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Localization calculation
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def localize(colors,measurements,motions,sensor_right,p_move): | |
# initializes p to a uniform distribution over a grid of the same dimensions as colors | |
def sense(p, colors, measurement): | |
aux = [[ 0.0 for row in range(len(p[0]))] for col in range(len(p))] | |
s = 0.0 | |
for i in range(len(p)): | |
for j in range(len(p[i])): | |
hit = (measurement == colors[i][j]) | |
aux[i][j] = p[i][j] * (hit * sensor_right + (1 - hit) * sensor_wrong) | |
s += aux[i][j] | |
for i in range(len(aux)): | |
for j in range(len(p[i])): | |
aux[i][j] /= s | |
return aux | |
def move(p, motion): | |
aux = [[ 0.0 for row in range(len(p[0]))] for col in range(len(p))] | |
for i in range(len(p)): | |
for j in range(len(p[i])): | |
aux[i][j] = (p_move * p[(i - motion[0]) % len(p)][j - motion[1] % len(p[i])]) + (p_stay * p[i][j]) | |
return aux | |
pinit = 1.0 / float(len(colors)) / float(len(colors[0])) | |
p = [[pinit for row in range(len(colors[0]))] for col in range(len(colors))] | |
sensor_wrong = 1.0 - sensor_right | |
p_stay = 1.0 - p_move | |
for k in range(len(measurements)): | |
p = move(p, motions[k]) | |
p = sense(p, colors, measurements[k]) | |
return p | |
def show(p): | |
rows = ['[' + ','.join(map(lambda x: '{0:.5f}'.format(x),r)) + ']' for r in p] | |
print '[' + ',\n '.join(rows) + ']' | |
############################################################# | |
# For the following test case, your output should be | |
# [[0.01105, 0.02464, 0.06799, 0.04472, 0.02465], | |
# [0.00715, 0.01017, 0.08696, 0.07988, 0.00935], | |
# [0.00739, 0.00894, 0.11272, 0.35350, 0.04065], | |
# [0.00910, 0.00715, 0.01434, 0.04313, 0.03642]] | |
# (within a tolerance of +/- 0.001 for each entry) | |
colors = [['R','G','G','R','R'], | |
['R','R','G','R','R'], | |
['R','R','G','G','R'], | |
['R','R','R','R','R']] | |
measurements = ['G','G','G','G','G'] | |
motions = [[0,0],[0,1],[1,0],[1,0],[0,1]] | |
p = localize(colors,measurements,motions,sensor_right = 0.7, p_move = 0.8) | |
show(p) # displays your answer |
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