directory + 'test_2018-08-03.csv', N, varF, F, init)
print('reservoir initialized')
functionInputs = [f_utils.getInputTuple(window) for i in range(O)]
functionsToApproximate, functionVectors = [], []
for i in range(O):
function_vector = f_utils.convertIntToBinaryVector(i, 2**window)
func = f_utils.convertVectorToFunction(function_vector)
functionsToApproximate.append(func)
# Only for printing purposes
functionVectors.append(function_vector)
output = OutputLayer(res, O, functionsToApproximate, functionInputs, delay,
dataStreamLength)
output.train(trainingSize)
output.test(testSize)
print(f'N = {N}')
print(f'K = {K}')
print(f'I = {I}')
print(f'L = {output.reservoir.L}')
print(f'window = {window}')
print(f'delay = {delay}')
print(f'dataStreamLength = {dataStreamLength}')
print(f'trainingSize = {trainingSize}')
print(f'testSize = {testSize}')
print(f'seed = {seed}')
print(f'O = {O}')
print()
