def read_gsexdi(fname, _larch=None, nmca=4, bad=None, **kws):
"""Read GSE XDI Scan Data to larch group,
summing ROI data for MCAs and apply deadtime corrections
"""
group = _larch.symtable.create_group()
group.__name__ = 'GSE XDI Data file %s' % fname
xdi = XDIFile(str(fname))
group._xdi = xdi
group.filename = fname
group.npts = xdi.npts
group.bad_channels = bad
group.dtc_taus = XSPRESS3_TAUS
if _larch.symtable.has_symbol('_sys.gsecars.xspress3_taus'):
group.dtc_taus = _larch.symtable._sys.gsecars.xspress3_taus
for family in ('scan', 'mono', 'facility'):
for key, val in xdi.attrs.get(family, {}).items():
if '||' in val:
val, addr = val.split('||')
try:
val = float(val)
except:
pass
setattr(group, "%s_%s" % (family, key), val)
ocrs, icrs = [], []
ctime = None
for attrname in dir(xdi):
if attrname.lower() == 'counttime':
ctime = getattr(xdi, attrname)
if ctime is None:
try:
ctime = xdi.TSCALER / 5.e7
except AttributeError:
ctime = 1.0
is_xspress3 = any(['13QX4' in a[1] for a in xdi.attrs['column'].items()])
group.with_xspress3 = is_xspress3
for i in range(nmca):
ocr = getattr(xdi, 'OutputCounts_mca%i' % (i + 1), None)
if ocr is None:
ocr = ctime
ocr = ocr / ctime
icr = getattr(xdi, 'InputCounts_mca%i' % (i + 1), None)
if icr is not None:
icr = icr / ctime
else:
icr = 1.0 * ocr
if is_xspress3:
tau = group.dtc_taus[i]
icr = estimate_icr(ocr * 1.00, tau, niter=7)
ocrs.append(ocr)
icrs.append(icr)
labels = []
sums = OrderedDict()
for i, arrname in enumerate(xdi.array_labels):
dat = getattr(xdi, arrname)
aname = sumname = rawname = arrname.lower()
if ('_mca' in aname and 'outputcounts' not in aname
and 'clock' not in aname):
sumname, imca = sumname.split('_mca')
imca = int(imca) - 1
datraw = dat * 1.0
rawname = sumname + '_nodtc'
dat = dat * icrs[imca] / ocrs[imca]
if any(np.isnan(dat)):
nan_pts = np.where(np.isnan(dat))[0]
dat[nan_pts] = datraw[nan_pts]
setattr(group, aname, dat)
if sumname not in labels:
labels.append(sumname)
sums[sumname] = dat
if rawname != sumname:
sums[rawname] = datraw
if rawname not in labels:
labels.append(rawname)
else:
sums[sumname] = sums[sumname] + dat
if rawname != sumname:
sums[rawname] = sums[rawname] + datraw
for name, dat in sums.items():
if not hasattr(group, name):
setattr(group, name, dat)
for arrname in xdi.array_labels:
sname = arrname.lower()
if sname not in labels:
labels.append(sname)
for imca in range(nmca):
setattr(group, 'ocr_mca%i' % (imca + 1), ocrs[imca])
setattr(group, 'icr_mca%i' % (imca + 1), icrs[imca])
group.array_labels = labels
return group
def gsexdi_deadtime_correct(fname,
channelname,
subdir='DT_Corrected',
bad=None,
_larch=None):
"""convert GSE XDI fluorescence XAFS scans to dead time corrected files"""
if not is_GSEXDI(fname):
print("'%s' is not a GSE XDI scan file\n" % fname)
return
out = Group()
out.orig_filename = fname
try:
xdi = read_gsexdi(fname, bad=bad, _larch=_larch)
except:
print('Could not read XDI file ', fname)
return
for attr in ('energy', 'i0', 'i1', 'i2', 'tscaler', 'counttime',
'scan_start_time', 'scan_end_time'):
