def test_disabled():
asaplog.disable()
msg = "TEST"
asaplog.push(msg)
asaplog.post()
out = "".join(stdout_redirect.content).strip()
assert_equals(out, '')
def _update_mask(self):
# Min and Max for new mask
xstart = self.rect['world'][0]
xend = self.rect['world'][2]
if xstart <= xend: newlist=[xstart,xend]
else: newlist = [xend,xstart]
# Mask or unmask
invmask = None
if self.rect['button'] == 1:
invmask = False
mflg = 'Mask'
elif self.rect['button'] == 3:
invmask = True
mflg = 'UNmask'
asaplog.push(mflg+': '+str(newlist))
asaplog.post()
newmask = self.scan.create_mask(newlist,invert=invmask)
# Logic operation to update mask
if invmask:
self.mask = mask_and(self.mask,newmask)
else:
self.mask = mask_or(self.mask,newmask)
# Plot masked regions
#if self.showmask or not self.once: self._plot_mask()
if self.showmask: self._plot_mask()
def save(self, fname=None, orientation=None, dpi=None, papertype=None):
"""
Save the plot to a file.
fname is the name of the output file. The image format is determined
from the file suffix; 'png', 'ps', and 'eps' are recognized. If no
file name is specified 'yyyymmdd_hhmmss.png' is created in the current
directory.
"""
from asap import rcParams
if papertype is None:
papertype = rcParams['plotter.papertype']
if fname is None:
from datetime import datetime
dstr = datetime.now().strftime('%Y%m%d_%H%M%S')
fname = 'asap'+dstr+'.png'
d = ['png','.ps','eps', 'svg']
from os.path import expandvars
fname = expandvars(fname)
if fname[-3:].lower() in d:
try:
if fname[-3:].lower() == ".ps":
from matplotlib import __version__ as mv
w = self.figure.get_figwidth()
h = self.figure.get_figheight()
if orientation is None:
# oriented
if w > h:
orientation = 'landscape'
else:
orientation = 'portrait'
from matplotlib.backends.backend_ps import papersize
pw,ph = papersize[papertype.lower()]
ds = None
if orientation == 'landscape':
ds = min(ph/w, pw/h)
else:
ds = min(pw/w, ph/h)
ow = ds * w
oh = ds * h
self.figure.set_size_inches((ow, oh))
self.figure.savefig(fname, orientation=orientation,
papertype=papertype.lower())
self.figure.set_size_inches((w, h))
print 'Written file %s' % (fname)
else:
if dpi is None:
dpi =150
self.figure.savefig(fname,dpi=dpi)
print 'Written file %s' % (fname)
except IOError, msg:
#print 'Failed to save %s: Error msg was\n\n%s' % (fname, err)
asaplog.post()
asaplog.push('Failed to save %s: Error msg was\n\n%s' % (fname, str(msg)))
asaplog.post( 'ERROR' )
return
def test_level():
asaplog.enable()
msg = "TEST"
asaplog.push(msg)
asaplog.post('ERROR')
out = "".join(stdout_redirect.content).strip()
assert_equals(out, "SEVERE: "+msg)
def set_panelling(self,which='r'):
""" This function is not available for the class flagplotter """
if which.lower().startswith('r'):
return
msg = "Pannel setting is fixed to row mode in 'flagplotter'"
asaplog.push(msg)
asaplog.post('ERROR')
self._panelling = 'r'
def stat_cal(self):
if not self._any_selection():
msg = "No selection to be calculated"
asaplog.push(msg)
asaplog.post('WARN')
return
self._selected_stats(rows=self._selpanels,regions=self._selregions)
self._clearup_selections(refresh=True)
def auto_fit(self, insitu=None, plot=False):
"""
Return a scan where the function is applied to all rows for
all Beams/IFs/Pols.
