def test_event_reduction(self):
# check that eventmode reduction can occur, and that there are the
# correct number of datasets produced.
# warnings filter for pixel size
with warnings.catch_warnings():
warnings.simplefilter("ignore", RuntimeWarning)
a = PlatypusReduce(pjoin(self.pth, "PLP0011613.nx.hdf"))
a.reduce(
pjoin(self.pth, "PLP0011641.nx.hdf"),
integrate=0,
rebin_percent=2,
eventmode=[0, 900, 1800],
)
assert_equal(a.y.shape[0], 2)
# check that two datasets are written out.
assert os.path.isfile("PLP0011641_0.dat")
assert os.path.isfile("PLP0011641_1.dat")
# check that the resolutions are pretty much the same
assert_allclose(a.x_err[0] / a.x[0],
a.x_err[1] / a.x[1],
atol=0.001)
# check that the (right?) timestamps are written into the datafile
tree = ET.parse(pjoin(os.getcwd(), "PLP0011641_1.xml"))
tree.find(".//REFentry").attrib["time"]
def test_accumulate_files_reduce(self):
# test by adding a file to itself. Should have smaller stats
fnames = ['PLP0000708.nx.hdf', 'PLP0000708.nx.hdf']
pths = [os.path.join(self.pth, fname) for fname in fnames]
plp.accumulate_HDF_files(pths)
with warnings.catch_warnings():
warnings.simplefilter('ignore', RuntimeWarning)
# it should be processable
fadd = PlatypusNexus(
os.path.join(os.getcwd(), 'ADD_PLP0000708.nx.hdf'))
fadd.process()
# it should also be reduceable
reducer = PlatypusReduce(
os.path.join(self.pth, 'PLP0000711.nx.hdf'))
datasets, reduced = reducer.reduce(
os.path.join(os.getcwd(), 'ADD_PLP0000708.nx.hdf'))
assert_('y' in reduced)
# the error bars should be smaller
datasets2, reduced2 = reducer.reduce(
os.path.join(self.pth, 'PLP0000708.nx.hdf'))
assert_(np.all(reduced['y_err'] < reduced2['y_err']))
def test_reduction_method(self):
# a quick smoke test to check that the reduction can occur
a = PlatypusReduce('PLP0000711.nx.hdf', data_folder=self.path,
rebin_percent=4)
# try reduction with the reduce method
a.reduce('PLP0000708.nx.hdf', data_folder=self.path, rebin_percent=4)
# try reduction with the __call__ method
a('PLP0000708.nx.hdf', data_folder=self.path, rebin_percent=4)
# this should also have saved a couple of files in the current
# directory
assert_(os.path.isfile('./PLP0000708_0.dat'))
assert_(os.path.isfile('./PLP0000708_0.xml'))
# try writing offspecular data
a.write_offspecular('offspec.xml', 0)
def test_reduction_method(self):
# a quick smoke test to check that the reduction can occur
# warnings filter for pixel size
with warnings.catch_warnings():
warnings.simplefilter("ignore", RuntimeWarning)
a = PlatypusReduce("PLP0000711.nx.hdf", data_folder=self.pth)
# try reduction with the reduce method
a.reduce(
"PLP0000708.nx.hdf",
data_folder=self.pth,
rebin_percent=4,
)
# try reduction with the __call__ method
a(
"PLP0000708.nx.hdf",
data_folder=self.pth,
rebin_percent=4,
)
# this should also have saved a couple of files in the current
# directory
assert os.path.isfile("./PLP0000708_0.dat")
assert os.path.isfile("./PLP0000708_0.xml")
# can we read the file
ReflectDataset("./PLP0000708_0.dat")
# try writing offspecular data
a.write_offspecular("offspec.xml", 0)
def test_accumulate_files_reduce(self):
# test by adding a file to itself. Should have smaller stats
fnames = ['PLP0000708.nx.hdf', 'PLP0000708.nx.hdf']
pths = [os.path.join(self.path, fname) for fname in fnames]
plp.accumulate_HDF_files(pths)
# it should be processable
fadd = PlatypusNexus(os.path.join(os.getcwd(),
'ADD_PLP0000708.nx.hdf'))
fadd.process()
# it should also be reduceable
reducer = PlatypusReduce(os.path.join(self.path,
'PLP0000711.nx.hdf'))
reduced = reducer.reduce(os.path.join(os.getcwd(),
'ADD_PLP0000708.nx.hdf'))
assert_('ydata' in reduced)
# the error bars should be smaller
reduced2 = reducer.reduce(os.path.join(self.path, 'PLP0000708.nx.hdf'))
assert_(np.all(reduced['ydata_sd'] < reduced2['ydata_sd']))
def test_event_reduction(self):
