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Update: tests
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‎test/fit/eiv/__init__.py‎

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# Copyright (c) Brockmann Consult GmbH, 2026.
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# License: MIT

‎test/fit/eiv/test_eiv_jax.py‎

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# Copyright (c) Brockmann Consult GmbH, 2026.
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# License: MIT
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import unittest
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import numpy as np
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from uncertaintyx.fit.eiv.jax import EIV
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from uncertaintyx.m.jax import Linear
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from uncertaintyx.plot.plots import MatrixPlot
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from uncertaintyx.plot.plots import RegressionPlot
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class ErrorsInVariablesTest(unittest.TestCase):
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"""
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Tests EIV regression.
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"""
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def test_linear_model(self):
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"""
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Tests EIV regression by fitting a linear model to generated
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test data with known uncertainties of x and y.
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"""
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n = 100
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x = np.linspace(0.0, 100.0, n).reshape((n, 1))
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u = 1.0 + np.sqrt(x)
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rng = np.random.default_rng(42)
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y = x + rng.normal(0.0, u, (n, 1))
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x = x + rng.normal(0.0, u, (n, 1))
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result = EIV().fit(Linear(), x, y, ux=u, uy=u)
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self.assertEqual(0, result.info)
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self.assertAlmostEqual(1.0, result.popt[0], delta=0.05)
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self.assertAlmostEqual(0.0, result.popt[1], delta=1.00)
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self.assertAlmostEqual(0.0, result.punc[0], delta=0.05)
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self.assertAlmostEqual(0.0, result.punc[1], delta=1.00)
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self.assertAlmostEqual(0.0, result.pcov[0, 0], delta=0.001)
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self.assertAlmostEqual(0.0, result.pcov[0, 1], delta=0.015)
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self.assertAlmostEqual(0.0, result.pcov[1, 0], delta=0.015)
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self.assertAlmostEqual(0.0, result.pcov[1, 1], delta=1.000)
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result = EIV().fit(Linear(), x, y, ux=u, uy=u, covar=True)
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self.assertEqual(0, result.info)
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self.assertAlmostEqual(1.0, result.popt[0], delta=0.05)
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self.assertAlmostEqual(0.0, result.popt[1], delta=1.00)
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self.assertAlmostEqual(0.0, result.punc[0], delta=0.05)
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self.assertAlmostEqual(0.0, result.punc[1], delta=1.00)
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self.assertAlmostEqual(0.0, result.pcov[0, 0], delta=0.001)
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self.assertAlmostEqual(0.0, result.pcov[0, 1], delta=0.015)
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self.assertAlmostEqual(0.0, result.pcov[1, 0], delta=0.015)
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self.assertAlmostEqual(0.0, result.pcov[1, 1], delta=1.000)
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RegressionPlot(result).plot(
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x,
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y,
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xlabel=r"$x$",
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ylabel=r"$y$",
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xrange=(-10.0, 110.0),
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yrange=(-10.0, 110.0),
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savefig="eiv.png",
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title="Errors-in-variables regression",
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)
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MatrixPlot().plot(
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result.ycov_p(np.linspace(0.5, 99.5, n)),
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xlabel=r"$x$",
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ylabel=r"$x$",
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xrange=(0.5, 99.5),
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yrange=(0.5, 99.5),
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cbar_max=4.0,
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cbar_min=-1.0,
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cbar_label=r"variance-covariance $U_p(y)$",
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savefig="eiv-ycov.png",
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title="Errors-in-variables regression",
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)
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if __name__ == "__main__":
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unittest.main()