if hasattr(xdi, attr):
setattr(out, attr, getattr(xdi, attr))
# some scans may not record separate counttime, but TSCALER
# is clock ticks for a 50MHz clock
if not hasattr(out, 'counttime'):
out.counttime = xdi.tscaler * 2.e-8
if hasattr(xdi, 'energy_readback'):
out.energy = xdi.energy_readback
arrname = None
channelname = channelname.lower().replace(' ', '_')
for arr in xdi.array_labels:
if arr.lower().startswith(channelname):
arrname = arr
break
if arrname is None:
print('Cannot find Channel %s in file %s ' % (channelname, fname))
return
out.ifluor = getattr(xdi, arrname)
out.ifluor_raw = getattr(xdi, arrname)
arrname_raw = arrname + '_nodtc'
if arrname_raw in xdi.array_labels:
out.ifluor_raw = getattr(xdi, arrname_raw)
out.mufluor = out.ifluor / out.i0
if hasattr(out, 'i1') or hasattr(out, 'itrans'):
i1 = getattr(out, 'i1', None)
if i1 is None:
i1 = getattr(out, 'itrans', None)
if i1 is not None:
i1 = i1 / out.i0
i1[np.where(i1 < 2.0e-20)] = 2.0e-20
out.mutrans = -np.log(i1)
npts = len(out.energy)
buff = ['# XDI/1.0 GSE/1.0']
header = OrderedDict()
hgroups = [
'beamline', 'facility', 'mono', 'undulator', 'detectors', 'scaler',
'detectorstage', 'samplestage', 'scan', 'scanparameters'
]
hskip = ['scanparameters.end', 'scanparameters.start']
for agroup in hgroups:
attrs = xdi._xdi.attrs.get(agroup, {})
if agroup == 'mono': agroup = 'monochromator'
header[agroup] = OrderedDict()
for sname in sorted(attrs.keys()):
if "%s.%s" % (agroup, sname) not in hskip:
header[agroup][sname] = attrs[sname]
header['facility']['name'] = 'APS'
header['facility']['xray_source'] = '3.6 cm undulator'
header['beamline']['name'] = '13-ID-E, GSECARS'
header['detectors']['i0'] = '20cm ion chamber, He'
header['detectors']['ifluor'] = 'Si SDD Vortex ME-4, 4 elements'
header['detectors']['ifluor_electronics'] = 'Quantum Xspress3 3.1.10'
mono_cut = 'Si(111)'
if xdi.mono_dspacing < 2:
mono_cut = 'Si(311)'
header['monochromator']['name'] = "%s, LN2 cooled" % mono_cut
out_arrays = OrderedDict()
out_arrays['energy'] = ('energy', 'eV')
out_arrays['mufluor'] = ('mufluor', None)
if hasattr(out, 'i1'):
out_arrays['mutrans'] = ('mutrans', None)
out_arrays['ifluor'] = ('ifluor', '# deadtime-corrected')
out_arrays['ifluor_raw'] = ('ifluor_raw', '# not deadtime-corrected')
out_arrays['i0'] = ('i0', None)
if hasattr(out, 'i1'):
out_arrays['itrans'] = ('i1', None)
if hasattr(out, 'i2'):
out_arrays['irefer'] = ('i2', None)
if hasattr(out, 'counttime'):
out_arrays['counttime'] = ('counttime', 'sec')
arrlabel = []
for iarr, aname in enumerate(out_arrays):
lab = "%12s " % aname
if iarr == 0: lab = "%11s " % aname
arrlabel.append(lab)
extra = out_arrays[aname][1]
if extra is None: extra = ''
buff.append("# Column.%i: %s %s" % (iarr + 1, aname, extra))
arrlabel = '#%s' % (' '.join(arrlabel))
ncol = len(out_arrays)
for family, fval in header.items():
for attr, val in fval.items():
buff.append("# %s.%s: %s" % (family.title(), attr, val))
buff.append("# ///")
for comment in xdi._xdi.comments.split('\n'):
c = comment.strip()
if len(c) > 0:
