Python SubplotHost.set_aspect方法代码示例

# 需要导入模块: from mpl_toolkits.axes_grid.parasite_axes import SubplotHost [as 别名]
# 或者: from mpl_toolkits.axes_grid.parasite_axes.SubplotHost import set_aspect [as 别名]
def test_polar_box():
    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).
    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)

    ax1.axis["right"].major_ticklabels.set_visible(True)
    ax1.axis["top"].major_ticklabels.set_visible(True)

    # let right axis shows ticklabels for 1st coordinate (angle)
    ax1.axis["right"].get_helper().nth_coord_ticks = 0
    # let bottom axis shows ticklabels for 2nd coordinate (radius)
    ax1.axis["bottom"].get_helper().nth_coord_ticks = 1

    fig.add_subplot(ax1)

    ax1.axis["lat"] = axis = grid_helper.new_floating_axis(0, 45, axes=ax1)
    axis.label.set_text("Test")
    axis.label.set_visible(True)
    axis.get_helper()._extremes = 2, 12

    ax1.axis["lon"] = axis = grid_helper.new_floating_axis(1, 6, axes=ax1)
    axis.label.set_text("Test 2")
    axis.get_helper()._extremes = -180, 90

    # A parasite axes with given transform
    ax2 = ParasiteAxesAuxTrans(ax1, tr, "equal")
    assert ax2.transData == tr + ax1.transData
    # Anything you draw in ax2 will match the ticks and grids of ax1.
    ax1.parasites.append(ax2)
    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)

# 需要导入模块: from mpl_toolkits.axes_grid.parasite_axes import SubplotHost [as 别名]
# 或者: from mpl_toolkits.axes_grid.parasite_axes.SubplotHost import set_aspect [as 别名]
def curvelinear_test2(fig):
    """
    polar projection, but in a rectangular box.
    """
    global ax1
    import numpy as np
    import  mpl_toolkits.axes_grid.angle_helper as angle_helper
    from matplotlib.projections import PolarAxes
    from matplotlib.transforms import Affine2D

    from mpl_toolkits.axes_grid.parasite_axes import SubplotHost

    from mpl_toolkits.axes_grid.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 = 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)

    fig.add_subplot(ax1)

    # Now creates floating axis

    #grid_helper = ax1.get_grid_helper()
    # floating axis whose first coordinate (theta) is fixed at 60
    ax1.axis["lat"] = axis = ax1.new_floating_axis(0, 60)
    axis.label.set_text(r"$\theta = 60^{\circ}$")
    axis.label.set_visible(True)

    # floating axis whose second coordinate (r) is fixed at 6
    ax1.axis["lon"] = axis = ax1.new_floating_axis(1, 6)
    axis.label.set_text(r"$r = 6$")

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

    ax1.grid(True)

# 需要导入模块: from mpl_toolkits.axes_grid.parasite_axes import SubplotHost [as 别名]
# 或者: from mpl_toolkits.axes_grid.parasite_axes.SubplotHost import set_aspect [as 别名]
def setup_rot_axes(fig, rect):
	tr = Affine2D().rotate_deg(90.0)
	grid_helper = gh.GridHelperCurveLinear(tr)
	ax1 = SubplotHost(fig, rect, grid_helper=grid_helper)
	fig.add_subplot(ax1)
	ax2 = ParasiteAxesAuxTrans(ax1, tr, "equal")
	ax1.set_ylim([end, start])
	ax1.set_xlim([-8, 4])
	ax2 = ax1.get_aux_axes(tr)
	ax1.set_aspect('auto')
	ax1.axis['top', 'right', 'left', 'bottom'].set_visible(False)
	return ax1, ax2

# 需要导入模块: from mpl_toolkits.axes_grid.parasite_axes import SubplotHost [as 别名]
# 或者: from mpl_toolkits.axes_grid.parasite_axes.SubplotHost import set_aspect [as 别名]
def curvelinear_test3(fig):
    """
    polar projection, but in a rectangular box.
    """
    global ax1, axis
    import numpy as np
    from . import angle_helper
    from matplotlib.projections import PolarAxes
    from matplotlib.transforms import Affine2D

    from mpl_toolkits.axes_grid.parasite_axes import SubplotHost

    # 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)
    # Find a grid values appropriate for the coordinate (degree,
    # minute, second).

    tick_formatter1 = angle_helper.FormatterDMS()
    # And also uses an appropriate formatter.  Note that,the
    # acceptable Locator and Formatter class is a bit different than
    # that of mpl's, and you cannot directly use mpl's Locator and
    # Formatter here (but may be possible in the future).