‎test/fit/eiv/test_eiv_numpy.py‎

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# Copyright (c) Brockmann Consult GmbH, 2026.
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# License: MIT
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import unittest
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import numpy as np
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from uncertaintyx.fit.eiv.numpy import EIV
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from uncertaintyx.m.jax import Linear
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from uncertaintyx.plot.plots import MatrixPlot
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from uncertaintyx.plot.plots import RegressionPlot
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class ErrorsInVariablesTest(unittest.TestCase):
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"""
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Tests EIV regression.
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"""
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def test_linear_model(self):
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"""
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Tests EIV regression by fitting a linear model to generated
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test data with known uncertainties of x and y.
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"""
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n = 100
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x = np.linspace(0.0, 100.0, n).reshape((n, 1))
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u = 1.0 + np.sqrt(x)
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rng = np.random.default_rng(42)
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y = x + rng.normal(0.0, u, (n, 1))
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x = x + rng.normal(0.0, u, (n, 1))
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result = EIV().fit(Linear(), x, y, ux=u, uy=u)
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self.assertEqual(0, result.info)
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self.assertAlmostEqual(1.0, result.popt[0], delta=0.05)
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self.assertAlmostEqual(0.0, result.popt[1], delta=1.00)
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self.assertAlmostEqual(0.0, result.punc[0], delta=0.05)
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self.assertAlmostEqual(0.0, result.punc[1], delta=1.00)
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self.assertAlmostEqual(0.0, result.pcov[0, 0], delta=0.001)
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self.assertAlmostEqual(0.0, result.pcov[0, 1], delta=0.015)
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self.assertAlmostEqual(0.0, result.pcov[1, 0], delta=0.015)
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self.assertAlmostEqual(0.0, result.pcov[1, 1], delta=1.000)
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RegressionPlot(result).plot(
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x,
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y,
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xlabel=r"$x$",
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ylabel=r"$y$",
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xrange=(-10.0, 110.0),
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yrange=(-10.0, 110.0),
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savefig="eiv.png",
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title="Errors-in-variables regression",
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)
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MatrixPlot().plot(
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result.ycov_p(np.linspace(0.5, 99.5, n)),
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xlabel=r"$x$",
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ylabel=r"$x$",
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xrange=(0.5, 99.5),
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yrange=(0.5, 99.5),
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cbar_max=4.0,
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cbar_min=-1.0,
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cbar_label=r"variance-covariance $U_p(y)$",
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savefig="eiv-ycov.png",
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title="Errors-in-variables regression",
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)
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if __name__ == "__main__":
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unittest.main()

‎test/fit/test_regression_jax.py‎

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Original file line numberDiff line numberDiff line change
@@ -38,10 +38,10 @@ def test_linear_model_homoscedastic(self):
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result = Bootstrap(HomoscedasticRegression(EIV())).fit(Linear(), x, y)
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self.assertEqual(0, result.info)
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self.assertAlmostEqual(1.0, result.popt[0], delta=0.1)
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self.assertAlmostEqual(0.0, result.popt[1], delta=5.0)
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self.assertAlmostEqual(0.0, result.punc[0], delta=0.1)
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self.assertAlmostEqual(0.0, result.punc[1], delta=5.0)
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self.assertAlmostEqual(1.0, result.popt[0], delta=0.10)
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self.assertAlmostEqual(0.0, result.popt[1], delta=5.00)
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self.assertAlmostEqual(0.0, result.punc[0], delta=0.05)
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self.assertAlmostEqual(0.0, result.punc[1], delta=1.50)
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print()
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print("popt = ", result.popt)
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)
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self.assertEqual(0, result.info)
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self.assertAlmostEqual(1.0, result.popt[0], delta=0.1)
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self.assertAlmostEqual(0.0, result.popt[1], delta=5.0)
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self.assertAlmostEqual(0.0, result.punc[0], delta=0.1)
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self.assertAlmostEqual(0.0, result.punc[1], delta=5.0)
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self.assertAlmostEqual(1.0, result.popt[0], delta=0.10)
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self.assertAlmostEqual(0.0, result.popt[1], delta=2.00)
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self.assertAlmostEqual(0.0, result.punc[0], delta=0.05)
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self.assertAlmostEqual(0.0, result.punc[1], delta=1.00)
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100100
print()
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print("popt = ", result.popt)
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146146
)
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148148
self.assertEqual(0, result.info)
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self.assertAlmostEqual(1.0, result.popt[0], delta=0.1)
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self.assertAlmostEqual(0.0, result.popt[1], delta=5.0)
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self.assertAlmostEqual(0.0, result.punc[0], delta=0.1)
152-
self.assertAlmostEqual(0.0, result.punc[1], delta=5.0)
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self.assertAlmostEqual(1.0, result.popt[0], delta=0.05)
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self.assertAlmostEqual(0.0, result.popt[1], delta=1.50)
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self.assertAlmostEqual(0.0, result.punc[0], delta=0.05)
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self.assertAlmostEqual(0.0, result.punc[1], delta=1.00)
153153

