gwexpy.interop.sdypy_

Interoperability with SDyPy and pyuff (Universal File Format).

Functions

`from_uff_dataset55`(uff_data)	Convert a pyuff dataset-55 dict to a `pandas.DataFrame`.
`from_uff_dataset58`(cls, uff_data, *[, ...])	Convert a pyuff dataset-58 dict to `TimeSeries` or `FrequencySeries`.

gwexpy.interop.sdypy_.from_uff_dataset58(cls: type, uff_data: dict, *, response_type: str | None = None) → Any[source]

Convert a pyuff dataset-58 dict to TimeSeries or FrequencySeries.

Parameters:

cls (type) – TimeSeries or FrequencySeries. If None or ambiguous, the function type field in the UFF data is used to auto-select.
uff_data (dict) – A single dataset-58 record as returned by pyuff.UFF().read_sets(). Expected keys: "x", "data", "func_type", "id1" (description), "rsp_dir", "ref_dir", etc.
response_type (str, optional) – Override for unit inference (e.g. "accel").

Return type:

TimeSeries or FrequencySeries

gwexpy.interop.sdypy_.from_uff_dataset55(uff_data: dict) → Any[source]

Convert a pyuff dataset-55 dict to a pandas.DataFrame.

Dataset type 55 contains modal model data: natural frequencies, modal damping, and mode shapes.

Parameters:: uff_data (dict) – A single dataset-55 record from pyuff.UFF().read_sets(). Expected keys: "modal_m" (mode number), "modal_freq", "modal_damp", "modal_viscous_damp", "r1"–"r6" (DOF responses), "node_nums", etc.
Return type:: pandas.DataFrame