Repository: matplotlib/matplotlib
File: lib/mpl_toolkits/axisartist/tests/test_grid_helper_curvelinear.py (Python)

Code before:
    axis.get_helper().set_extremes(-180, 90)

    # A parasite axes with given transform
    ax2 = ax1.get_aux_axes(tr, viewlim_mode="equal")
    assert ax2.transData == tr + ax1.transData
    # Anything you draw in ax2 will match the ticks and grids of ax1.
    ax2.plot(np.linspace(0, 30, 50), np.linspace(10, 10, 50))

    ax1.set_aspect(1.)
    ax1.set_xlim(-5, 12)
    ax1.set_ylim(-5, 10)

    ax1.grid(True)


# Remove tol & kerning_factor when this test image is regenerated.
@image_comparison(['axis_direction.png'], style='default', tol=0.13)
def test_axis_direction():
    plt.rcParams['text.kerning_factor'] = 6

    fig = plt.figure(figsize=(5, 5))

    # PolarAxes.PolarTransform takes radian. However, we want our coordinate
    # system in degree
    tr = (Affine2D().scale(np.pi / 180., 1.) +
          PolarAxes.PolarTransform())

    # polar projection, which involves cycle, and also has limits in
    # its coordinates, needs a special method to find the extremes
    # (min, max of the coordinate within the view).

    # 20, 20 : number of sampling points along x, y direction
    extreme_finder = angle_helper.ExtremeFinderCycle(20, 20,
                                                     lon_cycle=360,
                                                     lat_cycle=None,
                                                     lon_minmax=None,
                                                     lat_minmax=(0, 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)

    for axis in ax1.axis.values():
        axis.set_visible(False)

Review comment (suggestion):
```suggestion
    tr = Affine2D().scale(np.pi / 180, 1) + PolarAxes.PolarTransform()
```

Code after:

    # A parasite axes with given transform
    ax2 = ax1.get_aux_axes(tr, viewlim_mode="equal")
    assert ax2.transData == tr + ax1.transData
    # Anything you draw in ax2 will match the ticks and grids of ax1.
    ax2.plot(np.linspace(0, 30, 50), np.linspace(10, 10, 50))

    ax1.set_aspect(1.)
    ax1.set_xlim(-5, 12)
    ax1.set_ylim(-5, 10)

    ax1.grid(True)


# Remove tol & kerning_factor when this test image is regenerated.
@image_comparison(['axis_direction.png'], style='default', tol=0.13)
def test_axis_direction():
    plt.rcParams['text.kerning_factor'] = 6

    fig = plt.figure(figsize=(5, 5))

    # PolarAxes.PolarTransform takes radian. However, we want our coordinate
    # system in degree
    tr = Affine2D().scale(np.pi / 180., 1.) + PolarAxes.PolarTransform()

    # polar projection, which involves cycle, and also has limits in
    # its coordinates, needs a special method to find the extremes
    # (min, max of the coordinate within the view).

    # 20, 20 : number of sampling points along x, y direction
    extreme_finder = angle_helper.ExtremeFinderCycle(20, 20,
                                                     lon_cycle=360,
                                                     lat_cycle=None,
                                                     lon_minmax=None,
                                                     lat_minmax=(0, 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)

    for axis in ax1.axis.values():
        axis.set_visible(False)

    fig.add_subplot(ax1)