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rebuild docs with new discourse on front page
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‎3.1.1/_downloads/00157115776ca5e6a9574f992adbb8a7/demo_curvelinear_grid.py

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"""
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=====================
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Curvilinear grid demo
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=====================
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Custom grid and ticklines.
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This example demonstrates how to use
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`~.grid_helper_curvelinear.GridHelperCurveLinear` to define custom grids and
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ticklines by applying a transformation on the grid. This can be used, as
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shown on the second plot, to create polar projections in a rectangular box.
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"""
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import numpy as np
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import matplotlib.pyplot as plt
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from matplotlib.projections import PolarAxes
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from matplotlib.transforms import Affine2D
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from mpl_toolkits.axisartist import (
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angle_helper, Subplot, SubplotHost, ParasiteAxesAuxTrans)
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from mpl_toolkits.axisartist.grid_helper_curvelinear import (
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GridHelperCurveLinear)
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def curvelinear_test1(fig):
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"""
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Grid for custom transform.
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"""
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def tr(x, y):
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x, y = np.asarray(x), np.asarray(y)
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return x, y - x
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def inv_tr(x, y):
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x, y = np.asarray(x), np.asarray(y)
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return x, y + x
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grid_helper = GridHelperCurveLinear((tr, inv_tr))
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ax1 = Subplot(fig, 1, 2, 1, grid_helper=grid_helper)
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# ax1 will have a ticks and gridlines defined by the given
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# transform (+ transData of the Axes). Note that the transform of
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# the Axes itself (i.e., transData) is not affected by the given
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# transform.
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fig.add_subplot(ax1)
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xx, yy = tr([3, 6], [5, 10])
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ax1.plot(xx, yy, linewidth=2.0)
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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.axis["t"] = ax1.new_floating_axis(0, 3)
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ax1.axis["t2"] = ax1.new_floating_axis(1, 7)
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ax1.grid(True, zorder=0)
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def curvelinear_test2(fig):
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"""
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Polar projection, but in a rectangular box.
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"""
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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(
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nx=20, ny=20, # Number of sampling points in each direction.
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lon_cycle=360, lat_cycle=None,
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lon_minmax=None, lat_minmax=(0, np.inf),
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)
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# Find grid values appropriate for the coordinate (degree, minute, second).
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grid_locator1 = angle_helper.LocatorDMS(12)
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# Use an appropriate formatter. Note that the acceptable Locator and
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# Formatter classes are a bit different than that of Matplotlib, which
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# cannot directly be used here (this may be possible in the future).
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tick_formatter1 = angle_helper.FormatterDMS()
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grid_helper = GridHelperCurveLinear(
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tr, extreme_finder=extreme_finder,
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grid_locator1=grid_locator1, tick_formatter1=tick_formatter1)
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ax1 = SubplotHost(fig, 1, 2, 2, grid_helper=grid_helper)
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# make ticklabels of right and top axis visible.
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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.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, zorder=0)
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# A parasite axes with given transform
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ax2 = ParasiteAxesAuxTrans(ax1, tr, "equal")
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# note that 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, 51), np.linspace(10, 10, 51), linewidth=2)
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if __name__ == "__main__":
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fig = plt.figure(figsize=(7, 4))
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curvelinear_test1(fig)
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curvelinear_test2(fig)
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plt.show()

‎3.1.1/_downloads/0035868b7cf7fcb6c06f2b024e2ac642/polygon_selector_demo.py

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"""
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=====================
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Polygon Selector Demo
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=====================
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Shows how one can select indices of a polygon interactively.
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"""
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import numpy as np
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from matplotlib.widgets import PolygonSelector
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from matplotlib.path import Path
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class SelectFromCollection(object):
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"""Select indices from a matplotlib collection using `PolygonSelector`.
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Selected indices are saved in the `ind` attribute. This tool fades out the
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points that are not part of the selection (i.e., reduces their alpha
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values). If your collection has alpha < 1, this tool will permanently
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alter the alpha values.
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Note that this tool selects collection objects based on their *origins*
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(i.e., `offsets`).
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Parameters
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----------
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ax : :class:`~matplotlib.axes.Axes`
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Axes to interact with.
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collection : :class:`matplotlib.collections.Collection` subclass
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Collection you want to select from.
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alpha_other : 0 <= float <= 1
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To highlight a selection, this tool sets all selected points to an
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alpha value of 1 and non-selected points to `alpha_other`.
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"""
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def __init__(self, ax, collection, alpha_other=0.3):
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self.canvas = ax.figure.canvas
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self.collection = collection
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self.alpha_other = alpha_other
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self.xys = collection.get_offsets()
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self.Npts = len(self.xys)
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# Ensure that we have separate colors for each object
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self.fc = collection.get_facecolors()
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if len(self.fc) == 0:
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raise ValueError('Collection must have a facecolor')
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elif len(self.fc) == 1:
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self.fc = np.tile(self.fc, (self.Npts, 1))
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self.poly = PolygonSelector(ax, self.onselect)
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self.ind = []
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def onselect(self, verts):
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path = Path(verts)
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self.ind = np.nonzero(path.contains_points(self.xys))[0]
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self.fc[:, -1] = self.alpha_other
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self.fc[self.ind, -1] = 1
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self.collection.set_facecolors(self.fc)
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self.canvas.draw_idle()
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def disconnect(self):
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self.poly.disconnect_events()
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self.fc[:, -1] = 1
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self.collection.set_facecolors(self.fc)
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self.canvas.draw_idle()
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if __name__ == '__main__':
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import matplotlib.pyplot as plt
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fig, ax = plt.subplots()
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grid_size = 5
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grid_x = np.tile(np.arange(grid_size), grid_size)
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grid_y = np.repeat(np.arange(grid_size), grid_size)
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pts = ax.scatter(grid_x, grid_y)
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selector = SelectFromCollection(ax, pts)
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print("Select points in the figure by enclosing them within a polygon.")
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print("Press the 'esc' key to start a new polygon.")
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print("Try holding the 'shift' key to move all of the vertices.")
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print("Try holding the 'ctrl' key to move a single vertex.")
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plt.show()
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selector.disconnect()
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# After figure is closed print the coordinates of the selected points
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print('\nSelected points:')
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print(selector.xys[selector.ind])

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