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How to use initialize_b method in hypothesis

Best Python code snippet using hypothesis

HeatDiffusion.py

Source:HeatDiffusion.py

...16    lower[N-1] = 017    upper[0] = 018    return lower, diagonal, upper19# Initialization of boundary condition etc.20def initialize_b(T):21    h = 2 * L / N22    result = (-1*e*h**2) / D * np.ones((N, 1))23    result[0] = T24    result[N-1] = T25    return result26# Function to multiply a trigonal matrix and a vector27def trigonal_multiplication(lower, diagonal, upper, vector):28    result = np.zeros((N, 1))29    result[0] = diagonal[0] * vector[0]30    result[N-1] = diagonal[N-1] * vector[N-1]31    for i in range(1, N-1):32        result[i] = lower[i] * vector[i-1] + diagonal[i] * vector[i] + upper[i] * vector[i+1]33    return result34# Function that implements the forward-elimination, backward-substitution algorithm35def forward_elimination(lower, diagonal, upper, b):36    for i in range(0, N-2):37        if diagonal[i] > 0:38            m = (-1) * np.abs(lower[i+1]/diagonal[i])39        else:40            m = np.abs(lower[i + 1] / diagonal[i])41        lower[i+1] = lower[i+1] + m * diagonal[i]42        diagonal[i+1] = diagonal[i+1] + m * upper[i]43        b[i+1] = b[i+1] + m * b[i]44    return diagonal, b45# Function that implements the backward-substitution step46# The output vector contains the values for T_i47def backward_substitution(diagonal, b):48    result = np.zeros((N, 1))49    result[N-1] = b[N-1]50    result[0] = b[0]51    for i in range(2, N):52        result[N-i] = (b[N-i] - result[N-i+1])/diagonal[N-i]53    return result54# Function that implements a Jacobi iteration55def jacobi_step(lower, diagonal, upper, x, b):56    zero = np.zeros((N, 1))57    p = trigonal_multiplication(lower, zero, upper, x)58    x = trigonal_multiplication(zero, 1./diagonal, zero, b + p)59    return x60# Create array with spacing h and N points61def create_x_array():62    h = 2*L/N63    result = np.zeros((N, 1))64    for i in range(-int(np.floor(N/2)), int(np.floor(N/2))):65        result[int(np.floor(N/2)+i)] = h*i66    return result67# Function to run the full matrix algorithm68def run_matrix_algorithm():69    l, d, u = initialize_matrix(N)70    b = initialize_b(T_0)71    a, b = forward_elimination(l, d, u, b)72    y = backward_substitution(a, b)73    # Verify solution and calculate residual74    l, d, u = initialize_matrix(N)75    b = initialize_b(T_0)76    print('Residual:', trigonal_multiplication(l, d, u, y) - b)77    x = create_x_array()78    plt.plot(x, y, 'k--')79# Function to run the full jacobi algorithm80def run_jacobi_algorithm(steps):81    x = create_x_array()82    l, d, u = initialize_matrix(N)83    b = initialize_b(T_0)84    y = np.zeros((N, 1))85    for i in range(0, steps):86        y = jacobi_step((-1) * l, d, (-1) * u, y, b)87        plt.plot(x, y)88# Initializes the restriction matrices89def initialize_restriction_matrices():90    R1 = np.multiply((1/4), [[2.,1.,0,0,0,0,0,0,0],91                  [0,1.,2.,1.,0,0,0,0,0],92                  [0,0,0,1.,2.,1.,0,0,0],93                  [0,0,0,0,0,1.,2.,1.,0],94                  [0,0,0,0,0,0,0,1.,2.]])95    R2 = np.multiply((1/4), [[2.,1.,0,0,0],96                  [0,1.,2.,1.,0],97                  [0,0,0,1.,2.]])...

