def calfs(scantab,
scannos=[],
smooth=1,
tsysval=0.0,
tauval=0.0,
tcalval=0.0,
verify=False):
"""
Calibrate GBT frequency switched data.
Adopted from GBTIDL getfs.
Currently calfs identify the scans as frequency switched data if source
type enum is fson and fsoff. The data must contains 'CAL' signal
on/off in each integration. To identify 'CAL' on state, the source type
enum of foncal and foffcal need to be present.
Parameters:
scantab: scantable
scannos: list of scan numbers
smooth: optional box smoothing order for the reference
(default is 1 = no smoothing)
tsysval: optional user specified Tsys (default is 0.0,
use Tsys in the data)
tauval: optional user specified Tau
verify: Verify calibration if true
"""
varlist = vars()
from asap._asap import stmath
from asap._asap import srctype
stm = stmath()
stm._setinsitu(False)
# check = scantab.get_scan('*_fs*')
# if check is None:
# msg = "The input data appear to contain no Nod observing mode data."
# raise TypeError(msg)
s = scantab.get_scan(scannos)
del scantab
resspec = scantable(stm._dofs(s, scannos, smooth, tsysval, tauval,
tcalval))
###
if verify:
# get data
ssub = s.get_scan(scannos)
#ssubon = ssub.get_scan('*calon')
#ssuboff = ssub.get_scan('*[^calon]')
sel = selector()
sel.set_types([srctype.foncal, srctype.foffcal])
ssub.set_selection(sel)
ssubon = ssub.copy()
ssub.set_selection()
sel.reset()
sel.set_types([srctype.fson, srctype.fsoff])
ssub.set_selection(sel)
ssuboff = ssub.copy()
ssub.set_selection()
sel.reset()
import numpy
precal = {}
postcal = []
keys = ['fs', 'fs_calon', 'fsr', 'fsr_calon']
types = [srctype.fson, srctype.foncal, srctype.fsoff, srctype.foffcal]
ifnos = list(ssub.getifnos())
polnos = list(ssub.getpolnos())
for i in range(2):
#ss=ssuboff.get_scan('*'+keys[2*i])
ll = []
for j in range(len(ifnos)):
for k in range(len(polnos)):
sel.set_ifs(ifnos[j])
sel.set_polarizations(polnos[k])
sel.set_types(types[2 * i])
try:
#ss.set_selection(sel)
ssuboff.set_selection(sel)
except:
continue
ll.append(numpy.array(ss._getspectrum(0)))
sel.reset()
#ss.set_selection()
ssuboff.set_selection()
precal[keys[2 * i]] = ll
#del ss
#ss=ssubon.get_scan('*'+keys[2*i+1])
ll = []
for j in range(len(ifnos)):
for k in range(len(polnos)):
sel.set_ifs(ifnos[j])
sel.set_polarizations(polnos[k])
sel.set_types(types[2 * i + 1])
try:
#ss.set_selection(sel)
ssubon.set_selection(sel)
except:
continue
ll.append(numpy.array(ss._getspectrum(0)))
sel.reset()
#ss.set_selection()
ssubon.set_selection()
precal[keys[2 * i + 1]] = ll
#del ss
#sig=resspec.get_scan('*_fs')
#ref=resspec.get_scan('*_fsr')
sel.set_types(srctype.fson)
resspec.set_selection(sel)
sig = resspec.copy()
resspec.set_selection()
sel.reset()
sel.set_type(srctype.fsoff)
resspec.set_selection(sel)
ref = resspec.copy()
resspec.set_selection()
sel.reset()
for k in range(len(polnos)):
for j in range(len(ifnos)):
sel.set_ifs(ifnos[j])
sel.set_polarizations(polnos[k])
try:
sig.set_selection(sel)
postcal.append(numpy.array(sig._getspectrum(0)))
except:
ref.set_selection(sel)
postcal.append(numpy.array(ref._getspectrum(0)))
sel.reset()
resspec.set_selection()
del sel
# plot
asaplog.post()
asaplog.push(
'Plot only first spectrum for each [if,pol] pairs to verify calibration.'
