In Python, the absolute() method from the numpy module is used to find the absolute values of a NumPy array.
This method computes the absolute values of a complex array input. This is done element-wise.
Note: In Python, a list of lists can be used to generate a two-dimensional (2D) array.
numpy.absolute(arr,out=None, where=True,casting='same_kind', order='K', dtype=None,subok=True[, signature, extobj])
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<ufunc absolute'>)
arr: This represents the input array.
out: This specifies where the result is stored. This is an optional parameter.
where: This represents the condition in which the input gets broadcasted. This is an optional parameter.
casting: This specifies the kind of casting that is allowed. The value may be no, equiv, safe, same_kind, or unsafe. This is an optional parameter.
order: This defines the output array’s memory layout and calculation iteration order. Its default value is K.
C indicates that the output should be C-contiguous.F indicates that it should be F-contiguous.A indicates that it should be F-contiguous if the inputs are F-contiguous but not also C-contiguous. Otherwise, C-contiguous.K indicates that it should closely match the element ordering of the inputs.subok: If False is specified, it returns a strict array rather than a subtype. The default is True.
dtype: It modifies the DType of the output arrays. Its default value is None.
This method returns absolute values of an array.
Note: This function is abbreviated as
np.abs.
# import numpyimport numpy as np# create 2D array using np.arrayarr = np.array([[-7,-3.4,1.2 + 1j], [-2,3 + 1j,-9.5]])print('Abs Arr:', np.absolute(arr), sep='\n')print('Org Arr:', arr, sep='\n')print('Abs Arr:', np.absolute(arr, out=arr), sep='\n')print('Org Arr:', arr, sep='\n')
arr using the list of lists, which is then passed as an argument to the method np.array() to convert it to a numpy array.np.absolute() method to calculate the absolute values of the input array, arr.np.absolute() method to calculate the absolute values of the input array arr, but also store the results in the same array.