Programming Articles - Page 770 of 3363

Reset the fill value of the masked array to default in Numpy

AmitDiwan
Updated on 08-Feb-2022 10:50:12

587 Views

To reset the fill value of the ma, use the ma.MaskedArray.fill_value() method in Python Numpy and set it to None.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

Get the fill value of the masked array in Numpy

AmitDiwan
Updated on 08-Feb-2022 10:48:06

769 Views

To get the fill value, use the ma.MaskedArray.get_fill_value() method in Python Numpy. The filling value of the masked array is 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 the value is valid or not.StepsAt first, import the required library −import numpy as np import numpy.ma as maCreate an array with int elements using the numpy.array() method −arr = np.array([[65, 68, 81], [93, 33, ... Read More

Force the mask to soften in Numpy

AmitDiwan
Updated on 08-Feb-2022 10:46:11

159 Views

To force the mask to hard, use the ma.MaskedArray.soften_mask() method. Whether the mask of a masked array is hard or soft is determined by its hardmask property. The soften_mask() sets hardmask to False.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 ... Read More

Compute the differences between consecutive elements and prepend numbers in Numpy

AmitDiwan
Updated on 08-Feb-2022 10:41:20

414 Views

To compute the differences between consecutive elements of a masked array, use the MaskedArray.ediff1d() method in Python Numpy. The "to_begin" parameter sets the number(s) to prepend at the beginning of the returned differences.This function is the equivalent of numpy.ediff1d that takes masked values into account, see numpy.ediff1d for details.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 notStepsAt first, import the ... Read More

Using XPATH to search text containing  

Debomita Bhattacharjee
Updated on 08-Feb-2022 10:47:25

16K+ Views

We can use the locator xpath to identify elements having search text with   or spaces. Let us first examine the html code of a web element having trailing and leading spaces. In the below image, the text JAVA BASICS with tagname strong has spaces as reflected in the html code.If an element has spaces in its text or in the value of any attribute, then to create an xpath for such an element we have to use the normalize-space function. It removes all the trailing and leading spaces from the string. It also removes every new tab or lines ... Read More

Compute the differences between consecutive elements of a masked array in Numpy

AmitDiwan
Updated on 08-Feb-2022 10:38:27

200 Views

To compute the differences between consecutive elements of a masked array, use the MaskedArray.ediff1d() method in Python Numpy. This function is the equivalent of numpy.ediff1d that takes masked values into account, see numpy.ediff1d for details.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.StepsAt first, import the required library −import numpy as npCreate an array with int elements using the numpy.array() ... Read More

Use an index array to construct a new array from a set of choices with wrap mode in Numpy

AmitDiwan
Updated on 08-Feb-2022 10:37:19

200 Views

A new array from the set of choices is constructed using the np.ma.choose() method. The mode parameter is set to 'wrap'. If mode='wrap', values greater than n-1 are mapped to n-1; and then the new array is constructed.Given an array of integers and a list of n choice arrays, this method will create a new array that merges each of the choice arrays. Where a value in index is i, the new array will have the value that choices[i] contains in the same place.The choices parameter is the choice arrays. The index array and all of the choices should be ... Read More

Force the mask to harden in Numpy

AmitDiwan
Updated on 08-Feb-2022 10:33:46

146 Views

To force the mask to hard, use the ma.MaskedArray.harden_mask() method. Whether the mask of a masked array is hard or soft is determined by its hardmask property. The harden_mask() sets hardmask to True. 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

Return the length of the masked array in Numpy

AmitDiwan
Updated on 08-Feb-2022 10:31:21

518 Views

To return the length of the masked array, use the ma.MaskedArray.__len__() 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 array libraries.StepsAt first, import ... Read More

Return a new array when dtype is different from the current dtype in Numpy

AmitDiwan
Updated on 08-Feb-2022 10:26:20

137 Views

To return a new array when dtype is different from the current dtype, use the ma.MaskedArray.__array__(dtype) method in Python Numpy. We have set the dtype parameter to be float. 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 ... Read More

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