def main(night_name=None, key=None, filename=None):
"""
Manually add a file the the calibDB with "key"
i.e. adds
key night_name filename human-date unix-time
to the calibDB and copies "filename" from .../reduced_dir/night_name/ into
the calibDB
Note filename must be in .../reduced_dir/night_name/
"""
# ----------------------------------------------------------------------
# Set up
# ----------------------------------------------------------------------
# get parameters from config files/run time args/load paths + calibdb
p = spirouStartup.Begin(recipe=__NAME__)
# deal with arguments being None (i.e. get from sys.argv)
pos = [0, 1]
fmt = [str, str]
names = ['key', 'filename']
call = [key, filename]
# now get custom arguments
customargs = spirouStartup.GetCustomFromRuntime(p,
pos,
fmt,
names,
calls=call)
# get parameters from configuration files and run time arguments
p = spirouStartup.LoadArguments(p,
night_name,
customargs=customargs,
mainfitsfile='filename',
mainfitsdir='reduced')
# as we have custom arguments need to load the calibration database
p = spirouStartup.LoadCalibDB(p)
# ----------------------------------------------------------------------
# Read image file
# ----------------------------------------------------------------------
# read the image data
image, hdr, nbo, nx = spirouImage.ReadData(p, p['FITSFILENAME'])
# ----------------------------------------------------------------------
# Move to calibDB and update calibDB
# ----------------------------------------------------------------------
# set dark key
keydb = p['KEY']
# copy dark fits file to the calibDB folder
spirouDB.PutCalibFile(p, p['FITSFILENAME'])
# update the master calib DB file with new key
spirouDB.UpdateCalibMaster(p, keydb, p['FILENAME'], hdr)
# ----------------------------------------------------------------------
# End Message
# ----------------------------------------------------------------------
p = spirouStartup.End(p)
# return a copy of locally defined variables in the memory
return dict(locals())
def main(night_name=None, oldfile=None, newfile=None):
# ----------------------------------------------------------------------
# Set up
# ----------------------------------------------------------------------
# get parameters from config files/run time args/load paths + calibdb
p = spirouStartup.Begin(recipe=__NAME__)
# deal with arguments being None (i.e. get from sys.argv)
pos = [0, 1]
fmt = [str, str]
names = ['oldfile', 'newfile']
call = [oldfile, newfile]
# now get custom arguments
customargs = spirouStartup.GetCustomFromRuntime(p,
pos,
fmt,
names,
calls=call)
# get parameters from configuration files and run time arguments
p = spirouStartup.LoadArguments(p,
night_name,
customargs=customargs,
mainfitsfile='newfile')
# ----------------------------------------------------------------------
# Get files
# ----------------------------------------------------------------------
# check that path exists
emsg = '{0} file = {1} does not exist'
if not os.path.exists(p['OLDFILE']):
WLOG(p, 'error', emsg.format('old', p['OLDFILE']))
# check that paths exists
if not os.path.exists(p['NEWFILE']):
WLOG(p, 'error', emsg.format('new', p['NEWFILE']))
# load files
data1, hdr1, _, _ = spirouImage.ReadImage(p, filename=oldfile)
data2, hdr2, _, _ = spirouImage.ReadImage(p, filename=newfile)
# ----------------------------------------------------------------------
# Do difference image
# ----------------------------------------------------------------------
diff_image(p, data1, data2, 'old image', 'new image', scale=(1, 99))
# ----------------------------------------------------------------------
# End Message
# ----------------------------------------------------------------------
wmsg = 'Recipe {0} has been successfully completed'
WLOG(p, 'info', wmsg.format(p['PROGRAM']))
# return a copy of locally defined variables in the memory
return dict(locals())
def main(night_name=None, reffile=None):
# ----------------------------------------------------------------------
# Set up
# ----------------------------------------------------------------------
# get parameters from config files/run time args/load paths + calibdb
p = spirouStartup.Begin(recipe=__NAME__)
# deal with reference file being None (i.e. get from sys.argv)
if reffile is None:
customargs = spirouStartup.GetCustomFromRuntime(p, [0], [str],
['reffile'])
else:
customargs = dict(reffile=reffile)
# get parameters from configuration files and run time arguments
p = spirouStartup.LoadArguments(p, night_name, customargs=customargs,
mainfitsfile='reffile',
mainfitsdir='reduced')
# ----------------------------------------------------------------------
# Construct reference filename and get fiber type
# ----------------------------------------------------------------------
p, reffilename = spirouStartup.SingleFileSetup(p, filename=p['REFFILE'],
skipcheck=True)
p['REFFILENAME'] = reffilename
p.set_source('REFFILENAME', __NAME__ + '.main()')
# ----------------------------------------------------------------------
# Read image file
# ----------------------------------------------------------------------
# read the image data
data, hdr, nbo, nx = spirouImage.ReadData(p, p['REFFILENAME'])
# ----------------------------------------------------------------------
# Add keys and save file
# ----------------------------------------------------------------------
newfilename = p['REFFILE'].replace('.fits', '_edit.fits')
newpath = os.path.join(p['ARG_FILE_DIR'], newfilename)
# add keys from original header file
hdict = spirouImage.CopyOriginalKeys(hdr)
# set the version
hdict = spirouImage.AddKey(p, hdict, HEADER_KEY, value=HEADER_VALUE)
# log saving
wmsg = 'Writing file {0} to {1}'
WLOG(p, '', wmsg.format(newfilename, p['ARG_FILE_DIR']))
# save drift values
p = spirouImage.WriteImage(p, newpath, data, hdict)
# ----------------------------------------------------------------------
# End Message
# ----------------------------------------------------------------------
p = spirouStartup.End(p)
# return a copy of locally defined variables in the memory
return dict(locals())
def main(night_name=None, ufiles=None):
"""
cal_preprocess_spirou.py main function, if night_name and files are
None uses arguments from run time i.e.:
cal_preprocess_spirou.py [night_directory] [fitsfilename]
:param night_name: string or None, the folder within data raw directory
containing files (also reduced directory) i.e.
/data/raw/20170710 would be "20170710" but
/data/raw/AT5/20180409 would be "AT5/20180409"
:param ufiles: string, list or None, the list of files to process
Note can include wildcard i.e. "*.fits"
(if None assumes arg_file_names was set from run time)
:return ll: dictionary, containing all the local variables defined in
main
"""
# ----------------------------------------------------------------------
# Set up
# ----------------------------------------------------------------------
# get parameters from config files/run time args/load paths + calibdb
p = spirouStartup.Begin(recipe=__NAME__)
# need custom args (to accept full path or wild card
if ufiles is None:
names, types = ['ufiles'], [str]
customargs = spirouStartup.GetCustomFromRuntime(p, [0], types, names,
last_multi=True)
else:
customargs = dict(ufiles=ufiles)
# get parameters from configuration files and run time arguments
p = spirouStartup.LoadArguments(p, night_name, customargs=customargs,
mainfitsdir='raw')
# ----------------------------------------------------------------------
# Get hot pixels for corruption check
# ----------------------------------------------------------------------
hotpixels = spirouImage.PPGetHotPixels(p)
# ----------------------------------------------------------------------
# Process files (including wildcards)
# ----------------------------------------------------------------------
# get raw folder (assume all files are in the root directory)
rawdir = spirouConfig.Constants.RAW_DIR(p)
try:
ufiles = spirouFile.Paths(p['UFILES'], root=rawdir).abs_paths
except PathException as e:
WLOG(p, 'error', e)
# log how many files were found
wmsg = '{0} files found'
WLOG(p, '', wmsg.format(len(ufiles)))
# storage for output files
p['OUTPUT_NAMES'] = []
p.set_source('OUTPUT_NAMES', __NAME__ + '.main()')
# loop around files
for u_it, ufile in enumerate(ufiles):
# log the file process
wmsg = 'Processing file {0} ({1} of {2})'
WLOG(p, '', spirouStartup.spirouStartup.HEADER)
bfilename = os.path.basename(ufile)
WLOG(p, 'info', wmsg.format(bfilename, u_it+1, len(ufiles)))
WLOG(p, '', spirouStartup.spirouStartup.HEADER)
# ------------------------------------------------------------------
# Check that we can process file
# ------------------------------------------------------------------
# check if ufile exists
if not os.path.exists(ufile):
wmsg = 'File {0} does not exist... skipping'
WLOG(p, 'warning', wmsg.format(ufile))
continue
# skip processed files
elif p['PROCESSED_SUFFIX'] in bfilename:
wmsg = 'File {0} has been processed... skipping'
WLOG(p, 'warning', wmsg.format(ufile))
continue
# skip non-fits files
elif '.fits' not in bfilename:
wmsg = 'File {0} not a fits file... skipping'
WLOG(p, 'warning', wmsg.format(ufile))
continue
# skip index file
elif bfilename == spirouConfig.Constants.INDEX_OUTPUT_FILENAME():
wmsg = 'Skipping index fits file'
WLOG(p, 'warning', wmsg.format(ufile))
continue
# ------------------------------------------------------------------
# Read image file
# ------------------------------------------------------------------
# read the image data
rout = spirouImage.ReadImage(p, filename=ufile)
image, hdr, nx, ny = rout
# ------------------------------------------------------------------
# Identify file (and update filename, header and comments)
# ------------------------------------------------------------------
ufile, hdr = spirouImage.IdentifyUnProFile(p, ufile, hdr)
# ------------------------------------------------------------------
# correct image
# ------------------------------------------------------------------
# correct for the top and bottom reference pixels
WLOG(p, '', 'Correcting for top and bottom pixels')
image = spirouImage.PPCorrectTopBottom(p, image)
# correct by a median filter from the dark amplifiers
wmsg = 'Correcting by the median filter from dark amplifiers'
WLOG(p, '', wmsg)
image = spirouImage.PPMedianFilterDarkAmps(p, image)
# correct for the 1/f noise
wmsg = 'Correcting for the 1/f noise'
WLOG(p, '', wmsg)
image = spirouImage.PPMedianOneOverfNoise2(p, image)
# ------------------------------------------------------------------
# Quality control to check for corrupt files
# ------------------------------------------------------------------
# set passed variable and fail message list
passed, fail_msg = True, []
qc_values, qc_names, qc_logic, qc_pass = [], [], [], []
# ----------------------------------------------------------------------
# get pass condition
cout = spirouImage.PPTestForCorruptFile(p, image, hotpixels)
snr_hotpix, rms_list = cout
# print out SNR hotpix value
wmsg = 'Corruption check: SNR Hotpix value = {0:.5e}'
WLOG(p, '', wmsg.format(snr_hotpix))
#deal with printing corruption message
if snr_hotpix < p['PP_CORRUPT_SNR_HOTPIX']:
# add failed message to fail message list
fargs = [snr_hotpix, p['PP_CORRUPT_SNR_HOTPIX'],ufile ]
fmsg = ('File was found to be corrupted. (SNR_HOTPIX < threshold, '
'{0:.4e} < {1:.4e}). File will not be saved. '
'File = {2}'.format(*fargs))
fail_msg.append(fmsg)
passed = False
qc_pass.append(0)
else:
qc_pass.append(1)
# add to qc header lists
qc_values.append(snr_hotpix)
qc_names.append('snr_hotpix')
qc_logic.append('snr_hotpix < {0:.5e}'
''.format(p['PP_CORRUPT_SNR_HOTPIX']))
# ----------------------------------------------------------------------
if np.max(rms_list) > p['PP_CORRUPT_RMS_THRES']:
# add failed message to fail message list
fargs = [np.max(rms_list), p['PP_CORRUPT_RMS_THRES'], ufile]
fmsg = ('File was found to be corrupted. (RMS < threshold, '
'{0:.4e} > {1:.4e}). File will not be saved. '
'File = {0}'.format(*fargs))
fail_msg.append(fmsg)
passed = False
qc_pass.append(0)
else:
qc_pass.append(1)
# add to qc header lists
qc_values.append(np.max(rms_list))
qc_names.append('max(rms_list)')
qc_logic.append('max(rms_list) > {0:.4e}'
''.format(p['PP_CORRUPT_RMS_THRES']))
# ----------------------------------------------------------------------
# finally log the failed messages and set QC = 1 if we pass the
# quality control QC = 0 if we fail quality control
if passed:
WLOG(p, 'info', 'QUALITY CONTROL SUCCESSFUL - Well Done -')
p['QC'] = 1
p.set_source('QC', __NAME__ + '/main()')
else:
for farg in fail_msg:
wmsg = 'QUALITY CONTROL FAILED: {0}'
WLOG(p, 'warning', wmsg.format(farg))
p['QC'] = 0
p.set_source('QC', __NAME__ + '/main()')
WLOG(p, 'warning', '\tFile not written')
continue
# store in qc_params
qc_params = [qc_names, qc_values, qc_logic, qc_pass]
# ------------------------------------------------------------------
# rotate image
# ------------------------------------------------------------------
# rotation to match HARPS orientation (expected by DRS)
image = spirouImage.RotateImage(image, p['RAW_TO_PP_ROTATION'])
# ------------------------------------------------------------------
# Save rotated image
# ------------------------------------------------------------------
# construct rotated file name
outfits = spirouConfig.Constants.PP_FILE(p, bfilename)
outfitsname = os.path.basename(outfits)
# log that we are saving rotated image
WLOG(p, '', 'Saving Rotated Image in ' + outfitsname)
# add keys from original header file
hdict = spirouImage.CopyOriginalKeys(hdr)
# set the version
hdict = spirouImage.AddKey(p, hdict, p['KW_PPVERSION'])
hdict = spirouImage.AddKey(p, hdict, p['KW_PID'], value=p['PID'])
# set the inputs
hdict = spirouImage.AddKey1DList(p, hdict, p['KW_INFILE1'],
dim1name='file',
values=[os.path.basename(ufile)])
# add qc parameters
hdict = spirouImage.AddKey(p, hdict, p['KW_DRS_QC'], value=p['QC'])
hdict = spirouImage.AddKey1DList(p, hdict, p['KW_DRS_QC_NAME'],
values=qc_names)
hdict = spirouImage.AddQCKeys(p, hdict, qc_params)
# set the DRS type (for file indexing)
p['DRS_TYPE'] = 'RAW'
p.set_source('DRS_TYPE', __NAME__ + '.main()')
# write to file
p = spirouImage.WriteImage(p, outfits, image, hdict)
# index this file
p = spirouStartup.End(p, outputs='pp', end=False)
# ------------------------------------------------------------------
# append to output storage in p
# ------------------------------------------------------------------
p['OUTPUT_NAMES'].append(outfitsname)
# ----------------------------------------------------------------------
# End Message
# ----------------------------------------------------------------------
p = spirouStartup.End(p, outputs=None)
# return a copy of locally defined variables in the memory
return dict(locals())
def main(night_name=None, flatfile=None):
# ----------------------------------------------------------------------
# Set up
# ----------------------------------------------------------------------
# get parameters from config files/run time args/load paths + calibdb
p = spirouStartup.Begin(recipe=__NAME__)
# deal with arguments being None (i.e. get from sys.argv)
name, lname = ['flatfile'], ['Reference file']
req, call, call_priority = [True], [flatfile], [True]
# now get custom arguments
customargs = spirouStartup.GetCustomFromRuntime(p, [0], [str], name, req,
call, call_priority, lname)
# get parameters from configuration files and run time arguments
p = spirouStartup.LoadArguments(p,
night_name,
customargs=customargs,
mainfitsfile='flatfile')
# ----------------------------------------------------------------------
# Construct reference filename and get fiber type
# ----------------------------------------------------------------------
p, reffile = spirouStartup.SingleFileSetup(p, filename=p['FLATFILE'])
# ----------------------------------------------------------------------
# Once we have checked the e2dsfile we can load calibDB
# ----------------------------------------------------------------------
# as we have custom arguments need to load the calibration database
p = spirouStartup.LoadCalibDB(p)
# ----------------------------------------------------------------------
# Get the required fiber type from the constants file
# ----------------------------------------------------------------------
# get the fiber type (set to AB)
p['FIBER'] = p['EM_FIB_TYPE']
p['FIBER_TYPES'] = [p['EM_FIB_TYPE']]
# ----------------------------------------------------------------------
# Read flat image file
# ----------------------------------------------------------------------
# read the image data (for the header only)
image, hdr, ny, nx = spirouImage.ReadData(p, reffile)
# ----------------------------------------------------------------------
# fix for un-preprocessed files
# ----------------------------------------------------------------------
image = spirouImage.FixNonPreProcess(p, image)
# ----------------------------------------------------------------------
# Get basic image properties
# ----------------------------------------------------------------------
# create loc
loc = ParamDict()
# get sig det value
p = spirouImage.GetSigdet(p, hdr, name='sigdet')
# get exposure time
p = spirouImage.GetExpTime(p, hdr, name='exptime')
# get gain
p = spirouImage.GetGain(p, hdr, name='gain')
# ----------------------------------------------------------------------
# Resize flat image
# ----------------------------------------------------------------------
# rotate the image and convert from ADU/s to e-
image2 = spirouImage.ConvertToE(spirouImage.FlipImage(p, image), p=p)
# convert NaN to zeros
image2 = np.where(~np.isfinite(image2), np.zeros_like(image2), image2)
# resize image
bkwargs = dict(xlow=p['IC_CCDX_LOW'],
xhigh=p['IC_CCDX_HIGH'],
ylow=p['IC_CCDY_LOW'],
yhigh=p['IC_CCDY_HIGH'],
getshape=False)
image2 = spirouImage.ResizeImage(p, image2, **bkwargs)
# save flat to to loc and set source
loc['IMAGE'] = image2
loc.set_sources(['image'], __NAME__ + '/main()')
# log change in data size
wmsg = 'Image format changed to {0}x{1}'
WLOG(p, '', wmsg.format(*image2.shape))
# ----------------------------------------------------------------------
# Read shape or tilt slit angle
# ----------------------------------------------------------------------
# set source of tilt file
tsource = __NAME__ + '/main() + /spirouImage.ReadTiltFile'
if p['IC_EXTRACT_TYPE'] in EXTRACT_SHAPE_TYPES:
# log progress
WLOG(p, '', 'Debananafying (straightening) image')
# get the shape map
p, loc['SHAPE'] = spirouImage.ReadShapeMap(p, hdr)
loc.set_source('SHAPE', tsource)
else:
# get tilts
p, loc['TILT'] = spirouImage.ReadTiltFile(p, hdr)
loc.set_source('TILT', tsource)
# ----------------------------------------------------------------------
# Read blaze
# ----------------------------------------------------------------------
# get tilts
p, loc['BLAZE'] = spirouImage.ReadBlazeFile(p, hdr)
loc.set_source('BLAZE', __NAME__ + '/main() + /spirouImage.ReadBlazeFile')
# set number of orders from blaze file
loc['NBO'] = loc['BLAZE'].shape[0]
loc.set_source('NBO', __NAME__ + '/main()')
# ------------------------------------------------------------------
# Read wavelength solution
# ------------------------------------------------------------------
# set source of wave file
wsource = __NAME__ + '/main() + /spirouImage.GetWaveSolution'
# Force A and B to AB solution
if p['FIBER'] in ['A', 'B']:
wave_fiber = 'AB'
else:
wave_fiber = p['FIBER']
# get wave image
wout = spirouImage.GetWaveSolution(p,
hdr=hdr,
return_wavemap=True,
return_filename=True,
fiber=wave_fiber)
loc['WAVEPARAMS'], loc['WAVE'], loc['WAVEFILE'], loc['WSOURCE'] = wout
loc.set_sources(['WAVEPARAMS', 'WAVE', 'WAVEFILE', 'WSOURCE'], wsource)
# ------------------------------------------------------------------
# Get localisation coefficients
# ------------------------------------------------------------------
# storage for fiber parameters
loc['ALL_ACC'] = OrderedDict()
loc['ALL_ASS'] = OrderedDict()
# get this fibers parameters
for fiber in p['FIBER_TYPES']:
p = spirouImage.FiberParams(p, fiber, merge=True)
# get localisation fit coefficients
p, loc = spirouLOCOR.GetCoeffs(p, hdr, loc=loc)
# save all fibers
loc['ALL_ACC'][fiber] = loc['ACC']
loc['ALL_ASS'][fiber] = loc['ASS']
# ------------------------------------------------------------------
# Get telluric and telluric mask and add to loc
# ------------------------------------------------------------------
# log process
wmsg = 'Loading telluric model and locating "good" tranmission'
WLOG(p, '', wmsg)
# load telluric and get mask (add to loc)
loc = spirouExM.get_telluric(p, loc)
# ------------------------------------------------------------------
# Make 2D map of orders
# ------------------------------------------------------------------
# log progress
WLOG(p, '', 'Making 2D map of order locations')
# make the 2D wave-image
loc = spirouExM.order_profile(p, loc)
# ------------------------------------------------------------------
# Make 2D map of wavelengths accounting for shape / tilt
# ------------------------------------------------------------------
# log progress
WLOG(p, '', 'Mapping pixels on to wavelength grid')
# make the 2D map of wavelength
loc = spirouExM.create_wavelength_image(p, loc)
# ------------------------------------------------------------------
# Use spectra wavelength to create 2D image from wave-image
# ------------------------------------------------------------------
if p['EM_SAVE_MASK_MAP'] or p['EM_SAVE_TELL_SPEC']:
# log progress
WLOG(p, '', 'Creating image from wave-image interpolation')
# create image from waveimage
wkwargs = dict(x=loc['TELL_X'], y=loc['TELL_Y'])
loc = spirouExM.create_image_from_waveimage(loc, **wkwargs)
else:
loc['SPE'] = np.zeros_like(image2).astype(float)
# ------------------------------------------------------------------
# Create 2D mask (min to max lambda + transmission threshold)
# ------------------------------------------------------------------
if p['EM_SAVE_MASK_MAP']:
# log progress
WLOG(p, '', 'Creating wavelength/tranmission mask')
# create mask
loc = spirouExM.create_mask(p, loc)
else:
loc['TELL_MASK_2D'] = np.zeros_like(image2).astype(bool)
# ----------------------------------------------------------------------
# Quality control
# ----------------------------------------------------------------------
# set passed variable and fail message list
passed, fail_msg = True, []
qc_values, qc_names, qc_logic, qc_pass = [], [], [], []
# TODO: Needs doing
# finally log the failed messages and set QC = 1 if we pass the
# quality control QC = 0 if we fail quality control
if passed:
WLOG(p, 'info', 'QUALITY CONTROL SUCCESSFUL - Well Done -')
p['QC'] = 1
p.set_source('QC', __NAME__ + '/main()')
else:
for farg in fail_msg:
wmsg = 'QUALITY CONTROL FAILED: {0}'
WLOG(p, 'warning', wmsg.format(farg))
p['QC'] = 0
p.set_source('QC', __NAME__ + '/main()')
# add to qc header lists
qc_values.append('None')
qc_names.append('None')
qc_logic.append('None')
qc_pass.append(1)
# store in qc_params
qc_params = [qc_names, qc_values, qc_logic, qc_pass]
# ------------------------------------------------------------------
# Construct parameters for header
# ------------------------------------------------------------------
hdict = OrderedDict()
# set the version
hdict = spirouImage.AddKey(p, hdict, p['KW_VERSION'])
hdict = spirouImage.AddKey(p, hdict, p['KW_DRS_DATE'], value=p['DRS_DATE'])
hdict = spirouImage.AddKey(p, hdict, p['KW_DATE_NOW'], value=p['DATE_NOW'])
hdict = spirouImage.AddKey(p, hdict, p['KW_PID'], value=p['PID'])
# set the input files
if loc['SHAPE'] is not None:
hdict = spirouImage.AddKey(p,
hdict,
p['KW_CDBSHAPE'],
value=p['SHAPFILE'])
else:
hdict = spirouImage.AddKey(p,
hdict,
p['KW_CDBTILT'],
value=p['TILTFILE'])
hdict = spirouImage.AddKey(p, hdict, p['KW_CDBBLAZE'], value=p['BLAZFILE'])
hdict = spirouImage.AddKey(p, hdict, p['KW_CDBLOCO'], value=p['LOCOFILE'])
hdict = spirouImage.AddKey(p,
hdict,
p['KW_CDBWAVE'],
value=loc['WAVEFILE'])
hdict = spirouImage.AddKey(p,
hdict,
p['KW_WAVESOURCE'],
value=loc['WSOURCE'])
hdict = spirouImage.AddKey1DList(p,
hdict,
p['KW_INFILE1'],
dim1name='file',
values=p['FLATFILE'])
# add name of the TAPAS y data
hdict = spirouImage.AddKey(p,
hdict,
p['KW_EM_TELLY'],
value=loc['TELLSPE'])
# add name of the localisation fits file used
hfile = os.path.basename(loc['LOCO_CTR_FILE'])
hdict = spirouImage.AddKey(p, hdict, p['kw_EM_LOCFILE'], value=hfile)
# add the max and min wavelength threshold
hdict = spirouImage.AddKey(p,
hdict,
p['kw_EM_MINWAVE'],
value=p['EM_MIN_LAMBDA'])
hdict = spirouImage.AddKey(p,
hdict,
p['kw_EM_MAXWAVE'],
value=p['EM_MAX_LAMBDA'])
# add qc parameters
hdict = spirouImage.AddKey(p, hdict, p['KW_DRS_QC'], value=p['QC'])
hdict = spirouImage.AddQCKeys(p, hdict, qc_params)
# add the transmission cut
hdict = spirouImage.AddKey(p,
hdict,
p['kw_EM_TRASCUT'],
value=p['EM_TELL_THRESHOLD'])
# ------------------------------------------------------------------
# Deal with output preferences
# ------------------------------------------------------------------
# add bad pixel map (if required)
if p['EM_COMBINED_BADPIX']:
# get bad pix mask (True where bad)
badpixmask, bhdr, badfile = spirouImage.GetBadPixMap(p, hdr)
goodpixels = badpixmask == 0
# apply mask (multiply)
loc['TELL_MASK_2D'] = loc['TELL_MASK_2D'] & goodpixels.astype(bool)
else:
badfile = 'None'
# add to hdict
hdict = spirouImage.AddKey(p, hdict, p['KW_CDBBAD'], value=badfile)
# convert waveimage mask into float array
loc['TELL_MASK_2D'] = loc['TELL_MASK_2D'].astype('float')
# check EM_OUTPUT_TYPE and deal with set to "all"
if p['EM_OUTPUT_TYPE'] not in ["drs", "raw", "preprocess", "all"]:
emsg1 = '"EM_OUTPUT_TYPE" not understood'
emsg2 = ' must be either "drs", "raw" or "preprocess"'
emsg3 = ' currently EM_OUTPUT_TYPE="{0}"'.format(p['EM_OUTPUT_TYPE'])
WLOG(p, 'error', [emsg1, emsg2, emsg3])
outputs = []
elif p['EM_OUTPUT_TYPE'] != 'all':
outputs = [str(p['EM_OUTPUT_TYPE'])]
else:
outputs = ["drs", "raw", "preprocess"]
# ----------------------------------------------------------------------
# loop around output types
# ----------------------------------------------------------------------
for output in outputs:
# log progress
WLOG(p, '', 'Processing {0} outputs'.format(output))
# change EM_OUTPUT_TYPE
p['EM_OUTPUT_TYPE'] = output
# copy arrays
out_spe = np.array(loc['SPE'])
out_wave = np.array(loc['WAVEIMAGE'])
out_mask = np.array(loc['TELL_MASK_2D'])
# change image size if needed
if output in ["raw", "preprocess"]:
kk = dict(xsize=image.shape[1], ysize=image.shape[0])
if p['EM_SAVE_TELL_SPEC']:
WLOG(p, '', 'Resizing/Flipping SPE')
out_spe = spirouExM.unresize(p, out_spe, **kk)
WLOG(p, '', 'Rescaling SPE')
out_spe = out_spe / (p['GAIN'] * p['EXPTIME'])
if p['EM_SAVE_WAVE_MAP']:
WLOG(p, '', 'Resizing/Flipping WAVEIMAGE')
out_wave = spirouExM.unresize(p, out_wave, **kk)
if p['EM_SAVE_MASK_MAP']:
WLOG(p, '', 'Resizing/Flipping TELL_MASK_2D')
out_mask = spirouExM.unresize(p, out_mask, **kk)
# if raw need to rotate (undo pre-processing)
if output == "raw":
if p['EM_SAVE_TELL_SPEC']:
WLOG(p, '', 'Rotating SPE')
out_spe = np.rot90(out_spe, 1)
if p['EM_SAVE_WAVE_MAP']:
WLOG(p, '', 'Rotating WAVEIMAGE')
out_wave = np.rot90(out_wave, 1)
if p['EM_SAVE_MASK_MAP']:
WLOG(p, '', 'Rotating TELL_MASK_2D')
out_mask = np.rot90(out_mask, 1)
# ----------------------------------------------------------------------
# save 2D spectrum, wavelength image and mask to file
# ----------------------------------------------------------------------
# save telluric spectrum
if p['EM_SAVE_TELL_SPEC']:
# construct spectrum filename
specfitsfile, tag = spirouConfig.Constants.EM_SPE_FILE(p)
specfilename = os.path.split(specfitsfile)[-1]
# set the version
hdict = spirouImage.AddKey(p, hdict, p['KW_VERSION'])
hdict = spirouImage.AddKey(p,
hdict,
p['KW_DRS_DATE'],
value=p['DRS_DATE'])
hdict = spirouImage.AddKey(p,
hdict,
p['KW_DATE_NOW'],
value=p['DATE_NOW'])
hdict = spirouImage.AddKey(p, hdict, p['KW_OUTPUT'], value=tag)
# log progress
wmsg = 'Writing spectrum to file {0}'
WLOG(p, '', wmsg.format(specfilename))
# write to file
p = spirouImage.WriteImage(p, specfitsfile, out_spe, hdict=hdict)
# ----------------------------------------------------------------------
# save wave map
if p['EM_SAVE_WAVE_MAP']:
# construct waveimage filename
wavefitsfile, tag = spirouConfig.Constants.EM_WAVE_FILE(p)
wavefilename = os.path.split(wavefitsfile)[-1]
# set the version
hdict = spirouImage.AddKey(p, hdict, p['KW_VERSION'])
hdict = spirouImage.AddKey(p,
hdict,
p['KW_DRS_DATE'],
value=p['DRS_DATE'])
hdict = spirouImage.AddKey(p,
hdict,
p['KW_DATE_NOW'],
value=p['DATE_NOW'])
hdict = spirouImage.AddKey(p, hdict, p['KW_OUTPUT'], value=tag)
# log progress
wmsg = 'Writing wave image to file {0}'
WLOG(p, '', wmsg.format(wavefilename))
# write to file
p = spirouImage.WriteImage(p, wavefitsfile, out_wave, hdict=hdict)
# ----------------------------------------------------------------------
# save mask file
if p['EM_SAVE_MASK_MAP']:
# construct tell mask 2D filename
maskfitsfile, tag = spirouConfig.Constants.EM_MASK_FILE(p)
maskfilename = os.path.split(maskfitsfile)[-1]
# set the version
hdict = spirouImage.AddKey(p, hdict, p['KW_VERSION'])
hdict = spirouImage.AddKey(p,
hdict,
p['KW_DRS_DATE'],
value=p['DRS_DATE'])
hdict = spirouImage.AddKey(p,
hdict,
p['KW_DATE_NOW'],
value=p['DATE_NOW'])
hdict = spirouImage.AddKey(p, hdict, p['KW_OUTPUT'], value=tag)
# log progress
wmsg = 'Writing telluric mask to file {0}'
WLOG(p, '', wmsg.format(maskfilename))
# convert boolean mask to integers
writablemask = np.array(out_mask, dtype=float)
# write to file
p = spirouImage.WriteImage(p,
maskfitsfile,
writablemask,
hdict=hdict)
# ----------------------------------------------------------------------
# End Message
# ----------------------------------------------------------------------
p = spirouStartup.End(p)
# return a copy of locally defined variables in the memory
return dict(locals())
def main(night_name=None, ufile=None, xsize=None, ysize=None):
# ----------------------------------------------------------------------
# Set up
# ----------------------------------------------------------------------
# get parameters from config files/run time args/load paths + calibdb
p = spirouStartup.Begin(recipe=__NAME__)
# need custom args (to accept full path or wild card
if ufile is None or xsize is None or ysize is None:
pos = [0, 1, 2]
names, types = ['ufile', 'xsize', 'ysize'], [str, int, int]
customargs = spirouStartup.GetCustomFromRuntime(p,
pos,
types,
names,
last_multi=True)
else:
customargs = dict(ufile=ufile, xsize=xsize, ysize=ysize)
# get parameters from configuration files and run time arguments
p = spirouStartup.LoadArguments(p, night_name, customargs=customargs)
# add constants not currently in constants file
# ------------------------------------------------------------------
# Read image file
# ------------------------------------------------------------------
# read the image data
rout = spirouImage.ReadImage(p, filename=p['UFILE'])
image, hdr, nx, ny = rout
# ----------------------------------------------------------------------
# un-Resize image
# ----------------------------------------------------------------------
# create an array of given size
size = np.product([p['YSIZE'], p['XSIZE']])
newimage = np.repeat(np.nan, size).reshape(p['YSIZE'], p['XSIZE'])
# insert image at given pixels
xlow, xhigh = p['IC_CCDX_LOW'], p['IC_CCDX_HIGH']
ylow, yhigh = p['IC_CCDY_LOW'], p['IC_CCDY_HIGH']
newimage[ylow:yhigh, xlow:xhigh] = image
# rotate the image
newimage = spirouImage.FlipImage(p, newimage)
# ------------------------------------------------------------------
# Save rotated image
# ------------------------------------------------------------------
# construct rotated file name
outfits = ufile.replace('.fits', '_old.fits')
outfitsname = os.path.split(outfits)[-1]
# log that we are saving rotated image
WLOG(p, '', 'Saving Rotated Image in ' + outfitsname)
# add keys from original header file
hdict = spirouImage.CopyOriginalKeys(hdr)
# write to file
p = spirouImage.WriteImage(p, outfits, newimage, hdict)
# ----------------------------------------------------------------------
# End Message
# ----------------------------------------------------------------------
wmsg = 'Recipe {0} has been successfully completed'
WLOG(p, 'info', wmsg.format(p['PROGRAM']))
# return a copy of locally defined variables in the memory
return dict(locals())
def main(night_name=None, files=None):
# ----------------------------------------------------------------------
# Set up
# ----------------------------------------------------------------------
# get parameters from config files/run time args/load paths + calibdb
p = spirouStartup.Begin(recipe=__NAME__)
# get parameters from configuration files and run time arguments
customargs = spirouStartup.GetCustomFromRuntime(p, [0], [str], ['reffile'])
p = spirouStartup.LoadArguments(p,
night_name,
customargs=customargs,
mainfitsfile='reffile',
mainfitsdir='reduced')
# setup files and get fiber
p = spirouStartup.InitialFileSetup(p, calibdb=True)
# set the fiber type
p['FIB_TYP'] = [p['FIBER']]
# ----------------------------------------------------------------------
# Read image file
# ----------------------------------------------------------------------
# read the image data
gfkwargs = dict(path=p['REDUCED_DIR'], filename=p['REFFILE'])
p['REFFILENAME'] = spirouStartup.GetFile(p, **gfkwargs)
p.set_source('REFFILENAME', __NAME__ + '/main()')
# get the fiber type
p['FIBER'] = 'AB'
e2ds, hdr, nx, ny = spirouImage.ReadImage(p)
# Force A and B to AB solution
if p['FIBER'] in ['A', 'B']:
wave_fiber = 'AB'
else:
wave_fiber = p['FIBER']
# get wave image
_, wave, _ = spirouImage.GetWaveSolution(p,
hdr=hdr,
return_wavemap=True,
fiber=wave_fiber)
blaze = spirouImage.ReadBlazeFile(p)
# ----------------------------------------------------------------------
# Get lamp params
# ----------------------------------------------------------------------
# get lamp parameters
p = spirouTHORCA.GetLampParams(p, hdr)
# ----------------------------------------------------------------------
# Get catalogue and fitted line list
# ----------------------------------------------------------------------
# load line file (from p['IC_LL_LINE_FILE'])
ll_line_cat, ampl_line_cat = spirouImage.ReadLineList(p)
# construct fitted lines table filename
wavelltbl = spirouConfig.Constants.WAVE_LINE_FILE(p)
WLOG(p, '', wavelltbl)
# read fitted lines
ll_ord, ll_line_fit, ampl_line_fit = np.genfromtxt(wavelltbl,
skip_header=4,
skip_footer=2,
unpack=True,
usecols=(0, 1, 3))
# ----------------------------------------------------------------------
# Plots
# ----------------------------------------------------------------------
# define line colours
col = ['magenta', 'purple']
# get order parity
ll_ord_par = np.mod(ll_ord, 2)
print(ll_ord_par)
col2 = [col[int(x)] for x in ll_ord_par]
# start interactive plot
sPlt.start_interactive_session(p)
plt.figure()
for order_num in np.arange(nx):
plt.plot(wave[order_num], e2ds[order_num])
# get heights
heights = []
for line in range(len(ll_line_cat)):
heights.append(200000 + np.max([np.min(e2ds), ampl_line_cat[line]]))
# plot ll_line_cat
plt.vlines(ll_line_cat,
0,
heights,
colors='darkgreen',
linestyles='dashed')
# get heights
heights = []
for line in range(len(ll_line_fit)):
heights.append(200000 + np.max([np.min(e2ds), ampl_line_fit[line]]))
# plot ll_line_fit
plt.vlines(ll_line_fit, 0, heights, colors=col2, linestyles='dashdot')
plt.xlabel('Wavelength [nm]')
plt.ylabel('Flux e-')
plt.title(p['REFFILENAME'])
# end interactive session
# sPlt.end_interactive_session()
# old code:
# plt.ion()
# plt.figure()
#
# for order_num in np.arange(nx):
# plt.plot(wave[order_num], e2ds[order_num])
#
# for line in range(len(ll_line_cat)):
# plt.vlines(ll_line_cat[line], 0, 200000 +
# max(np.min(e2ds), ampl_line_cat[line]),
# colors='darkgreen', linestyles='dashed')
#
# for line in range(len(ll_line_fit)):
# plt.vlines(ll_line_fit[line], 0, 200000 +
# max(np.min(e2ds), ampl_line_fit[line]),
# colors='magenta', linestyles='dashdot')
#
# plt.xlabel('Wavelength [nm]')
# plt.ylabel('Flux e-')
# ----------------------------------------------------------------------
# End Message
# ----------------------------------------------------------------------
p = spirouStartup.End(p, outputs=None)
# return a copy of locally defined variables in the memory
return dict(locals())
def main(runname=None, quiet=False):
# ----------------------------------------------------------------------
# Set up
# ----------------------------------------------------------------------
# get parameters from config files/run time args/load paths + calibdb
p = spirouStartup.Begin(recipe=__NAME__, quiet=True)
# now get custom arguments
ckwargs = dict(positions=[0],
types=[str],
names=['RUNNAME'],
calls=[runname],
require_night_name=False,
required=[False])
customargs = spirouStartup.GetCustomFromRuntime(p, **ckwargs)
# add custom args straight to p
p = spirouStartup.LoadMinimum(p, customargs=customargs, quiet=True)
# ----------------------------------------------------------------------
# Read the run file and extract parameters
# ----------------------------------------------------------------------
# construct filename
rfile = os.path.join(UNIT_TEST_PATH, p['RUNNAME'])
# check if RUNNAME is None
if p['RUNNAME'] == 'None':
exists = False
emsgs = ['No unit test run file defined.']