test_clusterInitializers.py

Source:test_clusterInitializers.py

1import unittest2import numpy as np3import os4import sys56from .context import cluster_initializers78# from bmdcluster.initializers.cluster_initializers import initialize_A9# from bmdcluster.initializers.cluster_initializers import initialize_B101112class Testinitialize_A(unittest.TestCase):1314    def setUp(self):15        self.n = 41617    def test_initialize_A_assertions(self):1819        with self.subTest('Check data_cluster size assertion'):20            # Check that assertion error raised when the number of data clusters is greater21            # than or equal to the size of the dataset.22            with self.assertRaises(AssertionError):23                cluster_initializers.initialize_A(n = self.n, n_clusters = self.n)24        25        with self.subTest('Check init_ratio assertions'):2627            # Check that assertion error is raised when the init_ratio is outside of28            # the interval (0,1].2930            with self.assertRaises(AssertionError):31                cluster_initializers.initialize_A(n = self.n, n_clusters = self.n - 1, init_ratio = 1.1)3233            with self.assertRaises(AssertionError):34                cluster_initializers.initialize_A(n = self.n, n_clusters = self.n - 1, init_ratio = 0)35363738    def test_initialize_A_outputs(self):3940        with self.subTest('Check sum of entries'):41            # When init_ratio not set, each point should be assigned exactly one cluster.42            # Check sum of elements of cluster assignment matrix A.43            A = cluster_initializers.initialize_A(self.n, self.n-1)44            self.assertEqual(A.sum(), self.n)45464748        with self.subTest('Check init_ratio'):49            # Check that when init_ratio is set, the number of assigned clusters is50            # the expected number.51            A = cluster_initializers.initialize_A(n = self.n, n_clusters = self.n - 1, init_ratio = 0.5)52            self.assertEqual(A.sum(), self.n // 2)53545556        with self.subTest('Check bootstrap list passing'):57            # Test passing of list of tuples containing the positions of entries58            # to be set in the returned matrix.5960            A_expected = np.array([[1,0],61                                   [0,0],62                                   [0,1],63                                   [0,0]])646566            A = cluster_initializers.initialize_A(n = self.n, n_clusters = 2, bootstrap = [(0,0),(2,1)])67            self.assertTrue(np.array_equal(A, A_expected))68697071class TestInitializeB(unittest.TestCase):7273    def setUp(self):74        self.m = 3757677    def test_initializeB_output(self):7879        with self.subTest('Check B_ident'):80            # Check feature cluster matrix B is initialized to identity when B_ident set to True.81            B = cluster_initializers.initialize_B(self.m, B_ident = True)82            self.assertTrue(np.array_equal(np.identity(self.m), B))8384    85    # def test_check_assertions(self):8687    #     with self.assertRaises(AssertionError):88    #         initialize_B(self.m, B_ident = False, f_clusters = self.m + 1)8990    #     with self.assertRaises(AssertionError):91    #         initialize_B(self.m, B_ident = False, f_clusters = 1)9293    #@unittest.skip("No longer using keyword arguments in initialize_B")94    def test_initializeB_assertions(self):9596        with self.subTest('Check missing keyword argument'):97            # Check that MissingKeywordArgument raised when B_ident set to False and98            # without additional keyword arguments.99            with self.assertRaises(KeyError):100                cluster_initializers.initialize_B(self.m, B_ident = False)101102        with self.subTest('Check assertions'):103            # Check that when f_clusters is passed, that AssertionError is raised104            # f_clusters is not in the interval (1, m].105106            with self.assertRaises(AssertionError):107                cluster_initializers.initialize_B(self.m, B_ident = False, f_clusters = self.m + 1)108109            with self.assertRaises(AssertionError):110                cluster_initializers.initialize_B(self.m, B_ident = False, f_clusters = 1)111112if __name__ == '__main__':
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Exercise3.3.py

