"""

import numpy
import mozaik
from mozaik.core import BaseComponent
from mozaik import load_component
from mozaik.tools.distribution_parametrization import PyNNDistribution
from parameters import ParameterSet, UniformDist
from pyNN import space
from pyNN.errors import NothingToWriteError
from string import Template
from neo.core.spiketrain import SpikeTrain
import quantities as pq


logger = mozaik.getMozaikLogger()

class Sheet(BaseComponent):
    """
    Sheet is an abstraction of a 2D continuouse sheet of neurons, roughly
    corresponding to the PyNN Population class with the added spatial structure.

    The spatial position of all cells is kept within the PyNN Population object.
    Each sheet is assumed to be centered around (0,0) origin, corresponding to
    whatever excentricity the model is looking at. The internal representation
    of space is degrees of visual field. Thus x,y coordinates of a cell in all
    sheets correspond to the degrees of visual field this cell is away from the
    origin. However, the sheet and derived classes/methods are supposed to
    accept parameters in units that are most natural for the given parameter and
    recalculate these into the internal degrees of visual field representation.

import matplotlib
import time
import pylab
from mozaik.experiment import *
from pyNN import nest as sim
from model import VogelsAbbott
from mozaik.controller import run_experiments, setup_experiments, setup_logging
from mozaik.framework.population_selector import RCRandomPercentage
from mozaik.visualization.plotting import *
from mozaik.analysis.technical import NeuronAnnotationsToPerNeuronValues
from mozaik.storage.datastore import Hdf5DataStore,PickledDataStore
from NeuroTools.parameters import ParameterSet
from mozaik.storage.queries import *
import mozaik

logger = mozaik.getMozaikLogger("Mozaik")

if True:
    params = setup_experiments('FFI',sim)    
    jens_model = VogelsAbbott(sim,params)
    l4exc_kick = RCRandomPercentage(jens_model.sheets["V1_Exc_L4"],ParameterSet({'percentage': 20.0}))
    l4inh_kick = RCRandomPercentage(jens_model.sheets["V1_Inh_L4"],ParameterSet({'percentage': 20.0}))

    experiment_list =   [
                           #Lets kick the network up into activation
                           PoissonNetworkKick(jens_model,duration=70*7,sheet_list=["V1_Exc_L4","V1_Inh_L4"],recording_configuration_list=[l4exc_kick,l4inh_kick],lambda_list=[100,100]),
                           #Spontaneous Activity 
                           NoStimulation(jens_model,duration=70*7),
                        ]
    data_store = run_experiments(jens_model,experiment_list)
    #jens_model.connectors['V1L4ExcL4ExcConnection'].store_connections(data_store)