# check that rfile exists
elif not os.path.exists(rfile):
emsgs = ['Unit test run file "{0}" does not exist'.format(rfile)]
exists = False
else:
exists = True
emsgs = []
# deal with file wrong (or no file defined) --> print valid unit tests
if not exists:
emsgs.append('')
emsgs.append('Available units tests are:')
for rfile in os.listdir(UNIT_TEST_PATH):
emsgs.append('\t{0}'.format(rfile))
emsgs.append('')
emsgs.append('Located at {0}'.format(UNIT_TEST_PATH))
WLOG(p, 'error', emsgs)
# get the parameters in the run file
rparams = spirouConfig.GetConfigParams(p, filename=rfile)
# reset the DRS
if not quiet:
spirouTools.DRS_Reset(log=True, called=True)
# ----------------------------------------------------------------------
# Get runs
# ----------------------------------------------------------------------
runs = spirouUnitTests.get_runs(p, rparams, rfile)
# ----------------------------------------------------------------------
# Run runs
# ----------------------------------------------------------------------
# storage for times
times = OrderedDict()
errors = OrderedDict()
# log the start of the unit tests
spirouUnitTests.unit_log_title(p)
# loop around runs and process each
for runn in list(runs.keys()):
if p['DRS_DEBUG'] > 0:
# do run
rargs = [p, runn, runs[runn], times]
times = spirouUnitTests.manage_run(*rargs)
else:
# try to run
try:
# do run
rargs = [p, runn, runs[runn], times]
times = spirouUnitTests.manage_run(*rargs)
# Manage unexpected errors
except Exception as e:
wmsgs = ['Run "{0}" had an unexpected error:'.format(runn)]
for msg in str(e).split('\n'):
wmsgs.append('\t' + msg)
WLOG(p, 'warning', wmsgs)
errors[runn] = str(e)
# Manage expected errors
except SystemExit as e:
wmsgs = ['Run "{0}" had an expected error:'.format(runn)]
for msg in str(e).split('\n'):
wmsgs.append('\t' + msg)
WLOG(p, 'warning', wmsgs)
errors[runn] = str(e)
# ----------------------------------------------------------------------
# Make sure all plots are close
# ----------------------------------------------------------------------
sPlt.closeall()
# ----------------------------------------------------------------------
# Print timings
# ----------------------------------------------------------------------
spirouUnitTests.log_timings(p, times)
# ----------------------------------------------------------------------
# Print errors
# ----------------------------------------------------------------------
spirouUnitTests.log_errors(p, errors)
# ----------------------------------------------------------------------
# End Message
# ----------------------------------------------------------------------
wmsg = 'Recipe {0} has been successfully completed'
WLOG(p, 'info', wmsg.format(p['PROGRAM']))
# return a copy of locally defined variables in the memory
return dict(locals())
WLOG = spirouCore.wlog
# Get plotting functions
sPlt = spirouCore.sPlt
night_name = '18BQ08-Sep21'
reffile = '2305120o_pp_e2dsff_AB_tellu_corrected.fits'
# =============================================================================
# Start of code
# =============================================================================
# Main code here
if __name__ == "__main__":
# ----------------------------------------------------------------------
# get parameters from config files/run time args/load paths + calibdb
p = spirouStartup.Begin(recipe=__NAME__)
customargs = spirouStartup.GetCustomFromRuntime(p, [0], [str], ['reffile'],
[True], [reffile])
p = spirouStartup.LoadArguments(p,
night_name,
customargs=customargs,
mainfitsfile='reffile',
mainfitsdir='reduced')
p['FIBER'] = 'AB'
# load the calibDB
p = spirouStartup.LoadCalibDB(p)
# load ref spectrum
e2ds, hdr, nx, ny = spirouImage.ReadImage(p)
# get blaze
blaze = spirouImage.ReadBlazeFile(p)
# get wave image
_, wave, _ = spirouImage.GetWaveSolution(p, hdr=hdr, return_wavemap=True)
def main(night_name=None, reffile=None):
# ----------------------------------------------------------------------
# Set up
# ----------------------------------------------------------------------
# get parameters from config files/run time args/load paths + calibdb
p = spirouStartup.Begin(recipe=__NAME__)
customargs = spirouStartup.GetCustomFromRuntime(p, [0], [str], ['reffile'],
[True], [reffile])
p = spirouStartup.LoadArguments(p, night_name, customargs=customargs,
mainfitsfile='reffile',
mainfitsdir='reduced')
# load the calibDB
p = spirouStartup.LoadCalibDB(p)
# force plotting to 1
p['DRS_PLOT'] = 1
# ----------------------------------------------------------------------
# Read image file
# ----------------------------------------------------------------------
# read the image data
p, fpfitsfilename = spirouStartup.SingleFileSetup(p, filename=p['REFFILE'])
# get the fiber type
fiber1 = str(p['FIBER'])
e2ds, hdr, nx, ny = spirouImage.ReadImage(p)
p, blaze = spirouImage.ReadBlazeFile(p)
# set source of wave file
wsource = __NAME__ + '/main() + /spirouImage.GetWaveSolution'
# Force A and B to AB solution
if p['FIBER'] in ['A', 'B']:
wave_fiber = 'AB'
else:
wave_fiber = p['FIBER']
# get wave image
_, wave, _ = spirouImage.GetWaveSolution(p, hdr=hdr, return_wavemap=True,
fiber=wave_fiber)
# ----------------------------------------------------------------------
# Get basic image properties
# ----------------------------------------------------------------------
plt.ion()
plt.figure()
for i in np.arange(nx):
plt.plot(wave[i], e2ds[i])
plt.xlabel('Wavelength [nm]')
plt.ylabel('Flux e-')
plt.title('Extracted spectra')
plt.figure()
for i in np.arange(nx):
plt.plot(wave[i], e2ds[i] / blaze[i])
plt.xlabel('Wavelength [nm]')
plt.ylabel('Relative Flux e-')
plt.title('Blaze corrected Extracted spectra')
# ----------------------------------------------------------------------
# End Message
# ----------------------------------------------------------------------
p = spirouStartup.End(p, outputs=None)
# return a copy of locally defined variables in the memory
return dict(locals())
def main(filetype='DARK_DARK'):
"""
cal_DARK_spirou.py main function, if night_name and files are None uses
arguments from run time i.e.:
cal_DARK_spirou.py [night_directory] [fitsfilename]
:param night_name: string or None, the folder within data raw directory
containing files (also reduced directory) i.e.
/data/raw/20170710 would be "20170710" but
/data/raw/AT5/20180409 would be "AT5/20180409"
:param files: string, list or None, the list of files to use for
arg_file_names and fitsfilename
(if None assumes arg_file_names was set from run time)
:return ll: dictionary, containing all the local variables defined in
main
"""
# ----------------------------------------------------------------------
# Set up
# ----------------------------------------------------------------------
# set up function name
main_name = __NAME__ + '.main()'
# get parameters from config files/run time args/load paths + calibdb
p = spirouStartup.Begin(recipe=__NAME__)
# now get custom arguments
pos, fmt = [0], [str]
names, call = ['filetype'], [filetype]
customargs = spirouStartup.GetCustomFromRuntime(p, pos, fmt, names,
calls=call,
require_night_name=False)
p = spirouStartup.LoadArguments(p, None, customargs=customargs,
mainfitsdir='tmp',
require_night_name=False)
# set the DRS type (for file indexing)
p['DRS_TYPE'] = 'RAW'
p.set_source('DRS_TYPE', __NAME__ + '.main()')
# -------------------------------------------------------------------------
# find all "filetype" objects
filenames = spirouImage.FindFiles(p, filetype=p['FILETYPE'],
allowedtypes=p['ALLOWED_DARK_TYPES'])
# convert filenames to a numpy array
filenames = np.array(filenames)
# -------------------------------------------------------------------------
# julian date to know which file we need to
# process together
dark_time = np.zeros(len(filenames))
dark_exp, dark_pp_version, dark_wt_temp = [], [], []
basenames, nightnames, dark_cass_temp, dark_humidity = [], [], [], []
# log progress
WLOG(p, '', 'Reading all dark file headers')
# looping through the file headers
for it in range(len(filenames)):
# get night name
night_name = os.path.dirname(filenames[it]).split(p['TMP_DIR'])[-1]
# get header
hdr = spirouImage.ReadHeader(p, filepath=filenames[it])
# add MJDATE to dark times
dark_time[it] = float(hdr[p['KW_ACQTIME'][0]])
# add other keys (for tabular output)
basenames.append(os.path.basename(filenames[it]))
nightnames.append(night_name)
dark_exp.append(float(hdr[p['KW_EXPTIME'][0]]))
dark_pp_version.append(hdr[p['KW_PPVERSION'][0]])
dark_wt_temp.append(float(hdr[p['KW_WEATHER_TOWER_TEMP'][0]]))
dark_cass_temp.append(float(hdr[p['KW_CASS_TEMP'][0]]))
dark_humidity.append(float(hdr[p['KW_HUMIDITY'][0]]))
# -------------------------------------------------------------------------
# match files by date
# -------------------------------------------------------------------------
# log progress
wmsg = 'Matching dark files by observation time (+/- {0} hrs)'
WLOG(p, '', wmsg.format(p['DARK_MASTER_MATCH_TIME']))
# get the time threshold
time_thres = p['DARK_MASTER_MATCH_TIME']
# get items grouped by time
matched_id = spirouImage.GroupFilesByTime(p, dark_time, time_thres)
# -------------------------------------------------------------------------
# get the most recent position
lastpos = np.argmax(dark_time)
# load up the most recent dark
rout = spirouImage.ReadImage(p, filenames[lastpos], log=False)
data_ref, hdr_ref, nx, ny = rout
# set the night name and update the reduced directory
p['ARG_NIGHT_NAME'] = nightnames[lastpos]
p.set_source('ARG_NIGHT_NAME', __NAME__ + '.main()')
p['REDUCED_DIR'] = spirouConfig.Constants.REDUCED_DIR(p)
p.set_source('REDUCED_DIR', __NAME__ + '.main()')
# -------------------------------------------------------------------------
# Read individual files and sum groups
# -------------------------------------------------------------------------
# log process
WLOG(p, '', 'Reading Dark files and combining groups')
# Find all unique groups
u_groups = np.unique(matched_id)
# currently number of bins == number of groups
num_bins = len(u_groups)
# storage of dark cube
dark_cube = np.zeros([num_bins, ny, nx])
bin_cube = np.zeros(num_bins)
# loop through groups
for g_it, group_num in enumerate(u_groups):
# log progress
WLOG(p, '', '\tGroup {0} of {1}'.format(g_it + 1, len(u_groups)))
# find all files for this group
dark_ids = filenames[matched_id == group_num]
# load this groups files into a cube
cube = []
for filename in dark_ids:
# read data
data_it, _, _, _ = spirouImage.ReadImage(p, filename, log=False)
# add to cube
cube.append(data_it)
# median dark cube
groupdark = np.nanmedian(cube, axis=0)
# sum within each bin
dark_cube[g_it % num_bins] += groupdark
# record the number of cubes that are going into this bin
bin_cube[g_it % num_bins] += 1
# need to normalize if we have more than 1 cube per bin
for bin_it in range(num_bins):
dark_cube[bin_it] /= bin_cube[bin_it]
# -------------------------------------------------------------------------
# we perform a median filter over a +/- "med_size" pixel box
# -------------------------------------------------------------------------
# log process
WLOG(p, '', 'Performing median filter for {0} bins'.format(num_bins))
# get med_size from p
med_size = p['DARK_MASTER_MED_SIZE']
# storage of output dark cube
dark_cube1 = np.zeros([num_bins, ny, nx])
# loop around the bins
for bin_it in range(num_bins):
# get the dark for this bin
bindark = dark_cube[bin_it]
# performing a median filter of the image with [-med_size, med_size]
# box in x and 1 pixel wide in y. Skips the pixel considered,
# so this is equivalent of a 2*med_size boxcar
tmp = []
for jt in range(-med_size, med_size + 1):
if jt != 0:
tmp.append(np.roll(bindark, [0, jt]))
# low frequency image
lf_dark = np.nanmedian(tmp, axis=0)
# high frequency image
dark_cube1[bin_it] = bindark - lf_dark
# -------------------------------------------------------------------------
# median the dark cube to create the master dark
master_dark = np.nanmedian(dark_cube1, axis=0)
# ----------------------------------------------------------------------
# Quality control
# ----------------------------------------------------------------------
# set passed variable and fail message list
passed, fail_msg = True, []
qc_values, qc_names, qc_logic, qc_pass = [], [], [], []
# ----------------------------------------------------------------------
# finally log the failed messages and set QC = 1 if we pass the
# quality control QC = 0 if we fail quality control
if passed:
WLOG(p, 'info', 'QUALITY CONTROL SUCCESSFUL - Well Done -')
p['QC'] = 1
p.set_source('QC', __NAME__ + '/main()')
else:
for farg in fail_msg:
wmsg = 'QUALITY CONTROL FAILED: {0}'
WLOG(p, 'warning', wmsg.format(farg))
p['QC'] = 0
p.set_source('QC', __NAME__ + '/main()')
# add to qc header lists
qc_values.append('None')
qc_names.append('None')
qc_logic.append('None')
qc_pass.append(1)
# store in qc_params
qc_params = [qc_names, qc_values, qc_logic, qc_pass]
# ----------------------------------------------------------------------
# Save master dark to file
# ----------------------------------------------------------------------
# set reference filename
reffile = filenames[lastpos]
# construct folder and filename
darkmasterfits, tag = spirouConfig.Constants.DARK_FILE_MASTER(p, reffile)
darkmasterfitsname = os.path.basename(darkmasterfits)
# log writing of file
WLOG(p, '', 'Saving master dark to {0}'.format(darkmasterfitsname))
# construct big dark table
colnames = ['FILENAME', 'NIGHT', 'MJDATE', 'EXPTIME', 'WEATHER_TEMP',
'CASS_TEMP', 'RELHUMID', 'PVERSION', 'GROUPID']
values = [basenames, nightnames, dark_time, dark_exp, dark_wt_temp,
dark_cass_temp, dark_humidity, dark_pp_version, matched_id]
darktable = spirouImage.MakeTable(p, colnames, values)
# add keys from original header file
hdict = spirouImage.CopyOriginalKeys(hdr_ref)
# define new keys to add
hdict = spirouImage.AddKey(p, hdict, p['KW_VERSION'])
hdict = spirouImage.AddKey(p, hdict, p['KW_DRS_DATE'], value=p['DRS_DATE'])
hdict = spirouImage.AddKey(p, hdict, p['KW_DATE_NOW'], value=p['DATE_NOW'])
hdict = spirouImage.AddKey(p, hdict, p['KW_PID'], value=p['PID'])
hdict = spirouImage.AddKey(p, hdict, p['KW_OUTPUT'], value=tag)
# add qc parameters
hdict = spirouImage.AddKey(p, hdict, p['KW_DRS_QC'], value=p['QC'])
hdict = spirouImage.AddQCKeys(p, hdict, qc_params)
# write master dark + dark table to file
p = spirouImage.WriteImageTable(p, darkmasterfits, image=master_dark,
table=darktable, hdict=hdict)
# ----------------------------------------------------------------------
# Move to calibDB and update calibDB
# ----------------------------------------------------------------------
if p['QC']:
# set dark master key
keydb = 'DARKM'
# copy dark fits file to the calibDB folder
spirouDB.PutCalibFile(p, darkmasterfits)
# update the master calib DB file with new key
spirouDB.UpdateCalibMaster(p, keydb, darkmasterfitsname, hdr_ref)
# ----------------------------------------------------------------------
# End Message
# ----------------------------------------------------------------------
p = spirouStartup.End(p)
# return a copy of locally defined variables in the memory
return dict(locals())
def main(night_name=None, hcfile=None, fpfiles=None):
"""
cal_SLIT_spirou.py main function, if night_name and files are None uses
arguments from run time i.e.:
cal_SLIT_spirou.py [night_directory] [files]
:param night_name: string or None, the folder within data raw directory
containing files (also reduced directory) i.e.
/data/raw/20170710 would be "20170710" but
/data/raw/AT5/20180409 would be "AT5/20180409"
:param files: string, list or None, the list of files to use for
arg_file_names and fitsfilename
(if None assumes arg_file_names was set from run time)
:return ll: dictionary, containing all the local variables defined in
main
"""
# ----------------------------------------------------------------------
# Set up
# ----------------------------------------------------------------------
# get parameters from config files/run time args/load paths + calibdb
p = spirouStartup.Begin(recipe=__NAME__)
if hcfile is None or fpfiles is None:
names, types = ['hcfile', 'fpfiles'], [str, str]
customargs = spirouStartup.GetCustomFromRuntime(p, [0, 1],
types,
names,
last_multi=True)
else:
customargs = dict(hcfile=hcfile, fpfile=fpfiles)
# get parameters from configuration files and run time arguments
p = spirouStartup.LoadArguments(p,
night_name,
customargs=customargs,
mainfitsfile='fpfiles')
# ----------------------------------------------------------------------
# Construct reference filename and get fiber type
# ----------------------------------------------------------------------
p, hcfitsfilename = spirouStartup.SingleFileSetup(p, filename=p['HCFILE'])
p, fpfitsfiles = spirouStartup.MultiFileSetup(p, files=p['FPFILES'])
# set fiber (it doesn't matter with the 2D image but we need this to get
# the lamp type for FPFILES and HCFILES, AB == C
p['FIBER'] = 'AB'
p['FIB_TYP'] = [p['FIBER']]
fsource = __NAME__ + '/main()'
p.set_sources(['FIBER', 'FIB_TYP'], fsource)
# ----------------------------------------------------------------------
# Once we have checked the e2dsfile we can load calibDB
# ----------------------------------------------------------------------
# as we have custom arguments need to load the calibration database
p = spirouStartup.LoadCalibDB(p)
# add a force plot off
p['PLOT_PER_ORDER'] = PLOT_PER_ORDER
p.set_source('PLOT_PER_ORDER', __NAME__ + '.main()')
# ----------------------------------------------------------------------
# Read FP and HC files
# ----------------------------------------------------------------------
# read input fp and hc data
rkwargs = dict(filename=fpfitsfiles[0],
filenames=fpfitsfiles[1:],
framemath='add')
p, fpdata, fphdr = spirouImage.ReadImageAndCombine(p, **rkwargs)
hcdata, hchdr, _, _ = spirouImage.ReadImage(p, hcfitsfilename)
# add data and hdr to loc
loc = ParamDict()
loc['HCDATA'], loc['HCHDR'] = hcdata, hchdr
loc['FPDATA'], loc['FPHDR'] = fpdata, fphdr
# set the source
sources = ['HCDATA', 'HCHDR']
loc.set_sources(sources, 'spirouImage.ReadImage()')
sources = ['FPDATA', 'FPHDR']
loc.set_sources(sources, 'spirouImage.ReadImage()')
# ---------------------------------------------------------------------
# fix for un-preprocessed files
# ----------------------------------------------------------------------
hcdata = spirouImage.FixNonPreProcess(p, hcdata)
fpdata = spirouImage.FixNonPreProcess(p, fpdata)
# ----------------------------------------------------------------------
# Once we have checked the e2dsfile we can load calibDB
# ----------------------------------------------------------------------
# as we have custom arguments need to load the calibration database
p = spirouStartup.LoadCalibDB(p)
# add a force plot off
p['PLOT_PER_ORDER'] = PLOT_PER_ORDER
p.set_source('PLOT_PER_ORDER', __NAME__ + '.main()')
# ----------------------------------------------------------------------
# Get basic image properties for reference file
# ----------------------------------------------------------------------
# get sig det value
p = spirouImage.GetSigdet(p, fphdr, name='sigdet')
# get exposure time
p = spirouImage.GetExpTime(p, fphdr, name='exptime')
# get gain
p = spirouImage.GetGain(p, fphdr, name='gain')
# get lamp parameters
p = spirouTHORCA.GetLampParams(p, hchdr)
# get FP_FP DPRTYPE
p = spirouImage.ReadParam(p, fphdr, 'KW_DPRTYPE', 'DPRTYPE', dtype=str)
# ----------------------------------------------------------------------
# Correction of reference FP
# ----------------------------------------------------------------------
# set the number of frames
p['NBFRAMES'] = len(fpfitsfiles)
p.set_source('NBFRAMES', __NAME__ + '.main()')
# Correction of DARK
p, fpdatac = spirouImage.CorrectForDark(p, fpdata, fphdr)
# Resize hc data
# rotate the image and convert from ADU/s to e-
fpdata = spirouImage.ConvertToE(spirouImage.FlipImage(p, fpdatac), p=p)
# resize image
bkwargs = dict(xlow=p['IC_CCDX_LOW'],
xhigh=p['IC_CCDX_HIGH'],
ylow=p['IC_CCDY_LOW'],
yhigh=p['IC_CCDY_HIGH'],
getshape=False)
fpdata1 = spirouImage.ResizeImage(p, fpdata, **bkwargs)
# log change in data size
WLOG(p, '',
('FPref Image format changed to {0}x{1}').format(*fpdata1.shape))
# Correct for the BADPIX mask (set all bad pixels to zero)
bargs = [p, fpdata1, fphdr]
p, fpdata1 = spirouImage.CorrectForBadPix(*bargs)
p, badpixmask = spirouImage.CorrectForBadPix(*bargs, return_map=True)
# log progress
WLOG(p, '', 'Cleaning FPref hot pixels')
# correct hot pixels
fpdata1 = spirouEXTOR.CleanHotpix(fpdata1, badpixmask)
# add to loc
loc['FPDATA1'] = fpdata1
loc.set_source('FPDATA1', __NAME__ + '.main()')
# Log the number of dead pixels
# get the number of bad pixels
with warnings.catch_warnings(record=True) as _:
n_bad_pix = np.nansum(fpdata1 <= 0)
n_bad_pix_frac = n_bad_pix * 100 / np.product(fpdata1.shape)
# Log number
wmsg = 'Nb FPref dead pixels = {0} / {1:.2f} %'
WLOG(p, 'info', wmsg.format(int(n_bad_pix), n_bad_pix_frac))
# ----------------------------------------------------------------------
# Correction of HC
# ----------------------------------------------------------------------
# set the number of frames
p['NBFRAMES'] = 1
p.set_source('NBFRAMES', __NAME__ + '.main()')
# Correction of DARK
p, hcdatac = spirouImage.CorrectForDark(p, hcdata, hchdr)
# Resize hc data
# rotate the image and convert from ADU/s to e-
hcdata = spirouImage.ConvertToE(spirouImage.FlipImage(p, hcdatac), p=p)
# resize image
bkwargs = dict(xlow=p['IC_CCDX_LOW'],
xhigh=p['IC_CCDX_HIGH'],
ylow=p['IC_CCDY_LOW'],
yhigh=p['IC_CCDY_HIGH'],
getshape=False)
hcdata1 = spirouImage.ResizeImage(p, hcdata, **bkwargs)
# log change in data size
WLOG(p, '', ('HC Image format changed to {0}x{1}').format(*hcdata1.shape))
# Correct for the BADPIX mask (set all bad pixels to zero)
bargs = [p, hcdata1, hchdr]
p, hcdata1 = spirouImage.CorrectForBadPix(*bargs)
p, badpixmask = spirouImage.CorrectForBadPix(*bargs, return_map=True)
# log progress
WLOG(p, '', 'Cleaning HC hot pixels')
# correct hot pixels
hcdata1 = spirouEXTOR.CleanHotpix(hcdata1, badpixmask)
# add to loc
loc['HCDATA1'] = hcdata1
loc.set_source('HCDATA1', __NAME__ + '.main()')
# Log the number of dead pixels
# get the number of bad pixels
with warnings.catch_warnings(record=True) as _:
n_bad_pix = np.nansum(hcdata1 <= 0)
n_bad_pix_frac = n_bad_pix * 100 / np.product(hcdata1.shape)
# Log number
wmsg = 'Nb HC dead pixels = {0} / {1:.2f} %'
WLOG(p, 'info', wmsg.format(int(n_bad_pix), n_bad_pix_frac))
# -------------------------------------------------------------------------
# get all FP_FP files
# -------------------------------------------------------------------------
fpfilenames = spirouImage.FindFiles(p,
filetype=p['DPRTYPE'],
allowedtypes=p['ALLOWED_FP_TYPES'])
# convert filenames to a numpy array
fpfilenames = np.array(fpfilenames)
# julian date to know which file we need to
# process together
fp_time = np.zeros(len(fpfilenames))
basenames, fp_exp, fp_pp_version, nightnames = [], [], [], []
# log progress
WLOG(p, '', 'Reading all fp file headers')
# looping through the file headers
for it in range(len(fpfilenames)):
# log progress
wmsg = '\tReading file {0} / {1}'
WLOG(p, 'info', wmsg.format(it + 1, len(fpfilenames)))
# get fp filename
fpfilename = fpfilenames[it]
# get night name
night_name = os.path.dirname(fpfilenames[it]).split(p['TMP_DIR'])[-1]
# read data
data_it, hdr_it, _, _ = spirouImage.ReadImage(p, fpfilename)
# get header
hdr = spirouImage.ReadHeader(p, filepath=fpfilenames[it])
# add MJDATE to dark times
fp_time[it] = float(hdr[p['KW_ACQTIME'][0]])
# add other keys (for tabular output)
basenames.append(os.path.basename(fpfilenames[it]))
nightnames.append(night_name)
fp_exp.append(float(hdr[p['KW_EXPTIME'][0]]))
fp_pp_version.append(hdr[p['KW_PPVERSION'][0]])
# -------------------------------------------------------------------------
# match files by date
# -------------------------------------------------------------------------
# log progress
wmsg = 'Matching FP files by observation time (+/- {0} hrs)'
WLOG(p, '', wmsg.format(p['DARK_MASTER_MATCH_TIME']))
# get the time threshold
time_thres = p['FP_MASTER_MATCH_TIME']
# get items grouped by time
matched_id = spirouImage.GroupFilesByTime(p, fp_time, time_thres)
# -------------------------------------------------------------------------
# construct the master fp file (+ correct for dark/badpix)
# -------------------------------------------------------------------------
cargs = [fpdata1, fpfilenames, matched_id]
fpcube, transforms = spirouImage.ConstructMasterFP(p, *cargs)
# log process
wmsg1 = 'Master FP construction complete.'
wmsg2 = '\tAdding {0} group images to form FP master image'
WLOG(p, 'info', [wmsg1, wmsg2.format(len(fpcube))])
# sum the cube to make fp data
masterfp = np.sum(fpcube, axis=0)
# add to loc
loc['MASTERFP'] = masterfp
loc.set_source('MASTERFP', __NAME__ + '.main()')
# ------------------------------------------------------------------
# Get localisation coefficients
# ------------------------------------------------------------------
# original there is a loop but it is not used --> removed
p = spirouImage.FiberParams(p, p['FIBER'], merge=True)
# get localisation fit coefficients
p, loc = spirouLOCOR.GetCoeffs(p, fphdr, loc)
# ------------------------------------------------------------------
# Get master wave solution map
# ------------------------------------------------------------------
# get master wave map
masterwavefile = spirouDB.GetDatabaseMasterWave(p)
# log process
wmsg1 = 'Getting master wavelength grid'
wmsg2 = '\tFile = {0}'.format(os.path.basename(masterwavefile))
WLOG(p, '', [wmsg1, wmsg2])
# Force A and B to AB solution
if p['FIBER'] in ['A', 'B']:
wave_fiber = 'AB'
else:
wave_fiber = p['FIBER']
# read master wave map
wout = spirouImage.GetWaveSolution(p,
filename=masterwavefile,
return_wavemap=True,
quiet=True,
return_header=True,
fiber=wave_fiber)
loc['MASTERWAVEP'], loc['MASTERWAVE'] = wout[:2]
loc['MASTERWAVEHDR'], loc['WSOURCE'] = wout[2:]
# set sources
wsource = ['MASTERWAVEP', 'MASTERWAVE', 'MASTERWAVEHDR']
loc.set_sources(wsource, 'spirouImage.GetWaveSolution()')
# ----------------------------------------------------------------------
# Read UNe solution
# ----------------------------------------------------------------------
wave_u_ne, amp_u_ne = spirouImage.ReadLineList(p)
loc['LL_LINE'], loc['AMPL_LINE'] = wave_u_ne, amp_u_ne
source = __NAME__ + '.main() + spirouImage.ReadLineList()'
loc.set_sources(['LL_LINE', 'AMPL_LINE'], source)
# ----------------------------------------------------------------------
# Read cavity length file
# ----------------------------------------------------------------------
loc['CAVITY_LEN_COEFFS'] = spirouImage.ReadCavityLength(p)
source = __NAME__ + '.main() + spirouImage.ReadCavityLength()'
loc.set_source('CAVITY_LEN_COEFFS', source)
# ----------------------------------------------------------------------
# Calculate shape map
# ----------------------------------------------------------------------
# calculate dx map
loc = spirouImage.GetXShapeMap(p, loc)
# if dx map is None we shouldn't continue
if loc['DXMAP'] is None:
fargs = [
loc['MAXDXMAPINFO'][0], loc['MAXDXMAPINFO'][1], loc['MAXDXMAPSTD'],
p['SHAPE_QC_DXMAP_STD']
]
fmsg = ('The std of the dxmap for order {0} y-pixel {1} is too large.'
' std = {2} (limit = {3})'.format(*fargs))
wmsg = 'QUALITY CONTROL FAILED: {0}'
WLOG(p, 'warning', wmsg.format(fmsg))
WLOG(p, 'warning', 'Cannot continue. Exiting.')
# End Message
p = spirouStartup.End(p)
# return a copy of locally defined variables in the memory
return dict(locals())
# calculate dymap
loc = spirouImage.GetYShapeMap(p, loc, fphdr)
# ------------------------------------------------------------------
# Need to straighten the dxmap
# ------------------------------------------------------------------
# copy it first
loc['DXMAP0'] = np.array(loc['DXMAP'])
# straighten it
loc['DXMAP'] = spirouImage.EATransform(loc['DXMAP'], dymap=loc['DYMAP'])
# ------------------------------------------------------------------
# Need to straighten the hc data and fp data for debug
# ------------------------------------------------------------------
# log progress
WLOG(p, '', 'Shape finding complete. Applying transforms.')
