Dummy Detector

class lys_instr.dummy.MultiDetector.MultiDetectorDummy(data=None, indexShape=(), frameShape=(100, 100), exposure=0.1, **kwargs)[source]

Bases: MultiDetectorInterface

Dummy implementation of MultiDetectorInterface.

This class simulates a detector that Produces indexed frames from a supplied data source or by generating random frames. Acquisition runs in a background loop (started by start() in __init__) and populates an internal buffer. Signals updated, dataAcquired, and aliveStateChanged, defined in MultiDetectorInterface, are emitted as appropriate.

property axes

Axis coordinates for the full data.

Returns:: Coordinate arrays corresponding to each axis of the index grid.
Return type:: List[numpy.ndarray]

property frameShape

Shape of a single acquired data frame.

Returns:: Frame dimensions (height, width, …) as provided by the data source.
Return type:: tuple[int, …]

property indexShape

Shape of the index grid.

Returns:: Dimensions of the index grid used to iterate over frames.
Return type:: tuple[int, …]

setData(data=None, indexShape=None, frameShape=None)[source]

Configure the dummy data source.

Parameters:

data (Optional[DummyDataInterface]) – Data source. If None, a random-data generator (RandomData) is created.
indexShape (Optional[Tuple[int, ...]]) – Index-grid shape used by the random-data generator.
frameShape (Optional[Tuple[int, ...]]) – Frame shape used by the random-data generator.

settingsWidget()[source]

Create and return an optional settings QWidget.

Returns:: The settings panel widget.
Return type:: QtWidgets.QWidget

class lys_instr.dummy.detectorData.interface.DummyDataInterface[source]

Bases: object

Abstract interface for dummy detector data providers.

Subclasses should provide an iterable sequence of frames and metadata describing frame shape, index grid shape, and coordinate axes.

property axes

Axis coordinates for the full data.

Returns:: Coordinate arrays corresponding to each axis of the index grid.
Return type:: list[numpy.ndarray]

property frameShape

Shape of each data frame.

Returns:: Shape of each data frame.
Return type:: tuple[int, …]

property indexShape

Shape of the index grid for data frames.

Returns:: Shape of the index grid.
Return type:: tuple[int, …]

classmethod name()[source]

Return the name of the dummy data set.

Returns:: Name of the dummy data set.
Return type:: str

property nframes

Number of sub-frames per yielded frame.

Values > 1 indicate multi-slice frames (e.g., when an index row is treated as a leading frame dimension).

Returns:: Number of sub-frames per yielded frame.
Return type:: int

class lys_instr.dummy.detectorData.raman.RamanData(scanLevel=0)[source]

Bases: DummyDataInterface

Dummy Raman data provider backed by NumPy sample data.

The class loads resources/sampleRamanData.npy from the package and exposes frames, index shape and coordinate axes. It supports two scanLevel modes (0 or 1).

property axes

Axis coordinates for the full data.

Returns:: Coordinate arrays corresponding to each axis of the index grid.
Return type:: list[numpy.ndarray]

property frameShape

Shape of each data frame.

Returns:: Shape of each data frame.
Return type:: tuple[int, …]

property indexShape

Shape of the index grid to be filled by data frames.

Returns:: Shape of the index grid (empty tuple when no index).
Return type:: tuple[int, …]

classmethod name()[source]

Return the name of the data provider.

Returns:: Name of the data provider (“Raman”).
Return type:: str

property nframes

Number of sub-frames per yielded frame.

Returns:: Number of sub-frames per yielded frame (always 1 for this provider).
Return type:: int

class lys_instr.dummy.detectorData.random.RandomData(indexShape, frameShape)[source]

Bases: DummyDataInterface

Dummy random data provider for given index and frame shapes.

property axes

Axis coordinates for the full data.

Returns:: Coordinate arrays corresponding to each axis of the index grid (evenly spaced integers).
Return type:: list[numpy.ndarray]

property frameShape

Shape of each generated data frame.

Returns:: Shape of each generated data frame.
Return type:: tuple[int, …]

property indexShape

Shape of the index grid to be filled by generated data frames.

Returns:: Shape of the index grid.
Return type:: tuple[int, …]

classmethod name()[source]

Return the name of the data provider.

Returns:: Name of the data provider (“Random”).
Return type:: str

property nframes

Number of sub-frames per yielded frame.

If len(indexShape) + len(frameShape) <= 3 -> 1
If both are 2-D -> indexShape[1] (inner/column count)

Examples

indexShape=() and frameShape=(100, 100) -> 1
indexShape=(10,) and frameShape=(100, 100) -> 1
indexShape=(5, 3) and frameShape=(100, 100) -> 3

Returns:: Number of sub-frames per yielded frame.
Return type:: int
Raises:: NotImplementedError – If the combination of shapes is unsupported.

class lys_instr.dummy.detectorData.random.RandomData2D[source]

Bases: RandomData

Convenience 2-D random-data provider.

classmethod name()[source]

Return the name of the data provider.

Returns:: Name of the data provider (“Random 2D”).
Return type:: str