"""
from asap import scantable
if not isinstance(self.data, scantable):
msg = "Data is not a scantable"
raise TypeError(msg)
if insitu is None:
insitu = rcParams["insitu"]
if not insitu:
scan = self.data.copy()
else:
scan = self.data
rows = xrange(scan.nrow())
# Save parameters of baseline fits as a class attribute.
# NOTICE: This does not reflect changes in scantable!
if len(rows) > 0:
self.blpars = []
asaplog.push("Fitting:")
for r in rows:
out = " Scan[%d] Beam[%d] IF[%d] Pol[%d] Cycle[%d]" % (
scan.getscan(r),
scan.getbeam(r),
scan.getif(r),
scan.getpol(r),
scan.getcycle(r),
)
asaplog.push(out, False)
self.x = scan._getabcissa(r)
self.y = scan._getspectrum(r)
# self.mask = mask_and(self.mask, scan._getmask(r))
if len(self.x) == len(self.mask):
self.mask = mask_and(self.mask, self.data._getmask(row))
else:
asaplog.push("lengths of data and mask are not the same. " "preset mask will be ignored")
asaplog.post("WARN", "asapfit.fit")
self.mask = self.data._getmask(row)
self.data = None
self.fit()
x = self.get_parameters()
fpar = self.get_parameters()
if plot:
self.plot(residual=True)
x = raw_input("Accept fit ([y]/n): ")
if x.upper() == "N":
self.blpars.append(None)
continue
scan._setspectrum(self.fitter.getresidual(), r)
self.blpars.append(fpar)
if plot:
self._p.quit()
del self._p
self._p = None
return scan
def unmap(self):
"""
Hide the ASAPlot graphics window.
"""
if not self.window:
asaplog.push( "No plotter window to unmap." )
asaplog.post( "WARN" )
return
self.window.wm_withdraw()
def test_push():
asaplog.enable()
msg = "TEST"
asaplog.push(msg)
asaplog.push(msg)
asaplog.post()
input = "\n".join([msg]*2)
out = "".join(stdout_redirect.content).strip()
assert_equals(out, input)
def unmap(self):
"""
Hide the ASAPlot graphics window.
"""
if not self.window:
asaplog.push("No plotter window to unmap.")
asaplog.post("WARN")
return
self.window.wm_withdraw()
def terminate(self):
"""
Clear the figure.
"""
if not self.window:
asaplog.push("No plotter window to terminate.")
asaplog.post("WARN")
return
self.window.destroy()
def terminate(self):
"""
Clear the figure.
"""
if not self.window:
asaplog.push( "No plotter window to terminate." )
asaplog.post( "WARN" )
return
self.window.destroy()
def auto_fit(self, insitu=None, plot=False):
"""
Return a scan where the function is applied to all rows for
all Beams/IFs/Pols.
"""
from asap import scantable
if not isinstance(self.data, scantable):
msg = "Data is not a scantable"
raise TypeError(msg)
if insitu is None: insitu = rcParams['insitu']
if not insitu:
scan = self.data.copy()
else:
scan = self.data
rows = xrange(scan.nrow())
# Save parameters of baseline fits as a class attribute.
# NOTICE: This does not reflect changes in scantable!
if len(rows) > 0: self.blpars = []
asaplog.push("Fitting:")
for r in rows:
out = " Scan[%d] Beam[%d] IF[%d] Pol[%d] Cycle[%d]" % (
scan.getscan(r), scan.getbeam(r), scan.getif(r),
scan.getpol(r), scan.getcycle(r))
asaplog.push(out, False)
self.x = scan._getabcissa(r)
self.y = scan._getspectrum(r)
#self.mask = mask_and(self.mask, scan._getmask(r))
if len(self.x) == len(self.mask):
self.mask = mask_and(self.mask, self.data._getmask(row))
else:
asaplog.push('lengths of data and mask are not the same. '
'preset mask will be ignored')
asaplog.post('WARN', 'asapfit.fit')
self.mask = self.data._getmask(row)
self.data = None
self.fit()
x = self.get_parameters()
fpar = self.get_parameters()
if plot:
self.plot(residual=True)
x = raw_input("Accept fit ([y]/n): ")
if x.upper() == 'N':
self.blpars.append(None)
continue
scan._setspectrum(self.fitter.getresidual(), r)
self.blpars.append(fpar)
if plot:
self._p.quit()
del self._p
self._p = None
return scan
def separate(self, outname="", overwrite=False):
"""
Invoke sideband separation.
