def dump(self, filename=None):
"""
Reads all parameters and returns them as a python dictionary
@param filename: dump the content to a file as a JSON string
@return: dictionary
"""
logger.debug("InputWidget.dump")
res = {}
res["wavelength"] = float_(self.wavelength.text()) * 1e-10
calibrant = {"do_dspacing": bool(self.do_dspacing.isChecked())}
calibrant["file"] = str_(self.dspacing.text()).strip()
calibrant["calibrant"] = str_(self.detector.currentText())
res["calibrant"] = calibrant
detector = {"name": str_(self.detector.currentText()),
"file":str(self.detectorfile.text()).strip(),
"pixel1": float_(self.pixel1.text()),
"pixel2":float_(self.pixel2.text())}
res[detector] = detector
data = {"file": str_(self.data_file.text()).strip(),
"hdf5": str_(self.data_file_hdf5.text()).strip() or None}
res["data"] = data
mask = {"file": str_(self.mask_file.text()).strip(),
"hdf5": str_(self.mask_file_hdf5.text()).strip() or None,
"apply": bool(self.do_mask.isChecked())}
res["mask"] = mask
dark = {"file": str_(self.dark_current.text()).strip(),
"hdf5": str_(self.dark_file_hdf5.text()).strip() or None,
"apply": bool(self.do_dark.isChecked())}
res["dark"] = dark
flat = {"file": str_(self.flat_field.text()).strip(),
"hdf5": str_(self.flat_file_hdf5.text()).strip() or None,
"apply": bool(self.do_flat.isChecked())}
res["flat"] = flat
try:
with open(filename, "w") as myFile:
json.dump(res, myFile, indent=4)
except IOError as error:
logger.error("Error while saving config: %s" % error)
else:
logger.debug("Saved")
return res
def proceed(self):
with self._sem:
out = None
self.dump()
logger.debug("Let's work a bit")
self.set_ai()
# Default Keyword arguments
kwarg = {"unit": "2th_deg",
"dummy": None,
"delta_dummy": None,
"method": "lut",
"polarization_factor":0,
"filename": None,
"safe": False,
}
if self.q_nm.isChecked():
kwarg["unit"] = "q_nm^-1"
elif self.tth_deg.isChecked():
kwarg["unit"] = "2th_deg"
elif self.r_mm.isChecked():
kwarg["unit"] = "r_mm"
else:
logger.warning("Undefined unit !!! falling back on 2th_deg")
if bool(self.do_dummy.isChecked()):
kwarg["dummy"] = float_(self.val_dummy.text())
delta_dummy = str(self.delta_dummy.text())
if delta_dummy:
kwarg["delta_dummy"] = float(delta_dummy)
else:
kwarg["delta_dummy"] = None
if bool(self.do_polarization.isChecked()):
kwarg["polarization_factor"] = float(self.polarization_factor.value())
kwarg["nbPt_rad"] = int(str(self.rad_pt.text()).strip())
if self.do_2D.isChecked():
kwarg["nbPt_azim"] = int(str(self.rad_pt.text()).strip())
if self.do_OpenCL.isChecked():
platform = ocl.get_platform(self.platform.currentText())
pid = platform.id
did = platform.get_device(self.device.currentText()).id
if (pid is not None) and (did is not None):
kwarg["method"] = "lut_ocl_%i,%i" % (pid, did)
else:
kwarg["method"] = "lut_ocl"
if self.do_radial_range:
try:
rad_min = float_(self.radial_range_min.text())
rad_max = float_(self.radial_range_max.text())
except ValueError as error:
logger.error("error in parsing radial range: %s" % error)
else:
kwarg["radial_range"] = (rad_min, rad_max)
if self.do_azimuthal_range:
try:
azim_min = float_(self.azimuth_range_min.text())
azim_max = float_(self.azimuth_range_max.text())
except ValueError as error:
logger.error("error in parsing azimuthal range: %s" % error)
else:
kwarg["azimuth_range"] = (azim_min, azim_max)
logger.info("Parameters for integration:%s%s" % (os.linesep,
os.linesep.join(["\t%s:\t%s" % (k, v) for k, v in kwarg.items()])))
logger.debug("processing %s" % self.input_data)
