Programming Articles - Page 788 of 3363

To sort the masked array in-place, use the ma.MaskedArray.sort() method in Numpy. The axis parameter sets the axis along which to sort. The axis value is set 1.The method returns an array of the same type and shape as array. When the array is a structured array, the order parameter specifies which fields to compare first, second, and so on. This list does not need to include all of the fields.The endwith parameter, suggests whether missing values (if any) should be treated as the largest values (True) or the smallest values (False) When the array contains unmasked values sorting at ... Read More

To add each and every element of a masked array with a scalar value val, use the ma.MaskedArray.__add__() method. Returns the array with the value val added to every element. 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 ... Read More

To return the absolute value of a masked Array, use the ma.MaskedArray.__abs__() method. If the element is negative, the abs() method negates it and returns. 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 ... Read More

To check which element in a masked array is not equal to a given value, use the ma.MaskedArray.__ne__() method. True is returned for every array element not equal to a given value val. 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 ... Read More

To check which element in a masked array is equal to a given value, use the ma.MaskedArray.__eq__() method. True is returned for every array element equal to a given value val. 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 ... Read More

To check which element in a masked array is greater than or equal to a given value, use the ma.MaskedArray.__ge__() method. True is returned for every array element greater than or equal to a given value val. 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. ... Read More

To return the standard deviation of the masked array elements, use the ma.MaskedArray.std() in Numpy. The axis is set using the axis parameter. The axis is set to 0, for column axis.Returns the standard deviation, a measure of the spread of a distribution, of the array elements. The standard deviation is computed for the flattened array by default, otherwise over the specified axis.The axis parameter is the axis or axes along which the standard deviation is computed. The default is to compute the standard deviation of the flattened array. If this is a tuple of ints, a standard deviation is performed ... Read More

To return the standard deviation of the masked array elements, use the ma.MaskedArray.std() in Numpy. The axis is set using the axis parameter. The axis is set to 1, for row axis.Returns the standard deviation, a measure of the spread of a distribution, of the array elements. The standard deviation is computed for the flattened array by default, otherwise over the specified axis.The axis parameter is the axis or axes along which the standard deviation is computed. The default is to compute the standard deviation of the flattened array. If this is a tuple of ints, a standard deviation is ... Read More

To return the standard deviation of the masked array elements, use the ma.MaskedArray.std() in Numpy. The axis is set using the axis parameter.Returns the standard deviation, a measure of the spread of a distribution, of the array elements. The standard deviation is computed for the flattened array by default, otherwise over the specified axis.The axis parameter is the axis or axes along which the standard deviation is computed. The default is to compute the standard deviation of the flattened array. If this is a tuple of ints, a standard deviation is performed over multiple axes, instead of a single axis ... Read More

To return the standard deviation of the masked array elements, use the ma.MaskedArray.std() in Python Numpy. Returns the standard deviation, a measure of the spread of a distribution, of the array elements. The standard deviation is computed for the flattened array by default, otherwise over the specified axis.The axis parameter is the axis or axes along which the standard deviation is computed. The default is to compute the standard deviation of the flattened array. If this is a tuple of ints, a standard deviation is performed over multiple axes, instead of a single axis or all the axes as before.The ... Read More