Convert scientific Python objects#
Use to_*() and from_*() when converting an object already in memory.
Use file I/O when reading or writing a local file.
The conversion catalogue records the
supported classes, directions, optional dependencies, and metadata boundaries.
Start with an array#
from gwexpy.timeseries import TimeSeries
signal = TimeSeries([0.0, 1.0, 0.0, -1.0], sample_rate=4, t0=0, unit="V")
values = signal.value
The array contains values; keep signal.sample_rate, signal.t0, and signal.unit
when exporting to a representation that cannot preserve them. The
Scientific Python tutorial shows the complete
array-to-container workflow without requiring GWpy knowledge.
Use a library-specific bridge#
Follow the interoperability tutorial for worked pandas, xarray, and external-library conversions. Install the dependencies listed for the selected bridge and check which metadata survives the round trip.
For control-system plots, use a measured or modelled complex transfer response with the correct input/output units. An ASD or PSD describes noise amplitude or power; converting its container does not turn it into a system response.
Detailed capabilities#
The former catalogue sections remain available through these links.