Python EmPlotter.show方法代码示例

# 需要导入模块: from pyworkflow.em.plotter import EmPlotter [as 别名]
# 或者: from pyworkflow.em.plotter.EmPlotter import show [as 别名]
def createCtfPlot(ctfSet, ctfId):
    from pyworkflow.utils.path import removeExt
    ctfModel = ctfSet[ctfId]
    psdFn = ctfModel.getPsdFile()
    fn = removeExt(psdFn) + "_avrot.txt"
    gridsize = [1, 1]
    xplotter = EmPlotter(x=gridsize[0], y=gridsize[1], windowTitle='CTF Fitting')
    plot_title = "CTF Fitting"
    a = xplotter.createSubPlot(plot_title, 'pixels^-1', 'CTF', yformat=False)
    legendName = []
    for i in range(1, 5):
        _plotCurve(a, i, fn)
        if i == 1:
            legendName.append('rotational avg. No Astg')
        elif i == 2:
            legendName.append('rotational avg.')
        elif i == 3:
            legendName.append('CTF Fit')
        elif i == 4:
            legendName.append('Cross Correlation')
        elif i == 5:
            legendName.append('2sigma cross correlation of noise')
            
    xplotter.showLegend(legendName)
    a.grid(True)
    xplotter.show()

# 需要导入模块: from pyworkflow.em.plotter import EmPlotter [as 别名]
# 或者: from pyworkflow.em.plotter.EmPlotter import show [as 别名]
    def visualize(self, obj, **kwargs):
        model = PKPDAllometricScale()
        model.load(obj.fnScale.get())

        x = np.log10(np.asarray(model.X))
        xlabel = "%s [%s]" % (model.predictor, model.predictorUnits)
        for varName, varUnits in model.scaled_vars:
            plotter = EmPlotter()
            y = np.log10(np.asarray(model.Y[varName]))
            ylabel = "%s [%s]" % (varName, varUnits)
            ax = plotter.createSubPlot(varName, xlabel, ylabel)
            ax.plot(x, y, '.', label='Species')
            ax.plot(x, np.log10(model.models[varName][0])+x*model.models[varName][1],'r', label='R2=%f'%model.qualifiers[varName][0])
            leg = ax.legend(loc='upper right')
            if leg:
                leg.draggable()
            plotter.show()

        for varName, varUnits in model.averaged_vars:
            plotter = EmPlotter()
            y = np.asarray(model.Y[varName])
            ylabel = "%s [%s]" % (varName, varUnits)
            ax = plotter.createSubPlot("Scatter Plot", xlabel, ylabel)
            ax.plot(x, y, '.', label='Species')
            ax.plot(x, model.models[varName][0]*np.ones(x.shape),'r',label='Std=%f'%model.qualifiers[varName][0])
            leg = ax.legend(loc='upper right')
            if leg:
                leg.draggable()
            plotter.show()

# 需要导入模块: from pyworkflow.em.plotter import EmPlotter [as 别名]
# 或者: from pyworkflow.em.plotter.EmPlotter import show [as 别名]
    def press(self,event):

        sys.stdout.flush()
        if event.key == 'S':
            self.stop = True
            self.ax.set_title('Plot is Stopped. Press C to continue plotting')
        elif event.key == 'C':
            self.ax.set_title(self._getTitle())
            self.stop = False
            self.animate()
        EmPlotter.show(self)

# 需要导入模块: from pyworkflow.em.plotter import EmPlotter [as 别名]
# 或者: from pyworkflow.em.plotter.EmPlotter import show [as 别名]
    def paint(self, labels):
        for label in labels:
            self.lines[label], = self.ax.plot([], [], '-', label=label)

        anim = animation.FuncAnimation(
                self.fig, self.animate,
                interval=self.monitor.samplingInterval * 1000)  # miliseconds

        self.fig.canvas.mpl_connect('scroll_event', self.onscroll)
        self.fig.canvas.mpl_connect('key_press_event', self.press)
        EmPlotter.show(self)

