diff options
Diffstat (limited to 'python/correct_crosstalk.py')
-rwxr-xr-x | python/correct_crosstalk.py | 750 |
1 files changed, 0 insertions, 750 deletions
diff --git a/python/correct_crosstalk.py b/python/correct_crosstalk.py deleted file mode 100755 index 7d83912..0000000 --- a/python/correct_crosstalk.py +++ /dev/null @@ -1,750 +0,0 @@ -#!/usr/bin/env python3 -# -*- coding: utf-8 -*- -# -# References: -# [1] Definition of RMF and ARF file formats -# https://heasarc.gsfc.nasa.gov/docs/heasarc/caldb/docs/memos/cal_gen_92_002/cal_gen_92_002.html -# [2] CIAO: Auxiliary Response File -# http://cxc.harvard.edu/ciao/dictionary/arf.html -# [3] CIAO: Redistribution Matrix File -# http://cxc.harvard.edu/ciao/dictionary/rmf.html -# [4] astropy - FITS format code -# http://docs.astropy.org/en/stable/io/fits/usage/table.html#column-creation -# [5] XSPEC - Spectral Fitting -# https://heasarc.gsfc.nasa.gov/docs/xanadu/xspec/manual/XspecSpectralFitting.html -# -# -# Weitian LI -# Created: 2016-03-26 -# Updated: 2016-04-06 -# -# ChangeLog: -# 2016-04-06: -# * Fix `RMF: get_rmfimg()' for XMM EPIC RMF -# 2016-04-02: -# * Interpolate ARF in order to match the spectral channel energies -# * Add version and date information -# * Update documentations -# * Update header history contents -# 2016-04-01: -# * Greatly update the documentations (e.g., description, sample config) -# * Add class `RMF' -# * Add method `get_energy()' for class `ARF' -# * Split out class `SpectrumSet' from `Spectrum' -# * Implement background subtraction -# * Add config `subtract_bkg' and corresponding argument -# -# XXX/FIXME: -# * SpectrumSet: estimate channel errors by Monte Carlo simulations -# -# TODO: -# * Spectrum: implement the grouping function (and quality columns) -# * Split classes ARF, RMF, Spectrum, and SpectrumSet to a separate module -# - -__version__ = "0.3.0" -__date__ = "2016-04-02" - - -""" -Correct the crosstalk effect of XMM spectra by subtracting the photons that -scattered from the surrounding regions due to the finite PSF, and by -compensating the photons that scattered to the surrounding regions, according -to the generated crosstalk ARFs by SAS `arfgen'. - - -Sample config file (in `ConfigObj' syntax): ------------------------------------------------------------ -verbose = True -clobber = False -# whether to subtract the background before crosstalk correction -subtract_bkg = True -# whether to fix the negative channel values due to spectral subtractions -fix_negative = True - -[...] -... - -[reg2] -outfile = cc_reg2.pi -spec = reg2.pi -arf = reg2.arf -rmf = reg2.rmf -bkg = reg2_bkg.pi - [[cross_in]] - [[[in1]]] - spec = reg1.pi - arf = reg1.arf - rmf = reg1.rmf - bkg = reg1_bkg.pi - cross_arf = reg_1-2.arf - [[[in2]]] - spec = reg3.pi - arf = reg3.arf - rmf = reg3.rmf - bkg = reg3_bkg.pi - cross_arf = reg_3-2.arf - [[cross_out]] - cross_arf = reg_2-1.arf, reg_2-3.arf - -[...] -... ------------------------------------------------------------ -""" - - -import numpy as np -import scipy as sp -import scipy.interpolate -from astropy.io import fits -from configobj import ConfigObj - -import sys -import os -import argparse -from datetime import datetime - - -class ARF: # {{{ - """ - Class to handle the ARF (ancillary/auxiliary response file), - which contains the combined instrumental effective area - (telescope/filter/detector) and the quantum efficiency (QE) as a - function of energy averaged over time. - The effective area is [cm^2], and the QE is [counts/photon]; they are - multiplied together to create the ARF, resulting in [cm^2 counts/photon]. - - **CAVEAT/NOTE**: - Generally, the "ENERG_LO" and "ENERG_HI" columns of an ARF are *different* - to the "E_MIN" and "E_MAX" columns of a RMF (which are corresponding - to the spectrum channel energies). - For the XMM EPIC *pn* and Chandra *ACIS*, the generated ARF does NOT have - the same number of data points to that of spectral channels, i.e., the - "ENERG_LO" and "ENERG_HI" columns of ARF is different to the "E_MIN" and - "E_MAX" columns of RMF. - Therefore it is necessary to interpolate and extrapolate the ARF curve - in order to match the spectrum (or RMF "EBOUNDS" extension). - As for the XMM EPIC *MOS1* and *MOS2*, the ARF data points match the - spectral channels, i.e., the energy positions of each ARF data point and - spectral channel are consistent. Thus the interpolation is not needed. - - References: - [1] CIAO: Auxiliary Response File - http://cxc.harvard.edu/ciao/dictionary/arf.html - [2] Definition of RMF and ARF file formats - https://heasarc.gsfc.nasa.gov/docs/heasarc/caldb/docs/memos/cal_gen_92_002/cal_gen_92_002.html - """ - filename = None - fitsobj = None - # only consider the "SPECTRUM" extension - header = None - energ_lo = None - energ_hi = None - specresp = None - # function of the interpolated ARF - f_interp = None - - def __init__(self, filename): - self.filename = filename - self.fitsobj = fits.open(filename) - ext_specresp = self.fitsobj["SPECRESP"] - self.header = ext_specresp.header - self.energ_lo = ext_specresp.data["ENERG_LO"] - self.energ_hi = ext_specresp.data["ENERG_HI"] - self.specresp = ext_specresp.data["SPECRESP"] - - def get_data(self, copy=True): - if copy: - return self.specresp.copy() - else: - return self.specresp - - def get_energy(self, mean="geometric"): - """ - Return the mean energy values of the ARF. - - Arguments: - * mean: type of the mean energy: - + "geometric": geometric mean, i.e., e = sqrt(e_min*e_max) - + "arithmetic": arithmetic mean, i.e., e = 0.5*(e_min+e_max) - """ - if mean == "geometric": - energy = np.sqrt(self.energ_lo * self.energ_hi) - elif mean == "arithmetic": - energy = 0.5 * (self.energ_lo + self.energ_hi) - else: - raise ValueError("Invalid mean type: %s" % mean) - return energy - - def interpolate(self, x=None, verbose=False): - """ - Cubic interpolate the ARF curve using `scipy.interpolate' - - If the requested point is outside of the data range, the - fill value of *zero* is returned. - - Arguments: - * x: points at which the interpolation to be calculated. - - Return: - If x is None, then the interpolated function is returned, - otherwise, the interpolated data are returned. - """ - if not hasattr(self, "f_interp") or self.f_interp is None: - energy = self.get_energy() - arf = self.get_data(copy=False) - if verbose: - print("INFO: ARF interpolating (this may take a while) ...", - file=sys.stderr) - f_interp = sp.interpolate.interp1d(energy, arf, kind="cubic", - bounds_error=False, fill_value=0.0, assume_sorted=True) - self.f_interp = f_interp - if x is not None: - return self.f_interp(x) - else: - return self.f_interp -# class ARF }}} - - -class RMF: # {{{ - """ - Class to handle the RMF (redistribution matrix file), - which maps from energy space into detector pulse height (or position) - space. Since detectors are not perfect, this involves a spreading of - the observed counts by the detector resolution, which is expressed as - a matrix multiplication. - For X-ray spectral analysis, the RMF encodes the probability R(E,p) - that a detected photon of energy E will be assisgned to a given - channel value (PHA or PI) of p. - - The standard Legacy format [2] for the