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
