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Add two tests #4

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17c192c
Add two tests
Yiqing-Gu Mar 6, 2021
8b01234
Problem fixed
Yiqing-Gu Mar 18, 2021
1a07669
Adding timing function
Yiqing-Gu Mar 22, 2021
67c9c65
Adding reference and tutorial
Yiqing-Gu Mar 23, 2021
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105 changes: 105 additions & 0 deletions Tests/test_ConvexHull.py
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"""
Created on Sat Mar 6 13:42:53 2021

@author: ckielasjensen, Yiqing Gu
"""

from scipy.spatial import ConvexHull
from scipy.spatial import Delaunay

import random as random
import numpy as np
from polynomial.bernstein import Bernstein

# convex hull algorithm
def convexHullProperty(t1, t2, t3):

result = []

for cpts in [t1.cpts, t2.cpts, t3.cpts]:
hull = ConvexHull(cpts.T)
for simplex in hull.simplices:
result.append(cpts[0, simplex])
result.append(cpts[1, simplex])
return result

# checking whether point(s) is/are in convex hull
# reference: https://stackoverflow.com/questions/16750618/whats-an-efficient-way-to-find-if-a-point-lies-in-the-convex-hull-of-a-point-cl
def in_hull(points, hull):

if not isinstance(hull,Delaunay):
hull = Delaunay(hull)

result = hull.find_simplex(points)>=0
print(result)

assert result.all() == np.full((len(result),2), True, dtype = bool).all()


# test cases
def test_convexHull():

# test case 1 (fixed points)
critical_points1 = np.array([[0, 0, 5, 5],
[0, 3.3, 6.7, 10]], dtype=float)
critical_points2 = np.array([[5, 5, 10, 10],
[0, 3.3, 6.7, 10]], dtype=float)
critical_points3 = np.array([[10, 10, 0, 0],
[0, 4.4, 5.6, 10]], dtype=float)
trajectory1 = Bernstein(critical_points1, t0=0, tf=93)
trajectory2 = Bernstein(critical_points2, t0=0, tf=93)
trajectory3 = Bernstein(critical_points3, t0=0, tf=124)
testCase = convexHullProperty(trajectory1, trajectory2, trajectory3)
testPoints = np.array([(1,1), (2, 2)])

in_hull(testPoints, testCase)

#test case 2 (random points for checking, might cause error)
critical_points1 = np.array([[0, 0, 5, 5],
[0, 3.3, 6.7, 10]], dtype=float)
critical_points2 = np.array([[5, 5, 10, 10],
[0, 3.3, 6.7, 10]], dtype=float)
critical_points3 = np.array([[10, 10, 0, 0],
[0, 4.4, 5.6, 10]], dtype=float)
trajectory1 = Bernstein(critical_points1, t0=0, tf=93)
trajectory2 = Bernstein(critical_points2, t0=0, tf=93)
trajectory3 = Bernstein(critical_points3, t0=0, tf=124)
testCase = convexHullProperty(trajectory1, trajectory2, trajectory3)
testPoints = np.random.randint(0, 10, size=(10, 2))
print("Test points")
print(testPoints)

in_hull(testPoints, testCase)

#test case 3 (random points and random time interval, might cause error)
critical_points1 = np.array([[0, 0, 5, 5],
[0, 3.3, 6.7, 10]], dtype=float)
critical_points2 = np.array([[5, 5, 10, 10],
[0, 3.3, 6.7, 10]], dtype=float)
critical_points3 = np.array([[10, 10, 0, 0],
[0, 4.4, 5.6, 10]], dtype=float)
t_01=random.randint(0, 50)
t_f1=random.randint(55, 100)
t_02=random.randint(0, 50)
t_f2=random.randint(55, 100)
t_03=random.randint(0, 50)
t_f3=random.randint(55, 100)
trajectory1 = Bernstein(critical_points1, t0=t_01, tf=t_f1)
trajectory2 = Bernstein(critical_points2, t0=t_02, tf=t_f2)
trajectory3 = Bernstein(critical_points3, t0=t_03, tf=t_f3)
testCase = convexHullProperty(trajectory1, trajectory2, trajectory3)
testPoints = np.random.randint(0, 10, size=(20, 2))
print("Random time")
print("t_01 " + str(t_01) + " t_f1 " + str(t_f1))
print("t_02 " + str(t_02) + " t_f2 " + str(t_f2))
print("t_03 " + str(t_03) + " t_f3 " + str(t_f3))
print("Test points")
print(testPoints)

in_hull(testPoints, testCase)

if __name__ == '__main__':

#run tests
test_convexHull()

106 changes: 106 additions & 0 deletions Tests/test_EndPoint.py
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"""

@author: ckielasjensen, Yiqing Gu

"""

import numpy as np
import random as random
from polynomial.bernstein import Bernstein

# test for end points property
def endPointsProperty(t1, t2, t3):

result = []

