def get_pha_data(arg, make_copy=True, use_background=False):
"""
get_pha_data( filename [, make_copy=True [, use_background=False]])
get_pha_data( PHACrate [, make_copy=True [, use_background=False]])
"""
filename = ''
close_dataset = False
if type(arg) == str:
phadataset = open_crate_dataset(arg, pycrates.phacratedataset.PHACrateDataset)
if pycrates.is_pha(phadataset) != 1:
raise IOErr('badfile', arg, "PHACrateDataset obj")
filename = arg
close_dataset = True
elif pycrates.is_pha(arg) == 1:
phadataset = arg
filename = arg.get_filename()
make_copy=False
else:
raise IOErr('badfile', arg, "PHACrateDataset obj")
pha = _get_crate_by_blockname(phadataset, "SPECTRUM")
if pha is None:
pha = phadataset.get_crate(phadataset.get_current_crate())
if (pha.get_key('HDUCLAS1').value == 'SPECTRUM' or
pha.get_key('HDUCLAS2').value == 'SPECTRUM'):
pass
else:
pha = phadataset.get_crate(1)
if (pha.get_key('HDUCLAS1').value == 'SPECTRUM' or
pha.get_key('HDUCLAS2').value == 'SPECTRUM'):
pass
else:
# If background maybe better to go on to next block?
pha = None
if use_background:
# Used to read BKGs found in an additional block of
# Chandra Level 3 PHA files
for ii in range(phadataset.get_ncrates()):
block = phadataset.get_crate(ii+1)
hduclas2 = block.get_key('HDUCLAS2')
if hduclas2 is not None and hduclas2.value == 'BKG':
pha = block
if pha is None or pha.get_colnames() is None:
raise IOErr('filenotfound', arg)
keys = ['BACKFILE','ANCRFILE','RESPFILE',
'BACKSCAL','AREASCAL','EXPOSURE']
keys_or_cols = ['BACKSCAL','BACKSCUP','BACKSCDN','AREASCAL']
datasets = []
# Calling phadataset.is_pha_type1() is unreliable when
# both TYPE:I and TYPE:II keywords are in the header.
# Here, I instead test for a column, SPEC_NUM, that can
# *only* be present in Type II. SMD 05/15/13
if _try_col(pha, 'SPEC_NUM') is None:
data = {}
# Keywords
data['exposure'] = _try_key(pha, 'EXPOSURE', SherpaFloat)
#data['poisserr'] = _try_key(pha, 'POISSERR', bool)
data['backfile'] = _try_key(pha, 'BACKFILE')
data['arffile'] = _try_key(pha, 'ANCRFILE')
data['rmffile'] = _try_key(pha, 'RESPFILE')
# Keywords or columns
for name in keys_or_cols:
key = name.lower()
data[key] = _try_key(pha, name, SherpaFloat)
if data[key] is None:
data[key] = _try_col(pha, name, make_copy)
data['header'] = _get_meta_data(pha)
for key in keys:
try:
data['header'].pop(key)
except KeyError:
pass
# Columns
if not pha.column_exists('CHANNEL'):
raise IOErr('reqcol', 'CHANNEL', filename)
data['channel'] = _require_col(pha, 'CHANNEL', make_copy, fix_type=True)
# Make sure channel numbers, not indices
if int(data['channel'][0]) == 0 or pha.get_column('CHANNEL').get_tlmin() == 0:
data['channel'] = data['channel']+1
data['counts'] = None
if pha.column_exists('COUNTS'):
data['counts'] = _require_col(pha, 'COUNTS', make_copy, fix_type=True)
else:
if not pha.column_exists('RATE'):
raise IOErr('reqcol', 'COUNTS or RATE', filename)
data['counts'] = _require_col(pha, 'RATE', make_copy, fix_type=True)*data['exposure']
data['staterror'] = _try_col(pha, 'STAT_ERR', make_copy)
data['syserror'] = _try_col(pha, 'SYS_ERR', make_copy)
data['background_up'] = _try_col(pha, 'BACKGROUND_UP', make_copy, fix_type=True)
data['background_down'] = _try_col(pha, 'BACKGROUND_DOWN', make_copy, fix_type=True)
data['bin_lo'] = _try_col(pha, 'BIN_LO', make_copy,fix_type=True)
data['bin_hi'] = _try_col(pha, 'BIN_HI', make_copy,fix_type=True)
