# Command: DataConnect

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Name:

    DataConnect - Connect many neurons from data.

Synopsis:

      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.

Description:

      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

Author:

    Marc-Oliver Gewaltig

FirstVersion:

    August 2011

SeeAlso:

- DataConnect_i_D_s
- DataConnect_a
- Connect

Source:

    /opt/conda/conda-bld/nest_1512421404550/work/nest-2.12.0/lib/sli/nest-init.sli

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