/usr/lib/python2.7/dist-packages/cpl/dfs.py is in python-cpl 0.6.2-2.
This file is owned by root:root, with mode 0o644.
The actual contents of the file can be viewed below.
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162 163 164 165 166 167 168 169 170 171 172 173 174 175 176 177 178 179 180 181 182 183 184 185 186 187 188 189 190 191 192 193 194 195 196 197 198 199 200 201 202 203 204 205 206 207 208 209 210 211 212 213 214 215 216 217 218 219 220 221 222 223 224 225 226 227 228 229 230 231 232 233 234 235 236 237 238 239 240 241 242 243 244 245 246 247 248 249 250 251 252 253 254 255 256 257 258 259 260 261 262 263 264 265 266 267 268 269 270 271 272 273 274 275 276 277 278 279 280 281 282 283 284 285 286 287 | import os
import sys
try:
from astropy.io import fits
except:
import pyfits as fits
import cpl
class ProcessingInfo(object):
'''This class contains 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, datapaths = None):
'''
: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 datapaths: Dictionary with frame tags as keys and directory paths
as values to provide a full path for the raw and
calibration frames. Optional.
:type datapaths: :class:`dict`
'''
if isinstance(source, str):
header = fits.open(source)[0].header
elif isinstance(source, fits.HDUList):
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 %s to header' %
source.__class__.__name__)
self.name = header['HIERARCH ESO PRO REC1 ID']
self.product = header['HIERARCH ESO PRO CATG']
self.orig_filename = header['PIPEFILE']
if datapaths and self.product in datapaths:
self.orig_filename = os.path.join(datapaths[self.product],
self.orig_filename)
pipe_id = header.get('HIERARCH ESO PRO REC1 PIPE ID')
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 REC1 DRS ID')
self.md5sum = header.get('DATAMD5')
self.md5sums = {}
self.calib = _get_rec_keys(header, 'CAL', 'CATG', 'NAME', datapaths)
for cat, md5 in _get_rec_keys(header, 'CAL', 'CATG', 'DATAMD5').items():
if isinstance(md5, list):
for m, f in zip(md5, self.calib[cat]):
if m is not None:
self.md5sums[f] = m
elif md5 is not None:
self.md5sums[self.calib[cat]] = md5
raw = _get_rec_keys(header, 'RAW', 'CATG', 'NAME', datapaths)
if raw:
self.tag = list(raw.keys())[0]
self.raw = raw[self.tag]
md5 = _get_rec_keys(header, 'RAW', 'CATG', 'DATAMD5')[self.tag]
if isinstance(md5, list):
for m, f in zip(md5, self.raw):
if m is not None:
self.md5sums[f] = m
elif md5 is not None:
self.md5sums[self.raw] = md5
else:
self.tag = None
self.input = None
param = _get_rec_keys(header, 'PARAM', 'NAME', 'VALUE')
self.param = dict()
for k,v in param.items():
self.param[k] = _best_type(v)
def create_recipe(self):
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):
if isinstance(scriptfile, str):
scriptfile = file(scriptfile, mode='w')
scriptfile.write('import cpl\n\n')
scriptfile.write('# Recipe: %s.%s, Version %s, CPL version %s\n' %
(self.pipeline, self.name, self.version[1],
self.cpl_version))
scriptfile.write('%s = cpl.Recipe(%s, version = %s)\n' %
(self.name, repr(self.name), repr(self.version[0])))
scriptfile.write('\n# Parameters:\n')
for k,v in self.param.items():
scriptfile.write('%s.param.%s = %s\n' % (self.name, k, repr(v)))
if self.calib:
scriptfile.write('\n# Calibration frames:\n')
for k,v in self.calib.items():
scriptfile.write('%s.calib.%s = %s\n' % (self.name, k, repr(v)))
scriptfile.write('\n# Process input frames:\n')
scriptfile.write('%s.tag = %s\n' % (self.name, repr(self.tag)))
scriptfile.write('res = %s(%s)\n' % (self.name, repr(self.raw)))
scriptfile.write('%s = res.%s\n' % (self.product.lower(), self.product))
scriptfile.write('%s.writeto(%s)\n' % (self.product.lower(),
repr(self.orig_filename)))
def printinfo(self):
print('Recipe: %s, Version %s, CPL version %s ' % (
self.name, self.version, self.cpl_version))
print('Parameters:')
for k,v in self.param.items():
print(' %s.%s.%s = %s' % (self.pipeline, self.name, k, v))
if self.calib:
print('Calibration frames:')
for k,v in self.calib.items():
if isinstance(v, str):
print(' %s %s' % (v,k))
else:
for n in v:
print(' %s %s' % (n,k))
print('Input frames:')
if isinstance(self.raw, str):
print(' %s %s' % (self.raw, self.tag))
else:
for n in self.raw:
print(' %s %s' % (n, self.tag))
def _get_rec_keys(header, key, name, value, datapaths = None):
'''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 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`
:param datapaths: Dictionary with frame tags as keys and directory paths
as values to provide a full path for the raw and
calibration frames. Optional.
:type datapaths: :class:`dict`
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
_get_rec_keys('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 REC1 %s%i' % (key, i)
k = header['%s %s' % (prefix, name)]
fn = header.get('%s %s' % (prefix, value))
if datapaths and k in datapaths:
fn = os.path.join(datapaths[k], fn)
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
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)
if __name__ == '__main__':
import sys
datapaths = {
'BIAS':'raw', 'DARK':'raw', 'FLAT':'raw', 'ARC':'raw', 'OBJECT':'raw',
'LINE_CATALOG':'aux', 'TRACE_TABLE':'aux', 'GEOMETRY_TABLE':'aux',
'MASTER_BIAS':'result', 'MASTER_DARK':'result', 'MASTER_FLAT':'result',
'WAVECAL_TABLE':'result', 'PIXTABLE_OBJECT':'result',
}
for arg in sys.argv[1:]:
print('---------------------')
print('file: %s' % arg)
pi = ProcessingInfo(arg, datapaths = datapaths)
pi.printinfo()
|