214 lines
7.4 KiB
Python
214 lines
7.4 KiB
Python
import numpy as np
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import platform
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import matplotlib.pyplot as plt
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from matplotlib.path import Path
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from matplotlib.projections import PolarAxes
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from matplotlib.transforms import Affine2D, Transform
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from matplotlib.testing.decorators import image_comparison
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from mpl_toolkits.axes_grid1.parasite_axes import ParasiteAxes
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from mpl_toolkits.axisartist import SubplotHost
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from mpl_toolkits.axes_grid1.parasite_axes import host_subplot_class_factory
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from mpl_toolkits.axisartist import angle_helper
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from mpl_toolkits.axisartist.axislines import Axes
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from mpl_toolkits.axisartist.grid_helper_curvelinear import \
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GridHelperCurveLinear
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@image_comparison(['custom_transform.png'], style='default',
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tol=0.03 if platform.machine() == 'x86_64' else 0.04)
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def test_custom_transform():
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class MyTransform(Transform):
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input_dims = output_dims = 2
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def __init__(self, resolution):
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"""
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Resolution is the number of steps to interpolate between each input
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line segment to approximate its path in transformed space.
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"""
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Transform.__init__(self)
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self._resolution = resolution
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def transform(self, ll):
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x, y = ll.T
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return np.column_stack([x, y - x])
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transform_non_affine = transform
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def transform_path(self, path):
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ipath = path.interpolated(self._resolution)
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return Path(self.transform(ipath.vertices), ipath.codes)
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transform_path_non_affine = transform_path
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def inverted(self):
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return MyTransformInv(self._resolution)
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class MyTransformInv(Transform):
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input_dims = output_dims = 2
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def __init__(self, resolution):
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Transform.__init__(self)
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self._resolution = resolution
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def transform(self, ll):
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x, y = ll.T
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return np.column_stack([x, y + x])
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def inverted(self):
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return MyTransform(self._resolution)
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fig = plt.figure()
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SubplotHost = host_subplot_class_factory(Axes)
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tr = MyTransform(1)
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grid_helper = GridHelperCurveLinear(tr)
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ax1 = SubplotHost(fig, 1, 1, 1, grid_helper=grid_helper)
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fig.add_subplot(ax1)
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ax2 = ParasiteAxes(ax1, tr, viewlim_mode="equal")
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ax1.parasites.append(ax2)
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ax2.plot([3, 6], [5.0, 10.])
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ax1.set_aspect(1.)
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ax1.set_xlim(0, 10)
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ax1.set_ylim(0, 10)
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ax1.grid(True)
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@image_comparison(['polar_box.png'], style='default',
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tol={'aarch64': 0.04}.get(platform.machine(), 0.03))
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def test_polar_box():
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# Remove this line when this test image is regenerated.
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plt.rcParams['text.kerning_factor'] = 6
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fig = plt.figure(figsize=(5, 5))
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# PolarAxes.PolarTransform takes radian. However, we want our coordinate
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# system in degree
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tr = Affine2D().scale(np.pi / 180., 1.) + PolarAxes.PolarTransform()
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# polar projection, which involves cycle, and also has limits in
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# its coordinates, needs a special method to find the extremes
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# (min, max of the coordinate within the view).
