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# numpy.absolute

`numpy.``absolute`(x, /, out=None, *, where=True, casting='same_kind', order='K', dtype=None, subok=True[, signature, extobj]) = <ufunc 'absolute'>

  Calculate the absolute value element-wise.

  Parameters: | x : array_like Input array. out : ndarray, None, or tuple of ndarray and None, optional 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 of outputs. where : array_like, optional Values of True indicate to calculate the ufunc at that position, values of False indicate to leave the value in the output alone. **kwargs For other keyword-only arguments, see the ufunc docs.
  Returns: | absolute : ndarray An ndarray containing the absolute value of each element in x. For complex input, `a + ib`, the absolute value is .

  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()

  (Source code, png, pdf)

  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()

  (png, pdf)