)
asaplog.post('WARN')
p = new_asaplot()
rcp('lines', linewidth=1)
#nr=min(6,len(ifnos)*len(polnos))
nr = len(ifnos) / 2 * len(polnos)
titles = []
btics = []
if nr > 3:
asaplog.post()
asaplog.push('Only first 3 [if,pol] pairs are plotted.')
asaplog.post('WARN')
nr = 3
p.set_panels(rows=nr, cols=3, nplots=3 * nr, ganged=False)
for i in range(3 * nr):
b = False
if i >= 3 * nr - 3:
b = True
btics.append(b)
for i in range(nr):
p.subplot(3 * i)
p.color = 0
title = 'raw data IF%s,%s POL%s' % (
ifnos[2 * int(i / len(polnos))],
ifnos[2 * int(i / len(polnos)) + 1], polnos[i % len(polnos)])
titles.append(title)
#p.set_axes('title',title,fontsize=40)
ymin = 1.0e100
ymax = -1.0e100
nchan = s.nchan(ifnos[2 * int(i / len(polnos))])
edge = int(nchan * 0.01)
for j in range(4):
spmin = min(precal[keys[j]][i][edge:nchan - edge])
spmax = max(precal[keys[j]][i][edge:nchan - edge])
ymin = min(ymin, spmin)
ymax = max(ymax, spmax)
for j in range(4):
if i == 0:
p.set_line(label=keys[j])
else:
p.legend()
p.plot(precal[keys[j]][i])
p.axes.set_ylim(ymin - 0.1 * abs(ymin), ymax + 0.1 * abs(ymax))
if not btics[3 * i]:
p.axes.set_xticks([])
p.subplot(3 * i + 1)
p.color = 0
title = 'sig data IF%s POL%s' % (ifnos[2 * int(i / len(polnos))],
polnos[i % len(polnos)])
titles.append(title)
#p.set_axes('title',title)
p.legend()
ymin = postcal[2 * i][edge:nchan - edge].min()
ymax = postcal[2 * i][edge:nchan - edge].max()
p.plot(postcal[2 * i])
p.axes.set_ylim(ymin - 0.1 * abs(ymin), ymax + 0.1 * abs(ymax))
if not btics[3 * i + 1]:
p.axes.set_xticks([])
p.subplot(3 * i + 2)
p.color = 0
title = 'ref data IF%s POL%s' % (ifnos[2 * int(i / len(polnos)) +
1], polnos[i % len(polnos)])
titles.append(title)
#p.set_axes('title',title)
p.legend()
ymin = postcal[2 * i + 1][edge:nchan - edge].min()
ymax = postcal[2 * i + 1][edge:nchan - edge].max()
p.plot(postcal[2 * i + 1])
p.axes.set_ylim(ymin - 0.1 * abs(ymin), ymax + 0.1 * abs(ymax))
if not btics[3 * i + 2]:
p.axes.set_xticks([])
for i in range(3 * nr):
p.subplot(i)
p.set_axes('title', titles[i], fontsize='medium')
x = raw_input('Accept calibration ([y]/n): ')
if x.upper() == 'N':
p.quit()
del p
return scantab
p.quit()
del p
###
resspec._add_history("calfs", varlist)
return resspec
sel.set_polarizations(polnos[k])
try:
ress.set_selection(sel)
except:
continue
postcal.append(numpy.array(ress._getspectrum(0)))
sel.reset()
ress.set_selection()
del sel
# plot
asaplog.post()
asaplog.push(
'Plot only first spectrum for each [if,pol] pairs to verify calibration.'
)
asaplog.post('WARN')
p = new_asaplot()
rcp('lines', linewidth=1)
#nr=min(6,len(ifnos)*len(polnos))
nr = len(ifnos) * len(polnos)
titles = []
btics = []
if nr < 4:
p.set_panels(rows=nr, cols=2, nplots=2 * nr, ganged=False)
for i in range(2 * nr):
b = False
if i >= 2 * nr - 2:
b = True
btics.append(b)
elif nr == 4:
p.set_panels(rows=2, cols=4, nplots=8, ganged=False)
for i in range(2 * nr):
def plot(self, residual=False, components=None, plotparms=False, filename=None):
"""
Plot the last fit.
Parameters:
residual: an optional parameter indicating if the residual
should be plotted (default 'False')
components: a list of components to plot, e.g [0,1],
-1 plots the total fit. Default is to only
plot the total fit.