outname : a name of output scantable
overwrite : overwrite existing table
"""
out_default = "sbseparated.asap"
if len(outname) == 0:
outname = out_default
asaplog.post()
asaplog.push("The output file name is not specified.")
asaplog.push("Using default name '%s'" % outname)
asaplog.post("WARN")
if os.path.exists(outname):
if overwrite:
asaplog.push("removing the old file '%s'" % outname)
shutil.rmtree(outname)
else:
asaplog.post()
asaplog.push("Output file '%s' already exists." % outname)
asaplog.post("ERROR")
return False
self._separator.separate(outname)
def _selected_stats(self,rows=None,regions=None):
# check for the validity of plotter and get the plotter
theplotter = self._get_plotter()
scan = theplotter._data
if not scan:
asaplog.post()
asaplog.push("Invalid scantable")
asaplog.post("ERROR")
mathobj = stmath( rcParams['insitu'] )
statval = {}
statstr = ['max', 'min', 'mean', 'median', 'sum', 'stddev', 'rms']
if isinstance(rows, list) and len(rows) > 0:
for irow in rows:
for stat in statstr:
statval[stat] = mathobj._statsrow(scan,[],stat,irow)[0]
self._print_stats(scan,irow,statval,statstr=statstr)
del irow
if isinstance(regions,dict) and len(regions) > 0:
for srow, masklist in regions.iteritems():
if not isinstance(masklist,list) or len(masklist) ==0:
msg = "Ignoring invalid region selection for row = "+srow
asaplog.post()
asaplog.push(msg)
asaplog.post("WARN")
continue
irow = int(srow)
mask = scan.create_mask(masklist,invert=False,row=irow)
for stat in statstr:
statval[stat] = mathobj._statsrow(scan,mask,stat,irow)[0]
self._print_stats(scan,irow,statval,statstr=statstr,
mask=masklist)
del irow, mask
del srow, masklist
del scan, statval, mathobj
def _flag_operation(self,rows=None,regions=None,unflag=False):
# check for the validity of plotter and get the plotter
theplotter = self._get_plotter()
scan = theplotter._data
if not scan:
asaplog.post()
asaplog.push("Invalid scantable")
asaplog.post("ERROR")
if isinstance(rows,list) and len(rows) > 0:
scan.flag_row(rows=rows,unflag=unflag)
if isinstance(regions,dict) and len(regions) > 0:
for srow, masklist in regions.iteritems():
if not isinstance(masklist,list) or len(masklist) ==0:
msg = "Ignoring invalid region selection for row = "+srow
asaplog.post()
asaplog.push(msg)
asaplog.post("WARN")
continue
irow = int(srow)
mask = scan.create_mask(masklist,invert=False,row=irow)
scan.flag(row=irow,mask=mask,unflag=unflag)
del irow, mask
del srow, masklist
del scan
def _new_custombar(self):
backend = matplotlib.get_backend()
# Flag plotter relys on supported GUI backends
if not self._visible:
asaplog.push("GUI backend is not available")
asaplog.post("ERROR")
elif backend == "TkAgg":
from asap.customgui_tkagg import CustomFlagToolbarTkAgg
return CustomFlagToolbarTkAgg(self)
elif backend == "Qt4Agg":
from asap.customgui_qt4agg import CustomFlagToolbarQT4Agg
return CustomFlagToolbarQT4Agg(self)
else:
asaplog.push("Unsupported backend for interactive flagging. Use either TkAgg or PyQt4Agg")
asaplog.post("ERROR")
def _new_page(self,goback=False):
# check for the validity of plotter and get the plotter
theplotter = self._get_plotter()
top = None
header = theplotter._headtext
reset = False
doheader = (isinstance(header['textobj'],list) and \
len(header['textobj']) > 0)
if doheader:
top = theplotter._plotter.figure.subplotpars.top
fontsize = header['textobj'][0].get_fontproperties().get_size()
if theplotter._startrow <= 0:
msg = "The page counter is reset due to chages of plot settings. "
msg += "Plotting from the first page."