start_time = time.time()
if self.input_data in [None, []]:
logger.warning("No input data to process")
return
elif "ndim" in dir(self.input_data) and (self.input_data.ndim == 3):
# We have a numpy array of dim3
if "nbPt_azim" in kwarg:
out = numpy.zeros((self.input_data.shape[0], kwarg["nbPt_azim"], kwarg["nbPt_rad"]), dtype=numpy.float32)
for i in range(self.input_data.shape[0]):
self.progressBar.setValue(100.0 * i / self.input_data.shape[0])
kwarg["data"] = self.input_data[i]
out[i] = self.ai.integrate2d(kwarg)[0]
else:
out = numpy.zeros((self.input_data.shape[0], kwarg["nbPt_rad"]), dtype=numpy.float32)
for i in range(self.input_data.shape[0]):
self.progressBar.setValue(100.0 * i / self.input_data.shape[0])
kwarg["data"] = self.input_data[i]
out[i] = self.ai.integrate1d(**kwarg)[1]
elif "__len__" in dir(self.input_data):
out = []
for i, item in enumerate(self.input_data):
self.progressBar.setValue(100.0 * i / len(self.input_data))
logger.debug("processing %s" % item)
if (type(item) in types.StringTypes) and op.exists(item):
kwarg["data"] = fabio.open(item).data
if "nbPt_azim" in kwarg:
kwarg["filename"] = op.splitext(item)[0] + ".azim"
else:
kwarg["filename"] = op.splitext(item)[0] + ".dat"
else:
logger.warning("item is not a file ... guessing it is a numpy array")
kwarg["data"] = item
kwarg["filename"] = None
if "nbPt_azim" in kwarg:
out.append(self.ai.integrate2d(**kwarg)[0])
else:
out.append(self.ai.integrate1d(**kwarg)[0])
logger.info("Processing Done in %.3fs !" % (time.time() - start_time))
self.progressBar.setValue(100)
self.die()
return out
def dump(self, filename=".azimint.json"):
"""
Dump the status of the current widget to a file in JSON
@param filename: path where to save the config
@type filename: str
"""
print "Dump!"
to_save = { "poni": str(self.poni.text()).strip(),
"detector": str(self.detector.currentText()).lower(),
"wavelength":float_(self.wavelength.text()),
"splineFile":str(self.splineFile.text()).strip(),
"pixel1": float_(self.pixel1.text()),
"pixel2":float_(self.pixel2.text()),
"dist":float_(self.dist.text()),
"poni1":float_(self.poni1.text()).strip(),
"poni2":float_(self.poni2.text()).strip(),
"rot1":float_(self.rot1.text()).strip(),
"rot2":float_(self.rot2.text()).strip(),
"rot3":float_(self.rot3.text()).strip(),
"do_dummy": bool(self.do_dummy.isChecked()),
"do_mask": bool(self.do_mask.isChecked()),
"do_dark": bool(self.do_dark.isChecked()),
"do_flat": bool(self.do_flat.isChecked()),
"do_polarization":bool(self.do_polarization.isChecked()),
"val_dummy":float_(self.val_dummy.text()).strip(),
"delta_dummy":float_(self.delta_dummy.text()).strip(),
"mask_file":str(self.mask_file.text()).strip(),
"dark_current":str(self.dark_current.text()).strip(),
"flat_field":str(self.flat_field.text()).strip(),
"polarization_factor":float_(self.polarization_factor.value()),
"rad_pt":int_(self.rad_pt.text()),
"do_2D":bool(self.do_2D.isChecked()),
"azim_pt":int_(self.rad_pt.text()),
"chi_discontinuity_at_0": bool(self.chi_discontinuity_at_0.isChecked()),
"do_radial_range": bool(self.do_radial_range.isChecked()),
"do_azimuthal_range": bool(self.do_azimuthal_range.isChecked()),
"radial_range_min":float_(self.radial_range_min.text()),
"radial_range_max":float_(self.radial_range_max.text()),
"azimuth_range_min":float_(self.azimuth_range_min.text()),
"azimuth_range_max":float_(self.azimuth_range_max.text()),
}
if self.q_nm.isChecked():
to_save["unit"] = "q_nm^-1"
elif self.tth_deg.isChecked():
