def __init__(self, address, out_dirname, out_basename,
binning=1, brightness=1.0, color_scheme=0,
format='png', **kwds):
"""The mod_dump_bitmap class constructor stores the parameters passed from
the pyana configuration file in instance variables.
@param address Full data source address of the DAQ device
@param out_dirname Directory portion of output image pathname
@param out_basename Filename prefix of output image pathname
"""
#define COLOR_GRAY 0
#define COLOR_RAINBOW 1
#define COLOR_HEAT 2
#define COLOR_INVERT 3
super(mod_dump_bitmap, self).__init__(address=address, **kwds)
self._basename = cspad_tbx.getOptString(out_basename)
self._dirname = cspad_tbx.getOptString(out_dirname)
self._binning = cspad_tbx.getOptInteger(binning)
self._brightness = cspad_tbx.getOptFloat(brightness)
self._color_scheme = cspad_tbx.getOptInteger(color_scheme)
self._format = cspad_tbx.getOptString(format)
self._ext = self._format.lower()
self._logger = logging.getLogger(self.__class__.__name__)
if (not os.path.isdir(self._dirname)):
os.makedirs(self._dirname)
def __init__(self, address, directory, beam_x = None, beam_y = None, template = None):
"""
@param address Address string XXX Que?!
@param directory Directory portion of the MAR image paths
@param beam_x Beam center x in pixels. Uses dxtbx beam center if not specified.
@param beam_y Beam center y in pixels. Uses dxtbx beam center if not specified.
@param template Simple template for filtering files processed. If @param template
is in the file name, the file is accepted
"""
self._logger = logging.getLogger(self.__class__.__name__)
self._logger.setLevel(logging.INFO)
# This is needed as a key for the image data.
self._address = cspad_tbx.getOptString(address)
self._directory = cspad_tbx.getOptString(directory)
# Save the beam center and image template
self._beam_x = cspad_tbx.getOptInteger(beam_x)
self._beam_y = cspad_tbx.getOptInteger(beam_y)
self._template = cspad_tbx.getOptString(template)
# At the moment, we cannot use multiprocessing for this anyway.
# This has to be an absolute path to the image.
self._path = None
self._mccd_name = None
def __init__(self,
address,
out_dirname,
out_basename,
binning=1,
brightness=1.0,
color_scheme=0,
format='png',
**kwds):
"""The mod_dump_bitmap class constructor stores the parameters passed from
the pyana configuration file in instance variables.
@param address Full data source address of the DAQ device
@param out_dirname Directory portion of output image pathname
@param out_basename Filename prefix of output image pathname
"""
#define COLOR_GRAY 0
#define COLOR_RAINBOW 1
#define COLOR_HEAT 2
#define COLOR_INVERT 3
super(mod_dump_bitmap, self).__init__(address=address, **kwds)
self._basename = cspad_tbx.getOptString(out_basename)
self._dirname = cspad_tbx.getOptString(out_dirname)
self._binning = cspad_tbx.getOptInteger(binning)
self._brightness = cspad_tbx.getOptFloat(brightness)
self._color_scheme = cspad_tbx.getOptInteger(color_scheme)
self._format = cspad_tbx.getOptString(format)
self._ext = self._format.lower()
self._logger = logging.getLogger(self.__class__.__name__)
if (not os.path.isdir(self._dirname)):
os.makedirs(self._dirname)
def __init__(self,
address,
n_collate=None,
n_update=120,
common_mode_correction="none",
wait=None,
photon_counting=False,
sigma_scaling=False,
**kwds):
"""The mod_view class constructor XXX.