# 需要导入模块: from pyworkflow.em.plotter import EmPlotter [as 别名]
# 或者: from pyworkflow.em.plotter.EmPlotter import show [as 别名]
            def _plot(varLabelX, varLabelY, x, y, yp):
                plotter = EmPlotter()
                ax = plotter.createSubPlot("Plot", varLabelX, varLabelY)
                xValues = _values(x, useLog=self.useTimeLog())
                ax.plot(xValues, _values(y), 'x', label="Observations")
                idx = np.argsort(xValues)
                ypValues = _values(yp)
                ax.plot(np.asarray(xValues)[idx], np.asarray(ypValues)[idx], 'g', label="Fit")
                leg = ax.legend()
                if leg:
                    leg.draggable()

                plotter.show()

# 需要导入模块: from pyworkflow.em.plotter import EmPlotter [as 别名]
# 或者: from pyworkflow.em.plotter.EmPlotter import show [as 别名]
    def onscroll(self, event):

        if event.button == 'up':
            self.win += self.step
        else:
            self.win -= self.step
            if self.win < self.step:
               self.win = self.step

        if self.oldWin != self.win:
            self.ax.set_title(self._getTitle())
            self.oldWin= self.win
        self.animate()
        EmPlotter.show(self)

# 需要导入模块: from pyworkflow.em.plotter import EmPlotter [as 别名]
# 或者: from pyworkflow.em.plotter.EmPlotter import show [as 别名]
def createCtfPlot(ctfSet, ctfId):
    ctfModel = ctfSet[ctfId]
    psdFn = ctfModel.getPsdFile()
    fn = removeExt(psdFn) + "_avrot.txt"
    gridsize = [1, 1]
    xplotter = EmPlotter(x=gridsize[0], y=gridsize[1], windowTitle='CTF Fitting')
    plot_title = "CTF Fitting"
    a = xplotter.createSubPlot(plot_title, 'pixels^-1', 'CTF', yformat=False)
    
    legendName = ['rotational avg. No Astg',
                  'rotational avg.',
                  'CTF Fit',
                  'Cross Correlation',
                  '2sigma cross correlation of noise']
    for i in range(1, 6):
        _plotCurve(a, i, fn)
    xplotter.showLegend(legendName)
    a.grid(True)
    xplotter.show()

# 需要导入模块: from pyworkflow.em.plotter import EmPlotter [as 别名]
# 或者: from pyworkflow.em.plotter.EmPlotter import show [as 别名]
    def _onPlotSummaryClick(self, e=None):
        sampleKeys = self.samplesTree.selection()
        n = len(sampleKeys)

        if n == 1:
            self.showInfo("Please select several samples to plot.")
        else:
            if n > 1:
                samples = [self.experiment.samples[k] for k in sampleKeys]
            else:
                samples = self.experiment.samples.values()

            dataDict = {} # key will be time values
            for s in samples:
                xValues, yValues = self.getPlotValues(s)
                for x, y in izip(xValues, yValues):
                    if x in dataDict:
                        dataDict[x].append(y)
                    else:
                        dataDict[x] = [y]

            sortedTime = sorted(dataDict.keys())
            # We will store five values (min, 25%, 50%, 75%, max)
            # for each of the time entries computed
            percentileList = [0, 25, 50, 75, 100]
            Y = np.zeros((len(sortedTime), 5))
            for i, t in enumerate(sortedTime):
                Y[i,:] = np.percentile(dataDict[t], percentileList)

            plotter = EmPlotter()
            ax = plotter.createSubPlot("Summary Plot", self.getTimeLabel(),
                                       self.getMeasureLabel())
            ax.plot(sortedTime, Y[:, 0], 'r--', label="Minimum")
            ax.plot(sortedTime, Y[:, 1], 'b--', label="25%")
            ax.plot(sortedTime, Y[:, 2], 'g', label="50% (Median)")
            ax.plot(sortedTime, Y[:, 3], 'b--', label="75%")
            ax.plot(sortedTime, Y[:, 4], 'r--', label="Maximum")

            ax.legend()
            plotter.show()

