45 lines
1.9 KiB
Python
45 lines
1.9 KiB
Python
###################################################################################################
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# Using bsearch(Binary Search) and hsearch(Hill Climbing Search) to find optimum
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###################################################################################################
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if get_device("image_stats") is None:
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run("camtool")
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image_stats.start()
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image_stats.setNumberOfImages(5)
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laser_off()
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image_stats.captureBackground(10)
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laser_on()
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image_stats.setNumberOfImages(5)
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image_stats.enableBackground
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(True)
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def before_sample():
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image_stats.update()
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class FitnessFunction(ReadonlyRegisterBase):
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def doRead(self):
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r = lscan(gun_solenoid, [image_stats.com_x_mean, image_stats.com_y_mean] , 110.0, 120.0, 1.0, 0.1, before_read = before_sample)
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bounding_area = abs(max(r.getReadable(0)) - min(r.getReadable(0))) * abs(max(r.getReadable(1)) - min(r.getReadable(1)))
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return bounding_area
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add_device(FitnessFunction("fitness"), True)
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"""
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#Binary Search
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strategy = "Normal" # or "Boundary" or "FullNeighborhood"
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r = bsearch([ao1, ao2], fitness, [0.0,0.0], [21.0,26.0], [0.1, 0.1], maximum=True, strategy = strategy, latency = 0.01, title = "Binary Search")
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print "--------------- Binary Search -----------------"
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print r
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print r.print()
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print len(r.getRecords())
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"""
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#Hill Climbing Search
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#r = hsearch([gsx, gsy, gsrx, gsry], fitness,[-1.0,-1.0,-1.0,-1.0], [1.0,1.0,1.0,1.0], [0.1, 0.1, 0.1, 0.1], [0.01, 0.01, 0.01, 0.01], 3, relative = False, maximum=False, latency = 0.01, title = "Hill Climbing")
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r = hsearch([gsx,gsy,gsrx, gsry], fitness,[-1.0,-1.0,-1.0,-1.0], [1.0,1.0,1.0,1.0], [0.1,0.1, 0.1, 0.1], [0.01,0.01,0.01, 0.01], 2, relative = False, maximum=False, latency = 0.01, title = "Hill Climbing")
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print "--------------- Hill Climbing Search -----------------"
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print r
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print r.print()
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print len(r.getRecords()) |