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removed unit_parse_strict

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This commit is contained in:
Roman Krivonos 2024-11-11 14:41:31 +03:00
parent a733eabe47
commit b2cc0b68ad
13 changed files with 24 additions and 24 deletions
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2
scripts/00_scox1_lightcurve.py
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@ -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:

2
scripts/00_stats.py
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@ -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))

6
scripts/01_crabmodel_plot_poly.py
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@ -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'])

6
scripts/01_crabmodel_plot_sys.py
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@ -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'])

12
scripts/02_grxe_resid_plot.py
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@ -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

2
scripts/03_grxe_flux.py
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@ -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(

2
scripts/03_grxe_galprof.py
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@ -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))

6
scripts/03_grxe_galprof_plot.py
View File

@ -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)

2
scripts/03_grxe_map.py
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@ -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))

2
scripts/03_grxe_spec.py
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@ -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)

2
scripts/03_grxe_syserr.py
View File

@ -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]))

2
scripts/03_plot_skyreg.py
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@ -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()

2
scripts/03_scox1_spec.py
View File

@ -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