@param address Full data source address of the DAQ device
@param calib_dir Directory with calibration information
@param common_mode_correction The type of common mode correction to apply
@param dark_path Path to input average dark image
@param dark_stddev Path to input standard deviation dark
image, required if @p dark_path is given
@param wait Minimum time (in seconds) to wait on the current
image before moving on to the next
@param n_collate Number of shots to average, or <= 0 to
average all shots
@param n_update Number of shots between updates
"""
super(mod_view,
self).__init__(address=address,
common_mode_correction=common_mode_correction,
**kwds)
self.detector = cspad_tbx.address_split(address)[0]
self.nvalid = 0
self.ncollate = cspad_tbx.getOptInteger(n_collate)
self.nupdate = cspad_tbx.getOptInteger(n_update)
self.photon_counting = cspad_tbx.getOptBool(photon_counting)
self.sigma_scaling = cspad_tbx.getOptBool(sigma_scaling)
if (self.ncollate is None):
self.ncollate = self.nupdate
if (self.ncollate > self.nupdate):
self.ncollate = self.nupdate
self.logger.warning("n_collate capped to %d" % self.nupdate)
linger = True # XXX Make configurable
wait = cspad_tbx.getOptFloat(wait)
# Create a managed FIFO queue shared between the viewer and the
# current process. The current process will produce images, while
# the viewer process will consume them.
manager = multiprocessing.Manager()
self._queue = manager.Queue()
self._proc = multiprocessing.Process(target=_xray_frame_process,
args=(self._queue, linger, wait))
self._proc.start()
self.n_shots = 0
def __init__(self,
address,
n_collate = None,
n_update = 120,
common_mode_correction = "none",
wait=None,
photon_counting=False,
sigma_scaling=False,
**kwds):
"""The mod_view class constructor XXX.
@param address Full data source address of the DAQ device
@param calib_dir Directory with calibration information
@param common_mode_correction The type of common mode correction to apply
@param dark_path Path to input average dark image
@param dark_stddev Path to input standard deviation dark
image, required if @p dark_path is given
@param wait Minimum time (in seconds) to wait on the current
image before moving on to the next
@param n_collate Number of shots to average, or <= 0 to
average all shots
@param n_update Number of shots between updates
"""
super(mod_view, self).__init__(
address=address,
common_mode_correction=common_mode_correction,
**kwds)
self.detector = cspad_tbx.address_split(address)[0]
self.nvalid = 0
self.ncollate = cspad_tbx.getOptInteger(n_collate)
self.nupdate = cspad_tbx.getOptInteger(n_update)
self.photon_counting = cspad_tbx.getOptBool(photon_counting)
self.sigma_scaling = cspad_tbx.getOptBool(sigma_scaling)
if (self.ncollate is None):
self.ncollate = self.nupdate
if (self.ncollate > self.nupdate):
self.ncollate = self.nupdate
self.logger.warning("n_collate capped to %d" % self.nupdate)
linger = True # XXX Make configurable
wait = cspad_tbx.getOptFloat(wait)
# Create a managed FIFO queue shared between the viewer and the
# current process. The current process will produce images, while
# the viewer process will consume them.
manager = multiprocessing.Manager()
self._queue = manager.Queue()
self._proc = multiprocessing.Process(
target=_xray_frame_process, args=(self._queue, linger, wait))
self._proc.start()
self.n_shots = 0
def __init__(self,
address,
pickle_dirname=".",
pickle_basename="hist",
roi=None,
hist_min=None,
hist_max=None,
n_slots=None,
**kwds):
"""
@param address Address string XXX Que?!
@param pickle_dirname Directory portion of output pickle file
XXX mean, mu?
@param pickle_basename Filename prefix of output pickle file
image XXX mean, mu?
@param calib_dir Directory with calibration information
@param dark_path Path to input dark image
@param dark_stddev Path to input dark standard deviation
"""
super(pixel_histograms, self).__init__(address=address, **kwds)
self.pickle_dirname = cspad_tbx.getOptString(pickle_dirname)
self.pickle_basename = cspad_tbx.getOptString(pickle_basename)
self.hist_min = cspad_tbx.getOptFloat(hist_min)
self.hist_max = cspad_tbx.getOptFloat(hist_max)
self.n_slots = cspad_tbx.getOptInteger(n_slots)
self.histograms = {}
self.dimensions = None
self.roi = cspad_tbx.getOptROI(roi)
self.values = flex.long()
self.sigma_scaling = False
if self.hist_min is None: self.hist_min = -50
if self.hist_max is None: self.hist_max = 150
if self.n_slots is None: self.n_slots = 200
def __init__(self,
address,
target_energy,
angle=0,
n_collate = None,
n_update = 1,
threshold= 0.4,
filter="False",
clean="False",
mode="E1",
peak_ratio=0.17,
common_mode_correction = "none",
**kwds):
"""
@param address Address string XXX Que?!
