import io
from IPython.nbformat import current

def execute_notebook(nbfile):
    
    with io.open(nbfile) as f:
        nb = current.read(f, 'json')
    
    ip = get_ipython()
    
    for cell in nb.worksheets[0].cells:
        if cell.cell_type != 'code':
            continue
        ip.run_cell(cell.input)
        
execute_notebook("common.ipynb")

epochs = 100 
spikeMiliseconds = 100
spikeInterval = spikeMiliseconds * ms
spikeIntervalUnformatted = spikeMiliseconds * .001
dictionaryLongitude = 4
spikesPerChar=3
firstLayerSize = 15

dictionary = dictionary()
spiketimes = dictionary.spikeTimes(dictionaryLongitude, spikeInterval, spikesPerChar, epochs)
LIK = SpikeGeneratorGroup(firstLayerSize, spiketimes)
spikeMonitor = SpikeMonitor(LIK)

run(spikesPerChar * dictionaryLongitude * spikeInterval , report='text')

fig=plt.figure(figsize=(12,4))
for i in range(0,dictionaryLongitude):
    ax = fig.add_subplot(1,dictionaryLongitude,i+1)
    ax.imshow(dictionary.dictionary[i][1], interpolation="nearest", cmap = plt.cm.Greys_r)
    plt.xticks(np.arange(0,3, 1.0))

neuronArray = np.empty(0, dtype=int)
firetimeArray = np.empty(0, dtype=double)
neuronColor = np.random.rand(firstLayerSize)
colors = np.empty(0, dtype=float)

fig=plt.figure(figsize=(12,4))
for neuron in range(0,15):
    for fire in range(0,spikeMonitor.spiketimes[neuron].size):
       neuronArray = np.append(neuronArray, neuron)
       firetimeArray = np.append(firetimeArray,spikeMonitor.spiketimes[neuron][fire])
       colors = np.append(colors,neuronColor[neuron])

plt.scatter(firetimeArray,neuronArray, s=100, c=colors)
plt.xticks(np.arange(0,max(firetimeArray)+0.1, 0.1))
plt.yticks(np.arange(0,firstLayerSize, 1.0))
ylabel("Neuron number")
xlabel("Time(seconds)")
grid(True)

neuronArray = np.empty(0, dtype=int)
firetimeArray = np.empty(0, dtype=double)
neuronColor = np.random.rand(4)
colors = np.empty(0, dtype=float)

#Each neuron learn to represent a random character
neuronList=list(range(4))
np.random.shuffle(neuronList)


neuronIndex = 0
time = 0
for charNumber in range(0 ,dictionaryLongitude ):
    neuronIndex = (neuronIndex + 1)%4
    neuron = neuronList[neuronIndex]
    for charRepetetion in range(0,spikesPerChar):
         time = time + spikeInterval / ms
            
         neuronArray = np.append(neuronArray, neuron)
         firetimeArray = np.append(firetimeArray,time)
         colors = np.append(colors,neuronColor[neuron])

fig, ax = plt.subplots(subplot_kw=dict(axisbg='#EEEEEE'),figsize=(13,4))
points = plt.scatter(firetimeArray * ms,neuronArray, s=100, c=colors)
plt.yticks(np.arange(0,4, 1.0))
ylabel("Neuron number")
xlabel("Time(seconds)")
grid(True)