buff.append('# %s' % c)
buff.extend([
"# summed %s fluorescence data from %s" % (channelname, fname),
"# Dead-time correction applied", "#" + "-" * 78, arrlabel
])
efmt = "%11.4f"
ffmt = "%13.7f"
gfmt = "%13.7g"
for i in range(npts):
dline = ["", efmt % out.energy[i], ffmt % out.mufluor[i]]
if hasattr(out, 'i1'):
dline.append(ffmt % out.mutrans[i])
dline.extend(
[gfmt % out.ifluor[i], gfmt % out.ifluor_raw[i], gfmt % out.i0[i]])
if hasattr(out, 'i1'):
dline.append(gfmt % out.i1[i])
if hasattr(out, 'i2'):
dline.append(gfmt % out.i2[i])
if hasattr(out, 'counttime'):
dline.append(gfmt % out.counttime[i])
buff.append(" ".join(dline))
ofile = fname[:]
if ofile.startswith('..'):
ofile = ofile[3:]
ofile = ofile.replace('.', '_') + '.dat'
ofile = os.path.join(subdir, ofile)
if not os.path.exists(subdir):
os.mkdir(subdir)
try:
fout = open(ofile, 'w')
fout.write("\n".join(buff))
fout.close()
print("wrote %s, npts=%i, channel='%s'" % (ofile, npts, channelname))
except:
print("could not open / write to output file %s" % ofile)
return out
def read_gsexdi(fname, _larch=None, nmca=4, bad=None, **kws):
"""Read GSE XDI Scan Data to larch group,
summing ROI data for MCAs and apply deadtime corrections
"""
group = _larch.symtable.create_group()
group.__name__ = 'GSE XDI Data file %s' % fname
xdi = XDIFile(str(fname))
group._xdi = xdi
group.filename = fname
group.npts = xdi.npts
group.bad_channels = bad
for family in ('scan', 'mono', 'facility'):
for key, val in xdi.attrs.get(family, {}).items():
if '||' in val:
val, addr = val.split('||')
try:
val = float(val)
except:
pass
setattr(group, "%s_%s" % (family, key), val)
ocrs, icrs = [], []
ctime = None
for attrname in dir(xdi):
if attrname.lower() == 'counttime':
ctime = getattr(xdi, attrname)
if ctime is None:
try:
ctime = xdi.TSCALER / 5.e7
except AttributeError:
ctime = 1.0
is_xspress3 = any(['13QX4' in a[1] for a in xdi.attrs['column'].items()])
group.with_xspress3 = is_xspress3
dtc_taus = XSPRESS3_TAUS
if _larch.symtable.has_symbol('_sys.gsecars.xspress3_taus'):
dtc_taus = _larch.symtable._sys.gsecars.xspress3_taus
dtc_mode = 'icr/ocr'
for i in range(nmca):
mca = "mca%i" % (i + 1)
ocr = getattr(xdi, 'OutputCounts_%s' % mca, None)
clock = getattr(xdi, 'Clock_%s' % mca, None)
icr = getattr(xdi, 'InputCounts_%s' % mca, None)
dtfact = getattr(xdi, 'DTFactor_%s' % mca, None)
resets = getattr(xdi, 'ResetTicks_%s' % mca, None)
allevt = getattr(xdi, 'AllEvent_%s' % mca, None)
if ocr is None:
ocr = ctime
ocr = ocr / ctime
if icr is not None:
icr = icr / ctime
# Get ICR from one of several alternatives:
# 1. InputCounts_mca was given
# 2. DTFactor_mca was given
# 3. ResetTicks_mca and AllEvets_mca were given
# 4. Use "known values" for tau
if icr is None:
if dtfact is not None:
icr = ocr * dtfact
dtc_mode = 'dtfactor'
elif (clock is not None and resets is not None
and allevt is not None):
dtfact = clock / (clock - (6 * allevt + resets))
icr = ocr * dtfact
dtc_mode = 'resets'
# finally estimate from measured values of tau:
if icr is None:
icr = 1.0 * ocr
