added csv pull

utils/eval_baselines.py

@@ -79,11 +79,11 @@ def main(dim):
  for path in tqdm(file_paths):
  with fits.open(path) as hdul:
  if dim == '2d':
- arr = hdul[1].data[0][0]
+ arrs = [hdul[1].data[0][0]]
  elif dim == '2d_diffs' and len(hdul[1].data[0]) > 1:
- arr = hdul[1].data[0][1] - hdul[1].data[0][0]
+ arrs = [hdul[1].data[0][i + 1] - hdul[1].data[0][i] for i in range(len(hdul[1].data[0]) - 1)]
  elif dim == '3dt' and len(hdul[1].data[0]) > 2:
- arr = hdul[1].data[0][0:3]
+ arrs = [hdul[1].data[0][0:3]]
  else:
  continue
 
@@ -91,21 +91,21 @@ def main(dim):
  if ct % 10 == 0:
  print(df.mean())
  df.to_csv(save_path)
+ for group, arr in enumerate(arrs):
+ for algo in ALL_CODECS.keys():
+ try:
+ if algo == "JPEG_2K" and dim == '3dt':
+ test_results = benchmark_imagecodecs_compression_algos(arr.transpose(1, 2, 0), algo)
+ else:
+ test_results = benchmark_imagecodecs_compression_algos(arr, algo)
+
+ for column, value in test_results.items():
+ if column in df.columns:
+ df.at[path + f"_{group}", column] = value
+
+ except Exception as e:
+ print(f"Failed at {path} under exception {e}.")
 
- for algo in ALL_CODECS.keys():
- try:
- if algo == "JPEG_2K" and dim == '3dt':
- test_results = benchmark_imagecodecs_compression_algos(arr.transpose(1, 2, 0), algo)
- else:
- test_results = benchmark_imagecodecs_compression_algos(arr, algo)
- 
- for column, value in test_results.items():
- if column in df.columns:
- df.at[path, column] = value
- 
- except Exception as e:
- print(f"Failed at {path} under exception {e}.")
- 
 
 if __name__ == "__main__":
  parser = argparse.ArgumentParser(description="Process some 2D or 3D data.")