# 需要导入模块: from pyworkflow.em.plotter import EmPlotter [as 别名]
# 或者: from pyworkflow.em.plotter.EmPlotter import show [as 别名]
    def paint(self, labels):
        for label in labels:
            if (label == 'standard_deviation'):
                self.lines[label], = \
                    self.ax2.plot([], [], '-o',
                                  label='Standard deviation',
                                  color='r')
            if (label == 'ratio1'):
                self.lines[label], = \
                    self.ax.plot([], [], '-o',
                                 label='97.5/2.5 percentile',
                                 color='b')
            if (label == 'ratio2'):
                self.lines[label], = \
                    self.ax.plot([], [], '-*',
                                 label='max/97.5 percentile',
                                 color='b')

        anim = animation.FuncAnimation(self.fig, self.animate,
                                       interval=self.monitor.samplingInterval*1000)#miliseconds

        self.fig.canvas.mpl_connect('scroll_event', self.onscroll)
        self.fig.canvas.mpl_connect('key_press_event', self.press)
        EmPlotter.show(self)

# 需要导入模块: from pyworkflow.em.plotter import EmPlotter [as 别名]
# 或者: from pyworkflow.em.plotter.EmPlotter import show [as 别名]
    def _onPlotClick(self, e=None):
        selection = self.tree.selection()
        n = len(selection)

        if n < 1 or n > 2:
            self.showError("Select one or two variables to plot.")
        else:
            plotter = EmPlotter()
            varX = self._variables[selection[0]]
            xValues = self.observations[:, varX.index]

            def _label(var):
                return "%s [%s]" % (var.varName, var.unitStr)

            if n == 1:
                plotter.createSubPlot("Histogram", _label(varX), "Count")
                plotter.plotHist(xValues, 50)
            else: # n == 2
                varY = self._variables[selection[1]]
                yValues = self.observations[:, varY.index]
                ax = plotter.createSubPlot("Scatter Plot",
                                           _label(varX), _label(varY))
                ax.plot(xValues, yValues, '.')
            plotter.show()

# 需要导入模块: from pyworkflow.em.plotter import EmPlotter [as 别名]
# 或者: from pyworkflow.em.plotter.EmPlotter import show [as 别名]
    def visualize(self, obj, **kwargs):
        prot = obj
        fnProfiles = prot._getPath("profiles.txt")
        fh = open(fnProfiles,"r")
        Rtype = []
        Rlegends = []
        R = []
        state = 0
        for line in fh:
            if state==0:
                tokens = line.split("::")
                Rtype.append(tokens[0])
                Rlegends.append(tokens[1].strip())
                Ri=[]
                state=1
            elif state==1:
                tokens=line.strip().split()
                if len(tokens)==0:
                    R.append(Ri)
                    state=0
                else:
                    if len(Ri)==0:
                        for n in range(len(tokens)):
                            Ri.append([])
                for n in range(len(tokens)):
                    Ri[n].append(tokens[n])
        fh.close()

        plotter = None
        previousType = ""
        for legend, Ri, Rtypei  in izip(Rlegends, R, Rtype):
            if plotter is None or Rtypei!=previousType:
                if previousType!="":
                    self.addLimits(plotter,previousType,minX,maxX)
                plotter = EmPlotter()
                doShow = True
                if Rtypei=="ReversibleLiver" or Rtypei=="TimeDependentLiver" or Rtypei=="InductionLiver" or Rtypei=="StaticLiver" or Rtypei=="TransporterLiver":
                    Ilabel="[Ih] [uM]"
                elif Rtypei=="ReversibleGut" or Rtypei=="TimeDependentGut" or Rtypei=="InductionGut" or Rtypei=="StaticGut" or Rtypei=="TransporterGut":
                    Ilabel="[Ig] [uM]"
                elif Rtypei=="TransporterRenal":
                    Ilabel="[Cmax] [uM]"
                ax = plotter.createSubPlot("Plot", Ilabel, "R")
                previousType = Rtypei
                minX = None
                maxX = None
            else:
                doShow = False
                ax = plotter.getLastSubPlot()