# apply very last update of the debananafication
tkwargs = dict(dxmap=loc['DXMAP'], dymap=loc['DYMAP'])
loc['HCDATA2'] = spirouImage.EATransform(loc['HCDATA1'], **tkwargs)
loc['FPDATA2'] = spirouImage.EATransform(loc['FPDATA1'], **tkwargs)
loc.set_sources(['HCDATA2', 'FPDATA2'], __NAME__ + '.main()')
# ------------------------------------------------------------------
# Plotting
# ------------------------------------------------------------------
if p['DRS_PLOT'] > 0:
# plots setup: start interactive plot
sPlt.start_interactive_session(p)
# plot the shape process for one order
sPlt.slit_shape_angle_plot(p, loc)
# end interactive section
sPlt.end_interactive_session(p)
# ----------------------------------------------------------------------
# Quality control
# ----------------------------------------------------------------------
# TODO: Decide on some quality control criteria?
# set passed variable and fail message list
passed, fail_msg = True, []
qc_values, qc_names, qc_logic, qc_pass = [], [], [], []
# finally log the failed messages and set QC = 1 if we pass the
# quality control QC = 0 if we fail quality control
if passed:
WLOG(p, 'info', 'QUALITY CONTROL SUCCESSFUL - Well Done -')
p['QC'] = 1
p.set_source('QC', __NAME__ + '/main()')
else:
for farg in fail_msg:
wmsg = 'QUALITY CONTROL FAILED: {0}'
WLOG(p, 'warning', wmsg.format(farg))
p['QC'] = 0
p.set_source('QC', __NAME__ + '/main()')
# add to qc header lists
qc_values.append(loc['MAXDXMAPSTD'])
qc_names.append('DXMAP STD')
qc_logic.append('DXMAP STD < {0}'.format(p['SHAPE_QC_DXMAP_STD']))
qc_pass.append(1)
# store in qc_params
qc_params = [qc_names, qc_values, qc_logic, qc_pass]
# ------------------------------------------------------------------
# Writing FP big table
# ------------------------------------------------------------------
# construct big fp table
colnames = [
'FILENAME', 'NIGHT', 'MJDATE', 'EXPTIME', 'PVERSION', 'GROUPID',
'DXREF', 'DYREF', 'A', 'B', 'C', 'D'
]
values = [
basenames, nightnames, fp_time, fp_exp, fp_pp_version, matched_id,
transforms[:, 0], transforms[:, 1], transforms[:, 2], transforms[:, 3],
transforms[:, 4], transforms[:, 5]
]
fptable = spirouImage.MakeTable(p, colnames, values)
# ------------------------------------------------------------------
# Writing DXMAP to file
# ------------------------------------------------------------------
# get the raw tilt file name
raw_shape_file = os.path.basename(p['FITSFILENAME'])
# construct file name and path
shapexfits, tag = spirouConfig.Constants.SLIT_XSHAPE_FILE(p)
shapexfitsname = os.path.basename(shapexfits)
# Log that we are saving tilt file
wmsg = 'Saving shape x information in file: {0}'
WLOG(p, '', wmsg.format(shapexfitsname))
# Copy keys from fits file
hdict = spirouImage.CopyOriginalKeys(fphdr)
# add version number
hdict = spirouImage.AddKey(p, hdict, p['KW_VERSION'])
hdict = spirouImage.AddKey(p, hdict, p['KW_DRS_DATE'], value=p['DRS_DATE'])
hdict = spirouImage.AddKey(p, hdict, p['KW_DATE_NOW'], value=p['DATE_NOW'])
hdict = spirouImage.AddKey(p, hdict, p['KW_PID'], value=p['PID'])
hdict = spirouImage.AddKey(p, hdict, p['KW_OUTPUT'], value=tag)
hdict = spirouImage.AddKey(p, hdict, p['KW_CDBDARK'], value=p['DARKFILE'])
hdict = spirouImage.AddKey(p, hdict, p['KW_CDBBAD'], value=p['BADPFILE'])
hdict = spirouImage.AddKey(p, hdict, p['KW_CDBLOCO'], value=p['LOCOFILE'])
hdict = spirouImage.AddKey1DList(p,
hdict,
p['KW_INFILE1'],
dim1name='hcfile',
values=p['HCFILE'])
hdict = spirouImage.AddKey1DList(p,
hdict,
p['KW_INFILE2'],
dim1name='fpfile',
values=p['FPFILES'])
# add qc parameters
hdict = spirouImage.AddKey(p, hdict, p['KW_DRS_QC'], value=p['QC'])
hdict = spirouImage.AddQCKeys(p, hdict, qc_params)
# write tilt file to file
p = spirouImage.WriteImageTable(p,
shapexfits,
image=loc['DXMAP'],
table=fptable,
hdict=hdict)
# ------------------------------------------------------------------
# Writing DYMAP to file
# ------------------------------------------------------------------
# get the raw tilt file name
raw_shape_file = os.path.basename(p['FITSFILENAME'])
# construct file name and path
shapeyfits, tag = spirouConfig.Constants.SLIT_YSHAPE_FILE(p)
shapeyfitsname = os.path.basename(shapeyfits)
# Log that we are saving tilt file
wmsg = 'Saving shape y information in file: {0}'
WLOG(p, '', wmsg.format(shapeyfitsname))
# Copy keys from fits file
hdict = spirouImage.CopyOriginalKeys(fphdr)
# add version number
hdict = spirouImage.AddKey(p, hdict, p['KW_VERSION'])
hdict = spirouImage.AddKey(p, hdict, p['KW_DRS_DATE'], value=p['DRS_DATE'])
hdict = spirouImage.AddKey(p, hdict, p['KW_DATE_NOW'], value=p['DATE_NOW'])
hdict = spirouImage.AddKey(p, hdict, p['KW_PID'], value=p['PID'])
hdict = spirouImage.AddKey(p, hdict, p['KW_OUTPUT'], value=tag)
hdict = spirouImage.AddKey(p, hdict, p['KW_CDBDARK'], value=p['DARKFILE'])
hdict = spirouImage.AddKey(p, hdict, p['KW_CDBBAD'], value=p['BADPFILE'])
hdict = spirouImage.AddKey(p, hdict, p['KW_CDBLOCO'], value=p['LOCOFILE'])
hdict = spirouImage.AddKey1DList(p,
hdict,
p['KW_INFILE1'],
dim1name='hcfile',
values=p['HCFILE'])
hdict = spirouImage.AddKey1DList(p,
hdict,
p['KW_INFILE2'],
dim1name='fpfile',
values=p['FPFILES'])
# add qc parameters
hdict = spirouImage.AddKey(p, hdict, p['KW_DRS_QC'], value=p['QC'])
hdict = spirouImage.AddQCKeys(p, hdict, qc_params)
# write tilt file to file
p = spirouImage.WriteImageTable(p,
shapeyfits,
image=loc['DYMAP'],
table=fptable,
hdict=hdict)
# ------------------------------------------------------------------
# Writing Master FP to file
# ------------------------------------------------------------------
# get the raw tilt file name
raw_shape_file = os.path.basename(p['FITSFILENAME'])
# construct file name and path
fpmasterfits, tag = spirouConfig.Constants.SLIT_MASTER_FP_FILE(p)
fpmasterfitsname = os.path.basename(fpmasterfits)
# Log that we are saving tilt file
wmsg = 'Saving master FP file: {0}'
WLOG(p, '', wmsg.format(fpmasterfitsname))
# Copy keys from fits file
hdict = spirouImage.CopyOriginalKeys(fphdr)
# add version number
hdict = spirouImage.AddKey(p, hdict, p['KW_VERSION'])
hdict = spirouImage.AddKey(p, hdict, p['KW_DRS_DATE'], value=p['DRS_DATE'])
hdict = spirouImage.AddKey(p, hdict, p['KW_DATE_NOW'], value=p['DATE_NOW'])
hdict = spirouImage.AddKey(p, hdict, p['KW_PID'], value=p['PID'])
hdict = spirouImage.AddKey(p, hdict, p['KW_OUTPUT'], value=tag)
hdict = spirouImage.AddKey(p, hdict, p['KW_CDBDARK'], value=p['DARKFILE'])
hdict = spirouImage.AddKey(p, hdict, p['KW_CDBBAD'], value=p['BADPFILE'])
hdict = spirouImage.AddKey(p, hdict, p['KW_CDBLOCO'], value=p['LOCOFILE'])
hdict = spirouImage.AddKey1DList(p,
hdict,
p['KW_INFILE1'],
dim1name='hcfile',
values=p['HCFILE'])
hdict = spirouImage.AddKey1DList(p,
hdict,
p['KW_INFILE2'],
dim1name='fpfile',
values=p['FPFILES'])
# add qc parameters
hdict = spirouImage.AddKey(p, hdict, p['KW_DRS_QC'], value=p['QC'])
hdict = spirouImage.AddQCKeys(p, hdict, qc_params)
# write tilt file to file
p = spirouImage.WriteImageTable(p,
fpmasterfits,
image=masterfp,
table=fptable,
hdict=hdict)
# ------------------------------------------------------------------
# Writing sanity check files
# ------------------------------------------------------------------
if p['SHAPE_DEBUG_OUTPUTS']:
# log
WLOG(p, '', 'Saving debug sanity check files')
# construct file names
input_fp_file, tag1 = spirouConfig.Constants.SLIT_SHAPE_IN_FP_FILE(p)
output_fp_file, tag2 = spirouConfig.Constants.SLIT_SHAPE_OUT_FP_FILE(p)
input_hc_file, tag3 = spirouConfig.Constants.SLIT_SHAPE_IN_HC_FILE(p)
output_hc_file, tag4 = spirouConfig.Constants.SLIT_SHAPE_OUT_HC_FILE(p)
bdxmap_file, tag5 = spirouConfig.Constants.SLIT_SHAPE_BDXMAP_FILE(p)
# write input fp file
hdict = spirouImage.AddKey(p, hdict, p['KW_OUTPUT'], value=tag1)
p = spirouImage.WriteImage(p, input_fp_file, loc['FPDATA1'], hdict)
# write output fp file
hdict = spirouImage.AddKey(p, hdict, p['KW_OUTPUT'], value=tag2)
p = spirouImage.WriteImage(p, output_fp_file, loc['FPDATA2'], hdict)
# write input fp file
hdict = spirouImage.AddKey(p, hdict, p['KW_OUTPUT'], value=tag3)
p = spirouImage.WriteImage(p, input_hc_file, loc['HCDATA1'], hdict)
# write output fp file
hdict = spirouImage.AddKey(p, hdict, p['KW_OUTPUT'], value=tag4)
p = spirouImage.WriteImage(p, output_hc_file, loc['HCDATA2'], hdict)
# write overlap file
hdict = spirouImage.AddKey(p, hdict, p['KW_OUTPUT'], value=tag5)
p = spirouImage.WriteImage(p, bdxmap_file, loc['DXMAP0'], hdict)
# ----------------------------------------------------------------------
# Move to calibDB and update calibDB
# ----------------------------------------------------------------------
if p['QC']:
# add shape x
keydb = 'SHAPEX'
# copy shape file to the calibDB folder
spirouDB.PutCalibFile(p, shapexfits)
# update the master calib DB file with new key
spirouDB.UpdateCalibMaster(p, keydb, shapexfitsname, fphdr)
# add shape y
keydb = 'SHAPEY'
# copy shape file to the calibDB folder
spirouDB.PutCalibFile(p, shapeyfits)
# update the master calib DB file with new key
spirouDB.UpdateCalibMaster(p, keydb, shapeyfitsname, fphdr)
# add fp master
keydb = 'FPMASTER'
# copy shape file to the calibDB folder
spirouDB.PutCalibFile(p, fpmasterfits)
# update the master calib DB file with new key
spirouDB.UpdateCalibMaster(p, keydb, fpmasterfitsname, fphdr)
# ----------------------------------------------------------------------
# End Message
# ----------------------------------------------------------------------
p = spirouStartup.End(p)
# return a copy of locally defined variables in the memory
return dict(locals())
def main(night_name=None, fpfile=None, hcfiles=None):
"""
cal_WAVE_E2DS.py main function, if night_name and files are None uses
arguments from run time i.e.:
cal_DARK_spirou.py [night_directory] [fpfile] [hcfiles]
:param night_name: string or None, the folder within data raw directory
containing files (also reduced directory) i.e.
/data/raw/20170710 would be "20170710" but
/data/raw/AT5/20180409 would be "AT5/20180409"
:param fpfile: string, or None, the FP file to use for
arg_file_names and fitsfilename
(if None assumes arg_file_names was set from run time)
:param hcfiles: string, list or None, the list of HC files to use for
arg_file_names and fitsfilename
(if None assumes arg_file_names was set from run time)
:return ll: dictionary, containing all the local variables defined in
main
"""
# ----------------------------------------------------------------------
# Set up
# ----------------------------------------------------------------------
# test files TC2
# night_name = 'AT5/AT5-12/2018-05-29_17-41-44/'
# fpfile = '2279844a_fp_fp_pp_e2dsff_AB.fits'
# hcfiles = ['2279845c_hc_pp_e2dsff_AB.fits']
# test files TC3
# night_name = 'TC3/AT5/AT5-12/2018-07-24_16-17-57/'
# fpfile = '2294108a_pp_e2dsff_AB.fits'
# hcfiles = ['2294115c_pp_e2dsff_AB.fits']
# night_name = 'TC3/AT5/AT5-12/2018-07-25_16-49-50/'
# fpfile = '2294223a_pp_e2dsff_AB.fits'
# hcfiles = ['2294230c_pp_e2dsff_AB.fits']
# get parameters from config files/run time args/load paths + calibdb
p = spirouStartup.Begin(recipe=__NAME__)
if hcfiles is None or fpfile is None:
names, types = ['fpfile', 'hcfiles'], [str, str]
customargs = spirouStartup.GetCustomFromRuntime(p, [0, 1],
types,
names,
last_multi=True)
else:
customargs = dict(hcfiles=hcfiles, fpfile=fpfile)
# get parameters from configuration files and run time arguments
p = spirouStartup.LoadArguments(p,
night_name,
customargs=customargs,
mainfitsdir='reduced',
mainfitsfile='hcfiles')
# ----------------------------------------------------------------------
# Construct reference filename and get fiber type
# ----------------------------------------------------------------------
p, fpfitsfilename = spirouStartup.SingleFileSetup(p, filename=p['FPFILE'])
fiber1 = str(p['FIBER'])
p, hcfilenames = spirouStartup.MultiFileSetup(p, files=p['HCFILES'])
fiber2 = str(p['FIBER'])
# set the hcfilename to the first hcfilenames
hcfitsfilename = hcfilenames[0]
# ----------------------------------------------------------------------
# Once we have checked the e2dsfile we can load calibDB
# ----------------------------------------------------------------------
# as we have custom arguments need to load the calibration database
p = spirouStartup.LoadCalibDB(p)
# ----------------------------------------------------------------------
# Have to check that the fibers match
# ----------------------------------------------------------------------
if fiber1 == fiber2:
p['FIBER'] = fiber1
fsource = __NAME__ + '/main() & spirouStartup.GetFiberType()'
p.set_source('FIBER', fsource)
else:
emsg = 'Fiber not matching for {0} and {1}, should be the same'
eargs = [hcfitsfilename, fpfitsfilename]
WLOG(p, 'error', emsg.format(*eargs))
# set the fiber type
p['FIB_TYP'] = [p['FIBER']]
p.set_source('FIB_TYP', __NAME__ + '/main()')
# ----------------------------------------------------------------------
# Read FP and HC files
# ----------------------------------------------------------------------
# read and combine all HC files except the first (fpfitsfilename)
rargs = [p, 'add', hcfitsfilename, hcfilenames[1:]]
p, hcdata, hchdr = spirouImage.ReadImageAndCombine(*rargs)
# read first file (fpfitsfilename)
fpdata, fphdr, _, _ = spirouImage.ReadImage(p, fpfitsfilename)
# TODO: ------------------------------------------------------------
# TODO remove to test NaNs
# TODO: ------------------------------------------------------------
# hcmask = np.isfinite(hcdata)
# fpmask = np.isfinite(fpdata)
# hcdata[~hcmask] = 0.0
# fpdata[~fpmask] = 0.0
# TODO: ------------------------------------------------------------
# add data and hdr to loc
loc = ParamDict()
loc['HCDATA'], loc['HCHDR'] = hcdata, hchdr
loc['FPDATA'], loc['FPHDR'] = fpdata, fphdr
# set the source
sources = ['HCDATA', 'HCHDR']
loc.set_sources(sources, 'spirouImage.ReadImageAndCombine()')
sources = ['FPDATA', 'FPHDR']
loc.set_sources(sources, 'spirouImage.ReadImage()')
# ----------------------------------------------------------------------
# Get basic image properties for reference file
# ----------------------------------------------------------------------
# get sig det value
p = spirouImage.GetSigdet(p, hchdr, name='sigdet')
# get exposure time
p = spirouImage.GetExpTime(p, hchdr, name='exptime')
# get gain
p = spirouImage.GetGain(p, hchdr, name='gain')
# get acquisition time
p = spirouImage.GetAcqTime(p, hchdr, name='acqtime', kind='julian')
bjdref = p['ACQTIME']
# set sigdet and conad keywords (sigdet is changed later)
p['KW_CCD_SIGDET'][1] = p['SIGDET']
p['KW_CCD_CONAD'][1] = p['GAIN']
# get lamp parameters
p = spirouTHORCA.GetLampParams(p, hchdr)
# get number of orders
# we always get fibre A number because AB is doubled in constants file
loc['NBO'] = p['QC_LOC_NBO_FPALL']['A']
loc.set_source('NBO', __NAME__ + '.main()')
# get number of pixels in x from hcdata size
loc['NBPIX'] = loc['HCDATA'].shape[1]
loc.set_source('NBPIX', __NAME__ + '.main()')
# ----------------------------------------------------------------------
# Read blaze
# ----------------------------------------------------------------------
# get tilts
p, loc['BLAZE'] = spirouImage.ReadBlazeFile(p, hchdr)
loc.set_source('BLAZE', __NAME__ + '/main() + /spirouImage.ReadBlazeFile')
# make copy of blaze (as it's overwritten later)
loc['BLAZE2'] = np.copy(loc['BLAZE'])
# ----------------------------------------------------------------------
# Read wave solution
# ----------------------------------------------------------------------
# wavelength file; we will use the polynomial terms in its header,
# NOT the pixel values that would need to be interpolated
# set source of wave file
wsource = __NAME__ + '/main() + /spirouImage.GetWaveSolution'
# Force A and B to AB solution
if p['FIBER'] in ['A', 'B']:
wave_fiber = 'AB'
else:
wave_fiber = p['FIBER']
# get wave image
wout = spirouImage.GetWaveSolution(p,
hdr=hchdr,
return_wavemap=True,
return_filename=True,
fiber=wave_fiber)
loc['WAVEPARAMS'], loc['WAVE_INIT'], loc['WAVEFILE'], loc['WSOURCE'] = wout
loc.set_sources(['WAVE_INIT', 'WAVEFILE', 'WAVEPARAMS', 'WSOURCE'],
wsource)
poly_wave_sol = loc['WAVEPARAMS']
# ----------------------------------------------------------------------
# Check that wave parameters are consistent with "ic_ll_degr_fit"
# ----------------------------------------------------------------------
loc = spirouImage.CheckWaveSolConsistency(p, loc)
# ----------------------------------------------------------------------
# Read UNe solution
# ----------------------------------------------------------------------
wave_u_ne, amp_u_ne = spirouImage.ReadLineList(p)
loc['LL_LINE'], loc['AMPL_LINE'] = wave_u_ne, amp_u_ne
source = __NAME__ + '.main() + spirouImage.ReadLineList()'
loc.set_sources(['ll_line', 'ampl_line'], source)
# ----------------------------------------------------------------------
# Generate wave map from wave solution
# ----------------------------------------------------------------------
loc = spirouWAVE.generate_wave_map(p, loc)
# ----------------------------------------------------------------------
# Find Gaussian Peaks in HC spectrum
# ----------------------------------------------------------------------
loc = spirouWAVE.find_hc_gauss_peaks(p, loc)
# ----------------------------------------------------------------------
# Start plotting session
# ----------------------------------------------------------------------
if p['DRS_PLOT'] > 0:
# start interactive plot
sPlt.start_interactive_session(p)
# ----------------------------------------------------------------------
# Fit Gaussian peaks (in triplets) to
# ----------------------------------------------------------------------
loc = spirouWAVE.fit_gaussian_triplets(p, loc)
# ----------------------------------------------------------------------
# Generate Resolution map and line profiles
# ----------------------------------------------------------------------
# log progress
wmsg = 'Generating resolution map and '
# generate resolution map
loc = spirouWAVE.generate_resolution_map(p, loc)
# map line profile map
if p['DRS_PLOT'] > 0:
sPlt.wave_ea_plot_line_profiles(p, loc)
# ----------------------------------------------------------------------
# End plotting session
# ----------------------------------------------------------------------
# end interactive session
if p['DRS_PLOT'] > 0:
sPlt.end_interactive_session(p)
# ----------------------------------------------------------------------
# Set up all_lines storage
# ----------------------------------------------------------------------
# initialise up all_lines storage
all_lines_1 = []
# get parameters from p
n_ord_start = p['IC_HC_N_ORD_START_2']
n_ord_final = p['IC_HC_N_ORD_FINAL_2']
pixel_shift_inter = p['PIXEL_SHIFT_INTER']
pixel_shift_slope = p['PIXEL_SHIFT_SLOPE']
# get values from loc
xgau = np.array(loc['XGAU_T'])
dv = np.array(loc['DV_T'])
fit_per_order = np.array(loc['POLY_WAVE_SOL'])
ew = np.array(loc['EW_T'])
peak = np.array(loc['PEAK_T'])
amp_catalog = np.array(loc['AMP_CATALOG'])
wave_catalog = np.array(loc['WAVE_CATALOG'])
ord_t = np.array(loc['ORD_T'])
# loop through orders
for iord in range(n_ord_start, n_ord_final):
# keep relevant lines
# -> right order
# -> finite dv
gg = (ord_t == iord) & (np.isfinite(dv))
nlines = np.nansum(gg)
# put lines into ALL_LINES structure
# reminder:
# gparams[0] = output wavelengths
# gparams[1] = output sigma(gauss fit width)
# gparams[2] = output amplitude(gauss fit)
# gparams[3] = difference in input / output wavelength
# gparams[4] = input amplitudes
# gparams[5] = output pixel positions
# gparams[6] = output pixel sigma width (gauss fit width in pixels)
# gparams[7] = output weights for the pixel position
chebval = np.polynomial.chebyshev.chebval
# dummy array for weights
test = np.ones(np.shape(xgau[gg]), 'd') * 1e4
# get the final wavelength value for each peak in order
output_wave_1 = np.polyval(fit_per_order[iord][::-1], xgau[gg])
# output_wave_1 = chebval(xgau[gg], fit_per_order[iord])
# convert the pixel equivalent width to wavelength units
xgau_ew_ini = xgau[gg] - ew[gg] / 2
xgau_ew_fin = xgau[gg] + ew[gg] / 2
ew_ll_ini = np.polyval(fit_per_order[iord, :], xgau_ew_ini)
ew_ll_fin = np.polyval(fit_per_order[iord, :], xgau_ew_fin)
# ew_ll_ini = chebval(xgau_ew_ini, fit_per_order[iord])
# ew_ll_fin = chebval(xgau_ew_fin, fit_per_order[iord])
ew_ll = ew_ll_fin - ew_ll_ini
# put all lines in the order into array
gau_params = np.column_stack(
(output_wave_1, ew_ll, peak[gg], wave_catalog[gg] - output_wave_1,
amp_catalog[gg], xgau[gg], ew[gg], test))
# append the array for the order into a list
all_lines_1.append(gau_params)
# save dv in km/s and auxiliary order number
# res_1 = np.concatenate((res_1,2.997e5*(input_wave - output_wave_1)/
# output_wave_1))
# ord_save = np.concatenate((ord_save, test*iord))
# add to loc
loc['ALL_LINES_1'] = all_lines_1
loc['LL_PARAM_1'] = np.array(fit_per_order)
loc['LL_OUT_1'] = np.array(loc['WAVE_MAP2'])
loc.set_sources(['ALL_LINES_1', 'LL_PARAM_1'], __NAME__ + '/main()')
# For compatibility w/already defined functions, I need to save
# here all_lines_2
all_lines_2 = list(all_lines_1)
loc['ALL_LINES_2'] = all_lines_2
# loc['LL_PARAM_2'] = np.fliplr(fit_per_order)
# loc['LL_OUT_2'] = np.array(loc['WAVE_MAP2'])
# loc.set_sources(['ALL_LINES_2', 'LL_PARAM_2'], __NAME__ + '/main()')
# ------------------------------------------------------------------
# Littrow test
# ------------------------------------------------------------------
start = p['IC_LITTROW_ORDER_INIT_1']
end = p['IC_LITTROW_ORDER_FINAL_1']
# calculate echelle orders
o_orders = np.arange(start, end)
echelle_order = p['IC_HC_T_ORDER_START'] - o_orders
loc['ECHELLE_ORDERS'] = echelle_order
loc.set_source('ECHELLE_ORDERS', __NAME__ + '/main()')
# reset Littrow fit degree
p['IC_LITTROW_FIT_DEG_1'] = 7
# Do Littrow check
ckwargs = dict(ll=loc['LL_OUT_1'][start:end, :], iteration=1, log=True)
loc = spirouTHORCA.CalcLittrowSolution(p, loc, **ckwargs)
# Plot wave solution littrow check
if p['DRS_PLOT'] > 0:
# plot littrow x pixels against fitted wavelength solution
sPlt.wave_littrow_check_plot(p, loc, iteration=1)
# ------------------------------------------------------------------
# extrapolate Littrow solution
# ------------------------------------------------------------------
ekwargs = dict(ll=loc['LL_OUT_1'], iteration=1)
loc = spirouTHORCA.ExtrapolateLittrowSolution(p, loc, **ekwargs)
# ------------------------------------------------------------------
# Plot littrow solution
# ------------------------------------------------------------------
if p['DRS_PLOT'] > 0:
# plot littrow x pixels against fitted wavelength solution
sPlt.wave_littrow_extrap_plot(p, loc, iteration=1)
# ------------------------------------------------------------------
# Incorporate FP into solution
# ------------------------------------------------------------------
# Copy LL_OUT_1 and LL_PARAM_1 into new constants (for FP integration)
loc['LITTROW_EXTRAP_SOL_1'] = np.array(loc['LL_OUT_1'])
loc['LITTROW_EXTRAP_PARAM_1'] = np.array(loc['LL_PARAM_1'])
# only use FP if switched on in constants file
if p['IC_WAVE_USE_FP']:
# ------------------------------------------------------------------
# Find FP lines
# ------------------------------------------------------------------
# print message to screen
wmsg = 'Identification of lines in reference file: {0}'
WLOG(p, '', wmsg.format(fpfile))
# ------------------------------------------------------------------
# Get the FP solution
# ------------------------------------------------------------------
loc = spirouTHORCA.FPWaveSolutionNew(p, loc)
# ------------------------------------------------------------------
# FP solution plots
# ------------------------------------------------------------------
if p['DRS_PLOT'] > 0:
# Plot the FP extracted spectrum against wavelength solution
sPlt.wave_plot_final_fp_order(p, loc, iteration=1)
# Plot the measured FP cavity width offset against line number
sPlt.wave_local_width_offset_plot(p, loc)
# Plot the FP line wavelength residuals
sPlt.wave_fp_wavelength_residuals(p, loc)
# ------------------------------------------------------------------
# Create new wavelength solution
# ------------------------------------------------------------------
# TODO: Melissa fault - fix later
p['IC_HC_N_ORD_START_2'] = min(p['IC_HC_N_ORD_START_2'],
p['IC_FP_N_ORD_START'])
p['IC_HC_N_ORD_FINAL_2'] = max(p['IC_HC_N_ORD_FINAL_2'],
p['IC_FP_N_ORD_FINAL'])
start = p['IC_HC_N_ORD_START_2']
end = p['IC_HC_N_ORD_FINAL_2']
# recalculate echelle orders for Fit1DSolution
o_orders = np.arange(start, end)
echelle_order = p['IC_HC_T_ORDER_START'] - o_orders
loc['ECHELLE_ORDERS'] = echelle_order
loc.set_source('ECHELLE_ORDERS', __NAME__ + '/main()')
# select the orders to fit
lls = loc['LITTROW_EXTRAP_SOL_1'][start:end]
loc = spirouTHORCA.Fit1DSolution(p, loc, lls, iteration=2)
# from here, LL_OUT_2 wil be 0-47
# ------------------------------------------------------------------
# Repeat Littrow test
# ------------------------------------------------------------------
start = p['IC_LITTROW_ORDER_INIT_2']
end = p['IC_LITTROW_ORDER_FINAL_2']
# recalculate echelle orders for Littrow check
o_orders = np.arange(start, end)
echelle_order = p['IC_HC_T_ORDER_START'] - o_orders
loc['ECHELLE_ORDERS'] = echelle_order
loc.set_source('ECHELLE_ORDERS', __NAME__ + '/main()')
# Do Littrow check
ckwargs = dict(ll=loc['LL_OUT_2'][start:end, :], iteration=2, log=True)
loc = spirouTHORCA.CalcLittrowSolution(p, loc, **ckwargs)
# Plot wave solution littrow check
if p['DRS_PLOT'] > 0:
# plot littrow x pixels against fitted wavelength solution
sPlt.wave_littrow_check_plot(p, loc, iteration=2)
# ------------------------------------------------------------------
# extrapolate Littrow solution
# ------------------------------------------------------------------
ekwargs = dict(ll=loc['LL_OUT_2'], iteration=2)
loc = spirouTHORCA.ExtrapolateLittrowSolution(p, loc, **ekwargs)
# ------------------------------------------------------------------
# Plot littrow solution
# ------------------------------------------------------------------
if p['DRS_PLOT'] > 0:
# plot littrow x pixels against fitted wavelength solution
sPlt.wave_littrow_extrap_plot(p, loc, iteration=2)
# ------------------------------------------------------------------
# Join 0-47 and 47-49 solutions
# ------------------------------------------------------------------
loc = spirouTHORCA.JoinOrders(p, loc)
# ------------------------------------------------------------------
# Plot single order, wavelength-calibrated, with found lines
# ------------------------------------------------------------------
if p['DRS_PLOT'] > 0:
sPlt.wave_ea_plot_single_order(p, loc)
# ----------------------------------------------------------------------
# Do correlation on FP spectra
# ----------------------------------------------------------------------
# ------------------------------------------------------------------
# Compute photon noise uncertainty for FP
# ------------------------------------------------------------------
# set up the arguments for DeltaVrms2D
dargs = [loc['FPDATA'], loc['LL_FINAL']]
dkwargs = dict(sigdet=p['IC_DRIFT_NOISE'],
size=p['IC_DRIFT_BOXSIZE'],
threshold=p['IC_DRIFT_MAXFLUX'])
# run DeltaVrms2D
dvrmsref, wmeanref = spirouRV.DeltaVrms2D(*dargs, **dkwargs)
# save to loc
loc['DVRMSREF'], loc['WMEANREF'] = dvrmsref, wmeanref
loc.set_sources(['dvrmsref', 'wmeanref'], __NAME__ + '/main()()')
# log the estimated RV uncertainty
wmsg = 'On fiber {0} estimated RV uncertainty on spectrum is {1:.3f} m/s'
WLOG(p, 'info', wmsg.format(p['FIBER'], wmeanref))
# Use CCF Mask function with drift constants
p['CCF_MASK'] = p['DRIFT_CCF_MASK']
p['TARGET_RV'] = p['DRIFT_TARGET_RV']
p['CCF_WIDTH'] = p['DRIFT_CCF_WIDTH']
p['CCF_STEP'] = p['DRIFT_CCF_STEP']
p['RVMIN'] = p['TARGET_RV'] - p['CCF_WIDTH']
p['RVMAX'] = p['TARGET_RV'] + p['CCF_WIDTH'] + p['CCF_STEP']
# get the CCF mask from file (check location of mask)
loc = spirouRV.GetCCFMask(p, loc)
# TODO Check why Blaze makes bugs in correlbin
loc['BLAZE'] = np.ones((loc['NBO'], loc['NBPIX']))
# set sources
# loc.set_sources(['flat', 'blaze'], __NAME__ + '/main()')
loc.set_source('blaze', __NAME__ + '/main()')
# ----------------------------------------------------------------------
# Do correlation on FP
# ----------------------------------------------------------------------
# calculate and fit the CCF
loc['E2DSFF'] = np.array(loc['FPDATA'])
loc.set_source('E2DSFF', __NAME__ + '/main()')
p['CCF_FIT_TYPE'] = 1
loc['BERV'] = 0.0
loc['BERV_MAX'] = 0.0
loc['BJD'] = 0.0
# run the RV coravelation function with these parameters
loc['WAVE_LL'] = np.array(loc['LL_FINAL'])
loc['PARAM_LL'] = np.array(loc['LL_PARAM_FINAL'])
loc = spirouRV.Coravelation(p, loc)
# ----------------------------------------------------------------------
# Update the Correlation stats with values using fiber C (FP) drift
# ----------------------------------------------------------------------
# get the maximum number of orders to use
nbmax = p['CCF_NUM_ORDERS_MAX']
# get the average ccf
loc['AVERAGE_CCF'] = np.nansum(loc['CCF'][:nbmax], axis=0)
# normalize the average ccf
normalized_ccf = loc['AVERAGE_CCF'] / np.nanmax(loc['AVERAGE_CCF'])
# get the fit for the normalized average ccf
ccf_res, ccf_fit = spirouRV.FitCCF(p,
loc['RV_CCF'],
normalized_ccf,
fit_type=1)
loc['CCF_RES'] = ccf_res
loc['CCF_FIT'] = ccf_fit
# get the max cpp
loc['MAXCPP'] = np.nansum(loc['CCF_MAX']) / np.nansum(
loc['PIX_PASSED_ALL'])
# get the RV value from the normalised average ccf fit center location
loc['RV'] = float(ccf_res[1])
# get the contrast (ccf fit amplitude)
loc['CONTRAST'] = np.abs(100 * ccf_res[0])
# get the FWHM value
loc['FWHM'] = ccf_res[2] * spirouCore.spirouMath.fwhm()
# set the source
keys = [
'AVERAGE_CCF', 'MAXCPP', 'RV', 'CONTRAST', 'FWHM', 'CCF_RES', 'CCF_FIT'
]
loc.set_sources(keys, __NAME__ + '/main()')
# ----------------------------------------------------------------------
# log the stats
wmsg = ('FP Correlation: C={0:.1f}[%] DRIFT={1:.5f}[km/s] '
'FWHM={2:.4f}[km/s] maxcpp={3:.1f}')
wargs = [loc['CONTRAST'], float(ccf_res[1]), loc['FWHM'], loc['MAXCPP']]
WLOG(p, 'info', wmsg.format(*wargs))
# ----------------------------------------------------------------------
# rv ccf plot
# ----------------------------------------------------------------------
if p['DRS_PLOT'] > 0:
# Plot rv vs ccf (and rv vs ccf_fit)
p['OBJNAME'] = 'FP'
sPlt.ccf_rv_ccf_plot(p, loc['RV_CCF'], normalized_ccf, ccf_fit)
# TODO : Add QC of the FP CCF
# ----------------------------------------------------------------------
# Quality control
# ----------------------------------------------------------------------
# get parameters ffrom p
p['QC_RMS_LITTROW_MAX'] = p['QC_HC_RMS_LITTROW_MAX']
p['QC_DEV_LITTROW_MAX'] = p['QC_HC_DEV_LITTROW_MAX']
# set passed variable and fail message list
passed, fail_msg = True, []
qc_values, qc_names, qc_logic, qc_pass = [], [], [], []
# ----------------------------------------------------------------------
# quality control on sigma clip (sig1 > qc_hc_wave_sigma_max
if loc['SIG1'] > p['QC_HC_WAVE_SIGMA_MAX']:
fmsg = 'Sigma too high ({0:.5f} > {1:.5f})'
fail_msg.append(fmsg.format(loc['SIG1'], p['QC_HC_WAVE_SIGMA_MAX']))
passed = False
qc_pass.append(0)
else:
qc_pass.append(1)
# add to qc header lists
qc_values.append(loc['SIG1'])
qc_names.append('SIG1')
qc_logic.append('SIG1 > {0:.2f}'.format(p['QC_HC_WAVE_SIGMA_MAX']))
# ----------------------------------------------------------------------
# check the difference between consecutive orders is always positive
# get the differences
wave_diff = loc['LL_FINAL'][1:] - loc['LL_FINAL'][:-1]
if np.min(wave_diff) < 0:
fmsg = 'Negative wavelength difference between orders'
fail_msg.append(fmsg)
passed = False
qc_pass.append(0)
else:
qc_pass.append(1)
# add to qc header lists
qc_values.append(np.min(wave_diff))
qc_names.append('MIN WAVE DIFF')
qc_logic.append('MIN WAVE DIFF < 0')
# ----------------------------------------------------------------------
# check for infinites and NaNs in mean residuals from fit
if ~np.isfinite(loc['X_MEAN_2']):
# add failed message to the fail message list
fmsg = 'NaN or Inf in X_MEAN_2'
fail_msg.append(fmsg)
passed = False
qc_pass.append(0)
else:
qc_pass.append(1)
# add to qc header lists
qc_values.append(loc['X_MEAN_2'])
qc_names.append('X_MEAN_2')
qc_logic.append('X_MEAN_2 not finite')
# ----------------------------------------------------------------------
# iterate through Littrow test cut values
lit_it = 2
# checks every other value
# TODO: This QC check (or set of QC checks needs re-writing it is
# TODO: nearly impossible to understand
for x_it in range(1, len(loc['X_CUT_POINTS_' + str(lit_it)]), 2):
# get x cut point
x_cut_point = loc['X_CUT_POINTS_' + str(lit_it)][x_it]
# get the sigma for this cut point
sig_littrow = loc['LITTROW_SIG_' + str(lit_it)][x_it]
# get the abs min and max dev littrow values
min_littrow = abs(loc['LITTROW_MINDEV_' + str(lit_it)][x_it])
max_littrow = abs(loc['LITTROW_MAXDEV_' + str(lit_it)][x_it])
# get the corresponding order
min_littrow_ord = loc['LITTROW_MINDEVORD_' + str(lit_it)][x_it]
max_littrow_ord = loc['LITTROW_MAXDEVORD_' + str(lit_it)][x_it]
# check if sig littrow is above maximum
rms_littrow_max = p['QC_RMS_LITTROW_MAX']
dev_littrow_max = p['QC_DEV_LITTROW_MAX']
if sig_littrow > rms_littrow_max:
fmsg = ('Littrow test (x={0}) failed (sig littrow = '
'{1:.2f} > {2:.2f})')
fargs = [x_cut_point, sig_littrow, rms_littrow_max]
fail_msg.append(fmsg.format(*fargs))
passed = False
qc_pass.append(0)
else:
qc_pass.append(1)
# add to qc header lists
qc_values.append(sig_littrow)
qc_names.append('sig_littrow')
qc_logic.append('sig_littrow > {0:.2f}'.format(rms_littrow_max))
# ----------------------------------------------------------------------
# check if min/max littrow is out of bounds
if np.max([max_littrow, min_littrow]) > dev_littrow_max:
fmsg = ('Littrow test (x={0}) failed (min|max dev = '
'{1:.2f}|{2:.2f} > {3:.2f} for order {4}|{5})')
fargs = [
x_cut_point, min_littrow, max_littrow, dev_littrow_max,
min_littrow_ord, max_littrow_ord
]
fail_msg.append(fmsg.format(*fargs))
passed = False
qc_pass.append(0)
