Localization Homework Tests

'''Test data as specified in the video, with ability to run tests

Created on Feb 23, 2012
I've input the data that was in the video (only about 12 decimals of precision)
for testing my code.  In addition, there is a very simplistic testing system
embedded within the file (I didn't use PyUnit so that it could be run in the
browser based interperter).  However, there is none of my solution at all here,
I just put in a simple hard-coded p array where my algorithm would go, which
in turn makes the first test pass.  Put your algorithm in place of this.

@author: tomkent
'''
colors = [['red', 'green', 'green', 'red' , 'red'],
          ['red', 'red', 'green', 'red', 'red'],
          ['red', 'red', 'green', 'green', 'red'],
          ['red', 'red', 'red', 'red', 'red']]

measurements = ['green', 'green', 'green' ,'green', 'green']


motions = [[0,0],[0,1],[1,0],[1,0],[0,1]]

sensor_right = 0.7

p_move = 0.8

def show(p):
    for i in range(len(p)):
        print p[i]

#DO NOT USE IMPORT
#ENTER CODE BELOW HERE
#ANY CODE ABOVE WILL CAUSE
#HOMEWORK TO BE GRADED
#INCORRECT

def test_vals1():
    colors = [['green','green','green'],
              ['green','red','green'],
              ['green','green','green']]
    measurements = ['red']
    motions = [[0,0]]
    sensor_right = 1.0
    p_move = 1.0
    p_expected = [[0,0,0],[0,1.0,0],[0,0,0]]
    return colors, measurements, motions, sensor_right, p_move, p_expected

def test_vals2():
    colors = [['green','green','green'],
              ['green','red','red'],
              ['green','green','green']]
    measurements = ['red']
    motions = [[0,0]]
    sensor_right = 1.0
    p_move = 1.0
    p_expected = [[0,0,0],[0,0.5,0.5],[0,0,0]]
    return colors, measurements, motions, sensor_right, p_move, p_expected

def test_vals3():
    colors = [['green','green','green'],
              ['green','red','red'],
              ['green','green','green']]
    measurements = ['red']
    motions = [[0,0]]
    sensor_right = 0.8
    p_move = 1.0
    p_expected = [[0.066666666666666,0.066666666666666,0.066666666666666],
                  [0.066666666666666,0.266666666666666,0.266666666666666],
                  [0.066666666666666,0.066666666666666,0.066666666666666]]
    return colors, measurements, motions, sensor_right, p_move, p_expected

def test_vals4():
    colors = [['green','green','green'],
              ['green','red','red'],
              ['green','green','green']]
    measurements = ['red','red']
    motions = [[0,0],[0,1]]
    sensor_right = 0.8
    p_move = 1.0
    p_expected = [[0.033333333333333,0.033333333333333,0.033333333333333],
                  [0.133333333333333,0.133333333333333,0.533333333333333],
                  [0.033333333333333,0.033333333333333,0.033333333333333]]
    return colors, measurements, motions, sensor_right, p_move, p_expected

def test_vals5():
    colors = [['green','green','green'],
              ['green','red','red'],
              ['green','green','green']]
    measurements = ['red','red']
    motions = [[0,0],[0,1]]
    sensor_right = 1.0
    p_move = 1.0
    p_expected = [[0,0,0],[0,0,1.0],[0,0,0]]
    return colors, measurements, motions, sensor_right, p_move, p_expected

def test_vals6():
    colors = [['green','green','green'],
              ['green','red','red'],
              ['green','green','green']]
    measurements = ['red','red']
    motions = [[0,0],[0,1]]
    sensor_right = 0.8
    p_move = 0.5
    p_expected = [[0.028985507246,0.028985507246,0.028985507246],
                  [0.072463768115,0.289855072463,0.463768115942],
                  [0.028985507246,0.028985507246,0.028985507246]]
    return colors, measurements, motions, sensor_right, p_move, p_expected

def test_vals7():
    colors = [['green','green','green'],
              ['green','red','red'],
              ['green','green','green']]
    measurements = ['red','red']
    motions = [[0,0],[0,1]]
    sensor_right = 1.0
    p_move = 0.5
    p_expected = [[0,0,0],
                  [0,0.333333333333,0.666666666666],
                  [0,0,0]]
    return colors, measurements, motions, sensor_right, p_move, p_expected

def test_vals8():
    colors = [['red','green','green','red','red'],
              ['red','red','green','red','red'],
              ['red','red','green','green','red'],
              ['red','red','red','red','red']]
    measurements = ['green','green','green','green','green']
    motions = [[0,0],[0,1],[1,0],[1,0],[0,1]]
    sensor_right = 0.7
    p_move = 0.8
    p_expected = [[0.011059807427,0.024640415784,0.067996628067,0.044724870458,0.024651531216],
                  [0.007153204183,0.010171326481,0.086965960026,0.079884299659,0.009350668508],
                  [0.007397366886,0.008943730670,0.112729646702,0.353507229552,0.040655492078],
                  [0.009106505805,0.007153204183,0.014349221618,0.043133291358,0.036425599329]]
    return colors, measurements, motions, sensor_right, p_move, p_expected

def run_test(colors, measurements, motions, sensor_right, p_move, p_expected):
    p = []
    p = my_algorithm(colors, measurements, motions, sensor_right, p_move, p)

    results = True
    for p_row, exp_row in zip(p,p_expected):
        for p_val, exp_val in zip(p_row,exp_row):
            if abs(p_val - exp_val) > 1e-8:
                results = False
# If you want to see individual failures and their expected values, uncomment
# the next line
#                print str(p_val) + " != " + str(exp_val)

# If you want to compare your results with the expected results for each failed
# test, uncomment the next five lines
#    if not results:
#        print "test p"
#        show(p)
#        print "test expected p"
#        show(p_expected)

    return results

def run_all_tests():
    results = []
    # The *(xxx) expands the resultant tuple into arguments
    results.append(run_test(*(test_vals1())))
    results.append(run_test(*(test_vals2())))
    results.append(run_test(*(test_vals3())))
    results.append(run_test(*(test_vals4())))
    results.append(run_test(*(test_vals5())))
    results.append(run_test(*(test_vals6())))
    results.append(run_test(*(test_vals7())))
    results.append(run_test(*(test_vals8())))
    print "Test results are: " + str(results)

def my_algorithm(colors, measurements, motions, sensor_right, p_move, p):
    '''The location of your code to solve the problem

    Put all your stuff in here, the algorithm below that hard-codes p (to pass
    test #1) is obviously too simple.
    '''
    # My algorithm here is obviously too simple
    p = [[0,0,0],[0,1.0,0],[0,0,0,]]

    # This is the important part of it all
    return p

# Continue with the code supplied by the instructor
p = []

################################################################################
# IMPORTANT...you need to un-comment the correct line...for testing your
# algorithm, select the run_all_tests() line.  For the code you actually want to
# submit, uncomment the #p = my_algorithm(co... line.
################################################################################
#run_all_tests()
#p = my_algorithm(colors, measurements, motions, sensor_right, p_move, p)

#Your probability array must be printed
#with the following code.

show(p)