51c9a8283e
I made a lot of changes so that each chapter makes clear that they are all implementing the same basic bayesian algorithm. This required a lot of editting, and it doesn't make sense to try to do that atomically, hence this huge check in. I made a lot of edits, and haven't copy editted anything. i'm sure I introduced a lot of problems and discontinuities.
45 lines
1.3 KiB
Python
45 lines
1.3 KiB
Python
# -*- coding: utf-8 -*-
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"""
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Created on Sun May 11 13:21:39 2014
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@author: rlabbe
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"""
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from __future__ import print_function, division
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from numpy.random import randn
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import math
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class DogSimulation(object):
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def __init__(self, x0=0, velocity=1,
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measurement_variance=0.0, process_variance=0.0):
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""" x0 - initial position
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velocity - (+=right, -=left)
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measurement_variance - variance in measurement m^2
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process_variance - variance in process (m/s)^2
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"""
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self.x = x0
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self.velocity = velocity
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self.measurement_noise = math.sqrt(measurement_variance)
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self.process_noise = math.sqrt(process_variance)
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def move(self, dt=1.0):
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'''Compute new position of the dog assuming `dt` seconds have
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passed since the last update.'''
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# compute new position based on velocity. Add in some
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# process noise
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velocity = self.velocity + randn() * self.process_noise
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self.x += velocity * dt
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def sense_position(self):
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# simulate measuring the position with noise
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measurement = self.x + randn() * self.measurement_noise
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return measurement
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def move_and_sense(self, dt=1.0):
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self.move(dt)
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return self.sense_position()
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