Exemplo n.º 1
0
 def _process_data(self):
     for sect, opts in conf_sects.items():
         # if sect == 'scan': print( opts)
         if not self.cp.has_section(sect):
             continue
         bools = opts.get('bools', [])
         floats = opts.get('floats', [])
         ints = opts.get('ints', [])
         thissect = {}
         is_ordered = False
         if 'ordered' in opts:
             thissect = OrderedDict()
             is_ordered = True
         for opt in self.cp.options(sect):
             get = self.cp.get
             if opt in bools: get = self.cp.getboolean
             elif opt in floats: get = self.cp.getfloat
             elif opt in ints: get = self.cp.getint
             val = get(sect, opt)
             if is_ordered and '|' in val:
                 opt, val = val.split('|', 1)
                 opt = opt.strip()
                 val = val.strip()
             thissect[opt] = val
         self.config[sect] = thissect
Exemplo n.º 2
0
def read_stageconfig(filename=None, _larch=None):
    """read Sample Stage configurattion file, saving results

    Parameters
    ----------
    filename:   None or string, name of file holding sample positions (see Note)

    Examples
    --------
      read_stageconfig()

    Notes
    ------
      1. If filename is None (the default) 'SampleStage_autosave.ini'
         from the current working folder is used.
      2. the file timestamp is always tested to find new position names
      3. Generally, you don't need to do this explicitly, as
         move_samplestage will run this when necessary.

    """
    if filename is None: filename = DEF_SampleStageFile
    if not os.path.exists(filename):
        print 'No stageconfig found!'
        return None
    #endif

    stages = []
    positions = OrderedDict()
    ini = ConfigParser()
    ini.read(filename)

    for item in ini.options('stages'):
        line = ini.get('stages', item)
        words = [i.strip() for i in line.split('||')]
        stages.append(words[0])
    #endfor

    for item in ini.options('positions'):
        line = ini.get('positions', item)
        words = [i.strip() for i in line.split('||')]
        name = words[0].lower()
        vals = [float(i) for i in words[2].split(',')]
        positions[name] = vals
    #endfor
    this = Group(pos=positions,
                 stages=stages,
                 _modtime_=os.stat(filename).st_mtime)
    if _larch is not None:
        if not _larch.symtable.has_group('macros'):
            _larch.symtable.new_group('macros')
        _larch.symtable.macros.stage_conf = this
    print(" Read %d positions from stage configuration." % len(positions))

    return this
Exemplo n.º 3
0
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
Exemplo n.º 4
0
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
Exemplo n.º 5
0
    'scan': {
        'ints': ('dimension', ),
        'floats':
        ('start1', 'stop1', 'step1', 'time1', 'start2', 'stop2', 'step2')
    }
}

__c = (('general', ('mapdb', 'struck', 'scaler', 'xmap', 'mono', 'fileplugin',
                    'basedir', 'scandir', 'envfile')),
       ('xps', ('host', 'user', 'passwd', 'group', 'positioners')),
       ('scan', ('filename', 'dimension', 'comments', 'pos1', 'start1',
                 'stop1', 'step1', 'time1', 'pos2', 'start2', 'stop2',
                 'step2')), ('xrf', ('use', 'type', 'prefix', 'plugin')),
       ('fast_positioners', None), ('slow_positioners', None))

conf_objs = OrderedDict(__c)

conf_files = ('MapDefault.ini',
              '//cars5/Data/xas_user/config/FastMap/Default.ini')

##struck = 13IDC:str:
##scaler = 13IDC:scaler2

default_conf = """# FastMap configuration file (default)
[general]
mapdb = 13XRM:map:
mono = 13IDA:
struck = 13IDE:SIS1
scaler = 13IDE:scaler1
xmap = dxpMercury:
fileplugin = netCDF1:
Exemplo n.º 6
0
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
Exemplo n.º 7
0
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
Exemplo n.º 8
0
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
Exemplo n.º 9
0
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