def test_gaussianrs_reference_profile_calculator(data):
from dials.algorithms.profile_model.gaussian_rs.algorithm import (
GaussianRSReferenceCalculatorFactory, )
algorithm = GaussianRSReferenceCalculatorFactory.create(data.experiments)
reflections = flex.reflection_table_to_list_of_reflections(
data.reflections)
count = 0
for r in reflections:
try:
algorithm(r)
except Exception:
count += 1
assert len(reflections) == 15193
assert count == 0
profiles = algorithm.reference_profiles()
count = 0
for i in range(len(profiles)):
p = profiles[i].reference()
for j in range(len(p)):
d = p.data(j)
p.mask(j)
if len(d) != 0:
count += 1
assert count == 9
def test_gaussianrs_detector_space_with_deconvolution_intensity_calculator(
data):
algorithm = IntensityCalculatorFactory.create(data,
detector_space=True,
deconvolution=True)
reflections = flex.reflection_table_to_list_of_reflections(
data.reflections)
count = 0
for r in reflections:
try:
algorithm(r, [])
partiality_old = r.get("partiality_old")
partiality_new = r.get("partiality")
except Exception as e:
count += 1
continue
assert partiality_old < 1.0 and partiality_old >= 0
assert partiality_new < 1.0 and partiality_new >= 0
assert len(reflections) == 15193
assert count == 4802
def test_gaussianrs_mask_calculator(data):
from dials.algorithms.integration.parallel_integrator import MaskCalculatorFactory
algorithm = MaskCalculatorFactory.create(data.experiments)
reflections = flex.reflection_table_to_list_of_reflections(data.reflections)
for r in reflections:
algorithm(r, False)
def test_gaussianrs_detector_space_with_deconvolution_intensity_calculator(data):
algorithm = IntensityCalculatorFactory.create(
data, detector_space=True, deconvolution=True
)
reflections = flex.reflection_table_to_list_of_reflections(data.reflections)
errors = 0
for r in reflections:
try:
algorithm(r, [])
partiality_old = r.get("partiality_old")
partiality_new = r.get("partiality")
except Exception as e:
if ("Partiality too small to fit" in str(e)) or (
"DIALS_ASSERT(fit.niter() < 100) failure." in str(e)
):
errors += 1
continue
raise
assert partiality_old < 1.0 and partiality_old >= 0
assert partiality_new < 1.0 and partiality_new >= 0
assert len(reflections) == 15193
assert errors == 4802
def test_glm_background_calculator():
from dials.algorithms.background.glm.algorithm import GLMBackgroundCalculatorFactory
algorithm = GLMBackgroundCalculatorFactory.create(data.experiments)
reflections = flex.reflection_table_to_list_of_reflections(data.reflections)
count = 0
for r in reflections:
try:
algorithm(r)
except Exception:
count += 1
assert len(reflections) == 15193
assert count == 333
def test_simple_background_calculator(data):
from dials.algorithms.background.simple.algorithm import (
SimpleBackgroundCalculatorFactory, )
algorithm = SimpleBackgroundCalculatorFactory.create(data.experiments)
reflections = flex.reflection_table_to_list_of_reflections(
data.reflections)
errors = 0
for r in reflections:
try:
algorithm(r)
except Exception:
errors += 1
assert len(reflections) == 15193
assert errors == 333
def test_gaussianrs_reciprocal_space_intensity_calculator(data):
algorithm = IntensityCalculatorFactory.create(
data, detector_space=False, deconvolution=False
)
reflections = flex.reflection_table_to_list_of_reflections(data.reflections)
errors = 0
for r in reflections:
try:
algorithm(r, [])
except Exception:
errors += 1
assert len(reflections) == 15193
assert errors == 5296
def test_gaussianrs_detector_space_with_deconvolution_intensity_calculator2(
data):
from scitbx import matrix
reflections = flex.reflection_table_to_list_of_reflections(
data.reflections)
R = None
for r in reflections:
if r.get("partiality") > 0.9 and r.get("intensity.sum.value") > 100:
R = r
break
assert R is not None
px = R.get("xyzcal.px")
mm = R.get("xyzcal.mm")
px1 = (px[0] - 3, px[1] - 3, px[2])
px2 = (px[0] + 3, px[1] + 3, px[2])
mm1 = (mm[0] - 3 * 0.172, mm[1] - 3 * 0.172, mm[2])
mm2 = (mm[0] + 3 * 0.172, mm[1] + 3 * 0.172, mm[2])
s11 = matrix.col(data.experiments[0].detector[0].get_pixel_lab_coord(
px1[0:2])).normalize()
s12 = matrix.col(data.experiments[0].detector[0].get_pixel_lab_coord(
px2[0:2])).normalize()
R1 = R.copy()
R2 = R.copy()
R1.set_vec3_double("xyzcal.px", px1)
R1.set_vec3_double("xyzcal.mm", mm1)
R1.set_vec3_double("s1", s11)
R2.set_vec3_double("xyzcal.px", px2)
R2.set_vec3_double("xyzcal.mm", mm2)
R2.set_vec3_double("s1", s12)
compute_intensity = IntensityCalculatorFactory.create(data,
detector_space=True,
deconvolution=False)
compute_intensity(R, [])
R.set_double("intensity.prf.value.old", R.get("intensity.prf.value"))
R.set_double("intensity.prf.variance.old", R.get("intensity.prf.variance"))
R_no_deconvolution = R.copy()
# print "Partiality", R.get("partiality")
# print "Partiality Old", R.get("partiality_old")
# print "Intensity", R.get("intensity.prf.value")
# print "Intensity Old", R.get("intensity.prf.value.old")
from dials.algorithms.integration.parallel_integrator import MaskCalculatorFactory
mask_calculator = MaskCalculatorFactory.create(data.experiments)
mask_calculator(R1, True)
mask_calculator(R2, True)
# print R.get("shoebox").mask.as_numpy_array()[0,:,:]
compute_intensity = IntensityCalculatorFactory.create(data,
detector_space=True,
deconvolution=True)
compute_intensity(R, [R1, R2])
# compute_intensity(R, [R1, R2])
R_deconvolution = R.copy()
partiality1 = R_no_deconvolution.get("partiality")
partiality2 = R_deconvolution.get("partiality")
intensity = R_deconvolution.get("intensity.prf.value")
variance = R_deconvolution.get("intensity.prf.variance")
assert partiality1 <= partiality2
assert abs(intensity - 179.05997142249996) < 1e-7
assert abs(variance - 203.56992949599677) < 1e-7
