neuralib.imaging.spikes.cascade.CascadeModelConfig

class neuralib.imaging.spikes.cascade.CascadeModelConfig

Bases: TypedDict

model_name: str

Name of the model

sampling_rate: int

Sampling rate in Hz

training_datasets: list[str]

Dataset of ground truth data (in folder ‘Ground_truth’)

placeholder_1: int

protect formatting

noise_levels: list[int]

Noise levels for training (integers, normally 1-9)

placeholder_2: int

protect formatting

smoothing: float

Standard deviation of Gaussian smoothing in time (sec)

causal_kernel: int

Smoothing kernel is symmetric in time (0) or is causal (1)

windowsize: int

Windowsize in timepoints

before_frac: float

Fraction of timepoints before prediction point (0-1)

filter_sizes: list[int]

Filter sizes for each convolutional layer

filter_numbers: list[int]

Filter numbers for each convolutional layer

dense_expansion: int

For dense layer

loss_function: str

gradient-descent loss function

optimizer: str

Adagrad

nr_of_epochs: int

Number of training epochs per model

ensemble_size: int

Number of models trained for one noise level

batch_size: int

Batch size

training_finished: Literal['Yes', 'No', 'Running']

Yes / No / Running

verbose: int

level of status messages (0: minimal, 1: standard, 2: most, 3: all)

__init__(*args, **kwargs)

__new__(**kwargs)

clear() → None.  Remove all items from D.

copy() → a shallow copy of D

fromkeys(value=None, /)

Create a new dictionary with keys from iterable and values set to value.

get(key, default=None, /)

Return the value for key if key is in the dictionary, else default.

items() → a set-like object providing a view on D's items

keys() → a set-like object providing a view on D's keys

pop(k[, d]) → v, remove specified key and return the corresponding value.

If the key is not found, return the default if given; otherwise, raise a KeyError.

popitem()

Remove and return a (key, value) pair as a 2-tuple.

Pairs are returned in LIFO (last-in, first-out) order. Raises KeyError if the dict is empty.

setdefault(key, default=None, /)

Insert key with a value of default if key is not in the dictionary.

Return the value for key if key is in the dictionary, else default.

update([E, ]**F) → None.  Update D from dict/iterable E and F.

If E is present and has a .keys() method, then does: for k in E: D[k] = E[k] If E is present and lacks a .keys() method, then does: for k, v in E: D[k] = v In either case, this is followed by: for k in F: D[k] = F[k]

values() → an object providing a view on D's values