def _showFSC(self, paramName=None):
threshold = self.resolutionThreshold.get()
nrefs = len(self._refsList)
gridsize = self._getGridSize(nrefs)
xmipp.activateMathExtensions()
for ref3d in self._refsList:
xplotter = XmippPlotter(*gridsize, windowTitle='Resolution FSC')
legends = []
show = False
plot_title = 'Ref3D_%s' % ref3d
a = xplotter.createSubPlot(plot_title, 'frequency(1/A)', 'FSC', yformat=False)
legends = []
for it in self._iterations:
file_name = self.protocol._getFileName('resolutionXmdFile', iter=it, ref=ref3d)
if exists(file_name):
show = True
legends.append('iter %d' % it)
self._plotFSC(a, file_name)
xplotter.showLegend(legends)
if show:
if threshold < self.maxFrc:
a.plot([self.minInv, self.maxInv],[threshold, threshold], color='black', linestyle='--')
a.grid(True)
else:
raise Exception("Set a valid iteration to show its FSC")
return [xplotter]
def _showFSC(self, paramName=None):
threshold = self.resolutionThreshold.get()
nrefs = len(self._refsList)
gridsize = self._getGridSize(nrefs)
xmipp.activateMathExtensions()
for ref3d in self._refsList:
xplotter = XmippPlotter(*gridsize, windowTitle='Resolution FSC')
legends = []
show = False
plot_title = 'Ref3D_%s' % ref3d
a = xplotter.createSubPlot(plot_title,
'frequency(1/A)',
'FSC',
yformat=False)
legends = []
for it in self._iterations:
file_name = self.protocol._getFileName('resolutionXmdFile',
iter=it,
ref=ref3d)
if exists(file_name):
show = True
legends.append('iter %d' % it)
self._plotFSC(a, file_name)
xplotter.showLegend(legends)
if show:
if threshold < self.maxFrc:
a.plot([self.minInv, self.maxInv], [threshold, threshold],
color='black',
linestyle='--')
a.grid(True)
else:
raise Exception("Set a valid iteration to show its FSC")
return [xplotter]
def _plotDendrogram(self, e=None):
from pyworkflow.em.packages.xmipp3.plotter import XmippPlotter
xplotter = XmippPlotter()
self.plt = xplotter.createSubPlot("Dendrogram", "", "")
self.step = 0.25
self.rightMost = 0.0 # Used to arrange leaf nodes at the bottom
node = self.protocol.buildDendrogram()
self.plotNode(node, self.minHeight.get())
self.plt.set_xlim(0., self.rightMost + self.step)
self.plt.set_ylim(-10, 105)
return [xplotter]
def _plotDendrogram(self, e=None):
from pyworkflow.em.packages.xmipp3.plotter import XmippPlotter
xplotter = XmippPlotter()
self.plt = xplotter.createSubPlot("Dendrogram", "", "")
self.step = 0.25
self.rightMost = 0.0 # Used to arrange leaf nodes at the bottom
node = self.protocol.buildDendrogram()
self.plotNode(node, self.minHeight.get())
self.plt.set_xlim(0., self.rightMost + self.step)
self.plt.set_ylim(-10, 105)
return [xplotter]
def _createAngDist2D(self, it):
# Common variables to use
nrefs = len(self._refsList)
gridsize = self._getGridSize(nrefs)
xplotter = XmippPlotter(*gridsize, mainTitle='Iteration %d' % it, windowTitle="Angular Distribution")
for ref3d in self._refsList:
classesFn = self.protocol._getFileName('outClassesXmd', iter=it, ref=ref3d)
if exists(classesFn):
md = xmipp.MetaData(classesFn)
title = 'Ref3D_%d' % ref3d
xplotter.plotMdAngularDistribution(title, md)
else:
print "File %s does not exist" % classesFn
return None
return xplotter
def createSubPlot(self, title, xlabel, ylabel):
if self.useLastPlot and self.last_subplot:
ax = self.last_subplot
ax.cla()
ax.set_title(title)
else:
ax = XmippPlotter.createSubPlot(self, title, xlabel, ylabel)
return ax
def _createAngDist2D(self, it):
# Common variables to use
nrefs = len(self._refsList)
gridsize = self._getGridSize(nrefs)
xplotter = XmippPlotter(*gridsize,
mainTitle='Iteration %d' % it,
windowTitle="Angular Distribution")
