def _showBFactorPlot(self, key):
if key == 'guinier':
label = 'rlnFittedInterceptGuinierPlot'
title = "Polishing scale-factors"
else: # bfactor
label = 'rlnBfactorUsedForSharpening'
title = "Polishing B-factors"
modelStar = self.protocol._getFileName('bfactors')
if os.path.exists(modelStar):
table = Table(fileName=modelStar, tableName='perframe_bfactors')
frame = table.getColumnValues('rlnMovieFrameNumber')
bfactor = map(float, table.getColumnValues(label))
plotter = Plotter()
figure = plotter.getFigure()
a = figure.add_subplot(111)
a.grid(True)
a.set_xlabel('Movie frame number')
a.set_ylabel(label)
a.invert_yaxis()
a.plot(frame, list(bfactor))
a.set_title(title)
plotter.tightLayout()
return [plotter]
def createGlobalAlignmentPlot(meanX, meanY, first):
""" Create a plotter with the shift per frame. """
figureSize = (6, 4)
plotter = Plotter(*figureSize)
figure = plotter.getFigure()
ax = figure.add_subplot(111)
ax.grid()
ax.set_title('Global shift')
ax.set_xlabel('Shift x (pixels)')
ax.set_ylabel('Shift y (pixels)')
i = first
skipLabels = ceil(len(meanX) / 10.0)
labelTick = 1
for x, y in izip(meanX, meanY):
if labelTick == 1:
ax.text(x - 0.02, y + 0.02, str(i))
labelTick = skipLabels
else:
labelTick -= 1
i += 1
ax.plot(meanX, meanY, color='b')
ax.plot(meanX, meanY, 'yo')
plotter.tightLayout()
return plotter
def createAlignmentPlot(meanX, meanY):
""" Create a plotter with the cumulative shift per frame. """
figureSize = (8, 6)
plotter = Plotter(*figureSize)
figure = plotter.getFigure()
ax = figure.add_subplot(111)
ax.grid()
ax.axis('equal')
ax.set_title('Cartesian representation')
ax.set_xlabel('Drift x (pixels)')
ax.set_ylabel('Drift y (pixels)')
# Max range of the plot of the two coordinates
plotRange = max(max(meanX) - min(meanX), max(meanY) - min(meanY))
i = 1
skipLabels = ceil(len(meanX) / 10.0)
for x, y in izip(meanX, meanY):
if i % skipLabels == 0:
ax.text(x - 0.02 * plotRange, y + 0.02 * plotRange, str(i))
i += 1
ax.plot(meanX, meanY, color='b')
ax.plot(meanX, meanY, 'yo')
# setting the plot windows to properly see the data
ax.axis([min(meanX) - 0.1 * plotRange, max(meanX) + 0.1 * plotRange,
min(meanY) - 0.1 * plotRange, max(meanY) + 0.1 * plotRange])
plotter.tightLayout()
return plotter
def createAlignmentPlot(meanX, meanY):
""" Create a plotter with the cumulative shift per frame. """
sumMeanX = []
sumMeanY = []
figureSize = (8, 6)
plotter = Plotter(*figureSize)
figure = plotter.getFigure()
preX = 0.0
preY = 0.0
sumMeanX.append(0.0)
sumMeanY.append(0.0)
ax = figure.add_subplot(111)
ax.grid()
ax.set_title('Cartesian representation')
ax.set_xlabel('Drift x (pixels)')
ax.set_ylabel('Drift y (pixels)')
ax.plot(0, 0, 'yo-')
i = 1
for x, y in izip(meanX, meanY):
preX += x
preY += y
sumMeanX.append(preX)
sumMeanY.append(preY)
#ax.plot(preX, preY, 'yo-')
ax.text(preX-0.02, preY+0.02, str(i))
i += 1
ax.plot(sumMeanX, sumMeanY, color='b')
ax.plot(sumMeanX, sumMeanY, 'yo')
plotter.tightLayout()
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 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 movieCreatePlot(mic, saveFig):
import xmipp
meanX = []
meanY = []
figureSize = (8, 6)
#alignedMovie = mic.alignMetaData
md = xmipp.MetaData(mic.alignMetaData)
plotter = Plotter(*figureSize)
figure = plotter.getFigure()
preX = 0.0
preY = 0.0
meanX.append(0.0)
meanY.append(0.0)
ax = figure.add_subplot(111)
ax.grid()
ax.set_title('Cartesian representation')
ax.set_xlabel('Drift x (pixels)')
ax.set_ylabel('Drift y (pixels)')
ax.plot(0, 0, 'yo-')
for objId in md:
preX += md.getValue(xmipp.MDL_OPTICALFLOW_MEANX, objId)
preY += md.getValue(xmipp.MDL_OPTICALFLOW_MEANY, objId)
meanX.append(preX)
meanY.append(preY)
ax.plot(preX, preY, 'yo-')
ax.text(preX - 0.02, preY + 0.01, str(objId + 1))
ax.plot(np.asarray(meanX), np.asarray(meanY))
if saveFig:
plotter.savefig(mic.plotCart)
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 createGlobalAlignmentPlot(meanX, meanY, first):
""" Create a plotter with the cumulative shift per frame. """
sumMeanX = []
sumMeanY = []
preX = 0.0
preY = 0.0
figureSize = (6, 4)
plotter = Plotter(*figureSize)
figure = plotter.getFigure()
ax = figure.add_subplot(111)
ax.grid()
ax.set_title('Global frame shift (cumulative)')
ax.set_xlabel('Shift x (pixels)')
ax.set_ylabel('Shift y (pixels)')
if meanX[0] != 0 or meanY[0] != 0:
raise Exception("First frame shift must be (0,0)!")
