olftrans.data package

Submodules

olftrans.data.data module

class olftrans.data.data.Data[source]

Bases: object

find(data_type, key, loc_args=None)[source]
Parameters

  • data_type (Union[otp, rest, fi]) –

  • key (str) –

  • loc_args (Callable) –

save(data_type, data, metadata, fname=None)[source]
Parameters

data_type (Union[otp, rest, fi]) –

setup(clean=False)[source]
class olftrans.data.data.DataFI(Model: str, Currents: numpy.ndarray, Frequencies: numpy.ndarray, InputVar: str, SpikeVar: str, Params: dict, Repeats: int)[source]

Bases: object

Parameters

  • Model (str) –

  • Currents (numpy.ndarray) –

  • Frequencies (numpy.ndarray) –

  • InputVar (str) –

  • SpikeVar (str) –

  • Params (dict) –

  • Repeats (int) –

Return type

None

Currents: numpy.ndarray
Frequencies: numpy.ndarray
InputVar: str
Model: str
Params: dict
Repeats: int
SpikeVar: str
class olftrans.data.data.DataMetadata(dt: float, dur: float, start: float, stop: float, savgol_window: int = None, savgol_order: int = None)[source]

Bases: object

Parameters

  • dt (float) –

  • dur (float) –

  • start (float) –

  • stop (float) –

  • savgol_window (int) –

  • savgol_order (int) –

Return type

None

dt: float
dur: float
savgol_order: int = None
savgol_window: int = None
start: float
stop: float
class olftrans.data.data.DataOTP(Model: str, Amplitude: float, Br: numpy.ndarray, Dr: numpy.ndarray, Peak: numpy.ndarray, SS: numpy.ndarray)[source]

Bases: object

Parameters

  • Model (str) –

  • Amplitude (float) –

  • Br (numpy.ndarray) –

  • Dr (numpy.ndarray) –

  • Peak (numpy.ndarray) –

  • SS (numpy.ndarray) –

Return type

None

Amplitude: float
Br: numpy.ndarray
Dr: numpy.ndarray
Model: str
Peak: numpy.ndarray
SS: numpy.ndarray
class olftrans.data.data.DataRest(Model: str, ParamKey: str, ParamValue: numpy.ndarray, Smoothen: bool, Frequencies: numpy.ndarray, InputVar: str, SpikeVar: str, Params: dict, Repeats: int)[source]

Bases: object

Parameters

  • Model (str) –

  • ParamKey (str) –

  • ParamValue (numpy.ndarray) –

  • Smoothen (bool) –

  • Frequencies (numpy.ndarray) –

  • InputVar (str) –

  • SpikeVar (str) –

  • Params (dict) –

  • Repeats (int) –

Return type

None

Frequencies: numpy.ndarray
InputVar: str
Model: str
ParamKey: str
ParamValue: numpy.ndarray
Params: dict
Repeats: int
Smoothen: bool
SpikeVar: str

olftrans.data.hallem_carlson module

olftrans.data.hallem_carlson.get_data()[source]

olftrans.data.kreher module

olftrans.data.kreher.get_data()[source]

olftrans.data.physiology module

olftrans.data.physiology.get_data(dt, fpath='antenna_data.h5')[source]

olftrans.data.utils module

olftrans.data.utils.process_io(stim_t, stim, psth_t, psth, dt=0.0005)[source]

Process I/O

This function takes stimulus and PSTH, interpolates both at the same time resolution and make sure stimulus and PSTH are the same length. Padding is added with terminal values as needed.

Parameters

  • stim_t – Raw Stimulus Time Series

  • stim – Raw Stimulus - Should have the same dimensionality as stim_t

  • psth_t – Raw PSTH Time Stamps

  • psth – Raw PSTH - Should have the same dimensionality as psth_t

Keyword Arguments

dt – time step at which to interpolate the stimulus and PSTH

Returns

interpolated time series stim: interpolated stimulus psth: interpolated PSTH

Return type

t

Module contents