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extreme_finder = angle_helper.ExtremeFinderCycle(20, 20,
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lon_cycle=360,
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lat_cycle=None,
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lon_minmax=None,
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lat_minmax=(0, np.inf))
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grid_locator1 = angle_helper.LocatorDMS(12)
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tick_formatter1 = angle_helper.FormatterDMS()
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grid_helper = GridHelperCurveLinear(tr,
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extreme_finder=extreme_finder,
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grid_locator1=grid_locator1,
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tick_formatter1=tick_formatter1)
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ax1 = SubplotHost(fig, 1, 1, 1, grid_helper=grid_helper)
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ax1.axis["right"].major_ticklabels.set_visible(True)
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ax1.axis["top"].major_ticklabels.set_visible(True)
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# let right axis shows ticklabels for 1st coordinate (angle)
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ax1.axis["right"].get_helper().nth_coord_ticks = 0
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# let bottom axis shows ticklabels for 2nd coordinate (radius)
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ax1.axis["bottom"].get_helper().nth_coord_ticks = 1
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fig.add_subplot(ax1)
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ax1.axis["lat"] = axis = grid_helper.new_floating_axis(0, 45, axes=ax1)
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axis.label.set_text("Test")
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axis.label.set_visible(True)
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axis.get_helper().set_extremes(2, 12)
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ax1.axis["lon"] = axis = grid_helper.new_floating_axis(1, 6, axes=ax1)
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axis.label.set_text("Test 2")
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axis.get_helper().set_extremes(-180, 90)
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# A parasite axes with given transform
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ax2 = ParasiteAxes(ax1, tr, viewlim_mode="equal")
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assert ax2.transData == tr + ax1.transData
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# Anything you draw in ax2 will match the ticks and grids of ax1.
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ax1.parasites.append(ax2)
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ax2.plot(np.linspace(0, 30, 50), np.linspace(10, 10, 50))
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ax1.set_aspect(1.)
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ax1.set_xlim(-5, 12)
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ax1.set_ylim(-5, 10)
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ax1.grid(True)
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@image_comparison(['axis_direction.png'], style='default', tol=0.03)
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def test_axis_direction():
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# Remove this line when this test image is regenerated.
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plt.rcParams['text.kerning_factor'] = 6
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fig = plt.figure(figsize=(5, 5))
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# PolarAxes.PolarTransform takes radian. However, we want our coordinate
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# system in degree
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tr = Affine2D().scale(np.pi / 180., 1.) + PolarAxes.PolarTransform()
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# polar projection, which involves cycle, and also has limits in
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# its coordinates, needs a special method to find the extremes
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# (min, max of the coordinate within the view).
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# 20, 20 : number of sampling points along x, y direction
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extreme_finder = angle_helper.ExtremeFinderCycle(20, 20,
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lon_cycle=360,
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lat_cycle=None,
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lon_minmax=None,
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lat_minmax=(0, np.inf),
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)
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grid_locator1 = angle_helper.LocatorDMS(12)
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tick_formatter1 = angle_helper.FormatterDMS()
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grid_helper = GridHelperCurveLinear(tr,
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extreme_finder=extreme_finder,
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grid_locator1=grid_locator1,
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tick_formatter1=tick_formatter1)
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ax1 = SubplotHost(fig, 1, 1, 1, grid_helper=grid_helper)
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for axis in ax1.axis.values():
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axis.set_visible(False)
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fig.add_subplot(ax1)
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ax1.axis["lat1"] = axis = grid_helper.new_floating_axis(
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0, 130,
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axes=ax1, axis_direction="left")
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axis.label.set_text("Test")
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axis.label.set_visible(True)
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axis.get_helper().set_extremes(0.001, 10)
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ax1.axis["lat2"] = axis = grid_helper.new_floating_axis(
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0, 50,
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axes=ax1, axis_direction="right")
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axis.label.set_text("Test")
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axis.label.set_visible(True)
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axis.get_helper().set_extremes(0.001, 10)
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ax1.axis["lon"] = axis = grid_helper.new_floating_axis(
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1, 10,
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axes=ax1, axis_direction="bottom")
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axis.label.set_text("Test 2")
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axis.get_helper().set_extremes(50, 130)
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axis.major_ticklabels.set_axis_direction("top")
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axis.label.set_axis_direction("top")
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grid_helper.grid_finder.grid_locator1.set_params(nbins=5)
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grid_helper.grid_finder.grid_locator2.set_params(nbins=5)
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ax1.set_aspect(1.)
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ax1.set_xlim(-8, 8)
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ax1.set_ylim(-4, 12)
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ax1.grid(True)
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