neurocarto.util.edit.optimize
- neurocarto.util.edit.optimize.optimize_channelmap(bp, chmap, blueprint, sample_times=100, *, n_worker=1, **kwargs)
Sample and find the optimized channelmap that has maxima channel efficiency.
- Parameters:
bp (BlueprintFunctions)
chmap (ChannelMap) – initial channel map
blueprint (ndarray[tuple[int, ...], dtype[int]])
sample_times (int) – (int=100)
kwargs – selector parameters
n_worker (int)
- Returns:
tuple of (channelmap, aeff, ceff)
- Return type:
tuple[ChannelMap, float, float]
- neurocarto.util.edit.optimize.generate_channelmap(bp, chmap, blueprint, sample_times=100, *, n_worker=1, **kwargs)
generate a group of channel maps.
- Parameters:
bp (BlueprintFunctions)
chmap (ChannelMap) – channelmap type. It is a reference.
blueprint (ndarray[tuple[int, ...], dtype[int]])
sample_times (int) – N (int=100)
kwargs – selector parameters
n_worker (int)
- Returns:
tuple of ([channelmap], Array[aeff, N], Array[ceff, N])
- Return type:
tuple[list[ChannelMap], ndarray[tuple[int, …], dtype[float]], ndarray[tuple[int, …], dtype[float]]]