dtc_mode = 'none'
if is_xspress3:
tau = dtc_taus[i]
icr = estimate_icr(ocr * 1.00, tau, niter=7)
dtc_mode = 'saved_taus'
ocrs.append(ocr)
icrs.append(icr)
group.dtc_mode = dtc_mode
if dtc_mode == 'saved_taus':
group.dtc_taus = dtc_taus
labels = []
sums = OrderedDict()
for i, arrname in enumerate(xdi.array_labels):
dat = getattr(xdi, arrname)
if arrname.lower() == 'data':
arrname = '_data'
aname = sumname = rawname = arrname.lower()
if ('_mca' in aname and 'outputcounts' not in aname
and 'dtfactor' not in aname and 'clock' not in aname):
sumname, imca = sumname.split('_mca')
imca = int(imca) - 1
datraw = dat * 1.0
rawname = sumname + '_nodtc'
dat = dat * icrs[imca] / ocrs[imca]
if any(np.isnan(dat)):
nan_pts = np.where(np.isnan(dat))[0]
dat[nan_pts] = datraw[nan_pts]
setattr(group, aname, dat)
if sumname not in labels:
labels.append(sumname)
sums[sumname] = dat
if rawname != sumname:
sums[rawname] = datraw
if rawname not in labels:
labels.append(rawname)
else:
sums[sumname] = sums[sumname] + dat
if rawname != sumname:
sums[rawname] = sums[rawname] + datraw
for name, dat in sums.items():
if not hasattr(group, name):
setattr(group, name, dat)
for arrname in xdi.array_labels:
sname = arrname.lower()
if sname not in labels:
labels.append(sname)
data = []
for name in labels:
data.append(getattr(group, name))
group.data = np.array(data)
for imca in range(nmca):
setattr(group, 'ocr_mca%i' % (imca + 1), ocrs[imca])
setattr(group, 'icr_mca%i' % (imca + 1), icrs[imca])
group.array_labels = labels
return group
def read_gsexdi(fname, _larch=None, nmca=4, bad=None, **kws):
"""Read GSE XDI Scan Data to larch group,
summing ROI data for MCAs and apply deadtime corrections
"""
group = _larch.symtable.create_group()
group.__name__ ='GSE XDI Data file %s' % fname
xdi = XDIFile(str(fname))
group._xdi = xdi
group.filename = fname
group.npts = xdi.npts
group.bad_channels = bad
group.dtc_taus = XSPRESS3_TAUS
if _larch.symtable.has_symbol('_sys.gsecars.xspress3_taus'):
group.dtc_taus = _larch.symtable._sys.gsecars.xspress3_taus
for family in ('scan', 'mono', 'facility'):
for key, val in xdi.attrs.get(family, {}).items():
if '||' in val:
val, addr = val.split('||')
try:
val = float(val)
except:
pass
setattr(group, "%s_%s" % (family, key), val)
ocrs, icrs = [], []
ctime = None
for attrname in dir(xdi):
if attrname.lower() == 'counttime':
ctime = getattr(xdi, attrname)
if ctime is None:
try:
ctime = xdi.TSCALER / 5.e7
except AttributeError:
ctime = 1.0
is_xspress3 = any(['13QX4' in a[1] for a in xdi.attrs['column'].items()])
group.with_xspress3 = is_xspress3
for i in range(nmca):
ocr = getattr(xdi, 'OutputCounts_mca%i' % (i+1), None)
if ocr is None:
ocr = ctime
ocr = ocr/ctime
icr = getattr(xdi, 'InputCounts_mca%i' % (i+1), None)
if icr is not None:
icr = icr/ctime
else:
icr = 1.0*ocr
if is_xspress3:
tau = group.dtc_taus[i]
icr = estimate_icr(ocr*1.00, tau, niter=7)
ocrs.append(ocr)
icrs.append(icr)
labels = []
sums = OrderedDict()
for i, arrname in enumerate(xdi.array_labels):
dat = getattr(xdi, arrname)