154154
print()
155155
print("popt = ", result.popt)
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201201
self.assertEqual(0, result.info)
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self.assertAlmostEqual(1.0, result.popt[0], delta=0.05)
203-
self.assertAlmostEqual(0.0, result.popt[1], delta=2.00)
204-
self.assertAlmostEqual(0.0, result.punc[0], delta=0.20)
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self.assertAlmostEqual(0.0, result.punc[1], delta=2.00)
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self.assertAlmostEqual(0.0, result.popt[1], delta=1.50)
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self.assertAlmostEqual(0.0, result.punc[0], delta=0.05)
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self.assertAlmostEqual(0.0, result.punc[1], delta=1.00)
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207207
print()
208208
print("popt = ", result.popt)

‎test/fit/test_regression_numpy.py‎

Lines changed: 15 additions & 15 deletions
Original file line numberDiff line numberDiff line change
@@ -38,10 +38,10 @@ def test_linear_model_homoscedastic(self):
3838
result = Bootstrap(HomoscedasticRegression(EIV())).fit(Linear(), x, y)
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4040
self.assertEqual(0, result.info)
41-
self.assertAlmostEqual(1.0, result.popt[0], delta=0.1)
42-
self.assertAlmostEqual(0.0, result.popt[1], delta=5.0)
43-
self.assertAlmostEqual(0.0, result.punc[0], delta=0.1)
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self.assertAlmostEqual(0.0, result.punc[1], delta=5.0)
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self.assertAlmostEqual(1.0, result.popt[0], delta=0.10)
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self.assertAlmostEqual(0.0, result.popt[1], delta=5.00)
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self.assertAlmostEqual(0.0, result.punc[0], delta=0.05)
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self.assertAlmostEqual(0.0, result.punc[1], delta=1.50)
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4646
print()
4747
print("popt = ", result.popt)
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9292
)
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9494
self.assertEqual(0, result.info)
95-
self.assertAlmostEqual(1.0, result.popt[0], delta=0.1)
96-
self.assertAlmostEqual(0.0, result.popt[1], delta=5.0)
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self.assertAlmostEqual(0.0, result.punc[0], delta=0.1)
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self.assertAlmostEqual(0.0, result.punc[1], delta=5.0)
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self.assertAlmostEqual(1.0, result.popt[0], delta=0.10)
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self.assertAlmostEqual(0.0, result.popt[1], delta=2.00)
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self.assertAlmostEqual(0.0, result.punc[0], delta=0.05)
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self.assertAlmostEqual(0.0, result.punc[1], delta=1.00)
9999

100100
print()
101101
print("popt = ", result.popt)
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146146
)
147147

148148
self.assertEqual(0, result.info)
149-
self.assertAlmostEqual(1.0, result.popt[0], delta=0.1)
150-
self.assertAlmostEqual(0.0, result.popt[1], delta=5.0)
151-
self.assertAlmostEqual(0.0, result.punc[0], delta=0.1)
152-
self.assertAlmostEqual(0.0, result.punc[1], delta=5.0)
149+
self.assertAlmostEqual(1.0, result.popt[0], delta=0.05)
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self.assertAlmostEqual(0.0, result.popt[1], delta=1.50)
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self.assertAlmostEqual(0.0, result.punc[0], delta=0.05)
152+
self.assertAlmostEqual(0.0, result.punc[1], delta=1.00)
153153

154154
print()
155155
print("popt = ", result.popt)
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201201
self.assertEqual(0, result.info)
202202
self.assertAlmostEqual(1.0, result.popt[0], delta=0.05)
203-
self.assertAlmostEqual(0.0, result.popt[1], delta=2.00)
204-
self.assertAlmostEqual(0.0, result.punc[0], delta=0.20)
205-
self.assertAlmostEqual(0.0, result.punc[1], delta=2.00)
203+
self.assertAlmostEqual(0.0, result.popt[1], delta=1.50)
204+
self.assertAlmostEqual(0.0, result.punc[0], delta=0.05)
205+
self.assertAlmostEqual(0.0, result.punc[1], delta=1.00)
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207207
print()
208208
print("popt = ", result.popt)

