numpy.subtract(x1, x2, /, out=None, *, where=True, casting='same_kind', order='K', dtype=None, subok=True[, signature, extobj]) = <ufunc 'subtract'>
Subtract arguments, element-wise.
Parameters: |
x1, x2 : array_like The arrays to be subtracted from each other. 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 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. |
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Returns: |
y : ndarray The difference of |
Equivalent to x1 - x2
in terms of array broadcasting.
>>> np.subtract(1.0, 4.0) -3.0
>>> x1 = np.arange(9.0).reshape((3, 3)) >>> x2 = np.arange(3.0) >>> np.subtract(x1, x2) array([[ 0., 0., 0.], [ 3., 3., 3.], [ 6., 6., 6.]])
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https://docs.scipy.org/doc/numpy-1.14.2/reference/generated/numpy.subtract.html