gwexpy.interop.sdypy_๏ƒ

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,ย uff_data,ย *[,ย ...])

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) โ€“ TimeSeries or FrequencySeries. If None or ambiguous, the function type field in the UFF data is used to auto-select.

  • uff_data (dict) โ€“ 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) โ€“ 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) โ€“ A single dataset-55 record from pyuff.UFF().read_sets(). Expected keys: "modal_m" (mode number), "modal_freq", "modal_damp", "modal_viscous_damp", "r1"โ€“"r6" (DOF responses), "node_nums", etc.

Return type:

pandas.DataFrame