data['grouping'] = _try_col(pha, 'GROUPING', make_copy)
data['quality'] = _try_col(pha, 'QUALITY', make_copy)
datasets.append(data)
else:
# Type 2 PHA file support
data = {}
num = pha.get_nrows()
# Keywords
exposure = _try_key(pha, 'EXPOSURE', SherpaFloat)
#poisserr = _try_key(pha, 'POISSERR', bool)
backfile = _try_key(pha, 'BACKFILE')
arffile = _try_key(pha, 'ANCRFILE')
rmffile = _try_key(pha, 'RESPFILE')
# Keywords or columns
backscal = _try_key_list(pha, 'BACKSCAL', num)
if backscal is None:
backscal = _try_col_list(pha, 'BACKSCAL', num, make_copy)
backscup = _try_key_list(pha, 'BACKSCUP', num)
if backscup is None:
backscup = _try_col_list(pha, 'BACKSCUP', num, make_copy)
backscdn = _try_key_list(pha, 'BACKSCDN', num)
if backscdn is None:
backscdn = _try_col_list(pha, 'BACKSCDN', num, make_copy)
areascal = _try_key_list(pha, 'AREASCAL', num)
if areascal is None:
areascal = _try_col_list(pha, 'AREASCAL', num, make_copy)
# Columns
if not pha.column_exists('CHANNEL'):
raise IOErr('reqcol', 'CHANNEL', filename)
channel = _require_col_list(pha, 'CHANNEL', num, make_copy, fix_type=True)
# Make sure channel numbers, not indices
for ii in range(num):
if int(channel[ii][0]) == 0:
channel[ii] += 1
counts = None
if pha.column_exists('COUNTS'):
counts = _require_col_list(pha, 'COUNTS', num, make_copy, fix_type=True)
else:
if not pha.column_exists('RATE'):
raise IOErr('reqcol', 'COUNTS or RATE', filename)
counts = _require_col_list(pha, 'RATE', num, make_copy, fix_type=True) * exposure
staterror = _try_col_list(pha, 'STAT_ERR', num, make_copy)
syserror = _try_col_list(pha, 'SYS_ERR', num, make_copy)
background_up = _try_col_list(pha, 'BACKGROUND_UP', num, make_copy, fix_type=True)
background_down = _try_col_list(pha, 'BACKGROUND_DOWN', num, make_copy, fix_type=True)
bin_lo = _try_col_list(pha, 'BIN_LO', num, make_copy, fix_type=True)
bin_hi = _try_col_list(pha, 'BIN_HI', num, make_copy, fix_type=True)
grouping = _try_col_list(pha, 'GROUPING', num, make_copy)
quality = _try_col_list(pha, 'QUALITY', num, make_copy)
orders = _try_key_list(pha, 'TG_M', num)
if orders is None:
orders = _try_col_list(pha, 'TG_M', num, make_copy)
parts = _try_key_list(pha, 'TG_PART', num)
if parts is None:
parts = _try_col_list(pha, 'TG_PART', num, make_copy)
specnums = _try_col_list(pha, 'SPEC_NUM', num, make_copy)
srcids = _try_col_list(pha, 'TG_SRCID', num, make_copy)
# Iterate over all rows of channels, counts, errors, etc
# Populate a list of dictionaries containing individual dataset info
for (bscal, bscup, bscdn, arsc, chan, cnt, staterr, syserr,
backup, backdown, binlo, binhi, grp, qual, ordr, prt,
specnum, srcid
) in izip(backscal, backscup, backscdn, areascal, channel,
counts, staterror, syserror, background_up,
background_down, bin_lo, bin_hi, grouping, quality,
orders, parts, specnums, srcids):
data = {}
data['exposure'] = exposure
#data['poisserr'] = poisserr
data['backfile'] = backfile
data['arffile'] = arffile
data['rmffile'] = rmffile
data['backscal'] = bscal
data['backscup'] = bscup
data['backscdn'] = bscdn
data['areascal'] = arsc
data['channel'] = chan
data['counts'] = cnt
data['staterror'] = staterr
data['syserror'] = syserr
data['background_up'] = backup
data['background_down'] = backdown
data['bin_lo'] = binlo
data['bin_hi'] = binhi
data['grouping'] = grp
data['quality'] = qual
data['header'] = _get_meta_data(pha)
data['header']['TG_M'] = ordr
