def test_smoke(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, fname = reduce_stitch(
[708, 709, 710],
[711, 711, 711],
data_folder=self.pth,
reduction_options={"rebin_percent": 2},
)
a.save("test1.dat")
assert os.path.isfile("./test1.dat")
# reduce_stitch should take a ReductionOptions dict
opts = ReductionOptions()
opts["rebin_percent"] = 2
a2, fname = reduce_stitch(
[708, 709, 710],
[711, 711, 711],
data_folder=self.pth,
reduction_options=[opts] * 3,
)
a2.save("test2.dat")
assert os.path.isfile("./test2.dat")
assert_allclose(a.y, a2.y)
def test_smoke(self):
# a quick smoke test to check that the reduction can occur
# warnings filter for pixel size
a, fname = reduce_stitch(
[660, 661],
[658, 659],
data_folder=self.pth,
prefix="SPZ",
reduction_options={"rebin_percent": 2},
)
a.save("test1.dat")
assert os.path.isfile("./test1.dat")
# reduce_stitch should take a list of ReductionOptions dict,
# separate dicts are used for different angles
opts = ReductionOptions()
opts["rebin_percent"] = 2
a2, fname = reduce_stitch(
[660, 661],
[658, 659],
data_folder=self.pth,
prefix="SPZ",
reduction_options=[opts] * 2,
)
a2.save("test2.dat")
assert os.path.isfile("./test2.dat")
assert_allclose(a.y, a2.y)
def test_smoke(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, fname = reduce_stitch([708, 709, 710], [711, 711, 711],
data_folder=self.pth,
rebin_percent=2)
a.save('test1.dat')
def _reduce_row(self, entry):
"""Process a single row using reduce_stitch
Parameters
----------
entry : pandas.Series
Spreadsheet row for this data set
"""
# Identify the runs to be used for reduction
runs = run_list(entry, "refl")
directs = run_list(entry, "directs")
if self.verbose:
fmt = "Reducing %s [%s]/[%s]"
print(fmt % (
entry["name"],
", ".join("%d" % r for r in runs),
", ".join("%d" % r for r in directs),
))
sys.stdout.flush() # keep progress updated
if not runs:
warnings.warn("Row %d (%s) has no reflection runs. Skipped." %
(entry["source"], entry["name"]))
return None, None
if not directs:
warnings.warn("Row %d (%s) has no direct beam runs. Skipped." %
(entry["source"], entry["name"]))
return None, None
if len(runs) > len(directs):
warnings.warn("Row %d (%s) has differing numbers of"
" direct & reflection runs. Skipped." %
(entry["source"], entry["name"]))
return None, None
ds, fname = reduce_stitch(
runs,
directs,
trim_trailing=self.trim_trailing,
data_folder=self.data_folder,
reduction_options=self.reduction_options,
prefix=self.prefix,
)
return ds, fname
def _reduce_row(self, entry):
""" Process a single row using reduce_stitch
Parameters
----------
entry : pandas.Series
Spreadsheet row for this data set
"""
# Identify the runs to be used for reduction
runs = run_list(entry, 'refl')
directs = run_list(entry, 'directs')
if self.verbose:
fmt = "Reducing %s [%s]/[%s]"
print(fmt % (entry['name'],
", ".join('%d' % r for r in runs),
", ".join('%d' % r for r in directs)))
sys.stdout.flush() # keep progress updated
if not runs:
warnings.warn("Row %d (%s) has no reflection runs" %
(entry['source'], entry['name']))
return None, None
if not directs:
warnings.warn("Row %d (%s) has no direct beam runs" %
(entry['source'], entry['name']))
return None, None
if len(runs) != len(directs):
warnings.warn("Row %d (%s) has differing numbers of"
" direct & refln runs" %
(entry['source'], entry['name']))
return None, None
ds, fname = reduce_stitch(runs, directs, **self.kwds)
return ds, fname
def _reduce_row(self, entry):
""" Process a single row using reduce_stitch
Parameters
----------
entry : pandas.Series
Spreadsheet row for this data set
"""
# Identify the runs to be used for reduction
runs = run_list(entry, 'refl')
directs = run_list(entry, 'directs')
if self.verbose:
fmt = "Reducing %s [%s]/[%s]"
print(fmt % (entry['name'], ", ".join(
'%d' % r for r in runs), ", ".join('%d' % r for r in directs)))
sys.stdout.flush() # keep progress updated
if not runs:
warnings.warn("Row %d (%s) has no reflection runs. Skipped." %
(entry['source'], entry['name']))
return None, None
if not directs:
warnings.warn("Row %d (%s) has no direct beam runs. Skipped." %
(entry['source'], entry['name']))
return None, None
if len(runs) > len(directs):
warnings.warn("Row %d (%s) has differing numbers of"
" direct & reflection runs. Skipped." %
(entry['source'], entry['name']))
return None, None
ds, fname = reduce_stitch(runs, directs, **self.kwds)
return ds, fname
def test_smoke(self):
# a quick smoke test to check that the reduction can occur
a, fname = reduce_stitch([708, 709, 710], [711, 711, 711],
data_folder=self.path, rebin_percent=2)
a.save('test1.dat')
def test_smoke(self):
# a quick smoke test to check that the reduction can occur
a, fname = reduce_stitch([708, 709, 710], [711, 711, 711],
data_folder=self.pth, rebin_percent=2)
a.save('test1.dat')