# check that eventmode reduction can occur, and that there are the
# correct number of datasets produced.
a = PlatypusReduce(
os.path.join(self.pth, 'PLP0011613.nx.hdf'))
a.reduce(os.path.join(self.pth, 'PLP0011641.nx.hdf'),
integrate=0, rebin_percent=2, eventmode=[0, 900, 1800])
assert_equal(a.y.shape[0], 2)
# check that two datasets are written out.
assert_(os.path.isfile('PLP0011641_0.dat'))
assert_(os.path.isfile('PLP0011641_1.dat'))
# check that the resolutions are pretty much the same
assert_allclose(a.x_err[0] / a.x[0],
a.x_err[1] / a.x[1],
atol=0.001)
# check that the (right?) timestamps are written into the datafile
tree = ET.parse(os.path.join(os.getcwd(), 'PLP0011641_1.xml'))
tree.find('.//REFentry').attrib['time']
def test_accumulate_files_reduce(self):
# test by adding a file to itself. Should have smaller stats
fnames = ["PLP0000708.nx.hdf", "PLP0000708.nx.hdf"]
pths = [pjoin(self.pth, fname) for fname in fnames]
plp.accumulate_HDF_files(pths)
with warnings.catch_warnings():
warnings.simplefilter("ignore", RuntimeWarning)
# it should be processable
fadd = PlatypusNexus(pjoin(os.getcwd(), "ADD_PLP0000708.nx.hdf"))
fadd.process()
# it should also be reduceable
reducer = PlatypusReduce(pjoin(self.pth, "PLP0000711.nx.hdf"))
datasets, reduced = reducer.reduce(
pjoin(os.getcwd(), "ADD_PLP0000708.nx.hdf"))
assert_("y" in reduced)
# the error bars should be smaller
datasets2, reduced2 = reducer.reduce(
pjoin(self.pth, "PLP0000708.nx.hdf"))
assert_(np.all(reduced["y_err"] < reduced2["y_err"]))
def test_free_liquids(self):
# smoke test for free liquids
a0 = PlatypusReduce('PLP0038418.nx.hdf', data_folder=self.pth)
a1 = PlatypusReduce('PLP0038417.nx.hdf', data_folder=self.pth)
# try reduction with the reduce method
d0, r0 = a0.reduce('PLP0038420.nx.hdf', data_folder=self.pth,
rebin_percent=4)
d1, r1 = a1.reduce('PLP0038421.nx.hdf', data_folder=self.pth,
rebin_percent=4)
def test_reduction_method(self):
# a quick smoke test to check that the reduction can occur
a = PlatypusReduce('PLP0000711.nx.hdf', data_folder=self.pth)
# try reduction with the reduce method
a.reduce('PLP0000708.nx.hdf', data_folder=self.pth, rebin_percent=4)
# try reduction with the __call__ method
a('PLP0000708.nx.hdf', data_folder=self.pth, rebin_percent=4)
# this should also have saved a couple of files in the current
# directory
assert_(os.path.isfile('./PLP0000708_0.dat'))
assert_(os.path.isfile('./PLP0000708_0.xml'))
# try writing offspecular data
a.write_offspecular('offspec.xml', 0)
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"
"-------------------------------------------------------")