def test_fake(self):
"""test for fake image generation"""
with_plot = (logger.getEffectiveLevel() <= logging.DEBUG)
if with_plot:
import matplotlib
import matplotlib.pyplot as plt
fig = plt.figure()
ax = fig.add_subplot(1, 1, 1)
detectors = set(ALL_DETECTORS.values())
for idx, detector in enumerate(detectors):
det = detector()
# Skip generic detectors
if "MAX_SHAPE" not in dir(det):
continue
# skip the big detectors for now
if max(det.MAX_SHAPE) > 2000:
continue
ai = pyFAI.AzimuthalIntegrator(dist=0.01, poni1=0, poni2=0,
detector=det)
calibrant = ALL_CALIBRANTS["LaB6"]
calibrant.set_wavelength(1e-10)
img = calibrant.fake_calibration_image(ai)
if with_plot:
ax.cla()
ax.set_title(det.name)
ax.imshow(img, interpolation='nearest')
fig.show()
six.moves.input("enter> ")
logger.info("%s min: %s max: %s " % (det.name, img.min(), img.max()))
self.assert_(img.shape == det.shape, "Image (%s) has the right size" % (det.name,))
self.assert_(img.sum() > 0, "Image (%s) contains some data" % (det.name,))
sys.stderr.write(".")
def setup_instrument(self):
entry = self.experiment_file['entry']
entry.instrument = NXinstrument()
entry.instrument.monochromator = NXmonochromator()
entry.instrument.detector = NXdetector()
entry['instrument/monochromator/wavelength'] = NXfield(
0.5, dtype=np.float32)
entry['instrument/monochromator/wavelength'].attrs[
'units'] = 'Angstroms'
entry['instrument/monochromator/energy'] = NXfield(12.398419739640717 /
0.5,
dtype=np.float32)
entry['instrument/monochromator/energy'].attrs['units'] = 'keV'
entry['instrument/detector/distance'] = NXfield(100.0,
dtype=np.float32)
entry['instrument/detector/distance'].attrs['units'] = 'mm'
self.instrument = GridParameters()
self.instrument.add('experiment', 'experiment', 'Experiment Name')
self.instrument.add('wavelength',
entry['instrument/monochromator/wavelength'],
'Wavelength (Ang)')
self.instrument.add('distance', entry['instrument/detector/distance'],
'Detector Distance (mm)')
detector_list = sorted(
list(set([detector().name
for detector in ALL_DETECTORS.values()])))
self.instrument.add('detector', detector_list, 'Detector')
self.instrument['detector'].value = 'Pilatus CdTe 2M'
self.instrument.add('positions', [0, 1, 2, 3, 4],
'Number of Detector Positions',
slot=self.set_entries)
self.instrument['positions'].value = '0'
def test_detector_instanciate(self):
"""
this method try to instantiate all the detectors
"""
for k, v in ALL_DETECTORS.items():
logger.debug(k)
v()
def get_available_detectors():
detector_classes = set()
detector_names = []
for key, item in ALL_DETECTORS.items():
detector_classes.add(item)
for detector in detector_classes:
if len(detector.aliases) > 0:
detector_names.append(detector.aliases[0])
else:
detector_names.append(detector().__class__.__name__)
sorted_indices = sorted(range(len(detector_names)),
key=detector_names.__getitem__)
detector_names_sorted = [detector_names[i] for i in sorted_indices]
detector_classes_sorted = [
list(detector_classes)[i] for i in sorted_indices
]
base_class_index = detector_names_sorted.index('Detector')
del detector_names_sorted[base_class_index]
del detector_classes_sorted[base_class_index]
return detector_names_sorted, detector_classes_sorted
def test_detector_instanciate(self):
"""
this method try to instantiate all the detectors
"""
for k, v in ALL_DETECTORS.items():
logger.debug(k)
v()
def test_fake(self):
"""test for fake image generation"""
with_plot = False
if with_plot:
import matplotlib
matplotlib.use('Agg')
import matplotlib.pyplot as plt
from matplotlib.backends.backend_pdf import PdfPages
from matplotlib import rcParams
pp = PdfPages('fake.pdf')
rcParams['font.size'] = 6
plt.clf()
detectors = set(ALL_DETECTORS.values())
for idx, detector in enumerate(detectors):
det = detector()
# Skip generic detectors
if "MAX_SHAPE" not in dir(det):
continue
# skip the big detectors for now
if max(det.MAX_SHAPE) > 2000:
continue
ai = pyFAI.AzimuthalIntegrator(dist=0.01,
poni1=0,
poni2=0,
detector=det)
calibrant = ALL_CALIBRANTS["LaB6"]
calibrant.set_wavelength(1e-10)
img = calibrant.fake_calibration_image(ai)
if with_plot:
plt.clf
plt.subplot(3, 4, idx % 12)
plt.title(det.name)
plt.imshow(img, interpolation='nearest')
if idx != 0 and idx % 12 == 0:
pp.savefig()
plt.clf()
print(det.name, img.min(), img.max())
self.assert_(img.shape == det.shape,
"Image (%s) has the right size" % (det.name, ))
self.assert_(img.sum() > 0,
"Image (%s) contains some data" % (det.name, ))
sys.stderr.write(".")
