To return array of indices of the minimum values, use the ma.MaskedArray.argmin() method in Numpy. The axis parameter is used to set the axis values. For axis, If None, the index is into the flattened array, otherwise along the specified axis. The out is the array into which the result can be placed. Its type is preserved and it must be of the right shape to hold the output.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 ... Read More

To return array of indices of the minimum values, use the ma.MaskedArray.argmin() method in Numpy. For axis, If None, the index is into the flattened array, otherwise along the specified axis. The out is the array into which the result can be placed. Its type is preserved and it must be of the right shape to hold the output.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 ... Read More

To return array of indices of the maximum values, use the ma.MaskedArray.argmax() method in Numpy. The axis parameter is used to set the axis values.For axis, If None, the index is into the flattened array, otherwise along the specified axis. The out is the array into which the result can be placed. Its type is preserved and it must be of the right shape to hold the output.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 ... Read More

To return array of indices of the maximum values, use the ma.MaskedArray.argmax() method in Numpy. The axis parameter is used to set the axis values.For axis, If None, the index is into the flattened array, otherwise along the specified axis. The out is the array into which the result can be placed. Its type is preserved and it must be of the right shape to hold the output.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 ... Read More

To return array of indices of the maximum values, use the ma.MaskedArray.argmax() method in Numpy. Masked values are treated as if they had the value "fill_value". The "fill_value" is a parameter i.e. Value used to fill in the masked values.For axis, If None, the index is into the flattened array, otherwise along the specified axis. The out is the array into which the result can be placed. Its type is preserved and it must be of the right shape to hold the output.A masked array is the combination of a standard numpy.ndarray and a mask. A mask is either nomask, indicating ... Read More

To return a view of the array with axes transposed in Python, use the ma.MaskedArray.transpose() method in Numpy. For a 1-D array this has no effect, as a transposed vector is simply the same vector. To convert a 1-D array into a 2D column vector, an additional dimension must be added. np.atleast2d(a).T achieves this, as does a[:, np.newaxis]. For a 2-D array, this is a standard matrix transpose.The axes can be, None or no argument − reverses the order of the axes.tuple of ints − i in the j-th place in the tuple means a’s i-th axis becomes a.transpose()’s j-th ... Read More

To return a view of the array with axes transposed, use the ma.MaskedArray.transpose() method in Numpy. For a 1-D array this has no effect, as a transposed vector is simply the same vector. To convert a 1-D array into a 2D column vector, an additional dimension must be added. np.atleast2d(a).T achieves this, as does a[:, np.newaxis]. For a 2-D array, this is a standard matrix transpose.The axes can be, None or no argument − reverses the order of the axes.tuple of ints − i in the j-th place in the tuple means a’s i-th axis becomes a.transpose()’s j-th axis.n ints ... Read More

To return a view of the array with axis1 and axis2 interchanged, use the ma.MaskedArray.swapaxes() method in Numpy.For NumPy >= 1.10.0, if a is an ndarray, then a view of a is returned; otherwise a new array is created. For earlier NumPy versions a view of a is returned only if the order of the axes is changed, otherwise the input array is returned.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 ... Read More

To remove axes of length one in Python, use the ma.MaskedArray.squeeze() method in Numpy. Returns the input array, but with all or a subset of the dimensions of length 1 removed. This is always a itself or a view into a. Note that if all axes are squeezed, the result is a 0d array and not a scalar.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 ... 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 order is set using the "order" parameter. The 'F' order determines whether the array data should be viewed as in FORTRAN i.e. F (column-major).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 ... Read More