To return the outer product of two masked 1D arrays, use the ma.outer() method in Python Numpy. The first parameter is the input vector. Input is flattened if not already 1-dimensional. The second parameter is the second input vector. Input is flattened if not already 1-dimensional.A masked array is the ... Read More

To return the outer product of two 3D masked arrays, use the ma.outer() method in Python Numpy. The first parameter is the input vector. Input is flattened if not already 1-dimensional. The second parameter is the second input vector. Input is flattened if not already 1-dimensional.A masked array is the ... Read More

To return the outer product of two masked arrays, use the ma.outer() method in Python Numpy. The first parameter is the input vector. Input is flattened if not already 1-dimensional. The second parameter is the second input vector. Input is flattened if not already 1-dimensional.A masked array is the combination ... Read More

To mask rows and/or columns of a 2D array that contain masked values, use the np.ma.mask_rowcols() method in Numpy. The function returns a modified version of the input array, masked depending on the value of the axis parameter.Mask whole rows and/or columns of a 2D array that contain masked values. ... Read More

To compare and return True if an array is less than equal to another, use the numpy.char.less_equal() method in Python Numpy. The arr1 and arr2 are the two input string arrays of the same shape.Unlike numpy.less_equal, this comparison is performed by first stripping whitespace characters from the end of the ... Read More

To compute the bit-wise XOR of two 2D arrays element-wise, use the numpy.bitwise_xor() method in Python Numpy. Computes the bit-wise XOR of the underlying binary representation of the integers in the input arrays. This ufunc implements the C/Python operator ^.The 1st and 2nd parameter are the arrays, only integer and ... Read More

To check which element in a masked array is greater than the given value, use the ma.MaskedArray.__gt__() method. True is returned for every array element greater than the given value val. A masked array is the combination of a standard numpy.ndarray and a mask. A mask is either nomask, indicating ... Read More

To check which element in a masked array is less than or equal to a given value, use the ma.MaskedArray.__le__() method. Returns with boolean type i.e. True and False. A masked array is the combination of a standard numpy.ndarray and a mask. A mask is either nomask, indicating that no ... Read More

To check which element in a masked array is less than the given value, use the ma.MaskedArray.__lt__() method. Returns with boolean type i.e. True and False. 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 ... Read More

To return the variance of the masked array elements, use the ma.MaskedArray.var() in Numpy. The axis is set using the axis parameter. Returns the variance of the array elements, a measure of the spread of a distribution. The variance is computed for the flattened array by default, otherwise over the ... Read More