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It turns out I won't be able to make a Mac binary installer for matplotlib anytime soon. I use bdist_mpkg to make the Mac binary installers for MacOS X, and the current release of bdist_mpkg (4.4) is not compatible with Python 3. I don't know how to make binary installers without bdist_mpkg, though I'm sure it can be done. Also note that there are no numpy binary installers for MacOS X python 3. This *may* be due to the same issue. Fortunately, it is very easy to install matplotlib from source (much easier than it used to be, thanks to patching setupext.py for darwin). -- Russell
Hi Neal, my understanding is that matplotlib does not use OpenGL (thus the terrible performance you see). You might want to look into glumpy for mplot3d OpenGL acceleration. Ethan On Dec 14, 2012, at 5:23 AM, Neal Becker <ndb...@gm...> wrote: > I'm using fedora (17) linux. I notice on complicated 3d plot, interactive > performance can get sluggish. I'm using nouveau driver now, but wondering if > installing nvidia driver will improve mpl 3d performance? Does mpl use opengl? > > > ------------------------------------------------------------------------------ > LogMeIn Rescue: Anywhere, Anytime Remote support for IT. Free Trial > Remotely access PCs and mobile devices and provide instant support > Improve your efficiency, and focus on delivering more value-add services > Discover what IT Professionals Know. Rescue delivers > http://p.sf.net/sfu/logmein_12329d2d > _______________________________________________ > Matplotlib-users mailing list > Mat...@li... > https://lists.sourceforge.net/lists/listinfo/matplotlib-users
I've created a class that allows a user to add several charts to a MATPLOTLIB window. These can be either a line chart or a bar chart. It also has the feature that when a chart has already been added to the window (as identified from rowID) rather than draw a new plot it will replace the data in the old plot. ie it allows for updates (animation) This works grand for the line plot but I get corruption when plotting several bar charts. The class looks like: import math class TFrmPlot(): def __init__(self, point_lists, deleteCallback, plotType, rowID): import matplotlib matplotlib.interactive( True ) matplotlib.use( 'WXAgg' ) import matplotlib.pyplot as plt self.plt = plt self.fig = plt.figure() self.fig.canvas.mpl_connect('close_event', self.on_close) import matplotlib.axes as ax self.ax = ax self.deleteCallback = deleteCallback self.chartArray = [] self.addChart(point_lists, plotType, rowID) def close(self): self.plt.close('all') #self.fig.close() def replaceChartDataIfChartExists(self, point_lists, rowID): if rowID==0: pass for chart in self.chartArray: for plot in chart.plots: if plot.rowID == rowID: plot.points = point_lists if plot.plotType=="Point": plot.plotItem.set_data(point_lists[0],point_lists[1]) chart.subPlot.draw_artist(plot.plotItem) self.fig.canvas.blit(chart.subPlot.bbox) else: for rect, h in zip(plot.plotItem, point_lists[1]): rect.set_height(h) chart.subPlot.relim() chart.subPlot.autoscale_view(True,True,True) self.plt.draw() return True return False def addChart(self, point_lists, plotType, rowID): self.chartArray.append(TChart(rowID,plotType,point_lists)) self._drawAll() def addPlot(self, point_lists, plotType, rowID): chartNum = len(self.chartArray) self.chartArray[chartNum-1].plots.append(TPlot(rowID,plotType,point_lists)) self._drawAll() def on_close(self, event): self.deleteCallback() def _drawAll(self): self.plt.clf() numSubPlots = len(self.chartArray) numCols = self._noCols(numSubPlots) IndexConverter = TIndexConverter(numCols) subPlot = None for chartIndex in range(0,numSubPlots): if numSubPlots==1: subPlot = self.fig.add_subplot(1,1,1) elif numSubPlots==2: subPlot = self.fig.add_subplot(1,2,chartIndex+1) else: subPlot = self.fig.add_subplot(2,numCols,IndexConverter._getSubPlotIndex(chartIndex)) subPlot.relim() subPlot.autoscale_view(True,True,True) self.chartArray[chartIndex].subPlot = subPlot self._drawSubs(self.chartArray[chartIndex]) self.plt.show() def _drawSubs(self, chart): for plot in chart.plots: if plot.plotType=="Point": chart.subPlot.plot(plot.points[0],plot.points[1]) plot.plotItem = chart.subPlot.lines[len(chart.subPlot.lines)-1] else: kwargs = {"alpha":0.5} plot.plotItem = chart.subPlot.bar(plot.points[0],plot.points[1], width=self._calculateleastDiff(plot.points[0]), **kwargs) def _noCols(self, numSubPlots): return math.ceil(float(numSubPlots)/2.0) def _calculateleastDiff(self, xValues): xValues2 = sorted(xValues) leastDiff = None lastValue = None for value in xValues2: if lastValue is not None: diff = value-lastValue if leastDiff is None or diff < leastDiff: leastDiff = diff lastValue = value return leastDiff This is a bit long so to summarise: addChart -- basically adds a new subplot addPlot -- adds a new line or bar to an existing subplot replaceChartDataIfChartExists -- refreshes the data if the ID already exists The dummy data that I'm using just plots a positive gradient and a negative gradient line in succession. My plots however can get into a state where one/some or all of the bar plots become corrupted. It looks almost like the x/y axis has been rotated, with the individual bars not starting from the x-axis. The issue is intermittent; sometimes I will get several plots as expected. Once a plot becomes corrupted all future updates remain corrupted. Corrupted Chart: <http://matplotlib.1069221.n5.nabble.com/file/n40023/corrupted.png> -- View this message in context: http://matplotlib.1069221.n5.nabble.com/Bar-chart-corruption-when-plotting-multiple-subplots-in-MATPLOTLIB-tp40023.html Sent from the matplotlib - users mailing list archive at Nabble.com.
I'm using fedora (17) linux. I notice on complicated 3d plot, interactive performance can get sluggish. I'm using nouveau driver now, but wondering if installing nvidia driver will improve mpl 3d performance? Does mpl use opengl?