Source code for xmipp3.viewers.viewer_eliminate_empty_images

# **************************************************************************
# *
# * Authors:     Roberto Marabini (
# *
# * Unidad de  Bioinformatica of Centro Nacional de Biotecnologia , CSIC
# *
# * This program is free software; you can redistribute it and/or modify
# * it under the terms of the GNU General Public License as published by
# * the Free Software Foundation; either version 2 of the License, or
# * (at your option) any later version.
# *
# * This program is distributed in the hope that it will be useful,
# * but WITHOUT ANY WARRANTY; without even the implied warranty of
# * GNU General Public License for more details.
# *
# * You should have received a copy of the GNU General Public License
# * along with this program; if not, write to the Free Software
# * Foundation, Inc., 59 Temple Place, Suite 330, Boston, MA
# * 02111-1307  USA
# *
# *  All comments concerning this program package may be sent to the
# *  e-mail address ''
# *
# **************************************************************************

from pyworkflow.protocol.params import IntParam, LabelParam
from pyworkflow.viewer import DESKTOP_TKINTER, WEB_DJANGO, ProtocolViewer
from pwem.viewers import EmPlotter, ObjectView, ClassesView
from pwem.viewers.showj import MODE, MODE_MD, ORDER, VISIBLE, RENDER, SORT_BY

from xmipp3.protocols.protocol_eliminate_empty_images import \
    XmippProtEliminateEmptyClasses, XmippProtEliminateEmptyParticles

[docs]class XmippEliminateEmptyViewer(ProtocolViewer): """ This protocol computes the maximum resolution up to which two CTF estimations would be ``equivalent'', defining ``equivalent'' as having a wave aberration function shift smaller than 90 degrees """ _label = 'viewer Eliminate empty images' _environments = [DESKTOP_TKINTER, WEB_DJANGO] _targets = [XmippProtEliminateEmptyParticles, XmippProtEliminateEmptyClasses] def _defineParams(self, form): isClassType = isinstance(self.protocol, XmippProtEliminateEmptyClasses) self.imagesType = ('Averages' if isClassType else 'Particles') form.addSection(label='Visualization') form.addParam('visualizeIms', LabelParam, label="Visualize passed %s" % self.imagesType) form.addParam('visualizeImsDiscarded', LabelParam, label="Visualize discarded %s" % self.imagesType) if not isClassType: form.addParam('justSpace', LabelParam, label="") form.addParam('visualizeHistogram', IntParam, default=100, label="Visualize Histogram (Bin size)", help="Histogram of the emptiness score.") def _getVisualizeDict(self): return { 'visualizeIms': self._visualizeIms, 'visualizeImsDiscarded': self._visualizeImsDiscarded, 'visualizeHistogram': self._visualizeHistogram } def _visualizeImages(self, outputName): views = [] prot = self.protocol if hasattr(prot, outputName): ouputFn = getattr(prot, outputName).getFileName() ouputId = getattr(prot, outputName).strId() labels = ('id enabled _index _filename _xmipp_scoreEmptiness ' '_xmipp_scoreByVariance _xmipp_zScore ' '_xmipp_cumulativeSSNR _sampling ' '_ctfModel._defocusU _ctfModel._defocusV ' '_ctfModel._defocusAngle _transform._matrix') if 'Classes' in outputName: views.append(ClassesView(self._project, ouputId, ouputFn)) else: views.append(ObjectView(self._project, ouputId, ouputFn, viewParams={ORDER: labels, VISIBLE: labels, SORT_BY: '_xmipp_scoreEmptiness desc', MODE: MODE_MD, RENDER: '_filename'})) else: appendStr = ', yet.' if prot.isActive() else '.' self.infoMessage('%s does not have %s%s' % (prot.getObjLabel(), outputName, appendStr), title='Info message').show() return views def _visualizeIms(self, e=None): return self._visualizeImages(outputName="output%s" % self.imagesType) def _visualizeImsDiscarded(self, e=None): return self._visualizeImages(outputName="eliminated%s" % self.imagesType) def _visualizeHistogram(self, e=None): views = [] numberOfBins = self.visualizeHistogram.get() goodScores = [] badScores = [] if hasattr(self.protocol, "outputParticles"): goodScores += [part._xmipp_scoreEmptiness.get() for part in self.protocol.outputParticles] if hasattr(self.protocol, "eliminatedParticles"): badScores += [part._xmipp_scoreEmptiness.get() for part in self.protocol.eliminatedParticles] plotter = EmPlotter() plotter.createSubPlot("Emptiness Score", "Emptiness Score (a.u.)", "# of Particles") values = [goodScores, badScores] labels = ["Passed particles", "Discarded particles"] colors = ['green', 'red'] plotMultiHistogram(values, colors, labels, numberOfBins, plotter, views) return views
[docs]def plotMultiHistogram(valuesList, colors=None, legend=None, numOfBins=100, plotter=None, views=None, includeEmpties=False): """ Values list must be a n-list of list, where n is the number of the subhistograms to plot. Multiple histograms will be plot in the same chart If no views is passed, a new list-views will be returned with the hist. If no plotter is passed, a new generic one will be created. """ if not all([isinstance(x, list) for x in valuesList]): print("Not all items in values list are lists. Returning...") return if colors is None: from matplotlib import colors from random import shuffle colors = colors.cnames.keys() shuffle(colors) if any([len(x) for x in valuesList]): if plotter is None: plotter = EmPlotter() plotter.createSubPlot("Histogram", "Score", "# of Items") w1 = None finalLegend = [] for idx, values in enumerate(valuesList): if values or includeEmpties: if w1 is None: w1 = (max(values) - min(values)) / numOfBins else: numOfBins = int((max(values) - min(values)) / w1) plotter.plotHist(values, nbins=numOfBins, color=colors[idx]) if legend: finalLegend.append(legend[idx]) if finalLegend: plotter.legend(labels=finalLegend) if views is None: views = [plotter] else: views.append(plotter) return views