numpy.absolute — NumPy v1.13 Manual (original) (raw)
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 theufunc docs. |
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| 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()
