Python matplotlib.pyplot.polar() Examples

def test_markevery_polar():
    cases = [None,
         8,
         (30, 8),
         [16, 24, 30], [0,-1],
         slice(100, 200, 3),
         0.1, 0.3, 1.5,
         (0.0, 0.1), (0.45, 0.1)]

    cols = 3
    gs = matplotlib.gridspec.GridSpec(len(cases) // cols + 1, cols)

    r = np.linspace(0, 3.0, 200)
    theta = 2 * np.pi * r

    for i, case in enumerate(cases):
        row = (i // cols)
        col = i % cols
        plt.subplot(gs[row, col], polar = True)
        plt.title('markevery=%s' % str(case))
        plt.plot(theta, r, 'o', ls='-', ms=4,  markevery=case) 

def test_polar_wrap():
    D2R = np.pi / 180.0

    fig = plt.figure()

    plt.subplot(111, polar=True)

    plt.polar([179*D2R, -179*D2R], [0.2, 0.1], "b.-")
    plt.polar([179*D2R,  181*D2R], [0.2, 0.1], "g.-")
    plt.rgrids([0.05, 0.1, 0.15, 0.2, 0.25, 0.3])
    assert len(fig.axes) == 1, 'More than one polar axes created.'
    fig = plt.figure()

    plt.subplot(111, polar=True)
    plt.polar([2*D2R, -2*D2R], [0.2, 0.1], "b.-")
    plt.polar([2*D2R,  358*D2R], [0.2, 0.1], "g.-")
    plt.polar([358*D2R,  2*D2R], [0.2, 0.1], "r.-")
    plt.rgrids([0.05, 0.1, 0.15, 0.2, 0.25, 0.3]) 

def test_markevery_polar():
    cases = [None,
         8,
         (30, 8),
         [16, 24, 30], [0,-1],
         slice(100, 200, 3),
         0.1, 0.3, 1.5,
         (0.0, 0.1), (0.45, 0.1)]

    cols = 3
    gs = matplotlib.gridspec.GridSpec(len(cases) // cols + 1, cols)

    r = np.linspace(0, 3.0, 200)
    theta = 2 * np.pi * r

    for i, case in enumerate(cases):
        row = (i // cols)
        col = i % cols
        plt.subplot(gs[row, col], polar = True)
        plt.title('markevery=%s' % str(case))
        plt.plot(theta, r, 'o', ls='-', ms=4,  markevery=case) 

def test_polar_wrap():
    D2R = np.pi / 180.0

    fig = plt.figure()

    plt.subplot(111, polar=True)

    plt.polar([179*D2R, -179*D2R], [0.2, 0.1], "b.-")
    plt.polar([179*D2R,  181*D2R], [0.2, 0.1], "g.-")
    plt.rgrids([0.05, 0.1, 0.15, 0.2, 0.25, 0.3])
    assert len(fig.axes) == 1, 'More than one polar axes created.'
    fig = plt.figure()

    plt.subplot(111, polar=True)
    plt.polar([2*D2R, -2*D2R], [0.2, 0.1], "b.-")
    plt.polar([2*D2R,  358*D2R], [0.2, 0.1], "g.-")
    plt.polar([358*D2R,  2*D2R], [0.2, 0.1], "r.-")
    plt.rgrids([0.05, 0.1, 0.15, 0.2, 0.25, 0.3]) 

def test_polar_gridlines():
    fig = plt.figure()
    ax = fig.add_subplot(111, 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 animate(sync_output_dynamic, title=None, save_movie=None):
        """!
        @brief Shows animation of phase coordinates and animation of correlation matrix together for the Sync dynamic output on the same figure.
        
        @param[in] sync_output_dynamic (sync_dynamic): Output dynamic of the Sync network.
        @param[in] title (string): Title of the animation that is displayed on a figure if it is specified.
        @param[in] save_movie (string): If it is specified then animation will be stored to file that is specified in this parameter.
        