    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 list(six.itervalues(ax1.axis)):
        axis.set_visible(False)

    fig.add_subplot(ax1)

    grid_helper = ax1.get_grid_helper()
    ax1.axis["lat1"] = axis = grid_helper.new_floating_axis(
        0, 130, axes=ax1, axis_direction="left")
    axis.label.set_text("Test")
    axis.label.set_visible(True)
    axis.get_helper()._extremes = 0.001, 10

    grid_helper = ax1.get_grid_helper()
    ax1.axis["lat2"] = axis = grid_helper.new_floating_axis(
        0, 50, axes=ax1, axis_direction="right")
    axis.label.set_text("Test")
    axis.label.set_visible(True)
    axis.get_helper()._extremes = 0.001, 10

    ax1.axis["lon"] = axis = grid_helper.new_floating_axis(
        1, 10, axes=ax1, axis_direction="bottom")
    axis.label.set_text("Test 2")
    axis.get_helper()._extremes = 50, 130
    axis.major_ticklabels.set_axis_direction("top")
    axis.label.set_axis_direction("top")

    grid_helper.grid_finder.grid_locator1.den = 5
    grid_helper.grid_finder.grid_locator2._nbins = 5

    #     # 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)
    #     intp = cbook.simple_linear_interpolation
    #     ax2.plot(intp(np.array([0, 30]), 50),
    #              intp(np.array([10., 10.]), 50))

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

    ax1.grid(True)

# 需要导入模块: from mpl_toolkits.axes_grid.parasite_axes import SubplotHost [as 别名]
# 或者: from mpl_toolkits.axes_grid.parasite_axes.SubplotHost import set_aspect [as 别名]
def test3():

    import numpy as np
    from matplotlib.transforms import Transform
    from matplotlib.path import Path

    class MyTransform(Transform):
        input_dims = 2
        output_dims = 2
        is_separable = False

        def __init__(self, resolution):
            """
            Create a new Aitoff transform.  Resolution is the number of steps
            to interpolate between each input line segment to approximate its
            path in curved Aitoff space.
            """
            Transform.__init__(self)
            self._resolution = resolution

        def transform(self, ll):
            x = ll[:, 0:1]
            y = ll[:, 1:2]

            return np.concatenate((x, y - x), 1)

        transform.__doc__ = Transform.transform.__doc__

        transform_non_affine = transform
        transform_non_affine.__doc__ = Transform.transform_non_affine.__doc__

        def transform_path(self, path):
            vertices = path.vertices
            ipath = path.interpolated(self._resolution)
            return Path(self.transform(ipath.vertices), ipath.codes)

        transform_path.__doc__ = Transform.transform_path.__doc__

        transform_path_non_affine = transform_path
        transform_path_non_affine.__doc__ = Transform.transform_path_non_affine.__doc__

        def inverted(self):
            return MyTransformInv(self._resolution)

        inverted.__doc__ = Transform.inverted.__doc__

    class MyTransformInv(Transform):
        input_dims = 2
        output_dims = 2
        is_separable = False

        def __init__(self, resolution):
            Transform.__init__(self)
            self._resolution = resolution

        def transform(self, ll):
            x = ll[:, 0:1]
            y = ll[:, 1:2]

            return np.concatenate((x, y + x), 1)

        transform.__doc__ = Transform.transform.__doc__

        def inverted(self):
            return MyTransform(self._resolution)

        inverted.__doc__ = Transform.inverted.__doc__

    import matplotlib.pyplot as plt
    fig = plt.figure(1)
    fig.clf()
    tr = MyTransform(1)
    grid_helper = GridHelperCurveLinear(tr)

    from mpl_toolkits.axes_grid1.parasite_axes import host_subplot_class_factory
    from .axislines import Axes

    SubplotHost = host_subplot_class_factory(Axes)

    ax1 = SubplotHost(fig, 1, 1, 1, grid_helper=grid_helper)

    fig.add_subplot(ax1)

    ax2 = ParasiteAxesAuxTrans(ax1, tr, "equal")
    ax1.parasites.append(ax2)
    ax2.plot([3, 6], [5.0, 10.])

    ax1.set_aspect(1.)
    ax1.set_xlim(0, 10)
    ax1.set_ylim(0, 10)

    ax1.grid(True)
    plt.draw()

