Hi, with normal polar plot it would work, but there is the problem with the half plot. So I use AxisArtist already. The segfault is caused by GridHelperCurveLinear and it appears on all my Computers here Python 2.7 (2 x Win7 64Bit, 1xWin7 32Bit, 2x Linux 64Bit) and mpl 1.4.2
The current solution would work for me, if I could change the axis tick labels created with axisartist. Maik Am 12.04.2015 um 03:02 schrieb Thomas Caswell: > Malk, > > This is a bit of a gap in mpl currently (but has come up a couple of times ( > https://github.com/matplotlib/matplotlib/issues/4217, > https://github.com/matplotlib/matplotlib/issues/2203, and > http://matplotlib.org/devdocs/devel/MEP/MEP24.html). > > One of the hold ups has been lack of a developer that uses polar plots > day-to-day and a lack of really clear use cases. I think we have three (at > least) distinct use cases. > > 1. origin always an 0, negative radius rotates by pi, always full 2pi > around, always solid circle (no inner axes) (useful for plotting bunches of > vectors against each other) > 2. center is at arbitrary 'r', values less than 'origin' are just not > shown, always full 2pi, no inner axes (use for for dB plots showing power > as function of angle) > 3. inner axes with arbitrary origin, possibly not full 2pi > > It is not immediately clear to me if these can all be done with the same > projection or even if they can be done with the 'standard' Axes class or if > we need to user AxesArtist here. > > This discussion should probably move to MEP24/the devel list. > > What version of mpl are you using? Your example causes seg-faults (!) on > my system, but I have not sorted out why (may be really strange install > issues on my end). > > Tom > > On Thu, Apr 9, 2015 at 6:08 AM Maik Hoffmann <maik.hoffm...@b-tu.de> wrote: > >> Hello, >> I'm using mpl_toolkits.axisartist.floating_axes.GridHelperCurveLinear >> for creating half-polar plots from 180 degree measurements for receive >> sensitivity. >> >> Working with the measurement values itself is no problem if I let the >> values scaling start at zero. >> If I use normalized values I can plot it also, but if I transform it >> into the dB scale I got a segfault in this lib. >> >> I provide an example. For my problems I would like to have a solution >> that I can either use r limit from -30 to 0 (f3) or changing the tick >> labels in figure f2. >> >> And by the way is there a possibility that the if i want to plot data in >> the range from 80 to 120, that rlim(80,120) would set the 80 to the >> centerpoint? At the moment I got only a small stripe. >> >> [code] >> """Demo of polar plot of arbitrary theta. This is a workaround for MPL's >> polar plot limitation >> to a full 360 deg. >> >> Based on >> http://matplotlib.org/mpl_toolkits/axes_grid/examples/ >> demo_floating_axes.py >> >> get from >> https://github.com/neuropy/neuropy/blob/master/neuropy/ >> scripts/polar_demo.py >> TODO: license / copyright >> """ >> >> from __future__ import division >> from __future__ import print_function >> >> import numpy as np >> import matplotlib.pyplot as plt >> >> from matplotlib.transforms import Affine2D >> from matplotlib.projections import PolarAxes >> from mpl_toolkits.axisartist import angle_helper >> from mpl_toolkits.axisartist.grid_finder import MaxNLocator >> from mpl_toolkits.axisartist.floating_axes import GridHelperCurveLinear, >> FloatingSubplot >> >> >> def fractional_polar_axes(f, thlim=(0, 180), rlim=(0, 1), step=(30, 0.2), >> thlabel='theta', rlabel='r', ticklabels=True, >> theta_offset=0): >> """Return polar axes that adhere to desired theta (in deg) and r >> limits. steps for theta >> and r are really just hints for the locators.""" >> th0, th1 = thlim # deg >> r0, r1 = rlim >> thstep, rstep = step >> >> tr_rotate = Affine2D().translate(theta_offset, 0) >> # scale degrees to radians: >> tr_scale = Affine2D().scale(np.pi/180., 1.) >> #pa = axes(polar="true") # Create a polar axis >> pa = PolarAxes >> tr = tr_rotate + tr_scale + pa.PolarTransform() >> theta_grid_locator = angle_helper.LocatorDMS((th1-th0)//thstep) >> r_grid_locator = MaxNLocator((r1-r0)//rstep) >> theta_tick_formatter = angle_helper.FormatterDMS() >> >> grid_helper = GridHelperCurveLinear(tr, >> extremes=(th0, th1, r0, r1), >> grid_locator1=theta_grid_locator, >> grid_locator2=r_grid_locator, >> >> tick_formatter1=theta_tick_formatter, >> tick_formatter2=None) >> >> a = FloatingSubplot(f, 111, grid_helper=grid_helper) >> >> f.add_subplot(a) >> >> # adjust x axis (theta): >> a.axis["bottom"].set_visible(False) >> a.axis["top"].set_axis_direction("bottom") # tick direction >> a.axis["top"].toggle(ticklabels=ticklabels, label=bool(thlabel)) >> a.axis["top"].major_ticklabels.set_axis_direction("top") >> a.axis["top"].label.set_axis_direction("top") >> >> # adjust y axis (r): >> a.axis["left"].set_axis_direction("bottom") # tick direction >> a.axis["right"].set_axis_direction("top") # tick direction >> a.axis["left"].toggle(ticklabels=ticklabels, label=bool(rlabel)) >> >> # add labels: >> a.axis["top"].label.set_text(thlabel) >> a.axis["left"].label.set_text(rlabel) >> >> # create a parasite axes whose transData is theta, r: >> auxa = a.get_aux_axes(tr) >> # make aux_ax to have a clip path as in a?: >> auxa.patch = a.patch >> # this has a side effect that the patch is drawn twice, and >> possibly over some other >> # artists. So, we decrease the zorder a bit to prevent this: >> a.patch.zorder = -2 >> >> >> # add sector lines for both dimensions: >> thticks = grid_helper.grid_info['lon_info'][0] >> rticks = grid_helper.grid_info['lat_info'][0] >> for th in thticks[1:-1]: # all but the first and last >> auxa.plot([th, th], [r0, r1], '--', c='grey', zorder=-1) >> for ri, r in enumerate(rticks): >> # plot first r line as axes border in solid black only if it >> isn't at r=0 >> if ri == 0 and r != 0: >> ls, lw, color = 'solid', 2, 'black' >> else: >> ls, lw, color = 'dashed', 1, 'grey' >> # From http://stackoverflow.com/a/19828753/2020363 >> auxa.add_artist(plt.Circle([0, 0], radius=r, ls=ls, lw=lw, >> color=color, fill=False, >> transform=auxa.transData._b, zorder=-1)) >> >> return auxa >> >> >> if __name__ == '__main__': >> f1 = plt.figure(facecolor='white', figsize=(16/2.54, 12/2.54), >> dpi=600) >> a1 = fractional_polar_axes(f1, thlim=(-90, 90),step=(10, >> 0.2),theta_offset=90) >> # example spiral plot: >> thstep = 10 >> th = np.arange(-90, 90+thstep, thstep) # deg >> rstep = 1/(len(th)-1) >> r = np.arange(0, 1+rstep, rstep) >> a1.plot(th, r, 'b') >> >> >> f1.show() >> >> f2 = plt.figure(facecolor='white', figsize=(16/2.54, 12/2.54), >> dpi=600) >> a2 = fractional_polar_axes(f2, thlim=(-90, >> 90),rlim=(0,30),step=(10, 8),theta_offset=90) >> # example spiral plot: >> r2 = 20 * np.log10(r) +30 >> a2.plot(th, r2, 'b') >> >> f2.show() >> >> f3 = plt.figure(facecolor='white', figsize=(16/2.54, 12/2.54), >> dpi=600) >> a3 = fractional_polar_axes(f2, thlim=(-90, 90),rlim=(-30,0), >> step=(10, 8),theta_offset=90) >> # example spiral plot: >> r3 = 20 * np.log10(r) >> a3.plot(th, r2, 'b') >> >> f2.show() >> >> [\code] >> >> -- >> >> >> ------------------------------------------------------------ >> ------------------ >> BPM Camp - Free Virtual Workshop May 6th at 10am PDT/1PM EDT >> Develop your own process in accordance with the BPMN 2 standard >> Learn Process modeling best practices with Bonita BPM through live >> exercises >> http://www.bonitasoft.com/be-part-of-it/events/bpm-camp-virtual- >> event?utm_ >> source=Sourceforge_BPM_Camp_5_6_15&utm_medium=email&utm_campaign=VA_SF >> _______________________________________________ >> Matplotlib-users mailing list >> Matplotlib-users@lists.sourceforge.net >> https://lists.sourceforge.net/lists/listinfo/matplotlib-users >> > -- wissenschaftlicher Mitarbeiter Lehrstuhl Allgemeine Elektrotechnik und Messtechnik (AEMT) Fakultät Maschinenbau, Elektrotechnik und Wirtschaftsingenieurwesen Brandenburgische Technische Universität Cottbus Siemens-Halske-Ring 14 D-03046 Cottbus Tel.: +49-355-69-3425 Fax: +49-355-69-4104 http://www.tu-cottbus.de/fakultaet3/de/elektrotechnik-messtechnik/ ------------------------------------------------------------------------------ BPM Camp - Free Virtual Workshop May 6th at 10am PDT/1PM EDT Develop your own process in accordance with the BPMN 2 standard Learn Process modeling best practices with Bonita BPM through live exercises http://www.bonitasoft.com/be-part-of-it/events/bpm-camp-virtual- event?utm_ source=Sourceforge_BPM_Camp_5_6_15&utm_medium=email&utm_campaign=VA_SF _______________________________________________ Matplotlib-users mailing list Matplotlib-users@lists.sourceforge.net https://lists.sourceforge.net/lists/listinfo/matplotlib-users