plotparms: Inidicates if the parameter values should be present
on the plot
"""
from matplotlib import rc as rcp
if not self.fitted:
return
# if not self._p or self._p.is_dead:
if not (self._p and self._p._alive()):
from asap.asapplotter import new_asaplot
del self._p
self._p = new_asaplot(rcParams["plotter.gui"])
self._p.hold()
self._p.clear()
rcp("lines", linewidth=1)
self._p.set_panels()
self._p.palette(0)
tlab = "Spectrum"
xlab = "Abcissa"
ylab = "Ordinate"
from numpy import ma, logical_not, logical_and, array
m = self.mask
if self.data:
tlab = self.data._getsourcename(self._fittedrow)
xlab = self.data._getabcissalabel(self._fittedrow)
if self.data._getflagrow(self._fittedrow):
m = [False]
else:
m = logical_and(self.mask, array(self.data._getmask(self._fittedrow), copy=False))
ylab = self.data._get_ordinate_label()
colours = ["#777777", "#dddddd", "red", "orange", "purple", "green", "magenta", "cyan"]
nomask = True
for i in range(len(m)):
nomask = nomask and m[i]
if len(m) == 1:
m = m[0]
invm = not m
else:
invm = logical_not(m)
label0 = "Masked Region"
label1 = "Spectrum"
if nomask:
label0 = label1
else:
y = ma.masked_array(self.y, mask=m)
self._p.palette(1, colours)
self._p.set_line(label=label1)
self._p.plot(self.x, y)
self._p.palette(0, colours)
self._p.set_line(label=label0)
y = ma.masked_array(self.y, mask=invm)
self._p.plot(self.x, y)
if residual:
self._p.palette(7)
self._p.set_line(label="Residual")
y = ma.masked_array(self.get_residual(), mask=invm)
self._p.plot(self.x, y)
self._p.palette(2)
if components is not None:
cs = components
if isinstance(components, int):
cs = [components]
if plotparms:
self._p.text(0.15, 0.15, str(self.get_parameters()["formatted"]), size=8)
n = len(self.components)
self._p.palette(3)
for c in cs:
if 0 <= c < n:
lab = self.fitfuncs[c] + str(c)
self._p.set_line(label=lab)
y = ma.masked_array(self.fitter.evaluate(c), mask=invm)
self._p.plot(self.x, y)
elif c == -1:
self._p.palette(2)
self._p.set_line(label="Total Fit")
y = ma.masked_array(self.fitter.getfit(), mask=invm)
self._p.plot(self.x, y)
else:
self._p.palette(2)
self._p.set_line(label="Fit")
y = ma.masked_array(self.fitter.getfit(), mask=invm)
self._p.plot(self.x, y)
xlim = [min(self.x), max(self.x)]
self._p.axes.set_xlim(xlim)
self._p.set_axes("xlabel", xlab)
self._p.set_axes("ylabel", ylab)
self._p.set_axes("title", tlab)
self._p.release()
if not rcParams["plotter.gui"]:
self._p.save(filename)
def calfs(scantab, scannos=[], smooth=1, tsysval=0.0, tauval=0.0, tcalval=0.0, verify=False):
"""
Calibrate GBT frequency switched data.
Adopted from GBTIDL getfs.
Currently calfs identify the scans as frequency switched data if source
type enum is fson and fsoff. The data must contains 'CAL' signal
on/off in each integration. To identify 'CAL' on state, the source type
enum of foncal and foffcal need to be present.
Parameters:
scantab: scantable
scannos: list of scan numbers
smooth: optional box smoothing order for the reference
(default is 1 = no smoothing)
tsysval: optional user specified Tsys (default is 0.0,
use Tsys in the data)
tauval: optional user specified Tau
verify: Verify calibration if true
"""
varlist = vars()
from asap._asap import stmath
from asap._asap import srctype
stm = stmath()
stm._setinsitu(False)
