def test_load_geo():
geo = load_geo(pyFAI_calib)
assert geo
from xpdtools.tests.utils import pyFAI_calib
from xpdtools.tools import (
load_geo,
map_to_binner,
mask_img,
binned_outlier,
z_score_image,
polarization_correction,
overlay_mask,
generate_map_bin,
generate_binner,
move_center,
)
from xpdtools.jit_tools import mask_ring_median, mask_ring_mean
geo = load_geo(pyFAI_calib)
def test_mask_ring_mean():
values = np.asarray([0, 0, 0, 10, 0, 0, 0, 0])
positions = np.arange(0, len(values))
assert mask_ring_mean(values, positions, 1) == np.argmax(values)
def test_mask_ring_median():
values = np.asarray([0, 0, 0, 1, 0, 0, 0, 0])
positions = np.arange(0, len(values))
assert mask_ring_median(values, positions, 3) == np.argmax(values)
def test_load_geo():
0.557193323722,
0.537404961852,
0.531262989146,
0.508645587156,
0.493458701611,
0.488690872874,
0.47091430825,
0.458785722296,
0.4405,
0.430525121912,
0.427347771314,
],
"calibrant_name":
"undefined",
}
calibration = load_geo(cal_params)
class take_data:
def __init__(
self,
translation_motor,
rotation_motor,
phases,
raster_pixel_size,
poni: Geometry,
order=3,
):
"""Pencil beam x-ray diffraction tomography simulation
Parameters
def event(self, doc):
if self.dark_img is not None:
doc = next(self.db.fill_events([doc], self.descs))
if "cryostat_T" in doc["data"]:
doc["data"]["temperature"] = doc["data"].pop("cryostat_T")
# human readable timestamp
h_timestamp = _timestampstr(doc["time"])
# dark subtraction
img = doc["data"][self.image_data_key]
if str(img.dtype) == "uint16":
img = img.astype("float32")
if self.dark_img is not None:
img -= self.dark_img
if self.vis:
self.vis_callbacks["dark_sub_iq"]("event",
format_event(img=img))
if self.write_to_disk:
tiff_name = render_clean_makedir(
self.light_template,
human_timestamp=h_timestamp,
raw_event=doc,
raw_start=self.start_doc,
raw_descriptor=self.descriptor_doc,
analysis_stage="dark_sub",
ext=".tiff",
)
tifffile.imsave(tiff_name, img)
if self.analysis_setting == "full":
# background correction
if self.background_img is not None:
img -= self.background_img
# get calibration
if self.is_calibration:
calibration, geo = img_calibration(img, self.wavelength,
self.calibrant,
self.detector)
_save_calib_param(
calibration,
h_timestamp,
os.path.join(self.calibration_md_folder,
"xpdAcq_calib_info.yml"),
)
if self.write_to_disk:
poni_name = render_clean_makedir(
self.light_template,
human_timestamp=h_timestamp,
raw_event=doc,
raw_start=self.start_doc,
raw_descriptor=self.descriptor_doc,
analysis_stage="calib",
ext=".poni",
)
poni_saver(poni_name, calibration)
elif self.calibrant:
geo = load_geo(self.calibrant)
else:
geo = None
if geo:
img = polarization_correction(img, geo,
self.polarization_factor)
# Masking
if doc["seq_num"] == 1:
if (self.start_doc["sample_name"] == "Setup"
or self.mask_setting is None):
self.mask = np.ones(img.shape, dtype=bool)
else:
binner = generate_binner(geo, img.shape, self.mask)
self.mask = mask_img(img, binner,
**self.mask_kwargs)
if self.write_to_disk:
mask_name = render_clean_makedir(
self.light_template,
human_timestamp=h_timestamp,
raw_event=doc,
raw_start=self.start_doc,
raw_descriptor=self.descriptor_doc,
analysis_stage="mask",
ext="",
)
fit2d_save(self.mask, mask_name)
if self.vis:
overlay = overlay_mask(img, self.mask)
self.vis_callbacks["masked_img"](
"event", format_event(overlay_mask=overlay))
# binner
binner = generate_binner(geo, img.shape, self.mask)
q, iq = (
binner.bin_centers,
np.nan_to_num(binner(img.flatten())),
)
if self.vis:
self.vis_callbacks["iq"]("event",
format_event(q=q, iq=iq))
self.vis_callbacks["zscore"](
"event",
format_event(img=z_score_image(img, binner)),
)
if self.write_to_disk:
iq_name = render_clean_makedir(
self.light_template,
human_timestamp=h_timestamp,
raw_event=doc,
raw_start=self.start_doc,
raw_descriptor=self.descriptor_doc,
analysis_stage="iq_q",
ext="_Q.chi",
)
save_output(q, iq, iq_name, "Q")
tth = np.rad2deg(q_to_twotheta(q, self.wavelength))
if self.vis:
self.vis_callbacks["itth"]("event",
format_event(tth=tth,
iq=iq))
if self.write_to_disk:
itth_name = render_clean_makedir(
self.light_template,
human_timestamp=h_timestamp,
raw_event=doc,
raw_start=self.start_doc,
raw_descriptor=self.descriptor_doc,
analysis_stage="iq_tth",
ext="_tth.chi",
)
save_output(tth, iq, itth_name, "2theta")
