def test_basename_datafile(self):
# check that the right basename is returned
pth = 'a/b/c.nx.hdf'
assert_(basename_datafile(pth) == 'c')
pth = 'c.nx.hdf'
assert_(basename_datafile(pth) == 'c')
def test_basename_datafile(self):
# check that the right basename is returned
pth = "a/b/c.nx.hdf"
assert_(basename_datafile(pth) == "c")
pth = "c.nx.hdf"
assert_(basename_datafile(pth) == "c")
def test_basename_datafile(self):
# check that the right basename is returned
pth = 'a/b/c.nx.hdf'
assert_(basename_datafile(pth) == 'c')
pth = 'c.nx.hdf'
assert_(basename_datafile(pth) == 'c')
def reducer(self, callback=None):
"""
Reduce all the entries in reduction_entries
Parameters
----------
callback : callable
Function, `f(percent_finished)` that is called with the current
percentage progress of the reduction
"""
# refnx.reduce.reduce needs you to be in the directory where you're
# going to write files to
if self.output_directory:
os.chdir(self.output_directory)
# if no data directory was specified then assume it's the cwd
data_directory = self.data_directory
if not data_directory:
data_directory = "./"
def full_path(fname):
f = os.path.join(data_directory, fname)
return f
# if the streamed directory isn't mentioned then assume it's the same
# as the data directory
streamed_directory = self.streamed_directory
if not os.path.isdir(streamed_directory):
self.streamed_directory = data_directory
logging.info("-------------------------------------------------------"
"\nStarting reduction run")
logging.info(
"data_folder={data_directory}, trim_trailing=True, "
"lo_wavelength={low_wavelength}, "
"hi_wavelength={high_wavelength}, "
"rebin_percent={rebin_percent}, "
"normalise={monitor_normalisation}, "
"background={background_subtraction} "
"eventmode={streamed_reduction} "
"event_folder={streamed_directory}".format(**self.__dict__))
# sets up time slices for event reduction
if self.streamed_reduction:
eventmode = np.arange(self.stream_start, self.stream_end,
self.stream_duration)
eventmode = np.r_[eventmode, self.stream_end]
else:
eventmode = None
# are you manual beamfinding?
peak_pos = None
if self.manual_beam_find and self.manual_beam_finder is not None:
peak_pos = -1
idx = 0
cached_direct_beams = {}
for row, val in self.reduction_entries.items():
if not val["use"]:
continue
flood = None
if val["flood"]:
flood = full_path(val["flood"])
combined_dataset = None
# process entries one by one
for ref, db in zip(
["reflect-1", "reflect-2", "reflect-3"],
["direct-1", "direct-2", "direct-3"],
):
reflect = val[ref]
direct = val[db]
# if the file doesn't exist there's no point continuing
if (not os.path.isfile(full_path(reflect))) or (
not os.path.isfile(full_path(direct))):
continue
# which of the nspectra to reduce (or all)
ref_pn = PlatypusNexus(full_path(reflect))
if direct not in cached_direct_beams:
cached_direct_beams[direct] = PlatypusReduce(
direct, data_folder=data_directory)
reducer = cached_direct_beams[direct]
try:
reduced = reducer(
ref_pn,
scale=val["scale"],
h5norm=flood,
lo_wavelength=self.low_wavelength,
hi_wavelength=self.high_wavelength,
rebin_percent=self.rebin_percent,
normalise=self.monitor_normalisation,
background=self.background_subtraction,
manual_beam_find=self.manual_beam_finder,
peak_pos=peak_pos,
eventmode=eventmode,
event_folder=streamed_directory,
)
except Exception as e:
# typical Exception would be ValueError for non overlapping
# angles
logging.info(e)
continue
logging.info("Reduced {} vs {}, scale={}, angle={}".format(
reflect,
direct,
val["scale"],
reduced[1]["omega"][0, 0],
))
if combined_dataset is None:
combined_dataset = ReflectDataset()
fname = basename_datafile(reflect)
fname_dat = os.path.join(self.output_directory,
"c_{0}.dat".format(fname))
fname_xml = os.path.join(self.output_directory,
"c_{0}.xml".format(fname))
try:
combined_dataset.add_data(
reducer.data(),
requires_splice=True,
trim_trailing=True,
)
except ValueError as e:
# datasets don't overlap
logging.info(e)
continue
if combined_dataset is not None:
