def interactive_flag(self):
from matplotlib import rc as rcp
rcp('lines', linewidth=1)
guiflagger = flagplotter(visible=True)
#guiflagger.set_legend(loc=1,refresh=False)
guiflagger.set_showflagged(self.showflagged)
guiflagger.plot(self.scan)
finish = raw_input("Press enter to finish interactive flagging:")
guiflagger._plotter.unmap()
ismodified = guiflagger._ismodified
guiflagger._plotter = None
self.anyflag = ismodified
def interactive_flag(self):
from matplotlib import rc as rcp
rcp('lines', linewidth=1)
guiflagger = flagplotter(visible=True)
#guiflagger.set_legend(loc=1,refresh=False)
guiflagger.set_showflagged(self.showflagged)
guiflagger.plot(self.scan)
finish=raw_input("Press enter to finish interactive flagging:")
guiflagger._plotter.unmap()
ismodified = guiflagger._ismodified
guiflagger._plotter = None
self.anyflag = ismodified
def __init_plot(self):
n = self.scan.nrow()
if n > 16:
casalog.post( 'Only first 16 results are plotted.', priority = 'WARN' )
n = 16
# initialize plotter
from matplotlib import rc as rcp
rcp('lines', linewidth=1)
if not (self.fitter._p and self.fitter._p._alive()):
self.fitter._p = sdutil.get_plotter(self.plotlevel)
self.fitter._p.hold()
self.fitter._p.clear()
# set nrow and ncol (maximum 4x4)
self.fitter._p.set_panels(rows=n, cols=0, ganged=False)
casalog.post( 'nrow,ncol= %d,%d' % (self.fitter._p.rows, self.fitter._p.cols ) )
self.fitter._p.palette(0,["#777777", "#dddddd", "red", "orange", "purple", "green", "magenta", "cyan"])
def __init_plot(self):
n = self.scan.nrow()
if n > 16:
casalog.post('Only first 16 results are plotted.', priority='WARN')
n = 16
# initialize plotter
from matplotlib import rc as rcp
rcp('lines', linewidth=1)
if not (self.fitter._p and self.fitter._p._alive()):
self.fitter._p = sdutil.get_plotter(self.plotlevel)
self.fitter._p.hold()
self.fitter._p.clear()
# set nrow and ncol (maximum 4x4)
self.fitter._p.set_panels(rows=n, cols=0, ganged=False)
casalog.post('nrow,ncol= %d,%d' %
(self.fitter._p.rows, self.fitter._p.cols))
self.fitter._p.palette(0, [
"#777777", "#dddddd", "red", "orange", "purple", "green",
"magenta", "cyan"
])
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
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):
b = False
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)
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
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):
b=False
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)