Python gen_random_by_seed Beispiele

Beispiel #1

Datei: mechanical_volume_assembler.py Projekt: epsilony/mf

'''


@author: [email protected]
'''


import numpy as np
import common_tools


all_nodes_size = 13
random_seed = 47
rand = common_tools.gen_random_by_seed(random_seed)

def gen_test_datas():    
    result = [gen_test_data(value_dimension) for value_dimension in [1, 1, 2, 2, 2, 3, 3, 3]]
    return result

def gen_test_data(value_dimension):
    data = {}
    data['allNodesSize'] = all_nodes_size
    data['valueDimension'] = value_dimension;
    data['weight'] = rand.random()
    data['load'] = common_tools.gen_vector(value_dimension, rand)
    data['constitutiveLaw'] = common_tools.gen_constitutive(value_dimension, rand)
    
    (assembly_indes, test_shape_function, trial_shape_function) = gen_test_trial_shape_function(value_dimension)
    data['testShapeFunction'] = test_shape_function
    data['trialShapeFunction'] = trial_shape_function
    data['assemblyIndes'] = assembly_indes

Beispiel #2

'''


@author: [email protected]
'''

import numpy as np
import common_tools

all_nodes_size = 13
random_seed = 47
rand = common_tools.gen_random_by_seed(random_seed)


def gen_test_datas():
    result = [
        gen_test_data(value_dimension)
        for value_dimension in [1, 1, 2, 2, 3, 3]
    ]
    return result


def gen_test_data(value_dimension):
    data = {}
    data['allNodesSize'] = all_nodes_size
    data['valueDimension'] = value_dimension
    data['weight'] = rand.random()
    data['load'] = common_tools.gen_vector(value_dimension, rand)

    shape_func_nodes_num = rand.randint(1, all_nodes_size // 2)
    test_shape_function = common_tools.gen_matrix((1, shape_func_nodes_num),