def get_spot_convention(imagefile):
# Maybe 2 if RAXIS else 0..
return 2
from spotfinder.command_line.signal_strength import master_params
phil_params = master_params.extract()
imageobject = iotbx.detectors.ImageFactory(G["file"][start_frame])
beam_center_convention_from_image_object(imageobject, phil_params)
print "SPOT CONVENTION=", phil_params.spot_convention
return phil_params.spot_convention
def get_spot_convention(imagefile):
# Maybe 2 if RAXIS else 0..
return 2
from spotfinder.command_line.signal_strength import master_params
phil_params = master_params.extract()
imageobject = iotbx.detectors.ImageFactory(G["file"][start_frame])
beam_center_convention_from_image_object(imageobject, phil_params)
print "SPOT CONVENTION=", phil_params.spot_convention
return phil_params.spot_convention
def triage_image(self):
""" Performs a quick DISTL spotfinding without grid search.
NOTE: Convert to DIALS spotfinder when ready! (Even for CCTBX runs.)
"""
import spotfinder
from spotfinder.command_line.signal_strength import master_params as sf_params
from spotfinder.applications.wrappers import DistlOrganizer
sf_params = sf_params.extract()
sf_params.distl.image = self.conv_img
E = Empty()
E.argv=['Empty']
E.argv.append(sf_params.distl.image)
selected_output = []
total_output = []
bragg_spots = []
spotfinding_log = ['{}\n'.format(self.conv_img)]
# set spotfinding parameters for DISTL spotfinder
sf_params.distl.minimum_spot_area = self.params.cctbx.grid_search.area_median
sf_params.distl.minimum_spot_height = self.params.cctbx.grid_search.height_median
sf_params.distl.minimum_signal_height = int(self.params.cctbx.grid_search.height_median / 2)
# run DISTL spotfinder
with misc.Capturing() as junk_output:
Org = DistlOrganizer(verbose = False, argument_module=E,
phil_params=sf_params)
Org.printSpots()
# Extract relevant spotfinding info & make selection
for frame in Org.S.images.keys():
self.Bragg = Org.S.images[frame]['N_spots_inlier']
if self.Bragg >= self.params.image_triage.min_Bragg_peaks:
self.log_info.append('ACCEPTED! {} good Bragg peaks'\
''.format(self.Bragg))
status = None
else:
self.log_info.append('REJECTED')
status = 'failed triage'
return status
def __init__(self, file_name):
screen_params.__init__(self)
# XXX major hack - Boost.Python doesn't really deal with Unicode strings
if isinstance(file_name, unicode):
file_name = str(file_name)
if isinstance(file_name, str) or isinstance(file_name, dict):
self.file_name = file_name
from iotbx.detectors import ImageFactory, ImageException
try:
img = ImageFactory(file_name)
except ImageException as e:
raise Sorry(str(e))
img.read()
else:
img = file_name # assume it's already been read
self._raw = img
try:
img.show_header()
except Exception:
pass # intentional
detector = self._raw.get_detector()
if len(detector) == 1:
# Image size only makes sense for monolithic detectors.
image_size = detector[0].get_image_size()
self.set_image_size(w=image_size[0], h=image_size[1])
pixel_size = detector[0].get_pixel_size()
for panel in detector:
pstest = panel.get_pixel_size()
assert pixel_size[0] == pixel_size[1] == pstest[0] == pstest[1]
self.set_detector_resolution(pixel_size[0])
try:
from spotfinder.command_line.signal_strength import master_params
params = master_params.extract()
self._raw.initialize_viewer_properties(params)
except Exception:
pass # intentional
self._beam_center = None
self._integration = None
self._spots = None
self._color_scheme = None
if len(detector) == 1:
# Image size only makes sense for monolithic detectors.
image_size = detector[0].get_image_size()
self.set_image_size(
w=image_size[0],
h=image_size[1])
pixel_size = detector[0].get_pixel_size()
for panel in detector:
pstest = panel.get_pixel_size()
assert pixel_size[0] == pixel_size[1] == pstest[0] == pstest[1]
self.set_detector_resolution(pixel_size[0])
try:
from spotfinder.command_line.signal_strength import master_params
params = master_params.extract()
self._raw.initialize_viewer_properties(params)
except Exception: pass # intentional
self._beam_center = None
self._integration = None
self._spots = None
self._color_scheme = None
#self.update_image()
#self.convert_to_bitmap()
def set_integration_results (self, integration) :
self._integration = integration
mp = integration['mapped_predictions']
print "%d spot predictions loaded" % mp.size()
print "max. resolution is %g" % integration['resolution']
def triage_image(self):
""" Performs a quick DISTL spotfinding without grid search.