RMF uses a binary table in which - each row contains R(E,p) for a single value of E as a function of p. - Non-zero sequences of elements of R(E,p) are encoded using a set of - variable length array columns. This format is compact but hard to - manipulate and understand. - - **CAVEAT/NOTE**: - + See also the above ARF CAVEAT/NOTE. - + The "EBOUNDS" extension contains the `CHANNEL', `E_MIN' and `E_MAX' - columns. This `CHANNEL' is the same as that of a spectrum. Therefore, - the energy values determined from the `E_MIN' and `E_MAX' columns are - used to interpolate and extrapolate the ARF curve. - + The `ENERG_LO' and `ENERG_HI' columns of the "MATRIX" extension are - the same as that of a ARF. - - References: - [1] CIAO: Redistribution Matrix File - http://cxc.harvard.edu/ciao/dictionary/rmf.html - [2] Definition of RMF and ARF file formats - https://heasarc.gsfc.nasa.gov/docs/heasarc/caldb/docs/memos/cal_gen_92_002/cal_gen_92_002.html - """ - filename = None - fitsobj = None - ## extension "MATRIX" - hdr_matrix = None - energ_lo = None - energ_hi = None - n_grp = None - f_chan = None - n_chan = None - # raw squeezed RMF matrix data - matrix = None - ## extension "EBOUNDS" - hdr_ebounds = None - channel = None - e_min = None - e_max = None - ## converted 2D RMF matrix/image from the squeezed binary table - # size: len(energ_lo) x len(channel) - rmfimg = None - - def __init__(self, filename): - self.filename = filename - self.fitsobj = fits.open(filename) - ## "MATRIX" extension - ext_matrix = self.fitsobj["MATRIX"] - self.hdr_matrix = ext_matrix.header - self.energ_lo = ext_matrix.data["ENERG_LO"] - self.energ_hi = ext_matrix.data["ENERG_HI"] - self.n_grp = ext_matrix.data["N_GRP"] - self.f_chan = ext_matrix.data["F_CHAN"] - self.n_chan = ext_matrix.data["N_CHAN"] - self.matrix = ext_matrix.data["MATRIX"] - ## "EBOUNDS" extension - ext_ebounds = self.fitsobj["EBOUNDS"] - self.hdr_ebounds = ext_ebounds.header - self.channel = ext_ebounds.data["CHANNEL"] - self.e_min = ext_ebounds.data["E_MIN"] - self.e_max = ext_ebounds.data["E_MAX"] - - def get_energy(self, mean="geometric"): - """ - Return the mean energy values of the RMF "EBOUNDS". - - Arguments: - * mean: type of the mean energy: - + "geometric": geometric mean, i.e., e = sqrt(e_min*e_max) - + "arithmetic": arithmetic mean, i.e., e = 0.5*(e_min+e_max) - """ - if mean == "geometric": - energy = np.sqrt(self.e_min * self.e_max) - elif mean == "arithmetic": - energy = 0.5 * (self.e_min + self.e_max) - else: - raise ValueError("Invalid mean type: %s" % mean) - return energy - - def get_rmfimg(self): - """ - Convert the RMF data in squeezed binary table (standard Legacy format) - to a 2D image/matrix. - """ - def _make_rmfimg_row(n_channel, dtype, f_chan, n_chan, mat_row): - # make sure that `f_chan' and `n_chan' are 1-D numpy array - f_chan = np.array(f_chan).reshape(-1) - f_chan -= 1 # FITS indices are 1-based - n_chan = np.array(n_chan).reshape(-1) - idx = np.concatenate([ np.arange(f, f+n) \ - for f, n in zip(f_chan, n_chan) ]) - rmfrow = np.zeros(n_channel, dtype=dtype) - rmfrow[idx] = mat_row - return rmfrow - # - if self.rmfimg is None: - # Make the 2D RMF matrix/image - n_energy = len(self.energ_lo) - n_channel = len(self.channel) - rmf_dtype = self.matrix[0].dtype - rmfimg = np.zeros(shape=(n_energy, n_channel), dtype=rmf_dtype) - for i in np.arange(n_energy)[self.n_grp > 0]: - rmfimg[i, :] = _make_rmfimg_row(n_channel, rmf_dtype, - self.f_chan[i], self.n_chan[i], self.matrix[i]) - self.rmfimg = rmfimg - return self.rmfimg - - def write_rmfimg(self, outfile, clobber=False): - rmfimg = self.get_rmfimg() - # merge headers - header = self.hdr_matrix.copy(strip=True) - header.extend(self.hdr_ebounds.copy(strip=True)) - outfits = fits.PrimaryHDU(data=rmfimg, header=header) - outfits.writeto(outfile, checksum=True, clobber=clobber) -# class RMF }}} - - -class Spectrum: # {{{ - """ - Class that deals with the X-ray spectrum file (usually *.pi). - """ - filename = None - # FITS object return by `fits.open()' - fitsobj = None - # header of "SPECTRUM" extension - header = None - # "SPECTRUM" extension data - channel = None - # name of the spectrum data column (i.e., type, "COUNTS" or "RATE") - spec_type = None - # unit of the spectrum data ("count" for "COUNTS", "count/s" for "RATE") - spec_unit = None - # spectrum data - spec_data = None - # several important keywords - EXPOSURE = None - BACKSCAL = None - RESPFILE = None - ANCRFILE = None - BACKFILE = None - # numpy dtype and FITS format code of the spectrum data - spec_dtype = None - spec_fits_format = None - - def __init__(self, filename): - self.filename = filename - self.fitsobj = fits.open(filename) - ext_spec = self.fitsobj["SPECTRUM"] - self.header = ext_spec.header.copy(strip=True) - colnames = ext_spec.columns.names - if "COUNTS" in colnames: - self.spec_type = "COUNTS" - elif "RATE" in colnames: - self.spec_type = "RATE" - else: - raise ValueError("Invalid spectrum file") - self.channel = ext_spec.data.columns["CHANNEL"].array - col_spec_data = ext_spec.data.columns[self.spec_type] - self.spec_data = col_spec_data.array.copy() - self.spec_unit = col_spec_data.unit - self.spec_dtype = col_spec_data.dtype - self.spec_fits_format = col_spec_data.format - # keywords - self.EXPOSURE = self.header.get("EXPOSURE") - self.BACKSCAL = self.header.get("BACKSCAL") - self.AREASCAL = self.header.get("AREASCAL") - self.RESPFILE = self.header.get("RESPFILE") - self.ANCRFILE = self.header.get("ANCRFILE") - self.BACKFILE = self.header.get("BACKFILE") - - def get_data(self, copy=True): - if copy: - return self.spec_data.copy() - else: - return self.spec_data - - def get_channel(self, copy=True): - if copy: - return self.channel.copy() - else: - return self.channel - - def reset_header_keywords(self, - keywords=["ANCRFILE", "RESPFILE", "BACKFILE"]): - """ - Reset the keywords to "NONE" to avoid confusion or mistakes. - """ - for kw in keywords: - if kw in self.header: - header[kw] = "NONE" - - def write(self, filename, clobber=False): - """ - Create a new "SPECTRUM" table/extension and replace the original - one, then write to output file. - """ - ext_spec_cols = fits.ColDefs([ - fits.Column(name="CHANNEL", format="I", array=self.channel), - fits.Column(name=self.spec_type, format=self.spec_fits_format, - unit=self.spec_unit, array=self.spec_data)]) - ext_spec = fits.BinTableHDU.from_columns(ext_spec_cols, - header=self.header) - self.fitsobj["SPECTRUM"] = ext_spec - self.fitsobj.writeto(filename, clobber=clobber, checksum=True) -# class Spectrum }}} - - -class SpectrumSet(Spectrum): # {{{ - """ - This class handles a set of spectrum, including the source spectrum, - RMF, ARF, and the background spectrum. - - **NOTE**: - The "COUNTS" column data are converted from "int32" to "float32", - since this spectrum will be subtracted/compensated according to the - ratios of ARFs. - """ - # ARF object for this spectrum - arf = None - # RMF object for this spectrum - rmf = None - # background Spectrum object for this spectrum - bkg = None - - # numpy dtype and FITS format code to which the spectrum data be - # converted if the data is "COUNTS" - _spec_dtype = np.float32 - _spec_fits_format = "E" - - def __init__(self, filename, arffile=None, rmffile=None, bkgfile=None): - super(self.