import numpy as np from numpy.testing import assert_allclose import pytest import matplotlib as mpl from matplotlib import pyplot as plt from matplotlib.testing.decorators import image_comparison, check_figures_equal @image_comparison(['polar_axes'], style='default', tol=0.012) def test_polar_annotations(): # You can specify the xypoint and the xytext in different positions and # coordinate systems, and optionally turn on a connecting line and mark the # point with a marker. Annotations work on polar axes too. In the example # below, the xy point is in native coordinates (xycoords defaults to # 'data'). For a polar axes, this is in (theta, radius) space. The text # in this example is placed in the fractional figure coordinate system. # Text keyword args like horizontal and vertical alignment are respected. # Setup some data r = np.arange(0.0, 1.0, 0.001) theta = 2.0 * 2.0 * np.pi * r fig = plt.figure() ax = fig.add_subplot(polar=True) line, = ax.plot(theta, r, color='#ee8d18', lw=3) line, = ax.plot((0, 0), (0, 1), color="#0000ff", lw=1) ind = 800 thisr, thistheta = r[ind], theta[ind] ax.plot([thistheta], [thisr], 'o') ax.annotate('a polar annotation', xy=(thistheta, thisr), # theta, radius xytext=(0.05, 0.05), # fraction, fraction textcoords='figure fraction', arrowprops=dict(facecolor='black', shrink=0.05), horizontalalignment='left', verticalalignment='baseline', ) ax.tick_params(axis='x', tick1On=True, tick2On=True, direction='out') @image_comparison(['polar_coords'], style='default', remove_text=True, tol=0.012) def test_polar_coord_annotations(): # You can also use polar notation on a cartesian axes. Here the native # coordinate system ('data') is cartesian, so you need to specify the # xycoords and textcoords as 'polar' if you want to use (theta, radius). el = mpl.patches.Ellipse((0, 0), 10, 20, facecolor='r', alpha=0.5) fig = plt.figure() ax = fig.add_subplot(aspect='equal') ax.add_artist(el) el.set_clip_box(ax.bbox) ax.annotate('the top', xy=(np.pi/2., 10.), # theta, radius xytext=(np.pi/3, 20.), # theta, radius xycoords='polar', textcoords='polar', arrowprops=dict(facecolor='black', shrink=0.05), horizontalalignment='left', verticalalignment='baseline', clip_on=True, # clip to the axes bounding box ) ax.set_xlim(-20, 20) ax.set_ylim(-20, 20) @image_comparison(['polar_alignment.png']) def test_polar_alignment(): # Test changing the vertical/horizontal alignment of a polar graph. angles = np.arange(0, 360, 90) grid_values = [0, 0.2, 0.4, 0.6, 0.8, 1] fig = plt.figure() rect = [0.1, 0.1, 0.8, 0.8] horizontal = fig.add_axes(rect, polar=True, label='horizontal') horizontal.set_thetagrids(angles) vertical = fig.add_axes(rect, polar=True, label='vertical') vertical.patch.set_visible(False) for i in range(2): fig.axes[i].set_rgrids( grid_values, angle=angles[i], horizontalalignment='left', verticalalignment='top') def test_polar_twice(): fig = plt.figure() plt.polar([1, 2], [.1, .2]) plt.polar([3, 4], [.3, .4]) assert len(fig.axes) == 1, 'More than one polar axes created.' @check_figures_equal() def test_polar_wrap(fig_test, fig_ref): ax = fig_test.add_subplot(projection="polar") ax.plot(np.deg2rad([179, -179]), [0.2, 0.1]) ax.plot(np.deg2rad([2, -2]), [0.2, 0.1]) ax = fig_ref.add_subplot(projection="polar") ax.plot(np.deg2rad([179, 181]), [0.2, 0.1]) ax.plot(np.deg2rad([2, 358]), [0.2, 0.1]) @check_figures_equal() def test_polar_units_1(fig_test, fig_ref): import matplotlib.testing.jpl_units as units units.register() xs = [30.0, 45.0, 60.0, 90.0] ys = [1.0, 2.0, 3.0, 4.0] plt.figure(fig_test.number) plt.polar([x * units.deg for x in xs], ys) ax = fig_ref.add_subplot(projection="polar") ax.plot(np.deg2rad(xs), ys) ax.set(xlabel="deg") @check_figures_equal() def test_polar_units_2(fig_test, fig_ref): import matplotlib.testing.jpl_units as units units.register() xs = [30.0, 45.0, 60.0, 90.0] xs_deg = [x * units.deg for x in xs] ys = [1.0, 2.0, 3.0, 4.0] ys_km = [y * units.km for y in ys] plt.figure(fig_test.number) # test {theta,r}units. plt.polar(xs_deg, ys_km, thetaunits="rad", runits="km") assert isinstance(plt.gca().xaxis.get_major_formatter(), units.UnitDblFormatter) ax = fig_ref.add_subplot(projection="polar") ax.plot(np.deg2rad(xs), ys) ax.xaxis.set_major_formatter(mpl.ticker.FuncFormatter("{:.12}".format)) ax.set(xlabel="rad", ylabel="km") @image_comparison(['polar_rmin'], style='default') def test_polar_rmin(): r = np.arange(0, 3.0, 0.01) theta = 2*np.pi*r fig = plt.figure() ax = fig.add_axes([0.1, 0.1, 0.8, 0.8], polar=True) ax.plot(theta, r) ax.set_rmax(2.0) ax.set_rmin(0.5) @image_comparison(['polar_negative_rmin'], style='default') def test_polar_negative_rmin(): r = np.arange(-3.0, 0.0, 0.01) theta = 2*np.pi*r fig = plt.figure() ax = fig.add_axes([0.1, 0.1, 0.8, 0.8], polar=True) ax.plot(theta, r) ax.set_rmax(0.0) ax.set_rmin(-3.0) @image_comparison(['polar_rorigin'], style='default') def test_polar_rorigin(): r = np.arange(0, 3.0, 0.01) theta = 2*np.pi*r fig = plt.figure() ax = fig.add_axes([0.1, 0.1, 0.8, 0.8], polar=True) ax.plot(theta, r) ax.set_rmax(2.0) ax.set_rmin(0.5) ax.set_rorigin(0.0) @image_comparison(['polar_invertedylim.png'], style='default') def test_polar_invertedylim(): fig = plt.figure() ax = fig.add_axes([0.1, 0.1, 0.8, 0.8], polar=True) ax.set_ylim(2, 0) @image_comparison(['polar_invertedylim_rorigin.png'], style='default') def test_polar_invertedylim_rorigin(): fig = plt.figure() ax = fig.add_axes([0.1, 0.1, 0.8, 0.8], polar=True) ax.yaxis.set_inverted(True) # Set the rlims to inverted (2, 0) without calling set_rlim, to check that # viewlims are correctly unstaled before draw()ing. ax.plot([0, 0], [0, 2], c="none") ax.margins(0) ax.set_rorigin(3) @image_comparison(['polar_theta_position'], style='default') def test_polar_theta_position(): r = np.arange(0, 3.0, 0.01) theta = 2*np.pi*r fig = plt.figure() ax = fig.add_axes([0.1, 0.1, 0.8, 0.8], polar=True) ax.plot(theta, r) ax.set_theta_zero_location("NW", 30) ax.set_theta_direction('clockwise') @image_comparison(['polar_rlabel_position'], style='default') def test_polar_rlabel_position(): fig = plt.figure() ax = fig.add_subplot(projection='polar') ax.set_rlabel_position(315) ax.tick_params(rotation='auto') @image_comparison(['polar_theta_wedge'], style='default') def test_polar_theta_limits(): r = np.arange(0, 3.0, 0.01) theta = 2*np.pi*r theta_mins = np.arange(15.0, 361.0, 90.0) theta_maxs = np.arange(50.0, 361.0, 90.0) DIRECTIONS = ('out', 'in', 'inout') fig, axs = plt.subplots(len(theta_mins), len(theta_maxs), subplot_kw={'polar': True}, figsize=(8, 6)) for i, start in enumerate(theta_mins): for j, end in enumerate(theta_maxs): ax = axs[i, j] ax.plot(theta, r) if start < end: ax.set_thetamin(start) ax.set_thetamax(end) else: # Plot with clockwise orientation instead. ax.set_thetamin(end) ax.set_thetamax(start) ax.set_theta_direction('clockwise') ax.tick_params(tick1On=True, tick2On=True, direction=DIRECTIONS[i % len(DIRECTIONS)], rotation='auto') ax.yaxis.set_tick_params(label2On=True, rotation='auto') ax.xaxis.get_major_locator().base.set_params( # backcompat steps=[1, 2, 2.5, 5, 10]) @check_figures_equal(extensions=["png"]) def test_polar_rlim(fig_test, fig_ref): ax = fig_test.subplots(subplot_kw={'polar': True}) ax.set_rlim(top=10) ax.set_rlim(bottom=.5) ax = fig_ref.subplots(subplot_kw={'polar': True}) ax.set_rmax(10.) ax.set_rmin(.5) @check_figures_equal(extensions=["png"]) def test_polar_rlim_bottom(fig_test, fig_ref): ax = fig_test.subplots(subplot_kw={'polar': True}) ax.set_rlim(bottom=[.5, 10]) ax = fig_ref.subplots(subplot_kw={'polar': True}) ax.set_rmax(10.) ax.set_rmin(.5) def test_polar_rlim_zero(): ax = plt.figure().add_subplot(projection='polar') ax.plot(np.arange(10), np.arange(10) + .01) assert ax.get_ylim()[0] == 0 def test_polar_no_data(): plt.subplot(projection="polar") ax = plt.gca() assert ax.get_rmin() == 0 and ax.get_rmax() == 1 plt.close("all") # Used to behave differently (by triggering an autoscale with no data). plt.polar() ax = plt.gca() assert ax.get_rmin() == 0 and ax.get_rmax() == 1 def test_polar_not_datalim_adjustable(): ax = plt.figure().add_subplot(projection="polar") with pytest.raises(ValueError): ax.set_adjustable("datalim") def test_polar_gridlines(): fig = plt.figure() ax = fig.add_subplot(polar=True) # make all major grid lines lighter, only x grid lines set in 2.1.0 ax.grid(alpha=0.2) # hide y tick labels, no effect in 2.1.0 plt.setp(ax.yaxis.get_ticklabels(), visible=False) fig.canvas.draw() assert ax.xaxis.majorTicks[0].gridline.get_alpha() == .2 assert ax.yaxis.majorTicks[0].gridline.get_alpha() == .2 def test_get_tightbbox_polar(): fig, ax = plt.subplots(subplot_kw={'projection': 'polar'}) fig.canvas.draw() bb = ax.get_tightbbox(fig.canvas.get_renderer()) assert_allclose( bb.extents, [107.7778, 29.2778, 539.7847, 450.7222], rtol=1e-03) @check_figures_equal(extensions=["png"]) def test_polar_interpolation_steps_constant_r(fig_test, fig_ref): # Check that an extra half-turn doesn't make any difference -- modulo # antialiasing, which we disable here. p1 = (fig_test.add_subplot(121, projection="polar") .bar([0], [1], 3*np.pi, edgecolor="none", antialiased=False)) p2 = (fig_test.add_subplot(122, projection="polar") .bar([0], [1], -3*np.pi, edgecolor="none", antialiased=False)) p3 = (fig_ref.add_subplot(121, projection="polar") .bar([0], [1], 2*np.pi, edgecolor="none", antialiased=False)) p4 = (fig_ref.add_subplot(122, projection="polar") .bar([0], [1], -2*np.pi, edgecolor="none", antialiased=False)) @check_figures_equal(extensions=["png"]) def test_polar_interpolation_steps_variable_r(fig_test, fig_ref): l, = fig_test.add_subplot(projection="polar").plot([0, np.pi/2], [1, 2]) l.get_path()._interpolation_steps = 100 