Create test_dense_to_func.py

pytest/test_dense_to_func.py

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+import pytest
+import numpy as np
+from dense_to_func import dense_to_func
+from GENetLib.create_basis import create_bspline_basis, create_expon_basis, create_fourier_basis, create_monomial_basis, create_power_basis
+
+
+def test_dense_to_func_bspline():
+    location = np.linspace(0, 1, 100)
+    X = np.sin(2 * np.pi * location) + np.random.normal(0, 0.1, size=(100, 1))
+    tofunc = dense_to_func(location.tolist(), X, "Bspline", 4, 3)
+    assert 'coefs' in tofunc
+
+def test_dense_to_func_exponential():
+    location = np.linspace(0, 2, 100)
+    X = np.exp(-location) + np.random.normal(0, 0.1, size=(100, 1))
+    tofunc = dense_to_func(location.tolist(), X, "Exponential", 3, [0.5])
+    assert 'coefs' in tofunc
+
+def test_dense_to_func_fourier():
+    location = np.linspace(0, 2 * np.pi, 100)
+    X = np.sin(location) + np.random.normal(0, 0.1, size=(100, 1))
+    tofunc = dense_to_func(location.tolist(), X, "Fourier", 4, 2 * np.pi)
+    assert 'coefs' in tofunc
+
+def test_dense_to_func_monomial():
+    location = np.linspace(0, 1, 100)
+    X = location**2 + np.random.normal(0, 0.1, size=(100, 1))
+    tofunc = dense_to_func(location.tolist(), X, "Monomial", 3, [2])
+    assert 'coefs' in tofunc
+
+def test_dense_to_func_power():
+    location = np.linspace(0, 1, 100)
+    X = location**2 + np.random.normal(0, 0.1, size=(100, 1))
+    tofunc = dense_to_func(location.tolist(), X, "Power", 3, [2])
+    assert 'coefs' in tofunc
+
+
+def test_dense_to_func_plot():
+    location = np.linspace(0, 1, 100)
+    X = np.sin(2 * np.pi * location) + np.random.normal(0, 0.1, size=(100, 1))
+    tofunc = dense_to_func(location.tolist(), X, "Bspline", 4, 3, Plot=True)
+    assert 'coefs' in tofunc
+
+
+def test_dense_to_func_errors():
+    location = np.linspace(0, 1, 100)
+    X = np.sin(2 * np.pi * location) + np.random.normal(0, 0.1, size=(100, 1))
+    with pytest.raises(ValueError):
+        dense_to_func(np.array(location), X, "Bspline", 4, 3)  # location should be of list type
+    with pytest.raises(ValueError):
+        dense_to_func(location.tolist(), X, "Unknown", 4, 3)  # Unknown basis type
+
+
+def test_dense_to_func_nan():
+    location = np.linspace(0, 1, 100)
+    X = np.sin(2 * np.pi * location) + np.random.normal(0, 0.1, size=(100, 1))
+    X[X < 0] = np.nan  # Introduce NaN values
+    tofunc = dense_to_func(location.tolist(), X, "Bspline", 4, 3)
+    assert 'coefs' in tofunc
+
+
+def test_dense_to_func_empty():
+    location = []
+    X = np.empty((0, 1))
+    with pytest.raises(ValueError):
+        dense_to_func(location, X, "Bspline", 4, 3)  # location cannot be empty