jax.numpy.abs

jax.numpy.abs(x)

Calculate the absolute value element-wise.

LAX-backend implementation of absolute(). Original docstring below.

absolute(x, /, out=None, *, where=True, casting=’same_kind’, order=’K’, dtype=None, subok=True[, signature, extobj])

np.abs is a shorthand for this function.

Parameters

x (array_like) – Input array.

Returns

absolute – An ndarray containing the absolute value of each element in x. For complex input, a + ib, the absolute value is \(\sqrt{ a^2 + b^2 }\). This is a scalar if x is a scalar.

Return type

ndarray

Examples

>>> x = np.array([-1.2, 1.2])
>>> np.absolute(x)
array([ 1.2,  1.2])
>>> np.absolute(1.2 + 1j)
1.5620499351813308

Plot the function over [-10, 10]:

>>> import matplotlib.pyplot as plt

>>> x = np.linspace(start=-10, stop=10, num=101)
>>> plt.plot(x, np.absolute(x))
>>> plt.show()

Plot the function over the complex plane:

>>> xx = x + 1j * x[:, np.newaxis]
>>> plt.imshow(np.abs(xx), extent=[-10, 10, -10, 10], cmap='gray')
>>> plt.show()