def test(cmdline_overrides=[]):
tc = _Test()
tc.create_models(cmdline_overrides)
reflections = tc.generate_reflections()
# use a ReflectionManager to exclude reflections too close to the spindle,
# plus set the frame numbers
from dials.algorithms.refinement.reflection_manager import ReflectionManager
refman = ReflectionManager(reflections, tc.experiments, outlier_detector=None)
refman.finalise()
# create prediction parameterisation of the requested type
pred_param = ScanVaryingPredictionParameterisation(
tc.experiments,
[tc.det_param],
[tc.s0_param],
[tc.xlo_param],
[tc.xluc_param],
[tc.gon_param],
)
# keep only those reflections that pass inclusion criteria and have predictions
reflections = refman.get_matches()
# get analytical gradients
pred_param.compose(reflections)
an_grads = pred_param.get_gradients(reflections)
# get finite difference gradients
p_vals = pred_param.get_param_vals()
p_names = pred_param.get_param_names()
deltas = [1.0e-7] * len(p_vals)
for i, delta in enumerate(deltas):
val = p_vals[i]
p_vals[i] -= delta / 2.0
pred_param.set_param_vals(p_vals)
pred_param.compose(reflections)
tc.ref_predictor(reflections)
rev_state = reflections["xyzcal.mm"].deep_copy()
p_vals[i] += delta
pred_param.set_param_vals(p_vals)
pred_param.compose(reflections)
tc.ref_predictor(reflections)
fwd_state = reflections["xyzcal.mm"].deep_copy()
p_vals[i] = val
fd = fwd_state - rev_state
x_grads, y_grads, phi_grads = fd.parts()
x_grads /= delta
y_grads /= delta
phi_grads /= delta
try:
for (a, b) in zip(x_grads, an_grads[i]["dX_dp"]):
assert a == pytest.approx(b, abs=1e-5)
for (a, b) in zip(y_grads, an_grads[i]["dY_dp"]):
assert a == pytest.approx(b, abs=1e-5)
for (a, b) in zip(phi_grads, an_grads[i]["dphi_dp"]):
assert a == pytest.approx(b, abs=1e-5)
except AssertionError:
print("Failure for {}".format(p_names[i]))
raise
# return to the initial state
pred_param.set_param_vals(p_vals)
pred_param.compose(reflections)
def __call__(self, cmdline_overrides):
self.create_models(cmdline_overrides)
reflections = self.generate_reflections()
# use a ReflectionManager to exclude reflections too close to the spindle,
# plus set the frame numbers
from dials.algorithms.refinement.reflection_manager import ReflectionManager
refman = ReflectionManager(reflections, self.experiments,
outlier_detector=None)
# create prediction parameterisation of the requested type
pred_param = ScanVaryingPredictionParameterisation(self.experiments,
[self.det_param], [self.s0_param], [self.xlo_param], [self.xluc_param],
[self.gon_param])
# make a target to ensure reflections are predicted and refman is finalised
from dials.algorithms.refinement.target import \
LeastSquaresPositionalResidualWithRmsdCutoff
target = LeastSquaresPositionalResidualWithRmsdCutoff(self.experiments,
self.ref_predictor, refman, pred_param, restraints_parameterisation=None)
# keep only those reflections that pass inclusion criteria and have predictions
reflections = refman.get_matches()
# get analytical gradients
pred_param.compose(reflections)
an_grads = pred_param.get_gradients(reflections)
# get finite difference gradients
p_vals = pred_param.get_param_vals()
p_names = pred_param.get_param_names()
deltas = [1.e-7] * len(p_vals)
for i in range(len(deltas)):
val = p_vals[i]
p_vals[i] -= deltas[i] / 2.
pred_param.set_param_vals(p_vals)
pred_param.compose(reflections)
self.ref_predictor(reflections)
rev_state = reflections['xyzcal.mm'].deep_copy()
p_vals[i] += deltas[i]
pred_param.set_param_vals(p_vals)
pred_param.compose(reflections)
self.ref_predictor(reflections)
fwd_state = reflections['xyzcal.mm'].deep_copy()
p_vals[i] = val
fd = (fwd_state - rev_state)
x_grads, y_grads, phi_grads = fd.parts()
x_grads /= deltas[i]
y_grads /= deltas[i]
phi_grads /= deltas[i]
try:
for n, (a,b) in enumerate(zip(x_grads, an_grads[i]["dX_dp"])):
assert approx_equal(a, b, eps=1.e-5)
for n, (a,b) in enumerate(zip(y_grads, an_grads[i]["dY_dp"])):
assert approx_equal(a, b, eps=1.e-5)
for n, (a,b) in enumerate(zip(phi_grads, an_grads[i]["dphi_dp"])):
assert approx_equal(a, b, eps=1.e-5)
except AssertionError:
print "Failure for {0}".format(p_names[i])
raise
# return to the initial state
pred_param.set_param_vals(p_vals)
pred_param.compose(reflections)
print "OK"
return