Hi, everyone.
Let me explain what I wanted to do: First, I wanted to make a polar
plot with angles from 0 to 90. I could do it by adopting the
curvelinear grid demo ( http://goo.gl/kruXf ). And then I wanted to
present the radius in log10 scale. But setting the plot command to
semilogy or trying to set 'set_rscale('log')' all failed. Below I
pasted the code that works for radius in linear scale.
[Code]
#!/usr/bin/env python
import matplotlib.pyplot as plt
import numpy as np
#Modified from http://matplotlib.sourceforge.net/plot_directive/mpl_toolkits/axes_grid/examples/demo_floating_axis.py
#def curvelinear_test2(fig, lp_r, lp_t):
def curvelinear_test2(fig, lp_t, lp_r, rLower, rUpper):
rmin = np.min(lp_r)
rmax = np.max(lp_r)
print 'rm: ', rmin, 'rM: ', rmax,'rL: ', rLower, 'rU: ', rUpper
"""
polar projection, but in a rectangular box.
"""
global ax1
import mpl_toolkits.axisartist.angle_helper as angle_helper
from matplotlib.projections import PolarAxes
from matplotlib.transforms import Affine2D
from mpl_toolkits.axisartist import SubplotHost, ParasiteAxesAuxTrans
from mpl_toolkits.axisartist import GridHelperCurveLinear
from mpl_toolkits.axisartist.grid_helper_curvelinear import
GridHelperCurveLinear
# see demo_curvelinear_grid.py for details
tr = Affine2D().scale(np.pi/180., 1.) + PolarAxes.PolarTransform()
extreme_finder = angle_helper.ExtremeFinderCycle(20, 20,
lon_cycle = 360,
lat_cycle = None,
lon_minmax = (0, 360),
lat_minmax =
(-np.inf, np.inf),
#lat_minmax =
(rmin, np.inf),
)
grid_locator1 = angle_helper.LocatorDMS(12)
tick_formatter1 = angle_helper.FormatterDMS()
grid_helper = GridHelperCurveLinear(tr,
extreme_finder=extreme_finder,
grid_locator1=grid_locator1,
tick_formatter1=tick_formatter1
)
ax1 = SubplotHost(fig, 1, 1, 1, grid_helper=grid_helper)
fig.add_subplot(ax1)
# make ticklabels of all axis visible.
ax1.axis[:].major_ticklabels.set_visible(True)
#ax1.axis["top"].major_ticklabels.set_visible(True)
#ax1.axis["left"].major_ticklabels.set_visible(True)
#ax1.axis["bottom"].major_ticklabels.set_visible(True)
# show angle (0) at right and top
ax1.axis["right"].get_helper().nth_coord_ticks=0
ax1.axis["top"].get_helper().nth_coord_ticks=0
# show radius (1) at left and bottom
ax1.axis["left"].get_helper().nth_coord_ticks=1
ax1.axis["bottom"].get_helper().nth_coord_ticks=1
# set labels
ax1.axis["left"].label.set_text(r'ylabel')
ax1.axis["bottom"].label.set_text(r'xlabel')
ax1.axis["bottom"].major_ticklabels.set_rotation(-30)
ax1.set_aspect(1.)
ax1.set_xlim(rLower, rUpper)
ax1.set_ylim(rLower, rUpper)
#ax1.rscale('log')
# A parasite axes with given transform
ax2 = ParasiteAxesAuxTrans(ax1, tr, "equal")
# note that ax2.transData == tr + ax1.transData
# Anthing you draw in ax2 will match the ticks and grids of ax1.
ax1.parasites.append(ax2)
ax2.plot(lp_t, lp_r, 'o-')
#ax2.semilogy(lp_t, lp_r, 'o-')
#ax2.set_rscale('log')
#ax1.set_xscale('log')
#ax1.set_yscale('log')
ax1.grid(True)
if __name__ == "__main__":
fig = plt.figure(1, figsize=(5, 5))
fig.clf()
rmin = 1e-1
rmax = 1e2
lp_t = np.linspace(0., 90., 5)
lp_r = np.linspace(rmin, rmax/10, 5)*5
print "lp_t: ", lp_t
print "lp_r: ", lp_r
print "log10(lp_r): ", np.log10(lp_r)
curvelinear_test2(fig, lp_t, lp_r, rmin, rmax)
#curvelinear_test2(fig, lp_t, np.log10(lp_r), np.log10(rmin), np.log(rmax))
plt.show()
[/Code]
I'm using Enthought Python Distribution Version: 7.0-2 (32-bit) Python
2.7.1 on win32
and matplotlib.__version__ is '1.0.1'.
Thanks,
Junghun Shin
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