FrequencySeriesListο
Stability: Stable
What it isο
Use FrequencySeriesList to manage multiple FrequencySeries objects as a labeled collection with batch operations and conversion helpers.
Representative Signaturesο
FrequencySeriesList(data: list[FrequencySeries])
FrequencySeriesList.to_matrix()
Minimal Exampleο
from gwexpy.frequencyseries import FrequencySeries, FrequencySeriesList
import numpy as np
lst = FrequencySeriesList([FrequencySeries(np.ones(64), df=1.0)])
mat = lst.to_matrix()
API Referenceο
The detailed generated API continues below on this page.
Inherits from: FrequencySeriesBaseList
List of FrequencySeries objects.
Physical Contextο
Use FrequencySeriesList when you have several spectra that should keep their per-series identity: repeated measurements, different sensors, or several processing branches of the same channel.
each entry can still carry its own metadata and channel name
batch methods are convenient, but the list does not guarantee identical units,
df, or calibration state
Common Misreadingsο
assuming every entry is frequency-aligned just because they live in one list
overlaying spectra with different normalization or units and reading the result physically
treating list order as provenance unless you set names or labels deliberately
Where to go nextο
per-spectrum interpretation: FrequencySeries
aligned batch analysis: FrequencySeriesMatrix
practical workflow: Transfer Function Measurement
Methodsο
__init__ο
__init__(self, *items: 'Union[_FS, Iterable[_FS]]')
Initialize self. See help(type(self)) for accurate signature.
(Inherited from list)
EntryClassο
EntryClass(data, unit=None, f0=None, df=None, frequencies=None, name=None, epoch=None, channel=None, **kwargs)
Light wrapper of gwpyβs FrequencySeries for compatibility and future extension.
angleο
angle(self, *args, **kwargs) -> "'FrequencySeriesList'"
Alias for phase(). Returns a new FrequencySeriesList.
appendο
append(self, item: '_FS')
Append object to the end of the list.
(Inherited from list)
apply_responseο
apply_response(self, *args, **kwargs) -> "'FrequencySeriesList'"
Apply response to each FrequencySeries in the list. Returns a new FrequencySeriesList.
copyο
copy(self) -> "'FrequencySeriesBaseList[_FS]'"
Return a shallow copy of the list.
(Inherited from list)
cropο
crop(self, *args, **kwargs) -> "'FrequencySeriesList'"
Crop each FrequencySeries in the list. Returns a new FrequencySeriesList.
degreeο
degree(self, *args, **kwargs) -> "'FrequencySeriesList'"
Compute phase (in degrees) of each FrequencySeries. Returns a new FrequencySeriesList.
differentiate_timeο
differentiate_time(self, *args, **kwargs) -> "'FrequencySeriesList'"
Apply time differentiation to each item. Returns a new FrequencySeriesList.
extendο
extend(self, items: 'Iterable[_FS]') -> 'None'
Extend list by appending elements from the iterable.
(Inherited from list)
filterο
filter(self, *args, **kwargs) -> "'FrequencySeriesList'"
Apply filter to each FrequencySeries in the list. Returns a new FrequencySeriesList.
group_delayο
group_delay(self, *args, **kwargs) -> "'FrequencySeriesList'"
Compute group delay of each item. Returns a new FrequencySeriesList.
ifftο
ifft(self, *args, **kwargs)
Compute IFFT of each FrequencySeries. Returns a TimeSeriesList.
insertο
insert(self, index: 'int', item: '_FS') -> 'None'
Insert object before index.
(Inherited from list)
integrate_timeο
integrate_time(self, *args, **kwargs) -> "'FrequencySeriesList'"
Apply time integration to each item. Returns a new FrequencySeriesList.
interpolateο
interpolate(self, *args, **kwargs) -> "'FrequencySeriesList'"
Interpolate each FrequencySeries in the list. Returns a new FrequencySeriesList.
padο
pad(self, *args, **kwargs) -> "'FrequencySeriesList'"
Pad each FrequencySeries in the list. Returns a new FrequencySeriesList.
phaseο
phase(self, *args, **kwargs) -> "'FrequencySeriesList'"
Compute phase of each FrequencySeries. Returns a new FrequencySeriesList.
plotο
plot(self, **kwargs: 'Any')
Plot all series. Delegates to gwexpy.plot.Plot.
plot_allο
plot_all(self, *args: 'Any', **kwargs: 'Any')
Alias for plot(). Plots all series.
readο
read(source, *args, **kwargs)
No documentation available.
segmentsο
Frequency spans of each element (xspan).
smoothο
smooth(self, *args, **kwargs) -> "'FrequencySeriesList'"
Smooth each FrequencySeries. Returns a new FrequencySeriesList.
to_control_frdο
to_control_frd(self, *args, **kwargs) -> 'list'
Convert each item to control.FRD. Returns a list of FRD objects.
to_cupyο
to_cupy(self, *args, **kwargs) -> 'list'
Convert each item to cupy.ndarray. Returns a list of Arrays.
to_dbο
to_db(self, *args, **kwargs) -> "'FrequencySeriesList'"
Convert each FrequencySeries to dB. Returns a new FrequencySeriesList.
to_jaxο
to_jax(self, *args, **kwargs) -> 'list'
Convert each item to jax.Array. Returns a list of Arrays.
to_pandasο
to_pandas(self, **kwargs)
Convert to pandas.DataFrame. Columns are named by channel name or index.
to_tensorflowο
to_tensorflow(self, *args, **kwargs) -> 'list'
Convert each item to tensorflow.Tensor. Returns a list of Tensors.
to_tmultigraphο
to_tmultigraph(self, name: 'Optional[str]' = None) -> 'Any'
Convert to ROOT TMultiGraph.
to_torchο
to_torch(self, *args, **kwargs) -> 'list'
Convert each item to torch.Tensor. Returns a list of Tensors.
to_xarrayο
to_xarray(self)
Convert to xarray.DataArray. Concatenates along a new dimension βchannelβ.
writeο
write(self, target: 'str', *args: 'Any', **kwargs: 'Any') -> 'Any'
Write list to file (HDF5, ROOT, etc.).
For HDF5 output you can choose a layout (default is GWpy-compatible dataset-per-entry).
fsl.write("out.h5", format="hdf5") # GWpy-compatible (default)
fsl.write("out.h5", format="hdf5", layout="group") # legacy group-per-entry
Warning
Never unpickle data from untrusted sources. pickle/shelve can execute
arbitrary code on load.
Pickle portability note: pickled gwexpy FrequencySeriesList unpickles as a built-in
list of GWpy FrequencySeries (gwexpy not required on the loading side).
zpkο
zpk(self, *args, **kwargs) -> "'FrequencySeriesList'"
Apply ZPK filter to each FrequencySeries in the list. Returns a new FrequencySeriesList.