to_save["unit"] = "2th_deg"
elif self.r_mm.isChecked():
to_save["unit"] = "r_mm"
with open(filename, "w") as myFile:
json.dump(to_save, myFile, indent=4)
logger.debug("Saved")
def dump(self, filename=None):
"""
Reads all parameters and returns them as a python dictionary
@param filename: dump the content to a file as a JSON string
@return: dictionary
"""
logger.debug("InputWidget.dump")
res = {}
res["wavelength"] = float_(self.wavelength.text()) * 1e-10
calibrant = {"do_dspacing": bool(self.do_dspacing.isChecked())}
calibrant["file"] = str_(self.dspacing.text()).strip()
calibrant["calibrant"] = str_(self.detector.currentText())
res["calibrant"] = calibrant
detector = {
"name": str_(self.detector.currentText()),
"file": str(self.detectorfile.text()).strip(),
"pixel1": float_(self.pixel1.text()),
"pixel2": float_(self.pixel2.text())
}
res[detector] = detector
data = {
"file": str_(self.data_file.text()).strip(),
"hdf5": str_(self.data_file_hdf5.text()).strip() or None
}
res["data"] = data
mask = {
"file": str_(self.mask_file.text()).strip(),
"hdf5": str_(self.mask_file_hdf5.text()).strip() or None,
"apply": bool(self.do_mask.isChecked())
}
res["mask"] = mask
dark = {
"file": str_(self.dark_current.text()).strip(),
"hdf5": str_(self.dark_file_hdf5.text()).strip() or None,
"apply": bool(self.do_dark.isChecked())
}
res["dark"] = dark
flat = {
"file": str_(self.flat_field.text()).strip(),
"hdf5": str_(self.flat_file_hdf5.text()).strip() or None,
"apply": bool(self.do_flat.isChecked())
}
res["flat"] = flat
try:
with open(filename, "w") as myFile:
json.dump(res, myFile, indent=4)
except IOError as error:
logger.error("Error while saving config: %s" % error)
else:
logger.debug("Saved")
return res
def proceed(self):
with self._sem:
out = None
self.dump()
logger.debug("Let's work a bit")
self.set_ai()
# Default Keyword arguments
kwarg = {
"unit": "2th_deg",
"dummy": None,
"delta_dummy": None,
"method": "lut",
"polarization_factor": None,
"filename": None,
"safe": False,
}
if self.q_nm.isChecked():
kwarg["unit"] = "q_nm^-1"
elif self.tth_deg.isChecked():
kwarg["unit"] = "2th_deg"
elif self.tth_rad.isChecked():
kwarg["unit"] = "2th_rad"
elif self.r_mm.isChecked():
kwarg["unit"] = "r_mm"
elif self.q_A.isChecked():
kwarg["unit"] = "q_A^-1"
else:
logger.warning("Undefined unit !!! falling back on 2th_deg")
kwarg["correctSolidAngle"] = bool(self.do_solid_angle.isChecked())
if bool(self.do_dummy.isChecked()):
kwarg["dummy"] = float_(self.val_dummy.text())
delta_dummy = str(self.delta_dummy.text())
if delta_dummy:
kwarg["delta_dummy"] = float(delta_dummy)
else:
kwarg["delta_dummy"] = None
if bool(self.do_polarization.isChecked()):
kwarg["polarization_factor"] = float(
self.polarization_factor.value())
else:
kwarg["polarization_factor"] = None
kwarg["nbPt_rad"] = int(str(self.rad_pt.text()).strip())
if self.do_2D.isChecked():
kwarg["nbPt_azim"] = int(str(self.azim_pt.text()).strip())
if self.do_OpenCL.isChecked():
platform = ocl.get_platform(self.platform.currentText())
pid = platform.id
did = platform.get_device(self.device.currentText()).id
if (pid is not None) and (did is not None):
kwarg["method"] = "lut_ocl_%i,%i" % (pid, did)
else:
kwarg["method"] = "lut_ocl"
if self.do_radial_range.isChecked():
try:
rad_min = float_(self.radial_range_min.text())
rad_max = float_(self.radial_range_max.text())
except ValueError as error:
logger.error("error in parsing radial range: %s" % error)
else:
kwarg["radial_range"] = (rad_min, rad_max)
if kwarg["radial_range"] == (None, None):