if with_plot:
pp.savefig()
pp.close()
def guess_detector_by_shape(shape):
# for every detector known to pyFAI
for name, detector in sorted(ALL_DETECTORS.items()):
# if a shape limit is set
if hasattr(detector, 'MAX_SHAPE'):
if detector.MAX_SHAPE == shape:
return detector()
if hasattr(detector, 'BINNED_PIXEL_SIZE'):
for binning in detector.BINNED_PIXEL_SIZE.keys():
if shape == tuple(np.array(detector.MAX_SHAPE) / binning): # possibly needs to be reversed [::-1]
detector = detector()
detector.set_binning(binning)
return detector
return None
def test_fake(self):
"""test for fake image generation"""
with_plot = False
if with_plot:
import matplotlib
matplotlib.use('Agg')
import matplotlib.pyplot as plt
from matplotlib.backends.backend_pdf import PdfPages
from matplotlib import rcParams
pp = PdfPages('fake.pdf')
rcParams['font.size'] = 6
plt.clf()
detectors = set(ALL_DETECTORS.values())
for idx, detector in enumerate(detectors):
det = detector()
# Skip generic detectors
if "MAX_SHAPE" not in dir(det):
continue
# skip the big detectors for now
if max(det.MAX_SHAPE) > 2000:
continue
ai = pyFAI.AzimuthalIntegrator(dist=0.01, poni1=0, poni2=0,
detector=det)
calibrant = ALL_CALIBRANTS["LaB6"]
calibrant.set_wavelength(1e-10)
img = calibrant.fake_calibration_image(ai)
if with_plot:
plt.clf
plt.subplot(3, 4, idx % 12)
plt.title(det.name)
plt.imshow(img, interpolation='nearest')
if idx != 0 and idx % 12 == 0:
pp.savefig()
plt.clf()
print(det.name, img.min(), img.max())
self.assert_(img.shape == det.shape, "Image (%s) has the right size" % (det.name,))
self.assert_(img.sum() > 0, "Image (%s) contains some data" % (det.name,))
sys.stderr.write(".")
if with_plot:
pp.savefig()
pp.close()
def setup_instrument(self):
default = self.settings['nxrefine']
entry = self.configuration_file['entry']
entry['instrument/detector/distance'] = NXfield(default['distance'],
dtype=float)
entry['instrument/detector/distance'].attrs['units'] = 'mm'
self.instrument = GridParameters()
self.instrument.add('distance', entry['instrument/detector/distance'],
'Detector Distance (mm)')
detector_list = sorted(
list(set([detector().name
for detector in ALL_DETECTORS.values()])))
self.instrument.add('detector', detector_list, 'Detector')
self.instrument['detector'].value = 'Pilatus CdTe 2M'
self.instrument.add('positions', [0, 1, 2, 3, 4, 5, 6, 7, 8],
'Number of Detector Positions',
slot=self.set_entries)
self.instrument['positions'].value = '0'
def setup_instrument(self):
entry = self.experiment_file['entry']
entry.instrument = NXinstrument()
entry.instrument.monochromator = NXmonochromator()
entry.instrument.detector = NXdetector()
entry['instrument/monochromator/wavelength'] = NXfield(0.5, dtype=np.float32)
entry['instrument/monochromator/wavelength'].attrs['units'] = 'Angstroms'
entry['instrument/monochromator/energy'] = NXfield(12.398419739640717/0.5, dtype=np.float32)
entry['instrument/monochromator/energy'].attrs['units'] = 'keV'
entry['instrument/detector/distance'] = NXfield(100.0, dtype=np.float32)
entry['instrument/detector/distance'].attrs['units'] = 'mm'
self.instrument = GridParameters()
self.instrument.add('experiment', 'experiment', 'Experiment Name')
self.instrument.add('wavelength', entry['instrument/monochromator/wavelength'], 'Wavelength (Ang)')
self.instrument.add('distance', entry['instrument/detector/distance'], 'Detector Distance (mm)')
detector_list = sorted(list(set([detector().name for detector in ALL_DETECTORS.values()])))
self.instrument.add('detector', detector_list, 'Detector')
self.instrument['detector'].value = 'Pilatus CdTe 2M'
self.instrument.add('positions', [0,1,2,3,4], 'Number of Detector Positions', slot=self.set_entries)
self.instrument['positions'].value = '0'
from pyFAI.detectors import ALL_DETECTORS, Detector
from pyFAI.azimuthalIntegrator import AzimuthalIntegrator
from xicam.plugins.operationplugin import describe_input, describe_output, operation, output_names, display_name, units
def get_name(detector):
if detector.aliases:
name = detector.aliases[0]
else:
name = detector.__class__.__name__
return name
# Remove 'detector' and sort by name
_detectors = {get_name(detector): detector
for detector in ALL_DETECTORS.values()
if detector is not Detector}
_sorted_detectors = dict(sorted(_detectors.items()))
DetectorEnum = Enum('Detector', _sorted_detectors)
@operation
@output_names()
@units("distance", "mm")
@units("center_x", "mm")
@units("center_y", "mm")
@units("tilt", "degrees")
@units("tilt_plane_rotation", "degrees")
@describe_input("distance", "Distance to detector center")
@describe_input("center_x", "")
@describe_input("center_y", "")
def test_detector_instanciate(self):
"""
this method try to instanciate all the detectors
"""
for k, v in ALL_DETECTORS.iteritems():
v()
def test_detector_instanciate(self):
"""
this method try to instanciate all the detectors
"""
for k, v in ALL_DETECTORS.iteritems():
v()