data['header']['TG_PART'] = prt
data['header']['SPEC_NUM'] = specnum
data['header']['TG_SRCID'] = srcid
for key in keys:
try:
data['header'].pop(key)
except KeyError:
pass
datasets.append(data)
if close_dataset:
close_crate_dataset(phadataset)
return datasets, filename
def get_pha_data(arg, make_copy=True, use_background=False):
"""
get_pha_data( filename [, make_copy=True [, use_background=False]])
get_pha_data( PHACrate [, make_copy=True [, use_background=False]])
"""
filename = ''
close_dataset = False
if type(arg) == str:
phadataset = open_crate_dataset(
arg, pycrates.phacratedataset.PHACrateDataset)
if pycrates.is_pha(phadataset) != 1:
raise IOErr('badfile', arg, "PHACrateDataset obj")
filename = arg
close_dataset = True
elif pycrates.is_pha(arg) == 1:
phadataset = arg
filename = arg.get_filename()
make_copy = False
else:
raise IOErr('badfile', arg, "PHACrateDataset obj")
pha = _get_crate_by_blockname(phadataset, "SPECTRUM")
if pha is None:
pha = phadataset.get_crate(phadataset.get_current_crate())
if (pha.get_key('HDUCLAS1').value == 'SPECTRUM'
or pha.get_key('HDUCLAS2').value == 'SPECTRUM'):
pass
else:
pha = phadataset.get_crate(1)
if (pha.get_key('HDUCLAS1').value == 'SPECTRUM'
or pha.get_key('HDUCLAS2').value == 'SPECTRUM'):
pass
else:
# If background maybe better to go on to next block?
pha = None
if use_background:
# Used to read BKGs found in an additional block of
# Chandra Level 3 PHA files
for ii in range(phadataset.get_ncrates()):
block = phadataset.get_crate(ii + 1)
hduclas2 = block.get_key('HDUCLAS2')
if hduclas2 is not None and hduclas2.value == 'BKG':
pha = block
if pha is None or pha.get_colnames() is None:
raise IOErr('filenotfound', arg)
keys = [
'BACKFILE', 'ANCRFILE', 'RESPFILE', 'BACKSCAL', 'AREASCAL', 'EXPOSURE'
]
keys_or_cols = ['BACKSCAL', 'BACKSCUP', 'BACKSCDN', 'AREASCAL']
datasets = []
# Calling phadataset.is_pha_type1() is unreliable when
# both TYPE:I and TYPE:II keywords are in the header.
# Here, I instead test for a column, SPEC_NUM, that can
# *only* be present in Type II. SMD 05/15/13
if _try_col(pha, 'SPEC_NUM') is None:
data = {}
# Keywords
data['exposure'] = _try_key(pha, 'EXPOSURE', SherpaFloat)
# data['poisserr'] = _try_key(pha, 'POISSERR', bool)
data['backfile'] = _try_key(pha, 'BACKFILE')
data['arffile'] = _try_key(pha, 'ANCRFILE')
data['rmffile'] = _try_key(pha, 'RESPFILE')
# Keywords or columns
for name in keys_or_cols:
key = name.lower()
data[key] = _try_key(pha, name, SherpaFloat)
if data[key] is None:
data[key] = _try_col(pha, name, make_copy)
data['header'] = _get_meta_data(pha)
for key in keys:
try:
data['header'].pop(key)
except KeyError:
pass
# Columns
if not pha.column_exists('CHANNEL'):
raise IOErr('reqcol', 'CHANNEL', filename)
data['channel'] = _require_col(pha,
'CHANNEL',
make_copy,
fix_type=True)
# Make sure channel numbers, not indices
if int(data['channel'][0]) == 0 or pha.get_column(
'CHANNEL').get_tlmin() == 0:
data['channel'] = data['channel'] + 1
data['counts'] = None
if pha.column_exists('COUNTS'):
data['counts'] = _require_col(pha,
'COUNTS',
make_copy,
fix_type=True)
else:
if not pha.column_exists('RATE'):
raise IOErr('reqcol', 'COUNTS or RATE', filename)
data['counts'] = _require_col(
pha, 'RATE', make_copy, fix_type=True) * data['exposure']
data['staterror'] = _try_col(pha, 'STAT_ERR', make_copy)
data['syserror'] = _try_col(pha, 'SYS_ERR', make_copy)