‎test/fit/test_regression_torch.py‎

Lines changed: 15 additions & 15 deletions
Original file line numberDiff line numberDiff line change
@@ -38,10 +38,10 @@ def test_linear_model_homoscedastic(self):
3838
result = Bootstrap(HomoscedasticRegression(EIV())).fit(Linear(), x, y)
3939

4040
self.assertEqual(0, result.info)
41-
self.assertAlmostEqual(1.0, result.popt[0], delta=0.1)
42-
self.assertAlmostEqual(0.0, result.popt[1], delta=5.0)
43-
self.assertAlmostEqual(0.0, result.punc[0], delta=0.1)
44-
self.assertAlmostEqual(0.0, result.punc[1], delta=5.0)
41+
self.assertAlmostEqual(1.0, result.popt[0], delta=0.10)
42+
self.assertAlmostEqual(0.0, result.popt[1], delta=5.00)
43+
self.assertAlmostEqual(0.0, result.punc[0], delta=0.05)
44+
self.assertAlmostEqual(0.0, result.punc[1], delta=1.50)
4545

4646
print()
4747
print("popt = ", result.popt)
@@ -92,10 +92,10 @@ def test_linear_model_homo_heteroscedastic(self):
9292
)
9393

9494
self.assertEqual(0, result.info)
95-
self.assertAlmostEqual(1.0, result.popt[0], delta=0.1)
96-
self.assertAlmostEqual(0.0, result.popt[1], delta=5.0)
97-
self.assertAlmostEqual(0.0, result.punc[0], delta=0.1)
98-
self.assertAlmostEqual(0.0, result.punc[1], delta=5.0)
95+
self.assertAlmostEqual(1.0, result.popt[0], delta=0.10)
96+
self.assertAlmostEqual(0.0, result.popt[1], delta=2.00)
97+
self.assertAlmostEqual(0.0, result.punc[0], delta=0.05)
98+
self.assertAlmostEqual(0.0, result.punc[1], delta=1.00)
9999

100100
print()
101101
print("popt = ", result.popt)
@@ -146,10 +146,10 @@ def test_linear_model_hetero_homoscedastic(self):
146146
)
147147

148148
self.assertEqual(0, result.info)
149-
self.assertAlmostEqual(1.0, result.popt[0], delta=0.1)
150-
self.assertAlmostEqual(0.0, result.popt[1], delta=5.0)
151-
self.assertAlmostEqual(0.0, result.punc[0], delta=0.1)
152-
self.assertAlmostEqual(0.0, result.punc[1], delta=5.0)
149+
self.assertAlmostEqual(1.0, result.popt[0], delta=0.05)
150+
self.assertAlmostEqual(0.0, result.popt[1], delta=1.50)
151+
self.assertAlmostEqual(0.0, result.punc[0], delta=0.05)
152+
self.assertAlmostEqual(0.0, result.punc[1], delta=1.00)
153153

154154
print()
155155
print("popt = ", result.popt)
@@ -200,9 +200,9 @@ def test_linear_model_heteroscedastic(self):
200200

201201
self.assertEqual(0, result.info)
202202
self.assertAlmostEqual(1.0, result.popt[0], delta=0.05)
203-
self.assertAlmostEqual(0.0, result.popt[1], delta=2.00)
204-
self.assertAlmostEqual(0.0, result.punc[0], delta=0.20)
205-
self.assertAlmostEqual(0.0, result.punc[1], delta=2.00)
203+
self.assertAlmostEqual(0.0, result.popt[1], delta=1.50)
204+
self.assertAlmostEqual(0.0, result.punc[0], delta=0.05)
205+
self.assertAlmostEqual(0.0, result.punc[1], delta=1.00)
206206

207207
print()
208208
print("popt = ", result.popt)

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