# check = scantab.get_scan('*_fs*')
# if check is None:
# msg = "The input data appear to contain no Nod observing mode data."
# raise TypeError(msg)
s = scantab.get_scan(scannos)
del scantab
resspec = scantable(stm._dofs(s, scannos, smooth, tsysval,tauval,tcalval))
###
if verify:
# get data
ssub = s.get_scan(scannos)
#ssubon = ssub.get_scan('*calon')
#ssuboff = ssub.get_scan('*[^calon]')
sel = selector()
sel.set_types( [srctype.foncal,srctype.foffcal] )
ssub.set_selection( sel )
ssubon = ssub.copy()
ssub.set_selection()
sel.reset()
sel.set_types( [srctype.fson,srctype.fsoff] )
ssub.set_selection( sel )
ssuboff = ssub.copy()
ssub.set_selection()
sel.reset()
import numpy
precal={}
postcal=[]
keys=['fs','fs_calon','fsr','fsr_calon']
types=[srctype.fson,srctype.foncal,srctype.fsoff,srctype.foffcal]
ifnos=list(ssub.getifnos())
polnos=list(ssub.getpolnos())
for i in range(2):
#ss=ssuboff.get_scan('*'+keys[2*i])
ll=[]
for j in range(len(ifnos)):
for k in range(len(polnos)):
sel.set_ifs(ifnos[j])
sel.set_polarizations(polnos[k])
sel.set_types(types[2*i])
try:
#ss.set_selection(sel)
ssuboff.set_selection(sel)
except:
continue
ll.append(numpy.array(ss._getspectrum(0)))
sel.reset()
#ss.set_selection()
ssuboff.set_selection()
precal[keys[2*i]]=ll
#del ss
#ss=ssubon.get_scan('*'+keys[2*i+1])
ll=[]
for j in range(len(ifnos)):
for k in range(len(polnos)):
sel.set_ifs(ifnos[j])
sel.set_polarizations(polnos[k])
sel.set_types(types[2*i+1])
try:
#ss.set_selection(sel)
ssubon.set_selection(sel)
except:
continue
ll.append(numpy.array(ss._getspectrum(0)))
sel.reset()
#ss.set_selection()
ssubon.set_selection()
precal[keys[2*i+1]]=ll
#del ss
#sig=resspec.get_scan('*_fs')
#ref=resspec.get_scan('*_fsr')
sel.set_types( srctype.fson )
resspec.set_selection( sel )
sig=resspec.copy()
resspec.set_selection()
sel.reset()
sel.set_type( srctype.fsoff )
resspec.set_selection( sel )
ref=resspec.copy()
resspec.set_selection()
sel.reset()
for k in range(len(polnos)):
for j in range(len(ifnos)):
sel.set_ifs(ifnos[j])
sel.set_polarizations(polnos[k])
try:
sig.set_selection(sel)
postcal.append(numpy.array(sig._getspectrum(0)))
except:
ref.set_selection(sel)
postcal.append(numpy.array(ref._getspectrum(0)))
sel.reset()
resspec.set_selection()
del sel
# plot
asaplog.post()
asaplog.push('Plot only first spectrum for each [if,pol] pairs to verify calibration.')
asaplog.post('WARN')
p=new_asaplot()
rcp('lines', linewidth=1)
#nr=min(6,len(ifnos)*len(polnos))
nr=len(ifnos)/2*len(polnos)
titles=[]
btics=[]
if nr>3:
asaplog.post()
asaplog.push('Only first 3 [if,pol] pairs are plotted.')
asaplog.post('WARN')
nr=3
p.set_panels(rows=nr,cols=3,nplots=3*nr,ganged=False)
for i in range(3*nr):
b=False
if i >= 3*nr-3:
b=True
btics.append(b)
for i in range(nr):
p.subplot(3*i)
p.color=0
title='raw data IF%s,%s POL%s' % (ifnos[2*int(i/len(polnos))],ifnos[2*int(i/len(polnos))+1],polnos[i%len(polnos)])
titles.append(title)
#p.set_axes('title',title,fontsize=40)
ymin=1.0e100
ymax=-1.0e100
nchan=s.nchan(ifnos[2*int(i/len(polnos))])
edge=int(nchan*0.01)
for j in range(4):
spmin=min(precal[keys[j]][i][edge:nchan-edge])
spmax=max(precal[keys[j]][i][edge:nchan-edge])
ymin=min(ymin,spmin)
ymax=max(ymax,spmax)
for j in range(4):
if i==0:
p.set_line(label=keys[j])
else:
p.legend()
p.plot(precal[keys[j]][i])
p.axes.set_ylim(ymin-0.1*abs(ymin),ymax+0.1*abs(ymax))
if not btics[3*i]:
p.axes.set_xticks([])
p.subplot(3*i+1)
p.color=0
title='sig data IF%s POL%s' % (ifnos[2*int(i/len(polnos))],polnos[i%len(polnos)])
titles.append(title)
#p.set_axes('title',title)
p.legend()
ymin=postcal[2*i][edge:nchan-edge].min()
ymax=postcal[2*i][edge:nchan-edge].max()
p.plot(postcal[2*i])
p.axes.set_ylim(ymin-0.1*abs(ymin),ymax+0.1*abs(ymax))
if not btics[3*i+1]:
p.axes.set_xticks([])
p.subplot(3*i+2)
p.color=0
title='ref data IF%s POL%s' % (ifnos[2*int(i/len(polnos))+1],polnos[i%len(polnos)])
titles.append(title)
#p.set_axes('title',title)
p.legend()
ymin=postcal[2*i+1][edge:nchan-edge].min()
ymax=postcal[2*i+1][edge:nchan-edge].max()
p.plot(postcal[2*i+1])
p.axes.set_ylim(ymin-0.1*abs(ymin),ymax+0.1*abs(ymax))
if not btics[3*i+2]:
p.axes.set_xticks([])
for i in range(3*nr):
p.subplot(i)
p.set_axes('title',titles[i],fontsize='medium')
x=raw_input('Accept calibration ([y]/n): ' )
if x.upper() == 'N':
p.quit()
del p
return scantab
p.quit()
del p
###
resspec._add_history("calfs",varlist)
return resspec
for k in range(len(polnos)):
sel.set_ifs(ifnos[j])
sel.set_polarizations(polnos[k])
try:
ress.set_selection(sel)
except:
continue
postcal.append(numpy.array(ress._getspectrum(0)))
sel.reset()
ress.set_selection()
del sel
# plot
asaplog.post()
asaplog.push('Plot only first spectrum for each [if,pol] pairs to verify calibration.')