data['background_up'] = _try_col(pha,
'BACKGROUND_UP',
make_copy,
fix_type=True)
data['background_down'] = _try_col(pha,
'BACKGROUND_DOWN',
make_copy,
fix_type=True)
data['bin_lo'] = _try_col(pha, 'BIN_LO', make_copy, fix_type=True)
data['bin_hi'] = _try_col(pha, 'BIN_HI', make_copy, fix_type=True)
data['grouping'] = _try_col(pha, 'GROUPING', make_copy)
data['quality'] = _try_col(pha, 'QUALITY', make_copy)
datasets.append(data)
else:
# Type 2 PHA file support
data = {}
num = pha.get_nrows()
# Keywords
exposure = _try_key(pha, 'EXPOSURE', SherpaFloat)
# poisserr = _try_key(pha, 'POISSERR', bool)
backfile = _try_key(pha, 'BACKFILE')
arffile = _try_key(pha, 'ANCRFILE')
rmffile = _try_key(pha, 'RESPFILE')
# Keywords or columns
backscal = _try_key_list(pha, 'BACKSCAL', num)
if backscal is None:
backscal = _try_col_list(pha, 'BACKSCAL', num, make_copy)
backscup = _try_key_list(pha, 'BACKSCUP', num)
if backscup is None:
backscup = _try_col_list(pha, 'BACKSCUP', num, make_copy)
backscdn = _try_key_list(pha, 'BACKSCDN', num)
if backscdn is None:
backscdn = _try_col_list(pha, 'BACKSCDN', num, make_copy)
areascal = _try_key_list(pha, 'AREASCAL', num)
if areascal is None:
areascal = _try_col_list(pha, 'AREASCAL', num, make_copy)
# Columns
if not pha.column_exists('CHANNEL'):
raise IOErr('reqcol', 'CHANNEL', filename)
channel = _require_col_list(pha,
'CHANNEL',
num,
make_copy,
fix_type=True)
# Make sure channel numbers, not indices
for ii in range(num):
if int(channel[ii][0]) == 0:
channel[ii] += 1
counts = None
if pha.column_exists('COUNTS'):
counts = _require_col_list(pha,
'COUNTS',
num,
make_copy,
fix_type=True)
else:
if not pha.column_exists('RATE'):
raise IOErr('reqcol', 'COUNTS or RATE', filename)
counts = _require_col_list(
pha, 'RATE', num, make_copy, fix_type=True) * exposure
staterror = _try_col_list(pha, 'STAT_ERR', num, make_copy)
syserror = _try_col_list(pha, 'SYS_ERR', num, make_copy)
background_up = _try_col_list(pha,
'BACKGROUND_UP',
num,
make_copy,
fix_type=True)
background_down = _try_col_list(pha,
'BACKGROUND_DOWN',
num,
make_copy,
fix_type=True)
bin_lo = _try_col_list(pha, 'BIN_LO', num, make_copy, fix_type=True)
bin_hi = _try_col_list(pha, 'BIN_HI', num, make_copy, fix_type=True)
grouping = _try_col_list(pha, 'GROUPING', num, make_copy)
quality = _try_col_list(pha, 'QUALITY', num, make_copy)
orders = _try_key_list(pha, 'TG_M', num)
if orders is None:
orders = _try_col_list(pha, 'TG_M', num, make_copy)
parts = _try_key_list(pha, 'TG_PART', num)
if parts is None:
parts = _try_col_list(pha, 'TG_PART', num, make_copy)
specnums = _try_col_list(pha, 'SPEC_NUM', num, make_copy)
srcids = _try_col_list(pha, 'TG_SRCID', num, make_copy)
# Iterate over all rows of channels, counts, errors, etc
# Populate a list of dictionaries containing individual dataset info
for (bscal, bscup, bscdn, arsc, chan, cnt, staterr, syserr, backup,
backdown, binlo, binhi, grp, qual, ordr, prt, specnum,
srcid) in izip(backscal, backscup, backscdn, areascal, channel,
counts, staterror, syserror, background_up,
background_down, bin_lo, bin_hi, grouping, quality,
orders, parts, specnums, srcids):
data = {}
data['exposure'] = exposure
# data['poisserr'] = poisserr
data['backfile'] = backfile
data['arffile'] = arffile
data['rmffile'] = rmffile
data['backscal'] = bscal
data['backscup'] = bscup
data['backscdn'] = bscdn
data['areascal'] = arsc
data['channel'] = chan
data['counts'] = cnt
