Disabled external gits

cs457-gc/assignment_3_2/test/test.py

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+import time
+import pytest
+import json
+import sys
+import igl
+import numpy as np
+sys.path.append('../')
+sys.path.append('../src')
+
+
+import utils, laplacian_utils, mean_curvature_flow, remesher_helper
+from utils import parse_input_mesh, normalize_area, get_diverging_colors, remesh
+from mean_curvature_flow import MCF
+
+import copy
+import numpy.linalg as la
+
+import fitting 
+
+epsilon1 = 5e-2
+epsilon2 = 1e-3
+
+eps = 1E-6
+
+with open('test_data.json', 'r') as infile:
+    homework_data = json.load(infile)
+
+v = np.array(homework_data[0], dtype=float)
+f = np.array(homework_data[1], dtype=int)
+num_bdry_vx, num_intr_vx = int(homework_data[2]), int(homework_data[3])
+curr_mcf = MCF(num_bdry_vx, num_intr_vx)
+curr_mcf.bbox_diagonal = igl.bounding_box_diagonal(v)
+
+
+@pytest.mark.timeout(0.5)
+def test_mass_matrix():
+    student_mass_matrix = laplacian_utils.compute_mass_matrix(v, f).toarray()
+    assert np.linalg.norm(student_mass_matrix - np.array(homework_data[4], dtype=float)) < eps
+
+@pytest.mark.timeout(0.5)
+def test_cotan():
+    cotan, a, b, c, A = homework_data[5]
+    student_cotan = laplacian_utils.compute_cotangent(a, b, c, A)
+    assert np.linalg.norm(student_cotan - cotan) < eps
+
+@pytest.mark.timeout(0.5)
+def test_laplacian_matrix():
+    student_laplacian_matrix = laplacian_utils.compute_laplacian_matrix(v, f).toarray()
+    assert np.linalg.norm(student_laplacian_matrix - np.array(homework_data[6], dtype=float)) < eps
+
+@pytest.mark.timeout(0.5)
+def test_average_mean_curvature():
+    data = homework_data[7]
+    laplace_v = copy.deepcopy(v)
+    curr_mcf.update_system(laplace_v, f)
+    assert np.linalg.norm(curr_mcf.average_mean_curvature - data) < eps
+
+@pytest.mark.timeout(0.5)
+def test_laplace_solution():
+    data = homework_data[8]
+    laplace_v = copy.deepcopy(v)
+    curr_mcf.solve_laplace_equation(laplace_v, f)
+    assert np.linalg.norm(laplace_v - np.array(data, dtype=float)) < eps
+
+@pytest.mark.timeout(0.5)
+def test_meet_sc():
+    data = homework_data[9]
+    student_sc = [curr_mcf.meet_stopping_criteria([0.001, 0.001], epsilon1, epsilon2), curr_mcf.meet_stopping_criteria([1, 0.5], epsilon1, epsilon2)]
+
+    assert student_sc == data
+
+@pytest.mark.timeout(0.5)
+def test_mean_curvature_flow():
+    data = np.array(homework_data[10], dtype=float)
+    _, student_mean_curvature_flow = curr_mcf.run_mean_curvature_flow(v, f, 100, epsilon1, epsilon2)
+
+    assert np.linalg.norm(student_mean_curvature_flow - data) < eps
+
+@pytest.mark.timeout(0.5)
+def test_average_mean_curvature():
+    data = homework_data[7]
+    laplace_v = copy.deepcopy(v)
+    curr_mcf.update_system(laplace_v, f)
+    assert np.linalg.norm(curr_mcf.average_mean_curvature - data) < eps
+
+@pytest.mark.timeout(0.5)
+def test_laplace_solution():
+    data = homework_data[8]
+    laplace_v = copy.deepcopy(v)
+    curr_mcf.solve_laplace_equation(laplace_v, f)
+    assert np.linalg.norm(laplace_v - np.array(data, dtype=float)) < eps
+
+@pytest.mark.timeout(0.5)
+def test_meet_sc():
+    data = homework_data[9]
+    student_sc = [curr_mcf.meet_stopping_criteria([0.001, 0.001], epsilon1, epsilon2), curr_mcf.meet_stopping_criteria([1, 0.5], epsilon1, epsilon2)]
+
+    assert student_sc == data
+
+@pytest.mark.timeout(0.5)
+def test_mean_curvature_flow():
+    data = np.array(homework_data[10], dtype=float)
+    _, student_mean_curvature_flow = curr_mcf.run_mean_curvature_flow(v, f, 100, epsilon1, epsilon2)
+
+    assert np.linalg.norm(student_mean_curvature_flow - data) < eps
+
+
+fitting_v = np.array(homework_data[11], dtype=float)
+fitting_f = np.array(homework_data[12], dtype=int)
+
+@pytest.mark.timeout(0.5)
+def test_osculating_paraboloids():
+    [paraboloids_parameters, e1, e2, e3] = homework_data[13]
+    paraboloids_parameters = np.array(paraboloids_parameters)
+    e1 = np.array(e1)
+    e2 = np.array(e2)
+    e3 = np.array(e3)
+    student_paraboloids_parameters = fitting.compute_osculating_paraboloids(fitting_v, fitting_f, e1, e2, e3)
+    assert np.linalg.norm(student_paraboloids_parameters - paraboloids_parameters) < eps
+
+@pytest.mark.timeout(0.5)
+def test_osculating_paraboloid_first_derivatives():
+    [op_fd_x, op_fd_y, paraboloids_parameters] = homework_data[14]
+    op_fd_x = np.array(op_fd_x)
+    op_fd_y = np.array(op_fd_y)
+    paraboloids_parameters = np.array(paraboloids_parameters)
+    student_fd_x, student_fd_y = fitting.compute_osculating_paraboloid_first_derivatives(paraboloids_parameters)
+    assert np.linalg.norm(student_fd_x - op_fd_x) < eps
+    assert np.linalg.norm(student_fd_y - op_fd_y) < eps
+
+@pytest.mark.timeout(0.5)
+def test_osculating_paraboloid_second_derivatives():
+    [op_sd_xx, op_sd_xy, op_sd_yy, paraboloids_parameters] = homework_data[15]
+    op_sd_xx = np.array(op_sd_xx)
+    op_sd_xy = np.array(op_sd_xy)
+    op_sd_yy = np.array(op_sd_yy)
+    paraboloids_parameters = np.array(paraboloids_parameters)
+    student_sd_xx, student_sd_xy, student_sd_yy = fitting.compute_osculating_paraboloid_second_derivatives(paraboloids_parameters)
+
+    assert np.linalg.norm(student_sd_xx - op_sd_xx) < eps
+    assert np.linalg.norm(student_sd_xy - op_sd_xy) < eps
+    assert np.linalg.norm(student_sd_yy - op_sd_yy) < eps
+
+@pytest.mark.timeout(0.5)
+def test_mesh_principal_curvatures():
+    k1, k2, d1, d2 = homework_data[16]
+    k1 = np.array(k1)
+    k2 = np.array(k2)
+    d1 = np.array(d1)
+    d2 = np.array(d2)
+    student_k1, student_k2, student_d1, student_d2 = fitting.compute_mesh_principal_curvatures(fitting_v, fitting_f)
+    assert np.linalg.norm(k1 - student_k1) < eps
+    assert np.linalg.norm(k2 - student_k2) < eps
+    assert np.linalg.norm(d1 - student_d1) < eps
+    assert np.linalg.norm(d2 - student_d2) < eps