# finding initial and final postions. Choosing a position to plot coordinates.
for i, pt in enumerate(np.concatenate([t1.cpts[:, (0, -1)].T, t2.cpts[:, (0, -1)].T, t3.cpts[:, (0, -1)].T])):
result.append(pt[0])
result.append(pt[1])
return result

def applyTests(figures, expectation):
assert figures == expectation

def test_endPoint():

# test case 1
critical_points1 = np.array([[0, 0, 5, 5],
[0, 3.3, 6.7, 10]], dtype=float)
critical_points2 = np.array([[5, 5, 10, 10],
[0, 3.3, 6.7, 10]], dtype=float)
critical_points3 = np.array([[10, 10, 0, 0],
[0, 4.4, 5.6, 10]], dtype=float)
trajectory1 = Bernstein(critical_points1, t0=0, tf=93)
trajectory2 = Bernstein(critical_points2, t0=0, tf=93)
trajectory3 = Bernstein(critical_points3, t0=0, tf=124)
expectedValue = [0.0, 0.0, 5.0, 10.0, 5.0, 0.0, 10.0, 10.0, 10.0, 0.0, 0.0, 10.0]
endPointsResult = endPointsProperty(trajectory1, trajectory2, trajectory3)
applyTests(endPointsResult, expectedValue)

# test case 2 (random time interval)
critical_points1 = np.array([[0, 0, 5, 5],
[0, 3.3, 6.7, 10]], dtype=float)
critical_points2 = np.array([[5, 5, 10, 10],
[0, 3.3, 6.7, 10]], dtype=float)
critical_points3 = np.array([[10, 10, 0, 0],
[0, 4.4, 5.6, 10]], dtype=float)
t_01=random.randint(0, 30)
t_f1=random.randint(40, 70)
t_02=random.randint(0, 30)
t_f2=random.randint(40, 70)
t_03=random.randint(0, 30)
t_f3=random.randint(40, 70)
trajectory1 = Bernstein(critical_points1, t0=t_01, tf=t_f1)
trajectory2 = Bernstein(critical_points2, t0=t_02, tf=t_f2)
trajectory3 = Bernstein(critical_points3, t0=t_03, tf=t_f3)
expectedValue = [0.0, 0.0, 5.0, 10.0, 5.0, 0.0, 10.0, 10.0, 10.0, 0.0, 0.0, 10.0]
endPointsResult = endPointsProperty(trajectory1, trajectory2, trajectory3)
applyTests(endPointsResult, expectedValue)
print("Random time")
print("t_01 " + str(t_01) + " t_f1 " + str(t_f1))
print("t_02 " + str(t_02) + " t_f2 " + str(t_f2))
print("t_03 " + str(t_03) + " t_f3 " + str(t_f3))

#test case 3 (different critical points)
critical_points1 = np.array([[0, 4, 6, 7],
[0, 5, 6, 8]], dtype=float)
critical_points2 = np.array([[2, 5, 8, 9],
[2, 5, 8, 10]], dtype=float)
critical_points3 = np.array([[10, 7, 4, 2],
[6, 4.4, 5.6, 10]], dtype=float)
trajectory1 = Bernstein(critical_points1, t0=0, tf=93)
trajectory2 = Bernstein(critical_points2, t0=0, tf=93)
trajectory3 = Bernstein(critical_points3, t0=0, tf=124)
expectedValue = [0.0, 0.0, 7.0, 8.0, 2.0, 2.0, 9.0, 10.0, 10.0, 6.0, 2.0, 10.0]
endPointsResult = endPointsProperty(trajectory1, trajectory2, trajectory3)
applyTests(endPointsResult, expectedValue)

#test case 4 (different critical points and time interval)
critical_points1 = np.array([[0, 1, 2, 3],
[0, 3, 6, 8]], dtype=float)
critical_points2 = np.array([[5, 6, 9, 9],
[0, 4, 8, 10]], dtype=float)
critical_points3 = np.array([[10, 10, 7, 4],
[0, 4, 7, 9]], dtype=float)
t_01=random.randint(0, 30)
t_f1=random.randint(40, 70)
t_02=random.randint(0, 30)
t_f2=random.randint(40, 70)
t_03=random.randint(0, 30)
t_f3=random.randint(40, 70)
trajectory1 = Bernstein(critical_points1, t0=t_01, tf=t_f1)
trajectory2 = Bernstein(critical_points2, t0=t_02, tf=t_f2)
trajectory3 = Bernstein(critical_points3, t0=t_03, tf=t_f3)
expectedValue = [0.0, 0.0, 3.0, 8.0, 5.0, 0.0, 9.0, 10.0, 10.0, 0.0, 4.0, 9.0]
endPointsResult = endPointsProperty(trajectory1, trajectory2, trajectory3)
applyTests(endPointsResult, expectedValue)
print("Random time")
print("t_01 " + str(t_01) + " t_f1 " + str(t_f1))
print("t_02 " + str(t_02) + " t_f2 " + str(t_f2))
print("t_03 " + str(t_03) + " t_f3 " + str(t_f3))

if __name__ == '__main__':

#run tests
test_endPoint()