kwarg["radial_range"] = None
if self.do_azimuthal_range.isChecked():
try:
azim_min = float_(self.azimuth_range_min.text())
azim_max = float_(self.azimuth_range_max.text())
except ValueError as error:
logger.error("error in parsing azimuthal range: %s" %
error)
else:
kwarg["azimuth_range"] = (azim_min, azim_max)
if kwarg["azimuth_range"] == (None, None):
kwarg["azimuth_range"] = None
if self.do_poisson.isChecked():
kwarg["error_model"] = "poisson"
else:
kwarg["error_model"] = None
logger.info("Parameters for integration:%s%s" %
(os.linesep,
os.linesep.join(
["\t%s:\t%s" % (k, v)
for k, v in kwarg.items()])))
logger.debug("processing %s" % self.input_data)
start_time = time.time()
if self.input_data in [None, []]:
logger.warning("No input data to process")
return
elif "ndim" in dir(self.input_data) and (self.input_data.ndim
== 3):
# We have a numpy array of dim3
if "nbPt_azim" in kwarg:
out = numpy.zeros((self.input_data.shape[0],
kwarg["nbPt_azim"], kwarg["nbPt_rad"]),
dtype=numpy.float32)
for i in range(self.input_data.shape[0]):
self.progressBar.setValue(100.0 * i /
self.input_data.shape[0])
kwarg["data"] = self.input_data[i]
out[i] = self.ai.integrate2d(**kwarg)[0]
else:
if "nbPt_rad" in kwarg: # convert nbPt_rad -> nbPt
kwarg["nbPt"] = kwarg.pop("nbPt_rad")
out = numpy.zeros(
(self.input_data.shape[0], kwarg["nbPt"]),
dtype=numpy.float32)
for i in range(self.input_data.shape[0]):
self.progressBar.setValue(100.0 * i /
self.input_data.shape[0])
kwarg["data"] = self.input_data[i]
out[i] = self.ai.integrate1d(**kwarg)[1]
elif "__len__" in dir(self.input_data):
out = []
if self.hdf5_path:
import h5py
hdf5 = h5py.File(self.output_path)
if self.fast_dim:
if "nbPt_azim" in kwarg:
ds = hdf5.create_dataset(
"diffraction",
(1, self.fast_dim, kwarg["nbPt_azim"],
kwarg["nbPt_rad"]),
dtype=numpy.float32,
chunks=(1, self.fast_dim, kwarg["nbPt_azim"],
kwarg["nbPt_rad"]),
maxshape=(None, self.fast_dim,
kwarg["nbPt_azim"],
kwarg["nbPt_rad"]))
else:
ds = hdf5.create_dataset(
"diffraction",
(1, self.fast_dim, kwarg["nbPt_rad"]),
dtype=numpy.float32,
chunks=(1, self.fast_dim, kwarg["nbPt_rad"]),
maxshape=(None, self.fast_dim,
kwarg["nbPt_rad"]))
else:
if "nbPt_azim" in kwarg:
ds = hdf5.create_dataset(
"diffraction",
(1, kwarg["nbPt_azim"], kwarg["nbPt_rad"]),
dtype=numpy.float32,
chunks=(1, kwarg["nbPt_azim"],
kwarg["nbPt_rad"]),
maxshape=(None, kwarg["nbPt_azim"],
kwarg["nbPt_rad"]))
else:
ds = hdf5.create_dataset(
"diffraction", (1, kwarg["nbPt_rad"]),
dtype=numpy.float32,
chunks=(1, kwarg["nbPt_rad"]),
maxshape=(None, kwarg["nbPt_rad"]))
for i, item in enumerate(self.input_data):
self.progressBar.setValue(100.0 * i / len(self.input_data))
logger.debug("processing %s" % item)
if (type(item) in types.StringTypes) and op.exists(item):
kwarg["data"] = fabio.open(item).data
if self.hdf5_path is None:
if self.output_path and op.isdir(self.output_path):
outpath = op.join(
self.output_path,
op.splitext(op.basename(item))[0])
else:
outpath = op.splitext(item)[0]
if "nbPt_azim" in kwarg:
kwarg["filename"] = outpath + ".azim"
else:
kwarg["filename"] = outpath + ".dat"
else:
logger.warning(
"item is not a file ... guessing it is a numpy array"
)
kwarg["data"] = item
kwarg["filename"] = None
if kwarg.get("nbPt_azim"):
res = self.ai.integrate2d(**kwarg)[0]
else:
if "nbPt_rad" in kwarg: # convert nbPt_rad -> nbPt
kwarg["nbPt"] = kwarg.pop("nbPt_rad")
res = self.ai.integrate1d(**kwarg)[0]
out.append(res)
#TODO manage HDF5 stuff !!!