            x = np.asarray(Ri[0],dtype=np.float64)
            if len(Ri)==2:
                y=np.asarray(Ri[1],dtype=np.float64)
            else:
                y=np.asarray(Ri[2],dtype=np.float64)
            ax.plot(x, y, label=legend)

            minXi = np.min(x)
            maxXi = np.max(x)
            if minX==None:
                minX=minXi
                maxX=maxXi
            minX=min(minXi,minX)
            maxX=min(maxXi,maxX)

            leg = ax.legend()
            if leg:
                leg.draggable()

            if doShow:
                plotter.show()
            else:
                plotter.draw()
        self.addLimits(plotter,previousType,minX,maxX)

# 需要导入模块: from pyworkflow.em.plotter import EmPlotter [as 别名]
# 或者: from pyworkflow.em.plotter.EmPlotter import show [as 别名]

#.........这里部分代码省略.........
            y = _value(y, useMeasureLog)

            if x is not None and y is not None:
                newXValues.append(x)
                newYValues.append(y)

        return newXValues, newYValues

    def _onPlotClick(self, e=None):
        sampleKeys = self.samplesTree.selection()

        if sampleKeys:
            if self.plotter is None or self.plotter.isClosed():
                self.plotter = EmPlotter()
                doShow = True
                ax = self.plotter.createSubPlot("Plot", self.getTimeLabel(),
                                                self.getMeasureLabel())
                self.plotDict = {}
            else:
                doShow = False
                ax = self.plotter.getLastSubPlot()

            samples = [self.experiment.samples[k] for k in sampleKeys]
            for s in samples:
                if not s.sampleName in self.plotDict:
                    x, y = self.getPlotValues(s)
                    ax.plot(x, y, label=s.sampleName)
                    self.plotDict[s.sampleName] = True
            leg = ax.legend()
            if leg:
                leg.draggable()

            if doShow:
                self.plotter.show()
            else:
                self.plotter.draw()
        else:
            self.showInfo("Please select some sample(s) to plot.")

    def _onPlotSummaryClick(self, e=None):
        sampleKeys = self.samplesTree.selection()
        n = len(sampleKeys)

        if n == 1:
            self.showInfo("Please select several samples to plot.")
        else:
            if n > 1:
                samples = [self.experiment.samples[k] for k in sampleKeys]
            else:
                samples = self.experiment.samples.values()

            dataDict = {} # key will be time values
            for s in samples:
                xValues, yValues = self.getPlotValues(s)
                for x, y in izip(xValues, yValues):
                    if x in dataDict:
                        dataDict[x].append(y)
                    else:
                        dataDict[x] = [y]

            sortedTime = sorted(dataDict.keys())
            # We will store five values (min, 25%, 50%, 75%, max)
            # for each of the time entries computed
            percentileList = [0, 25, 50, 75, 100]
            Y = np.zeros((len(sortedTime), 5))
            for i, t in enumerate(sortedTime):

