gapnet.data_creation.spikeogram.generators

module documentation

(source)

Spikeogram generator functions

Function	`spikeogram_2D`	Generates a 2D spikeogram from the .mat-file.
Function	`spikeogram_3D`	Generates a 3D spikeogram from the .mat-file.

def spikeogram_2D(data, data_field='an_out_sum', bin_width=0.001, dtype='float32'): (source) ¶

Generates a 2D spikeogram from the .mat-file.

Parameters
data:`h5py.File`	the open .mat-file object
data_field:`str`	the datafield to use, e.g. 'an_out_sum'
bin_width:`float`	binwidth for downsampling, 1e-3 (1 ms)
dtype	datatype, default is 'float32'
Returns
`torch.Tensor`	tensor with 2 dimensions, i.e. [frequency, time]
Raises
`ValueError`	when <h5py.File>.Get() fails and return None

def spikeogram_3D(data, data_fields=None, bin_width=0.001, dtype='float32'): (source) ¶

Generates a 3D spikeogram from the .mat-file.

Parameters
data:`h5py.File`	the open .mat-file object
data_fields:`List[str]`	the datafields to use. Default is ['an_out_hs', 'an_out_ms', 'an_out_ls']
bin_width:`float`	binwidth for downsampling. Default is 1e-3 (1 ms)
dtype	datatype. Default is 'float32'
Returns
`torch.Tensor`	tensor with 3 dimensions, i.e. [channels, frequency, time]
Raises
`ValueError`	when <h5py.File>.Get() fails and return None