@param dirname Directory portion of output pickle file
@param basename Filename prefix of output pickle file
@param dark_path Path to input dark image
@param dark_stddev Path to input dark standard deviation
"""
super(mod_spectra, self).__init__(
address=address,
common_mode_correction=common_mode_correction,
**kwds
)
self.threshold=cspad_tbx.getOptFloat(threshold)
self.peak_ratio=cspad_tbx.getOptFloat(peak_ratio)
self.angle=cspad_tbx.getOptFloat(angle)
self.nv = 0
self.collate=None
self.data=None
self.ncollate = cspad_tbx.getOptInteger(n_collate)
self.nvalid = 0
self.n_shots = 0
self.nupdate = cspad_tbx.getOptInteger(n_update)
self.filter=filter
self.clean=clean
self.target=map(float,target_energy.split(","))
self.mode=mode
self.all=[]
if (self.ncollate is None):
self.ncollate = self.nupdate
if (self.ncollate > self.nupdate):
self.ncollate = self.nupdate
self.logger.warning("n_collate capped to %d" % self.nupdate)
def __init__(self,
address,
pickle_dirname=".",
pickle_basename="hist",
roi=None,
hist_min=None,
hist_max=None,
n_slots=None,
**kwds):
"""
@param address Address string XXX Que?!
@param pickle_dirname Directory portion of output pickle file
XXX mean, mu?
@param pickle_basename Filename prefix of output pickle file
image XXX mean, mu?
@param calib_dir Directory with calibration information
@param dark_path Path to input dark image
@param dark_stddev Path to input dark standard deviation
"""
super(pixel_histograms, self).__init__(
address=address,
**kwds
)
self.pickle_dirname = cspad_tbx.getOptString(pickle_dirname)
self.pickle_basename = cspad_tbx.getOptString(pickle_basename)
self.hist_min = cspad_tbx.getOptFloat(hist_min)
self.hist_max = cspad_tbx.getOptFloat(hist_max)
self.n_slots = cspad_tbx.getOptInteger(n_slots)
self.histograms = {}
self.dimensions = None
self.roi = cspad_tbx.getOptROI(roi)
self.values = flex.long()
self.sigma_scaling = False
if self.hist_min is None: self.hist_min = -50
if self.hist_max is None: self.hist_max = 150
if self.n_slots is None: self.n_slots = 200
def __init__(self,
address,
calib_dir=None,
common_mode_correction="none",
photon_threshold=None,
two_photon_threshold=None,
dark_path=None,
dark_stddev=None,
mask_path=None,
gain_map_path=None,
gain_map_level=None,
cache_image=True,
roi=None,
laser_1_status=None,
laser_4_status=None,
laser_wait_time=None,
override_beam_x=None,
override_beam_y=None,
bin_size=None,
crop_rayonix=False,
**kwds):
"""The common_mode_correction class constructor stores the
parameters passed from the pyana configuration file in instance
variables.
@param address Full data source address of the DAQ device
@param calib_dir Directory with calibration information
@param common_mode_correction The type of common mode correction to apply
@param dark_path Path to input average dark image
@param dark_stddev Path to input standard deviation dark
image, required if @p dark_path is given
@param mask_path Path to input mask. Pixels to mask out should be set to -2
@param gain_map_path Path to input gain map. Multiplied times the image.
@param gain_map_level If set, all the '1' pixels in the gain_map are set to this multiplier
and all the '0' pixels in the gain_map are set to '1'. If not set,
use the values in the gain_map directly
@param laser_1_status 0 or 1 to indicate that the laser should be off or on respectively
@param laser_4_status 0 or 1 to indicate that the laser should be off or on respectively
@param laser_wait_time Length of time in milliseconds to wait after a laser
change of status to begin accepting images again.
(rejection of images occurs immediately after status
change).
