DataConnect - Connect many neurons from data.
1. source dict model DataConnect_i_D_a -> -
source - GID of the source neuron
dict - dictionary with connection parameters
model - the synapse model as string or literal
2. [dict1 dict2 .... dict_n] DataConnect_a -> -
The argument is a list with synapse status dictionaries as obtained from GetStatus.
Variant 1:
This variant is used if connectivity data is explicitly given and read from files.
Connects the source neuron to targets according to the data in dict, using the synapse 'model'.
Dict is a parameter dictionary that must contain at least the following fields:
/target
/weight
/delay
Other parameters depend on the synapse model.
The values in the dictionaries are arrays of equal size, specifying the parameters for the
respective connection. The arrays should all be of type DoubleVectorDatum (numpy.array(dtype=float)).
Note that for performance reasons, target GIDs must be given as doubles rather than integers!
The second variant of DataConnect can be used to re-instantiate a given connectivity matrix.
The argument is a list of dictionaries, each containing at least the keys
/source
/target
/weight
/delay
/synapse_model
Example:
% assume a connected network
<< >> GetConnections /conns Set % Get all connections
conns { GetStatus } Map /syns Set % retrieve their synapse status
ResetKernel % clear everything
% rebuild neurons
syns DataConnect % restore the connecions
Marc-Oliver Gewaltig
August 2011
/var/www/debian/nest/nest-simulator-2.20.0/lib/sli/nest-init.sli