def index(reflections, detector, known_symmetry, beams):
'''calls the two color indexer class after setting up the phil parameters
and returns a class object'''
# cmd_line = command_line.argument_interpreter(master_params=master_phil_scope)
# working_phil = cmd_line.process_and_fetch(args=[])
params = master_phil_scope.extract()
params.refinement.parameterisation.beam.fix = "all"
params.refinement.parameterisation.detector.fix = "all"
params.indexing.known_symmetry.space_group = known_symmetry.space_group_info(
)
params.refinement.verbosity = 3
params.indexing.refinement_protocol.d_min_start
params.indexing.refinement_protocol.n_macro_cycles = 1
params.indexing.known_symmetry.unit_cell = known_symmetry.unit_cell()
params.indexing.debug = True
params.indexing.known_symmetry.absolute_angle_tolerance = 5.0
params.indexing.known_symmetry.relative_length_tolerance = 0.3
params.indexing.stills.rmsd_min_px = 3.5
filenames = [""]
reader = Reader(filenames)
masker = Masker(filenames)
imgsetdata = ImageSetData(reader, masker)
imgset = ImageSet(imgsetdata)
imgset.set_beam(beams[0])
imgset.set_detector(detector)
imagesets = [imgset]
orient = indexer_two_color(reflections, imagesets, params)
orient.index()
return orient
def index(reflections, detector, known_symmetry, beams):
params = master_phil_scope.extract()
params.refinement.parameterisation.beam.fix = "all"
params.refinement.parameterisation.detector.fix = "all"
params.indexing.known_symmetry.space_group = known_symmetry.space_group_info(
)
params.refinement.verbosity = 3
params.indexing.refinement_protocol.d_min_start
params.indexing.refinement_protocol.n_macro_cycles = 1
params.indexing.known_symmetry.unit_cell = known_symmetry.unit_cell()
params.indexing.debug = True
params.indexing.known_symmetry.absolute_angle_tolerance = 5.0
params.indexing.known_symmetry.relative_length_tolerance = 0.3
filenames = [""]
reader = Reader(filenames)
masker = Masker(filenames)
iset_data = ImageSetData(reader, masker)
imgset = ImageSet(iset_data)
imgset.set_beam(beams[0])
imgset.set_detector(detector)
imagesets = [imgset]
# dermen:
# modified rmsd_min_px this so test will pass, was originally set
# to 2 and the stills indexer's best.rmsd was of order ~2.8ish
# I dont know enough about the code itself to make the call on
# whether this is legit or not or whether 2.8 best.rmsd is
# something we should focus on improving...
params.indexing.stills.rmsd_min_px = 3.5
orient = indexer_two_color(reflections, imagesets, params)
orient.index()
return orient
def index(reflections, detector, known_symmetry, beams):
'''sets up two color indexer parameters and calls the indexer; returns the
candidate basis vectors from the 2-D grid search in two color indexer'''
# cmd_line = command_line.argument_interpreter(master_params=master_phil_scope)
# working_phil = cmd_line.process_and_fetch(args=[])
params = master_phil_scope.extract()
params.refinement.parameterisation.beam.fix = "all"
params.refinement.parameterisation.detector.fix = "all"
params.indexing.known_symmetry.space_group = known_symmetry.space_group_info(
)
params.refinement.verbosity = 3
params.indexing.refinement_protocol.d_min_start
params.indexing.refinement_protocol.n_macro_cycles = 1 # 5
params.indexing.known_symmetry.unit_cell = known_symmetry.unit_cell()
params.indexing.debug = True
params.indexing.known_symmetry.absolute_angle_tolerance = 5.0
params.indexing.known_symmetry.relative_length_tolerance = 0.3
params.indexing.stills.rmsd_min_px = 3.5
filenames = [""]
reader = Reader(filenames)
masker = Masker(filenames)
iset_data = ImageSetData(reader, masker)
imgset = ImageSet(iset_data)
imgset.set_beam(beams[0])
imgset.set_detector(detector)
imagesets = [imgset]
orient = indexer_two_color(reflections, imagesets, params) #, beams=beams)
orient.index()
cvecs = orient.candidate_basis_vectors
return cvecs
def generate_spots(crystal_model,
detector,
beam,
goniometer=None,
scan=None,
sel_fraction=1.0):
