Disabled external gits

cs457-gc/assignment_1_2/test/test2.py

@@ -0,0 +1,87 @@
+# import pytest
+import time
+import pytest
+import json
+import sys
+import igl
+import numpy as np
+sys.path.append('../')
+sys.path.append('../src')
+from src.energies import *
+eps = 1E-6
+
+with open('test_data2.json', 'r') as infile:
+    homework_datas = json.load(infile)
+
+# @pytest.mark.timeout(1)
+@pytest.mark.parametrize("data", homework_datas[0])
+def test_shape_energy_correctness(data):
+    V = np.array(data[0], dtype=float)
+    E = np.array(data[1], dtype=int)
+    l0 = np.array(data[2], dtype=float)
+    shape_energy_ground_truth = np.array(data[3])
+    shape_energy_student = compute_shape_energy(V, E, l0)
+    assert np.linalg.norm(shape_energy_ground_truth - shape_energy_student) < eps
+
+# @pytest.mark.timeout(1)
+@pytest.mark.parametrize("data", homework_datas[1])
+def test_equilibrium_engery_correctness(data):
+    V = np.array(data[0], dtype=float)
+    F = np.array(data[1], dtype=int)
+    x_csl = data[2]
+    equilibrium_engery_ground_truth = np.array(data[3])
+    equilibrium_engery_student = compute_equilibrium_energy(V, F, x_csl)
+    assert np.linalg.norm(equilibrium_engery_ground_truth - equilibrium_engery_student) < eps
+
+@pytest.mark.timeout(1)
+@pytest.mark.parametrize("data", homework_datas[2])
+def test_faces_area_gradient_correctness(data):
+    V = np.array(data[0], dtype=float)
+    F = np.array(data[1], dtype=int)
+    faces_area_gradient_ground_truth_x = np.array(data[2])
+    faces_area_gradient_ground_truth_y = np.array(data[3])
+    [faces_area_gradient_student_x,  faces_area_gradient_student_y] = compute_faces_area_gradient(V, F)
+    assert np.linalg.norm(faces_area_gradient_ground_truth_x - faces_area_gradient_student_x) < eps \
+           and np.linalg.norm(faces_area_gradient_ground_truth_y - faces_area_gradient_student_y) < eps
+
+@pytest.mark.timeout(1)
+@pytest.mark.parametrize("data", homework_datas[3])
+def test_equilibrium_energy_gradient_correctness(data):
+    V = np.array(data[0], dtype=float)
+    F = np.array(data[1], dtype=int)
+    x_csl = data[2]
+    equilibrium_energy_gradient = np.array(data[3])
+    equilibrium_energy_student = compute_equilibrium_energy_gradient(V, F, x_csl)
+    assert np.linalg.norm(equilibrium_energy_gradient - equilibrium_energy_student) < eps
+
+@pytest.mark.timeout(1)
+@pytest.mark.parametrize("data", homework_datas[4])
+def test_shape_energy_gradient_correctness(data):
+    V = np.array(data[0], dtype=float)
+    E = np.array(data[1], dtype=int)
+    l0 = np.array(data[2], dtype=float)
+    shape_energy_gradient_ground_truth = np.array(data[3])
+    shape_energy_gradient_student = compute_shape_energy_gradient(V, E, l0)
+    assert np.linalg.norm(shape_energy_gradient_ground_truth - shape_energy_gradient_student) < eps
+
+n = 100000
+F_big = np.arange(3 * n).reshape((n, 3))
+V_big = np.random.random((3 * n, 3))
+l0_big = np.zeros(3 * n)
+E_big = igl.edges(F_big)
+
+@pytest.mark.timeout(1)
+def test_shape_energy_timing():
+    compute_shape_energy(V_big, E_big, l0_big)
+
+@pytest.mark.timeout(1)
+def test_faces_area_gradient_timing():
+    compute_faces_area_gradient(V_big, F_big)
+
+@pytest.mark.timeout(1)
+def test_equilibrium_energy_gradient_timing():
+    compute_equilibrium_energy_gradient(V_big, F_big, 0)
+
+@pytest.mark.timeout(1)
+def test_shape_energy_gradient_timing():
+    compute_shape_energy_gradient(V_big, E_big, l0_big)