diff --git a/scripts/00_scox1_lightcurve.py b/scripts/00_scox1_lightcurve.py
index 1492459..e9fe5e4 100755
--- a/scripts/00_scox1_lightcurve.py
+++ b/scripts/00_scox1_lightcurve.py
@@ -42,7 +42,7 @@ enkey='A01'
 inkey="ALL"
 
 fn="detcnts.{}.{}.resid.fits".format(enkey,inkey)
-dat = Table.read(proddir+fn, unit_parse_strict='silent')
+dat = Table.read(proddir+fn)
 df = dat.to_pandas()
 
 with open(proddir+"detcnts.{}.ignored_scw.pkl".format(enkey), 'rb') as fp:
diff --git a/scripts/00_stats.py b/scripts/00_stats.py
index e79460d..51f7e48 100755
--- a/scripts/00_stats.py
+++ b/scripts/00_stats.py
@@ -49,7 +49,7 @@ print("Total {} ScWs, {:.1f} Ms".format(df_tot.shape[0], np.sum(df_tot['EXPOSURE
 
 fn="detcnts.{}.{}.resid.fits".format(enkey,inkey)
 print("Reading {}".format(proddir+fn))
-dat = Table.read(proddir+fn, unit_parse_strict='silent')
+dat = Table.read(proddir+fn)
 df = dat.to_pandas()
 
 df_bkg = df.query('REV >= {} & REV< {} & CLEAN > 0.0 & ( abs(LAT) > {} | abs(LON) > {}) & PHASE > {} & PHASE < {}'.format(revmin,revmax,bmax,lmax,phmin,phmax))
diff --git a/scripts/01_crabmodel_plot_poly.py b/scripts/01_crabmodel_plot_poly.py
index fdd50fe..9f88828 100755
--- a/scripts/01_crabmodel_plot_poly.py
+++ b/scripts/01_crabmodel_plot_poly.py
@@ -15,15 +15,15 @@ from ridge.config import *
 scale = 1e-3
 
 fn="detcnts.A01.crabmodel.fits"
-dat = Table.read(proddir+fn, unit_parse_strict='silent')
+dat = Table.read(proddir+fn)
 df1 = dat.to_pandas().sort_values(by=['REV'])
 
 fn="detcnts.A02.crabmodel.fits"
-dat = Table.read(proddir+fn, unit_parse_strict='silent')
+dat = Table.read(proddir+fn)
 df2 = dat.to_pandas().sort_values(by=['REV'])
 
 fn="detcnts.A03.crabmodel.fits"
-dat = Table.read(proddir+fn, unit_parse_strict='silent')
+dat = Table.read(proddir+fn)
 df3 = dat.to_pandas().sort_values(by=['REV'])
 
 
diff --git a/scripts/01_crabmodel_plot_sys.py b/scripts/01_crabmodel_plot_sys.py
index 86443b3..08394ea 100755
--- a/scripts/01_crabmodel_plot_sys.py
+++ b/scripts/01_crabmodel_plot_sys.py
@@ -17,15 +17,15 @@ scale = 1e-3
 nbins=30
 
 fn="detcnts.A01.crabmodel.fits"
-dat = Table.read(proddir+fn, unit_parse_strict='silent')
+dat = Table.read(proddir+fn)
 df1 = dat.to_pandas().sort_values(by=['REV'])
 
 fn="detcnts.A02.crabmodel.fits"
-dat = Table.read(proddir+fn, unit_parse_strict='silent')
+dat = Table.read(proddir+fn)
 df2 = dat.to_pandas().sort_values(by=['REV'])
 
 fn="detcnts.A03.crabmodel.fits"
-dat = Table.read(proddir+fn, unit_parse_strict='silent')
+dat = Table.read(proddir+fn)
 df3 = dat.to_pandas().sort_values(by=['REV'])
 
 
diff --git a/scripts/02_grxe_resid_plot.py b/scripts/02_grxe_resid_plot.py
index 5298e6a..c047639 100755
--- a/scripts/02_grxe_resid_plot.py
+++ b/scripts/02_grxe_resid_plot.py
@@ -50,7 +50,7 @@ ign=ignored_rev.tolist()
 