experiment = Experiment(beam=beam,
detector=detector,
goniometer=goniometer,
scan=scan,
crystal=crystal_model)
# if we don't set the imageset then from_predictions uses the StillsReflectionPredictor :-(
filenames = [""] * len(scan)
reader = Reader(filenames)
masker = Masker(filenames)
data = ImageSetData(reader, masker)
imageset = ImageSweep(data, beam, detector, goniometer, scan)
experiment.imageset = imageset
predicted = flex.reflection_table.from_predictions(experiment)
sel = flex.random_selection(len(predicted),
int(math.floor(sel_fraction * len(predicted))))
predicted = predicted.select(sel)
predicted['imageset_id'] = flex.size_t(len(predicted), 0)
predicted['xyzobs.px.value'] = predicted['xyzcal.px']
predicted['xyzobs.px.variance'] = flex.vec3_double(len(predicted),
(0.5, 0.5, 0.5))
return predicted
def test_elliptical_distortion(run_in_tmpdir):
"""Create distortion maps for elliptical distortion using a dummy experiments
with a small detector, for speed. Check those maps seem sensible"""
# Make a detector model
d = make_detector()
# The beam is also essential for a experiments to be serialisable
b = Beam((0, 0, 1), 1.0)
# Create and write out a experiments
imageset = ImageSet(ImageSetData(Reader(None, ["non-existent.cbf"]), None))
imageset.set_detector(d)
imageset.set_beam(b)
experiments = ExperimentListFactory.from_imageset_and_crystal(
imageset, None)
experiments.as_json("dummy.expt")
# Centre of distortion will be the far corner from the origin of the first
# panel
centre_xy = d[0].get_image_size_mm()
# Generate distortion maps
cmd = ("dials.generate_distortion_maps dummy.expt "
"mode=ellipse centre_xy={},{} "
"phi=0 l1=1.0 l2=0.95").format(*centre_xy)
easy_run.fully_buffered(command=cmd).raise_if_errors()
# Load the maps
with open("dx.pickle", "rb") as f:
dx = pickle.load(f)
with open("dy.pickle", "rb") as f:
dy = pickle.load(f)
# Check there are 4 maps each
assert len(dx) == len(dy) == 4
# Ellipse has phi=0, so all correction is in the dy map
for arr in dx:
assert min(arr) == max(arr) == 0.0
# The ellipse correction is centred at the middle of the detector and all in
# the Y direction. Therefore we expect a few things from the dy maps:
#
# (1) Within each panel the columns of the array are identical.
# (2) The two upper panels should be the same
# (3) The two lower panels should be the same.
# (4) One column from an upper panel is a negated, reversed column from a
# lower panel.
#
# All together expect the 4 dy maps to look something like this:
#
# /-----------\ /-----------\
# |-3 -3 -3 -3| |-3 -3 -3 -3|
# |-2 -2 -2 -2| |-2 -2 -2 -2|
# |-1 -1 -1 -1| |-1 -1 -1 -1|
# | 0 0 0 0| | 0 0 0 0|
# \-----------/ \-----------/
# /-----------\ /-----------\
# | 0 0 0 0| | 0 0 0 0|
# | 1 1 1 1| | 1 1 1 1|
# | 2 2 2 2| | 2 2 2 2|
# | 3 3 3 3| | 3 3 3 3|
# \-----------/ \-----------/
# So the fundamental data is all in the first column of first panel's map
col0 = dy[0].matrix_copy_column(0)
# The correction should be 5% of the distance from the ellipse centre to a
# corrected pixel (l2 = 0.95 above) along the slow axis. Check that is the
# case (for the first pixel at least)
vec_centre_to_first_px = matrix.col(d[0].get_pixel_lab_coord(
(0.5, 0.5))) - matrix.col(d[0].get_lab_coord(centre_xy))
dist_centre_to_first_px = vec_centre_to_first_px.dot(
matrix.col(d[0].get_slow_axis()))
corr_mm = dist_centre_to_first_px * 0.05
corr_px = corr_mm / d[0].get_pixel_size()[1]
assert col0[0] == pytest.approx(corr_px)
# Test (1) from above list for panel 0
for i in range(1, 50):
assert (col0 == dy[0].matrix_copy_column(i)).all_eq(True)
# Test (2)
assert (dy[0] == dy[1]).all_eq(True)
# Test (3)
assert (dy[2] == dy[3]).all_eq(True)
# Test (4)
assert col0 == pytest.approx(-1.0 * dy[2].matrix_copy_column(0).reversed())
# Test (1) for panel 2 as well, which then covers everything needed
col0 = dy[2].matrix_copy_column(0)
for i in range(1, 50):
assert (col0 == dy[2].matrix_copy_column(i)).all_eq(True)