# after you've finished reducing write a combined file.
with open(fname_dat, "wb") as f:
combined_dataset.save(f)
with open(fname_xml, "wb") as f:
combined_dataset.save_xml(f)
logging.info("Written combined files: {} and {}".format(
fname_dat, fname_xml))
# can be used to create a progress bar
idx += 1
if callback is not None:
ok = callback(100 * idx / len(self.reduction_entries))
if not ok:
break
logging.info("\nFinished reduction run"
"-------------------------------------------------------")
def reducer(self, callback=None):
"""
Reduce all the entries in reduction_entries
Parameters
----------
callback : callable
Function, `f(percent_finished)` that is called with the current
percentage progress of the reduction
"""
# refnx.reduce.reduce needs you to be in the directory where you're
# going to write files to
if self.output_directory:
os.chdir(self.output_directory)
# if no data directory was specified then assume it's the cwd
data_directory = self.data_directory
if not data_directory:
data_directory = './'
def full_path(fname):
f = os.path.join(data_directory, fname)
return f
# if the streamed directory isn't mentioned then assume it's the same
# as the data directory
streamed_directory = self.streamed_directory
if not os.path.isdir(streamed_directory):
self.streamed_directory = data_directory
logging.info('-------------------------------------------------------'
'\nStarting reduction run')
logging.info(
'data_folder={data_directory}, trim_trailing=True, '
'lo_wavelength={low_wavelength}, '
'hi_wavelength={high_wavelength}, '
'rebin_percent={rebin_percent}, '
'normalise={monitor_normalisation}, '
'background={background_subtraction} '
'eventmode={streamed_reduction} '
'event_folder={streamed_directory}'.format(**self.__dict__))
# sets up time slices for event reduction
if self.streamed_reduction:
eventmode = np.arange(self.stream_start,
self.stream_end,
self.stream_duration)
eventmode = np.r_[eventmode, self.stream_end]
else:
eventmode = None
# are you manual beamfinding?
peak_pos = None
if (self.manual_beam_find and
self.manual_beam_finder is not None):
peak_pos = -1
idx = 0
cached_direct_beams = {}
for row, val in self.reduction_entries.items():
if not val['use']:
continue
flood = None
if val['flood']:
flood = val['flood']
combined_dataset = None
# process entries one by one
for ref, db in zip(['reflect-1', 'reflect-2', 'reflect-3'],
['direct-1', 'direct-2', 'direct-3']):
reflect = val[ref]
direct = val[db]
# if the file doesn't exist there's no point continuing
if ((not os.path.isfile(full_path(reflect))) or
(not os.path.isfile(full_path(direct)))):
continue
# which of the nspectra to reduce (or all)
ref_pn = PlatypusNexus(reflect)
if direct not in cached_direct_beams:
cached_direct_beams[direct] = PlatypusReduce(
direct,
data_folder=data_directory)
reducer = cached_direct_beams[direct]
reduced = reducer(
ref_pn, scale=val['scale'],
norm_file_num=flood,
lo_wavelength=self.low_wavelength,
hi_wavelength=self.high_wavelength,
rebin_percent=self.rebin_percent,
normalise=self.monitor_normalisation,
background=self.background_subtraction,
manual_beam_find=self.manual_beam_finder,
peak_pos=peak_pos,
eventmode=eventmode,
event_folder=streamed_directory)
logging.info(
'Reduced {} vs {}, scale={}, angle={}'.format(
reflect, direct, val['scale'],
reduced['omega'][0, 0]))
if combined_dataset is None:
combined_dataset = ReflectDataset()
fname = basename_datafile(reflect)
fname_dat = os.path.join(self.output_directory,
'c_{0}.dat'.format(fname))
fname_xml = os.path.join(self.output_directory,
'c_{0}.xml'.format(fname))
combined_dataset.add_data(reducer.data(),
requires_splice=True,
trim_trailing=True)
if combined_dataset is not None:
# after you've finished reducing write a combined file.
with open(fname_dat, 'wb') as f:
combined_dataset.save(f)
with open(fname_xml, 'wb') as f:
combined_dataset.save_xml(f)
logging.info(
'Written combined files: {} and {}'.format(
fname_dat, fname_xml))
# can be used to create a progress bar
idx += 1
if callback is not None:
ok = callback(100 * idx / len(self.reduction_entries))
if not ok:
break
logging.info('\nFinished reduction run'
'-------------------------------------------------------')