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Create TestEig class and add eigen tests #3

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6f64381
Create TestEig class and add eigen tests
StephenJasina Oct 23, 2020
13496b8
Rename test_eig to test_spec
StephenJasina Oct 23, 2020
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63 changes: 32 additions & 31 deletions test.py
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Original file line number Diff line number Diff line change
@@ -1,7 +1,7 @@
__author__ = 'cs540-testers'
__credits__ = ['Harrison Clark', 'Stephen Jasina', 'Saurabh Kulkarni',
'Alex Moon']
version = 'v0.2.2'
version = 'v0.3.0'

import sys
import unittest
Expand Down Expand Up @@ -46,8 +46,22 @@ def test_values(self):
# S should have non-negative values on the diagonal
self.assertTrue(np.min(np.diagonal(S)) >= 0)

class TestGetEig(unittest.TestCase):
def test_small(self):
class TestEig(unittest.TestCase):
def check_eigen(self, S, Lambda, U, m):
self.assertEqual(np.shape(Lambda), (m, m))
# Check that Lambda is diagonal
self.assertEqual(np.count_nonzero(
Lambda - np.diag(np.diagonal(Lambda))), 0)
# Check that Lambda is sorted in decreasing order
self.assertTrue(np.all(np.equal(np.diagonal(Lambda),
sorted(np.diagonal(Lambda), reverse=True))))

# The eigenvectors should be the columns
self.assertEqual(np.shape(U), (784, m))
self.assertTrue(np.all(np.isclose(S @ U, U @ Lambda)))

class TestGetEig(TestEig):
def test_spec(self):
x = load_and_center_dataset(mnist_path)
S = get_covariance(x)
Lambda, U = get_eig(S, 2)
Expand All @@ -60,25 +74,18 @@ def test_small(self):
self.assertEqual(np.shape(U), (784, 2))
self.assertTrue(np.all(np.isclose(S @ U, U @ Lambda)))

def test_large(self):
def test_larger(self):
x = load_and_center_dataset(mnist_path)
S = get_covariance(x)
Lambda, U = get_eig(S, 784)

self.assertEqual(np.shape(Lambda), (784, 784))
# Check that Lambda is diagonal
self.assertEqual(np.count_nonzero(
Lambda - np.diag(np.diagonal(Lambda))), 0)
# Check that Lambda is sorted in decreasing order
self.assertTrue(np.all(np.equal(np.diagonal(Lambda),
sorted(np.diagonal(Lambda), reverse=True))))
Lambda, U = get_eig(S, 20)
self.check_eigen(S, Lambda, U, 20)

# The eigenvectors should be the columns
self.assertEqual(np.shape(U), (784, 784))
self.assertTrue(np.all(np.isclose(S @ U, U @ Lambda)))
Lambda, U = get_eig(S, 784)
self.check_eigen(S, Lambda, U, 784)

class TestGetEigPerc(unittest.TestCase):
def test_small(self):
class TestGetEigPerc(TestEig):
def test_spec(self):
x = load_and_center_dataset(mnist_path)
S = get_covariance(x)
Lambda, U = get_eig_perc(S, .07)
Expand All @@ -91,26 +98,20 @@ def test_small(self):
self.assertEqual(np.shape(U), (784, 2))
self.assertTrue(np.all(np.isclose(S @ U, U @ Lambda)))

def test_large(self):
def test_larger(self):
x = load_and_center_dataset(mnist_path)
S = get_covariance(x)
# This will select all eigenvalues/eigenvectors
Lambda, U = get_eig_perc(S, -1)

self.assertEqual(np.shape(Lambda), (784, 784))
# Check that Lambda is diagonal
self.assertEqual(np.count_nonzero(
Lambda - np.diag(np.diagonal(Lambda))), 0)
# Check that Lambda is sorted in decreasing order
self.assertTrue(np.all(np.equal(np.diagonal(Lambda),
sorted(np.diagonal(Lambda), reverse=True))))
# A value of perc=0.011 should yield 20 eigenvectors
Lambda, U = get_eig_perc(S, 0.011)
self.check_eigen(S, Lambda, U, 20)

# The eigenvectors should be the columns
self.assertEqual(np.shape(U), (784, 784))
self.assertTrue(np.all(np.isclose(S @ U, U @ Lambda)))
# This will select all eigenvalues/eigenvectors
Lambda, U = get_eig_perc(S, -1)
self.check_eigen(S, Lambda, U, 784)

class TestProjectImage(unittest.TestCase):
def test_shape(self):
def test_spec(self):
x = load_and_center_dataset(mnist_path)
S = get_covariance(x)
_, U = get_eig(S, 2)
Expand Down