# 需要导入模块: from mpl_toolkits.axes_grid.parasite_axes import SubplotHost [as 别名]
# 或者: from mpl_toolkits.axes_grid.parasite_axes.SubplotHost import set_aspect [as 别名]
def test_custom_transform():
    class MyTransform(Transform):
        input_dims = 2
        output_dims = 2
        is_separable = False

        def __init__(self, resolution):
            """
            Resolution is the number of steps to interpolate between each input
            line segment to approximate its path in transformed space.
            """
            Transform.__init__(self)
            self._resolution = resolution

        def transform(self, ll):
            x = ll[:, 0:1]
            y = ll[:, 1:2]

            return np.concatenate((x, y - x), 1)

        transform_non_affine = transform

        def transform_path(self, path):
            vertices = path.vertices
            ipath = path.interpolated(self._resolution)
            return Path(self.transform(ipath.vertices), ipath.codes)

        transform_path_non_affine = transform_path

        def inverted(self):
            return MyTransformInv(self._resolution)

    class MyTransformInv(Transform):
        input_dims = 2
        output_dims = 2
        is_separable = False

        def __init__(self, resolution):
            Transform.__init__(self)
            self._resolution = resolution

        def transform(self, ll):
            x = ll[:, 0:1]
            y = ll[:, 1:2]

            return np.concatenate((x, y+x), 1)

        def inverted(self):
            return MyTransform(self._resolution)

    fig = plt.figure()

    SubplotHost = host_subplot_class_factory(Axes)

    tr = MyTransform(1)
    grid_helper = GridHelperCurveLinear(tr)
    ax1 = SubplotHost(fig, 1, 1, 1, grid_helper=grid_helper)
    fig.add_subplot(ax1)

    ax2 = ParasiteAxesAuxTrans(ax1, tr, "equal")
    ax1.parasites.append(ax2)
    ax2.plot([3, 6], [5.0, 10.])

    ax1.set_aspect(1.)
    ax1.set_xlim(0, 10)
    ax1.set_ylim(0, 10)

    ax1.grid(True)

# 需要导入模块: from mpl_toolkits.axes_grid.parasite_axes import SubplotHost [as 别名]
# 或者: from mpl_toolkits.axes_grid.parasite_axes.SubplotHost import set_aspect [as 别名]
def test_axis_direction():
    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)

    ax1.axis["lat1"] = axis = grid_helper.new_floating_axis(
        0, 130,
        axes=ax1, axis_direction="left")
    axis.label.set_text("Test")
    axis.label.set_visible(True)
    axis.get_helper()._extremes = 0.001, 10

    ax1.axis["lat2"] = axis = grid_helper.new_floating_axis(
        0, 50,
        axes=ax1, axis_direction="right")
    axis.label.set_text("Test")
    axis.label.set_visible(True)
    axis.get_helper()._extremes = 0.001, 10

    ax1.axis["lon"] = axis = grid_helper.new_floating_axis(
        1, 10,
        axes=ax1, axis_direction="bottom")
    axis.label.set_text("Test 2")
    axis.get_helper()._extremes = 50, 130
    axis.major_ticklabels.set_axis_direction("top")
    axis.label.set_axis_direction("top")

    grid_helper.grid_finder.grid_locator1.den = 5
    grid_helper.grid_finder.grid_locator2._nbins = 5

    ax1.set_aspect(1.)
    ax1.set_xlim(-8, 8)
    ax1.set_ylim(-4, 12)

    ax1.grid(True)

# 需要导入模块: from mpl_toolkits.axes_grid.parasite_axes import SubplotHost [as 别名]
# 或者: from mpl_toolkits.axes_grid.parasite_axes.SubplotHost import set_aspect [as 别名]
def curvelinear_test2(fig):
    """
    polar projection, but in a rectangular box.
    """

    # 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)
    # Find a grid values appropriate for the coordinate (degree,
    # minute, second).

    tick_formatter1 = angle_helper.FormatterDMS()
    # And also uses an appropriate formatter.  Note that,the
    # acceptable Locator and Formatter class is a bit different than
    # that of mpl's, and you cannot directly use mpl's Locator and
    # Formatter here (but may be possible in the future).

    grid_helper = GridHelperCurveLinear(tr,
                                        extreme_finder=extreme_finder,
                                        grid_locator1=grid_locator1,
                                        tick_formatter1=tick_formatter1
                                        )


    ax1 = SubplotHost(fig, 1, 2, 2, grid_helper=grid_helper)

    # make ticklabels of right and top axis visible.
    ax1.axis["right"].major_ticklabels.set_visible(True)
    ax1.axis["top"].major_ticklabels.set_visible(True)

    # let right axis shows ticklabels for 1st coordinate (angle)
    ax1.axis["right"].get_helper().nth_coord_ticks=0
    # let bottom axis shows ticklabels for 2nd coordinate (radius)
    ax1.axis["bottom"].get_helper().nth_coord_ticks=1

    fig.add_subplot(ax1)


    # 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)
    intp = cbook.simple_linear_interpolation
    ax2.plot(intp(np.array([0, 30]), 50),
             intp(np.array([10., 10.]), 50))

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

    ax1.grid(True)