Say I have Numpy array p
and a Scipy sparse matrix q
such that
>>> p.shape
(10,)
>>> q.shape
(10,100)
I want to do a dot product of p and q. When I try with numpy I get the following:
>>> np.dot(p,q)
Traceback (most recent call last):
File "/usr/local/lib/python2.7/dist packages/IPython/core/interactiveshell.py", line 2883, in run_code
exec(code_obj, self.user_global_ns, self.user_ns)
File "<ipython-input-96-8260c6752ee5>", line 1, in <module>
np.dot(p,q)
ValueError: Cannot find a common data type.
I see in the Scipy documentation that
As of NumPy 1.7, np.dot is not aware of sparse matrices, therefore using it will result on unexpected results or errors. The corresponding dense matrix should be obtained first instead
But that defeats my purpose of using a sparse matrix. Soooo, how am I to do dot products between a sparse matrix and a 1D numpy array (numpy matrix, I am open to either) without losing the sparsity of my matrix?
I am using Numpy 1.8.2 and Scipy 0.15.1.