utils/pull_jwst_csv.py

@@ -0,0 +1,280 @@
+from astroquery.mast.missions import MastMissions
+
+missions = MastMissions(mission='jwst')
+
+"""
+Used to pull the list of observations that fit our filter criteria from 
+online JWST archives. See all filter details in the function call below.
+
+If your API query here times out, you may have to manually search into the UI here, and download as CSV:
+https://mast.stsci.edu/search/ui
+
+Use the parameters outlined below when searching.
+"""
+
+# Use query_criteria method to use selected form search conditions for making missions_mast search API call
+results = missions.query_criteria(select_cols=[
+ 'act_id',
+ 'targname',
+ 'ang_sep',
+ 'apername',
+ 'intarget',
+ 'bkgmeth',
+ 'bkgdtarg',
+ 'bartdelt',
+ 'cal_vcs',
+ 'cal_ver',
+ 'bkglevel',
+ 'bkgsub',
+ 'miri_cccstate',
+ 'cont_id',
+ 'crds_ver',
+ 'crds_ctx',
+ 'fileSetName',
+ 'date_end',
+ 'date_beg',
+ 'targ_dec',
+ 'miri_detmode',
+ 'miri_ditchdirc',
+ 'miri_dithopfr',
+ 'pixfrac',
+ 'effexptm',
+ 'effexptm',
+ 'effinttm',
+ 'intend',
+ 'eng_qual',
+ 'errtype',
+ 'duration',
+ 'exp_type',
+ 'expend',
+ 'is_psf',
+ 'expmid',
+ 'exposure',
+ 'expstart',
+ 'fastaxis',
+ 'fgs_focuspos',
+ 'filter',
+ 'gainfact',
+ 'nirspec_gwa_ytilt',
+ 'nirspec_gwa_xtilt',
+ 'gs_dec',
+ 'gs_udec',
+ 'gdstarid',
+ 'gs_order',
+ 'gs_mag',
+ 'gs_umag',
+ 'gs_dra',
+ 'gs_ura',
+ 'gsendtim',
+ 'gsstrttm',
+ 'nirspec_gwa_pxav',
+ 'nirspec_gwa_pyav',
+ 'nirspec_gwa_tilt',
+ 'nirspec_gwa_xp_v',
+ 'nirspec_gwa_yp_v',
+ 'helidelt',
+ 'hendtime',
+ 'hmidtime',
+ 'hstrtime',
+ 'hga_move',
+ 'origin',
+ 'instrume',
+ 'lamp',
+ 'opmode',
+ 'masterbg',
+ 'miri_coronmsk',
+ 'miri_mirnfrms',
+ 'miri_mirngrps',
+ 'miri_channel',
+ 'miri_pattnpts',
+ 'miri_spat_num',
+ 'miri_spec_num',
+ 'miri_band',
+ 'nirspec_msaconid',
+ 'nirspec_msametfl',
+ 'nirspec_msametid',
+ 'detector',
+ 'nirspec_fxd_slit',
+ 'nircam_smgrdpat',
+ 'obsfolder',
+ 'asntable',
+ 'asnpool',
+ 'nirspec_grating',
+ 'nircam_pupil',
+ 'nwfsest',
+ 'nircam_channel',
+ 'nircam_coronmsk',
+ 'nircam_module',
+ 'niriss_fwcpos',
+ 'niriss_focuspos',
+ 'niriss_pupil',
+ 'niriss_pwcpos',
+ 'nirspec_focuspos',
+ 'nirspec_is_imprt',
+ 'nirspec_spat_num',
+ 'nirspec_spec_num',
+ 'nirspec_nod_type',
+ 'miri_numdsets',
+ 'nsamples',
+ 'noutputs',
+ 'nextend',
+ 'groupgap',
+ 'drpfrms3',
+ 'drpfrms1',
+ 'nframes',
+ 'ngroups',
+ 'nints',
+ 'nirspec_nrs_norm',
+ 'subsize1',
+ 'subsize2',
+ 'niriss_nrimdtpt',
+ 'pridtpts',
+ 'subpxpts',
+ 'nirspec_nrs_ref',
+ 'nrststrt',
+ 'nresets',
+ 'miri_spatnstp',
+ 'miri_specnstp',
+ 'obslabel',
+ 'observtn',
+ 'oss_ver',
+ 'osf_file',
+ 'visitend',
+ 'opticalElements',
+ 'miri_mrsprchn',
+ 'pps_aper',
+ 'seq_id',
+ 'pi_name',
+ 'pxsclrt',
+ 'miri_dithpnts',
+ 'nirspec_dithpnts',
+ 'pcs_mode',
+ 'nircam_fam_la1',
+ 'nircam_fam_la2',
+ 'nircam_fam_la3',
+ 'patt_num',
+ 'datamode',
+ 'nirspec_preimage',
+ 'pwfseet',
+ 'pattsize',
+ 'patttype',
+ 'nircam_pridtype',
+ 'expripar',
+ 'timesys',
+ 'productLevel',
+ 'program',
+ 'category',
+ 'subcat',
+ 'proposal_type',
+ 'obs_id',
+ 'proposal_cycle',
+ 'title',
+ 'prop_dec',
+ 'prop_ra',
+ 'nircam_pilin',
+ 'targ_ra',
+ 'readpatt',
+ 'nirspec_rma_pos',
+ 'nirspec_fcsrlpos',
+ 'publicReleaseDate',
+ 'nircam_fa1value',
+ 'nircam_faphase1',
+ 'nircam_fastep1',
+ 'nircam_faunit1',
+ 'nircam_fa2value',
+ 'nircam_faphase2',
+ 'nircam_fastep2',
+ 'nircam_faunit2',
+ 'nircam_fa3value',
+ 'nircam_faphase3',
+ 'nircam_fastep3',
+ 'nircam_faunit3',
+ 'expcount',
+ 'prd_ver',
+ 'scicat',
+ 'dataprob',
+ 'segmfile',
+ 'selfref',
+ 'sca_num',
+ 'exsegnum',
+ 'rois',
+ 'roiw',
+ 'miri_spatstep',
+ 'miri_specstep',
+ 'slowaxis',
+ 'scatfile',
+ 'engqlptg',
+ 'sctarate',
+ 'miri_sptoffst',
+ 'exp_only',
+ 'miri_spcoffst',
+ 'date_obs',
+ 'miri_dsetstrt',
+ 'intstart',
+ 'substrt1',
+ 'substrt2',
+ 'miri_pattstrt',
+ 'nirspec_pattstrt',
+ 'nirspec_msastate',
+ 'access',
+ 'visitsta',
+ 'subarray',
+ 'nircam_subpxpat',
+ 'nirspec_subpxpat',
+ 'targcat',
+ 'targudec',
+ 'targdesc',
+ 'targprop',
+ 'mu_epoch',
+ 'mu_dec',
+ 'mu_ra',
+ 'targura',
+ 'targtype',
+ 'bstrtime',
+ 'bendtime',
+ 'bmidtime',
+ 'telescop',
+ 'template',
+ 'miri_cmd_tsel',
+ 'tframe',
+ 'tgroup',
+ 'tsample',
+ 'tsovisit',
+ 'texptime',
+ 'texptime',
+ 'nexposur',
+ 'numdthpt',
+ 'exsegtot',
+ 'tcatfile',
+ 'datamodl',
+ 'date',
+ 'expsteng',
+ 'gsendtim',
+ 'gsstrttm',
+ 'vststart',
+ 'gs_v3_pa',
+ 'frmdivsr',
+ 'va_dec',
+ 'va_ra',
+ 'visitgrp',
+ 'visid_id',
+ 'visit',
+ 'targoopp',
+ 'visitype',
+ 'wpower',
+ 'wtype',
+ 'dirimage',
+ 'xoffset',
+ 'yoffset',
+ 'zerofram'], exp_type='NRC_IMAGE',
+ instrume='NIRCAM',
+ opticalElements='*F200W;CLEAR*',
+ productLevel='*1b*',
+ targtype='FIXED',
+ visitsta='SUCCESSFUL',
+ access='PUBLIC',
+ effinttm='>30')
+
+df = results.to_pandas()
+print(len(df))
+df.to_csv('jwst_FINAL.csv')