aname = sumname = rawname = arrname.lower()
if ('_mca' in aname and 'outputcounts' not in aname and
'clock' not in aname):
sumname, imca = sumname.split('_mca')
imca = int(imca) - 1
datraw = dat*1.0
rawname = sumname + '_nodtc'
dat = dat * icrs[imca]/ ocrs[imca]
if any(np.isnan(dat)):
nan_pts = np.where(np.isnan(dat))[0]
dat[nan_pts] = datraw[nan_pts]
setattr(group, aname, dat)
if sumname not in labels:
labels.append(sumname)
sums[sumname] = dat
if rawname != sumname:
sums[rawname] = datraw
if rawname not in labels:
labels.append(rawname)
else:
sums[sumname] = sums[sumname] + dat
if rawname != sumname:
sums[rawname] = sums[rawname] + datraw
for name, dat in sums.items():
if not hasattr(group, name):
setattr(group, name, dat)
for arrname in xdi.array_labels:
sname = arrname.lower()
if sname not in labels:
labels.append(sname)
for imca in range(nmca):
setattr(group, 'ocr_mca%i' % (imca+1), ocrs[imca])
setattr(group, 'icr_mca%i' % (imca+1), icrs[imca])
group.array_labels = labels
return group
def gsexdi_deadtime_correct(fname, channelname, subdir='DT_Corrected',
bad=None, _larch=None):
"""convert GSE XDI fluorescence XAFS scans to dead time corrected files"""
if not is_GSEXDI(fname):
print("'%s' is not a GSE XDI scan file\n" % fname)
return
out = Group()
out.orig_filename = fname
try:
xdi = read_gsexdi(fname, bad=bad, _larch=_larch)
except:
print('Could not read XDI file ', fname)
return
for attr in ('energy', 'i0', 'i1', 'i2', 'tscaler',
'counttime', 'scan_start_time', 'scan_end_time'):
if hasattr(xdi, attr):
setattr(out, attr, getattr(xdi, attr))
# some scans may not record separate counttime, but TSCALER
# is clock ticks for a 50MHz clock
if not hasattr(out, 'counttime'):
out.counttime = xdi.tscaler * 2.e-8
if hasattr(xdi, 'energy_readback'):
out.energy = xdi.energy_readback
arrname = None
channelname = channelname.lower().replace(' ', '_')
for arr in xdi.array_labels:
if arr.lower().startswith(channelname):
arrname = arr
break
if arrname is None:
print('Cannot find Channel %s in file %s '% (channelname, fname))
return
out.ifluor = getattr(xdi, arrname)
out.ifluor_raw = getattr(xdi, arrname)
arrname_raw = arrname + '_nodtc'
if arrname_raw in xdi.array_labels:
out.ifluor_raw = getattr(xdi, arrname_raw)
out.mufluor = out.ifluor / out.i0
if hasattr(out, 'i1') or hasattr(out, 'itrans'):
i1 = getattr(out, 'i1', None)
if i1 is None:
i1 = getattr(out, 'itrans', None)
if i1 is not None:
i1 = i1 / out.i0
i1[np.where(i1<2.0e-20)] = 2.0e-20
out.mutrans = -np.log(i1)
npts = len(out.energy)
buff = ['# XDI/1.0 GSE/1.0']
header = OrderedDict()
hgroups = ['beamline', 'facility', 'mono', 'undulator', 'detectors',
'scaler', 'detectorstage', 'samplestage', 'scan', 'scanparameters']
hskip = ['scanparameters.end', 'scanparameters.start']
for agroup in hgroups:
attrs = xdi._xdi.attrs.get(agroup, {})
if agroup == 'mono': agroup = 'monochromator'
header[agroup] = OrderedDict()
for sname in sorted(attrs.keys()):
if "%s.%s" %( agroup, sname) not in hskip:
header[agroup][sname] = attrs[sname]
header['facility']['name'] = 'APS'