logger.info("Processing Done in %.3fs !" %
(time.time() - start_time))
self.progressBar.setValue(100)
self.die()
return out
def proceed(self):
with self._sem:
out = None
self.dump()
logger.debug("Let's work a bit")
self.set_ai()
# Default Keyword arguments
kwarg = {"unit": "2th_deg",
"dummy": None,
"delta_dummy": None,
"method": "lut",
"polarization_factor":None,
"filename": None,
"safe": False,
}
if self.q_nm.isChecked():
kwarg["unit"] = "q_nm^-1"
elif self.tth_deg.isChecked():
kwarg["unit"] = "2th_deg"
elif self.tth_rad.isChecked():
kwarg["unit"] = "2th_rad"
elif self.r_mm.isChecked():
kwarg["unit"] = "r_mm"
elif self.q_A.isChecked():
kwarg["unit"] = "q_A^-1"
else:
logger.warning("Undefined unit !!! falling back on 2th_deg")
kwarg["correctSolidAngle"] = bool(self.do_solid_angle.isChecked())
if bool(self.do_dummy.isChecked()):
kwarg["dummy"] = float_(self.val_dummy.text())
delta_dummy = str(self.delta_dummy.text())
if delta_dummy:
kwarg["delta_dummy"] = float(delta_dummy)
else:
kwarg["delta_dummy"] = None
if bool(self.do_polarization.isChecked()):
kwarg["polarization_factor"] = float(self.polarization_factor.value())
else:
kwarg["polarization_factor"] = None
kwarg["nbPt_rad"] = int(str(self.rad_pt.text()).strip())
if self.do_2D.isChecked():
kwarg["nbPt_azim"] = int(str(self.azim_pt.text()).strip())
if self.do_OpenCL.isChecked():
platform = ocl.get_platform(self.platform.currentText())
pid = platform.id
did = platform.get_device(self.device.currentText()).id
if (pid is not None) and (did is not None):
kwarg["method"] = "lut_ocl_%i,%i" % (pid, did)
else:
kwarg["method"] = "lut_ocl"
if self.do_radial_range.isChecked():
try:
rad_min = float_(self.radial_range_min.text())
rad_max = float_(self.radial_range_max.text())
except ValueError as error:
logger.error("error in parsing radial range: %s" % error)
else:
kwarg["radial_range"] = (rad_min, rad_max)
if kwarg["radial_range"] == (None, None):
kwarg["radial_range"] = None
if self.do_azimuthal_range.isChecked():
try:
azim_min = float_(self.azimuth_range_min.text())
azim_max = float_(self.azimuth_range_max.text())
except ValueError as error:
logger.error("error in parsing azimuthal range: %s" % error)
else:
kwarg["azimuth_range"] = (azim_min, azim_max)
if kwarg["azimuth_range"] == (None, None):
kwarg["azimuth_range"] = None
if self.do_poisson.isChecked():
kwarg["error_model"] = "poisson"
else:
kwarg["error_model"] = None
logger.info("Parameters for integration:%s%s" % (os.linesep,
os.linesep.join(["\t%s:\t%s" % (k, v) for k, v in kwarg.items()])))
logger.debug("processing %s" % self.input_data)
start_time = time.time()
if self.input_data in [None, []]:
logger.warning("No input data to process")
return
elif "ndim" in dir(self.input_data) and (self.input_data.ndim == 3):
