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')