# TODO: Should this be the QC header values?
# TODO: it does not change the outcome of QC (i.e. passed=False)
# TODO: So what is the point?
# if sig was out of bounds, recalculate
if sig_littrow > rms_littrow_max:
# conditions
check1 = min_littrow > dev_littrow_max
check2 = max_littrow > dev_littrow_max
# get the residuals
respix = loc['LITTROW_YY_' + str(lit_it)][x_it]
# check if both are out of bounds
if check1 and check2:
# remove respective orders
worst_order = (min_littrow_ord, max_littrow_ord)
respix_2 = np.delete(respix, worst_order)
redo_sigma = True
# check if min is out of bounds
elif check1:
# remove respective order
worst_order = min_littrow_ord
respix_2 = np.delete(respix, worst_order)
redo_sigma = True
# check if max is out of bounds
elif check2:
# remove respective order
worst_order = max_littrow_ord
respix_2 = np.delete(respix, max_littrow_ord)
redo_sigma = True
# else do not recalculate sigma
else:
redo_sigma, respix_2, worst_order = False, None, None
wmsg = 'No outlying orders, sig littrow not recalculated'
fail_msg.append(wmsg.format())
# if outlying order, recalculate stats
if redo_sigma:
mean = np.nansum(respix_2) / len(respix_2)
mean2 = np.nansum(respix_2**2) / len(respix_2)
rms = np.sqrt(mean2 - mean**2)
if rms > rms_littrow_max:
fmsg = ('Littrow test (x={0}) failed (sig littrow = '
'{1:.2f} > {2:.2f} removing order {3})')
fargs = [
x_cut_point, rms, rms_littrow_max, worst_order
]
fail_msg.append(fmsg.format(*fargs))
else:
wargs = [
x_cut_point, rms, rms_littrow_max, worst_order
]
wmsg = ('Littrow test (x={0}) passed (sig littrow = '
'{1:.2f} > {2:.2f} removing order {3})')
fail_msg.append(wmsg.format(*wargs))
else:
qc_pass.append(1)
# add to qc header lists
qc_values.append(np.max([max_littrow, min_littrow]))
qc_names.append('max or min littrow')
qc_logic.append('max or min littrow > {0:.2f}'
''.format(dev_littrow_max))
# finally log the failed messages and set QC = 1 if we pass the
# quality control QC = 0 if we fail quality control
if passed:
WLOG(p, 'info', 'QUALITY CONTROL SUCCESSFUL - Well Done -')
p['QC'] = 1
p.set_source('QC', __NAME__ + '/main()')
else:
for farg in fail_msg:
wmsg = 'QUALITY CONTROL FAILED: {0}'
WLOG(p, 'warning', wmsg.format(farg))
p['QC'] = 0
p.set_source('QC', __NAME__ + '/main()')
# store in qc_params
qc_params = [qc_names, qc_values, qc_logic, qc_pass]
# ------------------------------------------------------------------
# archive result in e2ds spectra
# ------------------------------------------------------------------
# get raw input file name(s)
raw_infiles1 = []
for hcfile in p['HCFILES']:
raw_infiles1.append(os.path.basename(hcfile))
raw_infile2 = os.path.basename(p['FPFILE'])
# get wave filename
wavefits, tag1 = spirouConfig.Constants.WAVE_FILE_EA_2(p)
wavefitsname = os.path.split(wavefits)[-1]
# log progress
wargs = [p['FIBER'], wavefits]
wmsg = 'Write wavelength solution for Fiber {0} in {1}'
WLOG(p, '', wmsg.format(*wargs))
# write solution to fitsfilename header
# copy original keys
hdict = spirouImage.CopyOriginalKeys(loc['HCHDR'])
# add version number
hdict = spirouImage.AddKey(p, hdict, p['KW_VERSION'])
hdict = spirouImage.AddKey(p, hdict, p['KW_DRS_DATE'], value=p['DRS_DATE'])
hdict = spirouImage.AddKey(p, hdict, p['KW_DATE_NOW'], value=p['DATE_NOW'])
hdict = spirouImage.AddKey(p, hdict, p['KW_PID'], value=p['PID'])
# set the input files
hdict = spirouImage.AddKey(p, hdict, p['KW_CDBBLAZE'], value=p['BLAZFILE'])
hdict = spirouImage.AddKey(p,
hdict,
p['KW_CDBWAVE'],
value=loc['WAVEFILE'])
hdict = spirouImage.AddKey(p,
hdict,
p['KW_WAVESOURCE'],
value=loc['WSOURCE'])
hdict = spirouImage.AddKey1DList(p,
hdict,
p['KW_INFILE1'],
dim1name='fpfile',
values=p['FPFILE'])
hdict = spirouImage.AddKey1DList(p,
hdict,
p['KW_INFILE2'],
dim1name='hcfile',
values=p['HCFILES'])
# add qc parameters
hdict = spirouImage.AddKey(p, hdict, p['KW_DRS_QC'], value=p['QC'])
hdict = spirouImage.AddQCKeys(p, hdict, qc_params)
# add wave solution date
hdict = spirouImage.AddKey(p,
hdict,
p['KW_WAVE_TIME1'],
value=p['MAX_TIME_HUMAN'])
hdict = spirouImage.AddKey(p,
hdict,
p['KW_WAVE_TIME2'],
value=p['MAX_TIME_UNIX'])
hdict = spirouImage.AddKey(p, hdict, p['KW_WAVE_CODE'], value=__NAME__)
# add number of orders
hdict = spirouImage.AddKey(p,
hdict,
p['KW_WAVE_ORD_N'],
value=loc['LL_PARAM_FINAL'].shape[0])
# add degree of fit
hdict = spirouImage.AddKey(p,
hdict,
p['KW_WAVE_LL_DEG'],
value=loc['LL_PARAM_FINAL'].shape[1] - 1)
# add wave solution
hdict = spirouImage.AddKey2DList(p,
hdict,
p['KW_WAVE_PARAM'],
values=loc['LL_PARAM_FINAL'])
# add FP CCF drift
# target RV and width
hdict = spirouImage.AddKey(p,
hdict,
p['KW_WFP_TARG_RV'],
value=p['TARGET_RV'])
hdict = spirouImage.AddKey(p,
hdict,
p['KW_WFP_WIDTH'],
value=p['CCF_WIDTH'])
# the rv step
# rvstep = np.abs(loc['RV_CCF'][0] - loc['RV_CCF'][1])
# hdict = spirouImage.AddKey(p, hdict, p['KW_CCF_CDELT'], value=rvstep)
hdict = spirouImage.AddKey(p, hdict, p['KW_WFP_STEP'], value=p['CCF_STEP'])
# add ccf stats
hdict = spirouImage.AddKey(p,
hdict,
p['KW_WFP_DRIFT'],
value=loc['CCF_RES'][1])
hdict = spirouImage.AddKey(p, hdict, p['KW_WFP_FWHM'], value=loc['FWHM'])
hdict = spirouImage.AddKey(p,
hdict,
p['KW_WFP_CONTRAST'],
value=loc['CONTRAST'])
hdict = spirouImage.AddKey(p,
hdict,
p['KW_WFP_MAXCPP'],
value=loc['MAXCPP'])
hdict = spirouImage.AddKey(p, hdict, p['KW_WFP_MASK'], value=p['CCF_MASK'])
hdict = spirouImage.AddKey(p,
hdict,
p['KW_WFP_LINES'],
value=np.nansum(loc['TOT_LINE']))
# write the wave "spectrum"
hdict = spirouImage.AddKey(p, hdict, p['KW_OUTPUT'], value=tag1)
p = spirouImage.WriteImage(p, wavefits, loc['LL_FINAL'], hdict)
# get filename for E2DS calibDB copy of FITSFILENAME
e2dscopy_filename = spirouConfig.Constants.WAVE_E2DS_COPY(p)[0]
wargs = [p['FIBER'], os.path.split(e2dscopy_filename)[-1]]
wmsg = 'Write reference E2DS spectra for Fiber {0} in {1}'
WLOG(p, '', wmsg.format(*wargs))
# make a copy of the E2DS file for the calibBD
p = spirouImage.WriteImage(p, e2dscopy_filename, loc['HCDATA'], hdict)
# only copy over if QC passed
if p['QC']:
# loop around hc files and update header with
for hcfile in p['HCFILES']:
raw_infilepath1 = os.path.join(p['ARG_FILE_DIR'], hcfile)
p = spirouImage.UpdateWaveSolution(p, loc, raw_infilepath1)
# update fp file
raw_infilepath2 = os.path.join(p['ARG_FILE_DIR'], raw_infile2)
p = spirouImage.UpdateWaveSolution(p, loc, raw_infilepath2)
# ------------------------------------------------------------------
# Save to result table
# ------------------------------------------------------------------
# calculate stats for table
final_mean = 1000 * loc['X_MEAN_2']
final_var = 1000 * loc['X_VAR_2']
num_lines = int(np.nansum(loc['X_ITER_2'][:, 2])) # loc['X_ITER_2']
err = 1000 * np.sqrt(loc['X_VAR_2'] / num_lines)
sig_littrow = 1000 * np.array(loc['LITTROW_SIG_' + str(lit_it)])
# construct filename
wavetbl = spirouConfig.Constants.WAVE_TBL_FILE_EA(p)
wavetblname = os.path.basename(wavetbl)
# construct and write table
columnnames = [
'night_name', 'file_name', 'fiber', 'mean', 'rms', 'N_lines', 'err',
'rms_L500', 'rms_L1000', 'rms_L1500', 'rms_L2000', 'rms_L2500',
'rms_L3000', 'rms_L3500'
]
columnformats = [
'{:20s}', '{:30s}', '{:3s}', '{:7.4f}', '{:6.2f}', '{:3d}', '{:6.3f}',
'{:6.2f}', '{:6.2f}', '{:6.2f}', '{:6.2f}', '{:6.2f}', '{:6.2f}',
'{:6.2f}'
]
columnvalues = [[p['ARG_NIGHT_NAME']], [p['ARG_FILE_NAMES'][0]],
[p['FIBER']], [final_mean], [final_var],
[num_lines], [err], [sig_littrow[0]], [sig_littrow[1]],
[sig_littrow[2]], [sig_littrow[3]], [sig_littrow[4]],
[sig_littrow[5]], [sig_littrow[6]]]
# make table
table = spirouImage.MakeTable(p,
columns=columnnames,
values=columnvalues,
formats=columnformats)
# merge table
wmsg = 'Global result summary saved in {0}'
WLOG(p, '', wmsg.format(wavetblname))
spirouImage.MergeTable(p, table, wavetbl, fmt='ascii.rst')
# ----------------------------------------------------------------------
# Save resolution and line profiles to file
# ----------------------------------------------------------------------
raw_infile = os.path.basename(p['FITSFILENAME'])
# get wave filename
resfits, tag3 = spirouConfig.Constants.WAVE_RES_FILE_EA(p)
resfitsname = os.path.basename(resfits)
WLOG(p, '', 'Saving wave resmap to {0}'.format(resfitsname))
# make a copy of the E2DS file for the calibBD
# set the version
hdict = spirouImage.AddKey(p, hdict, p['KW_VERSION'])
hdict = spirouImage.AddKey(p, hdict, p['KW_DRS_DATE'], value=p['DRS_DATE'])
hdict = spirouImage.AddKey(p, hdict, p['KW_DATE_NOW'], value=p['DATE_NOW'])
hdict = spirouImage.AddKey(p, hdict, p['KW_OUTPUT'], value=tag3)
# get res data in correct format
resdata, hdicts = spirouTHORCA.GenerateResFiles(p, loc, hdict)
# save to file
p = spirouImage.WriteImageMulti(p, resfits, resdata, hdicts=hdicts)
# ------------------------------------------------------------------
# Save line list table file
# ------------------------------------------------------------------
# construct filename
# TODO proper column values
wavelltbl = spirouConfig.Constants.WAVE_LINE_FILE_EA(p)
wavelltblname = os.path.split(wavelltbl)[-1]
# construct and write table
columnnames = ['order', 'll', 'dv', 'w', 'xi', 'xo', 'dvdx']
columnformats = [
'{:.0f}', '{:12.4f}', '{:13.5f}', '{:12.4f}', '{:12.4f}', '{:12.4f}',
'{:8.4f}'
]
columnvalues = []
# construct column values (flatten over orders)
for it in range(len(loc['X_DETAILS_2'])):
for jt in range(len(loc['X_DETAILS_2'][it][0])):
row = [
float(it), loc['X_DETAILS_2'][it][0][jt],
loc['LL_DETAILS_2'][it][0][jt], loc['X_DETAILS_2'][it][3][jt],
loc['X_DETAILS_2'][it][1][jt], loc['X_DETAILS_2'][it][2][jt],
loc['SCALE_2'][it][jt]
]
columnvalues.append(row)
# log saving
wmsg = 'List of lines used saved in {0}'
WLOG(p, '', wmsg.format(wavelltblname))
# make table
columnvalues = np.array(columnvalues).T
table = spirouImage.MakeTable(p,
columns=columnnames,
values=columnvalues,
formats=columnformats)
# write table
spirouImage.WriteTable(p, table, wavelltbl, fmt='ascii.rst')
# ------------------------------------------------------------------
# Move to calibDB and update calibDB
# ------------------------------------------------------------------
if p['QC']:
# set the wave key
keydb = 'WAVE_{0}'.format(p['FIBER'])
# copy wave file to calibDB folder
spirouDB.PutCalibFile(p, wavefits)
# update the master calib DB file with new key
spirouDB.UpdateCalibMaster(p, keydb, wavefitsname, loc['HCHDR'])
# set the hcref key
keydb = 'HCREF_{0}'.format(p['FIBER'])
# copy wave file to calibDB folder
spirouDB.PutCalibFile(p, e2dscopy_filename)
# update the master calib DB file with new key
e2dscopyfits = os.path.split(e2dscopy_filename)[-1]
spirouDB.UpdateCalibMaster(p, keydb, e2dscopyfits, loc['HCHDR'])
# ----------------------------------------------------------------------
# End Message
# ----------------------------------------------------------------------
p = spirouStartup.End(p)
# return p and loc
return dict(locals())
def main(directory=None):
# ----------------------------------------------------------------------
# Set up
# ----------------------------------------------------------------------
# get parameters from config files/run time args/load paths + calibdb
p = spirouStartup.Begin(recipe=__NAME__)
# deal with arguments being None (i.e. get from sys.argv)
pos = [0]
fmt = [str, str]
names = ['directory']
call = [directory]
# now get custom arguments
customargs = spirouStartup.GetCustomFromRuntime(p,
pos,
fmt,
names,
calls=call,
require_night_name=False)
p = spirouStartup.LoadArguments(p,
customargs=customargs,
require_night_name=False)
# ----------------------------------------------------------------------
# Check if we have an index file
# ----------------------------------------------------------------------
# get expected index file name and location
index_file = spirouConfig.Constants.INDEX_OUTPUT_FILENAME()
path = p['DIRECTORY']
index_path = os.path.join(path, index_file)
# get expected columns
columns = spirouConfig.Constants.GEN_OUTPUT_COLUMNS(p)
# create storage
loc = OrderedDict()
# if file exists then we have some indexed files
if os.path.exists(index_path):
rawloc = spirouImage.ReadFitsTable(p, index_path)
loc['FILENAME'] = list(rawloc['FILENAME'])
loc['LAST_MODIFIED'] = list(rawloc['LAST_MODIFIED'])
for col in columns:
if col not in rawloc.keys():
WLOG(p, '', '\t- Skipping column {0}'.format(col))
loc[col] = list(np.repeat([''], len(loc['FILENAME'])))
else:
loc[col] = list(rawloc[col])
# else we have to create this file
else:
loc['FILENAME'] = []
loc['LAST_MODIFIED'] = []
# loop around columns and add blank list to each
for col in columns:
loc[col] = []
# ----------------------------------------------------------------------
# Get all files in raw night_name directory
# ----------------------------------------------------------------------
# get all files in DRS_DATA_RAW/ARG_NIGHT_NAME
files = os.listdir(p['DIRECTORY'])
# sort file by name
files = np.sort(files)
# ----------------------------------------------------------------------
# Loop around all files and extract required header keys
# ----------------------------------------------------------------------
# log progress
WLOG(p, '', 'Analysing {0} files'.format(len(files)))
# loop around files and extract properties
for filename in files:
# skip any non-fits file files
if '.fits' not in filename:
continue
# skip the index file
if filename == os.path.basename(index_file):
continue
# skip non-preprocessed files (without .fits)
if p['PROCESSED_SUFFIX'].split('.fits')[0] not in filename:
continue
# if already in loc['FILENAME'] then skip
if filename in loc['FILENAME']:
continue
# construct absolute path for file
fitsfilename = os.path.join(p['DIRECTORY'], filename)
# read file header
hdr = spirouImage.ReadHeader(p, filepath=fitsfilename)
# add filename
loc['FILENAME'].append(filename)
loc['LAST_MODIFIED'].append(os.path.getmtime(fitsfilename))
# loop around columns and look for key in header
for col in columns:
# get value from header
if col in hdr:
value = str(hdr[col])
else:
value = '--'
# push into loc
loc[col].append(value)
# Make sure we have some files
if len(loc['FILENAME']) == 0:
wmsg = 'No pre-processed (*{0}) files present.'
WLOG(p, 'warning', wmsg.format(p['PROCESSED_SUFFIX']))
# ----------------------------------------------------------------------
# archive to table
# ----------------------------------------------------------------------
if len(loc['FILENAME']) != 0:
# construct table filename
outfile = spirouConfig.Constants.OFF_LISTING_RAW_FILE(p)
# log progress
WLOG(p, '', 'Creating ascii file for listing.')
# get column names
colnames = ['FILENAME', 'LAST_MODIFIED'] + list(columns)
# define the format for each column
formats = [None] * len(colnames)
# get the values for each column
values = []
for col in colnames:
values.append(loc[col])
# construct astropy table from column names, values and formats
table = spirouImage.MakeTable(p, colnames, values, formats)
# log saving of file
wmsg = 'Listing of directory on file {0}'
WLOG(p, '', wmsg.format(outfile))
# print out to screen
WLOG('', '', '')
WLOG('', '', 'Listing table:')
WLOG('', '', '')
spirouImage.PrintTable(table)
# ----------------------------------------------------------------------
# Update Index
# ----------------------------------------------------------------------
# ask whether to update index
question = 'Update/Write index.fits? [Y]es or [N]o'
cond = spirouStartup.spirouStartup.spirou_input_yes_no(p, question)
# if cond is True can update
if cond:
# log writing index file
wmsg = 'Writing index to file {0}'
WLOG(p, '', wmsg.format(index_path))
# update index
spirouStartup.SortSaveOutputs(p, loc, index_path)
else:
WLOG(p, 'warning', 'Skipped writing to index file')
# ----------------------------------------------------------------------
# End Message
# ----------------------------------------------------------------------
p = spirouStartup.End(p, outputs=None)
# return a copy of locally defined variables in the memory
return dict(locals())
def main(night_name=None, reffile=None):
"""
cal_DRIFT_E2DS_spirou.py main function, if arguments are None uses
arguments from run time i.e.:
cal_DRIFT_E2DS_spirou.py [night_directory] [reffile]
:param night_name: string or None, the folder within data raw directory
containing files (also reduced directory) i.e.
/data/raw/20170710 would be "20170710" but
/data/raw/AT5/20180409 would be "AT5/20180409"
:param reffile: string, the reference file to use
:return ll: dictionary, containing all the local variables defined in
main
"""
# ----------------------------------------------------------------------
# Set up
# ----------------------------------------------------------------------
# get parameters from config files/run time args/load paths + calibdb
p = spirouStartup.Begin(recipe=__NAME__)
# deal with reference file being None (i.e. get from sys.argv)
if reffile is None:
customargs = spirouStartup.GetCustomFromRuntime(
p, [0], [str], ['reffile'])
else:
customargs = dict(reffile=reffile)
# get parameters from configuration files and run time arguments
p = spirouStartup.LoadArguments(p,
night_name,
customargs=customargs,
mainfitsfile='reffile',
mainfitsdir='reduced')
# ----------------------------------------------------------------------
# Construct reference filename and get fiber type
# ----------------------------------------------------------------------
p, reffilename = spirouStartup.SingleFileSetup(p, filename=p['REFFILE'])
p['REFFILENAME'] = reffilename
p.set_source('REFFILENAME', __NAME__ + '.main()')
# ----------------------------------------------------------------------
# Once we have checked the e2dsfile we can load calibDB
# ----------------------------------------------------------------------
# as we have custom arguments need to load the calibration database
p = spirouStartup.LoadCalibDB(p)
# ----------------------------------------------------------------------
# Read image file
# ----------------------------------------------------------------------
# read the image data
speref, hdr, nbo, nx = spirouImage.ReadData(p, reffilename)
# add to loc
loc = ParamDict()
loc['SPEREF'] = speref
loc['NUMBER_ORDERS'] = nbo
loc.set_sources(['speref', 'number_orders'], __NAME__ + '/main()')
# ----------------------------------------------------------------------
# Get basic image properties for reference file
# ----------------------------------------------------------------------
# get sig det value
p = spirouImage.GetSigdet(p, hdr, name='sigdet')
# get exposure time
p = spirouImage.GetExpTime(p, hdr, name='exptime')
# get gain
p = spirouImage.GetGain(p, hdr, name='gain')
# get acquisition time
p = spirouImage.GetAcqTime(p, hdr, name='acqtime', kind='julian')
bjdref = p['ACQTIME']
# set sigdet and conad keywords (sigdet is changed later)
p['KW_CCD_SIGDET'][1] = p['SIGDET']
p['KW_CCD_CONAD'][1] = p['GAIN']
# ----------------------------------------------------------------------
# Read wavelength solution
# ----------------------------------------------------------------------
# Force A and B to AB solution
if p['FIBER'] in ['A', 'B']:
wave_fiber = 'AB'
else:
wave_fiber = p['FIBER']
# get wave image
wout = spirouImage.GetWaveSolution(p,
hdr=hdr,
fiber=wave_fiber,
return_wavemap=True,
return_filename=True)
_, loc['WAVE'], loc['WAVEFILE'], loc['WSOURCE'] = wout
source = __NAME__ + '/main() + /spirouImage.GetWaveSolution'
loc.set_sources(['WAVE', 'WAVEFILE', 'WSOURCE'], source)
# ----------------------------------------------------------------------
# Read Flat file
# ----------------------------------------------------------------------
# get flat
p, loc['FLAT'] = spirouImage.ReadFlatFile(p, hdr)
loc.set_source('FLAT', __NAME__ + '/main() + /spirouImage.ReadFlatFile')
# get all values in flat that are zero to 1
loc['FLAT'] = np.where(loc['FLAT'] == 0, 1.0, loc['FLAT'])
# ----------------------------------------------------------------------
# Background correction
# ----------------------------------------------------------------------
# log that we are performing background correction
if p['IC_DRIFT_BACK_CORR']:
WLOG(p, '', 'Perform background correction')
# get the box size from constants
bsize = p['DRIFT_PEAK_MINMAX_BOXSIZE']
# Loop around the orders
for order_num in range(loc['NUMBER_ORDERS']):
miny, maxy = spirouBACK.MeasureMinMax(loc['SPEREF'][order_num],
bsize)
loc['SPEREF'][order_num] = loc['SPEREF'][order_num] - miny
# ------------------------------------------------------------------
# Compute photon noise uncertainty for reference file
# ------------------------------------------------------------------
# set up the arguments for DeltaVrms2D
dargs = [loc['SPEREF'], loc['WAVE']]
dkwargs = dict(sigdet=p['IC_DRIFT_NOISE'],
size=p['IC_DRIFT_BOXSIZE'],
threshold=p['IC_DRIFT_MAXFLUX'])
# run DeltaVrms2D
dvrmsref, wmeanref = spirouRV.DeltaVrms2D(*dargs, **dkwargs)
# save to loc
loc['DVRMSREF'], loc['WMEANREF'] = dvrmsref, wmeanref
loc.set_sources(['dvrmsref', 'wmeanref'], __NAME__ + '/main()()')
# log the estimated RV uncertainty
wmsg = 'On fiber {0} estimated RV uncertainty on spectrum is {1:.3f} m/s'
WLOG(p, 'info', wmsg.format(p['FIBER'], wmeanref))
# ------------------------------------------------------------------
# Reference plots
# ------------------------------------------------------------------
if p['DRS_PLOT'] > 0:
# start interactive session if needed
sPlt.start_interactive_session(p)
# plot FP spectral order
sPlt.drift_plot_selected_wave_ref(p, loc)
# plot photon noise uncertainty
sPlt.drift_plot_photon_uncertainty(p, loc)
# ------------------------------------------------------------------
# Get all other files that match kw_OUTPUT and kw_EXT_TYPE from
# ref file
# ------------------------------------------------------------------
# get files
listfiles, listtypes = spirouImage.GetSimilarDriftFiles(p, hdr)
# get the number of files
nfiles = len(listfiles)
# Log the number of files found
wmsgs = [
'Number of files found on directory = {0}'.format(nfiles),
'\tExtensions allowed:'
]
for listtype in listtypes:
wmsgs.append('\t\t - {0}'.format(listtype))
WLOG(p, 'info', wmsgs)
# ------------------------------------------------------------------
# Set up Extract storage for all files
# ------------------------------------------------------------------
# decide whether we need to skip (for large number of files)
if len(listfiles) >= p['DRIFT_NLARGE']:
skip = p['DRIFT_E2DS_FILE_SKIP']
nfiles = int(nfiles / skip)
else:
skip = 1
# set up storage
loc['DRIFT'] = np.zeros((nfiles, loc['NUMBER_ORDERS']))
loc['ERRDRIFT'] = np.zeros((nfiles, loc['NUMBER_ORDERS']))
loc['DELTATIME'] = np.zeros(nfiles)
# set loc sources
keys = ['drift', 'errdrift', 'deltatime']
loc.set_sources(keys, __NAME__ + '/main()()')
# ------------------------------------------------------------------
# Loop around all files: correct for dark, reshape, extract and
# calculate dvrms and meanpond
# ------------------------------------------------------------------
wref = 1
for i_it in range(nfiles):
# get file for this iteration
fpfile = listfiles[::skip][i_it]
# Log the file we are reading
wmsg = 'Reading file {0}'
WLOG(p, '', wmsg.format(os.path.split(fpfile)[-1]))
# ------------------------------------------------------------------
# read e2ds files and get timestamp
# ------------------------------------------------------------------
# read data
rout = spirouImage.ReadData(p, filename=fpfile, log=False)
loc['SPE'], hdri, nxi, nyi = rout
# get acqtime
bjdspe = spirouImage.GetAcqTime(p,
hdri,
name='acqtime',
return_value=1,
kind='julian')
# test whether we want to subtract background
if p['IC_DRIFT_BACK_CORR']:
# Loop around the orders
for order_num in range(loc['NUMBER_ORDERS']):
# get the box size from constants
bsize = p['DRIFT_PEAK_MINMAX_BOXSIZE']
# Measurethe min and max flux
miny, maxy = spirouBACK.MeasureMinMax(loc['SPE'][order_num],
bsize)
# subtract off the background (miny)
loc['SPE'][order_num] = loc['SPE'][order_num] - miny
# ------------------------------------------------------------------
# Compute photon noise uncertainty for iteration file
# ------------------------------------------------------------------
# set up the arguments for DeltaVrms2D
dargs = [loc['SPE'], loc['WAVE']]
dkwargs = dict(sigdet=p['IC_DRIFT_NOISE'],
size=p['IC_DRIFT_BOXSIZE'],
threshold=p['IC_DRIFT_MAXFLUX'])
# run DeltaVrms2D
dvrmsspe, wmodespe = spirouRV.DeltaVrms2D(*dargs, **dkwargs)
# ------------------------------------------------------------------
# Compute the correction of the cosmics and re-normalisation by
# comparison with the reference spectrum
# ------------------------------------------------------------------
# correction of the cosmics and renomalisation by comparison with
# the reference spectrum
dargs = [p, loc['SPEREF'], loc['SPE']]
dkwargs = dict(threshold=p['IC_DRIFT_MAXFLUX'],
size=p['IC_DRIFT_BOXSIZE'],
cut=p['IC_DRIFT_CUT_E2DS'])
spen, cfluxr, cpt = spirouRV.ReNormCosmic2D(*dargs, **dkwargs)
# ------------------------------------------------------------------
# Calculate the RV drift
# ------------------------------------------------------------------
dargs = [loc['SPEREF'], spen, loc['WAVE']]
dkwargs = dict(sigdet=p['IC_DRIFT_NOISE'],
threshold=p['IC_DRIFT_MAXFLUX'],
size=p['IC_DRIFT_BOXSIZE'])
rv = spirouRV.CalcRVdrift2D(*dargs, **dkwargs)
# ------------------------------------------------------------------
# Calculate delta time
# ------------------------------------------------------------------
# calculate the time from reference (in hours)
deltatime = (bjdspe - bjdref) * 24
# ------------------------------------------------------------------
# Calculate RV properties
# ------------------------------------------------------------------
# calculate the mean flux ratio
meanfratio = np.nanmean(cfluxr)
# calculate the weighted mean radial velocity
wref = 1.0 / dvrmsref
meanrv = -1.0 * np.nansum(rv * wref) / np.nansum(wref)
err_meanrv = np.sqrt(dvrmsref + dvrmsspe)
merr = 1. / np.sqrt(np.nansum((1. / err_meanrv)**2))
# Log the RV properties
wmsg = (
'Time from ref={0:.2f} h - Drift mean= {1:.2f} +- {2:.3f} m/s '
'- Flux ratio= {3:.3f} - Nb Comsic= {4}')
WLOG(p, '', wmsg.format(deltatime, meanrv, merr, meanfratio, cpt))
# add this iteration to storage
loc['DRIFT'][i_it] = -1.0 * rv
loc['ERRDRIFT'][i_it] = err_meanrv
loc['DELTATIME'][i_it] = deltatime
# ------------------------------------------------------------------
# Calculate drift properties
# ------------------------------------------------------------------
# get the maximum number of orders to use
nomax = nbo # p['IC_DRIFT_N_ORDER_MAX']
# ------------------------------------------------------------------
# if use mean
if p['DRIFT_TYPE_E2DS'].upper() == 'WEIGHTED MEAN':
# mean radial velocity
sumwref = np.nansum(wref[:nomax])
meanrv = np.nansum(loc['DRIFT'][:, :nomax] * wref[:nomax], 1) / sumwref
# error in mean radial velocity
errdrift2 = loc['ERRDRIFT'][:, :nomax]**2
meanerr = 1.0 / np.sqrt(np.nansum(1.0 / errdrift2, 1))
# add to loc
loc['MDRIFT'] = meanrv
loc['MERRDRIFT'] = meanerr
# else use median
else:
# median drift
loc['MDRIFT'] = np.nanmedian(loc['DRIFT'][:, :nomax], 1)
# median err drift
loc['MERRDRIFT'] = np.nanmedian(loc['ERRDRIFT'][:, :nomax], 1)
# ------------------------------------------------------------------
# set source
loc.set_sources(['mdrift', 'merrdrift'], __NAME__ + '/main()()')
# ------------------------------------------------------------------
# peak to peak drift
driftptp = np.max(loc['MDRIFT']) - np.min(loc['MDRIFT'])
driftrms = np.std(loc['MDRIFT'])
# log th etotal drift peak-to-peak and rms
wmsg = ('Total drift Peak-to-Peak={0:.3f} m/s RMS={1:.3f} m/s in '
'{2:.2f} hour')
wargs = [driftptp, driftrms, np.max(loc['DELTATIME'])]
WLOG(p, '', wmsg.format(*wargs))
# ------------------------------------------------------------------
# Plot of mean drift
# ------------------------------------------------------------------
if p['DRS_PLOT'] > 0:
# start interactive session if needed
sPlt.start_interactive_session(p)
# plot delta time against median drift
sPlt.drift_plot_dtime_against_mdrift(p, loc, kind='e2ds')
# ----------------------------------------------------------------------
# Quality control
# ----------------------------------------------------------------------
# set passed variable and fail message list
passed, fail_msg = True, []
qc_values, qc_names, qc_logic, qc_pass = [], [], [], []
# TODO: Needs doing
# finally log the failed messages and set QC = 1 if we pass the
# quality control QC = 0 if we fail quality control
if passed:
WLOG(p, 'info', 'QUALITY CONTROL SUCCESSFUL - Well Done -')
p['QC'] = 1
p.set_source('QC', __NAME__ + '/main()')
else:
for farg in fail_msg:
wmsg = 'QUALITY CONTROL FAILED: {0}'
WLOG(p, 'warning', wmsg.format(farg))
p['QC'] = 0
p.set_source('QC', __NAME__ + '/main()')
# add to qc header lists
qc_values.append('None')
qc_names.append('None')
qc_logic.append('None')
qc_pass.append(1)
# store in qc_params
qc_params = [qc_names, qc_values, qc_logic, qc_pass]
# ------------------------------------------------------------------
# Save drift values to file
# ------------------------------------------------------------------
# get raw input file name
raw_infile = os.path.basename(p['REFFILE'])
# construct filename
driftfits, tag = spirouConfig.Constants.DRIFT_E2DS_FITS_FILE(p)
driftfitsname = os.path.split(driftfits)[-1]
# log that we are saving drift values
wmsg = 'Saving drift values of Fiber {0} in {1}'
WLOG(p, '', wmsg.format(p['FIBER'], driftfitsname))
# add keys from original header file
hdict = spirouImage.CopyOriginalKeys(hdr)
# set the version
hdict = spirouImage.AddKey(p, hdict, p['KW_VERSION'])
hdict = spirouImage.AddKey(p, hdict, p['KW_DRS_DATE'], value=p['DRS_DATE'])
hdict = spirouImage.AddKey(p, hdict, p['KW_DATE_NOW'], value=p['DATE_NOW'])
hdict = spirouImage.AddKey(p, hdict, p['KW_PID'], value=p['PID'])
hdict = spirouImage.AddKey(p, hdict, p['KW_OUTPUT'], value=tag)
# set the input files
hdict = spirouImage.AddKey(p, hdict, p['KW_CDBFLAT'], value=p['FLATFILE'])
hdict = spirouImage.AddKey(p, hdict, p['KW_REFFILE'], value=raw_infile)
hdict = spirouImage.AddKey(p,
hdict,
p['KW_CDBWAVE'],
value=loc['WAVEFILE'])
hdict = spirouImage.AddKey(p,
hdict,
p['KW_WAVESOURCE'],
value=loc['WSOURCE'])
# add qc parameters
hdict = spirouImage.AddKey(p, hdict, p['KW_DRS_QC'], value=p['QC'])
hdict = spirouImage.AddQCKeys(p, hdict, qc_params)
# save drift values
p = spirouImage.WriteImage(p, driftfits, loc['DRIFT'], hdict)
# ------------------------------------------------------------------
# print .tbl result
# ------------------------------------------------------------------
# construct filename
drifttbl = spirouConfig.Constants.DRIFT_E2DS_TBL_FILE(p)
drifttblname = os.path.split(drifttbl)[-1]
# construct and write table
columnnames = ['time', 'drift', 'drifterr']
columnformats = ['7.4f', '6.2f', '6.3f']
columnvalues = [loc['DELTATIME'], loc['MDRIFT'], loc['MERRDRIFT']]
table = spirouImage.MakeTable(p,
columns=columnnames,
values=columnvalues,
formats=columnformats)
# write table
wmsg = 'Average Drift saved in {0} Saved '
WLOG(p, '', wmsg.format(drifttblname))
spirouImage.WriteTable(p, table, drifttbl, fmt='ascii.rst')
# ----------------------------------------------------------------------
# End Message
# ----------------------------------------------------------------------
p = spirouStartup.End(p)
# return a copy of locally defined variables in the memory
return dict(locals())
def main(night_name=None, reffile=None):
"""
cal_DRIFT_E2DS_spirou.py main function, if arguments are None uses
arguments from run time i.e.:
cal_DRIFT_E2DS_spirou.py [night_directory] [reffile]
:param night_name: string or None, the folder within data raw directory
containing files (also reduced directory) i.e.