asaplog.push(msg)
asaplog.post('WARN')
reset = True
goback = False
if doheader:
extrastr = selstr = ''
if header.has_key('extrastr'):
extrastr = header['extrastr']
if header.has_key('selstr'):
selstr = header['selstr']
theplotter._reset_header()
theplotter._plotter.hold()
if goback:
self._set_prevpage_counter()
#theplotter._plotter.clear()
theplotter._plot(theplotter._data)
pagenum = self._get_pagenum()
self.set_pagecounter(pagenum)
# Plot header information
#if header['textobj']:
if doheader and pagenum == 1:
if top and top != theplotter._margins[3]:
# work around for sdplot in CASA. complete checking in future?
theplotter._plotter.figure.subplots_adjust(top=top)
if reset:
theplotter.print_header(plot=True,fontsize=fontsize,selstr=selstr, extrastr=extrastr)
else:
theplotter._header_plot(header['string'],fontsize=fontsize)
theplotter._plotter.release()
theplotter._plotter.tidy()
theplotter._plotter.show(hardrefresh=False)
del top
def _set_plot_counter(self, pagemode):
## page operation should be either "previous", "current", or "next"
availpage = ["p","c","n"]
pageop = pagemode[0].lower()
if not (pageop in availpage):
asaplog.post()
asaplog.push("Invalid page operation")
asaplog.post("ERROR")
if pageop == "n":
# nothing necessary to plot the next page
return
# check for the validity of plotter and get the plotter
theplotter = self._get_plotter()
# set row and panel counters to those of the 1st panel of previous page
maxpanel = 25
# the ID of the last panel in current plot
lastpanel = theplotter._ipanel
# the number of current subplots
currpnum = len(theplotter._plotter.subplots)
# the nuber of previous subplots
start_ipanel = None
if pageop == "c":
start_ipanel = max(lastpanel-currpnum+1, 0)
else:
## previous page
prevpnum = None
if theplotter._rows and theplotter._cols:
# when user set layout
prevpnum = theplotter._rows*theplotter._cols
else:
# no user specification
prevpnum = maxpanel
start_ipanel = max(lastpanel-currpnum-prevpnum+1, 0)
del prevpnum
# set the pannel ID of the last panel of the prev(-prev) page
theplotter._ipanel = start_ipanel-1
if theplotter._panelling == 'r':
theplotter._startrow = start_ipanel
else:
# the start row number of the next panel
theplotter._startrow = theplotter._panelrows[start_ipanel]
del lastpanel,currpnum,start_ipanel
def __init__(self,plotter=None, scan=None):
"""
Create a interactive masking object.
Either or both 'plotter' or/and 'scan' should be defined.
Parameters:
plotter: an ASAP plotter object for interactive selection
scan: a scantable to create a mask interactively
"""
# Return if GUI is not active
if not rcParams['plotter.gui']:
msg = 'GUI plotter is disabled.\n'
msg += 'Exit interactive mode.'
asaplog.push(msg)
asaplog.post("ERROR")
return
# Verify input parameters
if scan is None and plotter is None:
msg = "Either scantable or plotter should be defined."
raise TypeError(msg)
self.scan = None
self.p = None
self.newplot = False
if scan and isinstance(scan, scantable):
self.scan = scan
from asap.asapplotter import asapplotter
if plotter and isinstance(plotter,asapplotter):
self.p = plotter
if self.scan is None and isinstance(self.p._data,scantable):
self.scan = self.p._data
if self.scan is None:
msg = "Invalid scantable."