@param override_beam_x override value for x coordinate of beam center in pixels
@param override_beam_y override value for y coordinate of beam center in pixels
@param bin_size bin size for rayonix detector used to determin pixel size
@param crop_rayonix whether to crop rayonix images such that image center is the beam center
"""
# Cannot use the super().__init__() construct here, because
# common_mode_correction refers to the argument, and not the
# class.
mod_event_info.__init__(self, address=address, **kwds)
# The paths will be substituted in beginjob(), where evt and env
# are available.
self._dark_path = cspad_tbx.getOptString(dark_path)
self._dark_stddev_path = cspad_tbx.getOptString(dark_stddev)
self._gain_map_path = cspad_tbx.getOptString(gain_map_path)
self._mask_path = cspad_tbx.getOptString(mask_path)
self.gain_map_level = cspad_tbx.getOptFloat(gain_map_level)
self.common_mode_correction = cspad_tbx.getOptString(common_mode_correction)
self.photon_threshold = cspad_tbx.getOptFloat(photon_threshold)
self.two_photon_threshold = cspad_tbx.getOptFloat(two_photon_threshold)
self.cache_image = cspad_tbx.getOptBool(cache_image)
self.filter_laser_1_status = cspad_tbx.getOptInteger(laser_1_status)
self.filter_laser_4_status = cspad_tbx.getOptInteger(laser_4_status)
if self.filter_laser_1_status is not None:
self.filter_laser_1_status = bool(self.filter_laser_1_status)
if self.filter_laser_4_status is not None:
self.filter_laser_4_status = bool(self.filter_laser_4_status)
self.filter_laser_wait_time = cspad_tbx.getOptInteger(laser_wait_time)
self.override_beam_x = cspad_tbx.getOptFloat(override_beam_x)
self.override_beam_y = cspad_tbx.getOptFloat(override_beam_y)
self.bin_size = cspad_tbx.getOptInteger(bin_size)
self.crop_rayonix = cspad_tbx.getOptBool(crop_rayonix)
self.cspad_img = None # The current image - set by self.event()
self.sum_common_mode = 0
self.sumsq_common_mode = 0
self.roi = cspad_tbx.getOptROI(roi) # used to ignore the signal region in chebyshev fit
assert self.common_mode_correction in \
("gaussian", "mean", "median", "mode", "none", "chebyshev")
# Get and parse metrology.
self.sections = None
device = cspad_tbx.address_split(self.address)[2]
if device == 'Andor':
self.sections = [] # XXX FICTION
elif device == 'Cspad':
if self.address == 'XppGon-0|Cspad-0':
self.sections = [] # Not used for XPP
else:
self.sections = calib2sections(cspad_tbx.getOptString(calib_dir))
elif device == 'Cspad2x2':
# There is no metrology information for the Sc1 detector, so
# make it up. The sections are rotated by 90 degrees with
# respect to the "standing up" convention.
self.sections = [[Section(90, (185 / 2 + 0, (2 * 194 + 3) / 2)),
Section(90, (185 / 2 + 185, (2 * 194 + 3) / 2))]]
elif device == 'marccd':
self.sections = [] # XXX FICTION
elif device == 'pnCCD':
self.sections = [] # XXX FICTION
elif device == 'Rayonix':
self.sections = [] # XXX FICTION
elif device == 'Opal1000':
self.sections = [] # XXX FICTION
if self.sections is None:
raise RuntimeError("Failed to load metrology")
def __init__(self,
address,
dispatch=None,
integration_dirname=None,
integration_basename=None,
out_dirname=None,
out_basename=None,
roi=None,
distl_min_peaks=None,
distl_flags=None,
threshold=None,
xtal_target=None,
negate_hits=False,
trial_id=None,
db_logging=False,
progress_logging=False,
sql_buffer_size=1,
db_host=None,
db_name=None,
db_table_name=None,
db_experiment_tag=None,
db_user=None,
db_password=None,
db_tags=None,
trial=None,
rungroup_id=None,
db_version='v1',
**kwds):
"""The mod_hitfind class constructor stores the parameters passed
from the pyana configuration file in instance variables. All
parameters, except @p address are optional, and hence need not be
defined in pyana.cfg.