/data/raw/20170710 would be "20170710" but
/data/raw/AT5/20180409 would be "AT5/20180409"
:param reffile: string, the reference file to use
:return ll: dictionary, containing all the local variables defined in
main
"""
# ----------------------------------------------------------------------
# Set up
# ----------------------------------------------------------------------
# get parameters from config files/run time args/load paths + calibdb
p = spirouStartup.Begin(recipe=__NAME__)
# deal with reference file being None (i.e. get from sys.argv)
if reffile is None:
customargs = spirouStartup.GetCustomFromRuntime(
p, [0], [str], ['reffile'])
else:
customargs = dict(reffile=reffile)
# get parameters from configuration files and run time arguments
p = spirouStartup.LoadArguments(p,
night_name,
customargs=customargs,
mainfitsfile='reffile',
mainfitsdir='reduced')
# ----------------------------------------------------------------------
# Construct reference filename and get fiber type
# ----------------------------------------------------------------------
p, reffilename = spirouStartup.SingleFileSetup(p, filename=p['REFFILE'])
p['REFFILENAME'] = reffilename
p.set_source('REFFILENAME', __NAME__ + '.main()')
# ----------------------------------------------------------------------
# Once we have checked the e2dsfile we can load calibDB
# ----------------------------------------------------------------------
# as we have custom arguments need to load the calibration database
p = spirouStartup.LoadCalibDB(p)
# ----------------------------------------------------------------------
# Read image file
# ----------------------------------------------------------------------
# read the image data
speref, hdr, nbo, nx = spirouImage.ReadData(p, reffilename)
# add to loc
loc = ParamDict()
loc['SPEREF'] = speref
loc['NUMBER_ORDERS'] = nbo
loc.set_sources(['speref', 'number_orders'], __NAME__ + '/main()')
# ----------------------------------------------------------------------
# Get basic image properties for reference file
# ----------------------------------------------------------------------
# get sig det value
p = spirouImage.GetSigdet(p, hdr, name='sigdet')
# get exposure time
p = spirouImage.GetExpTime(p, hdr, name='exptime')
# get gain
p = spirouImage.GetGain(p, hdr, name='gain')
# get acquisition time
p = spirouImage.GetAcqTime(p, hdr, name='acqtime', kind='julian')
bjdref = p['ACQTIME']
# set sigdet and conad keywords (sigdet is changed later)
p['KW_CCD_SIGDET'][1] = p['SIGDET']
p['KW_CCD_CONAD'][1] = p['GAIN']
# manually set OBJNAME to FP
p['OBJNAME'] = 'FP'
# ----------------------------------------------------------------------
# Earth Velocity calculation
# ----------------------------------------------------------------------
if p['IC_IMAGE_TYPE'] == 'H4RG':
p, loc = spirouImage.GetEarthVelocityCorrection(p, loc, hdr)
# ----------------------------------------------------------------------
# Read wavelength solution
# ----------------------------------------------------------------------
# Force A and B to AB solution
if p['FIBER'] in ['A', 'B']:
wave_fiber = 'AB'
else:
wave_fiber = p['FIBER']
# # get wave image
# wout = spirouImage.GetWaveSolution(p, hdr=hdr, fiber=wave_fiber,
# return_wavemap=True)
# _, loc['WAVE'] = wout
# loc.set_source('WAVE', __NAME__+'/main() + /spirouImage.GetWaveSolution')
# get wave image
wout = spirouImage.GetWaveSolution(p,
hdr=hdr,
return_wavemap=True,
return_filename=True,
fiber=wave_fiber)
param_ll, wave_ll, wavefile, wsource = wout
# save to storage
loc['PARAM_LL'], loc['WAVE_LL'], loc['WAVEFILE'], loc['WSOURCE'] = wout
source = __NAME__ + '/main() + spirouTHORCA.GetWaveSolution()'
loc.set_sources(['WAVE_LL', 'PARAM_LL', 'WAVEFILE', 'WSOURCE'], source)
# ----------------------------------------------------------------------
# Read Flat file
# ----------------------------------------------------------------------
# get flat
p, loc['FLAT'] = spirouImage.ReadFlatFile(p, hdr)
loc.set_source('FLAT', __NAME__ + '/main() + /spirouImage.ReadFlatFile')
# get all values in flat that are zero to 1
loc['FLAT'] = np.where(loc['FLAT'] == 0, 1.0, loc['FLAT'])
# ----------------------------------------------------------------------
# Background correction
# ----------------------------------------------------------------------
# log that we are performing background correction
if p['IC_DRIFT_BACK_CORR']:
WLOG(p, '', 'Perform background correction')
# get the box size from constants
bsize = p['DRIFT_PEAK_MINMAX_BOXSIZE']
# Loop around the orders
for order_num in range(loc['NUMBER_ORDERS']):
miny, maxy = spirouBACK.MeasureMinMax(loc['SPEREF'][order_num],
bsize)
loc['SPEREF'][order_num] = loc['SPEREF'][order_num] - miny
# ----------------------------------------------------------------------
# Preliminary set up = no flat, no blaze
# ----------------------------------------------------------------------
# reset flat to all ones
# loc['FLAT'] = np.ones((nbo, nx))
# set blaze to all ones (if not bug in correlbin !!!
# TODO Check why Blaze makes bugs in correlbin
loc['BLAZE'] = np.ones((nbo, nx))
# set sources
# loc.set_sources(['flat', 'blaze'], __NAME__ + '/main()')
loc.set_sources(['blaze'], __NAME__ + '/main()')
# ------------------------------------------------------------------
# Compute photon noise uncertainty for reference file
# ------------------------------------------------------------------
# set up the arguments for DeltaVrms2D
dargs = [loc['SPEREF'], loc['WAVE_LL']]
dkwargs = dict(sigdet=p['IC_DRIFT_NOISE'],
size=p['IC_DRIFT_BOXSIZE'],
threshold=p['IC_DRIFT_MAXFLUX'])
# run DeltaVrms2D
dvrmsref, wmeanref = spirouRV.DeltaVrms2D(*dargs, **dkwargs)
# save to loc
loc['DVRMSREF'], loc['WMEANREF'] = dvrmsref, wmeanref
loc.set_sources(['dvrmsref', 'wmeanref'], __NAME__ + '/main()()')
# log the estimated RV uncertainty
wmsg = 'On fiber {0} estimated RV uncertainty on spectrum is {1:.3f} m/s'
WLOG(p, 'info', wmsg.format(p['FIBER'], wmeanref))
# ------------------------------------------------------------------
# Reference plots
# ------------------------------------------------------------------
if p['DRS_PLOT'] > 0:
# start interactive session if needed
sPlt.start_interactive_session(p)
# plot FP spectral order
# sPlt.drift_plot_selected_wave_ref(p, loc)
# plot photon noise uncertainty
sPlt.drift_plot_photon_uncertainty(p, loc)
# ----------------------------------------------------------------------
# Get template RV (from ccf_mask)
# ----------------------------------------------------------------------
# Use CCF Mask function with drift constants
p['CCF_MASK'] = p['DRIFT_CCF_MASK']
p['TARGET_RV'] = p['DRIFT_TARGET_RV']
p['CCF_WIDTH'] = p['DRIFT_CCF_WIDTH']
p['CCF_STEP'] = p['DRIFT_CCF_STEP']
# get the CCF mask from file (check location of mask)
loc = spirouRV.GetCCFMask(p, loc)
# check and deal with mask in microns (should be in nm)
if np.mean(loc['LL_MASK_CTR']) < 2.0:
loc['LL_MASK_CTR'] *= 1000.0
loc['LL_MASK_D'] *= 1000.0
# ----------------------------------------------------------------------
# Do correlation
# ----------------------------------------------------------------------
# calculate and fit the CCF
loc['E2DSFF'] = np.array(loc['SPEREF'])
loc.set_source('E2DSFF', __NAME__ + '/main()')
p['CCF_FIT_TYPE'] = 1
# run the RV coravelation function with these parameters
loc = spirouRV.Coravelation(p, loc)
# ----------------------------------------------------------------------
# Correlation stats
# ----------------------------------------------------------------------
# get the maximum number of orders to use
nbmax = p['CCF_NUM_ORDERS_MAX']
# get the average ccf
loc['AVERAGE_CCF'] = np.nansum(loc['CCF'][:nbmax], axis=0)
# normalize the average ccf
normalized_ccf = loc['AVERAGE_CCF'] / np.nanmax(loc['AVERAGE_CCF'])
# get the fit for the normalized average ccf
ccf_res, ccf_fit = spirouRV.FitCCF(p,
loc['RV_CCF'],
normalized_ccf,
fit_type=1)
loc['CCF_RES'] = ccf_res
loc['CCF_FIT'] = ccf_fit
# get the max cpp
loc['MAXCPP'] = np.nansum(loc['CCF_MAX']) / np.nansum(
loc['PIX_PASSED_ALL'])
# get the RV value from the normalised average ccf fit center location
loc['RV'] = float(ccf_res[1])
# get the contrast (ccf fit amplitude)
loc['CONTRAST'] = np.abs(100 * ccf_res[0])
# get the FWHM value
loc['FWHM'] = ccf_res[2] * spirouCore.spirouMath.fwhm()
# ----------------------------------------------------------------------
# set the source
keys = [
'average_ccf', 'maxcpp', 'rv', 'contrast', 'fwhm', 'ccf_res', 'ccf_fit'
]
loc.set_sources(keys, __NAME__ + '/main()')
# ----------------------------------------------------------------------
# log the stats
wmsg = ('Correlation: C={0:.1f}[%] RV={1:.5f}[km/s] '
'FWHM={2:.4f}[km/s] maxcpp={3:.1f}')
wargs = [loc['CONTRAST'], loc['RV'], loc['FWHM'], loc['MAXCPP']]
WLOG(p, 'info', wmsg.format(*wargs))
# get the reference RV in m/s
rvref = loc['RV'] * 1000.
# ----------------------------------------------------------------------
# rv ccf plot
# ----------------------------------------------------------------------
if p['DRS_PLOT'] > 0:
# Plot rv vs ccf (and rv vs ccf_fit)
sPlt.ccf_rv_ccf_plot(p, loc['RV_CCF'], normalized_ccf, ccf_fit)
# ------------------------------------------------------------------
# Get all other files that match kw_OUTPUT and kw_EXT_TYPE from
# ref file
# ------------------------------------------------------------------
# get files
listfiles, listtypes = spirouImage.GetSimilarDriftFiles(p, hdr)
# get the number of files
nfiles = len(listfiles)
# Log the number of files found
wmsgs = [
'Number of files found on directory = {0}'.format(nfiles),
'\tExtensions allowed:'
]
for listtype in listtypes:
wmsgs.append('\t\t - {0}'.format(listtype))
WLOG(p, 'info', wmsgs)
# ------------------------------------------------------------------
# Set up Extract storage for all files
# ------------------------------------------------------------------
# decide whether we need to skip (for large number of files)
if len(listfiles) >= p['DRIFT_NLARGE']:
skip = p['DRIFT_E2DS_FILE_SKIP']
nfiles = int(nfiles / skip)
else:
skip = 1
# set up storage
loc['MDRIFT'] = np.zeros(nfiles)
loc['MERRDRIFT'] = np.zeros(nfiles)
loc['DELTATIME'] = np.zeros(nfiles)
loc['FLUXRATIO'] = np.zeros(nfiles)
# set loc sources
keys = ['mdrift', 'merrdrift', 'deltatime']
loc.set_sources(keys, __NAME__ + '/main()()')
# ------------------------------------------------------------------
# Loop around all files: correct for dark, reshape, extract and
# calculate dvrms and meanpond
# ------------------------------------------------------------------
wref = 1
for i_it in range(nfiles):
# get file for this iteration
fpfile = listfiles[::skip][i_it]
# Log the file we are reading
wmsg = 'Reading file {0}'
WLOG(p, '', wmsg.format(os.path.split(fpfile)[-1]))
# ------------------------------------------------------------------
# read e2ds files and get timestamp
# ------------------------------------------------------------------
# read data
rout = spirouImage.ReadData(p, filename=fpfile, log=False)
loc['SPE'], hdri, nxi, nyi = rout
# get acqtime
bjdspe = spirouImage.GetAcqTime(p,
hdri,
name='acqtime',
return_value=1,
kind='julian')
# test whether we want to subtract background
if p['IC_DRIFT_BACK_CORR']:
# Loop around the orders
for order_num in range(loc['NUMBER_ORDERS']):
# get the box size from constants
bsize = p['DRIFT_PEAK_MINMAX_BOXSIZE']
# Measurethe min and max flux
miny, maxy = spirouBACK.MeasureMinMax(loc['SPE'][order_num],
bsize)
# subtract off the background (miny)
loc['SPE'][order_num] = loc['SPE'][order_num] - miny
# ------------------------------------------------------------------
# calculate flux ratio
# ------------------------------------------------------------------
sorder = p['IC_DRIFT_ORDER_PLOT']
fratio = np.nansum(loc['SPE'][sorder]) / np.nansum(
loc['SPEREF'][sorder])
loc['FLUXRATIO'][i_it] = fratio
# ------------------------------------------------------------------
# Compute photon noise uncertainty for reference file
# ------------------------------------------------------------------
# set up the arguments for DeltaVrms2D
dargs = [loc['SPE'], loc['WAVE_LL']]
dkwargs = dict(sigdet=p['IC_DRIFT_NOISE'],
size=p['IC_DRIFT_BOXSIZE'],
threshold=p['IC_DRIFT_MAXFLUX'])
# run DeltaVrms2D
dvrmsspe, wmeanspe = spirouRV.DeltaVrms2D(*dargs, **dkwargs)
# ----------------------------------------------------------------------
# Do correlation
# ----------------------------------------------------------------------
# calculate and fit the CCF
loc['E2DSFF'] = loc['SPE'] * 1.
loc.set_source('E2DSFF', __NAME__ + '/main()')
loc = spirouRV.Coravelation(p, loc)
# ----------------------------------------------------------------------
# Correlation stats
# ----------------------------------------------------------------------
# get the maximum number of orders to use
nbmax = p['CCF_NUM_ORDERS_MAX']
# get the average ccf
loc['AVERAGE_CCF'] = np.nansum(loc['CCF'][:nbmax], axis=0)
# normalize the average ccf
normalized_ccf = loc['AVERAGE_CCF'] / np.nanmax(loc['AVERAGE_CCF'])
# get the fit for the normalized average ccf
ccf_res, ccf_fit = spirouRV.FitCCF(p,
loc['RV_CCF'],
normalized_ccf,
fit_type=1)
# calculate the mean RV
meanrv = ccf_res[1] * 1000. - rvref
# ------------------------------------------------------------------
# Calculate delta time
# ------------------------------------------------------------------
# calculate the time from reference (in hours)
deltatime = (bjdspe - bjdref) * 24
err_meanrv = np.sqrt(dvrmsref + dvrmsspe)
merr = 1. / np.sqrt(np.nansum((1. / err_meanrv)**2))
# Log the RV properties
wmsg = ('Time from ref= {0:.2f} h '
'- Flux Ratio= {1:.2f} '
'- Drift mean= {2:.2f} +- '
'{3:.2f} m/s')
wargs = [deltatime, loc['FLUXRATIO'][i_it], meanrv, merr]
WLOG(p, '', wmsg.format(*wargs))
# add this iteration to storage
loc['MDRIFT'][i_it] = meanrv
loc['MERRDRIFT'][i_it] = merr
loc['DELTATIME'][i_it] = deltatime
# ------------------------------------------------------------------
# set source
loc.set_sources(['mdrift', 'merrdrift'], __NAME__ + '/main()()')
# ------------------------------------------------------------------
# peak to peak drift
driftptp = np.max(loc['MDRIFT']) - np.min(loc['MDRIFT'])
driftrms = np.std(loc['MDRIFT'])
# log th etotal drift peak-to-peak and rms
wmsg = ('Total drift Peak-to-Peak={0:.3f} m/s RMS={1:.3f} m/s in '
'{2:.2f} hour')
wargs = [driftptp, driftrms, np.max(loc['DELTATIME'])]
WLOG(p, '', wmsg.format(*wargs))
# ------------------------------------------------------------------
# Plot of mean drift
# ------------------------------------------------------------------
if p['DRS_PLOT'] > 0:
# start interactive session if needed
sPlt.start_interactive_session(p)
# plot delta time against median drift
sPlt.drift_plot_dtime_against_mdrift(p, loc, kind='e2ds')
# ------------------------------------------------------------------
# Save drift values to file
# ------------------------------------------------------------------
# # get raw input file name
# raw_infile = os.path.basename(p['REFFILE'])
# # construct filename
# driftfits, tag = spirouConfig.Constants.DRIFTCCF_E2DS_FITS_FILE(p)
# driftfitsname = os.path.split(driftfits)[-1]
# # log that we are saving drift values
# wmsg = 'Saving drift values of Fiber {0} in {1}'
# WLOG(p, '', wmsg.format(p['FIBER'], driftfitsname))
# # add keys from original header file
# hdict = spirouImage.CopyOriginalKeys(hdr)
# # add the reference RV
# hdict = spirouImage.AddKey(p, hdict, p['KW_REF_RV'], value=rvref)
#
# # set the version
# hdict = spirouImage.AddKey(p, hdict, p['KW_VERSION'])
# hdict = spirouImage.AddKey(p, hdict, p['KW_OUTPUT'], value=tag)
# # set the input files
# hdict = spirouImage.AddKey(p, hdict, p['KW_CDBFLAT'], value=p['FLATFILE'])
# hdict = spirouImage.AddKey(p, hdict, p['KW_REFFILE'], value=raw_infile)
# # save drift values
# p = spirouImage.WriteImage(p, driftfits, loc['DRIFT'], hdict)
# ------------------------------------------------------------------
# print .tbl result
# ------------------------------------------------------------------
# construct filename
drifttbl = spirouConfig.Constants.DRIFTCCF_E2DS_TBL_FILE(p)
drifttblname = os.path.split(drifttbl)[-1]
# construct and write table
columnnames = ['time', 'drift', 'drifterr']
columnformats = ['7.4f', '6.2f', '6.3f']
columnvalues = [loc['DELTATIME'], loc['MDRIFT'], loc['MERRDRIFT']]
table = spirouImage.MakeTable(p,
columns=columnnames,
values=columnvalues,
formats=columnformats)
# write table
wmsg = 'Average Drift saved in {0} Saved '
WLOG(p, '', wmsg.format(drifttblname))
spirouImage.WriteTable(p, table, drifttbl, fmt='ascii.rst')
# ----------------------------------------------------------------------
# End Message
# ----------------------------------------------------------------------
p = spirouStartup.End(p)
# return a copy of locally defined variables in the memory
return dict(locals())
def main(cores=1, objects=None, filetype='EXT_E2DS_FF_AB'):
# ----------------------------------------------------------------------
# Set up
# ----------------------------------------------------------------------
# set up function name
main_name = __NAME__ + '.main()'
# get parameters from config files/run time args/load paths + calibdb
p = spirouStartup.Begin(recipe=__NAME__)
# now get custom arguments
pos, fmt = [0, 1, 2], [int, str, str]
names = ['cores', 'objects', 'filetype']
call = [cores, objects, filetype]
required = [False, False, False]
customargs = spirouStartup.GetCustomFromRuntime(p,
pos,
fmt,
names,
calls=call,
required=required,
require_night_name=False)
p = spirouStartup.LoadArguments(p,
None,
customargs=customargs,
mainfitsdir='reduced',
require_night_name=False)
# keep track of errors
errors = []
# -------------------------------------------------------------------------
# find all objects (matching 'objects' if not None)
target_list = spirouTelluric.FindObjects(p)
# print number found
nfound = len(target_list)
nstar = 0
for target in list(target_list.keys()):
nstar += len(target_list[target])
wmsg = 'Found target "{0}" ({1} observations total)'
WLOG(p, 'info', wmsg.format(target, len(target_list[target])))
# list total found
wmsg = 'Found {0} observations total for {1} object(s)'
WLOG(p, 'info', wmsg.format(nstar, nfound))
# -------------------------------------------------------------------------
# Step 1: Run fit_tellu on all objects
# -------------------------------------------------------------------------
# for t_it, target in enumerate(list(target_list.keys())):
# # loop around object filenames
# for o_it, objfilename in enumerate(target_list[target]):
# # Log progress
# pargs = [p, 'Fit Tellurics', target, t_it, nfound,
# o_it, len(target_list[target])]
# spirouTelluric.UpdateProcessDB(*pargs)
# # get arguments from filename
# args = spirouTelluric.GetDBarguments(p, objfilename)
# # run obj_mk_tellu
# try:
# obj_fit_tellu.main(**args)
# except SystemExit as e:
# errors.append([pargs[1], objfilename, e])
# # force close all plots
# sPlt.closeall()
# -------------------------------------------------------------------------
# Step 2: Run mk_obj_template on each science target
# -------------------------------------------------------------------------
for t_it, target in enumerate(list(target_list.keys())):
# log progress (big)
pmsg = 'Make Telluric Template: Processing object = {0} ({1}/{2}'
wmsgs = [
'', '=' * 60, '',
pmsg.format(target, t_it + 1, nfound), '', '=' * 60, ''
]
WLOG(p, 'info', wmsgs, wrap=False)
# get last object
objfilename = target_list[target][-1]
# get arguments from filename
args = spirouTelluric.GetDBarguments(p, objfilename)
# run obj_mk_obj_template
try:
obj_mk_obj_template.main(**args)
except SystemExit as e:
errors.append(['Telluric Template', target, e])
# force close all plots
sPlt.closeall()
# -------------------------------------------------------------------------
# Step 3: Re-Run fit_tellu on all objects
# -------------------------------------------------------------------------
for t_it, target in enumerate(list(target_list.keys())):
# loop around object filenames
for o_it, objfilename in enumerate(target_list[target]):
# Log progress
pargs = [
p, 'Fit Tellurics II', target, t_it, nfound, o_it,
len(target_list[target])
]
spirouTelluric.UpdateProcessDB(*pargs)
# get arguments from filename
args = spirouTelluric.GetDBarguments(p, objfilename)
# run obj_mk_tellu
try:
obj_fit_tellu.main(**args)
except SystemExit as e:
errors.append([pargs[1], objfilename, e])
# force close all plots
sPlt.closeall()
# -------------------------------------------------------------------------
# Step 4: Re-Run mk_obj_template on each science target
# -------------------------------------------------------------------------
for t_it, target in enumerate(list(target_list.keys())):
# log progress (big)
pmsg = 'Make Telluric Template II: Processing object = {0} ({1}/{2}'
wmsgs = [
'', '=' * 60, '',
pmsg.format(target, t_it + 1, nfound), '', '=' * 60, ''
]
WLOG(p, 'info', wmsgs, wrap=False)
# get last object
objfilename = target_list[target][-1]
# get arguments from filename
args = spirouTelluric.GetDBarguments(p, objfilename)
# run obj_mk_obj_template
try:
obj_mk_obj_template.main(**args)
except SystemExit as e:
errors.append(['Telluric Template', target, e])
# force close all plots
sPlt.closeall()
# ----------------------------------------------------------------------
# Print all errors
# ----------------------------------------------------------------------
if len(errors) > 0:
emsgs = ['', '=' * 50, 'Errors were as follows: ']
# loop around errors
for error in errors:
emsgs.append('')
emsgs.append('{0}: Object = {1}'.format(error[0], error[1]))
emsgs.append('\t{0}'.format(error[2]))
emsgs.append('')
WLOG(p, 'error', emsgs)
# ----------------------------------------------------------------------
# End Message
# ----------------------------------------------------------------------
p = spirouStartup.End(p)
# return a copy of locally defined variables in the memory
return dict(locals())
def main(cores=1, filetype='EXT_E2DS_FF_AB'):
# ----------------------------------------------------------------------
# Set up
# ----------------------------------------------------------------------
# set up function name
main_name = __NAME__ + '.main()'
# get parameters from config files/run time args/load paths + calibdb
p = spirouStartup.Begin(recipe=__NAME__)
# now get custom arguments
pos, fmt = [0, 1], [int, str]
names, call = ['cores', 'filetype'], [cores, filetype]
customargs = spirouStartup.GetCustomFromRuntime(p,
pos,
fmt,
names,
calls=call,
require_night_name=False)
p = spirouStartup.LoadArguments(p,
None,
customargs=customargs,
mainfitsdir='reduced',
require_night_name=False)
# -------------------------------------------------------------------------
# find all telluric stars
telluric_stars = spirouTelluric.FindTelluricStars(p)
# print number found
nfound = len(telluric_stars)
nstar = 0
for tell_star in list(telluric_stars.keys()):
nstar += len(telluric_stars[tell_star])
wmsg = 'Found {0} Telluric stars ({1} observations total)'
WLOG(p, 'info', wmsg.format(nfound, nstar))
# # -------------------------------------------------------------------------
# # Step 0: Reset telluric database
# # -------------------------------------------------------------------------
# #reset = spirouTools.drs_reset.reset_confirmation(p, 'TelluDB')
# reset = True
# if reset:
# spirouTools.drs_reset.reset_telludb(p, False)
# keep track of errors
errors = []
# -------------------------------------------------------------------------
# Step 1: Run mk_tellu on all telluric stars
# -------------------------------------------------------------------------
for t_it, tell_star in enumerate(list(telluric_stars.keys())):
# loop around object filenames
for o_it, objfilename in enumerate(telluric_stars[tell_star]):
# Log progress
pargs = [
p, 'Make Tellurics I', tell_star, t_it, nfound, o_it,
len(telluric_stars[tell_star])
]
spirouTelluric.UpdateProcessDB(*pargs)
# get arguments from filename
args = spirouTelluric.GetDBarguments(p, objfilename)
# run obj_mk_tellu
try:
ll = obj_mk_tellu.main(**args)
except SystemExit as e:
errors.append([pargs[1], objfilename, e])
# force close all plots
sPlt.closeall()
# -------------------------------------------------------------------------
# Step 2: Run fit tellu on all telluric stars
# -------------------------------------------------------------------------
for t_it, tell_star in enumerate(list(telluric_stars.keys())):
# loop around object filenames
for o_it, objfilename in enumerate(telluric_stars[tell_star]):
# Log progress
pargs = [
p, 'Fit Tellurics', tell_star, t_it, nfound, o_it,
len(telluric_stars[tell_star])
]
spirouTelluric.UpdateProcessDB(*pargs)
# get arguments from filename
args = spirouTelluric.GetDBarguments(p, objfilename)
# run obj_mk_tellu
try:
obj_fit_tellu.main(**args)
except SystemExit as e:
errors.append([pargs[1], objfilename, e])
# force close all plots
sPlt.closeall()
# -------------------------------------------------------------------------
# step 3: Run mk_obj_template on each telluric star obj name
# -------------------------------------------------------------------------
for t_it, tell_star in enumerate(list(telluric_stars.keys())):
# log progress (big)
pmsg = 'Make Telluric Template: Processing object = {0} ({1}/{2}'
wmsgs = [
'', '=' * 60, '',
pmsg.format(tell_star, t_it + 1, nfound), '', '=' * 60, ''
]
WLOG(p, 'info', wmsgs, wrap=False)
# get last object
objfilename = telluric_stars[tell_star][-1]
# get arguments from filename
args = spirouTelluric.GetDBarguments(p, objfilename)
# run obj_mk_obj_template
try:
obj_mk_obj_template.main(**args)
except SystemExit as e:
errors.append(['Telluric Template', tell_star, e])
# force close all plots
sPlt.closeall()
# -------------------------------------------------------------------------
# step 4: Run mk_tellu on all telluric stars
# -------------------------------------------------------------------------
for t_it, tell_star in enumerate(list(telluric_stars.keys())):
# loop around object filenames
for o_it, objfilename in enumerate(telluric_stars[tell_star]):
# Log progress
pargs = [
p, 'Make Tellurics II', tell_star, t_it, nfound, o_it,
len(telluric_stars[tell_star])
]
spirouTelluric.UpdateProcessDB(*pargs)
# get arguments from filename
args = spirouTelluric.GetDBarguments(p, objfilename)
# run obj_mk_tellu
try:
obj_mk_tellu.main(**args)
except SystemExit as e:
errors.append([pargs[1], objfilename, e])
# force close all plots
sPlt.closeall()
# ----------------------------------------------------------------------
# Print all errors
# ----------------------------------------------------------------------
if len(errors) > 0:
emsgs = ['', '=' * 50, 'Errors were as follows: ']
# loop around errors
for error in errors:
emsgs.append('')
emsgs.append('{0}: Object = {1}'.format(error[0], error[1]))
emsgs.append('\t{0}'.format(error[2]))
emsgs.append('')
WLOG(p, 'error', emsgs)
# ----------------------------------------------------------------------
# End Message
# ----------------------------------------------------------------------
p = spirouStartup.End(p)
# return a copy of locally defined variables in the memory
return dict(locals())
def main(night_name=None, fpfile=None, hcfiles=None):
# ----------------------------------------------------------------------
# Set up
# ----------------------------------------------------------------------
# get parameters from config files/run time args/load paths + calibdb
p = spirouStartup.Begin(recipe=__NAME__)
if hcfiles is None or fpfile is None:
names, types = ['fpfile', 'hcfiles'], [str, str]
customargs = spirouStartup.GetCustomFromRuntime(p, [0, 1],
types,
names,
last_multi=True)
else:
customargs = dict(hcfiles=hcfiles, fpfile=fpfile)
# get parameters from configuration files and run time arguments
p = spirouStartup.LoadArguments(p,
night_name,
customargs=customargs,
mainfitsdir='reduced',
mainfitsfile='hcfiles')
# ----------------------------------------------------------------------
# Construct reference filename and get fiber type
# ----------------------------------------------------------------------
p, fpfitsfilename = spirouStartup.SingleFileSetup(p, filename=p['FPFILE'])
fiber1 = str(p['FIBER'])
p, hcfilenames = spirouStartup.MultiFileSetup(p, files=p['HCFILES'])
fiber2 = str(p['FIBER'])
# set the hcfilename to the first hcfilenames
hcfitsfilename = hcfilenames[0]
# ----------------------------------------------------------------------
# Once we have checked the e2dsfile we can load calibDB
# ----------------------------------------------------------------------
# as we have custom arguments need to load the calibration database
p = spirouStartup.LoadCalibDB(p)
# ----------------------------------------------------------------------
# Have to check that the fibers match
# ----------------------------------------------------------------------
if fiber1 == fiber2:
p['FIBER'] = fiber1
fsource = __NAME__ + '/main() & spirouStartup.GetFiberType()'
p.set_source('FIBER', fsource)
else:
emsg = 'Fiber not matching for {0} and {1}, should be the same'
eargs = [hcfitsfilename, fpfitsfilename]
WLOG(p, 'error', emsg.format(*eargs))
# set the fiber type
p['FIB_TYP'] = [p['FIBER']]
p.set_source('FIB_TYP', __NAME__ + '/main()')
# set find line mode
find_lines_mode = p['HC_FIND_LINES_MODE']
# ----------------------------------------------------------------------
# Read image file
# ----------------------------------------------------------------------
# read and combine all HC files except the first (fpfitsfilename)
rargs = [p, 'add', hcfitsfilename, hcfilenames[1:]]
p, hcdata, hchdr = spirouImage.ReadImageAndCombine(*rargs)
# read first file (fpfitsfilename)
fpdata, fphdr, _, _ = spirouImage.ReadImage(p, fpfitsfilename)
# add data and hdr to loc
loc = ParamDict()
loc['HCDATA'], loc['HCHDR'] = hcdata, hchdr
loc['FPDATA'], loc['FPHDR'] = fpdata, fphdr
# set the source
sources = ['HCDATA', 'HCHDR']
loc.set_sources(sources, 'spirouImage.ReadImageAndCombine()')
sources = ['FPDATA', 'FPHDR']
loc.set_sources(sources, 'spirouImage.ReadImage()')
# ----------------------------------------------------------------------
# Get basic image properties for reference file
# ----------------------------------------------------------------------
# get sig det value
p = spirouImage.GetSigdet(p, hchdr, name='sigdet')
# get exposure time
p = spirouImage.GetExpTime(p, hchdr, name='exptime')
# get gain
p = spirouImage.GetGain(p, hchdr, name='gain')
# get acquisition time
p = spirouImage.GetAcqTime(p, hchdr, name='acqtime', kind='julian')
bjdref = p['ACQTIME']
# set sigdet and conad keywords (sigdet is changed later)
p['KW_CCD_SIGDET'][1] = p['SIGDET']
p['KW_CCD_CONAD'][1] = p['GAIN']
# get lamp parameters
p = spirouTHORCA.GetLampParams(p, hchdr)
# ----------------------------------------------------------------------
# Obtain the flat
# ----------------------------------------------------------------------
# get the flat
p, loc = spirouFLAT.GetFlat(p, loc, hchdr)
# ----------------------------------------------------------------------
# Read blaze
# ----------------------------------------------------------------------
# get tilts
p, loc['BLAZE'] = spirouImage.ReadBlazeFile(p, hchdr)
loc.set_source('BLAZE', __NAME__ + '/main() + /spirouImage.ReadBlazeFile')
