Programming Articles - Page 783 of 3363

Right Shift every element of a masked array by a given scalar value in Python

AmitDiwan
Updated on 07-Feb-2022 09:09:10

159 Views

Right Shift every element of a masked array by a given scalar value, use the ma.MaskedArray.__rshift__() 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

Left Shift a given scalar value by every element of a masked array in NumPy

AmitDiwan
Updated on 07-Feb-2022 09:00:56

199 Views

Left Shift a given scalar value by every element of a masked array, use the ma.MaskedArray.__rlshift__() 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

Left Shift every element of a masked array by a given scalar value in NumPy

AmitDiwan
Updated on 07-Feb-2022 08:55:25

277 Views

Left Shift every element of a masked array by a given scalar value, use the ma.MaskedArray.__lshift__() 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

Raise a given scalar value to each and every element of a masked array in NumPy

AmitDiwan
Updated on 07-Feb-2022 08:51:01

160 Views

To raise a given scalar value to each and every element of a masked array, use the ma.MaskedArray.__rpow__() 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, ... Read More

Compute the truth value of NOT an array element-wise based on conditions in Numpy

AmitDiwan
Updated on 05-Feb-2022 12:16:31

202 Views

To compute the truth value of NOT an array element-wise, use the numpy.logical_not() method in Python Numpy. Return value is either True or False. We have set a condition here.Return value is the boolean result with the same shape as x of the NOT operation on elements of x. This is a scalar if x is a scalar. The out is a location into which the result is stored. If provided, it must have a shape that the inputs broadcast to. If not provided or None, a freshly-allocated array is returned. A tuple (possible only as a keyword argument) must ... Read More

Compute the truth value of NOT an array element-wise in Numpy

AmitDiwan
Updated on 05-Feb-2022 12:13:38

375 Views

To compute the truth value of NOT an array element-wise, use the numpy.logical_not() method in Python Numpy. Return value is either True or False.Return value is the boolean result with the same shape as x of the NOT operation on elements of x. This is a scalar if x is a scalar. The out is a location into which the result is stored. If provided, it must have a shape that the inputs broadcast to. If not provided or None, a freshly-allocated array is returned. A tuple (possible only as a keyword argument) must have length equal to the number ... Read More

Compute the truth value of an array XOR another array element-wise based on conditions in Numpy

AmitDiwan
Updated on 05-Feb-2022 12:10:27

194 Views

To compute the truth value of an array XOR another array element-wise, use the numpy.logical_xor() method in Python Numpy. Return value is either True or False. We have set conditions here. Return value is the Boolean result of the logical XOR operation applied to the elements of x1 and x2; the shape is determined by broadcasting. This is a scalar if both x1 and x2 are scalars.The condition is 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. Note ... Read More

Apply accumulate for a multi-dimensional array along axis 1 in Numpy

AmitDiwan
Updated on 05-Feb-2022 12:04:29

274 Views

To Accumulate the result of applying the operator to all elements, use the numpy.accumulate() method in Python Numpy. For a multi-dimensional array, accumulate is applied along only one axis. We will apply along axis 1.The numpy.ufunc has functions that operate element by element on whole arrays. The ufuncs are written in C (for speed) and linked into Python with NumPy’s ufunc facility. A universal function (or ufunc for short) is a function that operates on ndarrays in an element-by-element fashion, supporting array broadcasting, type casting, and several other standard features. That is, a ufunc is a“vectorized” wrapper for a function ... Read More

Apply accumulate for a multi-dimensional array along an axis in Numpy

AmitDiwan
Updated on 05-Feb-2022 12:02:31

223 Views

To Accumulate the result of applying the operator to all elements, use the numpy.accumulate() method in Python Numpy. For a multi-dimensional array, accumulate is applied along only one axisThe numpy.ufunc has functions that operate element by element on whole arrays. The ufuncs are written in C (for speed) and linked into Python with NumPy’s ufunc facility.A universal function (or ufunc for short) is a function that operates on ndarrays in an element-byelement fashion, supporting array broadcasting, type casting, and several other standard features. That is, a ufunc is a “vectorized” wrapper for a function that takes a fixed number of ... Read More

Accumulate the result of applying the operator to all elements in Numpy

AmitDiwan
Updated on 05-Feb-2022 12:00:08

769 Views

To Accumulate the result of applying the operator to all elements, use the numpy.accumulate() method in Python Numpy. We have shown examples of add and multiple. The add.accumulate() is equivalent to np.cumsum().The numpy.ufunc has functions that operate element by element on whole arrays. The ufuncs are written in C (for speed) and linked into Python with NumPy’s ufunc facility.A universal function (or ufunc for short) is a function that operates on ndarrays in an element-byelement fashion, supporting array broadcasting, type casting, and several other standard features. That is, a ufunc is a “vectorized” wrapper for a function that takes a ... Read More

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