__class__, self).__init__(filename) - # convert spectrum data type if necessary - if self.spec_data.dtype != self._spec_dtype: - self.spec_data = self.spec_data.astype(self._spec_dtype) - self.spec_dtype = self._spec_dtype - self.spec_fits_format = self._spec_fits_format - if arffile is not None: - self.arf = ARF(arffile) - if rmffile is not None: - self.rmf = RMF(rmffile) - if bkgfile is not None: - self.bkg = Spectrum(bkgfile) - - def get_energy(self, mean="geometric"): - """ - Get the energy values of each channel if RMF present. - - NOTE: - The "E_MIN" and "E_MAX" columns of the RMF is required to calculate - the spectrum channel energies. - And the channel energies are generally different to the "ENERG_LO" - and "ENERG_HI" of the corresponding ARF. - """ - if self.rmf is None: - return None - else: - return self.rmf.get_energy(mean=mean) - - def get_arf(self, mean="geometric", copy=True): - """ - Get the corresponding ARF curve data if the ARF presents. - - Return: - [ energy, resp ] - where the "energy" and "resp" are the ARF energy values and - spectral response array, respectively. - """ - if self.arf is None: - return None - else: - energy = self.arf.get_energy(mean=mean) - resp = self.arf.get_data(copy=copy) - return [ energy, resp ] - - def subtract_bkg(self, inplace=True, verbose=False): - """ - Subtract the background contribution from the source spectrum. - The `EXPOSURE' and `BACKSCAL' values are required to calculate - the fraction/ratio for the background subtraction. - - Arguments: - * inplace: whether replace the `spec_data' with the background- - subtracted spectrum data; If True, the attribute - `spec_bkg_subtracted' is also set to `True' when - the subtraction finished. - - Return: - background-subtracted spectrum data - """ - ratio = (self.EXPOSURE / self.bkg.EXPOSURE) * \ - (self.BACKSCAL / self.bkg.BACKSCAL) * \ - (self.AREASCAL / self.bkg.AREASCAL) - operation = " SUBTRACT_BACKGROUND: %s - %s * %s" % \ - (self.filename, ratio, self.bkg.filename) - if verbose: - print(operation, file=sys.stderr) - spec_data_subbkg = self.spec_data - ratio * self.bkg.get_data() - if inplace: - self.spec_data = spec_data_subbkg - self.spec_bkg_subtracted = True - # also record history - self.header.add_history(operation) - return spec_data_subbkg - - def subtract(self, spectrumset, cross_arf, verbose=False): - """ - Subtract the photons that originate from the surrounding regions - but were scattered into this spectrum due to the finite PSF. - - The background of this spectrum and the given spectrum should - both be subtracted before applying this subtraction for crosstalk - correction, as well as the below `compensate()' procedure. - - NOTE: - 1. The crosstalk ARF must be provided, since the `spectrumset.arf' - is required to be its ARF without taking crosstalk into account: - spec1_new = spec1 - spec2 * (cross_arf_2_to_1 / arf2) - 2. The ARF are interpolated to match the energies of spetral channels. - """ - operation = " SUBTRACT: %s - (%s/%s) * %s" % (self.filename, - cross_arf.filename, spectrumset.arf.filename, - spectrumset.filename) - if verbose: - print(operation, file=sys.stderr) - energy = self.get_energy() - arfresp_spec = spectrumset.arf.interpolate(x=energy, verbose=verbose) - arfresp_cross = cross_arf.interpolate(x=energy, verbose=verbose) - arf_ratio = arfresp_cross / arfresp_spec - # fix nan values due to division by zero - arf_ratio[np.isnan(arf_ratio)] = 0.0 - self.spec_data -= spectrumset.get_data() * arf_ratio - # record history - self.header.add_history(operation) - - def compensate(self, cross_arf, verbose=False): - """ - Compensate the photons that originate from this regions but were - scattered into the surrounding regions due to the finite PSF. - - formula: - spec1_new = spec1 + spec1 * (cross_arf_1_to_2 / arf1) - """ - operation = " COMPENSATE: %s + (%s/%s) * %s" % (self.filename, - cross_arf.filename, self.arf.filename, self.filename) - if verbose: - print(operation, file=sys.stderr) - energy = self.get_energy() - arfresp_this = self.arf.interpolate(x=energy, verbose=verbose) - arfresp_cross = cross_arf.interpolate(x=energy, verbose=verbose) - arf_ratio = arfresp_cross / arfresp_this - # fix nan values due to division by zero - arf_ratio[np.isnan(arf_ratio)] = 0.0 - self.spec_data += self.get_data() * arf_ratio - # record history - self.header.add_history(operation) - - def fix_negative(self, verbose=False): - """ - The subtractions may lead to negative counts, it may be necessary - to fix these channels with negative values. - """ - neg_counts = self.spec_data < 0 - N = len(neg_counts) - neg_channels = np.arange(N, dtype=np.int)[neg_counts] - if len(neg_channels) > 0: - print("WARNING: %d channels have NEGATIVE counts" % \ - len(neg_channels), file=sys.stderr) - i = 0 - while len(neg_channels) > 0: - i += 1 - if verbose: - if i == 1: - print("*** Fixing negative channels: iter %d..." % i, - end="", file=sys.stderr) - else: - print("%d..." % i, end="", file=sys.stderr) - for ch in neg_channels: - neg_val = self.spec_data[ch] - if ch < N-2: - self.spec_data[ch] = 0 - self.spec_data[(ch+1):(ch+3)] -= 0.5 * np.abs(neg_val) - else: - # just set to zero if it is the last 2 channels - self.spec_data[ch] = 0 - # update negative channels indices - neg_counts = self.spec_data < 0 - neg_channels = np.arange(N, dtype=np.int)[neg_counts] - if i > 0: - print("FIXED ***", file=sys.stderr) - # record history - self.header.add_history(" FIXED NEGATIVE CHANNELS") -# class SpectrumSet }}} - - -class Crosstalk: # {{{ - """ - Crosstalk correction. - """ - # `SpectrumSet' object for the spectrum to be corrected - spectrumset = None - # NOTE/XXX: do NOT use list (e.g., []) here, otherwise, all the - # instances will share these list properties. - # `SpectrumSet' and `ARF' objects corresponding to the spectra from - # which the photons were scattered into this spectrum. - cross_in_specset = None - cross_in_arf = None - # `ARF' objects corresponding to the regions to which the photons of - # this spectrum were scattered into. - cross_out_arf = None - # output filename to which write the corrected spectrum - outfile = None - - def __init__(self, config): - """ - Arguments: - * config: a section of the whole config file (`ConfigObj' object) - """ - self.cross_in_specset = [] - self.cross_in_arf = [] - self.cross_out_arf = [] - # this spectrum to be corrected - self.spectrumset = SpectrumSet(filename=config["spec"], - arffile=config["arf"], rmffile=config.get("rmf"), - bkgfile=config.get("bkg")) - # spectra and cross arf from which photons were scattered in - for reg_in in config["cross_in"].values(): - specset = SpectrumSet(filename=reg_in["spec"], - arffile=reg_in["arf"], rmffile=reg_in.get("rmf"), - bkgfile=reg_in.get("bkg")) - self.cross_in_specset.append(specset) - self.cross_in_arf.append(ARF(reg_in["cross_arf"])) - # regions into which the photons of this spectrum were scattered into - if "cross_out" in config.sections: - cross_arf = config["cross_out"].as_list("cross_arf") - for arffile in cross_arf: - self.cross_out_arf.append(ARF(arffile)) - # output