def gen_test_data(value_dimension, load_validity): data = {} data['allNodesSize'] = all_nodes_size data['allLagrangleNodesSize'] = all_lagrangle_nodes_size data['valueDimension'] = value_dimension data['weight'] = rand.random() data['load'] = common_tools.gen_vector(value_dimension, rand) data[ 'loadValidity'] = load_validity if None is not load_validity else common_tools.gen_vector( value_dimension, rand) >= 0.5 (assembly_indes, test_shape_function, trial_shape_function) = gen_test_trial_shape_function() data['testShapeFunction'] = test_shape_function data['trialShapeFunction'] = trial_shape_function data['assemblyIndes'] = assembly_indes (lagrangle_assemble_indes, lagrangle_shape_function) = gen_lagrangle_shape_function() data['lagrangleShapeFunction'] = lagrangle_shape_function data['lagrangleAssemblyIndes'] = lagrangle_assemble_indes (main_matrix_difference, main_vector_difference) = assemble_lagrangle_dirichlet(data) data['mainMatrixDifference'] = main_matrix_difference data['mainVectorDifference'] = main_vector_difference return data
def gen_test_data(value_dimension,load_validity): data = {} data['allNodesSize'] = all_nodes_size data['valueDimension'] = value_dimension data['weight'] = rand.random() data['load'] = common_tools.gen_vector(value_dimension, rand) data['loadValidity'] = load_validity if None is not load_validity else common_tools.gen_vector(value_dimension, rand) >= 0.5 data['penalty']=rand.random() (assembly_indes, test_shape_function, trial_shape_function) = gen_test_trial_shape_function() data['testShapeFunction'] = test_shape_function data['trialShapeFunction'] = trial_shape_function data['assemblyIndes'] = assembly_indes (main_matrix_difference, main_vector_difference) = assemble_penality_dirichlet(data) data['mainMatrixDifference'] = main_matrix_difference data['mainVectorDifference'] = main_vector_difference return data
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), rand) nodes_assemble_indes = common_tools.gen_nodes_indes(shape_func_nodes_num, 0, all_nodes_size, rand) data['testShapeFunction'] = test_shape_function data['assemblyIndes'] = nodes_assemble_indes whole_test_shape_function_vector = common_tools.shape_func_to_whole_vector(test_shape_function, nodes_assemble_indes, all_nodes_size) data['mainVectorDifference'] = assemble_general_force(data['weight'], data['load'], whole_test_shape_function_vector) return data
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 (main_matrix_difference, main_vector_difference) = assemble_mechanical_volume(data) data['mainMatrixDifference'] = main_matrix_difference data['mainVectorDifference'] = main_vector_difference return data
def gen_test_data(value_dimension): data = {} data['allNodesSize'] = all_nodes_size data['valueDimension'] = 1 data['spatialDimension'] = value_dimension data['weight'] = rand.random() data['load'] = common_tools.gen_vector(1, 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 (main_matrix_difference, main_vector_difference) = assemble_poisson_volume(data) data['mainMatrixDifference'] = main_matrix_difference data['mainVectorDifference'] = main_vector_difference return data
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), rand) nodes_assemble_indes = common_tools.gen_nodes_indes( shape_func_nodes_num, 0, all_nodes_size, rand) data['testShapeFunction'] = test_shape_function data['assemblyIndes'] = nodes_assemble_indes whole_test_shape_function_vector = common_tools.shape_func_to_whole_vector( test_shape_function, nodes_assemble_indes, all_nodes_size) data['mainVectorDifference'] = assemble_general_force( data['weight'], data['load'], whole_test_shape_function_vector) return data