raise TypeError(msg)
self.mask = _n_bools(self.scan.nchan(self.scan.getif(0)),True)
self.callback = None
self.event = None
self.once = False
self.showmask = True
self.rect = {}
self.xold = None
self.yold = None
self.xdataold = None
self.ydataold = None
self._polygons = []
def _create_flag_from_array(self,x,masklist,invert):
# Return True for channels which should be EXCLUDED (flag)
if len(masklist) <= 1:
asaplog.push()
asaplog.post("masklist should be a list of 2 elements")
asaplog.push("ERROR")
n = len(x)
# Base mask: flag out all channels
mask = _n_bools(n, True)
minval = min(masklist[0:2])
maxval = max(masklist[0:2])
for i in range(n):
if minval <= x[i] <= maxval:
mask[i] = False
if invert:
mask = mask_not(mask)
return mask
def _subplot_stats(self,selection):
statstr = ['max', 'min', 'median', 'mean', 'sum', 'std'] #'rms']
panelstr = selection['axes'].title.get_text()
ssep = "-"*70
asaplog.push(ssep)
asaplog.post()
for line in selection['axes'].lines:
# Don't include annotations
if line.get_label().startswith("_"):
continue
label = panelstr + ", "+line.get_label()
x = line.get_xdata()
newmsk = None
selmsk = self._create_flag_from_array(x,
selection['worldx'],
selection['invert'])
ydat = None
y = line.get_ydata()
if numpy.ma.isMaskedArray(y):
ydat = y.data
basemsk = y.mask
else:
ydat = y
basemsk = False
if not isinstance(basemsk, bool):
# should be ndarray
newmsk = mask_or(selmsk, basemsk)
elif basemsk:
# the whole original spectrum is flagged
newmsk = basemsk
else:
# no channel was flagged originally
newmsk = selmsk
mdata = numpy.ma.masked_array(ydat, mask=newmsk)
statval = {}
for stat in statstr:
# need to get the stat functions from the ma module!!!
statval[stat] = getattr(numpy.ma,stat)(mdata)
self._print_stats(statval, statstr=statstr, label=label,\
mask=selection['worldx'],\
unmask=selection['invert'])
asaplog.push(ssep)
asaplog.post()
def _plot_page(self,pagemode="next"):
# check for the validity of plotter and get the plotter
theplotter = self._get_plotter()
if theplotter._startrow <= 0:
msg = "The page counter is reset due to chages of plot settings. "
msg += "Plotting from the first page."
asaplog.post()
asaplog.push(msg)
asaplog.post('WARN')
goback = False
theplotter._plotter.hold()
#theplotter._plotter.legend(1)
self._set_plot_counter(pagemode)
theplotter._plot(theplotter._data)
self.set_pagecounter(self._get_pagenum())
theplotter._plotter.release()
theplotter._plotter.tidy()
theplotter._plotter.show(hardrefresh=False)
def unflag(self):
if not self._any_selection():
msg = "No selection to be Flagged"
asaplog.push(msg)
asaplog.post('WARN')
return
self._pause_buttons(operation="start",msg="Unflagging data...")
self._flag_operation(rows=self._selpanels,
regions=self._selregions,unflag=True)
sout = "Unflagged:\n"
sout += " rows = "+str(self._selpanels)+"\n"
sout += " regions: "+str(self._selregions)
asaplog.push(sout)
del sout
# check for the validity of plotter and get the plotter
theplotter = self._get_plotter()
theplotter._ismodified = True
self._clearup_selections(refresh=False)
self._plot_page(pagemode="current")
self._pause_buttons(operation="end")
def _print_stats(self,stats,statstr=None,label="",mask=None,unmask=False):
if not isinstance(stats,dict) or len(stats) == 0:
asaplog.post()
asaplog.push("Invalid statistic value")
asaplog.post("ERROR")
maskstr = "Not available"
if mask:
masktype = "mask"
maskstr = str(mask)
if unmask: masktype = "unmask"
sout = label + ", " + masktype + " = " + maskstr + "\n"
statvals = []
if not len(statstr):
statstr = stats.keys()
for key in statstr:
sout += key.ljust(10)
statvals.append(stats.pop(key))
sout += "\n"
sout += ("%f "*len(statstr) % tuple(statvals))
asaplog.push(sout)
def _add_region(self,event):
if not self.figmgr.toolbar.mode == '':
return
if event.button != 1 or event.inaxes == None:
return
# check for the validity of plotter and get the plotter
theplotter = self._get_plotter()
