Testing Class Material

hands_on_solutions/numerical_fuzzing/test_var.py

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+from math import isclose
+
+import numpy
+
+
+def test_var_deterministic():
+    x = numpy.array([-2.0, 2.0])
+    expected = 4.0
+    assert isclose(numpy.var(x), expected)
+
+
+def test_var_fuzzing():
+    rand_state = numpy.random.RandomState(8393)
+
+    N, D = 100000, 5
+    # Goal variances: [0.1 ,  0.45,  0.8 ,  1.15,  1.5]
+    expected = numpy.linspace(0.1, 1.5, D)
+
+    # Generate random, D-dimensional data
+    x = rand_state.randn(N, D) * numpy.sqrt(expected)
+    variance = numpy.var(x, axis=0)
+    numpy.testing.assert_allclose(variance, expected, rtol=1e-2)