def createPlot2D(self, volPrefix, md):
import xmipp
figurePath = self._getExtraPath(volPrefix +
'softAlignmentValidation2D.png')
figureSize = (8, 6)
#alignedMovie = mic.alignMetaData
plotter = Plotter(*figureSize)
figure = plotter.getFigure()
ax = figure.add_subplot(111)
ax.grid()
ax.set_title('Soft alignment validation map')
ax.set_xlabel('Angular Precision')
ax.set_ylabel('Angular Accuracy')
for objId in md:
x = md.getValue(xmipp.MDL_SCORE_BY_ALIGNABILITY_PRECISION, objId)
y = md.getValue(xmipp.MDL_SCORE_BY_ALIGNABILITY_ACCURACY, objId)
ax.plot(x, y, 'r.', markersize=1)
ax.grid(True, which='both')
ax.autoscale_view(True, True, True)
plotter.savefig(figurePath)
plotter.show()
return plotter
def createPlot2D(self,volPrefix,md):
import xmipp
figurePath = self._getExtraPath(volPrefix + 'softAlignmentValidation2D.png')
figureSize = (8, 6)
#alignedMovie = mic.alignMetaData
plotter = Plotter(*figureSize)
figure = plotter.getFigure()
ax = figure.add_subplot(111)
ax.grid()
ax.set_title('Soft alignment validation map')
ax.set_xlabel('Angular Precision')
ax.set_ylabel('Angular Accuracy')
for objId in md:
x = md.getValue(xmipp.MDL_SCORE_BY_ALIGNABILITY_PRECISION, objId)
y = md.getValue(xmipp.MDL_SCORE_BY_ALIGNABILITY_ACCURACY, objId)
ax.plot(x, y, 'r.',markersize=1)
ax.grid(True, which='both')
ax.autoscale_view(True,True,True)
plotter.savefig(figurePath)
plotter.show()
return plotter
def _visualizeLLPlot(self, e=None):
""" Plot -LL vs cycle :N:1,5:
"""
headerList, dataList, msg, title = self.parseFile.retrievemLLPlot()
if not dataList:
errorWindow(self.getTkRoot(), msg)
return
xplotter = Plotter(windowTitle=title)
a = xplotter.createSubPlot(title, headerList[0], '-LL', yformat=False)
# see
# https://matplotlib.org/api/_as_gen/matplotlib.axes.Axes.plot.html
a.plot(dataList[0], dataList[1], 'bx-')
xplotter.showLegend(headerList[1:])
xplotter.show()
def visualize(self, obj, **args):
cls = type(obj)
if issubclass(cls, AtsasProtConvertPdbToSAXS):
if obj.experimentalSAXS.empty():
fnInt=obj._getPath("pseudoatoms00.int")
else:
fnInt=obj._getPath("pseudoatoms00.fit")
import numpy
x=numpy.loadtxt(fnInt,skiprows=1)
xplotter = Plotter(windowTitle="SAXS Curves")
a = xplotter.createSubPlot('SAXS curves', 'Angstrongs^-1', 'log(SAXS)', yformat=False)
a.plot(x[:,0], numpy.log(x[:,1]))
a.plot(x[:,0], numpy.log(x[:,2]))
if obj.experimentalSAXS.empty():
xplotter.showLegend(['SAXS in solution','SAXS in vacuo'])
else:
xplotter.showLegend(['Experimental SAXS','SAXS from volume'])
xplotter.show()
def _visualizeRFactorPlot(self, e=None):
""" Plot Rfactor and Rfree vs cycle :N:[1,3]:
"""
headerList, dataList, msg, title = self.parseFile.retrieveRFactorPlot()
if not dataList:
errorWindow(self.getTkRoot(), msg)
return
xplotter = Plotter(windowTitle=title)
a = xplotter.createSubPlot(title,
headerList[0],
'Rfactor',
yformat=False)
# see
# https://matplotlib.org/api/_as_gen/matplotlib.axes.Axes.plot.html
# for plot options
a.plot(dataList[0], dataList[1], 'bx-', dataList[0], dataList[2],
'gx-') # plot start over line in blue
xplotter.showLegend(headerList[1:])
xplotter.show()
def _visualizeGeometryPlot(self, e=None):
""" Plot rmsBOND,zBOND, rmsANGL, zANGL and rmsCHIRALvs cycle :
N:1,7,8,9,10,11:
"""
headerList, dataList, msg, title = \
self.parseFile.retrieveGeometryPlot()
if not dataList:
errorWindow(self.getTkRoot(), msg)
return
xplotter = Plotter(windowTitle=title)
a = xplotter.createSubPlot(title,
headerList[0],
'geometry',
yformat=False)
# see
# https://matplotlib.org/api/_as_gen/matplotlib.axes.Axes.plot.html
# for plot options
a.plot(
dataList[0],
dataList[1],
'bx-',
dataList[0],
dataList[2],
'gx-',
dataList[0],
dataList[3],
'rx-',
dataList[0],
dataList[4],
'cx-',
dataList[0],
dataList[5],
'mx-',
) # plot start over line in blue
xplotter.showLegend(headerList[1:])
xplotter.show()