# this row resolution assumes row panelling
irow = int(self._getrownum(event.inaxes))
if irow in self._selpanels:
msg = "The whole spectrum is already selected"
asaplog.post()
asaplog.push(msg)
asaplog.post('WARN')
return
self._thisregion = {'axes': event.inaxes,'xs': event.x,
'worldx': [event.xdata,event.xdata]}
theplotter._plotter.register('button_press',None)
self.xold = event.x
self.xdataold = event.xdata
theplotter._plotter.register('motion_notify', self._xspan_draw)
theplotter._plotter.register('button_press', self._xspan_end)
def _plot_selections(self,regions=None,panels=None):
### mark panels/spectra selections in the page
if not self._any_selection() and not (regions or panels):
return
regions = regions or self._selregions.copy() or {}
panels = panels or self._selpanels or []
if not isinstance(regions,dict):
asaplog.post()
asaplog.push("Invalid region specification")
asaplog.post('ERROR')
if not isinstance(panels,list):
asaplog.post()
asaplog.push("Invalid panel specification")
asaplog.post('ERROR')
# check for the validity of plotter and get the plotter
theplotter = self._get_plotter()
strow = self._getrownum(theplotter._plotter.subplots[0]['axes'])
enrow = self._getrownum(theplotter._plotter.subplots[-1]['axes'])
for irow in range(int(strow),int(enrow)+1):
if regions.has_key(str(irow)):
ax = theplotter._plotter.subplots[irow - int(strow)]['axes']
mlist = regions.pop(str(irow))
# WORKAROUND for the issue axvspan started to reset xlim.
axlimx = ax.get_xlim()
for i in range(len(mlist)):
self._polygons.append(ax.axvspan(mlist[i][0],mlist[i][1],
facecolor='0.7'))
ax.set_xlim(axlimx)
del ax,mlist,axlimx
if irow in panels:
ax = theplotter._plotter.subplots[irow - int(strow)]['axes']
shadow = Rectangle((0,0),1,1,facecolor='0.7',
transform=ax.transAxes,visible=True)
self._polygons.append(ax.add_patch(shadow))
del ax,shadow
theplotter._plotter.canvas.draw()
del regions,panels,strow,enrow
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
precal[keys[2 * i + 1]] = ll
#del ss
for j in range(len(ifnos)):
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:
def set_range(self,xstart=None,xend=None,ystart=None,yend=None,refresh=False, offset=None):
""" This function is not available for the class flagplotter """
msg = "Plot range setting is not allowed in 'flagplotter'"
asaplog.push(msg)
asaplog.post('ERROR')
self._panelling = 'r'
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
def select_mask(self,once=False,showmask=True):
"""
Do interactive mask selection.
Modify masks interactively by adding/deleting regions with
mouse drawing.(left-button: mask; right-button: UNmask)
Note that the interactive region selection is available only
when GUI plotter is active.
Parameters:
once: If specified as True, you can modify masks only
once. Else if False, you can modify them repeatedly.
showmask: If specified as True, the masked regions are plotted
on the plotter.
Note this parameter is valid only when once=True.
Otherwise, maskes are forced to be plotted for reference.
"""
# Return if GUI is not active
if not rcParams['plotter.gui']:
msg = 'GUI plotter is disabled.\n'
msg += 'Exit interactive mode.'
asaplog.push(msg)
asaplog.post("ERROR")
return
self.once = once
if self.once:
self.showmask = showmask
else:
if not showmask:
asaplog.post()
asaplog.push('showmask spcification is ignored. Mask regions are plotted anyway.')
asaplog.post("WARN")
self.showmask = True
if not self.p:
asaplog.push('A new ASAP plotter will be loaded')
asaplog.post()
from asap.asapplotter import asapplotter
self.p = asapplotter()
self.newplot = True
self.p._assert_plotter(action='reload')
from matplotlib import rc as rcp
rcp('lines', linewidth=1)
# Plot selected spectra if needed
if self.scan != self.p._data:
if len(self.scan.getifnos()) > 16:
asaplog.post()
asaplog.push("Number of panels > 16. Plotting the first 16...")
