gaussian

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gaussian#

class brainpy.state.spatial.gaussian(x=spatial.distance, mean=0.0, std=1.0)[source]#

Gaussian distance-dependent connection probability.

Returns a callable p(d) = exp(-(d-mean)^2 / (2 std^2)) matching NEST’s nest.spatial_distributions.gaussian(distance, mean, std).

Parameters:

  • x (object, optional) – The distance sentinel (or a per-axis expression such as distance.x).

  • mean (float or Quantity, optional) – Distribution mean (length); bare floats are taken in micrometres. Default 0.

  • std (float or Quantity, optional) – Standard deviation (length); bare floats are taken in micrometres. Default 1.

Returns:

p(d) mapping a distance (Quantity) to a connection probability.

Return type:

callable

Examples

>>> from brainpy import state as bp
>>> import brainunit as u
>>> p = bp.spatial.gaussian(bp.spatial.distance, std=0.5)
>>> float(u.get_magnitude(p(0.0 * u.um)))
1.0
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