        """

        dynamic = sync_output_dynamic.output[0]
        correlation_matrix = sync_output_dynamic.allocate_correlation_matrix(0)

        figure = plt.figure(1)
        if title is not None:
            figure.suptitle(title, fontsize = 26, fontweight = 'bold')

        ax1 = figure.add_subplot(121, projection='polar')
        ax2 = figure.add_subplot(122)

        artist1, = ax1.plot(dynamic, [1.0] * len(dynamic), marker='o', color='blue', ls='')
        artist2 = ax2.imshow(correlation_matrix, cmap = plt.get_cmap('Accent'), interpolation='kaiser')

        def init_frame():
            return [artist1, artist2]

        def frame_generation(index_dynamic):
            dynamic = sync_output_dynamic.output[index_dynamic]
            artist1.set_data(dynamic, [1.0] * len(dynamic))

            correlation_matrix = sync_output_dynamic.allocate_correlation_matrix(index_dynamic)
            artist2.set_data(correlation_matrix)

            return [artist1, artist2]

        dynamic_animation = animation.FuncAnimation(figure, frame_generation, len(sync_output_dynamic), interval=75, init_func=init_frame, repeat_delay=5000)

        if save_movie is not None:
            dynamic_animation.save(save_movie, writer='ffmpeg', fps=15, bitrate=1500)
        else:
            plt.show() 

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(111, 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') 

def test_polar_coord_annotations():
    # You can also use polar notation on a catesian 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)
    from matplotlib.patches import Ellipse
    el = Ellipse((0, 0), 10, 20, facecolor='r', alpha=0.5)

    fig = plt.figure()
    ax = fig.add_subplot(111, 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) 

def test_polar_alignment():
    '''
    Test that changing the vertical/horizontal alignment of a polar graph
    works as expected '''
    ranges = [(0, 5), (0, 5)]

    angles = np.arange(0, 360, 90)

    levels = 5

    fig = plt.figure()

    figureSize = [0.1, 0.1, 0.8, 0.8]

    horizontal = fig.add_axes(figureSize, polar=True, label='horizontal')
    vertical = fig.add_axes(figureSize, polar=True, label='vertical')

    axes = [horizontal, vertical]

    horizontal.set_thetagrids(angles)

    vertical.patch.set_visible(False)

    for i in range(2):
        grid = np.linspace(*ranges[i], num=levels)
        gridValues = [0, 0.2, 0.4, 0.6, 0.8, 1]
        axes[i].set_rgrids(gridValues, angle=angles[i],
                           horizontalalignment='left',
                           verticalalignment='top') 

def test_polar_wrap():
    fig = plt.figure()
    plt.subplot(111, polar=True)
    plt.polar(np.deg2rad([179, -179]), [0.2, 0.1], "b.-")
    plt.polar(np.deg2rad([179,  181]), [0.2, 0.1], "g.-")
    plt.rgrids([0.05, 0.1, 0.15, 0.2, 0.25, 0.3])
    assert len(fig.axes) == 1, 'More than one polar axes created.'

    fig = plt.figure()
    plt.subplot(111, polar=True)
    plt.polar(np.deg2rad([2, -2]), [0.2, 0.1], "b.-")
    plt.polar(np.deg2rad([2, 358]), [0.2, 0.1], "g.-")
    plt.polar(np.deg2rad([358, 2]), [0.2, 0.1], "r.-")
    plt.rgrids([0.05, 0.1, 0.15, 0.2, 0.25, 0.3]) 

def test_polar_units():
    import matplotlib.testing.jpl_units as units
    units.register()

    pi = np.pi
    deg = units.deg
    km = units.km

    x1 = [pi/6.0, pi/4.0, pi/3.0, pi/2.0]
    x2 = [30.0*deg, 45.0*deg, 60.0*deg, 90.0*deg]

    y1 = [1.0, 2.0, 3.0, 4.0]
    y2 = [4.0, 3.0, 2.0, 1.0]

    fig = plt.figure()

    plt.polar(x2, y1, color="blue")

    # polar(x2, y1, color = "red", xunits="rad")
    # polar(x2, y2, color = "green")

    fig = plt.figure()

    # make sure runits and theta units work
    y1 = [y*km for y in y1]
    plt.polar(x2, y1, color="blue", thetaunits="rad", runits="km")
    assert isinstance(plt.gca().get_xaxis().get_major_formatter(),
                      units.UnitDblFormatter) 