asaplog.post("WARN")
# Need replot
self.p._legendloc = 1
self.p.plot(self.scan)
# disable casa toolbar
if self.p._plotter.figmgr.casabar:
self.p._plotter.figmgr.casabar.disable_button()
self.p._plotter.figmgr.casabar.disable_prev()
self.p._plotter.figmgr.casabar.disable_next()
for panel in self.p._plotter.subplots:
xmin, xmax = panel['axes'].get_xlim()
marg = 0.05*abs(xmax-xmin)
panel['axes'].set_xlim(xmin-marg, xmax+marg)
if rcParams['plotter.ganged']: break
self.p._plotter.show()
# Plot initial mask region
#if self.showmask or not self.once:
if self.showmask:
self._plot_mask()
print ''
print 'Selected regions are shaded with yellow. (gray: projections)'
print 'Now you can modify the selection.'
print 'Draw rectangles with Left-mouse to add the regions,'
print 'or with Right-mouse to exclude the regions.'
if self.event != None:
self._region_start(self.event)
else:
self.p._plotter.register('button_press',None)
self.p._plotter.register('button_press',self._region_start)
from matplotlib import _pylab_helpers
from asap.parameters import rcParams as asaprcParams
from asap.logging import asaplog
# API change in mpl >= 0.98
try:
from matplotlib.transforms import blended_transform_factory
except ImportError:
from matplotlib.transforms import blend_xy_sep_transform as blended_transform_factory
mvers = matplotlib.__version__.split(".")
if int(mvers[0]) == 0 and int(mvers[1]) < 99:
#print "Warning: matplotlib version < 0.87. This might cause errors. Please upgrade."
asaplog.push( "matplotlib version < 0.99. This might cause errors. Please upgrade." )
asaplog.post( 'WARN' )
class asaplotbase:
"""
ASAP plotting base class based on matplotlib.
"""
def __init__(self, rows=1, cols=0, title='', size=None, buffering=False):
"""
Create a new instance of the ASAPlot plotting class.
If rows < 1 then a separate call to set_panels() is required to define
the panel layout; refer to the doctext for set_panels().
"""
self.is_dead = False
self.figure = Figure(figsize=size, facecolor='#ddddee')
def fit(self, row=0, estimate=False):
"""
Execute the actual fitting process. All the state has to be set.
Parameters:
row: specify the row in the scantable
estimate: auto-compute an initial parameter set (default False)
This can be used to compute estimates even if fit was
called before.
Example:
s = scantable('myscan.asap')
s.set_cursor(thepol=1) # select second pol
f = fitter()
f.set_scan(s)
f.set_function(poly=0)
f.fit(row=0) # fit first row
"""
if ((self.x is None or self.y is None) and self.data is None) or self.fitfunc is None:
msg = "Fitter not yet initialised. Please set data & fit function"
raise RuntimeError(msg)
if self.data is not None:
if self.data._getflagrow(row):
raise RuntimeError, "Can not fit flagged row."
self.x = self.data._getabcissa(row)
self.y = self.data._getspectrum(row)
# self.mask = mask_and(self.mask, self.data._getmask(row))
if len(self.x) == len(self.mask):
self.mask = mask_and(self.mask, self.data._getmask(row))
else:
asaplog.push("lengths of data and mask are not the same. " "preset mask will be ignored")
asaplog.post("WARN", "asapfit.fit")
self.mask = self.data._getmask(row)
asaplog.push("Fitting:")
i = row
out = "Scan[%d] Beam[%d] IF[%d] Pol[%d] Cycle[%d]" % (
self.data.getscan(i),
self.data.getbeam(i),
self.data.getif(i),
self.data.getpol(i),
self.data.getcycle(i),
)
asaplog.push(out, False)
self.fitter.setdata(self.x, self.y, self.mask)
if self.fitfunc == "gauss" or self.fitfunc == "lorentz":
ps = self.fitter.getparameters()
if len(ps) == 0 or estimate:
self.fitter.estimate()
fxdpar = list(self.fitter.getfixedparameters())
if len(fxdpar) and fxdpar.count(0) == 0:
raise RuntimeError, "No point fitting, if all parameters are fixed."