# correct the data with the flat
# TODO: Should this be used?
# log
# WLOG(p, '', 'Applying flat correction')
# loc['HCDATA'] = loc['HCDATA']/loc['FLAT']
# loc['FPDATA'] = loc['FPDATA']/loc['FLAT']
# ----------------------------------------------------------------------
# Start plotting session
# ----------------------------------------------------------------------
if p['DRS_PLOT'] > 0:
# start interactive plot
sPlt.start_interactive_session(p)
# ----------------------------------------------------------------------
# loop around fiber type
# ----------------------------------------------------------------------
for fiber in p['FIB_TYP']:
# set fiber type for inside loop
p['FIBER'] = fiber
# ------------------------------------------------------------------
# Instrumental drift computation (if previous solution exists)
# ------------------------------------------------------------------
# get key
keydb = 'HCREF_{0}'.format(p['FIBER'])
# check for key in calibDB
if keydb in p['CALIBDB'].keys():
# log process
wmsg = ('Doing Instrumental drift computation from previous '
'calibration')
WLOG(p, '', wmsg)
# calculate instrument drift
loc = spirouTHORCA.CalcInstrumentDrift(p, loc)
# ------------------------------------------------------------------
# Wave solution
# ------------------------------------------------------------------
# log message for loop
wmsg = 'Processing Wavelength Calibration for Fiber {0}'
WLOG(p, 'info', wmsg.format(p['FIBER']))
# ------------------------------------------------------------------
# Part 1 of cal_HC
# ------------------------------------------------------------------
p, loc = cal_HC_E2DS_spirou.part1(p, loc, mode=find_lines_mode)
# ------------------------------------------------------------------
# FP solution
# ------------------------------------------------------------------
# log message
wmsg = 'Calculating FP wave solution'
WLOG(p, '', wmsg)
# calculate FP wave solution
# spirouTHORCA.FPWaveSolution(p, loc, mode=find_lines_mode)
spirouTHORCA.FPWaveSolutionNew(p, loc)
# ------------------------------------------------------------------
# FP solution plots
# ------------------------------------------------------------------
if p['DRS_PLOT'] > 0:
# Plot the FP extracted spectrum against wavelength solution
sPlt.wave_plot_final_fp_order(p, loc, iteration=1)
# Plot the measured FP cavity width offset against line number
sPlt.wave_local_width_offset_plot(p, loc)
# Plot the FP line wavelength residuals
sPlt.wave_fp_wavelength_residuals(p, loc)
# ------------------------------------------------------------------
# Part 2 of cal_HC
# ------------------------------------------------------------------
# set params for part2
p['QC_RMS_LITTROW_MAX'] = p['QC_WAVE_RMS_LITTROW_MAX']
p['QC_DEV_LITTROW_MAX'] = p['QC_WAVE_DEV_LITTROW_MAX']
p['IC_HC_N_ORD_START_2'] = min(p['IC_HC_N_ORD_START_2'],
p['IC_FP_N_ORD_START'])
p['IC_HC_N_ORD_FINAL_2'] = max(p['IC_HC_N_ORD_FINAL_2'],
p['IC_FP_N_ORD_FINAL'])
# run part 2
# p, loc = part2test(p, loc)
p, loc = cal_HC_E2DS_spirou.part2(p, loc)
# ----------------------------------------------------------------------
# End plotting session
# ----------------------------------------------------------------------
# end interactive session
sPlt.end_interactive_session(p)
# ----------------------------------------------------------------------
# End Message
# ----------------------------------------------------------------------
p = spirouStartup.End(p)
# return a copy of locally defined variables in the memory
return dict(locals())
def main(night_name=None, e2dsfiles=None):
"""
cal_CCF_E2DS_spirou.py main function, if arguments are None uses
arguments from run time i.e.:
cal_CCF_E2DS_spirou.py [night_directory] [E2DSfilename] [mask] [RV]
[width] [step]
:param night_name: string or None, the folder within data raw directory
containing files (also reduced directory) i.e.
/data/raw/20170710 would be "20170710" but
/data/raw/AT5/20180409 would be "AT5/20180409"
:param e2dsfiles: list of string, the E2DS files to use
:return ll: dictionary, containing all the local variables defined in
main
"""
# ----------------------------------------------------------------------
# Set up
# ----------------------------------------------------------------------
# get parameters from config files/run time args/load paths + calibdb
p = spirouStartup.Begin(recipe=__NAME__)
# need custom args (to accept full path or wild card
if e2dsfiles is None:
names, types = ['e2dsfiles'], [str]
customargs = spirouStartup.GetCustomFromRuntime(p, [0],
types,
names,
last_multi=True)
else:
customargs = dict(e2dsfiles=e2dsfiles)
# get parameters from configuration files and run time arguments
p = spirouStartup.LoadArguments(p,
night_name,
customargs=customargs,
mainfitsdir='reduced')
# ----------------------------------------------------------------------
# Process files (including wildcards)
# ----------------------------------------------------------------------
try:
e2dsfiles = spirouFile.Paths(p['E2DSFILES'],
root=p['ARG_FILE_DIR']).abs_paths
except PathException as e:
WLOG(p, 'error', e)
# loop around files
for it, e2dsfile in enumerate(e2dsfiles):
# get the base file name
e2dsfilename = os.path.basename(e2dsfile)
# log the file process
wargs = [e2dsfilename, it + 1, len(e2dsfiles)]
wmsg = ' * Processing file {0} ({1} of {2})'.format(*wargs)
WLOG(p, '', spirouStartup.spirouStartup.HEADER)
WLOG(p, '', wmsg)
WLOG(p, '', spirouStartup.spirouStartup.HEADER)
# ------------------------------------------------------------------
# Check that we can process file
# ------------------------------------------------------------------
# check if ufile exists
if not os.path.exists(e2dsfile):
wmsg = 'File {0} does not exist... skipping'
WLOG(p, 'warning', wmsg.format(e2dsfilename))
continue
elif ('e2ds' not in e2dsfilename) and ('e2dsff' not in e2dsfilename):
wmsg = 'File {0} not a valid E2DS or E2DSFF file'
WLOG(p, 'warning', wmsg.format(e2dsfilename))
continue
elif '.fits' not in e2dsfilename:
wmsg = 'File {0} not a fits file... skipping'
WLOG(p, 'warning', wmsg.format(e2dsfilename))
continue
# ----------------------------------------------------------------------
# Read image file
# ----------------------------------------------------------------------
# read the image data
e2ds, hdr, nbo, nx = spirouImage.ReadData(p, e2dsfile)
# add to loc
loc = ParamDict()
loc['E2DS'] = e2ds
loc['NUMBER_ORDERS'] = nbo
loc.set_sources(['E2DS', 'number_orders'], __NAME__ + '/main()')
# ----------------------------------------------------------------------
# Get basic image properties for reference file
# ----------------------------------------------------------------------
# get sig det value
p = spirouImage.GetSigdet(p, hdr, name='sigdet')
# get exposure time
p = spirouImage.GetExpTime(p, hdr, name='exptime')
# get gain
p = spirouImage.GetGain(p, hdr, name='gain')
# get acquisition time
p = spirouImage.GetAcqTime(p, hdr, name='acqtime', kind='julian')
# ----------------------------------------------------------------------
# Read star parameters
# ----------------------------------------------------------------------
p = spirouImage.ReadParam(p, hdr, 'KW_OBJRA', dtype=str)
p = spirouImage.ReadParam(p, hdr, 'KW_OBJDEC', dtype=str)
p = spirouImage.ReadParam(p, hdr, 'KW_OBJEQUIN')
p = spirouImage.ReadParam(p, hdr, 'KW_OBJRAPM')
p = spirouImage.ReadParam(p, hdr, 'KW_OBJDECPM')
p = spirouImage.ReadParam(p, hdr, 'KW_DATE_OBS', dtype=str)
p = spirouImage.ReadParam(p, hdr, 'KW_UTC_OBS', dtype=str)
# -----------------------------------------------------------------------
# Earth Velocity calculation
# -----------------------------------------------------------------------
if p['IC_IMAGE_TYPE'] == 'H4RG':
loc = spirouImage.EarthVelocityCorrection(p,
loc,
method=p['CCF_BERVMODE'])
else:
loc['BERV'], loc['BJD'] = 0.0, 0.0
loc['BERV_MAX'], loc['BERV_SOURCE'] = 0.0, 'None'
loc.set_sources(['BERV', 'BJD', 'BERV_MAX'], __NAME__ + '.main()')
# ----------------------------------------------------------------------
# archive ccf to fits file
# ----------------------------------------------------------------------
outfilename = str(e2dsfile)
# add keys
hdict = spirouImage.CopyOriginalKeys(hdr)
# add berv values
hdict = spirouImage.AddKey(p, hdict, p['KW_BERV'], value=loc['BERV'])
hdict = spirouImage.AddKey(p, hdict, p['KW_BJD'], value=loc['BJD'])
hdict = spirouImage.AddKey(p,
hdict,
p['KW_BERV_MAX'],
value=loc['BERV_MAX'])
hdict = spirouImage.AddKey(p,
hdict,
p['KW_BERV_SOURCE'],
value=loc['BERV_SOURCE'])
# write image and add header keys (via hdict)
p = spirouImage.WriteImage(p, outfilename, e2ds, hdict)
# ----------------------------------------------------------------------
# End Message
# ----------------------------------------------------------------------
p = spirouStartup.End(p)
# return a copy of locally defined variables in the memory
return dict(locals())
def main(night_name=None, reffile=None):
"""
cal_DRIFTPEAK_E2DS_spirou.py main function, if arguments are None uses
arguments from run time i.e.:
cal_DRIFTPEAK_E2DS_spirou.py [night_directory] [reffile]
:param night_name: string or None, the folder within data raw directory
containing files (also reduced directory) i.e.
/data/raw/20170710 would be "20170710" but
/data/raw/AT5/20180409 would be "AT5/20180409"
:param reffile: string, the reference file to use
:return ll: dictionary, containing all the local variables defined in
main
"""
# ----------------------------------------------------------------------
# Set up
# ----------------------------------------------------------------------
# get parameters from config files/run time args/load paths + calibdb
p = spirouStartup.Begin(recipe=__NAME__)
# deal with reference file being None (i.e. get from sys.argv)
if reffile is None:
customargs = spirouStartup.GetCustomFromRuntime(
p, [0], [str], ['reffile'])
else:
customargs = dict(reffile=reffile)
# get parameters from configuration files and run time arguments
p = spirouStartup.LoadArguments(p,
night_name,
customargs=customargs,
mainfitsfile='reffile',
mainfitsdir='reduced')
# ----------------------------------------------------------------------
# Construct reference filename and get fiber type
# ----------------------------------------------------------------------
p, reffilename = spirouStartup.SingleFileSetup(p, filename=p['REFFILE'])
p['REFFILENAME'] = reffilename
p.set_source('REFFILENAME', __NAME__ + '.main()')
# ----------------------------------------------------------------------
# Once we have checked the e2dsfile we can load calibDB
# ----------------------------------------------------------------------
# as we have custom arguments need to load the calibration database
p = spirouStartup.LoadCalibDB(p)
# ----------------------------------------------------------------------
# Read image file
# ----------------------------------------------------------------------
# read the image data
speref, hdr, nbo, nx = spirouImage.ReadData(p, p['REFFILENAME'])
# add to loc
loc = ParamDict()
loc['SPEREF'] = speref
loc['NUMBER_ORDERS'] = nbo
loc.set_sources(['SPEREF', 'NUMBER_ORDERS'], __NAME__ + '/main()')
# ----------------------------------------------------------------------
# Get lamp type
# ----------------------------------------------------------------------
# get lamp type
if p['KW_EXT_TYPE'][0] in hdr:
ext_type = hdr[p['KW_EXT_TYPE'][0]]
drift_types = p['DRIFT_PEAK_ALLOWED_TYPES'].keys()
found = False
for kind in drift_types:
if ext_type == kind:
loc['LAMP'] = p['DRIFT_PEAK_ALLOWED_TYPES'][kind]
found = True
if not found:
eargs1 = [p['KW_EXT_TYPE'][0], ' or '.join(drift_types)]
emsg1 = (
'Wrong type of image for Drift, header key "{0}" should be'
'{1}'.format(*eargs1))
emsg2 = '\tPlease check DRIFT_PEAK_ALLOWED_TYPES'
WLOG(p, 'error', [emsg1, emsg2])
else:
emsg = 'Header key = "{0}" missing from file {1}'
eargs = [p['KW_EXT_TYPE'][0], p['REFFILENAME']]
WLOG(p, 'error', emsg.format(*eargs))
loc.set_source('LAMP', __NAME__ + '/main()')
# ----------------------------------------------------------------------
# Get basic image properties for reference file
# ----------------------------------------------------------------------
# get sig det value
p = spirouImage.GetSigdet(p, hdr, name='sigdet')
# get exposure time
p = spirouImage.GetExpTime(p, hdr, name='exptime')
# get gain
p = spirouImage.GetGain(p, hdr, name='gain')
# get acquisition time
p = spirouImage.GetAcqTime(p, hdr, name='acqtime', kind='julian')
bjdref = p['ACQTIME']
# set sigdet and conad keywords (sigdet is changed later)
p['KW_CCD_SIGDET'][1] = p['SIGDET']
p['KW_CCD_CONAD'][1] = p['GAIN']
# ----------------------------------------------------------------------
# Read wavelength solution
# ----------------------------------------------------------------------
# Force A and B to AB solution
if p['FIBER'] in ['A', 'B']:
wave_fiber = 'AB'
else:
wave_fiber = p['FIBER']
# get wave image
source = __NAME__ + '/main() + /spirouImage.GetWaveSolution'
wout = spirouImage.GetWaveSolution(p,
hdr=hdr,
return_wavemap=True,
return_filename=True,
fiber=wave_fiber)
_, loc['WAVE'], loc['WAVEFILE'], loc['WSOURCE'] = wout
loc.set_sources(['WAVE', 'WAVEFILE', 'WSOURCE'], source)
# ----------------------------------------------------------------------
# Read Flat file
# ----------------------------------------------------------------------
# get flat
p, loc['FLAT'] = spirouImage.ReadFlatFile(p, hdr)
loc.set_source('FLAT', __NAME__ + '/main() + /spirouImage.ReadFlatFile')
# get all values in flat that are zero to 1
loc['FLAT'] = np.where(loc['FLAT'] == 0, 1.0, loc['FLAT'])
# correct for flat file
loc['SPEREF'] = loc['SPEREF'] / loc['FLAT']
# ----------------------------------------------------------------------
# Background correction
# ----------------------------------------------------------------------
# test whether we want to subtract background
if p['IC_DRIFT_BACK_CORR']:
# Loop around the orders
for order_num in range(loc['NUMBER_ORDERS']):
# get the box size from constants
bsize = p['DRIFT_PEAK_MINMAX_BOXSIZE']
# Measurethe min and max flux
miny, maxy = spirouBACK.MeasureMinMax(loc['SPEREF'][order_num],
bsize)
# subtract off the background (miny)
loc['SPEREF'][order_num] = loc['SPEREF'][order_num] - miny
# ----------------------------------------------------------------------
# Identify FP peaks in reference file
# ----------------------------------------------------------------------
# log that we are identifying peaks
wmsg = 'Identification of lines in reference file: {0}'
WLOG(p, '', wmsg.format(p['REFFILE']))
# get the position of FP peaks from reference file
loc = spirouRV.CreateDriftFile(p, loc)
# ----------------------------------------------------------------------
# Removal of suspiciously wide FP lines
# ----------------------------------------------------------------------
loc = spirouRV.RemoveWidePeaks(p, loc)
# ----------------------------------------------------------------------
# Get reference drift
# ----------------------------------------------------------------------
# are we using gaussfit?
gaussfit = p['DRIFT_PEAK_GETDRIFT_GAUSSFIT']
# get drift
loc['XREF'] = spirouRV.GetDrift(p,
loc['SPEREF'],
loc['ORDPEAK'],
loc['XPEAK'],
gaussfit=gaussfit)
loc.set_source('XREF', __NAME__ + '/main()')
# remove any drifts that are zero (i.e. peak not measured
loc = spirouRV.RemoveZeroPeaks(p, loc)
# ------------------------------------------------------------------
# Reference plots
# ------------------------------------------------------------------
if p['DRS_PLOT'] > 0:
# start interactive session if needed
sPlt.start_interactive_session(p)
# plot FP spectral order
sPlt.drift_plot_selected_wave_ref(p, loc)
# ------------------------------------------------------------------
# Get all other files that match kw_OUTPUT and kw_EXT_TYPE from
# ref file
# ------------------------------------------------------------------
# get files
listfiles, listtypes = spirouImage.GetSimilarDriftFiles(p, hdr)
# get the number of files
nfiles = len(listfiles)
# Log the number of files found
wmsgs = [
'Number of files found on directory = {0}'.format(nfiles),
'\tExtensions allowed:'
]
for listtype in listtypes:
wmsgs.append('\t\t - {0}'.format(listtype))
WLOG(p, 'info', wmsgs)
# ------------------------------------------------------------------
# Set up Extract storage for all files
# ------------------------------------------------------------------
# decide whether we need to skip (for large number of files)
if len(listfiles) >= p['DRIFT_NLARGE']:
skip = p['DRIFT_PEAK_FILE_SKIP']
nfiles = int(nfiles / skip)
else:
skip = 1
# set up storage
loc['DRIFT'] = np.zeros((nfiles, loc['NUMBER_ORDERS']))
loc['DRIFT_LEFT'] = np.zeros((nfiles, loc['NUMBER_ORDERS']))
loc['DRIFT_RIGHT'] = np.zeros((nfiles, loc['NUMBER_ORDERS']))
loc['ERRDRIFT'] = np.zeros((nfiles, loc['NUMBER_ORDERS']))
loc['DELTATIME'] = np.zeros(nfiles)
loc['MEANRV'] = np.zeros(nfiles)
loc['MEANRV_LEFT'] = np.zeros(nfiles)
loc['MEANRV_RIGHT'] = np.zeros(nfiles)
loc['MERRDRIFT'] = np.zeros(nfiles)
loc['FLUXRATIO'] = np.zeros(nfiles)
# add sources
source = __NAME__ + '/main()'
keys = [
'drift', 'drift_left', 'drift_right', 'errdrift', 'deltatime',
'meanrv', 'meanrv_left', 'meanrv_right', 'merrdrift', 'fluxratio'
]
loc.set_sources(keys, source)
# ------------------------------------------------------------------
# Loop around all files: correct for dark, reshape, extract and
# calculate dvrms and meanpond
# ------------------------------------------------------------------
# get the maximum number of orders to use
nomin = p['IC_DRIFT_PEAK_N_ORDER_MIN']
nomax = p['IC_DRIFT_PEAK_N_ORDER_MAX']
# loop around files
for i_it in range(nfiles):
# get file for this iteration
fpfile = listfiles[::skip][i_it]
# Log the file we are reading
wmsg = 'Reading file {0}'
WLOG(p, '', wmsg.format(os.path.split(fpfile)[-1]))
# ------------------------------------------------------------------
# read e2ds files and get timestamp
# ------------------------------------------------------------------
# read data
rout = spirouImage.ReadData(p, filename=fpfile, log=False)
loc['SPE'], hdri, nxi, nyi = rout
# apply flat
loc['SPE'] = loc['SPE'] / loc['FLAT']
# get acqtime
bjdspe = spirouImage.GetAcqTime(p,
hdri,
name='acqtime',
return_value=1,
kind='julian')
# ----------------------------------------------------------------------
# Background correction
# ----------------------------------------------------------------------
# test whether we want to subtract background
if p['IC_DRIFT_BACK_CORR']:
# Loop around the orders
for order_num in range(loc['NUMBER_ORDERS']):
# get the box size from constants
bsize = p['DRIFT_PEAK_MINMAX_BOXSIZE']
# Measurethe min and max flux
miny, maxy = spirouBACK.MeasureMinMax(loc['SPE'][order_num],
bsize)
# subtract off the background (miny)
loc['SPE'][order_num] = loc['SPE'][order_num] - miny
# ------------------------------------------------------------------
# calculate flux ratio
# ------------------------------------------------------------------
sorder = p['IC_DRIFT_ORDER_PLOT']
fratio = np.nansum(loc['SPE'][sorder]) / np.nansum(
loc['SPEREF'][sorder])
loc['FLUXRATIO'][i_it] = fratio
# ------------------------------------------------------------------
# Calculate delta time
# ------------------------------------------------------------------
# calculate the time from reference (in hours)
loc['DELTATIME'][i_it] = (bjdspe - bjdref) * 24
# ------------------------------------------------------------------
# Calculate PearsonR coefficient
# ------------------------------------------------------------------
pargs = [loc['NUMBER_ORDERS'], loc['SPE'], loc['SPEREF']]
correlation_coeffs = spirouRV.PearsonRtest(*pargs)
# ----------------------------------------------------------------------
# Get drift with comparison to the reference image
# ----------------------------------------------------------------------
# only calculate drift if the correlation between orders and
# reference file is above threshold
prcut = p['DRIFT_PEAK_PEARSONR_CUT']
if np.min(correlation_coeffs[nomin:nomax]) > prcut:
# get drifts for each order
dargs = [p, loc['SPE'], loc['ORDPEAK'], loc['XREF']]
x = spirouRV.GetDrift(*dargs, gaussfit=gaussfit)
# get delta v
loc['DV'] = (x - loc['XREF']) * loc['VRPEAK']
# sigma clip
loc = spirouRV.SigmaClip(loc, sigma=p['DRIFT_PEAK_SIGMACLIP'])
# work out median drifts per order
loc = spirouRV.DriftPerOrder(loc, i_it)
# work out mean drift across all orders
loc = spirouRV.DriftAllOrders(p, loc, i_it, nomin, nomax)
# log the mean drift
wmsg = ('Time from ref= {0:.2f} h - Flux Ratio= {1:.3f} '
'- Drift mean= {2:.2f} +- {3:.2f} m/s')
wargs = [
loc['DELTATIME'][i_it], loc['FLUXRATIO'][i_it],
loc['MEANRV'][i_it], loc['MERRDRIFT'][i_it]
]
WLOG(p, 'info', wmsg.format(*wargs))
# else we can't use this extract
else:
if p['DRS_PLOT'] > 0:
# start interactive session if needed
sPlt.plt.ioff()
# plot comparison between spe and ref
sPlt.drift_plot_correlation_comp(p, loc, correlation_coeffs,
i_it)
sPlt.plt.show()
sPlt.plt.close()
# turn interactive plotting back on
sPlt.plt.ion()
# log that we cannot use this extraction
wmsg1 = 'The correlation of some orders compared to the template is'
wmsg2 = ' < {0}, something went wrong in the extract.'
WLOG(p, 'warning', wmsg1)
WLOG(p, 'warning', wmsg2.format(prcut))
# ------------------------------------------------------------------
# peak to peak drift
driftptp = np.max(loc['MEANRV']) - np.min(loc['MEANRV'])
driftrms = np.std(loc['MEANRV'])
# log th etotal drift peak-to-peak and rms
wmsg = ('Total drift Peak-to-Peak={0:.3f} m/s RMS={1:.3f} m/s in '
'{2:.2f} hour')
wargs = [driftptp, driftrms, np.max(loc['DELTATIME'])]
WLOG(p, '', wmsg.format(*wargs))
# ------------------------------------------------------------------
# Plot of mean drift
# ------------------------------------------------------------------
if p['DRS_PLOT'] > 0:
# start interactive session if needed
sPlt.start_interactive_session(p)
# plot delta time against median drift
sPlt.drift_peak_plot_dtime_against_drift(p, loc)
# ----------------------------------------------------------------------
# Quality control
# ----------------------------------------------------------------------
# set passed variable and fail message list
passed, fail_msg = True, []
qc_values, qc_names, qc_logic, qc_pass = [], [], [], []
# TODO: Needs doing
# finally log the failed messages and set QC = 1 if we pass the
# quality control QC = 0 if we fail quality control
if passed:
WLOG(p, 'info', 'QUALITY CONTROL SUCCESSFUL - Well Done -')
p['QC'] = 1
p.set_source('QC', __NAME__ + '/main()')
else:
for farg in fail_msg:
wmsg = 'QUALITY CONTROL FAILED: {0}'
WLOG(p, 'warning', wmsg.format(farg))
p['QC'] = 0
p.set_source('QC', __NAME__ + '/main()')
# add to qc header lists
qc_values.append('None')
qc_names.append('None')
qc_logic.append('None')
qc_pass.append(1)
# store in qc_params
qc_params = [qc_names, qc_values, qc_logic, qc_pass]
# ------------------------------------------------------------------
# Save drift values to file
# ------------------------------------------------------------------
# get raw input file name
raw_infile = os.path.basename(p['REFFILE'])
# construct filename
driftfits, tag = spirouConfig.Constants.DRIFTPEAK_E2DS_FITS_FILE(p)
driftfitsname = os.path.split(driftfits)[-1]
# log that we are saving drift values
wmsg = 'Saving drift values of Fiber {0} in {1}'
WLOG(p, '', wmsg.format(p['FIBER'], driftfitsname))
# add keys from original header file
hdict = spirouImage.CopyOriginalKeys(hdr)
# set the version
hdict = spirouImage.AddKey(p, hdict, p['KW_VERSION'])
hdict = spirouImage.AddKey(p, hdict, p['KW_DRS_DATE'], value=p['DRS_DATE'])
hdict = spirouImage.AddKey(p, hdict, p['KW_DATE_NOW'], value=p['DATE_NOW'])
hdict = spirouImage.AddKey(p, hdict, p['KW_PID'], value=p['PID'])
hdict = spirouImage.AddKey(p, hdict, p['KW_OUTPUT'], value=tag)
# set the input files
hdict = spirouImage.AddKey(p, hdict, p['KW_CDBFLAT'], value=p['FLATFILE'])
hdict = spirouImage.AddKey(p, hdict, p['KW_REFFILE'], value=raw_infile)
hdict = spirouImage.AddKey(p,
hdict,
p['KW_CDBWAVE'],
value=loc['WAVEFILE'])
hdict = spirouImage.AddKey(p,
hdict,
p['KW_WAVESOURCE'],
value=loc['WSOURCE'])
# add qc parameters
hdict = spirouImage.AddKey(p, hdict, p['KW_DRS_QC'], value=p['QC'])
hdict = spirouImage.AddQCKeys(p, hdict, qc_params)
# save drift values
p = spirouImage.WriteImage(p, driftfits, loc['DRIFT'], hdict)
# ------------------------------------------------------------------
# print .tbl result
# ------------------------------------------------------------------
# construct filename
drifttbl = spirouConfig.Constants.DRIFTPEAK_E2DS_TBL_FILE(p)
drifttblname = os.path.split(drifttbl)[-1]
# construct and write table
columnnames = ['time', 'drift', 'drifterr', 'drift_left', 'drift_right']
columnformats = ['7.4f', '6.2f', '6.3f', '6.2f', '6.2f']
columnvalues = [
loc['DELTATIME'], loc['MEANRV'], loc['MERRDRIFT'], loc['MEANRV_LEFT'],
loc['MEANRV_RIGHT']
]
table = spirouImage.MakeTable(p,
columns=columnnames,
values=columnvalues,
formats=columnformats)
# write table
wmsg = 'Average Drift saved in {0} Saved '
WLOG(p, '', wmsg.format(drifttblname))
spirouImage.WriteTable(p, table, drifttbl, fmt='ascii.rst')
# ------------------------------------------------------------------
# Plot amp and llpeak
# ------------------------------------------------------------------
if p['DRS_PLOT'] and p['DRIFT_PEAK_PLOT_LINE_LOG_AMP']:
# start interactive session if needed
sPlt.start_interactive_session(p)
# plot delta time against median drift
sPlt.drift_peak_plot_llpeak_amps(p, loc)
# ----------------------------------------------------------------------
# End Message
# ----------------------------------------------------------------------
p = spirouStartup.End(p)
# return a copy of locally defined variables in the memory
return dict(locals())
def main(night_name=None, hcfile=None, fpfiles=None):
"""
cal_SLIT_spirou.py main function, if night_name and files are None uses
arguments from run time i.e.:
cal_SLIT_spirou.py [night_directory] [files]
:param night_name: string or None, the folder within data raw directory
containing files (also reduced directory) i.e.
