70 lines
1.9 KiB
Python
70 lines
1.9 KiB
Python
import numpy as np
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import matplotlib.pyplot as plt
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from sho import *
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def yonly_cover_sum(sol, domain_width, sensor_range, fixed_x = (10,30)):
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"""Compute the coverage quality of the given vector."""
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domain = np.zeros((domain_width,domain_width))
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sensors = [ (fixed_x[0], sol[0]), (fixed_x[1], sol[1]) ]
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return np.sum(pb.coverage(domain, sensors, sensor_range))
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if __name__ == "__main__":
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d = 2
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w = 40
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n = 2
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r = 0.3 * w
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# Common termination and checkpointing.
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history = []
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iters = make.iter(
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iters.several,
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agains = [
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make.iter(iters.max,
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nb_it = 100),
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make.iter(iters.log,
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fmt="\r{it} {val}"),
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make.iter(iters.history,
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history = history)
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]
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)
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x0,x1 = 0.25*w, 0.75*w
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val,sol = algo.greedy(
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make.func(yonly_cover_sum,
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domain_width = w,
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sensor_range = r,
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fixed_x = (x0,x1) ),
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make.init(num.rand,
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dim = 2, # Two sensors moving along y axis.
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scale = w),
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make.neig(num.neighb_square,
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scale = 0.1 * w,
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domain_width = w
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),
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iters
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)
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sensors = [ (int(x0), int(round(sol[0]))), (int(x1), int(round(sol[1]))) ]
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print("\n{} : {}".format(val,sensors))
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shape=(w,w)
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fig = plt.figure()
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ax1 = fig.add_subplot(121, projection='3d')
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ax2 = fig.add_subplot(122)
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f = make.func(yonly_cover_sum,
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domain_width = w,
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sensor_range = r)
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plot.surface(ax1, shape, f)
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plot.path(ax1, shape, history)
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domain = np.zeros(shape)
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domain = pb.coverage(domain, sensors, r)
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domain = plot.highlight_sensors(domain, sensors)
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ax2.imshow(domain)
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plt.show()
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