i = first
for x, y in izip(meanX, meanY):
preX += x
preY += y
sumMeanX.append(preX)
sumMeanY.append(preY)
ax.text(preX - 0.02, preY + 0.02, str(i))
i += 1
ax.plot(sumMeanX, sumMeanY, color='b')
ax.plot(sumMeanX, sumMeanY, 'yo')
plotter.tightLayout()
return plotter
def _plotHistogram(self, param=None):
md = MetaData()
md.read(self.protocol._getFileName(FN_METADATA_HISTOGRAM))
x_axis = []
y_axis = []
i = 0
for idx in md:
x_axis_ = md.getValue(MDL_X, idx)
if i == 0:
x0 = x_axis_
elif i == 1:
x1 = x_axis_
y_axis_ = md.getValue(MDL_COUNT, idx)
i += 1
x_axis.append(x_axis_)
y_axis.append(y_axis_)
delta = x1 - x0
fig = plt.figure()
plt.bar(x_axis, y_axis, width=delta)
plt.title("Resolutions Histogram")
plt.xlabel("Resolution (A)")
plt.ylabel("Counts")
return [Plotter(figure2=fig)]
def _plotResMapSlices(self, data=None, **kwargs):
from ResMap_visualization import plotResMapVolume
plotDict = loads(self.plotData.get())
if data is None:
data = self._getVolumeMatrix('volume1_resmap.map')
data = np.ma.masked_where(data > plotDict['currentRes'], data, copy=True)
kwargs.update(plotDict)
fig = plotResMapVolume(data, **kwargs)
return Plotter(figure=fig)
def createGlobalAlignmentPlot(meanX, meanY, first, pixSize):
""" Create a plotter with the shift per frame. """
sumMeanX = []
sumMeanY = []
def px_to_ang(px):
y1, y2 = px.get_ylim()
x1, x2 = px.get_xlim()
ax_ang2.set_ylim(y1 * pixSize, y2 * pixSize)
ax_ang.set_xlim(x1 * pixSize, x2 * pixSize)
ax_ang.figure.canvas.draw()
ax_ang2.figure.canvas.draw()
figureSize = (6, 4)
plotter = Plotter(*figureSize)
figure = plotter.getFigure()
ax_px = figure.add_subplot(111)
ax_px.grid()
ax_px.set_xlabel('Shift x (px)')
ax_px.set_ylabel('Shift y (px)')
ax_ang = ax_px.twiny()
ax_ang.set_xlabel('Shift x (A)')
ax_ang2 = ax_px.twinx()
ax_ang2.set_ylabel('Shift y (A)')
i = first
# The output and log files list the shifts relative to the first frame.
# ROB unit seems to be pixels since sampling rate is only asked
# by the program if dose filtering is required
skipLabels = ceil(len(meanX) / 10.0)
labelTick = 1
for x, y in zip(meanX, meanY):
sumMeanX.append(x)
sumMeanY.append(y)
if labelTick == 1:
ax_px.text(x - 0.02, y + 0.02, str(i))
labelTick = skipLabels
else:
labelTick -= 1
i += 1
# automatically update lim of ax_ang when lim of ax_px changes.
ax_px.callbacks.connect("ylim_changed", px_to_ang)
ax_px.callbacks.connect("xlim_changed", px_to_ang)
ax_px.plot(sumMeanX, sumMeanY, color='b')
ax_px.plot(sumMeanX, sumMeanY, 'yo')
ax_px.plot(sumMeanX[0], sumMeanY[0], 'ro', markersize=10, linewidth=0.5)
ax_px.set_title('Global frame alignment')
plotter.tightLayout()
return plotter
def createGlobalAlignmentPlot(meanX, meanY, first, pixSize):
""" Create a plotter with the shift per frame. """
sumMeanX = []
sumMeanY = []
def px_to_ang(ax_px):
y1, y2 = ax_px.get_ylim()
x1, x2 = ax_px.get_xlim()
ax_ang2.set_ylim(y1 * pixSize, y2 * pixSize)
ax_ang.set_xlim(x1 * pixSize, x2 * pixSize)
ax_ang.figure.canvas.draw()
ax_ang2.figure.canvas.draw()
figureSize = (6, 4)
plotter = Plotter(*figureSize)
figure = plotter.getFigure()
ax_px = figure.add_subplot(111)
ax_px.grid()
ax_px.set_xlabel('Shift x (px)')
ax_px.set_ylabel('Shift y (px)')
ax_ang = ax_px.twiny()
ax_ang.set_xlabel('Shift x (A)')
ax_ang2 = ax_px.twinx()
ax_ang2.set_ylabel('Shift y (A)')