if self.composition:
fq_q, fq, fq_config = fq_getter(
q,
iq,
composition=self.composition,
**self.fq_kwargs)
if self.vis:
self.vis_callbacks["fq"]("event",
format_event(q=fq_q,
fq=fq))
r, gr, pdf_config = pdf_getter(
q,
iq,
composition=self.composition,
**self.pdf_kwargs)
if self.vis:
self.vis_callbacks["pdf"]("event",
format_event(r=r,
pdf=gr))
if self.write_to_disk:
pdf_name = render_clean_makedir(
self.light_template,
human_timestamp=h_timestamp,
raw_event=doc,
raw_start=self.start_doc,
raw_descriptor=self.descriptor_doc,
analysis_stage="pdf",
ext=".gr",
)
pdf_saver(r, gr, pdf_config, pdf_name)
def event(self, doc):
if self.dark_img is not None:
doc = next(self.db.fill_events([doc], self.descs))
if 'cryostat_T' in doc['data']:
doc['data']['temperature'] = doc['data'].pop('cryostat_T')
# human readable timestamp
h_timestamp = _timestampstr(doc['time'])
# dark subtraction
img = doc['data'][self.image_data_key]
if str(img.dtype) == 'uint16':
img = img.astype('float32')
if self.dark_img is not None:
img -= self.dark_img
if self.vis:
self.vis_callbacks['dark_sub_iq']('event',
format_event(img=img))
if self.write_to_disk:
tiff_name = render_clean_makedir(
self.light_template,
human_timestamp=h_timestamp,
raw_event=doc,
raw_start=self.start_doc,
raw_descriptor=self.descriptor_doc,
analysis_stage='dark_sub',
ext='.tiff')
tifffile.imsave(tiff_name, img)
if self.analysis_setting == 'full':
# background correction
if self.background_img is not None:
img -= self.background_img
# get calibration
if self.is_calibration:
calibration, geo = img_calibration(img, self.wavelength,
self.calibrant,
self.detector)
_save_calib_param(
calibration, h_timestamp,
os.path.join(self.calibration_md_folder,
'xpdAcq_calib_info.yml'))
if self.write_to_disk:
poni_name = render_clean_makedir(
self.light_template,
human_timestamp=h_timestamp,
raw_event=doc,
raw_start=self.start_doc,
raw_descriptor=self.descriptor_doc,
analysis_stage='calib',
ext='.poni')
poni_saver(poni_name, calibration)
elif self.calibrant:
geo = load_geo(self.calibrant)
else:
geo = None
if geo:
img = polarization_correction(img, geo,
self.polarization_factor)
# Masking
if doc['seq_num'] == 1:
if (self.start_doc['sample_name'] == 'Setup'
or self.mask_setting is None):
self.mask = np.ones(img.shape, dtype=bool)
else:
binner = generate_binner(geo, img.shape, self.mask)
self.mask = mask_img(img, binner,
**self.mask_kwargs)
if self.write_to_disk:
mask_name = render_clean_makedir(
self.light_template,
human_timestamp=h_timestamp,
raw_event=doc,
raw_start=self.start_doc,
raw_descriptor=self.descriptor_doc,
analysis_stage='mask',
ext='')
fit2d_save(self.mask, mask_name)
if self.vis:
overlay = overlay_mask(img, self.mask)
self.vis_callbacks['masked_img'](
'event', format_event(overlay_mask=overlay))
# binner
binner = generate_binner(geo, img.shape, self.mask)
q, iq = binner.bin_centers, np.nan_to_num(
binner(img.flatten()))
if self.vis:
self.vis_callbacks['iq']('event',
format_event(q=q, iq=iq))
self.vis_callbacks['zscore'](
'event',
format_event(img=z_score_image(img, binner)))
if self.write_to_disk:
iq_name = render_clean_makedir(
self.light_template,
human_timestamp=h_timestamp,
raw_event=doc,
raw_start=self.start_doc,
raw_descriptor=self.descriptor_doc,
analysis_stage='iq_q',
ext='_Q.chi')
save_output(q, iq, iq_name, 'Q')
tth = np.rad2deg(q_to_twotheta(q, self.wavelength))
if self.vis:
self.vis_callbacks['itth']('event',
format_event(tth=tth,
iq=iq))
if self.write_to_disk:
itth_name = render_clean_makedir(
self.light_template,
human_timestamp=h_timestamp,
raw_event=doc,
raw_start=self.start_doc,
raw_descriptor=self.descriptor_doc,
analysis_stage='iq_tth',
ext='_tth.chi')
save_output(tth, iq, itth_name, '2theta')
if self.composition:
fq_q, fq, fq_config = fq_getter(
q,
iq,
composition=self.composition,
**self.fq_kwargs)
if self.vis:
self.vis_callbacks['fq']('event',
format_event(q=fq_q,
fq=fq))
r, gr, pdf_config = pdf_getter(
q,
iq,
composition=self.composition,
**self.pdf_kwargs)
if self.vis:
self.vis_callbacks['pdf']('event',
format_event(r=r,
pdf=gr))
if self.write_to_disk:
pdf_name = render_clean_makedir(
self.light_template,
human_timestamp=h_timestamp,
raw_event=doc,
raw_start=self.start_doc,
raw_descriptor=self.descriptor_doc,
analysis_stage='pdf',
ext='.gr')
pdf_saver(r, gr, pdf_config, pdf_name)