data['staterror'] = staterr
data['syserror'] = syserr
data['background_up'] = backup
data['background_down'] = backdown
data['bin_lo'] = binlo
data['bin_hi'] = binhi
data['grouping'] = grp
data['quality'] = qual
data['header'] = _get_meta_data(pha)
data['header']['TG_M'] = ordr
data['header']['TG_PART'] = prt
data['header']['SPEC_NUM'] = specnum
data['header']['TG_SRCID'] = srcid
for key in keys:
try:
data['header'].pop(key)
except KeyError:
pass
datasets.append(data)
if close_dataset:
close_crate_dataset(phadataset)
return datasets, filename
def get_pha_data(arg, make_copy=True, use_background=False):
"""
get_pha_data( filename [, make_copy=True [, use_background=False]])
get_pha_data( PHACrate [, make_copy=True [, use_background=False]])
"""
filename = ''
if type(arg) == str:
#pha = pycrates.read_pha(arg, use_background)
pha = _open_crate(pycrates.PHACrate, [arg, use_background])
filename = arg
# Make a copy of the data, since we don't know that pycrates will
# do something sensible wrt reference counting
elif pycrates.is_pha(arg) == pycrates.dmSUCCESS:
pha = arg
filename = arg.get_filename()
make_copy=False
else:
raise IOErr('badfile', arg, "PHACrate obj")
if pha is None or pha.get_colnames() is None:
raise IOErr('filenotfound', arg)
keys = ['BACKFILE','ANCRFILE','RESPFILE',
'BACKSCAL','AREASCAL','EXPOSURE']
datasets = []
if (pha.pha1_type_flag or
(not pha.pha1_type_flag and len(pha.spec_num.get_values())==1)):
data = {}
# Keywords
data['exposure'] = _try_key(pha.exposure, SherpaFloat)
#data['poisserr'] = _try_key(pha.poisserr, bool)
data['backfile'] = _try_key(pha.backfile_key)
data['arffile'] = _try_key(pha.ancrfile_key)
data['rmffile'] = _try_key(pha.respfile_key)
# Keywords or columns
data['backscal'] = _try_key(pha.backscal_key, SherpaFloat)
if data['backscal'] is None:
data['backscal'] = _try_col(pha.backscal, make_copy)
data['backscup'] = _try_key(pha.backscup_key, SherpaFloat)
if data['backscup'] is None:
data['backscup'] = _try_col(pha.backscup, make_copy)
data['backscdn'] = _try_key(pha.backscdn_key, SherpaFloat)
if data['backscdn'] is None:
data['backscdn'] = _try_col(pha.backscdn, make_copy)
data['areascal'] = _try_key(pha.areascal_key, SherpaFloat)
if data['areascal'] is None:
data['areascal'] = _try_col(pha.areascal, make_copy)
data['header'] = _get_meta_data(pha)
for key in keys:
try:
data['header'].pop(key)
except KeyError:
pass
# Columns
if pha.channel is None:
raise IOErr('reqcol', 'CHANNEL', filename)
data['channel'] = _require_col(pha.channel, make_copy, fix_type=True)
# Make sure channel numbers, not indices
if pha.channel.get_tlmin() == 0:
data['channel'] = data['channel']+1
data['counts'] = None
if pha.counts is not None:
data['counts'] = _require_col(pha.counts, make_copy, fix_type=True)
else:
if pha.rate is None:
raise IOErr('reqcol', 'COUNTS or RATE', filename)
data['counts'] = _require_col(pha.rate, make_copy, fix_type=True)*data['exposure']
data['staterror'] = _try_col(pha.stat_err, make_copy)
data['syserror'] = _try_col(pha.sys_err, make_copy)
data['background_up'] = _try_col(pha.background_up, make_copy, fix_type=True)
data['background_down'] = _try_col(pha.background_down, make_copy, fix_type=True)
data['bin_lo'] = _try_col(pha.bin_lo, make_copy,fix_type=True)
data['bin_hi'] = _try_col(pha.bin_hi, make_copy,fix_type=True)
data['grouping'] = _try_col(pha.grouping, make_copy)
