def test_cudh_small_orthorhombic_triclinic(fixture_small_triclinic):
"""Test if the triclinic and orthorhombic implementations give the same answer for an orthorhombic box."""
n_atoms, n_bins, coords, box, histo_ref = fixture_small_triclinic
box_ort = get_orthorhombic_box()
box_tri = get_orthorhombic_triclinic_box()
for precision in ['single', 'double']:
for check_input in [True, False]:
for algo in [1, 2, 3]:
histo_ort = cudh.histograms(coords,
r_max,
n_bins,
box=box_ort,
force_triclinic=False,
precision=precision,
check_input=check_input,
algorithm=algo)
histo_tri = cudh.histograms(coords,
r_max,
n_bins,
box=box_tri,
force_triclinic=True,
precision=precision,
check_input=check_input,
algorithm=algo)
util.compare(histo_ort, histo_tri)
def test_cudh_invalid_small_single(fixture_small_invalid):
n_atoms, n_bins, coords, histo_ref = fixture_small_invalid
for gpu_id in range(cudh.get_num_devices()):
with pytest.raises(ValueError):
cudh.histograms(coords,
r_max,
n_bins,
precision="single",
gpu_id=gpu_id,
check_input=True)
def test_cudh_xlarge_single(fixture_xlarge):
n_atoms, n_bins, coords, histo_ref = fixture_xlarge
for gpu_id in range(cudh.get_num_devices()):
for algo in [1, 2, 3]:
histo_cudh = cudh.histograms(coords,
r_max,
n_bins,
precision="single",
gpu_id=gpu_id,
algorithm=algo)
util.compare(histo_ref, histo_cudh)
def test_cudh_medium_manybins_single(fixture_medium_manybins):
n_atoms, n_bins, coords, histo_ref = fixture_medium_manybins
for check_input in [True, False]:
for gpu_id in range(cudh.get_num_devices()):
for algo in [1, 2, 3]:
histo_cudh = cudh.histograms(coords,
r_max,
n_bins,
precision="single",
gpu_id=gpu_id,
check_input=check_input,
algorithm=algo)
util.compare(histo_ref, histo_cudh)
def test_cudh_small_triclinic(fixture_small_triclinic):
"""Check if pydh and cudh give the same answer with triclinic boxes."""
n_atoms, n_bins, coords, box, histo_ref = fixture_small_triclinic
for precision in ['single', 'double']:
for check_input in [True, False]:
for algo in [1, 2, 3]:
histo = cudh.histograms(coords,
r_max,
n_bins,
box=box,
precision=precision,
check_input=check_input,
algorithm=algo)
util.compare(histo_ref, histo)
def test_cudh_medium_scaled_single(fixture_medium):
n_atoms, n_bins, coords, histo_ref = fixture_medium
n_el = len(n_atoms)
scale_factors = np.ones(n_el * (n_el + 1) / 2)
scale_factors *= 0.5
for check_input in [True, False]:
for gpu_id in range(cudh.get_num_devices()):
for algo in [1, 2, 3]:
histo_cudh = cudh.histograms(coords,
r_max,
n_bins,
precision="single",
gpu_id=gpu_id,
scale_factors=scale_factors,
check_input=check_input,
algorithm=algo)
assert (histo_ref.sum() == 2.0 * histo_cudh.sum())
def test_cudh_medium_masked_single(fixture_medium):
n_atoms, n_bins, coords, histo_ref = fixture_medium
n_el = len(n_atoms)
mask_array = np.ones(n_el * (n_el + 1) / 2)
mask_array[::2] = 0
for check_input in [True, False]:
for gpu_id in range(cudh.get_num_devices()):
for algo in [1, 2, 3]:
histo_cudh = cudh.histograms(coords,
r_max,
n_bins,
precision="single",
gpu_id=gpu_id,
mask_array=mask_array,
check_input=check_input,
algorithm=algo)
col_sum = histo_cudh.sum(axis=0)
assert (np.sum(col_sum[1::2]) == 0)
# no box
box = []
# --- r_max, valid when coordinates are in a unit box
r_max = math.sqrt(3.0)
bap = get_bap()
t0 = time.time()
if run_values['kernel'] == "cudh":
xxxx = cudh.histograms(coords,
r_max,
run_values['bins'],
run_values['precision'],
gpu_id=gpu_id,
do_histo2_only=run_values['histo2'],
thread_block_x=run_values['thread_block_x'],
check_input=run_values['check_input'],
box=box,
algorithm=run_values['gpu_algorithm'],
verbose=True)
else:
xxxx = pydh.histograms(coords,
r_max,
run_values['bins'],
run_values['precision'],
check_input=run_values['check_input'],
do_histo2_only=run_values['histo2'],
n_threads=run_values['threads'],
blocksize=run_values['blocksize'],
box=box,
