#!/usr/bin/python
# -*- coding: utf-8 -*-
import os
from array import array
from stat import ST_SIZE
import numpy as np
from .config import OBJSIMPY_DIR

import logging
logger = logging.getLogger(__name__)

def read(filename):
    f = open(filename, 'rb')
    size = os.stat(filename)[ST_SIZE]
    n_spikes = size//8
    logger.info("read({}):\nsize={},  n_spikes={}".format(filename, size, n_spikes))
    spikes = array('i')
    spikes.fromfile(f, 2*n_spikes)
    f.close()

    spike_times = map(lambda i:spikes[2*i], range(n_spikes))
    neuron_numbers = map(lambda i:spikes[2*i+1], range(n_spikes))
    return list(spike_times), list(neuron_numbers)

def write(spike_times_ms, senders, filename, first_node_id=0, dt=0.1):
    ''' dt is time step in ms
    '''
    steps = np.int64(spike_times_ms / dt)
    neuron_numbers = senders - first_node_id
    times_and_neurons = array('i', np.int64(np.array(np.array(zip(steps, neuron_numbers)).flat)))
    f = open(filename, "wb")
    times_and_neurons.tofile(f)
    f.close()    

def _from_memory(detec):
    import nest
    ev = nest.GetStatus(detec, "events")[0]
    return ev["times"], ev["senders"]
    
if __name__=="__main__":
    import pylab,sys
    filename = os.path.join(OBJSIMPY_DIR, '..', 'test', 'data', 'simdata_minimal', 'MyLayerspikes.dat.bin')
    n_paras = len(sys.argv)-1
    if (n_paras>0):
        filename = sys.argv[1]
        
    spike_times, neuron_numbers = read(filename)
    n_spikes = len(spike_times)

    start_index = 0
    if (n_paras>1):
        start = float(sys.argv[2])
        while start_index < n_spikes:
            if spike_times[start_index] >= start:
                break
            start_index += 1
    
    stop_index = start_index
    if (n_paras>2):
        stop = float(sys.argv[3])
        while stop_index < n_spikes:
            if spike_times[stop_index] >= stop:
                break
            stop_index += 1
    else:
        stop_index = n_spikes
    
    print("start_index="+str(start_index))
    print("stop_index="+str(stop_index))
    pylab.plot(spike_times[start_index:stop_index], neuron_numbers[start_index:stop_index],'.')
    pylab.show()