/data/raw/20170710 would be "20170710" but
/data/raw/AT5/20180409 would be "AT5/20180409"
:param files: string, list or None, the list of files to use for
arg_file_names and fitsfilename
(if None assumes arg_file_names was set from run time)
:return ll: dictionary, containing all the local variables defined in
main
"""
# ----------------------------------------------------------------------
# Set up
# ----------------------------------------------------------------------
# get parameters from config files/run time args/load paths + calibdb
p = spirouStartup.Begin(recipe=__NAME__)
if hcfile is None or fpfiles is None:
names, types = ['hcfile', 'fpfiles'], [str, str]
customargs = spirouStartup.GetCustomFromRuntime(p, [0, 1],
types,
names,
last_multi=True)
else:
customargs = dict(hcfile=hcfile, fpfiles=fpfiles)
# get parameters from configuration files and run time arguments
p = spirouStartup.LoadArguments(p,
night_name,
customargs=customargs,
mainfitsfile='fpfiles')
# ----------------------------------------------------------------------
# Construct reference filename and get fiber type
# ----------------------------------------------------------------------
p, hcfitsfilename = spirouStartup.SingleFileSetup(p, filename=p['HCFILE'])
p, fpfilenames = spirouStartup.MultiFileSetup(p, files=p['FPFILES'])
# set fiber (it doesn't matter with the 2D image but we need this to get
# the lamp type for FPFILES and HCFILES, AB == C
p['FIBER'] = 'AB'
p['FIB_TYP'] = [p['FIBER']]
fsource = __NAME__ + '/main()'
p.set_sources(['FIBER', 'FIB_TYP'], fsource)
# set the hcfilename to the first hcfilenames
fpfitsfilename = fpfilenames[0]
# ----------------------------------------------------------------------
# Once we have checked the e2dsfile we can load calibDB
# ----------------------------------------------------------------------
# as we have custom arguments need to load the calibration database
p = spirouStartup.LoadCalibDB(p)
# add a force plot off
p['PLOT_PER_ORDER'] = PLOT_PER_ORDER
p.set_source('PLOT_PER_ORDER', __NAME__ + '.main()')
# ----------------------------------------------------------------------
# Read FP and HC files
# ----------------------------------------------------------------------
# read and combine all FP files except the first (fpfitsfilename)
rargs = [p, 'add', fpfitsfilename, fpfilenames[1:]]
p, fpdata, fphdr = spirouImage.ReadImageAndCombine(*rargs)
# read first file (hcfitsfilename)
hcdata, hchdr, _, _ = spirouImage.ReadImage(p, hcfitsfilename)
# add data and hdr to loc
loc = ParamDict()
loc['HCDATA'], loc['HCHDR'] = hcdata, hchdr
loc['FPDATA'], loc['FPHDR'] = fpdata, fphdr
# set the source
sources = ['HCDATA', 'HCHDR']
loc.set_sources(sources, 'spirouImage.ReadImageAndCombine()')
sources = ['FPDATA', 'FPHDR']
loc.set_sources(sources, 'spirouImage.ReadImage()')
# ---------------------------------------------------------------------
# fix for un-preprocessed files
# ----------------------------------------------------------------------
hcdata = spirouImage.FixNonPreProcess(p, hcdata)
fpdata = spirouImage.FixNonPreProcess(p, fpdata)
# ----------------------------------------------------------------------
# Get basic image properties for reference file
# ----------------------------------------------------------------------
# get sig det value
p = spirouImage.GetSigdet(p, fphdr, name='sigdet')
# get exposure time
p = spirouImage.GetExpTime(p, fphdr, name='exptime')
# get gain
p = spirouImage.GetGain(p, fphdr, name='gain')
# get lamp parameters
p = spirouTHORCA.GetLampParams(p, hchdr)
# ----------------------------------------------------------------------
# Correction of DARK
# ----------------------------------------------------------------------
# p, hcdatac = spirouImage.CorrectForDark(p, hcdata, hchdr)
hcdatac = hcdata
p['DARKFILE'] = 'None'
# p, fpdatac = spirouImage.CorrectForDark(p, fpdata, fphdr)
fpdatac = fpdata
# ----------------------------------------------------------------------
# Resize hc data
# ----------------------------------------------------------------------
# rotate the image and convert from ADU/s to e-
hcdata = spirouImage.ConvertToE(spirouImage.FlipImage(p, hcdatac), p=p)
# convert NaN to zeros
hcdata0 = np.where(~np.isfinite(hcdata), np.zeros_like(hcdata), hcdata)
# resize image
bkwargs = dict(xlow=p['IC_CCDX_LOW'],
xhigh=p['IC_CCDX_HIGH'],
ylow=p['IC_CCDY_LOW'],
yhigh=p['IC_CCDY_HIGH'],
getshape=False)
hcdata2 = spirouImage.ResizeImage(p, hcdata0, **bkwargs)
# log change in data size
WLOG(p, '', ('HC Image format changed to '
'{0}x{1}').format(*hcdata2.shape))
# ----------------------------------------------------------------------
# Resize fp data
# ----------------------------------------------------------------------
# rotate the image and convert from ADU/s to e-
fpdata = spirouImage.ConvertToE(spirouImage.FlipImage(p, fpdatac), p=p)
# convert NaN to zeros
fpdata0 = np.where(~np.isfinite(fpdata), np.zeros_like(fpdata), fpdata)
# resize image
bkwargs = dict(xlow=p['IC_CCDX_LOW'],
xhigh=p['IC_CCDX_HIGH'],
ylow=p['IC_CCDY_LOW'],
yhigh=p['IC_CCDY_HIGH'],
getshape=False)
fpdata2 = spirouImage.ResizeImage(p, fpdata0, **bkwargs)
# log change in data size
WLOG(p, '', ('FP Image format changed to '
'{0}x{1}').format(*fpdata2.shape))
# ----------------------------------------------------------------------
# Correct for the BADPIX mask (set all bad pixels to zero)
# ----------------------------------------------------------------------
# p, hcdata2 = spirouImage.CorrectForBadPix(p, hcdata2, hchdr)
# p, fpdata2 = spirouImage.CorrectForBadPix(p, fpdata2, fphdr)
p['BADPFILE'] = 'None'
# save data to loc
loc['HCDATA'] = hcdata2
loc.set_source('HCDATA', __NAME__ + '/main()')
# save data to loc
loc['FPDATA'] = fpdata2
loc.set_source('FPDATA', __NAME__ + '/main()')
# ----------------------------------------------------------------------
# Log the number of dead pixels
# ----------------------------------------------------------------------
# get the number of bad pixels
n_bad_pix = np.nansum(hcdata2 <= 0)
n_bad_pix_frac = n_bad_pix * 100 / np.product(hcdata2.shape)
# Log number
wmsg = 'Nb HC dead pixels = {0} / {1:.2f} %'
WLOG(p, 'info', wmsg.format(int(n_bad_pix), n_bad_pix_frac))
# ----------------------------------------------------------------------
# Log the number of dead pixels
# ----------------------------------------------------------------------
# get the number of bad pixels
n_bad_pix = np.nansum(fpdata2 <= 0)
n_bad_pix_frac = n_bad_pix * 100 / np.product(fpdata2.shape)
# Log number
wmsg = 'Nb FP dead pixels = {0} / {1:.2f} %'
WLOG(p, 'info', wmsg.format(int(n_bad_pix), n_bad_pix_frac))
# ------------------------------------------------------------------
# Get localisation coefficients
# ------------------------------------------------------------------
# original there is a loop but it is not used --> removed
p = spirouImage.FiberParams(p, p['FIBER'], merge=True)
# get localisation fit coefficients
p, loc = spirouLOCOR.GetCoeffs(p, fphdr, loc)
# ------------------------------------------------------------------
# Get master wave solution map
# ------------------------------------------------------------------
# get master wave map
masterwavefile = spirouDB.GetDatabaseMasterWave(p)
# log process
wmsg1 = 'Getting master wavelength grid'
wmsg2 = '\tFile = {0}'.format(os.path.basename(masterwavefile))
WLOG(p, '', [wmsg1, wmsg2])
# Force A and B to AB solution
if p['FIBER'] in ['A', 'B']:
wave_fiber = 'AB'
else:
wave_fiber = p['FIBER']
# read master wave map
wout = spirouImage.GetWaveSolution(p,
filename=masterwavefile,
return_wavemap=True,
quiet=True,
return_header=True,
fiber=wave_fiber)
loc['MASTERWAVEP'], loc['MASTERWAVE'] = wout[:2]
loc['MASTERWAVEHDR'], loc['WSOURCE'] = wout[2:]
# set sources
wsource = ['MASTERWAVEP', 'MASTERWAVE', 'MASTERWAVEHDR']
loc.set_sources(wsource, 'spirouImage.GetWaveSolution()')
# ----------------------------------------------------------------------
# Read UNe solution
# ----------------------------------------------------------------------
wave_u_ne, amp_u_ne = spirouImage.ReadLineList(p)
loc['LL_LINE'], loc['AMPL_LINE'] = wave_u_ne, amp_u_ne
source = __NAME__ + '.main() + spirouImage.ReadLineList()'
loc.set_sources(['LL_LINE', 'AMPL_LINE'], source)
# ----------------------------------------------------------------------
# Read cavity length file
# ----------------------------------------------------------------------
loc['CAVITY_LEN_COEFFS'] = spirouImage.ReadCavityLength(p)
source = __NAME__ + '.main() + spirouImage.ReadCavityLength()'
loc.set_source('CAVITY_LEN_COEFFS', source)
# ------------------------------------------------------------------
# Calculate shape map
# ------------------------------------------------------------------
loc = spirouImage.GetShapeMap(p, loc)
# ------------------------------------------------------------------
# Plotting
# ------------------------------------------------------------------
if p['DRS_PLOT'] > 0:
# plots setup: start interactive plot
sPlt.start_interactive_session(p)
# plot the shape process for one order
sPlt.slit_shape_angle_plot(p, loc)
# end interactive section
sPlt.end_interactive_session(p)
# ----------------------------------------------------------------------
# Quality control
# ----------------------------------------------------------------------
# TODO: Decide on some quality control criteria?
# set passed variable and fail message list
passed, fail_msg = True, []
qc_values, qc_names, qc_logic, qc_pass = [], [], [], []
# finally log the failed messages and set QC = 1 if we pass the
# quality control QC = 0 if we fail quality control
if passed:
WLOG(p, 'info', 'QUALITY CONTROL SUCCESSFUL - Well Done -')
p['QC'] = 1
p.set_source('QC', __NAME__ + '/main()')
else:
for farg in fail_msg:
wmsg = 'QUALITY CONTROL FAILED: {0}'
WLOG(p, 'warning', wmsg.format(farg))
p['QC'] = 0
p.set_source('QC', __NAME__ + '/main()')
# add to qc header lists
qc_values.append('None')
qc_names.append('None')
qc_logic.append('None')
qc_pass.append(1)
# store in qc_params
qc_params = [qc_names, qc_values, qc_logic, qc_pass]
# ------------------------------------------------------------------
# Writing DXMAP to file
# ------------------------------------------------------------------
# get the raw tilt file name
raw_shape_file = os.path.basename(p['FITSFILENAME'])
# construct file name and path
shapefits, tag = spirouConfig.Constants.SLIT_XSHAPE_FILE(p)
shapefitsname = os.path.basename(shapefits)
# Log that we are saving tilt file
wmsg = 'Saving shape information in file: {0}'
WLOG(p, '', wmsg.format(shapefitsname))
# Copy keys from fits file
hdict = spirouImage.CopyOriginalKeys(fphdr)
# add version number
hdict = spirouImage.AddKey(p, hdict, p['KW_VERSION'])
hdict = spirouImage.AddKey(p, hdict, p['KW_DRS_DATE'], value=p['DRS_DATE'])
hdict = spirouImage.AddKey(p, hdict, p['KW_DATE_NOW'], value=p['DATE_NOW'])
hdict = spirouImage.AddKey(p, hdict, p['KW_PID'], value=p['PID'])
hdict = spirouImage.AddKey(p, hdict, p['KW_OUTPUT'], value=tag)
hdict = spirouImage.AddKey(p, hdict, p['KW_CDBDARK'], value=p['DARKFILE'])
hdict = spirouImage.AddKey(p, hdict, p['KW_CDBBAD'], value=p['BADPFILE'])
hdict = spirouImage.AddKey(p, hdict, p['KW_CDBLOCO'], value=p['LOCOFILE'])
hdict = spirouImage.AddKey1DList(p,
hdict,
p['KW_INFILE1'],
dim1name='hcfile',
values=p['HCFILE'])
hdict = spirouImage.AddKey1DList(p,
hdict,
p['KW_INFILE2'],
dim1name='fpfile',
values=p['FPFILES'])
# add qc parameters
hdict = spirouImage.AddKey(p, hdict, p['KW_DRS_QC'], value=p['QC'])
hdict = spirouImage.AddQCKeys(p, hdict, qc_params)
# write tilt file to file
p = spirouImage.WriteImage(p, shapefits, loc['DXMAP'], hdict)
# ------------------------------------------------------------------
# Writing sanity check files
# ------------------------------------------------------------------
if p['SHAPE_DEBUG_OUTPUTS']:
# log
WLOG(p, '', 'Saving debug sanity check files')
# construct file names
input_fp_file, tag1 = spirouConfig.Constants.SLIT_SHAPE_IN_FP_FILE(p)
output_fp_file, tag2 = spirouConfig.Constants.SLIT_SHAPE_OUT_FP_FILE(p)
input_hc_file, tag3 = spirouConfig.Constants.SLIT_SHAPE_IN_HC_FILE(p)
output_hc_file, tag4 = spirouConfig.Constants.SLIT_SHAPE_OUT_HC_FILE(p)
overlap_file, tag5 = spirouConfig.Constants.SLIT_SHAPE_OVERLAP_FILE(p)
# write input fp file
hdict = spirouImage.AddKey(p, hdict, p['KW_OUTPUT'], value=tag1)
p = spirouImage.WriteImage(p, input_fp_file, loc['FPDATA'], hdict)
# write output fp file
hdict = spirouImage.AddKey(p, hdict, p['KW_OUTPUT'], value=tag2)
p = spirouImage.WriteImage(p, output_fp_file, loc['FPDATA2'], hdict)
# write input fp file
hdict = spirouImage.AddKey(p, hdict, p['KW_OUTPUT'], value=tag3)
p = spirouImage.WriteImage(p, input_hc_file, loc['HCDATA'], hdict)
# write output fp file
hdict = spirouImage.AddKey(p, hdict, p['KW_OUTPUT'], value=tag4)
p = spirouImage.WriteImage(p, output_hc_file, loc['HCDATA2'], hdict)
# write overlap file
hdict = spirouImage.AddKey(p, hdict, p['KW_OUTPUT'], value=tag5)
p = spirouImage.WriteImage(p, overlap_file, loc['ORDER_OVERLAP'],
hdict)
# ----------------------------------------------------------------------
# Move to calibDB and update calibDB
# ----------------------------------------------------------------------
if p['QC']:
keydb = 'SHAPE'
# copy shape file to the calibDB folder
spirouDB.PutCalibFile(p, shapefits)
# update the master calib DB file with new key
spirouDB.UpdateCalibMaster(p, keydb, shapefitsname, fphdr)
# ----------------------------------------------------------------------
# End Message
# ----------------------------------------------------------------------
p = spirouStartup.End(p)
# return a copy of locally defined variables in the memory
return dict(locals())
def main(runname=None, quiet=False):
# ----------------------------------------------------------------------
# Set up
# ----------------------------------------------------------------------
# get parameters from config files/run time args/load paths + calibdb
p = spirouStartup.Begin(recipe=__NAME__, quiet=True)
# now get custom arguments
ckwargs = dict(positions=[0], types=[str], names=['RUNNAME'],
calls=[runname], require_night_name=False,
required=[False])
customargs = spirouStartup.GetCustomFromRuntime(p, **ckwargs)
# add custom args straight to p
p = spirouStartup.LoadMinimum(p, customargs=customargs)
# ----------------------------------------------------------------------
# Read the run file and extract parameters
# ----------------------------------------------------------------------
# construct filename
rfile = os.path.join(UNIT_TEST_PATH, p['RUNNAME'])
# check if RUNNAME is None
if p['RUNNAME'] == 'None':
exists = False
emsgs = ['No unit test run file defined.']
# check that rfile exists
elif not os.path.exists(rfile):
emsgs = ['Unit test run file "{0}" does not exist'.format(rfile)]
exists = False
else:
exists = True
emsgs = []
# deal with file wrong (or no file defined) --> print valid unit tests
if not exists:
emsgs.append('')
emsgs.append('Available units tests are:')
for rfile in os.listdir(UNIT_TEST_PATH):
emsgs.append('\t{0}'.format(rfile))
emsgs.append('')
emsgs.append('Located at {0}'.format(UNIT_TEST_PATH))
WLOG(p, 'error', emsgs)
# get the parameters in the run file
rparams = spirouConfig.GetConfigParams(p, filename=rfile)
# reset the DRS
if not quiet:
spirouTools.DRS_Reset(log=False, called=True)
# ----------------------------------------------------------------------
# Get runs
# ----------------------------------------------------------------------
runs = spirouUnitTests.get_runs(p, rparams, rfile)
# ----------------------------------------------------------------------
# group runs (for parallelisation)
# ----------------------------------------------------------------------
# get groups that can be run in parallel
groups = group_runs(runs)
# split groups by max number of processes
groups = parallelize(groups, MAX_PROCESSES)
# loop around groups
for group_name in groups:
# process storage
pp = []
# loop around sub groups (to be run at the same time)
for sub_group in groups[group_name]:
# make sub_group a dict
sruns = make_subgroup_dict(sub_group, group_name)
# do parallel run
process = Process(target=unit_wrapper, args=(p, sruns))
process.start()
pp.append(process)
# do not continue until
for process in pp:
while process.is_alive():
pass
# ----------------------------------------------------------------------
# End Message
# ----------------------------------------------------------------------
wmsg = 'Recipe {0} has been successfully completed'
WLOG(p, 'info', wmsg.format(p['PROGRAM']))
# return a copy of locally defined variables in the memory
return dict(locals())
def main(preview=1):
# ----------------------------------------------------------------------
# get values from config file
p = spirouStartup.Begin(recipe=__NAME__, quiet=True)
customargs = spirouStartup.GetCustomFromRuntime(p, [0], [int], ['preview'],
calls=[preview],
required=[False],
require_night_name=False)
p = spirouStartup.LoadArguments(p, None, customargs=customargs,
require_night_name=False)
# ----------------------------------------------------------------------
# if in preview mode tell user
if p['PREVIEW']:
WLOG(p, 'info', 'Running in preview mode.')
# ----------------------------------------------------------------------
# read and ask for new version
WLOG(p, '', 'Reading DRS version')
# set new version
version = ask_for_new_version()
# add tag of version
if version is not None:
# tag head with version
git_remove_tag(version)
git_tag_head(version)
new = True
else:
version = str(__version__)
new = False
# ----------------------------------------------------------------------
# update DRS files
if not p['PREVIEW']:
update_version_file(VERSIONFILE, version)
update_py_version(CONSTFILE, version)
# ----------------------------------------------------------------------
# create new changelog
WLOG(p, '', 'Updating changelog')
if not p['PREVIEW']:
git_change_log(FILENAME)
else:
git_change_log('tmp.txt')
preview_log('tmp.txt')
if new:
git_remove_tag(version)
# ----------------------------------------------------------------------
# if we are in preview mode should we keep these changes and update version
if p['PREVIEW']:
uinput = input('Keep changes? [Y]es [N]o:\t')
if 'Y' in uinput.upper():
# redo tagging
git_remove_tag(version)
git_tag_head(version)
# update version file and python version file
update_version_file(VERSIONFILE, version)
update_py_version(CONSTFILE, version)
# move the tmp.txt to change log
shutil.move('tmp.txt', FILENAME)
else:
os.remove('tmp.txt')
# ----------------------------------------------------------------------
# End Message
# ----------------------------------------------------------------------
p = spirouStartup.End(p, outputs=None)
# return a copy of locally defined variables in the memory
return dict(locals())
def main(night_name=None,
e2dsfile=None,
mask=None,
rv=None,
width=None,
step=None):
"""
cal_CCF_E2DS_spirou.py main function, if arguments are None uses
arguments from run time i.e.:
cal_CCF_E2DS_spirou.py [night_directory] [E2DSfilename] [mask] [RV]
[width] [step]
:param night_name: string or None, the folder within data raw directory
containing files (also reduced directory) i.e.
/data/raw/20170710 would be "20170710" but
/data/raw/AT5/20180409 would be "AT5/20180409"
:param e2dsfile: string, the E2DS file to use
:param mask: string, the mask file to use (i.e. "UrNe.mas")
:param rv: float, the target RV to use
:param width: float, the CCF width to use
:param step: float, the CCF step to use
:return ll: dictionary, containing all the local variables defined in
main
"""
# ----------------------------------------------------------------------
# Set up
# ----------------------------------------------------------------------
# get parameters from config files/run time args/load paths + calibdb
p = spirouStartup.Begin(recipe=__NAME__)
# deal with arguments being None (i.e. get from sys.argv)
pos = [0, 1, 2, 3, 4]
fmt = [str, str, float, float, float]
name = ['e2dsfile', 'ccf_mask', 'target_rv', 'ccf_width', 'ccf_step']
lname = ['input_file', 'CCF_mask', 'RV', 'CCF_width', 'CCF_step']
req = [True, True, True, False, False]
call = [e2dsfile, mask, rv, width, step]
call_priority = [True, True, True, True, True]
# now get custom arguments
customargs = spirouStartup.GetCustomFromRuntime(p, pos, fmt, name, req,
call, call_priority, lname)
# get parameters from configuration files and run time arguments
p = spirouStartup.LoadArguments(p,
night_name,
customargs=customargs,
mainfitsfile='e2dsfile',
mainfitsdir='reduced')
# ----------------------------------------------------------------------
# Construct reference filename and get fiber type
# ----------------------------------------------------------------------
p, e2dsfilename = spirouStartup.SingleFileSetup(p, filename=p['E2DSFILE'])
# ----------------------------------------------------------------------
# Once we have checked the e2dsfile we can load calibDB
# ----------------------------------------------------------------------
# as we have custom arguments need to load the calibration database
p = spirouStartup.LoadCalibDB(p)
# ----------------------------------------------------------------------
# Deal with optional run time arguments
# ----------------------------------------------------------------------
# define default arguments (if ccf_width and ccf_step are not defined
# in function call or run time arguments
if 'ccf_width' not in p:
p['CCF_WIDTH'] = p['IC_CCF_WIDTH']
if 'ccf_step' not in p:
p['CCF_STEP'] = p['IC_CCF_STEP']
# ----------------------------------------------------------------------
# Read image file
# ----------------------------------------------------------------------
# read the image data
e2ds, hdr, nbo, nx = spirouImage.ReadData(p, e2dsfilename)
# add to loc
loc = ParamDict()
loc['E2DS'] = e2ds
loc['NUMBER_ORDERS'] = nbo
loc.set_sources(['E2DS', 'number_orders'], __NAME__ + '/main()')
# ----------------------------------------------------------------------
# Get basic image properties for reference file
# ----------------------------------------------------------------------
# get sig det value
p = spirouImage.GetSigdet(p, hdr, name='sigdet')
# get exposure time
p = spirouImage.GetExpTime(p, hdr, name='exptime')
# get gain
p = spirouImage.GetGain(p, hdr, name='gain')
# get acquisition time
p = spirouImage.GetAcqTime(p, hdr, name='acqtime', kind='julian')
# get obj name
p = spirouImage.ReadParam(p, hdr, 'KW_OBJNAME', name='OBJNAME', dtype=str)
bjdref = p['ACQTIME']
# set sigdet and conad keywords (sigdet is changed later)
p['KW_CCD_SIGDET'][1] = p['SIGDET']
p['KW_CCD_CONAD'][1] = p['GAIN']
# ----------------------------------------------------------------------
# Earth Velocity calculation
# ----------------------------------------------------------------------
if p['IC_IMAGE_TYPE'] == 'H4RG':
p, loc = spirouImage.GetEarthVelocityCorrection(p, loc, hdr)
# ----------------------------------------------------------------------
# Read wavelength solution
# ----------------------------------------------------------------------
# log
WLOG(p, '', 'Reading wavelength solution ')
# Force A and B to AB solution
if p['FIBER'] in ['A', 'B']:
wave_fiber = 'AB'
else:
wave_fiber = p['FIBER']
# get wave image
wout = spirouImage.GetWaveSolution(p,
hdr=hdr,
return_wavemap=True,
return_filename=True,
fiber=wave_fiber)
param_ll, wave_ll, wavefile, wsource = wout
# save to storage
loc['PARAM_LL'], loc['WAVE_LL'], loc['WAVEFILE'], loc['WSOURCE'] = wout
source = __NAME__ + '/main() + spirouTHORCA.GetWaveSolution()'
loc.set_sources(['WAVE_LL', 'PARAM_LL', 'WAVEFILE', 'WSOURCE'], source)
# ----------------------------------------------------------------------
# Read Flat file
# ----------------------------------------------------------------------
# TODO We do not need to correct FLAT
# log
# WLOG(p, '', 'Reading Flat-Field ')
# get flat
# loc['FLAT'] = spirouImage.ReadFlatFile(p, hdr)
# loc.set_source('FLAT', __NAME__ + '/main() + /spirouImage.ReadFlatFile')
# get all values in flat that are zero to 1
# loc['FLAT'] = np.where(loc['FLAT'] == 0, 1.0, loc['FLAT'])
# get blaze
# p, loc['BLAZE'] = spirouImage.ReadBlazeFile(p, hdr)
p, blaze0 = spirouImage.ReadBlazeFile(p, hdr)
# ----------------------------------------------------------------------
# Preliminary set up = no flat, no blaze
# ----------------------------------------------------------------------
# reset flat to all ones
# loc['FLAT'] = np.ones((nbo, nx))
# set blaze to all ones (if not bug in correlbin !!!
# TODO Check why Blaze makes bugs in correlbin
loc['BLAZE'] = np.ones((nbo, nx))
# set sources
# loc.set_sources(['flat', 'blaze'], __NAME__ + '/main()')
loc.set_sources(['blaze'], __NAME__ + '/main()')
# Modification of E2DS array with N.A.N
if np.isnan(np.sum(e2ds)):
WLOG(p, 'warning', 'NaN values found in e2ds, converting process')
# First basic approach Replacing N.A.N by zeros
# e2ds[np.isnan(e2ds)] = 0
# Second approach replacing N.A.N by the Adjusted Blaze
e2dsb = e2ds / blaze0
for i in np.arange(len(e2ds)):
with warnings.catch_warnings(record=True) as _:
rap = np.mean(e2dsb[i][np.isfinite(e2dsb[i])])
if np.isnan(rap):
rap = 0.0
e2ds[i] = np.where(np.isfinite(e2dsb[i]), e2ds[i], blaze0[i] * rap)
# ----------------------------------------------------------------------
# correct extracted image for flat
# ----------------------------------------------------------------------
# loc['E2DSFF'] = e2ds/loc['FLAT']
# loc['E2DSFF'] = e2ds*1.
loc['E2DSFF'] = e2ds
loc.set_source('E2DSFF', __NAME__ + '/main()')
# ----------------------------------------------------------------------
# Compute photon noise uncertainty for reference file
# ----------------------------------------------------------------------
# set up the arguments for DeltaVrms2D
dargs = [loc['E2DS'], loc['WAVE_LL']]
dkwargs = dict(sigdet=p['IC_DRIFT_NOISE'],
size=p['IC_DRIFT_BOXSIZE'],
threshold=p['IC_DRIFT_MAXFLUX'])
# run DeltaVrms2D
dvrmsref, wmeanref = spirouRV.DeltaVrms2D(*dargs, **dkwargs)
# save to loc
loc['DVRMSREF'], loc['WMEANREF'] = dvrmsref, wmeanref
loc.set_sources(['dvrmsref', 'wmeanref'], __NAME__ + '/main()()')
# log the estimated RV uncertainty
# wmsg = 'On fiber {0} estimated RV uncertainty on spectrum is {1:.3f} m/s'
# WLOG(p, 'info', wmsg.format(p['FIBER'], wmeanref))
wmsg = 'On fiber estimated RV uncertainty on spectrum is {0:.3f} m/s'
WLOG(p, 'info', wmsg.format(wmeanref))
# TEST N.A.N
# loc['E2DSFF'][20:22,2000:3000]=np.nan
# e2ds[20:30,1000:3000]=np.nan
# ----------------------------------------------------------------------
# Reference plots
# ----------------------------------------------------------------------
if p['DRS_PLOT'] > 0:
# start interactive session if needed
sPlt.start_interactive_session(p)
# plot FP spectral order
sPlt.drift_plot_selected_wave_ref(p,
loc,
x=loc['WAVE_LL'],
y=loc['E2DS'])
# plot photon noise uncertainty
sPlt.drift_plot_photon_uncertainty(p, loc)
# ----------------------------------------------------------------------
# Get template RV (from ccf_mask)
# ----------------------------------------------------------------------
# get the CCF mask from file (check location of mask)
loc = spirouRV.GetCCFMask(p, loc)
# check and deal with mask in microns (should be in nm)
if np.mean(loc['LL_MASK_CTR']) < 2.0:
loc['LL_MASK_CTR'] *= 1000.0
loc['LL_MASK_D'] *= 1000.0
# ----------------------------------------------------------------------
# Do correlation
# ----------------------------------------------------------------------
# calculate and fit the CCF
loc = spirouRV.Coravelation(p, loc)
# ----------------------------------------------------------------------
# Correlation stats
# ----------------------------------------------------------------------
# get the maximum number of orders to use
nbmax = p['CCF_NUM_ORDERS_MAX']
# get the average ccf
loc['AVERAGE_CCF'] = np.nansum(loc['CCF'][:nbmax], axis=0)
# normalize the average ccf
normalized_ccf = loc['AVERAGE_CCF'] / np.max(loc['AVERAGE_CCF'])
# get the fit for the normalized average ccf
ccf_res, ccf_fit = spirouRV.FitCCF(p,
loc['RV_CCF'],
normalized_ccf,
fit_type=0)
loc['CCF_RES'] = ccf_res
loc['CCF_FIT'] = ccf_fit
# get the max cpp
loc['MAXCPP'] = np.nansum(loc['CCF_MAX']) / np.nansum(
loc['PIX_PASSED_ALL'])
# get the RV value from the normalised average ccf fit center location
loc['RV'] = float(ccf_res[1])
# get the contrast (ccf fit amplitude)
loc['CONTRAST'] = np.abs(100 * ccf_res[0])
# get the FWHM value
loc['FWHM'] = ccf_res[2] * spirouCore.spirouMath.fwhm()
# ----------------------------------------------------------------------
# set the source
keys = [
'average_ccf', 'maxcpp', 'rv', 'contrast', 'fwhm', 'ccf_res', 'ccf_fit'
]
loc.set_sources(keys, __NAME__ + '/main()')
# ----------------------------------------------------------------------
# log the stats
wmsg = ('Correlation: C={0:.1f}[%] RV={1:.5f}[km/s] '
'FWHM={2:.4f}[km/s] maxcpp={3:.1f}')
wargs = [loc['CONTRAST'], loc['RV'], loc['FWHM'], loc['MAXCPP']]
WLOG(p, 'info', wmsg.format(*wargs))
# ----------------------------------------------------------------------
# rv ccf plot
# ----------------------------------------------------------------------
if p['DRS_PLOT'] > 0:
# Plot rv vs ccf (and rv vs ccf_fit)
sPlt.ccf_rv_ccf_plot(p, loc['RV_CCF'], normalized_ccf, ccf_fit)
# ----------------------------------------------------------------------
# Quality control
# ----------------------------------------------------------------------
# set passed variable and fail message list
passed, fail_msg = True, []
qc_values, qc_names, qc_logic, qc_pass = [], [], [], []
# TODO: Needs doing
# finally log the failed messages and set QC = 1 if we pass the
# quality control QC = 0 if we fail quality control
if passed:
WLOG(p, 'info', 'QUALITY CONTROL SUCCESSFUL - Well Done -')
p['QC'] = 1
p.set_source('QC', __NAME__ + '/main()')
else:
for farg in fail_msg:
wmsg = 'QUALITY CONTROL FAILED: {0}'
WLOG(p, 'warning', wmsg.format(farg))
p['QC'] = 0
p.set_source('QC', __NAME__ + '/main()')
# add to qc header lists
qc_values.append('None')
qc_names.append('None')
qc_logic.append('None')
qc_pass.append(1)
# store in qc_params
qc_params = [qc_names, qc_values, qc_logic, qc_pass]
# ----------------------------------------------------------------------
# archive ccf to table
# ----------------------------------------------------------------------
# construct filename
res_table_file = spirouConfig.Constants.CCF_TABLE_FILE(p)
# log progress
WLOG(p, '', 'Archiving CCF on file {0}'.format(res_table_file))
# define column names
columns = ['order', 'maxcpp', 'nlines', 'contrast', 'RV', 'sig']
# define values for each column
values = [
loc['ORDERS'], loc['CCF_MAX'] / loc['PIX_PASSED_ALL'], loc['TOT_LINE'],
np.abs(100 * loc['CCF_ALL_RESULTS'][:, 0]),
loc['CCF_ALL_RESULTS'][:, 1], loc['CCF_ALL_RESULTS'][:, 2]
]
# define the format for each column
formats = ['2.0f', '5.0f', '4.0f', '4.1f', '9.4f', '7.4f']
# construct astropy table from column names, values and formats
table = spirouImage.MakeTable(p, columns, values, formats)
# save table to file
spirouImage.WriteTable(p, table, res_table_file, fmt='ascii')
# ----------------------------------------------------------------------
# archive ccf to fits file
# ----------------------------------------------------------------------
raw_infile = os.path.basename(p['E2DSFILE'])
# construct folder and filename
corfile, tag = spirouConfig.Constants.CCF_FITS_FILE(p)
corfilename = os.path.split(corfile)[-1]
# log that we are archiving the CCF on file
WLOG(p, '', 'Archiving CCF on file {0}'.format(corfilename))
# get constants from p
mask = p['CCF_MASK']
# if file exists remove it
if os.path.exists(corfile):
os.remove(corfile)
# add the average ccf to the end of ccf
data = np.vstack([loc['CCF'], loc['AVERAGE_CCF']])
# add drs keys
hdict = spirouImage.CopyOriginalKeys(hdr)
hdict = spirouImage.AddKey(p, hdict, p['KW_VERSION'])
hdict = spirouImage.AddKey(p, hdict, p['KW_DRS_DATE'], value=p['DRS_DATE'])
hdict = spirouImage.AddKey(p, hdict, p['KW_DATE_NOW'], value=p['DATE_NOW'])
hdict = spirouImage.AddKey(p, hdict, p['KW_PID'], value=p['PID'])
hdict = spirouImage.AddKey(p, hdict, p['KW_OUTPUT'], value=tag)
# set the input files
hdict = spirouImage.AddKey(p, hdict, p['KW_CDBBLAZE'], value=p['BLAZFILE'])
hdict = spirouImage.AddKey(p,
hdict,
p['KW_CDBWAVE'],
value=loc['WAVEFILE'])
hdict = spirouImage.AddKey(p,
hdict,
p['KW_WAVESOURCE'],
value=loc['WSOURCE'])
hdict = spirouImage.AddKey1DList(p,
hdict,
p['KW_INFILE1'],
dim1name='file',
values=p['E2DSFILE'])
hdict = spirouImage.AddKey(p,
hdict,
p['KW_INCCFMASK'],
value=p['CCF_MASK'])
hdict = spirouImage.AddKey(p, hdict, p['KW_INRV'], value=p['TARGET_RV'])
hdict = spirouImage.AddKey(p, hdict, p['KW_INWIDTH'], value=p['CCF_WIDTH'])
hdict = spirouImage.AddKey(p, hdict, p['KW_INSTEP'], value=p['CCF_STEP'])
# add qc parameters
hdict = spirouImage.AddKey(p, hdict, p['KW_DRS_QC'], value=p['QC'])
hdict = spirouImage.AddQCKeys(p, hdict, qc_params)
# add CCF keys
hdict = spirouImage.AddKey(p, hdict, p['KW_CCF_CTYPE'], value='km/s')
hdict = spirouImage.AddKey(p,
hdict,
p['KW_CCF_CRVAL'],
value=loc['RV_CCF'][0])
# the rv step
rvstep = np.abs(loc['RV_CCF'][0] - loc['RV_CCF'][1])
hdict = spirouImage.AddKey(p, hdict, p['KW_CCF_CDELT'], value=rvstep)
# add ccf stats
hdict = spirouImage.AddKey(p,
hdict,
p['KW_CCF_RV'],
value=loc['CCF_RES'][1])
hdict = spirouImage.AddKey(p, hdict, p['KW_CCF_RVC'], value=loc['RV'])
hdict = spirouImage.AddKey(p, hdict, p['KW_CCF_FWHM'], value=loc['FWHM'])
hdict = spirouImage.AddKey(p,
hdict,
p['KW_CCF_WMREF'],
value=loc['WMEANREF'])
hdict = spirouImage.AddKey(p,
hdict,
p['KW_CCF_CONTRAST'],
value=loc['CONTRAST'])
hdict = spirouImage.AddKey(p,
hdict,
p['KW_CCF_MAXCPP'],
value=loc['MAXCPP'])
hdict = spirouImage.AddKey(p, hdict, p['KW_CCF_MASK'], value=p['CCF_MASK'])
hdict = spirouImage.AddKey(p,
hdict,
p['KW_CCF_LINES'],
value=np.nansum(loc['TOT_LINE']))
# add berv values
hdict = spirouImage.AddKey(p, hdict, p['KW_BERV'], value=loc['BERV'])
hdict = spirouImage.AddKey(p, hdict, p['KW_BJD'], value=loc['BJD'])
hdict = spirouImage.AddKey(p,
hdict,
p['KW_BERV_MAX'],
value=loc['BERV_MAX'])
# write image and add header keys (via hdict)
p = spirouImage.WriteImage(p, corfile, data, hdict)
# ----------------------------------------------------------------------
# End Message
# ----------------------------------------------------------------------
p = spirouStartup.End(p)
# return a copy of locally defined variables in the memory
return dict(locals())
def main(night_name=None, fpfile=None, hcfiles=None):
"""
cal_wave_spirou.py main function, if night_name and files are None uses
arguments from run time i.e.:
cal_wave_spirou.py [night_directory] [fpfile] [hcfiles]
:param night_name: string or None, the folder within data reduced directory
containing files (also reduced directory) i.e.