 enkey="A01"
 fn="detcnts.{}.{}.resid.fits".format(enkey,inkey)
-dat = Table.read(proddir+fn, unit_parse_strict='silent')
+dat = Table.read(proddir+fn)
 df = dat.to_pandas()
 print("N={}".format(df.shape[0]))
 query = "REV != @ign"
@@ -67,7 +67,7 @@ sg_mean,sg_sem,skew_val,skew_err = get_spec(df, sigma=sigma,  grxe_err_cut=grxe_
 
 enkey="A02"
 fn="detcnts.{}.{}.resid.fits".format(enkey,inkey)
-dat = Table.read(proddir+fn, unit_parse_strict='silent')
+dat = Table.read(proddir+fn)
 df = dat.to_pandas()
 print("N={}".format(df.shape[0]))
 query = "REV != @ign"
@@ -84,7 +84,7 @@ sg_mean,sg_sem, skew_val, skew_err = get_spec(df, sigma=sigma,  grxe_err_cut=grx
 
 enkey="A03"
 fn="detcnts.{}.{}.resid.fits".format(enkey,inkey)
-dat = Table.read(proddir+fn, unit_parse_strict='silent')
+dat = Table.read(proddir+fn)
 df = dat.to_pandas()
 print("N={}".format(df.shape[0]))
 query = "REV != @ign"
@@ -103,13 +103,13 @@ sg_mean,sg_sem, skew_val, skew_err = get_spec(df, sigma=sigma,  grxe_err_cut=grx
 ### 
 
 scale=1.0E-2
-dat = Table.read(fresid1, unit_parse_strict='silent')
+dat = Table.read(fresid1)
 df1 = dat.to_pandas().sort_values(by=['REV'])
 
-dat = Table.read(fresid2, unit_parse_strict='silent')
+dat = Table.read(fresid2)
 df2 = dat.to_pandas().sort_values(by=['REV'])
 
-dat = Table.read(fresid3, unit_parse_strict='silent')
+dat = Table.read(fresid3)
 df3 = dat.to_pandas().sort_values(by=['REV'])
 
 s=2
diff --git a/scripts/03_grxe_flux.py b/scripts/03_grxe_flux.py
index 2cf8710..68c7b6e 100755
--- a/scripts/03_grxe_flux.py
+++ b/scripts/03_grxe_flux.py
@@ -74,7 +74,7 @@ for skey in skeys:
     for enkey in ebands0.keys():
         fn="detcnts.{}.{}.resid.fits".format(enkey,inkey)
         print("Reading {}".format(proddir+fn))
-        dat = Table.read(proddir+fn, unit_parse_strict='silent')
+        dat = Table.read(proddir+fn) 
         df = dat.to_pandas()
 
         query = "LON > {} & LON < {} & LAT > {} & LAT < {} & REV != @ign".format(
diff --git a/scripts/03_grxe_galprof.py b/scripts/03_grxe_galprof.py
index 78f9f2a..36aedb6 100755
--- a/scripts/03_grxe_galprof.py
+++ b/scripts/03_grxe_galprof.py
@@ -46,7 +46,7 @@ key="ALL"
 fn='detcnts.{}.{}.resid.fits'.format(enkey,key)
 
 print("Reading {}".format(proddir+fn))
-dat = Table.read(proddir+fn, unit_parse_strict='silent')
+dat = Table.read(proddir+fn)
 df = dat.to_pandas()
 