data['quality'] = _try_col(pha.quality, make_copy)
datasets.append(data)
else:
# Type 2 PHA file support
data = {}
num = pha.spec_num.get_nsets()
# Keywords
exposure = _try_key(pha.exposure, SherpaFloat)
#poisserr = _try_key(pha.poisserr, bool)
backfile = _try_key(pha.backfile_key)
arffile = _try_key(pha.ancrfile_key)
rmffile = _try_key(pha.respfile_key)
# Keywords or columns
backscal = _try_key_list(pha.backscal_key, num)
if pha.backscal_key is None:
backscal = _try_col_list(pha.backscal, num, make_copy)
backscup = _try_key_list(pha.backscup_key, num)
if pha.backscup_key is None:
backscup = _try_col_list(pha.backscup, num, make_copy)
backscdn = _try_key_list(pha.backscdn_key, num)
if pha.backscdn_key is None:
backscdn = _try_col_list(pha.backscdn, num, make_copy)
areascal = _try_key_list(pha.areascal_key, num)
if pha.areascal_key is None:
areascal = _try_col_list(pha.areascal, num, make_copy)
# Columns
if pha.channel is None:
raise IOErr('reqcol', 'CHANNEL', filename)
channel = _require_col_list(pha.channel, num, make_copy, fix_type=True)
counts = None
if pha.counts is not None:
counts = _require_col_list(pha.counts, num, make_copy, fix_type=True)
else:
if pha.rate is None:
raise IOErr('reqcol', 'COUNTS or RATE', filename)
counts = _require_col_list(pha.rate, num, make_copy, fix_type=True) * exposure
staterror = _try_col_list(pha.stat_err, num, make_copy)
syserror = _try_col_list(pha.sys_err, num, make_copy)
background_up = _try_col_list(pha.background_up, num, make_copy, fix_type=True)
background_down = _try_col_list(pha.background_down, num, make_copy, fix_type=True)
bin_lo = _try_col_list(pha.bin_lo, num, make_copy,
fix_type=True)
bin_hi = _try_col_list(pha.bin_hi, num, make_copy,
fix_type=True)
grouping = _try_col_list(pha.grouping, num, make_copy)
quality = _try_col_list(pha.quality, num, make_copy)
orders = _try_key_list(pha.tg_m_key,num)
if pha.tg_m_key is None:
orders = _try_col_list(pha.tg_m, num, make_copy)
parts = _try_key_list(pha.tg_part_key,num)
if pha.tg_part_key is None:
parts = _try_col_list(pha.tg_part, num, make_copy)
specnums = _try_col_list(pha.spec_num, num, make_copy)
srcids = _try_col_list(pha.tg_srcid, num, make_copy)
# Iterate over all rows of channels, counts, errors, etc
# Populate a list of dictionaries containing individual dataset info
for (bscal, bscup, bscdn, arsc, chan, cnt, staterr, syserr,
backup, backdown, binlo, binhi, grp, qual, ordr, prt,
specnum, srcid
) in izip(backscal, backscup, backscdn, areascal, channel,
counts, staterror, syserror, background_up,
background_down, bin_lo, bin_hi, grouping, quality,
orders, parts, specnums, srcids):
data = {}
data['exposure'] = exposure
#data['poisserr'] = poisserr
data['backfile'] = backfile
data['arffile'] = arffile
data['rmffile'] = rmffile
data['backscal'] = bscal
data['backscup'] = bscup
data['backscdn'] = bscdn
data['areascal'] = arsc
data['channel'] = chan
data['counts'] = cnt
data['staterror'] = staterr
data['syserror'] = syserr
data['background_up'] = backup
data['background_down'] = backdown
data['bin_lo'] = binlo
data['bin_hi'] = binhi
data['grouping'] = grp
data['quality'] = qual
data['header'] = _get_meta_data(pha)
data['header']['TG_M'] = ordr
data['header']['TG_PART'] = prt
data['header']['SPEC_NUM'] = specnum
data['header']['TG_SRCID'] = srcid
for key in keys:
try:
data['header'].pop(key)
except KeyError:
pass
datasets.append(data)
return datasets, filename
