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- #15

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- #15

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3352e58
Try to fix broken tns
0xCoto Jan 21, 2023
2cb2f0d
Remove rm
0xCoto Jan 26, 2023
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50 changes: 25 additions & 25 deletions frbcat/tns.py
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Original file line number Diff line number Diff line change
Expand Up @@ -58,7 +58,7 @@ def __init__(self,

self.units = {'back_end': None,
'barycentric_event_time': None,
'burst_bandwidth': 'MHz',
#'burst_bandwidth': 'MHz',
'burst_width': 'ms',
'burst_width_err': 'ms',
'dec_frac': 'frac. degrees',
Expand All @@ -73,13 +73,13 @@ def __init__(self,
'fluence_err': 'Jy ms',
'flux': 'Jy',
'flux_err': 'Jy',
'frac_lin_pol': None,
#'frac_lin_pol': None,
'galactic_max_dm': 'pc cm^-3',
'galactic_max_dm_model': None,
'gl_frac': 'frac. degrees',
'gb_frac': 'frac. degrees',
'group': None,
'host_redshift': None,
#'host_redshift': None,
'inst_bandwidth': 'MHz',
'internal_name': None,
'lastmodified': None,
Expand All @@ -98,10 +98,10 @@ def __init__(self,
'repeater_of_objid': None,
'reporter_name': None,
'reports_id': None,
'rm': 'rad m^-2',
'rm_err': 'rad m^-2',
#'rm': 'rad m^-2',
#'rm_err': 'rad m^-2',
'sampling_time': 'ms',
'scattering_time': 'ms',
#'scattering_time': 'ms',
'scattering_time_err': 'ms',
'snr': None,
'telescope': None,
Expand Down Expand Up @@ -311,9 +311,9 @@ def clean_df(self, df):
'reports_id': int,
'photometry_id': int,
'snr': float,
'num_channels': int,
'host_redshift': float,
'frac_lin_pol': float})
'num_channels': int})
#'host_redshift': float,
#'frac_lin_pol': float})

# Clean up columns
df.repeater_of_objid = df.repeater_of_objid.replace(r'^\s*$', np.nan,
Expand Down Expand Up @@ -357,18 +357,18 @@ def clean_df(self, df):
err[err == ''] = np.nan
df['fluence_err'] = err.astype(float)

for c in ('burst_width', 'scattering_time'):
cols = df[c].str.strip(' ms').str.partition(' (')[[0, 2]]
df[c] = cols[0].astype(float)
err = cols[2].str.strip(')')
err[err == ''] = np.nan
df[c + '_err'] = err.astype(float)
#for c in ('burst_width', 'scattering_time'):
# cols = df[c].str.strip(' ms').str.partition(' (')[[0, 2]]
# df[c] = cols[0].astype(float)
# err = cols[2].str.strip(')')
# err[err == ''] = np.nan
# df[c + '_err'] = err.astype(float)

cols = df.burst_bandwidth.str.strip(' MHz').str.partition(' (')[[0, 2]]
df['burst_bandwidth'] = cols[0].astype(float)
err = cols[2].str.strip(')')
err[err == ''] = np.nan
df['burst_bandwidth_err'] = err.astype(float)
#cols = df.burst_bandwidth.str.strip(' MHz').str.partition(' (')[[0, 2]]
#df['burst_bandwidth'] = cols[0].astype(float)
#err = cols[2].str.strip(')')
#err[err == ''] = np.nan
#df['burst_bandwidth_err'] = err.astype(float)

# Commenting out as some FAST entries seem to use GHz
# instead of MHz units in the reference frequency field
Expand All @@ -378,11 +378,11 @@ def clean_df(self, df):
s = 'sampling_time'
df[s] = df[s].str.strip(' ms').astype(float)

cols = df.rm.str.strip(' rad/m2').str.partition(' (')[[0, 2]]
df['rm'] = cols[0].astype(float)
err = cols[2].str.strip(')')
err[err == ''] = np.nan
df['rm_err'] = err.astype(float)
#cols = df.rm.str.strip(' rad/m2').str.partition(' (')[[0, 2]]
#df['rm'] = cols[0].astype(float)
#err = cols[2].str.strip(')')
#err[err == ''] = np.nan
#df['rm_err'] = err.astype(float)

# Convert time columns to datetime objects
dates = ('time_received', 'barycentric_event_time', 'discovery_date',
Expand Down