neuralib.model.rastermap.core.RasterMapResult

class neuralib.model.rastermap.core.RasterMapResult[source]

Bases: object

Container for storing the rastermap result, For both GUI load and customized plotting purpose

Dimension parameters:

N = Number of neurons/pixel

T = Number of image pulse

C = Number of clusters = N / binsize

__init__(filename, save_path, isort, embedding, ops, user_clusters=NOTHING, super_neurons=None)

Method generated by attrs for class RasterMapResult.

Parameters:

Return type:

None

Methods

`__init__`(filename, save_path, isort, ...[, ...])	Method generated by attrs for class RasterMapResult.
`load`(path)	Load the results from rastermap output
`save`(path)	For GUI loading & cache computing for plotting in different time domains

Attributes

`filename`	Filename of the neural activity data (i.e., .tif or .avi for wfield activity; .npy Array[float, [N, T]] file for cellular)
`save_path`	filename for the rastermap result save
`isort`	Array[int, N]
`embedding`	Array[float, [N, 1]]
`ops`	`RasterOptions`
`user_clusters`	list of clusters `UserCluster`
`super_neurons`	super neuron activity.
`n_super`	number of clusters

__init__(filename, save_path, isort, embedding, ops, user_clusters=NOTHING, super_neurons=None)

Method generated by attrs for class RasterMapResult.

Parameters:

Return type:

None

filename: str: Filename of the neural activity data (i.e., *.tif or *.avi for wfield activity; .npy Array[float, [N, T]] file for cellular)

classmethod load(path)[source]

Load the results from rastermap output

Parameters:: path (str | Path | bytes | BinaryIO | BufferedIOBase | BufferedReader) – file path of the rastermap output
Returns:: RasterMapResult
Return type:: Self

save(path)[source]

For GUI loading & cache computing for plotting in different time domains