def test_curl():
x1, x2, x3 = symbols('x1 x2 x3')
X = [x1 * x2**3, x2 - cos(x3), x3**3 - x1]
arg = [x1, x2, x3]
j = Arraypy(3)
k0 = TensorArray(j, (1))
k0[0] = x1 * x2**3
k0[1] = x2 - cos(x3)
k0[2] = x3**3 - x1
k1 = Arraypy([1, 3, 1]).to_tensor(1)
k1[1] = x1 * x2**3
k1[2] = x2 - cos(x3)
k1[3] = x3**3 - x1
v0 = TensorArray(j, (1))
v0[0] = x1
v0[1] = x2
v0[2] = x3
v1 = Arraypy([1, 3, 1]).to_tensor(1)
v1[1] = x1
v1[2] = x2
v1[3] = x3
s0 = TensorArray(j, (1))
s0[0] = -sin(x3)
s0[1] = 1
s0[2] = -3 * x1 * x2**2
s1 = Arraypy([1, 3, 1]).to_tensor(1)
s1[1] = -sin(x3)
s1[2] = 1
s1[3] = -3 * x1 * x2**2
assert curl(X, arg) == [-sin(x3), 1, -3 * x1 * x2**2]
assert isinstance(curl(X, arg), list)
assert curl(X, arg, 'a') == list2arraypy([-sin(x3), 1, -3 * x1 * x2**2])
assert isinstance(curl(X, arg, 'a'), Arraypy)
assert curl(X, arg, 't') == s0
assert isinstance(curl(X, arg, 't'), TensorArray)
assert curl(X, arg, 't').type_pq == (1, 0)
assert curl(k0, arg) == s0
assert isinstance(curl(k0, arg), TensorArray)
assert curl(X, arg, 't').type_pq == (1, 0)
assert curl(k0, arg, 'a') == list2arraypy([-sin(x3), 1, -3 * x1 * x2**2])
assert isinstance(curl(k0, arg, 'a'), Arraypy)
assert curl(k0, arg, 't') == s0
assert isinstance(curl(k0, arg, 't'), TensorArray)
assert curl(X, arg, 't').type_pq == (1, 0)
assert curl(k1, v1, 't') == s1
assert isinstance(curl(k1, v1, 't'), TensorArray)
assert curl(k1, v1, 't').type_pq == (1, 0)
def test_df_var_tnsr0():
x1, x2, x3 = symbols('x1 x2 x3')
f = x1**2 * x2 + sin(x2 * x3 - x2)
var_tnsr0 = TensorArray(Arraypy(3), (1))
var_tnsr0[0] = x1
var_tnsr0[1] = x2
var_tnsr0[2] = x3
assert df(f, var_tnsr0) == [
2 * x1 * x2, x1**2 + (x3 - 1) * cos(x2 * x3 - x2), x2 *
cos(x2 * x3 - x2)]
assert isinstance(df(f, var_tnsr0), list)
assert df(f, var_tnsr0, 'l') == [
2 * x1 * x2, x1**2 + (x3 - 1) * cos(x2 * x3 - x2), x2 *
cos(x2 * x3 - x2)]
assert isinstance(df(f, var_tnsr0, 'l'), list)
assert df(f, var_tnsr0, 'a') == list2arraypy(
[2 * x1 * x2, x1**2 + (x3 - 1) * cos(x2 * x3 - x2), x2 *
cos(x2 * x3 - x2)])
assert isinstance(df(f, var_tnsr0, 'a'), Arraypy)
assert df(f, var_tnsr0, 't') == list2tensor(
[2 * x1 * x2, x1**2 + (x3 - 1) * cos(x2 * x3 - x2), x2 *
cos(x2 * x3 - x2)])
assert isinstance(df(f, var_tnsr0, 't'), TensorArray)
assert df(f, var_tnsr0, 't').type_pq == (0, 1)
def test_calculation():
# Arraypy
list_of_ones = [1 for i in range(9)]
list_of_nines = [9 for i in range(9)]
shape = (3, 3)
a = list2arraypy(list_of_ones, shape)
b = list2arraypy(list_of_nines, shape)
if sys.version_info[0] >= 3:
c = a + b
for i in c:
assert i == 10
c = b - a
for i in c:
assert i == 8
else:
c = a + b
idx = c.start_index
for i in range(len(c)):
assert c[idx] == 10
idx = c.next_index(idx)
idx = c.start_index
c = b - a
for i in range(len(c)):
assert c[idx] == 8
idx = c.next_index(idx)
# TensorArray
x0, x1, y0, y1 = symbols('X[0], X[1], Y[0], Y[1]')
tensor1 = TensorArray(Arraypy(2, 'X'), 1)
tensor2 = TensorArray(Arraypy(2, 'Y'), -1)
assert tensor1.rank == tensor2.rank == 1
res_tensor = tensor_product(tensor1, tensor2)
assert len(res_tensor) == 4
assert res_tensor.rank == 2
assert res_tensor[0, 0] == x0 * y0
assert res_tensor[0, 1] == x0 * y1
assert res_tensor[1, 0] == x1 * y0
assert res_tensor[1, 1] == x1 * y1
def test_iterator():
if sys.version_info[0] >= 3:
array = list2arraypy([0, 1, 2, 3], (2, 2))
j = 0
for i in array:
