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Found 26504 Articles for Server Side Programming

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To XOR every element of a masked array by a given scalar value, use the ma.MaskedArray.__ixor__() method in Python Numpy. Returns self^=value. 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, ... Read More

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To get the mod of every element of a masked Array with a scalar value, use the ma.MaskedArray.__imod__() 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, ... Read More

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To shift the bits of an integer to the right, use the numpy.right_shift() method in Python Numpy. Bits are shifted to the right x2. Because the internal representation of numbers is in binary format, this operation is equivalent to dividing x1 by 2**x2.The x1 is the Input values. The x2 is the number of bits to remove at the right of x1. If x1.shape != x2.shape, they must be broadcastable to a common shape.The function right_shift() returns x1 with bits shifted x2 times to the right. This is a scalar if both x1 and x2 are scalars.StepsAt first, import the ... Read More

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To compute the bit-wise XOR of two 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 boolean types are handled. If x1.shape != x2.shape, they must be broadcastable to a common shape.The where parameter is the condition broadcast over the input. At locations where the condition is True, the out array will be set to the ufunc result. Elsewhere, the out array will retain its original value. ... Read More

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To true divide each element of a masked Array by a scalar value in-place, use the ma.MaskedArray.__itruediv__() 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 More

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To compute the bit-wise XOR of a 1D and a 2D array 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 boolean types are handled. If x1.shape != x2.shape, they must be broadcastable to a common shape.StepsAt first, import the required library −import numpy as npCreating two numpy arrays using the array() method. We have inserted elements of int type −arr1 = np.array([32, 95, 82, 69, 38, 49]) arr2 ... Read More

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To add a scalar value with each element of a masked Array in-place, use the ma.MaskedArray.__iadd__() 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 sparse ... Read More

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To replace tab characters by a fixed tabsize in a string array, use the numpy.char.expandtabs() method in Python Numpy. The "tabsize" parameter is used to replace tabs with tabsize number of spaces. If not given defaults to 8 spaces.The function expandtabs() returns a copy of each string element where all tab characters are replaced by one or more spaces, depending on the current column and the given tabsize. The column number is reset to zero after each newline occurring in the string. This doesn’t understand other non-printing characters or escape sequences.The numpy.char module provides a set of vectorized string operations ... Read More

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To return a copy of each string element where all tab characters are replaced by spaces, use the numpy.char.expandtabs() method in Python Numpy. We can also set the "tabsize" parameter i.e. replace tabs with tabsize number of spaces. If not given defaults to 8 spaces.The function expandtabs() returns a copy of each string element where all tab characters are replaced by one or more spaces, depending on the current column and the given tabsize. The column number is reset to zero after each newline occurring in the string. This doesn’t understand other non-printing characters or escape sequences.The numpy.char module provides ... Read More

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To decode string array values that is already encoded, use the numpy.char.decode() method in Python Numpy. The "encoding" parameter sets the name of the encode used while encoding. The set of available codecs comes from the Python standard library, and may be extended at runtime. The type of the result will depend on the encoding specified.The numpy.char module provides a set of vectorized string operations for arrays of type numpy.str_ or numpy.bytes_.StepsAt first, import the required library −import numpy as npCreate a One-Dimensional array of string −arr = np.array(['Bella', 'Tom', 'John', 'Kate', 'Amy', 'Brad']) Displaying our array −print("Array...", arr)Get the ... Read More