header['facility']['xray_source'] = '3.6 cm undulator'
header['beamline']['name'] = '13-ID-E, GSECARS'
header['detectors']['i0'] = '20cm ion chamber, He'
header['detectors']['ifluor'] = 'Si SDD Vortex ME-4, 4 elements'
header['detectors']['ifluor_electronics'] = 'Quantum Xspress3 3.1.10'
mono_cut = 'Si(111)'
if xdi.mono_dspacing < 2:
mono_cut = 'Si(311)'
header['monochromator']['name'] = "%s, LN2 cooled" % mono_cut
out_arrays = OrderedDict()
out_arrays['energy'] = ('energy', 'eV')
out_arrays['mufluor'] = ('mufluor', None)
if hasattr(out, 'i1'):
out_arrays['mutrans'] = ('mutrans', None)
out_arrays['ifluor'] = ('ifluor', '# deadtime-corrected')
out_arrays['ifluor_raw'] = ('ifluor_raw', '# not deadtime-corrected')
out_arrays['i0'] = ('i0', None)
if hasattr(out, 'i1'):
out_arrays['itrans'] = ('i1', None)
if hasattr(out, 'i2'):
out_arrays['irefer'] = ('i2', None)
if hasattr(out, 'counttime'):
out_arrays['counttime'] = ('counttime', 'sec')
arrlabel = []
for iarr, aname in enumerate(out_arrays):
lab = "%12s " % aname
if iarr == 0: lab = "%11s " % aname
arrlabel.append(lab)
extra = out_arrays[aname][1]
if extra is None: extra = ''
buff.append("# Column.%i: %s %s" % (iarr+1, aname, extra))
arrlabel = '#%s' % (' '.join(arrlabel))
ncol = len(out_arrays)
for family, fval in header.items():
for attr, val in fval.items():
buff.append("# %s.%s: %s" % (family.title(), attr, val))
buff.append("# ///")
for comment in xdi._xdi.comments.split('\n'):
c = comment.strip()
if len(c) > 0:
buff.append('# %s' % c)
buff.extend(["# summed %s fluorescence data from %s" % (channelname, fname),
"# Dead-time correction applied",
"#"+ "-"*78, arrlabel])
efmt = "%11.4f"
ffmt = "%13.7f"
gfmt = "%13.7g"
for i in range(npts):
dline = ["", efmt % out.energy[i], ffmt % out.mufluor[i]]
if hasattr(out, 'i1'):
dline.append(ffmt % out.mutrans[i])
dline.extend([gfmt % out.ifluor[i],
gfmt % out.ifluor_raw[i],
gfmt % out.i0[i]])
if hasattr(out, 'i1'):
dline.append(gfmt % out.i1[i])
if hasattr(out, 'i2'):
dline.append(gfmt % out.i2[i])
if hasattr(out, 'counttime'):
dline.append(gfmt % out.counttime[i])
buff.append(" ".join(dline))
ofile = fname[:]
if ofile.startswith('..'):
ofile = ofile[3:]
ofile = ofile.replace('.', '_') + '.dat'
ofile = os.path.join(subdir, ofile)
if not os.path.exists(subdir):
os.mkdir(subdir)
try:
fout = open(ofile, 'w')
fout.write("\n".join(buff))
fout.close()
print("wrote %s, npts=%i, channel='%s'" % (ofile, npts, channelname))
except:
print("could not open / write to output file %s" % ofile)
return out
def read_gsexdi(fname, _larch=None, nmca=4, bad=None, **kws):
"""Read GSE XDI Scan Data to larch group,
summing ROI data for MCAs and apply deadtime corrections
"""
group = _larch.symtable.create_group()
group.__name__ ='GSE XDI Data file %s' % fname
xdi = XDIFile(str(fname))
group._xdi = xdi
group.path = fname
path, suffix = os.path.split(fname)
group.filename = suffix
group.npts = xdi.npts
group.bad_channels = bad
for family in ('scan', 'mono', 'facility'):
for key, val in xdi.attrs.get(family, {}).items():