@param address Full data source address of the DAQ device
@param dispatch Function to call
@param integration_dirname
Directory portion of output integration file
pathname
@param integration_basename
Filename prefix of output integration file
pathname
@param out_dirname Directory portion of output image pathname
@param out_basename Filename prefix of output image pathname
@param roi Region of interest for thresholding, on the
form fast_low:fast_high,slow_low:slow_high
@param threshold Minimum value in region of interest to pass
"""
super(mod_hitfind, self).__init__(address=address, **kwds)
self.m_dispatch = cspad_tbx.getOptString(dispatch)
self.m_integration_basename = cspad_tbx.getOptString(
integration_basename)
self.m_integration_dirname = cspad_tbx.getOptString(
integration_dirname)
self.m_out_basename = cspad_tbx.getOptString(out_basename)
self.m_out_dirname = cspad_tbx.getOptString(out_dirname)
self.m_distl_min_peaks = cspad_tbx.getOptInteger(distl_min_peaks)
self.m_distl_flags = cspad_tbx.getOptStrings(distl_flags)
self.m_threshold = cspad_tbx.getOptInteger(threshold)
self.m_xtal_target = cspad_tbx.getOptString(xtal_target)
self.m_negate_hits = cspad_tbx.getOptBool(negate_hits)
self.m_trial_id = cspad_tbx.getOptInteger(trial_id)
self.m_db_logging = cspad_tbx.getOptBool(db_logging)
self.m_progress_logging = cspad_tbx.getOptBool(progress_logging)
self.m_sql_buffer_size = cspad_tbx.getOptInteger(sql_buffer_size)
self.m_db_host = cspad_tbx.getOptString(db_host)
self.m_db_name = cspad_tbx.getOptString(db_name)
self.m_db_table_name = cspad_tbx.getOptString(db_table_name)
self.m_db_experiment_tag = cspad_tbx.getOptString(db_experiment_tag)
self.m_db_user = cspad_tbx.getOptString(db_user)
self.m_db_password = cspad_tbx.getOptString(db_password)
self.m_db_tags = cspad_tbx.getOptString(db_tags)
self.m_trial = cspad_tbx.getOptInteger(trial)
self.m_rungroup_id = cspad_tbx.getOptInteger(rungroup_id)
self.m_db_version = cspad_tbx.getOptString(db_version)
# A ROI should not contain any ASIC boundaries, as these are
# noisy. Hence circular ROI:s around the beam centre are probably
# not such a grand idea.
self.m_roi = cspad_tbx.getOptROI(roi)
# Verify that dist_min_peaks is either "restrictive" or
# "permissive", but not both. ^ is the logical xor operator
if self.m_distl_min_peaks is not None:
if (not (('permissive' in self.m_distl_flags) ^
('restrictive' in self.m_distl_flags))):
raise RuntimeError("""Sorry, with the distl_min_peaks option,
distl_flags must be set to 'permissive' or 'restrictive'.""")
if (self.m_roi is not None):
raise RuntimeError("""Sorry, either specify region of interest
(roi) or distl_min_peaks, but not both.""")
if self.m_db_logging:
self.buffered_sql_entries = []
assert self.m_sql_buffer_size >= 1
if self.m_progress_logging:
if self.m_db_version == 'v1':
self.buffered_progress_entries = []
assert self.m_sql_buffer_size >= 1
self.isoforms = {}
elif self.m_db_version == 'v2':
from xfel.ui import db_phil_str
from libtbx.phil import parse
extra_phil = """
input {
trial = None
.type = int
trial_id = None
.type = int
rungroup = None
.type = int
}
"""
self.db_params = parse(db_phil_str + extra_phil).extract()
self.db_params.experiment_tag = self.m_db_experiment_tag
self.db_params.db.host = self.m_db_host
self.db_params.db.name = self.m_db_name
self.db_params.db.user = self.m_db_user
self.db_params.db.password = self.m_db_password
self.db_params.input.trial = self.m_trial
self.db_params.input.rungroup = self.m_rungroup_id
if self.m_db_tags is None:
self.m_db_tags = ""
def __init__(self,
address,
dispatch = None,
integration_dirname = None,
integration_basename = None,
out_dirname = None,
out_basename = None,
roi = None,
distl_min_peaks = None,
distl_flags = None,
threshold = None,
xtal_target = None,
negate_hits = False,
trial_id = None,
db_logging = False,
progress_logging = False,
sql_buffer_size = 1,
db_host = None,
db_name = None,
db_table_name = None,
db_experiment_tag = None,
db_user = None,
db_password = None,
db_tags = None,
rungroup_id = None,
**kwds):
"""The mod_hitfind class constructor stores the parameters passed
from the pyana configuration file in instance variables. All
parameters, except @p address are optional, and hence need not be
defined in pyana.cfg.