cs457-gc/assignment_3_2/test/test_data.json

@@ -0,0 +1 @@
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0.0, 0.0, 0.0], [0.0, -1.4142135623730951, 0.0, 0.0, 0.0, 0.7071067811865475, 0.7071067811865475, 0.0, 3.14018491736755e-16], [0.0, 0.0, -1.4142135623730951, 0.0, 0.7071067811865475, 0.0, 0.0, 0.7071067811865475, 3.14018491736755e-16], [0.0, 0.0, 0.0, -1.0000000000000002, 0.0, 0.0, 0.5000000000000001, 0.5000000000000001, 0.0], [0.5000000000000001, 0.0, 0.7071067811865475, 0.0, -2.138010440969447, 0.28867513459481287, 0.0, 0.0, 0.6422285251880866], [0.5000000000000001, 0.7071067811865475, 0.0, 0.0, 0.28867513459481287, -2.138010440969447, 0.0, 0.0, 0.6422285251880866], [0.0, 0.7071067811865475, 0.0, 0.5000000000000001, 0.0, 0.0, -2.1380104409694467, 0.28867513459481287, 0.6422285251880866], [0.0, 0.0, 0.7071067811865475, 0.5000000000000001, 0.0, 0.0, 0.28867513459481287, -2.138010440969447, 0.6422285251880866], [0.0, 3.14018491736755e-16, 3.14018491736755e-16, 0.0, 0.6422285251880866, 0.6422285251880866, 0.6422285251880866, 0.6422285251880866, -2.568914100752347]], 0.2816496580927726, [[-1.0, 0.0, 1.0], [1.0, 0.0, 1.0], [-1.0, 0.0, -1.0], [1.0, 0.0, -1.0], [-1.0, 0.0, 0.0], [0.0, 0.0, 1.0], [1.0, 0.0, 0.0], [0.0, 0.0, -1.0], [-0.0, -0.0, -0.0]], [true, false], [0.2816496580927726, 0.0], [[0.276388, 0.44722, 0.850649], [-0.723607, 0.44722, 0.525725], [-0.723607, 0.44722, -0.525725], [0.276388, 0.44722, -0.850649], [0.894426, 0.447216, 0.0], [0.688189, 0.525736, 0.499997], [-0.262869, 0.525738, 0.809012], [-0.850648, 0.525736, 0.0], [-0.262869, 0.525738, -0.809012], [0.688189, 0.525736, -0.499997], [0.0, 1.0, 0.0], [0.162456, 0.850654, 0.499995], [0.52573, 0.850652, 0.0], [-0.425323, 0.850654, 0.309011], [-0.425323, 0.850654, -0.309011], [0.162456, 0.850654, -0.499995]], [[8, 2, 14], [0, 5, 11], [15, 8, 14], [13, 6, 11], [6, 0, 11], [12, 9, 15], [2, 7, 14], [11, 5, 12], [11, 12, 10], [9, 3, 15], [14, 13, 10], [15, 14, 10], [4, 9, 12], [7, 1, 13], [13, 11, 10], [14, 7, 13], [12, 15, 10], [1, 6, 13], [3, 8, 15], [5, 4, 12]], [[[-0.6831148489909354, -0.674723891553982, 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-0.28108360189029Line truncated