"""
This is the code to start lab6.  
"""

#import the cod for the pyNN nest interface.
import pyNN.nest as sim

#set up some constants in all caps for my style.
RUN_DURATION = 200
TIME_STEP = 0.1

numberNeurons = 2
numberOutputNeurons = 2

#Python functions don't need to return anything.
def connectInput(cells):
    #Make a spike source
    inputSpikeTimes = [10.0,110.0]
    spikeArray = {'spike_times': [inputSpikeTimes]}
    spikeGen=sim.Population(1,sim.SpikeSourceArray,spikeArray,
                            label='inputSpikes_0')

    #make a synapse
    firingWt = 0.1
    connector = []
    connector = connector + [(0,0,firingWt,TIME_STEP)]
    fromListConnector = sim.FromListConnector(connector)
    sim.Projection(spikeGen, cells,  fromListConnector, receptor_type='excitatory')
    

def connectInputToOutput(inputCells,outputCells):
    #make a synapse
    firingWt = 0.2
    connector = []
    connector = connector + [(0,0,firingWt,TIME_STEP)]
    fromListConnector = sim.FromListConnector(connector)
    #step 3
    sim.Projection(inputCells, outputCells,  fromListConnector, receptor_type='excitatory')
    stp_model= sim.TsodyksMarkramSynapse(weight=firingWt)

    #step 3
    #sim.Projection(inputCells, outputCells,  fromListConnector, synapse_type = stp_model)
    

#----main---
sim.setup(timestep=TIME_STEP,min_delay=TIME_STEP, max_delay=TIME_STEP, debug=0)

inputCells=sim.Population(numberNeurons,sim.IF_cond_exp,  cellparams={})
inputCells.record({'spikes'})

outputCells=sim.Population(numberOutputNeurons,sim.IF_cond_exp,  cellparams={})
outputCells.record({'spikes'})


connectInput(inputCells)

connectInputToOutput(inputCells,outputCells)

sim.run(RUN_DURATION)

inputCells.write_data("lab6SpikesInput.pkl",'spikes')
outputCells.write_data("lab6SpikesOutput.pkl",'spikes')