def load_table(filename):
"""
Load a table from a given file.
Supports csv, tab, tex, vo, vot, xml, fits, and hdf5.
Parameters
----------
filename : str
File to read
Returns
-------
table : Table
Table of data.
"""
supported = get_table_formats()
fmt = os.path.splitext(filename)[-1][1:].lower() # extension sans '.'
if fmt in ['csv', 'tab', 'tex'] and fmt in supported:
log.info("Reading file {0}".format(filename))
t = ascii.read(filename)
elif fmt in ['vo', 'vot', 'xml', 'fits', 'hdf5'] and fmt in supported:
log.info("Reading file {0}".format(filename))
t = Table.read(filename)
else:
log.error("Table format not recognized or supported")
log.error("{0} [{1}]".format(filename, fmt))
raise Exception("Table format not recognized or supported")
return t
def load_table(filename):
"""
Load a table from a given file.
Supports csv, tab, tex, vo, vot, xml, fits, and hdf5.
Parameters
----------
filename : str
File to read
Returns
-------
table : Table
Table of data.
"""
supported = get_table_formats()
fmt = os.path.splitext(filename)[-1][1:].lower() # extension sans '.'
if fmt in ['csv', 'tab', 'tex'] and fmt in supported:
log.info("Reading file {0}".format(filename))
t = ascii.read(filename)
elif fmt in ['vo', 'vot', 'xml', 'fits', 'hdf5'] and fmt in supported:
log.info("Reading file {0}".format(filename))
t = Table.read(filename)
else:
log.error("Table format not recognized or supported")
log.error("{0} [{1}]".format(filename, fmt))
raise Exception("Table format not recognized or supported")
return t
def main2():
"""
As per main() but we operate on columns instead of rows. So much faster!
"""
global colnames
if len(sys.argv) != 3:
print "Usage ", __file__, " inputcatalog outputcatalog"
sys.exit()
infile = sys.argv[-2]
outfile = sys.argv[-1]
print 'read'
master = Table.read(infile)
print 'colnames'
colnames = get_colnames(master)
print 'filtering'
# don't have to worry about rows where the first col has the source we want
second = np.where(master['local_rms_2'] <= master['local_rms_1'])
master = shuffle_left_rows(master, second, 2)
print "strip cols"
master = strip_cols(master)
print 'write'
if os.path.exists(outfile):
os.remove(outfile)
master.write(outfile)
def fits_to_packets(file):
logger.info(f'Processing fits file {file}')
parser = StixTCTMParser()
control = Table.read(str(file), hdu=1)
data = Table.read(str(file), hdu=2)
binary_packets = [
ConstBitArray(hex=hex).tobytes() for hex in data['data']
][-2:]
packets = [parser.parse_binary(bd)[0] for bd in binary_packets][-2:]
if np.abs([((len(data['data'][i]) // 2) - (control['data_len'][i] + 7))
for i in range(len(data))]).sum() > 0:
raise ValueError('Packet size and expected length do not match')
# packets = list(chain.from_iterable(packets))
# Filter keeping only TM packets
# packets = list(filter(lambda x: x['header']['TMTC'] == 'TM', packets))
# Packet ordering is not guaranteed so sort by coarse time then seq count
# packets.sort(key=lambda x: (x['header']['coarse_time'], x['header']['seq_count']))
return packets
def load_table(filename):
"""
:param filename:
:return:
"""
supported = get_table_formats()
fmt = os.path.splitext(filename)[-1][1:].lower() #extension sans '.'
if fmt in ['csv', 'tab', 'tex'] and fmt in supported:
log.info("Reading file {0}".format(filename))
t = ascii.read(filename)
elif fmt in ['vo', 'vot', 'xml', 'fits','hdf5'] and fmt in supported:
log.info("Reading file {0}".format(filename))
t = Table.read(filename)
else:
log.error("Table format not recognized or supported")
log.error("{0} [{1}]".format(filename,fmt))
t= None
return t
def load_table(filename):
"""
:param filename:
:return:
"""
supported = get_table_formats()
fmt = os.path.splitext(filename)[-1][1:].lower() #extension sans '.'
if fmt in ['csv', 'tab', 'tex'] and fmt in supported:
log.info("Reading file {0}".format(filename))
t = ascii.read(filename)
elif fmt in ['vo', 'vot', 'xml', 'fits', 'hdf5'] and fmt in supported:
log.info("Reading file {0}".format(filename))
t = Table.read(filename)
else:
log.error("Table format not recognized or supported")
log.error("{0} [{1}]".format(filename, fmt))
t = None
return t
def load(self, catalogue_file, **kwargs):
""" load the given file and create the object.
kwargs can have any build option like key_ra, key_mag etc.
