
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 MoreReturn a copy of the masked array collapsed into one dimension in column-major order in Numpy
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 MoreReturn a copy of the masked array collapsed into one dimension in row-major order in Numpy
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 MoreReturn a copy of the masked array collapsed into one dimension in Numpy
To return a copy of the array collapsed into one dimension, use the ma.MaskedArray.flatten() method in Numpy.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. A mask is either nomask, indicating that no value of the associated array is invalid, or an array of ...
Read MoreReturn range of values from the masked array for each row in Numpy
To return the range of values from a masked array, use the ma.MaskedArray.ptp() method in Numpy. Peak to peak (maximum - minimum) value along a given axis.The ptp() method returns a new array holding the result, unless out was specified, in which case a reference to out is returned.The axis parameter is the axis along which to find the peaks. If None (default) the flattened array is used. The out is a parameter, an alternative output array in which to place the result. It must have the same shape and buffer length as the expected output but the type will ...
Read MoreReturn range of values from a masked array for each column in Numpy
To return the range of values from a masked array, use the ma.MaskedArray.ptp() method in Numpy. Peak to peak (maximum - minimum) value along a given axis. The axis is set using the axis parameter.The ptp() method returns a new array holding the result, unless out was specified, in which case a reference to out is returned.The axis parameter is the axis along which to find the peaks. If None (default) the flattened array is used. The out is a parameter, an alternative output array in which to place the result. It must have the same shape and buffer length ...
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