hxtorch

Modules

Classes

`CalibrationPath`	Path to a calibration.
`HWDBPath`	Path to a hardware database.

Functions

hxtorch.dense_spikes_to_list(spikes: tuple[numpy.ndarray[numpy.int32], numpy.ndarray[numpy.float32]], input_size: int) → list[list[list[_pygrenade_vx_common.Time]]]

hxtorch.extract_n_madc(samples: list[list[list[tuple[_pygrenade_vx_common.Time, pyhaldls_vx_v3.MADCSampleFromChip.Value]]]], n_samples: int) → tuple[numpy.ndarray[numpy.int32], numpy.ndarray[numpy.int32]]

hxtorch.extract_n_spikes(spike_times: list[list[list[_pygrenade_vx_common.Time]]], n_events: int, max_spikes: int) → tuple[numpy.ndarray[numpy.int32], numpy.ndarray[numpy.float32]]

hxtorch.get_unique_identifier(hwdb_path: Optional[hxtorch::core::HWDBPath] = None) → list[str]

Return the unique identifier of the chip with the initialized connection.

@param hwdb_path Optional path to the hwdb to use @return The identifier as string

hxtorch.init_hardware(path: Optional[_hxtorch_core.HWDBPath, None] = None, ann: bool = False)

Initialize the hardware automatically from the environment.

Parameters

path – Optional path to the hwdb to use.
ann – Boolean flag indicating whether non-spiking or spiking calibration is loaded.

hxtorch.init_hardware_minimal(): Initialize automatically from the environment without ExperimentInit and without any calibration.