"""
# ---------------------
# - Parsing the input
if catalogue_file.endswith(".fits"):
# loading from fits file
fits = pf.open(catalogue_file)
header = fits[self._build_properties["data_index"]].header
data = fits[self._build_properties["data_index"]].data
if type(data) == pf.fitsrec.FITS_rec:
from astrobject.utils.tools import fitsrec_to_dict
data = TableColumns(fitsrec_to_dict(data))
elif catalogue_file.endswith(".pkl"):
# loading from pkl
fits = None
header = None
data = load_pkl(catalogue_file)
if not type(data) is Table:
try:
data = Table(data)
except:
warnings.warn(
"Convertion of 'data' into astropy Table failed")
else:
fits = None
header = None
format_ = kwargs.pop("format", "ascii")
data = Table.read(catalogue_file, format=format_, **kwargs)
# ---------------------
# - Calling Creates
self.create(data, header, **kwargs)
self._properties["filename"] = catalogue_file
self._derived_properties["fits"] = fits
def load(self,catalogue_file,**kwargs):
""" load the given file and create the object.
kwargs can have any build option like key_ra, key_mag etc.
"""
# ---------------------
# - Parsing the input
if catalogue_file.endswith(".fits"):
# loading from fits file
fits = pf.open(catalogue_file)
header = fits[self._build_properties["data_index"]].header
data = fits[self._build_properties["data_index"]].data
if type(data) == pf.fitsrec.FITS_rec:
from astrobject.utils.tools import fitsrec_to_dict
data = TableColumns(fitsrec_to_dict(data))
elif catalogue_file.endswith(".pkl"):
# loading from pkl
fits = None
header = None
data = load_pkl(catalogue_file)
if not type(data) is Table:
try:
data = Table(data)
except:
warnings.warn("Convertion of 'data' into astropy Table failed")
else:
fits = None
header = None
format_ = kwargs.pop("format","ascii")
data = Table.read(catalogue_file,format=format_,**kwargs)
# ---------------------
# - Calling Creates
self.create(data, header, **kwargs)
self._properties["filename"] = catalogue_file
self._derived_properties["fits"] = fits
166
174
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197
204
212
220
227
""".split()
killring = ['Name', 'island_deep', 'source_deep', 'uuid_deep', 'flags_deep']
killring.extend(['uuid_{0}'.format(f) for f in mids])
print "table load"
tab = Table.read(input) # "all_wide.fits")
# remove columns we don't want
print "killing columns"
for n in killring:
if n in tab.colnames:
del tab[n]
print "renaming deep -> wide"
for n in tab.colnames:
if 'deep' in n:
tab[n].name = n.replace('deep', 'wide')
print "making names"
# make a new column which is the IAU source name
c = Table.Column([
"GLEAM J" +
ul,
)
from astropy.io import fits
from astropy.table.table import Table
from stixcore.data.test import test_data
from stixcore.idb.manager import IDBManager
from stixcore.products.level0.scienceL0 import ScienceProduct
from stixcore.products.product import Product, read_qtable
name_counter = defaultdict(int)
IDB = IDBManager(test_data.idb.DIR).get_idb("2.26.34")
descriptions = Table.read("stixcore/data/test/ddpd.in.csv",
format='csv',
delimiter="\t")
def mtable(columns, data, tclass):
t = table(cls=tclass, style="width: 100%; table-layout:fixed;")
_tr = tr()
for c, style in columns:
_tr.add(th(c, style=style))
t.add(thead(_tr))
tb = tbody()
for r in data:
_tr = tr()
for i, c in enumerate(r):
_tr.add(td(c, style=columns[i][1]))
tb.add(_tr)