# 需要导入模块: from pyworkflow.em.plotter import EmPlotter [as 别名]
# 或者: from pyworkflow.em.plotter.EmPlotter import show [as 别名]
    def press(self, event):
        def numericKey(key):
            self.colorChanged = True
            number = int(key)
            index = 3+number*3
            if (index + 3) > self.lenPlots:
                return
            if self.color['gpuMem_%d' % number] != 'w':
                self.oldColor['gpuMem_%d' % number] = \
                    self.color['gpuMem_%d' % number]
                self.oldColor['gpuUse_%d' % number] = \
                    self.color['gpuUse_%d' % number]
                self.oldColor['gpuTem_%d' % number] = \
                    self.color['gpuTem_%d' % number]
                self.color['gpuMem_%d' % number] = "w"
                self.color['gpuUse_%d' % number] = "w"
                self.color['gpuTem_%d' % number] = "w"
            else:
                self.color['gpuMem_%d' % number] = \
                    self.oldColor['gpuMem_%d' % number]
                self.color['gpuUse_%d' % number] = \
                    self.oldColor['gpuUse_%d' % number]
                self.color['gpuTem_%d' % number] = \
                    self.oldColor['gpuTem_%d' % number]

        def cpuKey(key):
            self.colorChanged = True
            if self.color['cpu'] != 'w':
                self.oldColor['cpu'] = self.color['cpu']
                self.oldColor['mem'] = self.color['mem']
                self.oldColor['swap'] = self.color['swap']
                self.color['cpu'] = "w"
                self.color['mem'] = "w"
                self.color['swap'] = "w"
            else:
                self.color['cpu'] = self.oldColor['cpu']
                self.color['swap'] = self.oldColor['swap']
                self.color['mem'] = self.oldColor['mem']

        def netKey(key):
            self.colorChanged = True
            if self.color['%s_send' % self.nifName] != 'w':
                self.oldColor['%s_send' % self.nifName] = \
                    self.color['%s_send' % self.nifName]
                self.oldColor['%s_recv' % self.nifName] = \
                    self.color['%s_recv' % self.nifName]
                self.color['%s_send' % self.nifName] = "w"
                self.color['%s_recv' % self.nifName] = "w"
            else:
                self.color['%s_send' % self.nifName] = \
                    self.oldColor['%s_send' % self.nifName]
                self.color['%s_recv' % self.nifName] = \
                    self.oldColor['%s_recv' % self.nifName]

        def diskKey(key):
            self.colorChanged = True
            if self.color['disk_read'] != 'w':
                self.oldColor['disk_read'] = self.color['disk_read']
                self.oldColor['disk_write'] = self.color['disk_write']
                self.color['disk_read'] = "w"
                self.color['disk_write'] = "w"
            else:
                self.color['disk_read'] = self.oldColor['disk_read']
                self.color['disk_write'] = self.oldColor['disk_write']

        sys.stdout.flush()
        if event.key == 'S':
            self.stop = True
            self.ax.set_title('Plot has been Stopped. '
                              'Press C to continue plotting')
        elif event.key == 'C':
            self.ax.set_title(self._getTitle())
            self.stop = False
            self.animate()
        elif event.key.isdigit():
            numericKey(event.key)
            self.animate()
        elif event.key == 'c':
            cpuKey(event.key)
            self.animate()
        elif event.key == 'n':
            netKey(event.key)
            self.animate()
        elif event.key == 'd':
            diskKey(event.key)
            self.animate()
        EmPlotter.show(self)

# 需要导入模块: from pyworkflow.em.plotter import EmPlotter [as 别名]
# 或者: from pyworkflow.em.plotter.EmPlotter import show [as 别名]
class PKPDResponsiveDialog(dialog.Dialog):
    def __init__(self, parent, title, **kwargs):
        """ From kwargs:
                message: message tooltip to show when browsing.
                selected: the item that should be selected.
                validateSelectionCallback: a callback function to validate selected items.
        """
        self.values = []
        self.plotter = None
        self.targetProtocol = kwargs['targetProtocol']
        self.experiment = self.targetProtocol.experiment
        self.varNameX = kwargs['varNameX']
        self.varNameY = kwargs['varNameY']
        self.provider = SamplesTreeProvider(self.experiment)
        self.model = self.loadModel()
        self.validateSelectionCallback = kwargs.get('validateSelectionCallback', None)
        self.setLabels()