assert i == j
j += 1
array = array.reshape(4)
j = 0
for i in array:
assert i == j
j += 1
def test_equality():
first_list = [1, 2, 3, 4]
second_list = [1, 2, 3, 4]
third_list = [4, 3, 2, 1]
assert first_list == second_list
assert first_list != third_list
first_arraypy = list2arraypy(first_list, (2, 2))
second_arraypy = list2arraypy(second_list, (2, 2))
third_arraypy = list2arraypy(third_list, (2, 2))
fourth_arraypy = list2arraypy(first_list, 4)
assert first_arraypy == second_arraypy
second_arraypy[0, 0] = 0
assert first_arraypy != second_arraypy
assert first_arraypy != third_arraypy
assert first_arraypy != fourth_arraypy
first_tensor = list2tensor(first_list, (2, 2), (1, 1))
second_tensor = list2tensor(second_list, (2, 2), (1, 1))
third_tensor = list2tensor(second_list, (2, 2), (-1, 1))
assert first_tensor == second_tensor
assert first_tensor != third_tensor
def test_arraypy_converting():
arr_arraypy = list2arraypy([1, 2, 3, 4], (2, 2))
arr_list = arr_arraypy.to_list()
assert (isinstance(arr_list, list))
arr_tensor = arr_arraypy.to_tensor((1, -1))
assert (isinstance(arr_tensor, TensorArray))
arr_matrix = arr_arraypy.to_matrix()
assert (isinstance(arr_matrix, Matrix))
idx = (0, 0)
for i in range(len(arr_arraypy)):
assert arr_arraypy[idx] == arr_tensor[idx] == arr_matrix[idx]
idx = arr_arraypy.next_index(idx)
def test_converting_functions():
arr_list = [1, 2, 3, 4]
arr_matrix = Matrix(((1, 2), (3, 4)))
# list
arr_arraypy = list2arraypy(arr_list, (2, 2))
assert (isinstance(arr_arraypy, Arraypy))
arr_tensor = list2tensor(arr_list, (2, 2), (-1, -1))
assert (isinstance(arr_tensor, TensorArray))
# Matrix
arr_arraypy = matrix2arraypy(arr_matrix)
assert (isinstance(arr_arraypy, Arraypy))
arr_tensor = matrix2tensor(arr_matrix, (-1, -1))
assert (isinstance(arr_tensor, TensorArray))
def test_df_varlist():
x1, x2, x3 = symbols('x1 x2 x3')
f = x1**2 * x2 + sin(x2 * x3 - x2)
var_list = [x1, x2, x3]
assert df(f, var_list) == [
2 * x1 * x2, x1**2 + (x3 - 1) * cos(x2 * x3 - x2), x2 *
cos(x2 * x3 - x2)]
assert isinstance(df(f, var_list), list)
assert df(f, var_list, 'l') == [
2 * x1 * x2, x1**2 + (x3 - 1) * cos(x2 * x3 - x2), x2 *
cos(x2 * x3 - x2)]
assert isinstance(df(f, var_list, 'l'), list)
assert df(f, var_list, 'a') == list2arraypy(
[2 * x1 * x2, x1**2 + (x3 - 1) * cos(x2 * x3 - x2), x2 *
cos(x2 * x3 - x2)])
assert isinstance(df(f, var_list, 'a'), Arraypy)
assert df(f, var_list, 't') == list2tensor(
[2 * x1 * x2, x1**2 + (x3 - 1) * cos(x2 * x3 - x2), x2 *
cos(x2 * x3 - x2)])
assert isinstance(df(f, var_list, 't'), TensorArray)
assert df(f, var_list, 't').type_pq == (0, 1)
# -*- coding: utf-8 -*-
from tensor_analysis.arraypy import Arraypy, TensorArray, list2arraypy, \
list2tensor, matrix2arraypy, matrix2tensor
from tensor_analysis.tensor_methods import symmetric, asymmetric
from sympy import Symbol, symbols
arr = list2arraypy(list(range(9)), (3, 3))
# 0 1 2
# 3 4 5
# 6 7 8
def test_symmetric():
# Arraypy
sym_arr = symmetric(arr)
# 0.0 2.0 4.0
# 2.0 4.0 6.0
# 4.0 6.0 8.0
assert sym_arr[0, 1] == sym_arr[1, 0]
assert sym_arr[0, 2] == sym_arr[1, 1] == sym_arr[2, 0]
assert sym_arr[2, 1] == sym_arr[1, 2]
# TensorArray
tensor = arr.to_tensor((1, 1))
sym_tensor = asymmetric(tensor)
assert sym_tensor[0, 1] == -sym_tensor[1, 0]
assert sym_tensor[0, 2] == -sym_tensor[2, 0]
assert sym_tensor[2, 1] == -sym_tensor[1, 2]