for ref3d in self._refsList:
classesFn = self.protocol._getFileName('outClassesXmd',
iter=it,
ref=ref3d)
if exists(classesFn):
md = xmipp.MetaData(classesFn)
title = 'Ref3D_%d' % ref3d
xplotter.plotMdAngularDistribution(title, md)
else:
print "File %s does not exist" % classesFn
return None
return xplotter
def createPlots(protML, selectedPlots):
''' Launch some plot for an ML2D protocol run '''
from pyworkflow.em.packages.xmipp3.plotter import XmippPlotter
import xmipp
protML._plot_count = 0
lastIter = protML._lastIteration()
if lastIter == 0:
return
refs = protML._getIterClasses(it=lastIter, block='classes')
# if not exists(refs):
# return
# blocks = getBlocksInMetaDataFile(refs)
# lastBlock = blocks[-1]
def doPlot(plotName):
return plotName in selectedPlots
# Remove 'mirror' from list if DoMirror is false
if doPlot('doShowMirror') and not protML.doMirror:
selectedPlots.remove('doShowMirror')
n = len(selectedPlots)
if n == 0:
#showWarning("ML2D plots", "Nothing to plot", protML.master)
print "No plots"
return
elif n == 1:
gridsize = [1, 1]
elif n == 2:
gridsize = [2, 1]
else:
gridsize = [2, 2]
xplotter = XmippPlotter(x=gridsize[0], y=gridsize[1])
# Create data to plot
iters = range(1, lastIter+1)
ll = []
pmax = []
for iter in iters:
logs = protML._getIterClasses(it=iter, block='info')
md = xmipp.MetaData(logs)
id = md.firstObject()
ll.append(md.getValue(xmipp.MDL_LL, id))
pmax.append(md.getValue(xmipp.MDL_PMAX, id))
if doPlot('doShowLL'):
a = xplotter.createSubPlot('Log-likelihood (should increase)', 'iterations', 'LL', yformat=True)
a.plot(iters, ll)
#Create plot of mirror for last iteration
if doPlot('doShowMirror'):
from numpy import arange
from matplotlib.ticker import FormatStrFormatter
md = xmipp.MetaData(refs)
mirrors = [md.getValue(xmipp.MDL_MIRRORFRAC, id) for id in md]
nrefs = len(mirrors)
ind = arange(1, nrefs + 1)
width = 0.85
a = xplotter.createSubPlot('Mirror fractions on last iteration', 'classes', 'mirror fraction')
a.set_xticks(ind + 0.45)
a.xaxis.set_major_formatter(FormatStrFormatter('%1.0f'))
a.bar(ind, mirrors, width, color='b')
a.set_ylim([0, 1.])
a.set_xlim([0.8, nrefs + 1])
if doPlot('doShowPmax'):
a = xplotter.createSubPlot('Probabilities distribution', 'iterations', 'Pmax/Psum')
a.plot(iters, pmax, color='green')
if doPlot('doShowSignalChange'):
md = xmipp.MetaData()
for iter in iters:
fn = protML._getIterClasses(it=iter, block='classes')
md2 = xmipp.MetaData(fn)
md2.fillConstant(xmipp.MDL_ITER, str(iter))
md.unionAll(md2)
# 'iter(.*[1-9].*)@2D/ML2D/run_004/ml2d_iter_refs.xmd')
#a = plt.subplot(gs[1, 1])
#print "md:", md
md2 = xmipp.MetaData()
md2.aggregate(md, xmipp.AGGR_MAX, xmipp.MDL_ITER, xmipp.MDL_SIGNALCHANGE, xmipp.MDL_MAX)
signal_change = [md2.getValue(xmipp.MDL_MAX, id) for id in md2]
xplotter.createSubPlot('Maximum signal change', 'iterations', 'signal change')
xplotter.plot(iters, signal_change, color='green')
return [xplotter]
def __init__(self, **kwargs):
""" Create the plotter, 'data' should be passed in **kwargs.
"""
self._data = kwargs.get('data')
XmippPlotter.__init__(self, **kwargs)
self.useLastPlot = False
def _plotHistogramAngularMovement(self, paramName=None):
from numpy import arange
from matplotlib.ticker import FormatStrFormatter
plots = []
colors = ['g', 'b', 'r', 'y', 'c', 'm', 'k']
lenColors=len(colors)
numberOfBins = self.numberOfBins.get()
md = xmipp.MetaData()
for it in self._iterations:
mdFn = self.protocol._mdDevitationsFn(it)
if xmipp.existsBlockInMetaDataFile(mdFn):
md.read(mdFn)
if not self.usePsi:
md.fillConstant(xmipp.MDL_ANGLE_PSI,0.)
