forked from 170010011/fr
82 lines
2.6 KiB
Python
82 lines
2.6 KiB
Python
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# intersect.py
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#
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# Demonstrate how Shapely can be used to analyze and plot the intersection of
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# a trajectory and regions in space.
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from functools import partial
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import random
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import pylab
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from shapely.geometry import LineString, Point
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from shapely.ops import unary_union
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# Build patches as in dissolved.py
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r = partial(random.uniform, -20.0, 20.0)
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points = [Point(r(), r()) for i in range(100)]
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spots = [p.buffer(2.5) for p in points]
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patches = unary_union(spots)
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# Represent the following geolocation parameters
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#
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# initial position: -25, -25
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# heading: 45.0
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# speed: 50*sqrt(2)
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#
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# as a line
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vector = LineString(((-25.0, -25.0), (25.0, 25.0)))
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# Find intercepted and missed patches. List the former so we can count them
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# later
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intercepts = [patch for patch in patches.geoms if vector.intersects(patch)]
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misses = (patch for patch in patches.geoms if not vector.intersects(patch))
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# Plot the intersection
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intersection = vector.intersection(patches)
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assert intersection.geom_type in ['MultiLineString']
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if __name__ == "__main__":
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# Illustrate the results using matplotlib's pylab interface
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pylab.figure(num=None, figsize=(4, 4), dpi=180)
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# Plot the misses
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for spot in misses:
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x, y = spot.exterior.xy
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pylab.fill(x, y, color='#cccccc', aa=True)
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pylab.plot(x, y, color='#999999', aa=True, lw=1.0)
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# Do the same for the holes of the patch
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for hole in spot.interiors:
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x, y = hole.xy
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pylab.fill(x, y, color='#ffffff', aa=True)
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pylab.plot(x, y, color='#999999', aa=True, lw=1.0)
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# Plot the intercepts
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for spot in intercepts:
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x, y = spot.exterior.xy
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pylab.fill(x, y, color='red', alpha=0.25, aa=True)
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pylab.plot(x, y, color='red', alpha=0.5, aa=True, lw=1.0)
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# Do the same for the holes of the patch
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for hole in spot.interiors:
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x, y = hole.xy
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pylab.fill(x, y, color='#ffffff', aa=True)
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pylab.plot(x, y, color='red', alpha=0.5, aa=True, lw=1.0)
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# Draw the projected trajectory
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pylab.arrow(-25, -25, 50, 50, color='#999999', aa=True,
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head_width=1.0, head_length=1.0)
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for segment in intersection.geoms:
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x, y = segment.xy
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pylab.plot(x, y, color='red', aa=True, lw=1.5)
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# Write the number of patches and the total patch area to the figure
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pylab.text(-28, 25,
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"Patches: %d/%d (%d), total length: %.1f" \
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% (len(intercepts), len(patches.geoms),
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len(intersection.geoms), intersection.length))
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pylab.savefig('intersect.png')
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