def test_correctness_calcRlogRdotv(N=1000, K=10):
R = np.random.rand(N, K)
v = np.random.rand(N)
H1 = calcRlogRdotv_numpy(R, v)
H2 = calcRlogRdotv_cython(R, v)
H3 = calcRlogRdotv_numexpr(R, v)
H4 = calcRlogRdotv(R, v)
assert np.allclose(H1, H2)
assert np.allclose(H1, H3)
assert np.allclose(H1, H4)
def calcRlogRdotv(R, v, algVersion='cython'):
''' Computes R * log(R) and takes inner product with weight vector v.
Returns
--------
H : 1D array, size K
H[k] = inner(v, R[:,k] * log(R[:,k]))
'''
if hasCython and algVersion.count('cython'):
if R.ndim == 1:
return calcRlogRdotv_1D_cython(R, v)
else:
return calcRlogRdotv_cython(R, v)
elif hasNumexpr and algVersion.count('numexpr'):
return calcRlogRdotv_numexpr(R, v)
else:
return calcRlogRdotv_numpy(R, v)