code: def create(genome, config, time_constant):
          
          genome_config = config.genome_config
          required = required_for_output(genome_config.input_keys, genome_config.output_keys, genome.connections)
  
          # Gather inputs and expressed connections.
          node_inputs = {}
          for cg in itervalues(genome.connections):
              if not cg.enabled:
                  continue
  
              i, o = cg.key
              if o not in required and i not in required:
                  continue
  
              if o not in node_inputs:
                  node_inputs[o] = [(i, cg.weight)]
              else:
                  node_inputs[o].append((i, cg.weight))
  
          node_evals = {}
          for node_key, inputs in iteritems(node_inputs):
              node = genome.nodes[node_key]
              activation_function = genome_config.activation_defs.get(node.activation)
              aggregation_function = genome_config.aggregation_function_defs.get(node.aggregation)
              node_evals[node_key] = CTRNNNodeEval(time_constant,
                                                   activation_function,
                                                   aggregation_function,
                                                   node.bias,
                                                   node.response,
                                                   inputs)
  
          return CTRNN(genome_config.input_keys, genome_config.output_keys, node_evals)
docs: Receives a genome and returns its phenotype (a CTRNN).