asaplog.post('WARN')
p=new_asaplot()
rcp('lines', linewidth=1)
#nr=min(6,len(ifnos)*len(polnos))
nr=len(ifnos)*len(polnos)
titles=[]
btics=[]
if nr<4:
p.set_panels(rows=nr,cols=2,nplots=2*nr,ganged=False)
for i in range(2*nr):
b=False
if i >= 2*nr-2:
b=True
btics.append(b)
elif nr==4:
p.set_panels(rows=2,cols=4,nplots=8,ganged=False)
for i in range(2*nr):
def plot(self,
residual=False,
components=None,
plotparms=False,
filename=None):
"""
Plot the last fit.
Parameters:
residual: an optional parameter indicating if the residual
should be plotted (default 'False')
components: a list of components to plot, e.g [0,1],
-1 plots the total fit. Default is to only
plot the total fit.
plotparms: Inidicates if the parameter values should be present
on the plot
"""
from matplotlib import rc as rcp
if not self.fitted:
return
#if not self._p or self._p.is_dead:
if not (self._p and self._p._alive()):
from asap.asapplotter import new_asaplot
del self._p
self._p = new_asaplot(rcParams['plotter.gui'])
self._p.hold()
self._p.clear()
rcp('lines', linewidth=1)
self._p.set_panels()
self._p.palette(0)
tlab = 'Spectrum'
xlab = 'Abcissa'
ylab = 'Ordinate'
from numpy import ma, logical_not, logical_and, array
m = self.mask
if self.data:
tlab = self.data._getsourcename(self._fittedrow)
xlab = self.data._getabcissalabel(self._fittedrow)
if self.data._getflagrow(self._fittedrow):
m = [False]
else:
m = logical_and(
self.mask,
array(self.data._getmask(self._fittedrow), copy=False))
ylab = self.data._get_ordinate_label()
colours = [
"#777777", "#dddddd", "red", "orange", "purple", "green",
"magenta", "cyan"
]
nomask = True
for i in range(len(m)):
nomask = nomask and m[i]
if len(m) == 1:
m = m[0]
invm = (not m)
else:
invm = logical_not(m)
label0 = 'Masked Region'
label1 = 'Spectrum'
if (nomask):
label0 = label1
else:
y = ma.masked_array(self.y, mask=m)
self._p.palette(1, colours)
self._p.set_line(label=label1)
self._p.plot(self.x, y)
self._p.palette(0, colours)
self._p.set_line(label=label0)
y = ma.masked_array(self.y, mask=invm)
self._p.plot(self.x, y)
if residual:
self._p.palette(7)
self._p.set_line(label='Residual')
y = ma.masked_array(self.get_residual(), mask=invm)
self._p.plot(self.x, y)
self._p.palette(2)
if components is not None:
cs = components
if isinstance(components, int): cs = [components]
if plotparms:
self._p.text(0.15,
0.15,
str(self.get_parameters()['formatted']),
size=8)
n = len(self.components)
self._p.palette(3)
for c in cs:
if 0 <= c < n:
lab = self.fitfuncs[c] + str(c)
self._p.set_line(label=lab)
y = ma.masked_array(self.fitter.evaluate(c), mask=invm)
self._p.plot(self.x, y)
elif c == -1:
self._p.palette(2)
self._p.set_line(label="Total Fit")
y = ma.masked_array(self.fitter.getfit(), mask=invm)
self._p.plot(self.x, y)
else:
self._p.palette(2)
self._p.set_line(label='Fit')
y = ma.masked_array(self.fitter.getfit(), mask=invm)
self._p.plot(self.x, y)
xlim = [min(self.x), max(self.x)]
self._p.axes.set_xlim(xlim)
self._p.set_axes('xlabel', xlab)
self._p.set_axes('ylabel', ylab)
self._p.set_axes('title', tlab)
self._p.release()
if (not rcParams['plotter.gui']):
self._p.save(filename)