@param address Full data source address of the DAQ device
@param dispatch Function to call
@param integration_dirname
Directory portion of output integration file
pathname
@param integration_basename
Filename prefix of output integration file
pathname
@param out_dirname Directory portion of output image pathname
@param out_basename Filename prefix of output image pathname
@param roi Region of interest for thresholding, on the
form fast_low:fast_high,slow_low:slow_high
@param threshold Minimum value in region of interest to pass
"""
super(mod_hitfind, self).__init__(address=address, **kwds)
self.m_dispatch = cspad_tbx.getOptString(dispatch)
self.m_integration_basename = cspad_tbx.getOptString(integration_basename)
self.m_integration_dirname = cspad_tbx.getOptString(integration_dirname)
self.m_out_basename = cspad_tbx.getOptString(out_basename)
self.m_out_dirname = cspad_tbx.getOptString(out_dirname)
self.m_distl_min_peaks = cspad_tbx.getOptInteger(distl_min_peaks)
self.m_distl_flags = cspad_tbx.getOptStrings(distl_flags)
self.m_threshold = cspad_tbx.getOptInteger(threshold)
self.m_xtal_target = cspad_tbx.getOptString(xtal_target)
self.m_negate_hits = cspad_tbx.getOptBool(negate_hits)
self.m_trial_id = cspad_tbx.getOptInteger(trial_id)
self.m_db_logging = cspad_tbx.getOptBool(db_logging)
self.m_progress_logging = cspad_tbx.getOptBool(progress_logging)
self.m_sql_buffer_size = cspad_tbx.getOptInteger(sql_buffer_size)
self.m_db_host = cspad_tbx.getOptString(db_host)
self.m_db_name = cspad_tbx.getOptString(db_name)
self.m_db_table_name = cspad_tbx.getOptString(db_table_name)
self.m_db_experiment_tag = cspad_tbx.getOptString(db_experiment_tag)
self.m_db_user = cspad_tbx.getOptString(db_user)
self.m_db_password = cspad_tbx.getOptString(db_password)
self.m_db_tags = cspad_tbx.getOptString(db_tags)
self.m_rungroup_id = cspad_tbx.getOptInteger(rungroup_id)
# A ROI should not contain any ASIC boundaries, as these are
# noisy. Hence circular ROI:s around the beam centre are probably
# not such a grand idea.
self.m_roi = cspad_tbx.getOptROI(roi)
# Verify that dist_min_peaks is either "restrictive" or
# "permissive", but not both. ^ is the logical xor operator
if self.m_distl_min_peaks is not None:
if (not (('permissive' in self.m_distl_flags) ^
('restrictive' in self.m_distl_flags))):
raise RuntimeError("""Sorry, with the distl_min_peaks option,
distl_flags must be set to 'permissive' or 'restrictive'.""")
if (self.m_roi is not None):
raise RuntimeError("""Sorry, either specify region of interest
(roi) or distl_min_peaks, but not both.""")
if self.m_db_logging:
self.buffered_sql_entries = []
assert self.m_sql_buffer_size >= 1
if self.m_progress_logging:
self.buffered_progress_entries = []
assert self.m_sql_buffer_size >= 1
self.isoforms = {}
if self.m_db_tags is None:
self.m_db_tags = ""