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) 

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) 

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') 

def test_polar_rlabel_position():
    fig = plt.figure()
    ax = fig.add_subplot(111, projection='polar')
    ax.set_rlabel_position(315)
    ax.tick_params(rotation='auto') 

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, axes = 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 = axes[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') 

def test_polar_coord_annotations():
    # You can also use polar notation on a catesian 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)
    from matplotlib.patches import Ellipse
    el = Ellipse((0, 0), 10, 20, facecolor='r', alpha=0.5)

    fig = plt.figure()
    ax = fig.add_subplot(111, 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) 

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(111, 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') 

def test_polar_coord_annotations():
    # You can also use polar notation on a catesian 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)
    from matplotlib.patches import Ellipse
    el = Ellipse((0, 0), 10, 20, facecolor='r', alpha=0.5)

    fig = plt.figure()
    ax = fig.add_subplot(111, 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) 

def test_polar_alignment():
    '''
    Test that changing the vertical/horizontal alignment of a polar graph
    works as expected '''
    ranges = [(0, 5), (0, 5)]

    angles = np.arange(0, 360, 90)

    levels = 5

    fig = plt.figure()

    figureSize = [0.1, 0.1, 0.8, 0.8]

    horizontal = fig.add_axes(figureSize, polar=True, label='horizontal')
    vertical = fig.add_axes(figureSize, polar=True, label='vertical')

    axes = [horizontal, vertical]

    horizontal.set_thetagrids(angles)

    vertical.patch.set_visible(False)

    for i in range(2):
        grid = np.linspace(*ranges[i], num=levels)
        gridValues = [0, 0.2, 0.4, 0.6, 0.8, 1]
        axes[i].set_rgrids(gridValues, angle=angles[i],
                           horizontalalignment='left',
                           verticalalignment='top') 

def test_polar_wrap():
    fig = plt.figure()
    plt.subplot(111, polar=True)
    plt.polar(np.deg2rad([179, -179]), [0.2, 0.1], "b.-")
    plt.polar(np.deg2rad([179,  181]), [0.2, 0.1], "g.-")
    plt.rgrids([0.05, 0.1, 0.15, 0.2, 0.25, 0.3])
    assert len(fig.axes) == 1, 'More than one polar axes created.'

    fig = plt.figure()
    plt.subplot(111, polar=True)
    plt.polar(np.deg2rad([2, -2]), [0.2, 0.1], "b.-")
    plt.polar(np.deg2rad([2, 358]), [0.2, 0.1], "g.-")
    plt.polar(np.deg2rad([358, 2]), [0.2, 0.1], "r.-")
    plt.rgrids([0.05, 0.1, 0.15, 0.2, 0.25, 0.3]) 

def test_polar_units():
    import matplotlib.testing.jpl_units as units
    units.register()

    pi = np.pi
    deg = units.deg
    km = units.km

    x1 = [pi/6.0, pi/4.0, pi/3.0, pi/2.0]
    x2 = [30.0*deg, 45.0*deg, 60.0*deg, 90.0*deg]

    y1 = [1.0, 2.0, 3.0, 4.0]
    y2 = [4.0, 3.0, 2.0, 1.0]

    fig = plt.figure()

    plt.polar(x2, y1, color="blue")

    # polar(x2, y1, color = "red", xunits="rad")
    # polar(x2, y2, color = "green")

    fig = plt.figure()

    # make sure runits and theta units work
    y1 = [y*km for y in y1]
    plt.polar(x2, y1, color="blue", thetaunits="rad", runits="km")
    assert isinstance(plt.gca().get_xaxis().get_major_formatter(),
                      units.UnitDblFormatter) 

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) 

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) 

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') 

def test_polar_rlabel_position():
    fig = plt.figure()
    ax = fig.add_subplot(111, projection='polar')
    ax.set_rlabel_position(315)
    ax.tick_params(rotation='auto') 

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, axes = 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 = axes[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') 

def test_polar_gridlines():
    fig = plt.figure()
    ax = fig.add_subplot(111, 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_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) 

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(111, 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',
                )