def test_vector_dist(exponent): rn = CudaFn(5) [xarr, yarr], [x, y] = noise_elements(rn, n=2) weight = _pos_vector(CudaFn(5)) weighting = CudaFnVectorWeighting(weight, exponent=exponent) if exponent in (1.0, float('inf')): true_dist = np.linalg.norm(weight.asarray() * (xarr - yarr), ord=exponent) else: true_dist = np.linalg.norm( weight.asarray() ** (1 / exponent) * (xarr - yarr), ord=exponent) if exponent == float('inf'): # Not yet implemented, should raise with pytest.raises(NotImplementedError): weighting.dist(x, y) else: assert almost_equal(weighting.dist(x, y), true_dist) # Same with free function pdist = cu_weighted_dist(weight, exponent=exponent) if exponent == float('inf'): # Not yet implemented, should raise with pytest.raises(NotImplementedError): pdist(x, y) else: assert almost_equal(pdist(x, y), true_dist)
def test_vector_dist(exponent): rn = CudaFn(5) [xarr, yarr], [x, y] = noise_elements(rn, n=2) weight = _pos_vector(CudaFn(5)) weighting = CudaFnArrayWeighting(weight, exponent=exponent) if exponent in (1.0, float('inf')): true_dist = np.linalg.norm(weight.asarray() * (xarr - yarr), ord=exponent) else: true_dist = np.linalg.norm(weight.asarray()**(1 / exponent) * (xarr - yarr), ord=exponent) if exponent == float('inf'): # Not yet implemented, should raise with pytest.raises(NotImplementedError): weighting.dist(x, y) else: assert almost_equal(weighting.dist(x, y), true_dist) # Same with free function pdist = cu_weighted_dist(weight, exponent=exponent) if exponent == float('inf'): # Not yet implemented, should raise with pytest.raises(NotImplementedError): pdist(x, y) else: assert almost_equal(pdist(x, y), true_dist)
def test_const_dist(exponent): rn = CudaFn(5) [xarr, yarr], [x, y] = noise_elements(rn, n=2) constant = 1.5 weighting = CudaFnConstWeighting(constant, exponent=exponent) factor = 1 if exponent == float('inf') else constant ** (1 / exponent) true_dist = factor * np.linalg.norm(xarr - yarr, ord=exponent) if exponent == float('inf'): # Not yet implemented, should raise with pytest.raises(NotImplementedError): weighting.dist(x, y) else: assert almost_equal(weighting.dist(x, y), true_dist) # Same with free function pdist = cu_weighted_dist(constant, exponent=exponent) if exponent == float('inf'): # Not yet implemented, should raise with pytest.raises(NotImplementedError): pdist(x, y) else: assert almost_equal(pdist(x, y), true_dist)
def test_const_dist(exponent): rn = CudaFn(5) [xarr, yarr], [x, y] = noise_elements(rn, n=2) constant = 1.5 weighting = CudaFnConstWeighting(constant, exponent=exponent) factor = 1 if exponent == float('inf') else constant**(1 / exponent) true_dist = factor * np.linalg.norm(xarr - yarr, ord=exponent) if exponent == float('inf'): # Not yet implemented, should raise with pytest.raises(NotImplementedError): weighting.dist(x, y) else: assert almost_equal(weighting.dist(x, y), true_dist) # Same with free function pdist = cu_weighted_dist(constant, exponent=exponent) if exponent == float('inf'): # Not yet implemented, should raise with pytest.raises(NotImplementedError): pdist(x, y) else: assert almost_equal(pdist(x, y), true_dist)