Remove redundant asserts

[lispandfound]

These assert statements were breaking gcmt-to-realisation because the values had type np.float64 not float, so I have removed the assertions

[gemini-code-assist]

Summary of Changes

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This pull request addresses a runtime issue in the gcmt-to-realisation script by removing type assertion statements that were causing failures. The assertions incorrectly expected standard Python float types, while the actual values were numpy.float64, leading to unnecessary program interruptions. The removal of these checks ensures the script can process numpy float types without error, improving its robustness.

Highlights

• Type Assertion Removal: Removed redundant isinstance type assertions for nodal plane parameters (strike, dip, rake) in gcmt_to_realisation.py.
• Bug Fix: Resolved a runtime issue where these assertions were incorrectly failing for numpy.float64 values, which are distinct from Python's built-in float type.

Changelog

• workflow/scripts/gcmt_to_realisation.py
  • Removed isinstance assertions for strike1, dip1, rake1, strike2, dip2, and rake2 variables.

Activity

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[Copilot]

Pull request overview

Removes runtime assert isinstance(...) checks in gcmt-to-realisation that were failing when values are np.float64, allowing GCMT CSV-derived nodal-plane values to flow through without hard type assertions.

Changes:

• Removed six isinstance(..., float | int) asserts for strike/dip/rake values read from the published GCMT CSV.

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[Copilot]

nodal_plane_2 is constructed with arguments in a different order than nodal_plane_1 (and likely the NodalPlane API). Here it passes (strike2, rake2, dip2), which swaps dip and rake and will produce an incorrect nodal plane; use the same (strike, dip, rake) ordering as for plane 1 (and as implied by NodalPlane(**solution["nodalPlanes"][1])).

Suggested change

	nodal_plane_2 = NodalPlane(strike2, rake2, dip2)
	nodal_plane_2 = NodalPlane(strike2, dip2, rake2)

[Copilot]

This PR removes type asserts for strike/dip/rake because pandas returns np.float64, but there are still asserts later in this function (assert isinstance(magnitude, float) and assert isinstance(centroid_depth, float)) that will also fail for np.float64 (and potentially int). Consider removing these asserts too, or replacing them with a numbers.Real/np.floating check or explicit float(...) conversion at the point of use.

[gemini-code-assist]

Code Review

This pull request removes several assert statements that were causing issues due to type mismatches with numpy data types. While this fixes the immediate problem, it also removes valuable type validation. My review suggests reintroducing these assertions with a more robust type check that accommodates numpy's numeric types, ensuring both correctness and robustness without causing crashes.

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workflow/scripts/gcmt_to_realisation.py (174-179)

While these assertions were failing due to np.float64 types, removing them entirely eliminates important type validation. This could lead to unexpected errors downstream if the data is not numeric. A better approach is to modify the assertions to correctly handle numpy's numeric types. You can include np.number in the type check, which is a base type for numpy's numeric scalars.

        assert isinstance(strike1, (int, float, np.number))
        assert isinstance(dip1, (int, float, np.number))
        assert isinstance(rake1, (int, float, np.number))
        assert isinstance(strike2, (int, float, np.number))
        assert isinstance(dip2, (int, float, np.number))
        assert isinstance(rake2, (int, float, np.number))