"""
from spotfinder.command_line.signal_strength import master_params as sf_params
sf_params = sf_params.extract()
sf_params.distl.image = self.img
E = Empty()
E.argv = ['Empty']
E.argv.append(sf_params.distl.image)
log_info = ['{}\n'.format(self.img)]
img_filename = os.path.basename(self.img)
# Perform spotfinding
# ... using spotfinding grid search
if self.params.image_triage.type == 'grid_search':
log_info.append('\n CCTBX TRIAGE grid search:')
# Determine grid search extent
a_min = self.params.image_triage.grid_search.area_min
a_max = self.params.image_triage.grid_search.area_max
a_step = (a_max -
a_min) // self.params.image_triage.grid_search.step_size
h_min = self.params.image_triage.grid_search.height_min
h_max = self.params.image_triage.grid_search.height_max
h_step = (h_max -
h_min) // self.params.image_triage.grid_search.step_size
# Cycle through grid points
spotlist = []
for spa in range(a_min, a_max + 1, a_step):
for sph in range(h_min, h_max + 1, h_step):
sf_params.distl.minimum_spot_area = spa
sf_params.distl.minimum_spot_height = sph
sf_params.distl.minimum_signal_height = sph
# Perform spotfinding
Bragg_spots = self.run_distl(sf_params)
N_Bragg_spots = len(Bragg_spots)
if N_Bragg_spots > 0:
total_intensity = flex.sum(flex.double(Bragg_spots))
else:
total_intensity = 0
spotlist.append({
'bragg': N_Bragg_spots,
'ti': total_intensity,
'spa': spa,
'sph': sph
})
log_info.append('{:<{w}}: H = {:<2}, A = {:<2}, Bragg = {:<6.0f} '\
'total intensity = {:<12.4f}'.format(img_filename, sph, spa,
N_Bragg_spots, total_intensity, w = len(img_filename)))
# Pick best spotfinding result (highest total intensity seems to work for now
pick = sorted(spotlist, key=lambda j: j['ti'])[-1]
N_Bragg_spots = pick['bragg']
start_sph = pick['sph']
start_sih = pick['sph']
start_spa = pick['spa']
# ... using spotfinding without grid search
else:
# Set spotfinding params
sf_params.distl.minimum_spot_area = self.params.cctbx.grid_search.area_median
sf_params.distl.minimum_spot_height = self.params.cctbx.grid_search.height_median
sf_params.distl.minimum_signal_height = self.params.cctbx.grid_search.height_median
# Perform spotfinding
Bragg_spots = self.run_distl(sf_params)
# Extract spotfinding results
N_Bragg_spots = len(Bragg_spots)
start_sph = self.params.cctbx.grid_search.height_median
start_sih = self.params.cctbx.grid_search.height_median
start_spa = self.params.cctbx.grid_search.area_median
# Determine triage success
if N_Bragg_spots >= self.params.image_triage.min_Bragg_peaks:
log_info.append('ACCEPTED! Selected starting point:')
log_info.append('{:<{w}}: S = {:<2}, H = {:<2}, A = {:<2}, Bragg = {:<6.0f}'\
''.format(img_filename, start_sih, start_sph, start_spa,
N_Bragg_spots, w = len(img_filename)))
status = None
else:
log_info.append(
'REJECTED! ({} Bragg peaks found)'.format(N_Bragg_spots))
status = 'failed triage'
log_entry = "\n".join(log_info)
return status, log_entry, start_sph, start_spa
if len(detector) == 1:
# Image size only makes sense for monolithic detectors.
image_size = detector[0].get_image_size()
self.set_image_size(
w=image_size[0],
h=image_size[1])
pixel_size = detector[0].get_pixel_size()
for panel in detector:
pstest = panel.get_pixel_size()
assert pixel_size[0] == pixel_size[1] == pstest[0] == pstest[1]
self.set_detector_resolution(pixel_size[0])
try:
from spotfinder.command_line.signal_strength import master_params
params = master_params.extract()
self._raw.initialize_viewer_properties(params)
except Exception: pass # intentional
self._beam_center = None
self._integration = None
self._spots = None
self._color_scheme = None
#self.update_image()
#self.convert_to_bitmap()
def set_integration_results (self, integration) :
self._integration = integration
mp = integration['mapped_predictions']
print "%d spot predictions loaded" % mp.size()
print "max. resolution is %g" % integration['resolution']
def triage_image(self):
""" Performs a quick DISTL spotfinding without grid search.
"""
from spotfinder.command_line.signal_strength import master_params as sf_params
sf_params = sf_params.extract()
sf_params.distl.image = self.img
E = Empty()
E.argv=['Empty']
E.argv.append(sf_params.distl.image)
log_info = ['{}\n'.format(self.img)]
img_filename = os.path.basename(self.img)
# Perform spotfinding
# ... using spotfinding grid search
if self.params.image_triage.type == 'grid_search':
log_info.append('\n CCTBX TRIAGE grid search:')
# Determine grid search extent
a_min = self.params.image_triage.grid_search.area_min
a_max = self.params.image_triage.grid_search.area_max
a_step = (a_max - a_min) // self.params.image_triage.grid_search.step_size
h_min = self.params.image_triage.grid_search.height_min
h_max = self.params.image_triage.grid_search.height_max
h_step = (h_max - h_min) // self.params.image_triage.grid_search.step_size
# Cycle through grid points
spotlist = []
for spa in range(a_min, a_max + 1, a_step):
for sph in range(h_min, h_max + 1, h_step):
sf_params.distl.minimum_spot_area = spa
sf_params.distl.minimum_spot_height = sph
sf_params.distl.minimum_signal_height = sph
# Perform spotfinding
Bragg_spots = self.run_distl(sf_params)
N_Bragg_spots = len(Bragg_spots)
if N_Bragg_spots > 0:
total_intensity = flex.sum(flex.double(Bragg_spots))
else:
total_intensity = 0
spotlist.append({'bragg':N_Bragg_spots, 'ti':total_intensity,
'spa':spa, 'sph':sph})
log_info.append('{:<{w}}: H = {:<2}, A = {:<2}, Bragg = {:<6.0f} '\
'total intensity = {:<12.4f}'.format(img_filename, sph, spa,
N_Bragg_spots, total_intensity, w = len(img_filename)))
# Pick best spotfinding result (highest total intensity seems to work for now
pick = sorted(spotlist, key = lambda j: j['ti'])[-1]
N_Bragg_spots = pick['bragg']
start_sph = pick['sph']
start_sih = pick['sph']
start_spa = pick['spa']
# ... using spotfinding without grid search
else:
# Set spotfinding params
sf_params.distl.minimum_spot_area = self.params.cctbx.grid_search.area_median
sf_params.distl.minimum_spot_height = self.params.cctbx.grid_search.height_median
sf_params.distl.minimum_signal_height = self.params.cctbx.grid_search.height_median
# Perform spotfinding
Bragg_spots = self.run_distl(sf_params)
# Extract spotfinding results
N_Bragg_spots = len(Bragg_spots)
start_sph = self.params.cctbx.grid_search.height_median
start_sih = self.params.cctbx.grid_search.height_median
start_spa = self.params.cctbx.grid_search.area_median
# Determine triage success
if N_Bragg_spots >= self.params.image_triage.min_Bragg_peaks:
log_info.append('ACCEPTED! Selected starting point:')
log_info.append('{:<{w}}: S = {:<2}, H = {:<2}, A = {:<2}, Bragg = {:<6.0f}'\
''.format(img_filename, start_sih, start_sph, start_spa,
N_Bragg_spots, w = len(img_filename)))
status = None
else:
log_info.append('REJECTED!')
status = 'failed triage'
log_entry = "\n".join(log_info)
return status, log_entry, start_sph, start_spa