/usr/lib/python2.7/dist-packages/cpl/dfs.py is in python-cpl 0.7.2-1build2.
This file is owned by root:root, with mode 0o644.
The actual contents of the file can be viewed below.
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try: # pragma: no cover
from astropy.io import fits
except ImportError:
import pyfits as fits
import cpl
class ProcessingInfo(object):
'''Support for reading input files and parameters from the FITS
header of a CPL processed file.
This is done through the FITS headers that were written by the DFS function
called within the processing recipe.
.. attribute:: name
Recipe name
.. attribute:: version
Recipe version string
.. attribute:: pipeline
Pipeline name
.. attribute:: cpl_version
CPL version string
.. attribute:: tag
Tag name
.. attribute:: calib
Calibration frames from a FITS file processed with CPL.
The result of this function may directly set as :attr:`cpl.Recipe.calib`
attribute::
import cpl
myrecipe = cpl.Recipe('muse_bias')
myrecipe.calib = cpl.dfs.ProcessingInfo('MASTER_BIAS_0.fits').calib
.. note::
This will not work properly for files that had
:class:`astropy.io.fits.HDUList` inputs since they have assigned a
temporary file name only.
.. attribute:: raw
Raw (input) frames
.. note::
This will not work properly for files that had
:class:`astropy.io.fits.HDUList` inputs since they have assigned a
temporary file name only.
.. attribute:: param
Processing parameters.
The result of this function may directly set as :attr:`cpl.Recipe.param`
attribute::
import cpl
myrecipe = cpl.Recipe('muse_bias')
myrecipe.param = cpl.dfs.ProcessingInfo('MASTER_BIAS_0.fits').param
.. attribute:: md5sum
MD5 sum of the data portions of the output file (header keyword
'DATAMD5').
.. attribute:: md5sums
MD5 sums of the input and calibration files. :class:`dict` with the
file name as key and the corresponding MD5 sum as value.
.. note::
Due to a design decision in CPL, the raw input files are not
accompanied with the MD5 sum.
'''
def __init__(self, source, recno = -1):
'''
:param source: Object pointing to the result file header
:type source: :class:`str` or :class:`astropy.io.fits.HDUList`
or :class:`astropy.io.fits.PrimaryHDU` or
:class:`astropy.io.fits.Header`
:param recno: Record number. Optional. If not given, the last record
(with the highest record number) is used.
:type recno: :class:`int`
'''
if isinstance(source, str):
header = fits.open(source)[0].header
elif isinstance(source, (fits.HDUList, list)):
header = source[0].header
elif isinstance(source, fits.PrimaryHDU):
header = source.header
elif isinstance(source, (fits.Header, dict)):
header = source
else:
raise ValueError('Cannot assign type {0} to header'.format(
source.__class__.__name__))
if recno < 0:
for reccnt in range(1, 2**16):
if 'HIERARCH ESO PRO REC{0} ID'.format(reccnt) not in header:
break
recno += reccnt
self.name = header['HIERARCH ESO PRO REC{0} ID'.format(recno)]
self.product = header['HIERARCH ESO PRO CATG']
self.orig_filename = header['PIPEFILE']
pipe_id = header.get('HIERARCH ESO PRO REC{0} PIPE ID'.format(recno))
if pipe_id:
self.pipeline, version = pipe_id.split('/')
num_version = 0
for i in version.split('.'):
num_version = num_version * 100 + int(i)
self.version = (num_version, version)
else:
self.pipeline = None
self.version = None
self.cpl_version = header.get('HIERARCH ESO PRO REC{0} DRS ID'.format(recno))
self.md5sum = header.get('DATAMD5')
self.md5sums = {}
self.calib = ProcessingInfo._get_rec_keys(header, recno, 'CAL', 'CATG', 'NAME')
for cat, md5 in ProcessingInfo._get_rec_keys(header, recno, 'CAL', 'CATG',
'DATAMD5').items():
if isinstance(md5, list):
for i, m in enumerate(md5):
if m is not None:
self.md5sums[self.calib[cat][i]] = m
elif md5 is not None:
self.md5sums[self.calib[cat]] = md5
raw = ProcessingInfo._get_rec_keys(header, recno, 'RAW', 'CATG', 'NAME')
if raw:
self.tag = list(raw.keys())[0]
self.raw = raw[self.tag]
md5 = ProcessingInfo._get_rec_keys(header, recno, 'RAW', 'CATG',
'DATAMD5')[self.tag]
if isinstance(md5, list):
for i, m in enumerate(md5):
if m is not None:
self.md5sums[self.raw[i]] = m
elif md5 is not None:
self.md5sums[self.raw] = md5
else:
self.tag = None
self.raw = None
self.input = None
param = ProcessingInfo._get_rec_keys(header, recno, 'PARAM', 'NAME', 'VALUE')
self.param = dict()
for k,v in param.items():
self.param[k] = ProcessingInfo._best_type(v)
def create_recipe(self):
'''Create a recipe and configure it with the parameters, calibration frames,
and the input tag. The recipe version will be the latest available one.