 #df = df.query('abs(LAT) < {} & abs(LON) < {}'.format(5,5))
diff --git a/scripts/03_grxe_galprof_plot.py b/scripts/03_grxe_galprof_plot.py
index 1d813d9..a9fa02a 100755
--- a/scripts/03_grxe_galprof_plot.py
+++ b/scripts/03_grxe_galprof_plot.py
@@ -15,15 +15,15 @@ from ridge.config import *
 scale = 100.0
 
 fn="detcnts.A01.ALL.resid.galprof.fits"
-dat = Table.read(profdir+fn, unit_parse_strict='silent')
+dat = Table.read(profdir+fn)
 df1 = dat.to_pandas().sort_values(by=['LON1'])
 
 fn="detcnts.A02.ALL.resid.galprof.fits"
-dat = Table.read(profdir+fn, unit_parse_strict='silent')
+dat = Table.read(profdir+fn)
 df2 = dat.to_pandas().sort_values(by=['LON1'])
 
 fn="detcnts.A03.ALL.resid.galprof.fits"
-dat = Table.read(profdir+fn, unit_parse_strict='silent')
+dat = Table.read(profdir+fn)
 df3 = dat.to_pandas().sort_values(by=['LON1'])
 
 df_cobe = pd.read_csv('../data/cobe_ibis_resp_lon.dat', sep=' ', header=None)
diff --git a/scripts/03_grxe_map.py b/scripts/03_grxe_map.py
index bf80fc4..aea1939 100755
--- a/scripts/03_grxe_map.py
+++ b/scripts/03_grxe_map.py
@@ -46,7 +46,7 @@ key="ALL"
 fn='detcnts.{}.{}.resid.fits'.format(enkey,key)
 
 print("Reading {}".format(proddir+fn))
-dat = Table.read(proddir+fn, unit_parse_strict='silent')
+dat = Table.read(proddir+fn)
 df = dat.to_pandas()
 
 #df = df.query('abs(LAT) < {} & abs(LON) < {}'.format(5,5))
diff --git a/scripts/03_grxe_spec.py b/scripts/03_grxe_spec.py
index 4f4a118..638021d 100755
--- a/scripts/03_grxe_spec.py
+++ b/scripts/03_grxe_spec.py
@@ -146,7 +146,7 @@ for skey in skeys:
         #with fits.open(proddir+fn) as data:
         #    df = pd.DataFrame(data[1].data)
 
-        dat = Table.read(proddir+fn, unit_parse_strict='silent')
+        dat = Table.read(proddir+fn)
         df = dat.to_pandas()
 
         #print(df.columns)
diff --git a/scripts/03_grxe_syserr.py b/scripts/03_grxe_syserr.py
index 1ca3ec3..322e3c1 100755
--- a/scripts/03_grxe_syserr.py
+++ b/scripts/03_grxe_syserr.py
@@ -38,7 +38,7 @@ enkey = sys.argv[1]
 
 fn="detcnts.{}.{}.resid.fits".format(enkey,key)
 print("Reading {}".format(proddir+fn))
-dat = Table.read(proddir+fn, unit_parse_strict='silent')
+dat = Table.read(proddir+fn)
 df = dat.to_pandas()
 
 print("Number of ScWs: {}".format(df.shape[0]))
diff --git a/scripts/03_plot_skyreg.py b/scripts/03_plot_skyreg.py
index b0419b7..6b87ee9 100755
--- a/scripts/03_plot_skyreg.py
+++ b/scripts/03_plot_skyreg.py
@@ -44,7 +44,7 @@ key = "ALL"
 
 fn="detcnts.{}.{}.resid.fits".format(enkey,key)
 print("Reading {}".format(proddir+fn))
-dat = Table.read(proddir+fn, unit_parse_strict='silent')
+dat = Table.read(proddir+fn)
 df = dat.to_pandas()
 
 
diff --git a/scripts/03_scox1_spec.py b/scripts/03_scox1_spec.py
index c0624b8..1c9b483 100755
--- a/scripts/03_scox1_spec.py
+++ b/scripts/03_scox1_spec.py
@@ -87,7 +87,7 @@ if not os.path.exists(fitsdir):
 for enkey in ebands0.keys():
         
     fn="detcnts.{}.{}.resid.fits".format(enkey,inkey)
-    dat = Table.read(proddir+fn, unit_parse_strict='silent')
+    dat = Table.read(proddir+fn)
     df = dat.to_pandas()
 
     #crab_sep_max=2.0