def test_correctness_calcRlogR(N=1000, K=10):
R = np.random.rand(N, K)
H1 = calcRlogR_numpy_forloop(R)
H2 = calcRlogR_numpy_vectorized(R)
H3 = calcRlogR_cython(R)
H4 = calcRlogR_numexpr(R)
assert np.allclose(H1, H2)
assert np.allclose(H1, H3)
assert np.allclose(H1, H4)
def calcRlogR(R, algVersion='cython'):
''' Compute R * log(R), then sum along columns of result.
Returns
--------
H : 1D array, size K
H[k] = sum(R[:,k] * log(R[:,k]))
'''
if hasCython and algVersion.count('cython'):
if R.ndim == 1:
return calcRlogR_1D_cython(R)
else:
return calcRlogR_cython(R)
elif hasNumexpr and algVersion.count('numexpr'):
return calcRlogR_numexpr(R)
else:
return calcRlogR_numpy_vectorized(R)