'''
recipe = cpl.Recipe(self.name)
recipe.param = self.param
recipe.calib = self.calib
recipe.tag = self.tag
return recipe
def create_script(self, scriptfile = sys.stdout):
'''Create a sample script that creates the recipe, configures it with
the parameters, calibration frames and input tags, and finally
starts the recipe.
'''
if isinstance(scriptfile, str):
scriptfile = file(scriptfile, mode='w')
scriptfile.write('import cpl\n\n')
scriptfile.write('# Recipe: {0}.{1}, Version {2}, CPL version {3}\n'.format(
self.pipeline, self.name, self.version[1], self.cpl_version))
scriptfile.write('{0} = cpl.Recipe({1}, version = {2})\n'.format(
self.name, repr(self.name), repr(self.version[0])))
scriptfile.write('\n# Parameters:\n')
for k,v in self.param.items():
scriptfile.write('{0}.param.{1} = {2}\n'.format(self.name, k, repr(v)))
if self.calib:
scriptfile.write('\n# Calibration frames:\n')
for k,v in self.calib.items():
scriptfile.write('{0}.calib.{1} = {2}\n'.format(self.name, k, repr(v)))
scriptfile.write('\n# Process input frames:\n')
scriptfile.write('{0}.tag = {1}\n'.format(self.name, repr(self.tag)))
scriptfile.write('res = {0}({1})\n'.format(self.name, repr(self.raw)))
# scriptfile.write('{0} = res.{1}\n'.format(self.product.lower(), self.product))
# scriptfile.write('{0}.writeto({1})\n'.format(self.product.lower(),
# repr(self.orig_filename)))
def __str__(self):
s = 'Recipe: {0}, Version {1}, CPL version {2}\n'.format(
self.name, self.version, self.cpl_version)
s += 'Parameters:\n'
for k,v in self.param.items():
s += ' {0}.{1}.{2} = {3}\n'.format(self.pipeline, self.name, k, v)
if self.calib:
s += 'Calibration frames:\n'
for k,v in self.calib.items():
if isinstance(v, (str, unicode)):
s += ' {0} {1}\n'.format(v,k)
else:
m = max(len(n) for n in v)
for n in v:
s += ' {0:<{width}} {1}\n'.format(n, m, width = m)
if self.raw is not None:
s += 'Input frames:\n'
if isinstance(self.raw, (str, unicode)):
s += ' {0} {1}\n'.format(self.raw, self.tag)
else:
m = max(len(n) for n in self.raw)
for n in self.raw:
s += ' {0:<{width}} {1}\n'.format(n, self.tag, width = m)
return s
def printinfo(self):
'''Print the recipe information to standard output.
'''
print(str(self))
@staticmethod
def _get_rec_keys(header, recno, key, name, value):
'''Get a dictionary of key/value pairs from the DFS section of the
header.
:param key: Common keyword for the value. Usually 'PARAM' for
parameters, 'RAW' for raw frames, and 'CAL' for
calibration frames.
:type key: :class:`str`
:param recno: Record number.
:type recno: :class:`int`
:param name: Header keyword (last part) for the name of each key
:type name: :class:`str`
:param value: Header keyword (last part) for the value of each key
:type name: :class:`str`
When the header
HIERARCH ESO PRO REC1 PARAM1 NAME = 'nifu'
HIERARCH ESO PRO REC1 PARAM1 VALUE = '1'
HIERARCH ESO PRO REC1 PARAM2 NAME = 'combine'
HIERARCH ESO PRO REC1 PARAM2 VALUE = 'median'
is called with
ProcessingInfo._get_rec_keys(1, 'PARAM', 'NAME', 'VALUE')
the returned dictionary will contain the keys
res['nifu'] = '1'
res['combine'] = 'median'
'''
res = dict()
for i in range(1, 2**16):
try:
prefix = 'HIERARCH ESO PRO REC{0} {1}{2}'.format(recno, key, i)
k = header['{0} {1}'.format(prefix, name)]
fn = header.get('{0} {1}'.format(prefix, value))
if k not in res:
res[k] = fn
elif isinstance(res[k], list):
res[k].append(fn)
else:
res[k] = [ res[k], fn ]
except KeyError:
break
return res
@staticmethod
def _best_type(value):
'''Convert the value to the best applicable type: :class:`int`,
:class:`float`, :class:`bool` or :class`str`.
:param value: Value to convert.
:type value: :class:`str`
'''
for t in int, float:
try:
return t(value)
except ValueError:
pass
return {'true':True, 'false':False}.get(value, value)
@staticmethod
def list(source):
'''Get a list of all `ProcessingInfo` objects in the FITS header. The
list is sorted by the execution order.
:param source: Object pointing to the result file header
:type source: :class:`str` or :class:`astropy.io.fits.HDUList`
or :class:`astropy.io.fits.PrimaryHDU` or
:class:`astropy.io.fits.Header`
'''
pi = []
for i in range(1, 2**16):
try:
pi.append(ProcessingInfo(source, i))
except KeyError:
break
return pi
if __name__ == '__main__':
for arg in sys.argv[1:]:
print('{0}\nfile: {1}'.format('-' * 72, arg))
pi = cpl.dfs.ProcessingInfo(arg)
pi.printinfo()
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