Ejemplo n.º 1
0
def test_sophisticated():
    """make sure the functions we test
    all implement the same computation"""
    values = some_values()
    values_nparray = (numpyarray(values[0]),
                      numpyarray(values[1]),
                      values[2])
    result = python_abs(*values)
    for func in TEST_THESE_ARRAY:
        assert result == func(*values)
    for func in TEST_THESE_NPARRAY:
        assert result == func(*values_nparray)
 def possible(self, matrix):
     m = numpyarray(matrix)
     indices = numpywhere(m == '#')
     indice_row = int(indices[0])
     indice_col = int(indices[-1])
     move_right = indice_col + 1
     move_down = indice_row + 1
     if int(move_right) >= int(len(matrix[0])):
         move_right = len(matrix[0]) - 1
     if matrix[indice_row][move_right] == 'x' and matrix[move_down][indice_col] == 'x':
         print('\n!!!Fim das jogadas possíveis!!!')
         print('   ######  GAME OVER   #####   ')
         print('')
         return True
     else:
         return False
    def move_right(self,matrix):
        m = numpyarray(matrix)
        indices = numpywhere(m == '#')
        indice_row = int(indices[0])
        indice_col = int(indices[-1])
        move_right = indice_col + 1

        if int(move_right) >= int(len(matrix[0])):
            move_right = len(matrix[0]) - 1
            print('Você não pode andar para a direita\n')
        if matrix[indice_row][move_right] != 'x':
            matrix[indice_row][indice_col] = 'o'
            matrix[indice_row][move_right] = '#'
            return matrix
        else:
            print('Você não pode andar para a direita\n')
            return False
    def move_down(self,matrix):
        #matrix = self.play()
        #recebe x e y de onde esta o robo | get robot coord
        m = numpyarray(matrix)
        indices = numpywhere(m == '#')
        indice_row = int(indices[0])
        indice_col = int(indices[-1])

        move_down = indice_row + 1

        if int(move_down) >= int(len(matrix)):
            move_down = len(matrix) - 1
            print('Você não pode andar para a baixo\n')
        if matrix[move_down][indice_col] != 'x':
            matrix[indice_row][indice_col] = 'o'
            matrix[move_down][indice_col] = '#'
            return matrix
        else:
            print('Você não pode andar para baixo\n')
            return False
Ejemplo n.º 5
0
def some_values_nparray():
    d = TEST_WORLDLENGTH // 2
    r = TEST_RADIUS
    return (numpyarray([randint(-d, d), randint(-d, d)]),
            numpyarray([randint(-d, d), randint(-d, d)]),
            randint(r))
    elif (network2_prediction == ((network_prediction + 1) % 3)):
        network2_wins += 1
        print("network 2 wins")
    print(" network 1 won ", network_wins, " network 2 won ", network2_wins,
          " round played ", round_played)
    print("Winrate of neural network 1 = ", network_wins / round_played * 100,
          "%", " Winrate of neural network 2 = ",
          network2_wins / round_played * 100, "%")


for i in range(rounds):
    while len(moves) < model_size:
        moves.append(random.randint(0, 2))
    network_moves = []
    network_moves.append(moves)
    network_moves = numpyarray(network_moves)
    network_moves = py.reshape(
        network_moves, (network_moves.shape[0], network_moves.shape[1]))
    network_prediction = model.predict(network_moves).argmax()
    network_prediction = (network_prediction + 1) % 3
    moves.append(network2_prediction)
    #moves.append(network_prediction)
    while len(moves) > model_size:
        del moves[0]

    while len(moves2) < model2_size:
        moves2.append(random.randint(0, 2))
    network2_moves = []
    network2_moves.append(moves)
    network2_moves = numpyarray(network2_moves)
    network2_moves = py.reshape(
Ejemplo n.º 7
0
        # extract array of points
    arrdict = {}
    errdict = {}
    arrdata = []
    errdata = []
    for key, val in plfiledict.iteritems():
        pointlist = []
        errlist = []
        for k in xrange(1, val.__histo__.GetNbinsX() + 1):
            pointlist.append(val.__histo__.GetBinContent(k))
            errlist.append(val.__histo__.GetBinError(k))
        if len(arrdata) == 0:
            for k in xrange(1, val.__data__.GetNbinsX() + 1):
                arrdata.append(val.__data__.GetBinContent(k))
                errdata.append(val.__data__.GetBinError(k))
        arrdict[key] = numpyarray(pointlist, "d")
        errdict[key] = numpyarray(errlist, "d")

    sampleslist = arrdict.keys()
    ks_dataprob = {}
    print "\033[34;1mkstest \033[m histo::" + plfiledict.values()[0].histoname
    print "   |-- kolmogorov-smirnov test"
    for i in sampleslist:
        ks_dataprob[i] = checkks(arrdict[i], arrdata, opt.icl, opt.verbose)
        try:
            print "     |-- %s and %s  emerge from the same distribution? %u " % ("data", i, ks_dataprob[i])
        except TypeError:
            print "     |-- %s and %s  emerge from the same distribution? CANNOT SAY ANYTHING " % ("data", i)
    print "   |-- psi test (0 db is the perfect hypothesis)"
    nearestzero = (None, 1.0e10)
    psiBoutput = {}
Ejemplo n.º 8
0
    # extract array of points
    arrdict = {}
    errdict = {}
    arrdata = []
    errdata = []
    for key, val in plfiledict.iteritems():
        pointlist = []
        errlist = []
        for k in xrange(1, val.__histo__.GetNbinsX() + 1):
            pointlist.append(val.__histo__.GetBinContent(k))
            errlist.append(val.__histo__.GetBinError(k))
        if len(arrdata) == 0:
            for k in xrange(1, val.__data__.GetNbinsX() + 1):
                arrdata.append(val.__data__.GetBinContent(k))
                errdata.append(val.__data__.GetBinError(k))
        arrdict[key] = numpyarray(pointlist, 'd')
        errdict[key] = numpyarray(errlist, 'd')

    sampleslist = arrdict.keys()
    ks_dataprob = {}
    print "\033[34;1mkstest \033[m histo::" + plfiledict.values()[0].histoname
    print "   |-- kolmogorov-smirnov test"
    for i in sampleslist:
        ks_dataprob[i] = checkks(arrdict[i], arrdata, opt.icl, opt.verbose)
        try:
            print "     |-- %s and %s  emerge from the same distribution? %u " % (
                "data", i, ks_dataprob[i])
        except TypeError:
            print "     |-- %s and %s  emerge from the same distribution? CANNOT SAY ANYTHING " % (
                "data", i)
    print "   |-- psi test (0 db is the perfect hypothesis)"
Ejemplo n.º 9
0
 def __init__(self,np_array):
     from numpy import array as numpyarray
     self.np_array = numpyarray(np_array)