3

Are there alternative or better ways to convert a numpy matrix to a python array than this?

>>> import numpy
>>> import array
>>> b = numpy.matrix("1.0 2.0 3.0; 4.0 5.0 6.0", dtype="float16")
>>> print(b)
[[ 1. 2. 3.]
 [ 4. 5. 6.]]
>>> a = array.array("f")
>>> a.fromlist((b.flatten().tolist())[0])
>>> print(a)
array('f', [1.0, 2.0, 3.0, 4.0, 5.0, 6.0])
Divakar
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asked Aug 18, 2016 at 11:08

2 Answers 2

2

You could convert to a NumPy array and generate its flattened version with .ravel() or .flatten(). This could also be achieved by simply using the function np.ravel itself as it does both these takes under the hood. Finally, use array.array() on it, like so -

a = array.array('f',np.ravel(b))

Sample run -

In [107]: b
Out[107]: 
matrix([[ 1., 2., 3.],
 [ 4., 5., 6.]], dtype=float16)
In [108]: array.array('f',np.ravel(b))
Out[108]: array('f', [1.0, 2.0, 3.0, 4.0, 5.0, 6.0])
answered Aug 18, 2016 at 11:13
1

here is an example :

>>> x = np.matrix(np.arange(12).reshape((3,4))); x
matrix([[ 0, 1, 2, 3],
 [ 4, 5, 6, 7],
 [ 8, 9, 10, 11]])
>>> x.tolist()
[[0, 1, 2, 3], [4, 5, 6, 7], [8, 9, 10, 11]]
answered Aug 18, 2016 at 11:13

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