Source:Exercise3.3.py

...35        A[i][i] = 536    return A373839def initialize_b(n):40    B = [1] * n41    B[0] = 342    B[-1] = 343    return B444546def find(a, b, x):47    norma = a[0][0] * x[0] + a[0][1] * x[1] - b[0]48    n = len(a)4950    for i in range(1, n):51        temp = 052        temp += a[i][i - 1] * x[i - 1] + a[i][i] * x[i]53        if i + 1 < n:54            temp += a[i][i + 1] * x[i + 1]5556        temp -= b[i]57        norma = max(abs(norma), abs(temp))5859    if abs(norma) >= 0.5e-4:60        return True61    else:62        return False636465def sumForCholesky(a, i, x0, xn):66    s = 067    if i - 1 >= 0:68        s += a[i][i-1] * xn[i-1]69    if i + 1 < len(a):70        s += a[i][i+1] * x0[i+1]71    return s727374def gauss_seidel(a, b):75    x0 = [0] * len(a)76    xn = [0] * len(a)77    flag = True78    counter = 07980    while flag:81        for i in range(0, len(a)):82            athrisma = sumForCholesky(a, i, x0, xn)83            xn[i] = (b[i] - athrisma) / a[i][i]84        counter += 185        flag = find(a, b, xn)86        for i in range(0, len(a)):87            x0[i] = xn[i]8889    print("Î§ÏÎµÎ¹Î¬ÏÏÎ·ÎºÎ±Î½", counter, "ÎÏÎ±Î½Î±Î»Î®ÏÎµÎ¹Ï ")90    return x0919293a10 = initialize_a(10)                          # ÎÏÏÎ¹ÎºÎ¿ÏÎ¿Î¹ÎµÎ¯ ÏÎ¿Î½ ÏÎ¯Î½Î±ÎºÎ± Î10 (10x10) ÏÏÎ¿Î¹ÏÎµÎ¯Î±94b10 = initialize_b(10)                          # ÎÏÏÎ¹ÎºÎ¿ÏÎ¿Î¹ÎµÎ¯ ÏÎ¿Î½ ÏÎ¯Î½Î±ÎºÎ± Î10 (10) ÏÏÎ¿Î¹ÏÎµÎ¯Î±95a10000 = initialize_a(10000)                    # ÎÏÏÎ¹ÎºÎ¿ÏÎ¿Î¹ÎµÎ¯ ÏÎ¿Î½ ÏÎ¯Î½Î±ÎºÎ± Î10000 (10000x10000)96b10000 = initialize_b(10000)9798print("ÎÎ¹Î± n=10 : ")99# printAB(a10, b10)                             # Î¤ÏÏÏÎ½ÎµÎ¹ ÏÎ¿Î½ ÎµÏÎ±ÏÎ¾Î·Î¼ÎÎ½Î¿ ÏÎ¯Î½Î±ÎºÎ±100x10 = gauss_seidel(a10, b10)                    # ÎÎ¬Î½ÎµÎ¹ Gauss_Seidel ÎºÎ±Î¹ ÎµÏÎ¹ÏÏÏÎÏÎµÎ¹ ÎÎ½Î±Î½ ÏÎ¯Î½Î±ÎºÎ± Î¼Îµ ÏÎ¹Ï ÏÎ¯Î¶ÎµÏ101# Î ÏÏÎ½Î¬ÏÏÎ·ÏÎ· Gauss_Seidel ÏÏÎ¹Î½ Î¿Î»Î¿ÎºÎ»Î·ÏÏÎ¸ÎµÎ¯ ÏÏÏÏÎ½ÎµÎ¹ ÏÎ¿Î½ Î±ÏÎ¹Î¸Î¼Ï ÏÏÎ½ ÎµÏÎ±Î½Î±Î»Î®ÏÎµÏÎ½ ÏÎ¿Ï ÏÏÎµÎ¹Î¬ÏÏÎ·ÎºÎ±Î½102print_result(x10)                               # ÏÏÏÏÎ½ÎµÎ¹ ÏÎ¿Î½ ÏÎ¯Î½Î±ÎºÎ± Î¼Îµ ÏÎ¹Ï ÏÎ¯Î¶ÎµÏ103104print("ÎÎ¹Î± n=10000 : ")105gauss_seidel(a10000, b10000)                    # Î Î±ÏÏÎ¼Î¿Î¹Î± Î¼Îµ ÎµÏÎ¬Î½Ï106# ÎµÎ´Ï Î´ÎµÎ½ ÏÏÏÏÎ½Î¿ÏÎ¼Îµ ÏÎ¿Î½ ÏÎ¯Î½Î±ÎºÎ± ÎºÎ±Î¸ÏÏ ÎµÎ¯Î½Î±Î¹ ÏÎ¿Î»Ï Î¼ÎµÎ³Î¬Î»Î¿Ï107108print()
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