filename - self.outfile = config["outfile"] - - def do_correction(self, subtract_bkg=True, fix_negative=False, - verbose=False): - """ - Perform the crosstalk correction. The background contribution - for each spectrum is subtracted first if `subtract_bkg' is True. - The basic correction procedures are recorded to the header. - """ - self.spectrumset.header.add_history("Crosstalk Correction BEGIN") - self.spectrumset.header.add_history(" TOOL: %s (v%s) @ %s" % (\ - os.path.basename(sys.argv[0]), __version__, - datetime.utcnow().isoformat())) - # background subtraction - if subtract_bkg: - if verbose: - print("INFO: subtract background ...", file=sys.stderr) - self.spectrumset.subtract_bkg(inplace=True, verbose=verbose) - # also apply background subtraction to the surrounding spectra - for specset in self.cross_in_specset: - specset.subtract_bkg(inplace=True, verbose=verbose) - # subtractions - if verbose: - print("INFO: apply subtractions ...", file=sys.stderr) - for specset, cross_arf in zip(self.cross_in_specset, - self.cross_in_arf): - self.spectrumset.subtract(spectrumset=specset, - cross_arf=cross_arf, verbose=verbose) - # compensations - if verbose: - print("INFO: apply compensations ...", file=sys.stderr) - for cross_arf in self.cross_out_arf: - self.spectrumset.compensate(cross_arf=cross_arf, - verbose=verbose) - # fix negative values in channels - if fix_negative: - if verbose: - print("INFO: fix negative channel values ...", file=sys.stderr) - self.spectrumset.fix_negative(verbose=verbose) - self.spectrumset.header.add_history("END Crosstalk Correction") - - def write(self, filename=None, clobber=False): - if filename is None: - filename = self.outfile - self.spectrumset.reset_header_keywords( - keywords=["ANCRFILE", "BACKFILE"]) - self.spectrumset.write(filename, clobber=clobber) -# class Crosstalk }}} - - -def set_argument(name, default, cmdargs, config): - value = default - if name in config.keys(): - value = config.as_bool(name) - value_cmd = vars(cmdargs)[name] - if value_cmd != default: - value = value_cmd # command arguments overwrite others - return value - - -def main(): - parser = argparse.ArgumentParser( - description="Correct the crosstalk effects for XMM EPIC spectra", - epilog="Version: %s (%s)" % (__version__, __date__)) - parser.add_argument("config", help="config file in which describes " +\ - "the crosstalk relations ('ConfigObj' syntax)") - parser.add_argument("-B", "--no-subtract-bkg", dest="subtract_bkg", - action="store_false", help="do NOT subtract background first") - parser.add_argument("-N", "--fix-negative", dest="fix_negative", - action="store_true", help="fix negative channel values") - parser.add_argument("-C", "--clobber", dest="clobber", - action="store_true", help="overwrite output file if exists") - parser.add_argument("-v", "--verbose", dest="verbose", - action="store_true", help="show verbose information") - args = parser.parse_args() - - config = ConfigObj(args.config) - - subtract_bkg = set_argument("subtract_bkg", True, args, config) - fix_negative = set_argument("fix_negative", False, args, config) - verbose = set_argument("verbose", False, args, config) - clobber = set_argument("clobber", False, args, config) - - for region in config.sections: - if verbose: - print("INFO: processing '%s' ..." % region, file=sys.stderr) - crosstalk = Crosstalk(config.get(region)) - crosstalk.do_correction(subtract_bkg=subtract_bkg, - fix_negative=fix_negative, verbose=verbose) - crosstalk.write(clobber=clobber) - - -if __name__ == "__main__": - main() - -# vim: set ts=4 sw=4 tw=0 fenc=utf-8 ft=python: # |