/data/reduced/20170710 would be "20170710" but
/data/reduced/AT5/20180409 is "AT5/20180409"
:param fpfile: string, or None, the FP file to use for
arg_file_names and fitsfilename
(if None assumes arg_file_names was set from run time)
:param hcfiles: string, list or None, the list of HC files to use for
arg_file_names and fitsfilename
(if None assumes arg_file_names was set from run time)
:return ll: dictionary, containing all the local variables defined in
main
"""
# ----------------------------------------------------------------------
# Set up
# ----------------------------------------------------------------------
# get parameters from config files/run time args/load paths + calibdb
p = spirouStartup.Begin(recipe=__NAME__)
if hcfiles is None or fpfile is None:
names, types = ['fpfile', 'hcfiles'], [str, str]
customargs = spirouStartup.GetCustomFromRuntime(p, [0, 1],
types,
names,
last_multi=True)
else:
customargs = dict(hcfiles=hcfiles, fpfile=fpfile)
# get parameters from configuration files and run time arguments
p = spirouStartup.LoadArguments(p,
night_name,
customargs=customargs,
mainfitsdir='reduced',
mainfitsfile='hcfiles')
# ----------------------------------------------------------------------
# Construct reference filename and get fiber type
# ----------------------------------------------------------------------
p, fpfitsfilename = spirouStartup.SingleFileSetup(p, filename=p['FPFILE'])
fiber1 = str(p['FIBER'])
p, hcfilenames = spirouStartup.MultiFileSetup(p, files=p['HCFILES'])
fiber2 = str(p['FIBER'])
# set the hcfilename to the first hcfilenames
hcfitsfilename = hcfilenames[0]
# ----------------------------------------------------------------------
# Once we have checked the e2dsfile we can load calibDB
# ----------------------------------------------------------------------
# as we have custom arguments need to load the calibration database
p = spirouStartup.LoadCalibDB(p)
# ----------------------------------------------------------------------
# Have to check that the fibers match
# ----------------------------------------------------------------------
if fiber1 == fiber2:
p['FIBER'] = fiber1
fsource = __NAME__ + '/main() & spirouStartup.GetFiberType()'
p.set_source('FIBER', fsource)
else:
emsg = 'Fiber not matching for {0} and {1}, should be the same'
eargs = [hcfitsfilename, fpfitsfilename]
WLOG(p, 'error', emsg.format(*eargs))
# set the fiber type
p['FIB_TYP'] = [p['FIBER']]
p.set_source('FIB_TYP', __NAME__ + '/main()')
# ----------------------------------------------------------------------
# Read FP and HC files
# ----------------------------------------------------------------------
# read and combine all HC files except the first (fpfitsfilename)
rargs = [p, 'add', hcfitsfilename, hcfilenames[1:]]
p, hcdata, hchdr = spirouImage.ReadImageAndCombine(*rargs)
# read first file (fpfitsfilename)
fpdata, fphdr, _, _ = spirouImage.ReadImage(p, fpfitsfilename)
# add data and hdr to loc
loc = ParamDict()
loc['HCDATA'], loc['HCHDR'], loc['HCCDR'] = hcdata, hchdr, hchdr.comments
loc['FPDATA'], loc['FPHDR'], loc['FPCDR'] = fpdata, fphdr, fphdr.comments
# set the source
sources = ['HCDATA', 'HCHDR', 'HCCDR']
loc.set_sources(sources, 'spirouImage.ReadImageAndCombine()')
sources = ['FPDATA', 'FPHDR', 'FPCDR']
loc.set_sources(sources, 'spirouImage.ReadImage()')
# ----------------------------------------------------------------------
# Get basic image properties for reference file
# ----------------------------------------------------------------------
# get sig det value
p = spirouImage.GetSigdet(p, hchdr, name='sigdet')
# get exposure time
p = spirouImage.GetExpTime(p, hchdr, name='exptime')
# get gain
p = spirouImage.GetGain(p, hchdr, name='gain')
# get acquisition time
p = spirouImage.GetAcqTime(p, hchdr, name='acqtime', kind='julian')
bjdref = p['ACQTIME']
# set sigdet and conad keywords (sigdet is changed later)
p['KW_CCD_SIGDET'][1] = p['SIGDET']
p['KW_CCD_CONAD'][1] = p['GAIN']
# get lamp parameters
p = spirouWAVE2.get_lamp_parameters(p, hchdr)
# get number of orders
# we always get fibre A number because AB is doubled in constants file
loc['NBO'] = p['QC_LOC_NBO_FPALL']['A']
loc.set_source('NBO', __NAME__ + '.main()')
# get number of pixels in x from hcdata size
loc['NBPIX'] = loc['HCDATA'].shape[1]
loc.set_source('NBPIX', __NAME__ + '.main()')
# ----------------------------------------------------------------------
# Read blaze
# ----------------------------------------------------------------------
# get tilts
p, loc['BLAZE'] = spirouImage.ReadBlazeFile(p, hchdr)
loc.set_source('BLAZE', __NAME__ + '/main() + /spirouImage.ReadBlazeFile')
# make copy of blaze (as it's overwritten later in CCF part)
# TODO is this needed? More sensible to make and set copy in CCF?
loc['BLAZE2'] = np.copy(loc['BLAZE'])
# ----------------------------------------------------------------------
# Read wave solution
# ----------------------------------------------------------------------
# wavelength file; we will use the polynomial terms in its header,
# NOT the pixel values that would need to be interpolated
# set source of wave file
wsource = __NAME__ + '/main() + /spirouImage.GetWaveSolution'
# Force A and B to AB solution
if p['FIBER'] in ['A', 'B']:
wave_fiber = 'AB'
else:
wave_fiber = p['FIBER']
# get wave image
wout = spirouImage.GetWaveSolution(p,
hdr=hchdr,
return_wavemap=True,
return_filename=True,
fiber=wave_fiber)
loc['WAVEPARAMS'], loc['WAVE_INIT'], loc['WAVEFILE'], loc['WSOURCE'] = wout
loc.set_sources(['WAVE_INIT', 'WAVEFILE', 'WAVEPARAMS', 'WSOURCE'],
wsource)
poly_wave_sol = loc['WAVEPARAMS']
# ----------------------------------------------------------------------
# Check that wave parameters are consistent with "ic_ll_degr_fit"
# ----------------------------------------------------------------------
loc = spirouImage.CheckWaveSolConsistency(p, loc)
# ----------------------------------------------------------------------
# HC wavelength solution
# ----------------------------------------------------------------------
# log that we are running the HC part and the mode
wmsg = 'Now running the HC solution, mode = {0}'
WLOG(p, 'info', wmsg.format(p['WAVE_MODE_HC']))
# get the solution
loc = spirouWAVE2.do_hc_wavesol(p, loc)
# ----------------------------------------------------------------------
# Quality control - HC solution
# ----------------------------------------------------------------------
# set passed variable and fail message list
passed, fail_msg = True, []
qc_values, qc_names, qc_logic, qc_pass = [], [], [], []
# ----------------------------------------------------------------------
# quality control on sigma clip (sig1 > qc_hc_wave_sigma_max
if loc['SIG1'] > p['QC_HC_WAVE_SIGMA_MAX']:
fmsg = 'Sigma too high ({0:.5f} > {1:.5f})'
fail_msg.append(fmsg.format(loc['SIG1'], p['QC_HC_WAVE_SIGMA_MAX']))
passed = False
qc_pass.append(0)
else:
qc_pass.append(1)
# add to qc header lists
qc_values.append(loc['SIG1'])
qc_names.append('SIG1 HC')
qc_logic.append('SIG1 > {0:.2f}'.format(p['QC_HC_WAVE_SIGMA_MAX']))
# ----------------------------------------------------------------------
# check the difference between consecutive orders is always positive
# get the differences
wave_diff = loc['WAVE_MAP2'][1:] - loc['WAVE_MAP2'][:-1]
if np.min(wave_diff) < 0:
fmsg = 'Negative wavelength difference between orders'
fail_msg.append(fmsg)
passed = False
qc_pass.append(0)
else:
qc_pass.append(1)
# add to qc header lists
qc_values.append(np.min(wave_diff))
qc_names.append('MIN WAVE DIFF HC')
qc_logic.append('MIN WAVE DIFF < 0')
# ----------------------------------------------------------------------
# check the difference between consecutive pixels along an order is
# always positive
# loop through the orders
ord_check = np.zeros((loc['NBO']), dtype=bool)
for order in range(loc['NBO']):
oc = np.all(loc['WAVE_MAP2'][order, 1:] > loc['WAVE_MAP2'][order, :-1])
ord_check[order] = oc
# TODO: Melissa Why is this here????
# ord_check[5] = False
if np.all(ord_check):
qc_pass.append(1)
qc_values.append('None')
else:
fmsg = 'Negative wavelength difference along an order'
fail_msg.append(fmsg)
passed = False
qc_pass.append(0)
qc_values.append(np.ndarray.tolist(np.where(~ord_check)[0]))
# add to qc header lists
# vale: array of orders where it fails
qc_names.append('WAVE DIFF ALONG ORDER HC')
qc_logic.append('WAVE DIFF ALONG ORDER < 0')
# ----------------------------------------------------------------------
# finally log the failed messages and set QC = 1 if we pass the
# quality control QC = 0 if we fail quality control
if passed:
WLOG(p, 'info', 'QUALITY CONTROL SUCCESSFUL - Well Done -')
p['QC'] = 1
p.set_source('QC', __NAME__ + '/main()')
else:
for farg in fail_msg:
wmsg = 'QUALITY CONTROL FAILED: {0}'
WLOG(p, 'warning', wmsg.format(farg))
p['QC'] = 0
p.set_source('QC', __NAME__ + '/main()')
# store in qc_params
qc_params = [qc_names, qc_values, qc_logic, qc_pass]
# ----------------------------------------------------------------------
# log the global stats
# ----------------------------------------------------------------------
# calculate catalog-fit residuals in km/s
res_hc = []
sumres_hc = 0.0
sumres2_hc = 0.0
for order in range(loc['NBO']):
# get HC line wavelengths for the order
order_mask = loc['ORD_T'] == order
hc_x_ord = loc['XGAU_T'][order_mask]
hc_ll_ord = np.polyval(loc['POLY_WAVE_SOL'][order][::-1], hc_x_ord)
hc_ll_cat = loc['WAVE_CATALOG'][order_mask]
hc_ll_diff = hc_ll_ord - hc_ll_cat
res_hc.append(hc_ll_diff * speed_of_light / hc_ll_cat)
sumres_hc += np.nansum(res_hc[order])
sumres2_hc += np.nansum(res_hc[order]**2)
total_lines_hc = len(np.concatenate(res_hc))
final_mean_hc = sumres_hc / total_lines_hc
final_var_hc = (sumres2_hc / total_lines_hc) - (final_mean_hc**2)
wmsg1 = 'On fiber {0} HC fit line statistic:'.format(p['FIBER'])
wargs2 = [
final_mean_hc * 1000.0,
np.sqrt(final_var_hc) * 1000.0, total_lines_hc,
1000.0 * np.sqrt(final_var_hc / total_lines_hc)
]
wmsg2 = ('\tmean={0:.3f}[m/s] rms={1:.1f} {2} HC lines (error on mean '
'value:{3:.4f}[m/s])'.format(*wargs2))
WLOG(p, 'info', [wmsg1, wmsg2])
# ----------------------------------------------------------------------
# Save wave map to file
# ----------------------------------------------------------------------
# TODO single file-naming function? Ask Neil
# get base input filenames
bfilenames = []
for raw_file in p['ARG_FILE_NAMES']:
bfilenames.append(os.path.basename(raw_file))
# get wave filename
wavefits, tag1 = spirouConfig.Constants.WAVE_FILE_EA(p)
wavefitsname = os.path.basename(wavefits)
# log progress
WLOG(p, '', 'Saving wave map to {0}'.format(wavefitsname))
# log progress
wargs = [p['FIBER'], wavefitsname]
wmsg = 'Write wavelength solution for Fiber {0} in {1}'
WLOG(p, '', wmsg.format(*wargs))
# write solution to fitsfilename header
# copy original keys
hdict = spirouImage.CopyOriginalKeys(loc['HCHDR'], loc['HCCDR'])
# set the version
hdict = spirouImage.AddKey(p, hdict, p['KW_VERSION'])
# TODO add DRS_DATE and DRS_NOW
hdict = spirouImage.AddKey(p, hdict, p['KW_PID'], value=p['PID'])
hdict = spirouImage.AddKey(p, hdict, p['KW_OUTPUT'], value=tag1)
# set the input files
hdict = spirouImage.AddKey(p, hdict, p['KW_CDBBAD'], value=p['BLAZFILE'])
# add qc parameters
hdict = spirouImage.AddKey(p, hdict, p['KW_DRS_QC'], value=p['QC'])
hdict = spirouImage.AddQCKeys(p, hdict, qc_params)
# add wave solution date
hdict = spirouImage.AddKey(p,
hdict,
p['KW_WAVE_TIME1'],
value=p['MAX_TIME_HUMAN'])
hdict = spirouImage.AddKey(p,
hdict,
p['KW_WAVE_TIME2'],
value=p['MAX_TIME_UNIX'])
hdict = spirouImage.AddKey(p, hdict, p['KW_WAVE_CODE'], value=__NAME__)
hdict = spirouImage.AddKey(p,
hdict,
p['KW_CDBWAVE'],
value=loc['WAVEFILE'])
hdict = spirouImage.AddKey(p,
hdict,
p['KW_WAVESOURCE'],
value=loc['WSOURCE'])
hdict = spirouImage.AddKey1DList(p,
hdict,
p['KW_INFILE1'],
dim1name='file',
values=p['ARG_FILE_NAMES'])
# add number of orders
hdict = spirouImage.AddKey(p,
hdict,
p['KW_WAVE_ORD_N'],
value=loc['POLY_WAVE_SOL'].shape[0])
# add degree of fit
hdict = spirouImage.AddKey(p,
hdict,
p['KW_WAVE_LL_DEG'],
value=loc['POLY_WAVE_SOL'].shape[1] - 1)
# add wave solution
hdict = spirouImage.AddKey2DList(p,
hdict,
p['KW_WAVE_PARAM'],
values=loc['POLY_WAVE_SOL'])
# write the wave "spectrum"
p = spirouImage.WriteImage(p, wavefits, loc['WAVE_MAP2'], hdict)
# get filename for E2DS calibDB copy of FITSFILENAME
e2dscopy_filename, tag2 = spirouConfig.Constants.WAVE_E2DS_COPY(p)
wargs = [p['FIBER'], os.path.split(e2dscopy_filename)[-1]]
wmsg = 'Write reference E2DS spectra for Fiber {0} in {1}'
WLOG(p, '', wmsg.format(*wargs))
# make a copy of the E2DS file for the calibBD
hdict = spirouImage.AddKey(p, hdict, p['KW_OUTPUT'], value=tag2)
p = spirouImage.WriteImage(p, e2dscopy_filename, loc['HCDATA'], hdict)
# ----------------------------------------------------------------------
# Save resolution and line profiles to file
# ----------------------------------------------------------------------
raw_infile = os.path.basename(p['FITSFILENAME'])
# get wave filename
resfits, tag3 = spirouConfig.Constants.WAVE_RES_FILE_EA(p)
resfitsname = os.path.basename(resfits)
WLOG(p, '', 'Saving wave resmap to {0}'.format(resfitsname))
# make a copy of the E2DS file for the calibBD
# set the version
hdict = spirouImage.AddKey(p, hdict, p['KW_VERSION'])
# TODO add DRS_DATE and DRS_NOW
hdict = spirouImage.AddKey(p, hdict, p['KW_OUTPUT'], value=tag3)
# get res data in correct format
resdata, hdicts = spirouWAVE2.generate_res_files(p, loc, hdict)
# save to file
p = spirouImage.WriteImageMulti(p, resfits, resdata, hdicts=hdicts)
# ----------------------------------------------------------------------
# Update calibDB
# ----------------------------------------------------------------------
if p['QC']:
# set the wave key
keydb = 'WAVE_{0}'.format(p['FIBER'])
# copy wave file to calibDB folder
spirouDB.PutCalibFile(p, wavefits)
# update the master calib DB file with new key
spirouDB.UpdateCalibMaster(p, keydb, wavefitsname, loc['HCHDR'])
# set the hcref key
keydb = 'HCREF_{0}'.format(p['FIBER'])
# copy wave file to calibDB folder
spirouDB.PutCalibFile(p, e2dscopy_filename)
# update the master calib DB file with new key
e2dscopyfits = os.path.split(e2dscopy_filename)[-1]
spirouDB.UpdateCalibMaster(p, keydb, e2dscopyfits, loc['HCHDR'])
# ----------------------------------------------------------------------
# Update header of current files
# ----------------------------------------------------------------------
# only copy over if QC passed
if p['QC']:
rdir = os.path.dirname(wavefits)
# loop around hc files and update header with
for rawhcfile in p['ARG_FILE_NAMES']:
hcfile = os.path.join(rdir, rawhcfile)
raw_infilepath1 = os.path.join(p['ARG_FILE_DIR'], hcfile)
p = spirouImage.UpdateWaveSolutionHC(p, loc, raw_infilepath1)
# ----------------------------------------------------------------------
# HC+FP wavelength solution
# ----------------------------------------------------------------------
# check if there's a FP input and if HC solution passed QCs
if has_fp and p['QC']:
# log that we are doing the FP solution
wmsg = 'Now running the combined FP-HC solution, mode = {}'
WLOG(p, 'info', wmsg.format(p['WAVE_MODE_FP']))
# do the wavelength solution
loc = spirouWAVE2.do_fp_wavesol(p, loc)
# ----------------------------------------------------------------------
# Quality control
# ----------------------------------------------------------------------
# get parameters ffrom p
p['QC_RMS_LITTROW_MAX'] = p['QC_HC_RMS_LITTROW_MAX']
p['QC_DEV_LITTROW_MAX'] = p['QC_HC_DEV_LITTROW_MAX']
# set passed variable and fail message list
# passed, fail_msg = True, []
# qc_values, qc_names, qc_logic, qc_pass = [], [], [], []
# ----------------------------------------------------------------------
# check the difference between consecutive orders is always positive
# get the differences
wave_diff = loc['LL_FINAL'][1:] - loc['LL_FINAL'][:-1]
if np.min(wave_diff) < 0:
fmsg = 'Negative wavelength difference between orders'
fail_msg.append(fmsg)
passed = False
qc_pass.append(0)
else:
qc_pass.append(1)
# add to qc header lists
qc_values.append(np.min(wave_diff))
qc_names.append('MIN WAVE DIFF FP-HC')
qc_logic.append('MIN WAVE DIFF < 0')
# ----------------------------------------------------------------------
# check for infinites and NaNs in mean residuals from fit
if ~np.isfinite(loc['X_MEAN_2']):
# add failed message to the fail message list
fmsg = 'NaN or Inf in X_MEAN_2'
fail_msg.append(fmsg)
passed = False
qc_pass.append(0)
else:
qc_pass.append(1)
# add to qc header lists
qc_values.append(loc['X_MEAN_2'])
qc_names.append('X_MEAN_2')
qc_logic.append('X_MEAN_2 not finite')
# ----------------------------------------------------------------------
# iterate through Littrow test cut values
lit_it = 2
# checks every other value
# TODO: This QC check (or set of QC checks needs re-writing it is
# TODO: nearly impossible to understand
for x_it in range(1, len(loc['X_CUT_POINTS_' + str(lit_it)]), 2):
# get x cut point
x_cut_point = loc['X_CUT_POINTS_' + str(lit_it)][x_it]
# get the sigma for this cut point
sig_littrow = loc['LITTROW_SIG_' + str(lit_it)][x_it]
# get the abs min and max dev littrow values
min_littrow = abs(loc['LITTROW_MINDEV_' + str(lit_it)][x_it])
max_littrow = abs(loc['LITTROW_MAXDEV_' + str(lit_it)][x_it])
# get the corresponding order
min_littrow_ord = loc['LITTROW_MINDEVORD_' + str(lit_it)][x_it]
max_littrow_ord = loc['LITTROW_MAXDEVORD_' + str(lit_it)][x_it]
# check if sig littrow is above maximum
rms_littrow_max = p['QC_RMS_LITTROW_MAX']
dev_littrow_max = p['QC_DEV_LITTROW_MAX']
if sig_littrow > rms_littrow_max:
fmsg = ('Littrow test (x={0}) failed (sig littrow = '
'{1:.2f} > {2:.2f})')
fargs = [x_cut_point, sig_littrow, rms_littrow_max]
fail_msg.append(fmsg.format(*fargs))
passed = False
qc_pass.append(0)
else:
qc_pass.append(1)
# add to qc header lists
qc_values.append(sig_littrow)
qc_names.append('sig_littrow')
qc_logic.append('sig_littrow > {0:.2f}'.format(rms_littrow_max))
# ----------------------------------------------------------------------
# check if min/max littrow is out of bounds
if np.max([max_littrow, min_littrow]) > dev_littrow_max:
fmsg = ('Littrow test (x={0}) failed (min|max dev = '
'{1:.2f}|{2:.2f} > {3:.2f} for order {4}|{5})')
fargs = [
x_cut_point, min_littrow, max_littrow, dev_littrow_max,
min_littrow_ord, max_littrow_ord
]
fail_msg.append(fmsg.format(*fargs))
passed = False
qc_pass.append(0)
# TODO: Should this be the QC header values?
# TODO: it does not change the outcome of QC (i.e. passed=False)
# TODO: So what is the point?
# if sig was out of bounds, recalculate
if sig_littrow > rms_littrow_max:
# conditions
check1 = min_littrow > dev_littrow_max
check2 = max_littrow > dev_littrow_max
# get the residuals
respix = loc['LITTROW_YY_' + str(lit_it)][x_it]
# check if both are out of bounds
if check1 and check2:
# remove respective orders
worst_order = (min_littrow_ord, max_littrow_ord)
respix_2 = np.delete(respix, worst_order)
redo_sigma = True
# check if min is out of bounds
elif check1:
# remove respective order
worst_order = min_littrow_ord
respix_2 = np.delete(respix, worst_order)
redo_sigma = True
# check if max is out of bounds
elif check2:
# remove respective order
worst_order = max_littrow_ord
respix_2 = np.delete(respix, max_littrow_ord)
redo_sigma = True
# else do not recalculate sigma
else:
redo_sigma, respix_2, worst_order = False, None, None
wmsg = 'No outlying orders, sig littrow not recalculated'
fail_msg.append(wmsg.format())
# if outlying order, recalculate stats
if redo_sigma:
mean = np.nansum(respix_2) / len(respix_2)
mean2 = np.nansum(respix_2**2) / len(respix_2)
rms = np.sqrt(mean2 - mean**2)
if rms > rms_littrow_max:
fmsg = (
'Littrow test (x={0}) failed (sig littrow = '
'{1:.2f} > {2:.2f} removing order {3})')
fargs = [
x_cut_point, rms, rms_littrow_max, worst_order
]
fail_msg.append(fmsg.format(*fargs))
else:
wargs = [
x_cut_point, rms, rms_littrow_max, worst_order
]
wmsg = (
'Littrow test (x={0}) passed (sig littrow = '
'{1:.2f} > {2:.2f} removing order {3})')
fail_msg.append(wmsg.format(*wargs))
else:
qc_pass.append(1)
# add to qc header lists
qc_values.append(np.max([max_littrow, min_littrow]))
qc_names.append('max or min littrow')
qc_logic.append('max or min littrow > {0:.2f}'
''.format(dev_littrow_max))
# finally log the failed messages and set QC = 1 if we pass the
# quality control QC = 0 if we fail quality control
if passed:
WLOG(p, 'info', 'QUALITY CONTROL SUCCESSFUL - Well Done -')
p['QC'] = 1
p.set_source('QC', __NAME__ + '/main()')
else:
for farg in fail_msg:
wmsg = 'QUALITY CONTROL FAILED: {0}'
WLOG(p, 'warning', wmsg.format(farg))
p['QC'] = 0
p.set_source('QC', __NAME__ + '/main()')
# store in qc_params
qc_params = [qc_names, qc_values, qc_logic, qc_pass]
# ------------------------------------------------------------------
# archive result in e2ds spectra
# ------------------------------------------------------------------
# get raw input file name(s)
raw_infiles1 = []
for hcfile in p['HCFILES']:
raw_infiles1.append(os.path.basename(hcfile))
raw_infile2 = os.path.basename(p['FPFILE'])
# get wave filename
wavefits, tag1 = spirouConfig.Constants.WAVE_FILE_EA_2(p)
wavefitsname = os.path.split(wavefits)[-1]
# log progress
wargs = [p['FIBER'], wavefits]
wmsg = 'Write wavelength solution for Fiber {0} in {1}'
WLOG(p, '', wmsg.format(*wargs))
# write solution to fitsfilename header
# copy original keys
hdict = spirouImage.CopyOriginalKeys(loc['HCHDR'], loc['HCCDR'])
# add version number
hdict = spirouImage.AddKey(p, hdict, p['KW_VERSION'])
hdict = spirouImage.AddKey(p, hdict, p['KW_PID'], value=p['PID'])
# set the input files
hdict = spirouImage.AddKey(p,
hdict,
p['KW_CDBBAD'],
value=p['BLAZFILE'])
hdict = spirouImage.AddKey(p,
hdict,
p['KW_CDBWAVE'],
value=loc['WAVEFILE'])
hdict = spirouImage.AddKey(p,
hdict,
p['KW_WAVESOURCE'],
value=loc['WSOURCE'])
hdict = spirouImage.AddKey1DList(p,
hdict,
p['KW_INFILE1'],
dim1name='fpfile',
values=p['FPFILE'])
hdict = spirouImage.AddKey1DList(p,
hdict,
p['KW_INFILE2'],
dim1name='hcfile',
values=p['HCFILES'])
# add qc parameters
hdict = spirouImage.AddKey(p, hdict, p['KW_DRS_QC'], value=p['QC'])
hdict = spirouImage.AddQCKeys(p, hdict, qc_params)
# add wave solution date
hdict = spirouImage.AddKey(p,
hdict,
p['KW_WAVE_TIME1'],
value=p['MAX_TIME_HUMAN'])
hdict = spirouImage.AddKey(p,
hdict,
p['KW_WAVE_TIME2'],
value=p['MAX_TIME_UNIX'])
hdict = spirouImage.AddKey(p, hdict, p['KW_WAVE_CODE'], value=__NAME__)
# add number of orders
hdict = spirouImage.AddKey(p,
hdict,
p['KW_WAVE_ORD_N'],
value=loc['LL_PARAM_FINAL'].shape[0])
# add degree of fit
hdict = spirouImage.AddKey(p,
hdict,
p['KW_WAVE_LL_DEG'],
value=loc['LL_PARAM_FINAL'].shape[1] - 1)
# add wave solution
hdict = spirouImage.AddKey2DList(p,
hdict,
p['KW_WAVE_PARAM'],
values=loc['LL_PARAM_FINAL'])
# add FP CCF drift
# target RV and width
hdict = spirouImage.AddKey(p,
hdict,
p['KW_WFP_TARG_RV'],
value=p['TARGET_RV'])
hdict = spirouImage.AddKey(p,
hdict,
p['KW_WFP_WIDTH'],
value=p['CCF_WIDTH'])
# the rv step
# rvstep = np.abs(loc['RV_CCF'][0] - loc['RV_CCF'][1])
# hdict = spirouImage.AddKey(p, hdict, p['KW_CCF_CDELT'], value=rvstep)
hdict = spirouImage.AddKey(p,
hdict,
p['KW_WFP_STEP'],
value=p['CCF_STEP'])
# add ccf stats
hdict = spirouImage.AddKey(p,
hdict,
p['KW_WFP_DRIFT'],
value=loc['CCF_RES'][1])
hdict = spirouImage.AddKey(p,
hdict,
p['KW_WFP_FWHM'],
value=loc['FWHM'])
hdict = spirouImage.AddKey(p,
hdict,
p['KW_WFP_CONTRAST'],
value=loc['CONTRAST'])
hdict = spirouImage.AddKey(p,
hdict,
p['KW_WFP_MAXCPP'],
value=loc['MAXCPP'])
hdict = spirouImage.AddKey(p,
hdict,
p['KW_WFP_MASK'],
value=p['CCF_MASK'])
hdict = spirouImage.AddKey(p,
hdict,
p['KW_WFP_LINES'],
value=np.nansum(loc['TOT_LINE']))
# write the wave "spectrum"
hdict = spirouImage.AddKey(p, hdict, p['KW_OUTPUT'], value=tag1)
p = spirouImage.WriteImage(p, wavefits, loc['LL_FINAL'], hdict)
# get filename for E2DS calibDB copy of FITSFILENAME
e2dscopy_filename = spirouConfig.Constants.WAVE_E2DS_COPY(p)[0]
wargs = [p['FIBER'], os.path.split(e2dscopy_filename)[-1]]
wmsg = 'Write reference E2DS spectra for Fiber {0} in {1}'
WLOG(p, '', wmsg.format(*wargs))
# make a copy of the E2DS file for the calibBD
p = spirouImage.WriteImage(p, e2dscopy_filename, loc['HCDATA'], hdict)
# only copy over if QC passed
if p['QC']:
# loop around hc files and update header with
for hcfile in p['HCFILES']:
raw_infilepath1 = os.path.join(p['ARG_FILE_DIR'], hcfile)
p = spirouImage.UpdateWaveSolution(p, loc, raw_infilepath1)
# update fp file
raw_infilepath2 = os.path.join(p['ARG_FILE_DIR'], raw_infile2)
p = spirouImage.UpdateWaveSolution(p, loc, raw_infilepath2)
# ------------------------------------------------------------------
# Save to result table
# ------------------------------------------------------------------
# calculate stats for table
final_mean = 1000 * loc['X_MEAN_2']
final_var = 1000 * loc['X_VAR_2']
num_lines = loc['TOTAL_LINES_2']
err = 1000 * np.sqrt(loc['X_VAR_2'] / num_lines)
sig_littrow = 1000 * np.array(loc['LITTROW_SIG_' + str(lit_it)])
# construct filename
wavetbl = spirouConfig.Constants.WAVE_TBL_FILE_EA(p)
wavetblname = os.path.basename(wavetbl)
# construct and write table
columnnames = [
'night_name', 'file_name', 'fiber', 'mean', 'rms', 'N_lines',
'err', 'rms_L500', 'rms_L1000', 'rms_L1500', 'rms_L2000',
'rms_L2500', 'rms_L3000', 'rms_L3500'
]
columnformats = [
'{:20s}', '{:30s}', '{:3s}', '{:7.4f}', '{:6.2f}', '{:3d}',
'{:6.3f}', '{:6.2f}', '{:6.2f}', '{:6.2f}', '{:6.2f}', '{:6.2f}',
'{:6.2f}', '{:6.2f}'
]
columnvalues = [[p['ARG_NIGHT_NAME']], [p['ARG_FILE_NAMES'][0]],
[p['FIBER']], [final_mean], [final_var], [num_lines],
[err], [sig_littrow[0]], [sig_littrow[1]],
[sig_littrow[2]], [sig_littrow[3]], [sig_littrow[4]],
[sig_littrow[5]], [sig_littrow[6]]]
# make table
table = spirouImage.MakeTable(p,
columns=columnnames,
values=columnvalues,
formats=columnformats)
# merge table
wmsg = 'Global result summary saved in {0}'
WLOG(p, '', wmsg.format(wavetblname))
spirouImage.MergeTable(p, table, wavetbl, fmt='ascii.rst')
# ------------------------------------------------------------------
# Save line list table file
# ------------------------------------------------------------------
# construct filename
# TODO proper column values
wavelltbl = spirouConfig.Constants.WAVE_LINE_FILE_EA(p)
wavelltblname = os.path.split(wavelltbl)[-1]
# construct and write table
columnnames = ['order', 'll', 'dv', 'w', 'xi', 'xo', 'dvdx']
columnformats = [
'{:.0f}', '{:12.4f}', '{:13.5f}', '{:12.4f}', '{:12.4f}',
'{:12.4f}', '{:8.4f}'
]
columnvalues = []
# construct column values (flatten over orders)
for it in range(len(loc['X_DETAILS_2'])):
for jt in range(len(loc['X_DETAILS_2'][it][0])):
row = [
float(it), loc['X_DETAILS_2'][it][0][jt],
loc['LL_DETAILS_2'][it][0][jt],
loc['X_DETAILS_2'][it][3][jt],
loc['X_DETAILS_2'][it][1][jt],
loc['X_DETAILS_2'][it][2][jt], loc['SCALE_2'][it][jt]
]
columnvalues.append(row)
# log saving
wmsg = 'List of lines used saved in {0}'
WLOG(p, '', wmsg.format(wavelltblname))
# make table
columnvalues = np.array(columnvalues).T
table = spirouImage.MakeTable(p,
columns=columnnames,
values=columnvalues,
formats=columnformats)
# write table
spirouImage.WriteTable(p, table, wavelltbl, fmt='ascii.rst')
# ------------------------------------------------------------------
# Move to calibDB and update calibDB
# ------------------------------------------------------------------
if p['QC']:
# set the wave key
keydb = 'WAVE_{0}'.format(p['FIBER'])
# copy wave file to calibDB folder
spirouDB.PutCalibFile(p, wavefits)
# update the master calib DB file with new key
spirouDB.UpdateCalibMaster(p, keydb, wavefitsname, loc['HCHDR'])
# set the hcref key
keydb = 'HCREF_{0}'.format(p['FIBER'])
# copy wave file to calibDB folder
spirouDB.PutCalibFile(p, e2dscopy_filename)
# update the master calib DB file with new key
e2dscopyfits = os.path.split(e2dscopy_filename)[-1]
spirouDB.UpdateCalibMaster(p, keydb, e2dscopyfits, loc['HCHDR'])
# If the HC solution failed QCs we do not compute FP-HC solution
elif has_fp and not p['QC']:
wmsg = 'HC solution failed quality controls; FP not processed'
WLOG(p, 'warning', wmsg)
# If there is no FP file we log that
elif not has_fp:
wmsg = 'No FP file given; FP-HC combined solution cannot be generated'
WLOG(p, 'warning', wmsg)
# ----------------------------------------------------------------------
# End Message
# ----------------------------------------------------------------------
p = spirouStartup.End(p)
# return p and loc
return dict(locals())