# We have a numpy array of dim3
if "nbPt_azim" in kwarg:
out = numpy.zeros((self.input_data.shape[0], kwarg["nbPt_azim"], kwarg["nbPt_rad"]), dtype=numpy.float32)
for i in range(self.input_data.shape[0]):
self.progressBar.setValue(100.0 * i / self.input_data.shape[0])
kwarg["data"] = self.input_data[i]
out[i] = self.ai.integrate2d(**kwarg)[0]
else:
if "nbPt_rad" in kwarg: # convert nbPt_rad -> nbPt
kwarg["nbPt"] = kwarg.pop("nbPt_rad")
out = numpy.zeros((self.input_data.shape[0], kwarg["nbPt"]), dtype=numpy.float32)
for i in range(self.input_data.shape[0]):
self.progressBar.setValue(100.0 * i / self.input_data.shape[0])
kwarg["data"] = self.input_data[i]
out[i] = self.ai.integrate1d(**kwarg)[1]
elif "__len__" in dir(self.input_data):
out = []
if self.hdf5_path:
import h5py
hdf5 = h5py.File(self.output_path)
if self.fast_dim:
if "nbPt_azim" in kwarg:
ds = hdf5.create_dataset("diffraction",(1,self.fast_dim,kwarg["nbPt_azim"],kwarg["nbPt_rad"]),
dtype = numpy.float32,
chunks=(1,self.fast_dim,kwarg["nbPt_azim"],kwarg["nbPt_rad"]),
maxshape=(None,self.fast_dim,kwarg["nbPt_azim"],kwarg["nbPt_rad"]))
else:
ds = hdf5.create_dataset("diffraction",(1,self.fast_dim,kwarg["nbPt_rad"]),
dtype = numpy.float32,
chunks=(1,self.fast_dim,kwarg["nbPt_rad"]),
maxshape=(None,self.fast_dim,kwarg["nbPt_rad"]))
else:
if "nbPt_azim" in kwarg:
ds = hdf5.create_dataset("diffraction",(1,kwarg["nbPt_azim"],kwarg["nbPt_rad"]),
dtype = numpy.float32,
chunks=(1,kwarg["nbPt_azim"],kwarg["nbPt_rad"]),
maxshape=(None,kwarg["nbPt_azim"],kwarg["nbPt_rad"]))
else:
ds = hdf5.create_dataset("diffraction",(1,kwarg["nbPt_rad"]),
dtype = numpy.float32,
chunks=(1,kwarg["nbPt_rad"]),
maxshape=(None,kwarg["nbPt_rad"]))
for i, item in enumerate(self.input_data):
self.progressBar.setValue(100.0 * i / len(self.input_data))
logger.debug("processing %s" % item)
if (type(item) in types.StringTypes) and op.exists(item):
kwarg["data"] = fabio.open(item).data
if self.hdf5_path is None:
if self.output_path and op.isdir(self.output_path):
outpath = op.join(self.output_path,op.splitext(op.basename(item))[0])
else:
outpath = op.splitext(item)[0]
if "nbPt_azim" in kwarg:
kwarg["filename"] = outpath + ".azim"
else:
kwarg["filename"] = outpath + ".dat"
else:
logger.warning("item is not a file ... guessing it is a numpy array")
kwarg["data"] = item
kwarg["filename"] = None
if kwarg.get("nbPt_azim"):
res=self.ai.integrate2d(**kwarg)[0]
else:
if "nbPt_rad" in kwarg: # convert nbPt_rad -> nbPt
kwarg["nbPt"] = kwarg.pop("nbPt_rad")
res=self.ai.integrate1d(**kwarg)[0]
out.append(res)
#TODO manage HDF5 stuff !!!
logger.info("Processing Done in %.3fs !" % (time.time() - start_time))
self.progressBar.setValue(100)
self.die()
return out