def __init__(self, plots = False):
# Do we make scatterplots?
self.do_plots = plots
# Let's say we have a scan of 100 images
self.image_range = (1, 100)
# Make a random P1 crystal
a = random.uniform(10,50) * \
self.random_direction_close_to(matrix.col((1, 0, 0)))
b = random.uniform(10,50) * \
self.random_direction_close_to(matrix.col((0, 1, 0)))
c = random.uniform(10,50) * \
self.random_direction_close_to(matrix.col((0, 0, 1)))
self.xl = crystal_model(a, b, c, space_group_symbol = "P 1")
# Make a beam with wavelength in the range 0.8--1.2 and s0 direction close
# to 0,0,1
s0 = random.uniform(0.8, 1.2) * \
self.random_direction_close_to(matrix.col((0, 0, 1)))
self.beam = Beam(s0)
# Make a standard goniometer model along X
self.goniometer = Goniometer((1,0,0))
# Make a simple single panel detector
d1 = matrix.col((1, 0, 0))
d2 = matrix.col((0, -1, 0))
npx_fast = 1475
npx_slow = 1679
pix_size_f = pix_size_s = 0.172
from dxtbx.model.experiment import detector_factory
self.detector = detector_factory.make_detector("PAD", d1, d2,
matrix.col((0, 0, -110)), (pix_size_f, pix_size_s),
(npx_fast, npx_slow), (0, 2e20))
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)