def getTestPlot(request):
""" Just a test of a custom render function. """
from pyworkflow.gui.plotter import Plotter
xplotter = Plotter()
xplotter.createSubPlot("Particle sorting", "Particle number", "Zscore")
x = range(100)
xplotter.plot(x)
canvas = xplotter.getCanvas()
response = HttpResponse(content_type='image/png')
canvas.print_png(response)
return response
def getTestPlot(request):
""" Just a test of a custom render function. """
from pyworkflow.gui.plotter import Plotter
xplotter = Plotter()
xplotter.createSubPlot("Particle sorting", "Particle number", "Zscore")
x = range(100)
xplotter.plot(x)
canvas = xplotter.getCanvas()
response = HttpResponse(content_type='image/png')
canvas.print_png(response)
return response
def plotFile(dbName, dbPreffix, plotType,
columnsStr, colorsStr, linesStr, markersStr,
xcolumn, ylabel, xlabel, title, bins, orderColumn, orderDirection):
columns = columnsStr.split()
colors = colorsStr.split()
lines = linesStr.split()
markers = markersStr.split()
data = PlotData(dbName, dbPreffix, orderColumn, orderDirection)
#setObj = getSetObject(dbName, dbPreffix)
plotter = Plotter(windowTitle=title)
ax = plotter.createSubPlot(title, xlabel, ylabel)
xvalues = data.getColumnValues(xcolumn) if xcolumn else range(0, data.getSize())
#xvalues = range(0, setObj.getSize()) if not isxvalues else []
for i, col in enumerate(columns):
yvalues = data.getColumnValues(col)
color = colors[i]
line = lines[i]
if bins:
ax.hist(yvalues, bins=int(bins), color=color, linestyle=line, label=col)
else:
if plotType == 'Plot':
marker = (markers[i] if not markers[i] == 'none' else None)
ax.plot(xvalues, yvalues, color, marker=marker, linestyle=line, label=col)
else:
ax.scatter(xvalues, yvalues, c=color, label=col, alpha=0.5)
ax.legend(columns)
return plotter
def plotFile(dbName, dbPreffix, plotType, columnsStr, colorsStr, linesStr,
markersStr, xcolumn, ylabel, xlabel, title, bins, orderColumn,
orderDirection):
columns = columnsStr.split()
colors = colorsStr.split()
lines = linesStr.split()
markers = markersStr.split()
data = PlotData(dbName, dbPreffix, orderColumn, orderDirection)
#setObj = getSetObject(dbName, dbPreffix)
plotter = Plotter(windowTitle=title)
ax = plotter.createSubPlot(title, xlabel, ylabel)
xvalues = data.getColumnValues(xcolumn) if xcolumn else range(0, data.getSize())
#xvalues = range(0, setObj.getSize()) if not isxvalues else []
for i, col in enumerate(columns):
yvalues = data.getColumnValues(col)
color = colors[i]
line = lines[i]
if bins:
ax.hist(yvalues, bins=int(bins), color=color, linestyle=line, label=col)
else:
if plotType == 'Plot':
marker = (markers[i] if not markers[i] == 'none' else None)
ax.plot(xvalues, yvalues, color, marker=marker, linestyle=line, label=col)
else:
ax.scatter(xvalues, yvalues, c=color, label=col, alpha=0.5)
ax.legend(columns)
return plotter
def createFromFile(cls, dbName, dbPreffix, plotType, columnsStr, colorsStr, linesStr,
markersStr, xcolumn, ylabel, xlabel, title, bins, orderColumn,
orderDirection):
columns = columnsStr.split()
colors = colorsStr.split()
lines = linesStr.split()
markers = markersStr.split()
data = PlotData(dbName, dbPreffix, orderColumn, orderDirection)
plotter = Plotter(windowTitle=title)
ax = plotter.createSubPlot(title, xlabel, ylabel)
xvalues = data.getColumnValues(xcolumn) if xcolumn else range(0, data.getSize())
for i, col in enumerate(columns):
yvalues = data.getColumnValues(col)
color = colors[i]
line = lines[i]
colLabel = col if not col.startswith("_") else col[1:]
if bins:
yvalues = data._removeInfinites(yvalues)
ax.hist(yvalues, bins=int(bins), color=color, linestyle=line, label=colLabel)
else:
if plotType == 'Plot':
marker = (markers[i] if not markers[i] == 'none' else None)
ax.plot(xvalues, yvalues, color, marker=marker, linestyle=line, label=colLabel)
else:
ax.scatter(xvalues, yvalues, c=color, label=col, alpha=0.5)
ax.legend()
return plotter
def _plotGrid(self, grid, x, y):
plotter = Plotter(windowTitle="Acquisitions for grid %s" % grid)
plt = plotter.createSubPlot("Locations", "X", "Y")
plt.axis('scaled')
plt.autoscale(tight=True)
self.loadAtlasImg(plt, grid)
colors = ["cyan"] * len(x)
area = np.pi * 3
plotter.scatterP(x, y, s=area, c=colors, edgecolors='none', alpha=1)
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 _createSpectraPlot(self, label, array, index, objId=None):
if objId is None:
objId = index
# Number of harmonics calculated
plotter = Plotter()
a = plotter.createSubPlot('Spectrum for %s %d' % (label, objId),
xlabel='Harmonics', ylabel='Energy')
n = self.spectraHighHarmonic.get() - self.spectraLowHarmonic.get() + 1
i1 = (index-1) * n
i2 = i1 + n
xdata = range(self.spectraLowHarmonic.get(), self.spectraHighHarmonic.get()+1)
ydata = array[i1:i2]
a.plot(xdata, ydata)
plotFile = join(self.plotsDir, 'spectra_%s%06d.png' % (label, objId))
plotter.savefig(plotFile)
return plotFile
def _createSpectraPlot(self, label, array, index, objId=None):
if objId is None:
objId = index
# Number of harmonics calculated
plotter = Plotter()
a = plotter.createSubPlot('Spectrum for %s %d' % (label, objId),
xlabel='Harmonics', ylabel='Energy')
n = self.spectraHighHarmonic.get() - self.spectraLowHarmonic.get() + 1
i1 = (index-1) * n
i2 = i1 + n
xdata = range(self.spectraLowHarmonic.get(), self.spectraHighHarmonic.get()+1)
ydata = array[i1:i2]
a.plot(xdata, ydata)
plotFile = join(self.plotsDir, 'spectra_%s%06d.png' % (label, objId))
plotter.savefig(plotFile)
return plotFile
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()