nrefs = len(self._refsList)
gridsize = self._getGridSize(nrefs)
xplotterShift = XmippPlotter(*gridsize, mainTitle='Iteration_%d\n' % it, windowTitle="ShiftDistribution")
xplotter = XmippPlotter(*gridsize, mainTitle='Iteration_%d' % it, windowTitle="AngularDistribution")
for ref3d in self._refsList:
mDoutRef3D = xmipp.MetaData()
mDoutRef3D.importObjects(md, xmipp.MDValueEQ(xmipp.MDL_REF3D, ref3d))
_frequency = "Frequency (%d)" % mDoutRef3D.size()
xplotterShift.createSubPlot("%s_ref3D_%d"%(xmipp.label2Str(xmipp.MDL_SHIFT_DIFF),ref3d), "pixels", _frequency)
xplotter.createSubPlot("%s_ref3D_%d"%(xmipp.label2Str(xmipp.MDL_ANGLE_DIFF),ref3d), "degrees", _frequency)
#mDoutRef3D.write("*****@*****.**",MD_APPEND)
xplotter.plotMd(mDoutRef3D,
xmipp.MDL_ANGLE_DIFF,
xmipp.MDL_ANGLE_DIFF,
color=colors[ref3d%lenColors],
#nbins=50
nbins=int(numberOfBins)
)#if nbins is present do an histogram
xplotterShift.plotMd(mDoutRef3D,
xmipp.MDL_SHIFT_DIFF,
xmipp.MDL_SHIFT_DIFF,
color=colors[ref3d%lenColors],
nbins=int(numberOfBins)
)#if nbins is present do an histogram
if self.angleSort:
mDoutRef3D.sort(xmipp.MDL_ANGLE_DIFF)
fn = xmipp.FileName()
baseFileName = self.protocol._getTmpPath("angle_sort.xmd")
fn = self.protocol._getRefBlockFileName("angle_iter", it, "ref3D", ref3d, baseFileName)
mDoutRef3D.write(fn, xmipp.MD_APPEND)
print "File with sorted angles saved in:", fn
if self.shiftSort:
mDoutRef3D.sort(xmipp.MDL_SHIFT_DIFF)
fn = xmipp.FileName()
baseFileName = self.protocol._getTmpPath("angle_sort.xmd")
fn = self.protocol._getRefBlockFileName("shift_iter", it, "ref3D", ref3d, baseFileName)
mDoutRef3D.write(fn, xmipp.MD_APPEND)
print "File with sorted shifts saved in:", fn
plots.append(xplotterShift)
plots.append(xplotter)
else:
print "File %s does not exist" % mdFn
return plots
def _plotHistogramAngularMovement(self, paramName=None):
from numpy import arange
from matplotlib.ticker import FormatStrFormatter
plots = []
colors = ['g', 'b', 'r', 'y', 'c', 'm', 'k']
lenColors = len(colors)
numberOfBins = self.numberOfBins.get()
md = xmipp.MetaData()
for it in self._iterations:
mdFn = self.protocol._mdDevitationsFn(it)
if xmipp.existsBlockInMetaDataFile(mdFn):
md.read(mdFn)
if not self.usePsi:
md.fillConstant(xmipp.MDL_ANGLE_PSI, 0.)
nrefs = len(self._refsList)
gridsize = self._getGridSize(nrefs)
xplotterShift = XmippPlotter(*gridsize,
mainTitle='Iteration_%d\n' % it,
windowTitle="ShiftDistribution")
xplotter = XmippPlotter(*gridsize,
mainTitle='Iteration_%d' % it,
windowTitle="AngularDistribution")
for ref3d in self._refsList:
mDoutRef3D = xmipp.MetaData()
mDoutRef3D.importObjects(
md, xmipp.MDValueEQ(xmipp.MDL_REF3D, ref3d))
_frequency = "Frequency (%d)" % mDoutRef3D.size()
xplotterShift.createSubPlot(
"%s_ref3D_%d" %
(xmipp.label2Str(xmipp.MDL_SHIFT_DIFF), ref3d),
"pixels", _frequency)
xplotter.createSubPlot(
"%s_ref3D_%d" %
(xmipp.label2Str(xmipp.MDL_ANGLE_DIFF), ref3d),
"degrees", _frequency)
#mDoutRef3D.write("*****@*****.**",MD_APPEND)
xplotter.plotMd(
mDoutRef3D,
xmipp.MDL_ANGLE_DIFF,
xmipp.MDL_ANGLE_DIFF,
color=colors[ref3d % lenColors],
#nbins=50
nbins=int(numberOfBins)
) #if nbins is present do an histogram
xplotterShift.plotMd(
mDoutRef3D,
xmipp.MDL_SHIFT_DIFF,
xmipp.MDL_SHIFT_DIFF,
color=colors[ref3d % lenColors],
nbins=int(numberOfBins
)) #if nbins is present do an histogram
if self.angleSort:
mDoutRef3D.sort(xmipp.MDL_ANGLE_DIFF)
fn = xmipp.FileName()
baseFileName = self.protocol._getTmpPath(
"angle_sort.xmd")
fn = self.protocol._getRefBlockFileName(
"angle_iter", it, "ref3D", ref3d, baseFileName)
mDoutRef3D.write(fn, xmipp.MD_APPEND)
print "File with sorted angles saved in:", fn
if self.shiftSort:
mDoutRef3D.sort(xmipp.MDL_SHIFT_DIFF)
fn = xmipp.FileName()
baseFileName = self.protocol._getTmpPath(
"angle_sort.xmd")
fn = self.protocol._getRefBlockFileName(
"shift_iter", it, "ref3D", ref3d, baseFileName)
mDoutRef3D.write(fn, xmipp.MD_APPEND)
print "File with sorted shifts saved in:", fn
plots.append(xplotterShift)
plots.append(xplotter)
else:
print "File %s does not exist" % mdFn
return plots
