superneuromat.SNN.from_jsons#

SNN.from_jsons(json_str: str, net_id: int | str = 0, skipkeys: list[str] | tuple[str] | None = None)[source]#

Update this SNN from a SuperNeuroMat JSON string.

Parameters:

  • json_str (str) – _description_

  • net_id (int | str (default: 0)) – ID of the network to load. Can be an integer, which represents its index in the JSON network list, or a string, which represents the name of the network stored in json_dict["networks"]["meta"]["name"].

  • skipkeys (list[str] | tuple[str] | None (default: None)) – Keys from json_dict["networks"]["data"] to skip when loading the network.

Returns:

This SNN will be updated with the specified network data from the JSON string.

Return type:

self

Raises:

ValueError – If network with given ID not found, or if multiple networks with the given ID are found.

Examples

>>> snn = SNN()
>>> with open('my_model.snn.json', 'r') as f:
>>>     snn.from_jsons(f.read(), net_id="My SNN")