def plot1D(self, ctfSet, ctfId):
ctfModel = ctfSet[ctfId]
psdFn = ctfModel.getPsdFile()
fn = os.path.join(
pwutils.removeExt(psdFn).replace("_ctf", "") + '_EPA.log')
xplotter = EmPlotter(windowTitle='GCTF results')
plot_title = '%s # %d\n' % (ctfSet.getTsId(),
ctfId) + getPlotSubtitle(ctfModel)
a = xplotter.createSubPlot(plot_title, 'Resolution (Angstroms)', 'CTF')
a.invert_xaxis()
version = Plugin.getActiveVersion()
curves = [1, 4, 5] if version == '1.18' else [1, 3, 4]
for i in curves:
_plotCurve(a, i, fn)
xplotter.showLegend([
'simulated CTF',
# 'equiphase avg.',
# 'bg', # only for v1.18
'equiphase avg. - bg',
'cross correlation'
])
a.grid(True)
return xplotter
def createCtfPlot(ctfSet, ctfId):
""" Create EmPlotter instance. """
ctfModel = ctfSet[ctfId]
psdFn = ctfModel.getPsdFile()
fn = removeExt(psdFn) + "_avrot.txt"
xplotter = EmPlotter(windowTitle='CTFFind results')
plot_title = getPlotSubtitle(ctfModel)
a = xplotter.createSubPlot(plot_title, 'Spacial frequency (1/A)',
'Amplitude (or cross-correlation)')
legendName = ['Amplitude spectrum', 'CTF Fit', 'Quality of fit']
_plotCurves(a, fn)
xplotter.showLegend(legendName, loc='upper right')
a.set_ylim([-0.1, 1.1])
a.grid(True)
xplotter.show()
def _showGuinier(self, volume):
nrefs = len(self._refsList)
gridsize = self._getGridSize(nrefs)
guinierFn = volume + ".guinier"
d2 = self._getGuinierValue(guinierFn, 0)
legends = ["lnFweighted ln(F)", "corrected ln(F)", "model"]
xplotter = EmPlotter(*gridsize, windowTitle='Guinier Plots')
subPlot = xplotter.createSubPlot(basename(volume),
'd^-2(A^-2)',
'ln(F)',
yformat=False)
for i, legend in enumerate(legends):
y = self._getGuinierValue(guinierFn, i + 2)
subPlot.plot(d2, y)
xplotter.showLegend(legends)
subPlot.grid(True)
return xplotter
def createCtfPlot(ctfSet, ctfId):
ctfModel = ctfSet[ctfId]
psdFn = ctfModel.getPsdFile()
fn = pwutils.removeExt(psdFn) + "_EPA.log"
xplotter = EmPlotter(windowTitle='CTF Fitting')
plot_title = getPlotSubtitle(ctfModel)
a = xplotter.createSubPlot(plot_title, 'Resolution (Angstroms)', 'CTF')
a.invert_xaxis()
version = Plugin.getActiveVersion()
curves = [1, 4, 5] if version == '1.18' else [1, 3, 4]
for i in curves:
_plotCurve(a, i, fn)
xplotter.showLegend([
'simulated CTF',
# 'equiphase avg.',
# 'bg', # only for v1.18
'equiphase avg. - bg',
'cross correlation'
])
a.grid(True)
xplotter.show()
def _showFSC(self, paramName=None):
threshold = self.resolutionThresholdFSC.get()
iterations = self._getIterations()
groups = self._getGroups()
if self.isGoldStdProt():
template = 'fscdoc_m_%02d.stk'
title = 'Masked FSC'
else:
template = 'fscdoc_%02d.stk'
title = 'FSC'
if self.groupFSC == 0: # group by iterations
files = [(it, self._getFinalPath(template % it))
for it in iterations]
legendPrefix = 'iter'
else:
it = iterations[-1] # show only last iteration
legendPrefix = 'group'
def group(f): # retrieve the group number
return int(f.split('_')[-1].split('.')[0])
groupFiles = glob(self._getFinalPath('ofscdoc_%02d_???.stk' % it))
groupFiles.sort()
files = [(group(f), f) for f in groupFiles if group(f) in groups]
if not files: # empty files
return [
self.errorMessage("Please select valid groups to display",
title="Wrong groups selection")
]
plotter = EmPlotter(x=1, y=1, windowTitle='Resolution FSC')
a = plotter.createSubPlot(title, 'Angstroms^-1', 'FSC', yformat=False)
legends = []
for it, fscFile in files:
if os.path.exists(fscFile):
self._plotFSC(a, fscFile)
legends.append('%s %d' % (legendPrefix, it))
else:
print("Missing file: ", fscFile)
# plot final FSC curve (from BP)
if self.groupFSC == 0 and not self.isGoldStdProt():
lastIter = self.protocol._getLastIterNumber()
if lastIter in iterations:
fscFinalFile = self._getFinalPath('ofscdoc_%02d.stk' %
lastIter)
if os.path.exists(fscFinalFile):
self._plotFSC(a, fscFinalFile)
legends.append('final')
if threshold < self.maxfsc:
a.plot([self.minInv, self.maxInv], [threshold, threshold],
color='black',
linestyle='--')
plotter.showLegend(legends)
a.grid(True)
return [plotter]