if self._constraints:
for c in self._constraints:
self.fitter.addconstraint(c[0] + [c[-1]])
if self.uselinear:
converged = self.fitter.lfit()
else:
converged = self.fitter.fit()
if not converged:
raise RuntimeError, "Fit didn't converge."
self._fittedrow = row
self.fitted = True
return
def fit(self, row=0, estimate=False):
"""
Execute the actual fitting process. All the state has to be set.
Parameters:
row: specify the row in the scantable
estimate: auto-compute an initial parameter set (default False)
This can be used to compute estimates even if fit was
called before.
Example:
s = scantable('myscan.asap')
s.set_cursor(thepol=1) # select second pol
f = fitter()
f.set_scan(s)
f.set_function(poly=0)
f.fit(row=0) # fit first row
"""
if ((self.x is None or self.y is None) and self.data is None) \
or self.fitfunc is None:
msg = "Fitter not yet initialised. Please set data & fit function"
raise RuntimeError(msg)
if self.data is not None:
if self.data._getflagrow(row):
raise RuntimeError, "Can not fit flagged row."
self.x = self.data._getabcissa(row)
self.y = self.data._getspectrum(row)
#self.mask = mask_and(self.mask, self.data._getmask(row))
if len(self.x) == len(self.mask):
self.mask = mask_and(self.mask, self.data._getmask(row))
else:
asaplog.push('lengths of data and mask are not the same. '
'preset mask will be ignored')
asaplog.post('WARN', 'asapfit.fit')
self.mask = self.data._getmask(row)
asaplog.push("Fitting:")
i = row
out = "Scan[%d] Beam[%d] IF[%d] Pol[%d] Cycle[%d]" % (
self.data.getscan(i), self.data.getbeam(i), self.data.getif(i),
self.data.getpol(i), self.data.getcycle(i))
asaplog.push(out, False)
self.fitter.setdata(self.x, self.y, self.mask)
if self.fitfunc == 'gauss' or self.fitfunc == 'lorentz':
ps = self.fitter.getparameters()
if len(ps) == 0 or estimate:
self.fitter.estimate()
fxdpar = list(self.fitter.getfixedparameters())
if len(fxdpar) and fxdpar.count(0) == 0:
raise RuntimeError, "No point fitting, if all parameters are fixed."
if self._constraints:
for c in self._constraints:
self.fitter.addconstraint(c[0] + [c[-1]])
if self.uselinear:
converged = self.fitter.lfit()
else:
converged = self.fitter.fit()
if not converged:
raise RuntimeError, "Fit didn't converge."
self._fittedrow = row
self.fitted = True
return
def _print_stats(self,scan,row,stats,statstr=None,mask=None):
if not isinstance(scan, scantable):
asaplog.post()
asaplog.push("Invalid scantable")
asaplog.post("ERROR")
if row < 0 or row > scan.nrow():
asaplog.post()
asaplog.push("Invalid row number")
asaplog.post("ERROR")
if not isinstance(stats,dict) or len(stats) == 0:
asaplog.post()
asaplog.push("Invalid statistic value")
asaplog.post("ERROR")
maskstr = "All"
if mask:
maskstr = str(mask)
ssep = "-"*70+"\n"
sout = ssep
sout += ("Row=%d Scan=%d IF=%d Pol=%d Time=%s mask=%s" % \
(row, scan.getscan(row), scan.getif(row), scan.getpol(row), scan.get_time(row),maskstr))
sout += "\n"
statvals = []
if not len(statstr):
statstr = stats.keys()
for key in statstr:
sout += key.ljust(10)
statvals.append(stats.pop(key))
sout += "\n"
sout += ("%f "*len(statstr) % tuple(statvals))
sout += "\n"+ssep
asaplog.push(sout)
del sout, ssep, maskstr, statvals, key, scan, row, stats, statstr, mask