def _update_instrument_angles(self, workspace, q_values, wave):
"""
Updates the instrument angles in the specified workspace, using the specified wavelength
and the specified Q-Values. This is required when calculating absorption corrections for
indirect elastic. This is used only for ISIS instruments.
:param workspace: The workspace whose instrument angles to update.
:param q_values: The extracted Q-Values (MomentumTransfer)
:param wave: The wavelength
"""
work_dir = config['defaultsave.directory']
k0 = 4.0 * math.pi / wave
theta = 2.0 * np.degrees(np.arcsin(q_values / k0)) # convert to angle
filename = 'Elastic_angles.txt'
path = os.path.join(work_dir, filename)
logger.information('Creating angles file : ' + path)
handle = open(path, 'w')
head = 'spectrum,theta'
handle.write(head + " \n")
for n in range(0, len(theta)):
handle.write(str(n + 1) + ' ' + str(theta[n]) + "\n")
handle.close()
update_alg = self.createChildAlgorithm("UpdateInstrumentFromFile",
enableLogging=False)
update_alg.setProperty("Workspace", workspace)
update_alg.setProperty("Filename", path)
update_alg.setProperty("MoveMonitors", False)
update_alg.setProperty("IgnorePhi", True)
update_alg.setProperty("AsciiHeader", head)
update_alg.setProperty("SkipFirstNLines", 1)
def _output_sample_logs(instrument, run_number, van_run_number, workspace,
rb_num):
def write_to_file():
with open(output_path, "w", newline="") as logfile:
writer = csv.writer(logfile, ["Sample Log", "Avg Value"])
for log in output_dict:
writer.writerow([log, output_dict[log]])
output_dict = {}
sample_run = workspace.getRun()
log_names = sample_run.keys()
# Collect numerical sample logs.
for name in log_names:
try:
output_dict[name] = sample_run.getPropertyAsSingleValue(name)
except ValueError:
logger.information(
f"Could not convert {name} to a numerical value. It will not be included in the "
f"sample logs output file.")
focus_dir = path.join(output_settings.get_output_path(), "Focus")
if not path.exists(focus_dir):
makedirs(focus_dir)
output_path = path.join(focus_dir,
(instrument + "_" + run_number + "_" +
van_run_number + "_sample_logs.csv"))
write_to_file()
if rb_num:
focus_user_dir = path.join(output_settings.get_output_path(),
"User", rb_num, "Focus")
if not path.exists(focus_user_dir):
makedirs(focus_user_dir)
output_path = path.join(focus_user_dir,
(instrument + "_" + run_number + "_" +
van_run_number + "_sample_logs.csv"))
write_to_file()
def set_current_calibration(self, success_info=None):
if success_info:
logger.information("Thread executed in " +
str(success_info.elapsed_time) + " seconds.")
self.current_calibration = deepcopy(self.pending_calibration)
self.calibration_notifier.notify_subscribers(self.current_calibration)
self.emit_update_fields_signal()
self.pending_calibration.clear()
def _create_waves_indirect_elastic(self, workspace):
"""
Creates a wavelength workspace, from the workspace with the specified input workspace
name, using an Elastic instrument definition file. E-Mode must be Indirect and the y-axis
of the input workspace must be in units of Q.
:param workspace: The input workspace.
:return: The output wavelength workspace.
"""
self._indirect_elastic = True
self._q_values = workspace.getAxis(1).extractValues()
instrument_name = workspace.getInstrument().getName()
self._isis_instrument = instrument_name == "IRIS" or instrument_name == "OSIRIS"
# ---------- Load Elastic Instrument Definition File ----------
if self._isis_instrument:
idf_name = instrument_name + '_elastic_Definition.xml'
idf_path = os.path.join(config.getInstrumentDirectory(), idf_name)
logger.information('IDF = %s' % idf_path)
load_alg = self.createChildAlgorithm("LoadInstrument",
enableLogging=True)
load_alg.setProperty("Workspace", workspace)
load_alg.setProperty("Filename", idf_path)
load_alg.setProperty("RewriteSpectraMap", True)
load_alg.execute()
e_fixed = float(self._efixed)
logger.information('Efixed = %f' % e_fixed)
# ---------- Set Instrument Parameters ----------
sip_alg = self.createChildAlgorithm("SetInstrumentParameter",
enableLogging=False)
sip_alg.setProperty("Workspace", workspace)
sip_alg.setProperty("ParameterName", 'EFixed')
sip_alg.setProperty("ParameterType", 'Number')
sip_alg.setProperty("Value", str(e_fixed))
sip_alg.execute()
# ---------- Calculate Wavelength ----------
wave = math.sqrt(81.787 / e_fixed)
logger.information('Wavelength = %f' % wave)
workspace.getAxis(0).setUnit('Wavelength')
# ---------- Format Input Workspace ---------
convert_alg = self.createChildAlgorithm("ConvertToHistogram",
enableLogging=False)
convert_alg.setProperty("InputWorkspace", workspace)
convert_alg.execute()
workspace = self._crop_ws(
convert_alg.getProperty("OutputWorkspace").value)
# --------- Set wavelengths as X-values in Output Workspace ----------
waves = (0.01 * np.arange(-1, workspace.blocksize())) + wave
logger.information('Waves for the dummy workspace: ' + str(waves))
nhist = workspace.getNumberHistograms()
for idx in range(nhist):
workspace.setX(idx, waves)
if self._isis_instrument:
workspace.replaceAxis(1, SpectraAxis.create(workspace))
self._update_instrument_angles(workspace, self._q_values, wave)
return workspace