i = first
# The output _rlnMicrographShiftX/Y shifts relative to the first frame.
# Unit is pixels of the original (unbinned) movies (Takanori, 2018)
skipLabels = ceil(len(meanX) / 10.0)
labelTick = 1
for x, y in zip(meanX, meanY):
sumMeanX.append(x)
sumMeanY.append(y)
if labelTick == 1:
ax_px.text(x - 0.02, y + 0.02, str(i))
labelTick = skipLabels
else:
labelTick -= 1
i += 1
# automatically update lim of ax_ang when lim of ax_px changes.
ax_px.callbacks.connect("ylim_changed", px_to_ang)
ax_px.callbacks.connect("xlim_changed", px_to_ang)
ax_px.plot(sumMeanX, sumMeanY, color='b')
ax_px.plot(sumMeanX, sumMeanY, 'yo')
ax_px.plot(sumMeanX[0], sumMeanY[0], 'ro', markersize=10, linewidth=0.5)
ax_px.set_title('Global frame alignment')
plotter.tightLayout()
return plotter
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 _runPreWhiteningWeb(protocol, results):
newAng = protocol.prewhitenAng.get()
newRamp = protocol.prewhitenRamp.get()
figsize = (18, 9)
gridsize = [0, 0]
plotter = Plotter(*gridsize, figsize=figsize, windowTitle="ResMap")
myCreatePrewhiteningFigure(results, plotter.getFigure(), newAng, newRamp)
return plotter
def createGlobalAlignmentPlot(meanX, meanY, first):
""" Create a plotter with the shift per frame. """
sumMeanX = []
sumMeanY = []
preX = 0.0
preY = 0.0
figureSize = (6, 4)
plotter = Plotter(*figureSize)
figure = plotter.getFigure()
ax = figure.add_subplot(111)
ax.grid()
ax.set_title('Alignment based upon full frames')
ax.set_xlabel('Shift x (pixels)')
ax.set_ylabel('Shift y (pixels)')
# morioncor2 (1.0.2) values refer to the middle frame, so first frame is no longer 0,0
#if meanX[0] != 0 or meanY[0] != 0:
# raise Exception("First frame shift must be (0,0)!")
i = first
# ROB no accumulation is needed
# see Motioncor2 user manual: "The output and log files list the shifts relative to the first frame."
# or middle frame for motioncor2 1.0.2
# ROB unit seems to be pixels since samplingrate is only asked by the program if
# dose filtering is required
skipLabels = ceil(len(meanX) / 10.0)
labelTick = 1
for x, y in izip(meanX, meanY):
#preX += x
#preY += y
preX = x
preY = y
sumMeanX.append(preX)
sumMeanY.append(preY)
if labelTick == 1:
ax.text(preX - 0.02, preY + 0.02, str(i))
labelTick = skipLabels
else:
labelTick -= 1
i += 1
ax.plot(sumMeanX, sumMeanY, color='b')
ax.plot(sumMeanX, sumMeanY, 'yo')
plotter.tightLayout()
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 _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 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 createGlobalAlignmentPlot(meanX, meanY, first):
""" Create a plotter with the shift per frame. """
sumMeanX = []
sumMeanY = []
preX = 0.0
preY = 0.0
figureSize = (6, 4)
plotter = Plotter(*figureSize)
figure = plotter.getFigure()
ax = figure.add_subplot(111)
ax.grid()
ax.set_title('Alignment based upon full frames')
ax.set_xlabel('Shift x (pixels)')
ax.set_ylabel('Shift y (pixels)')
i = first
skipLabels = ceil(len(meanX)/10.0)
labelTick = 1
for x, y in izip(meanX, meanY):
preX = x
preY = y
sumMeanX.append(preX)
sumMeanY.append(preY)
if labelTick == 1:
ax.text(preX - 0.02, preY + 0.02, str(i))
labelTick = skipLabels
else:
labelTick -= 1
i += 1
ax.plot(sumMeanX, sumMeanY, color='b')
ax.plot(sumMeanX, sumMeanY, 'yo')
plotter.tightLayout()
return plotter
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()
def _plotHistogram(self):
from ResMap_visualization import plotResolutionHistogram
histogramData = loads(self.histogramData.get())
fig = plotResolutionHistogram(histogramData)
return Plotter(figure=fig)
def _plotVolumeSlices(self, **kwargs):
from ResMap_visualization import plotOriginalVolume
fig = plotOriginalVolume(self._getVolumeMatrix('volume1.map'), **kwargs)
return Plotter(figure=fig)
