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ENH: warnings in tests #21

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jankoslavic opened this issue Feb 28, 2025 · 0 comments
Open

ENH: warnings in tests #21

jankoslavic opened this issue Feb 28, 2025 · 0 comments
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@jankoslavic
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There are a few warning in the tests. @jasasonc would you be so kind and take a look if we can handle it without warnings?

=============================== warnings summary ===============================
tests/multiaxial_test.py::test_data
/home/runner/work/FLife/FLife/tests/../FLife/multiaxial/cplane.py:214: RuntimeWarning: invalid value encountered in divide
N1 = np.sqrt(spectral_moment(f, multiaxial_psd, 2) / l0) / (2*np.pi)

tests/multiaxial_test.py::test_data
/home/runner/work/FLife/FLife/tests/../FLife/multiaxial/cplane.py:214: RuntimeWarning: invalid value encountered in sqrt
N1 = np.sqrt(spectral_moment(f, multiaxial_psd, 2) / l0) / (2*np.pi)

tests/multiaxial_test.py::test_data
/opt/hostedtoolcache/Python/3.13.2/x64/lib/python3.13/site-packages/scipy/optimize/_differentiable_functions.py:317: UserWarning: delta_grad == 0.0. Check if the approximated function is linear. If the function is linear better results can be obtained by defining the Hessian as zero instead of using quasi-Newton approximations.
self.H.update(self.x - self.x_prev, self.g - self.g_prev)

tests/multiaxial_test.py::test_data
/opt/hostedtoolcache/Python/3.13.2/x64/lib/python3.13/site-packages/scipy/optimize/_differentiable_functions.py:552: UserWarning: delta_grad == 0.0. Check if the approximated function is linear. If the function is linear better results can be obtained by defining the Hessian as zero instead of using quasi-Newton approximations.
self.H.update(delta_x, delta_g)

tests/test_basic.py::test_data
/home/runner/work/FLife/FLife/tests/../FLife/spectralData.py:217: UserWarning: Tuple input has been deprecated. Use dictionary input instead.
warnings.warn('Tuple input has been deprecated. Use dictionary input instead.')

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