To return the inner product of two masked arrays, use the ma.inner() method in Python Numpy. Ordinary inner product of vectors for 1-D arrays (without complex conjugation), in higher dimensions a sum product over the last axes.The out parameter suggests, if both the arrays are scalars or both 1-D arrays ... Read More

To append masked arrays along specific axis, use the ma.append() method in Python Numpy. The axis is set using the "axis" parameter. The values are appended to a copy of the first parameter array. These values are appended to a copy of first parameter array. It must be of the ... Read More

To join a sequence of masked arrays along specific axis, use the ma.stack() method in Python Numpy. The axis is set using the "axis" parameter. The axis parameter specifies the index of the new axis in the dimensions of the result. For example, if axis=0 it will be the first ... Read More

To join a sequence of masked arrays, use the ma.stack()  method in Python Numpy. The axis parameter specifies the index of the new axis in the dimensions of the result. For example, if axis=0 it will be the first dimension and if axis=-1 it will be the last dimension.The out ... Read More

To stack masked arrays in sequence vertically (row wise), use the ma.vstack() method in Python Numpy. This is equivalent to concatenation along the first axis after 1-D arrays of shape (N, ) have been reshaped to (1, N). Rebuilds arrays divided by vsplit.This function makes most sense for arrays with ... Read More

To stack masked arrays in sequence horizontally (column wise), use the ma.hstack() method in Python Numpy. his is equivalent to concatenation along the second axis, except for 1-D arrays where it concatenates along the first axis. Rebuilds arrays divided by hsplit.This function makes most sense for arrays with up to ... Read More

To stack masked arrays in sequence depth wise (along third axis), use the ma.dstack() method in Python Numpy. 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 ... Read More

To concatenate a sequence of masked arrays, use the ma.concatenate() method in Python Numpy. The axis is set using the "axis" parameter. Here, we have set axis 0.The parameters are the arrays that must have the same shape, except in the dimension corresponding to axis (the first, by default). The ... Read More

To concatenate a sequence of masked arrays, use the ma.concatenate() method in Python Numpy. The axis is set using the "axis" parameter.The parameters are the arrays that must have the same shape, except in the dimension corresponding to axis (the first, by default). The axis is the axis along which ... Read More

To concatenate a sequence of arrays, use the ma.concatenate() method in Python Numpy. The parameters are the arrays that must have the same shape, except in the dimension corresponding to axis (the first, by default). The axis is the axis along which the arrays will be joined. Default is 0. ... Read More