if '||' in val:
val, addr = val.split('||')
try:
val = float(val)
except:
pass
setattr(group, "%s_%s" % (family, key), val)
ocrs, icrs = [], []
ctime = None
for attrname in dir(xdi):
if attrname.lower() == 'counttime':
ctime = getattr(xdi, attrname)
if ctime is None:
try:
ctime = xdi.TSCALER / 5.e7
except AttributeError:
ctime = 1.0
is_xspress3 = any(['13QX4' in a[1] for a in xdi.attrs['column'].items()])
group.with_xspress3 = is_xspress3
dtc_taus = XSPRESS3_TAUS
if _larch.symtable.has_symbol('_sys.gsecars.xspress3_taus'):
dtc_taus = _larch.symtable._sys.gsecars.xspress3_taus
dtc_mode = 'icr/ocr'
for i in range(nmca):
mca = "mca%i" % (i+1)
ocr = getattr(xdi, 'OutputCounts_%s' % mca, None)
clock = getattr(xdi, 'Clock_%s' % mca, None)
icr = getattr(xdi, 'InputCounts_%s' % mca, None)
dtfact = getattr(xdi, 'DTFactor_%s' % mca, None)
resets = getattr(xdi, 'ResetTicks_%s' % mca, None)
allevt = getattr(xdi, 'AllEvent_%s' % mca, None)
if ocr is None:
ocr = ctime
ocr = ocr/ctime
if icr is not None:
icr = icr/ctime
# Get ICR from one of several alternatives:
# 1. InputCounts_mca was given
# 2. DTFactor_mca was given
# 3. ResetTicks_mca and AllEvets_mca were given
# 4. Use "known values" for tau
if icr is None:
if dtfact is not None:
icr = ocr * dtfact
dtc_mode = 'dtfactor'
elif (clock is not None and
resets is not None and
allevt is not None):
dtfact = clock/(clock - (6*allevt + resets))
icr = ocr * dtfact
dtc_mode = 'resets'
# finally estimate from measured values of tau:
if icr is None:
icr = 1.0*ocr
dtc_mode = 'none'
if is_xspress3:
tau = dtc_taus[i]
icr = estimate_icr(ocr*1.00, tau, niter=7)
dtc_mode = 'saved_taus'
ocrs.append(ocr)
icrs.append(icr)
group.dtc_mode = dtc_mode
if dtc_mode == 'saved_taus':
group.dtc_taus = dtc_taus
labels = []
sums = OrderedDict()
for i, arrname in enumerate(xdi.array_labels):
dat = getattr(xdi, arrname)
if arrname.lower() == 'data':
arrname = '_data'
aname = sumname = rawname = arrname.lower()
if ('_mca' in aname and
'outputcounts' not in aname and
'dtfactor' not in aname and
'clock' not in aname):
sumname, imca = sumname.split('_mca')
imca = int(imca) - 1
datraw = dat*1.0
rawname = sumname + '_nodtc'
dat = dat * icrs[imca]/ ocrs[imca]
if any(np.isnan(dat)):
nan_pts = np.where(np.isnan(dat))[0]
dat[nan_pts] = datraw[nan_pts]
setattr(group, aname, dat)
if sumname not in labels:
labels.append(sumname)
sums[sumname] = dat
if rawname != sumname:
sums[rawname] = datraw
if rawname not in labels:
labels.append(rawname)
else:
sums[sumname] = sums[sumname] + dat
if rawname != sumname:
sums[rawname] = sums[rawname] + datraw
for name, dat in sums.items():
if not hasattr(group, name):
setattr(group, name, dat)
for arrname in xdi.array_labels:
sname = arrname.lower()
if sname not in labels:
labels.append(sname)
data = []
for name in labels:
data.append(getattr(group, name))
group.data = np.array(data)
for imca in range(nmca):
setattr(group, 'ocr_mca%i' % (imca+1), ocrs[imca])
setattr(group, 'icr_mca%i' % (imca+1), icrs[imca])
group.array_labels = labels
return group
