numpy.polynomial.polyutils.as_series(alist, trim=True)
[source]
Return argument as a list of 1-d arrays.
The returned list contains array(s) of dtype double, complex double, or object. A 1-d argument of shape (N,)
is parsed into N
arrays of size one; a 2-d argument of shape (M,N)
is parsed into M
arrays of size N
(i.e., is “parsed by row”); and a higher dimensional array raises a Value Error if it is not first reshaped into either a 1-d or 2-d array.
Parameters: |
alist : array_like A 1- or 2-d array_like trim : boolean, optional When True, trailing zeros are removed from the inputs. When False, the inputs are passed through intact. |
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Returns: |
[a1, a2,…] : list of 1-D arrays A copy of the input data as a list of 1-d arrays. |
Raises: |
ValueError Raised when |
>>> from numpy.polynomial import polyutils as pu >>> a = np.arange(4) >>> pu.as_series(a) [array([ 0.]), array([ 1.]), array([ 2.]), array([ 3.])] >>> b = np.arange(6).reshape((2,3)) >>> pu.as_series(b) [array([ 0., 1., 2.]), array([ 3., 4., 5.])]
>>> pu.as_series((1, np.arange(3), np.arange(2, dtype=np.float16))) [array([ 1.]), array([ 0., 1., 2.]), array([ 0., 1.])]
>>> pu.as_series([2, [1.1, 0.]]) [array([ 2.]), array([ 1.1])]
>>> pu.as_series([2, [1.1, 0.]], trim=False) [array([ 2.]), array([ 1.1, 0. ])]
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https://docs.scipy.org/doc/numpy-1.14.2/reference/generated/numpy.polynomial.polyutils.as_series.html