fig_ref.add_subplot(projection="polar").plot( np.linspace(0, np.pi/2, 101), np.linspace(1, 2, 101)) def test_thetalim_valid_invalid(): ax = plt.subplot(projection='polar') ax.set_thetalim(0, 2 * np.pi) # doesn't raise. ax.set_thetalim(thetamin=800, thetamax=440) # doesn't raise. with pytest.raises(ValueError, match='angle range must be less than a full circle'): ax.set_thetalim(0, 3 * np.pi) with pytest.raises(ValueError, match='angle range must be less than a full circle'): ax.set_thetalim(thetamin=800, thetamax=400) def test_thetalim_args(): ax = plt.subplot(projection='polar') ax.set_thetalim(0, 1) assert tuple(np.radians((ax.get_thetamin(), ax.get_thetamax()))) == (0, 1) ax.set_thetalim((2, 3)) assert tuple(np.radians((ax.get_thetamin(), ax.get_thetamax()))) == (2, 3) def test_default_thetalocator(): # Ideally we would check AAAABBC, but the smallest axes currently puts a # single tick at 150° because MaxNLocator doesn't have a way to accept 15° # while rejecting 150°. fig, axs = plt.subplot_mosaic( "AAAABB.", subplot_kw={"projection": "polar"}) for ax in axs.values(): ax.set_thetalim(0, np.pi) for ax in axs.values(): ticklocs = np.degrees(ax.xaxis.get_majorticklocs()).tolist() assert pytest.approx(90) in ticklocs assert pytest.approx(100) not in ticklocs def test_axvspan(): ax = plt.subplot(projection="polar") span = plt.axvspan(0, np.pi/4) assert span.get_path()._interpolation_steps > 1 @check_figures_equal(extensions=["png"]) def test_remove_shared_polar(fig_ref, fig_test): # Removing shared polar axes used to crash. Test removing them, keeping in # both cases just the lower left axes of a grid to avoid running into a # separate issue (now being fixed) of ticklabel visibility for shared axes. axs = fig_ref.subplots( 2, 2, sharex=True, subplot_kw={"projection": "polar"}) for i in [0, 1, 3]: axs.flat[i].remove() axs = fig_test.subplots( 2, 2, sharey=True, subplot_kw={"projection": "polar"}) for i in [0, 1, 3]: axs.flat[i].remove() def test_shared_polar_keeps_ticklabels(): fig, axs = plt.subplots( 2, 2, subplot_kw={"projection": "polar"}, sharex=True, sharey=True) fig.canvas.draw() assert axs[0, 1].xaxis.majorTicks[0].get_visible() assert axs[0, 1].yaxis.majorTicks[0].get_visible() fig, axs = plt.subplot_mosaic( "ab\ncd", subplot_kw={"projection": "polar"}, sharex=True, sharey=True) fig.canvas.draw() assert axs["b"].xaxis.majorTicks[0].get_visible() assert axs["b"].yaxis.majorTicks[0].get_visible() def test_axvline_axvspan_do_not_modify_rlims(): ax = plt.subplot(projection="polar") ax.axvspan(0, 1) ax.axvline(.5) ax.plot([.1, .2]) assert ax.get_ylim() == (0, .2) def test_cursor_precision(): ax = plt.subplot(projection="polar") # Higher radii correspond to higher theta-precisions. assert ax.format_coord(0, 0) == "θ=0π (0°), r=0.000" assert ax.format_coord(0, .1) == "θ=0.00π (0°), r=0.100" assert ax.format_coord(0, 1) == "θ=0.000π (0.0°), r=1.000" assert ax.format_coord(1, 0) == "θ=0.3π (57°), r=0.000" assert ax.format_coord(1, .1) == "θ=0.32π (57°), r=0.100" assert ax.format_coord(1, 1) == "θ=0.318π (57.3°), r=1.000" assert ax.format_coord(2, 0) == "θ=0.6π (115°), r=0.000" assert ax.format_coord(2, .1) == "θ=0.64π (115°), r=0.100" assert ax.format_coord(2, 1) == "θ=0.637π (114.6°), r=1.000"