        dialog.Dialog.__init__(self, parent, title,
                        buttons=[('Select', dialog.RESULT_YES),
                                 ('Cancel', dialog.RESULT_CANCEL)])

    def setLabels(self):
        pass

    def loadModel(self):
        model = self.targetProtocol.createModel()
        model.setExperiment(self.experiment)
        # if hasattr(self.protODE, "deltaT"):
        #     model.deltaT = self.protODE.deltaT.get()
        model.setXVar(self.varNameX)
        model.setYVar(self.varNameY)
        return model

    def body(self, bodyFrame):
        bodyFrame.config(bg='white')
        gui.configureWeigths(bodyFrame)
        self._createSamplesFrame(bodyFrame)
        self._createSlidersFrame(bodyFrame)
        self._createLogsFrame(bodyFrame)

    def _createSamplesFrame(self, content):
        frame = tk.Frame(content, bg='white')
        #frame = tk.LabelFrame(content, text='General')
        lfSamples = tk.LabelFrame(frame, text="Samples", bg='white')
        gui.configureWeigths(frame)
        lfSamples.grid(row=0, column=0, sticky='news', padx=5, pady=5)
        self.samplesTree = self._addBoundTree(lfSamples,
                                                  self.provider, 10)
        self.samplesTree.itemClick = self._onSampleChanged

        frame.grid(row=0, column=0, sticky='news', padx=5, pady=5)

    def _createSlidersFrame(self, content):
        frame = tk.Frame(content, bg='white')
        lfBounds = tk.LabelFrame(frame, text="Parameter Bounds", bg='white')
        gui.configureWeigths(frame)

        i = 0
        self.sliders = {}
        paramUnits = self.targetProtocol.parameterUnits
        for paramName, bounds in self.targetProtocol.getParameterBounds().iteritems():
            bounds = bounds or (0, 1)
            slider = MinMaxSlider(lfBounds, "%s [%s]"%(paramName,strUnit(paramUnits[i])),
                                  bounds[0], bounds[1],
                                  callback=self._onVarChanged)
            slider.grid(row=i, column=0, padx=5, pady=5)
            self.sliders[paramName] = slider
            i += 1

        lfBounds.grid(row=0, column=0, sticky='news', padx=5, pady=5)
        frame.grid(row=0, column=1, sticky='news', padx=5, pady=5)

    def _createLogsFrame(self, content):
        frame = tk.Frame(content)

        def addVar(text, col, varName):
            varFrame = tk.Frame(frame)
            varFrame.grid(row=0, column=col, sticky='new')
            label = tk.Label(varFrame, text=text)#, font=self.fontBold)
            label.grid(row=0, column=0, padx=5, pady=2, sticky='nw')
            combo = tk.Label(varFrame, text=varName, width=10)
            combo.grid(row=0, column=1, sticky='nw', padx=5, pady=5)
            radioVar = tk.IntVar()
            radio = tk.Checkbutton(varFrame, text='Log10', variable=radioVar)
            radio.grid(row=0, column=2, sticky='nw', padx=5, pady=5)
            return combo, radio, radioVar

        self.timeWidget = addVar('Time variable', 0, self.varNameX)
        self.timeWidget[2].trace('w', self._onLogChanged)
        self.measureWidget = addVar('Measure variable', 1, self.varNameY)
        measureVar = self.measureWidget[2]
        measureVar.set(True)
        measureVar.trace('w', self._onLogChanged)
        frame.grid(row=1, column=0, columnspan=2, sticky='news', padx=5, pady=5)

    def _addBoundTree(self, parent, provider, height):
        bt = BoundTree(parent, provider, height=height)
        bt.grid(row=0, column=0, sticky='news', padx=5, pady=5)
        gui.configureWeigths(parent)
#.........这里部分代码省略.........