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Contourf with Polar Projection produces artifacts (changes with "levels") #20060

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@ngc1535git

Description

@ngc1535git

Bug report

Bug summary

Interpolated data (by griddata) plotted in Cartesian coordinates with Contourf render free of artifacts regardless of how fine the contours are (by levels). When the subplot uses polar projection, artifacts, such as polygons and thin rays, develop.

import numpy as npimport matplotlib.pyplot as pltfrom scipy.interpolate import griddatagridsize =150graphlevels = 80plt.figure(figsize=(12,10))ax = plt.subplot(111,projection='polar')x = [72.90,68.00,59.14,44.38,29.63,63.94,59.68,51.92,38.98,26.03,47.34,44.20,38.46,28.89,19.31,23.40,20.40,15.34,10.28,-0.18,-0.14,-0.09,-0.04,0.02,-25.39,-23.66,-20.57,-15.40,-10.23,-47.56,-44.34,-38.54,-28.89,-19.22,-64.01,-59.68,-51.89,-38.90,-25.90,-72.77,-67.84,-58.98,-44.21,-29.44,-72.75,-67.83,-58.96,-44.18,-29.41,-59.63,-51.82,-38.83,-25.84,-47.42,-44.20,-38.40,-28.76,-19.12,-23.40,-20.32,-15.19,-10.08,0.27,0.25,0.23,0.20,23.92,20.80,15.63,10.46,47.93,44.67,38.86,29.17,19.48,64.40,60.03,52.20,39.18,26.15,73.08,68.12,59.26,44.47,29.68,-4.81]y = [12.93,12.01,10.38,7.67,4.99,37.03,34.49,29.93,22.33,14.77,56.60,52.75,45.82,34.26,22.72,64.60,56.14,42.02,27.90,73.66,68.67,59.68,44.68,29.68,69.12,64.45,56.00,41.92,27.84,56.26,52.45,45.56,34.08,22.61,36.59,34.11,29.61,22.11,14.62,12.48,11.62,10.04,7.43,4.83,-13.33,-12.31,-10.78,-8.21,-5.58,-34.84,-30.36,-22.87,-15.36,-57.04,-53.20,-46.31,-34.83,-23.34,-65.20,-56.72,-42.62,-28.53,-69.33,-60.31,-45.31,-30.31,-65.09,-56.63,-42.55,-28.47,-56.81,-52.99,-46.13,-34.69,-23.23,-36.99,-34.53,-30.08,-22.66,-15.22,-12.73,-11.93,-10.44,-7.94,-5.40,-1.22,]skybrightness = [19.26,19.31,19.21,19.65,19.40,19.26,19.23,19.43,19.57,19.52,19.19,19.31,19.33,19.68,19.50,19.29,19.45,19.50,19.23,18.98,19.28,19.46,19.54,19.22,19.03,19.18,19.35,19.37,19.08,18.99,18.98,19.26,19.36,19.08,18.79,18.85,19.13,19.17,19.05,18.51,18.64,18.88,18.92,18.93,18.12,18.34,18.72,18.82,18.74,18.22,18.46,18.76,18.26,18.13,18.24,18.46,18.58,17.30,18.38,18.08,18.24,17.68,18.34,18.46,18.65,18.23,18.70,18.52,18.79,18.83,18.18,18.51,19.01,19.08,19.08,18.99,19.02,19.07,19.20,19.27,19.06,19.01,19.28,19.46,19.30,18.94]xgrid = np.linspace(min(x), max(x),gridsize)ygrid = np.linspace(min(y), max(y),gridsize)xgrid, ygrid = np.meshgrid(xgrid, ygrid, indexing='ij')nsb_grid = griddata((x,y),skybrightness,(xgrid, ygrid), method='linear')r = np.sqrt(xgrid**2 + ygrid**2)theta = np.arctan2(ygrid, xgrid)plt.rc('ytick', labelsize=16)ax.set_facecolor('#eeddcc')colors = plt.cm.get_cmap('RdYlBu')levels,steps = np.linspace(min(skybrightness), max(skybrightness)+0.3,graphlevels, retstep=True)ticks = np.linspace(min(skybrightness), max(skybrightness)+0.3,12)cax = ax.contourf(theta, r, nsb_grid, levels=levels, cmap=colors)cbar = plt.colorbar(cax, fraction=0.046, pad=0.04, ticks=ticks)cbar.set_label(r'mag/arcsec$^2$')ax.set_theta_zero_location('N')ax.set_theta_direction(-1)ax.set_rmax(75)ax.set_yticks(range(10, 80, 20))ax.set_xticklabels([r'N', r'NE', r'E', r'SE', r'S', r'SW', r'W', r'NW'])ax.grid(alpha=0.3)plt.savefig('StackOverflowHELP.png')

Actual outcome
Output of the above
Capture1

Cartesian version with cax = ax.contourf(xgrid ygrid, nsb_grid, levels=levels, cmap=colors)
Capture4

Note that Polar Project with very small levels (12) is artifact free:
Capture

# If applicable, paste the console output here##

Expected outcome

Matplotlib version
Ubuntu 18.04.5 LTS
Matplotlib Version: 2.2.2

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