From 807c49efbb94ff3424438d9c985f5683c969c3ac Mon Sep 17 00:00:00 2001
From: Daniel Adriaansen <dadriaan@ucar.edu>
Date: Mon, 23 Dec 2024 22:24:35 +0000
Subject: [PATCH] Removes erroneous code from script that this script was
 copied from.

---
 .../create_raob_mask_file.py                  | 87 -------------------
 1 file changed, 87 deletions(-)

diff --git a/parm/use_cases/model_applications/land_surface/PointStat_fcstUFS_obsGDAS_CTP_HI/create_raob_mask_file.py b/parm/use_cases/model_applications/land_surface/PointStat_fcstUFS_obsGDAS_CTP_HI/create_raob_mask_file.py
index 4eeb6c6f4..0d2f17597 100644
--- a/parm/use_cases/model_applications/land_surface/PointStat_fcstUFS_obsGDAS_CTP_HI/create_raob_mask_file.py
+++ b/parm/use_cases/model_applications/land_surface/PointStat_fcstUFS_obsGDAS_CTP_HI/create_raob_mask_file.py
@@ -46,90 +46,3 @@
 # Write out the text file that GenVxMask needs
 point_data['latlon'].astype('object').to_csv(outfile,index=False,sep=' ',header=['RAOB_SITES'],quoting=3,escapechar=' ')
 
-exit()
-
-# Array to hold the CTP values for each station
-ctp = np.array([])
-
-# Process each group, which is defined as a single site
-# Each site will have the MET 11-column data.
-for name,group in groups:
-
-  print("")
-  print("PROCESSING SITE: %s" % (name))
-  
-  # First, make sure there is only one valid time
-  timegrp = group.groupby('vld')
-  if timegrp.ngroups>1:
-    print("INFO: FOUND MULTIPLE SOUNDINGS FOR THIS SITE.")
-    print("USING THE FIRST")
-    timegrp_name = [sg_name for sg_name,sg_df in timegrp]
-    prof = timegrp.get_group(timegrp_name[0])
-  else:
-    prof = group
-
-  # Filter out stations that we don't want to process
-  if name not in point_data['sid'].values.tolist():
-    continue
-
-  # In each group here, there are rows for each variable at each pressure level.
-  # Thus, we can subset based on TMP and just use the pressure data for TMP.
-  sub = prof[prof['var']=='TMP']
-
-  # Ensure the temperature subset has data
-  if len(sub)==0:
-    print("ERROR! NO TMP DATA.")
-    print("UNABLE TO COMPUTE CTP FOR SID: %s" % (name))
-    ctp = np.append(ctp,-9999.)
-    continue
-
-  # Subset out the data for this site into individual arrays
-  # and add units using MetPy
-  tmpsub = sub['obs'].astype('float').values*units('degK')
-  prssub = sub['lvl'].astype('float').values*units('hPa')
-  qcsub = sub['qc'].astype('int').values
-
-  # The pressures must exceed 300 hPa above the lowest in the sounding
-  if max(prssub.m)<= min(prssub.m+300.0):
-    print("ERROR! SOUNDING TOP PRESSURE DOES NOT EXCEED 300 hPa ABOVE THE LOWEST PRESSURE.")
-    print("UNABLE TO COMPUTE CTP FOR SID: %s" % (name))
-    ctp = np.append(ctp,-9999.)
-  else:
-    # Append the CTP value
-    thisctp = land_surface.calc_ctp(prssub,tmpsub)
-    ctp = np.append(ctp,thisctp.m)
-
-# After each station is processed, add in the missing 11-column data
-# lvl --> set to 1000.0
-# hgt --> set to 0
-# qc --> set to 'NA' for now
-# var --> set to "CTP"
-# typ --> reset from ADPUPA to ADPSFC
-point_data['obs'] = ctp
-point_data['lvl'] = [1000.0]*len(point_data)
-point_data['hgt'] = [0]*len(point_data)
-point_data['qc'] = ['NA']*len(point_data)
-point_data['var'] = ['CTP']*len(point_data)
-point_data['typ'] = ['ADPSFC']*len(point_data)
-
-# Assign proper dtypes
-met_col_dtypes = {'typ':'string',
-                  'sid':'string',
-                  'vld':'string',
-                  'lat':'float64',
-                  'lon':'float64',
-                  'elv':'float64',
-                  'var':'string',
-                  'lvl':'float64',
-                  'hgt':'float64',
-                  'qc':'string',
-                  'obs':'float64'}
-point_data = point_data.astype(met_col_dtypes)
-
-# Reorder the columns to be correct
-point_data = point_data[['typ','sid','vld','lat','lon','elv','var','lvl','hgt','qc','obs']]
-
-print(point_data)
-
-# Convert to MET object
-point_data = point_data.values.tolist()