import numpy
import mlprec

# load data
datafile = "time_reber.dat"
data = numpy.loadtxt(datafile,delimiter=' ')
if  numpy.rank(data) == 1:
    data = numpy.reshape(data, (numpy.shape(data)[0], 1))
num_data = numpy.shape(data)[0]
dim_in   = numpy.shape(data)[1]
print "num_data=%d dim_in=%d" % (num_data, dim_in)

# data -= numpy.mean(data)

inputs = numpy.array(data)
targets = numpy.array(data)

p = mlprec.mlp(inputs,targets, 5, 1.0, 0.8, "softmax")

for rep in range(100):

    p.mlptrain(inputs,targets,0.0025,100)

    if  dim_in == 1:
        p.mlpplot(inputs,targets,100)
    else:
        p.mlpplotreber(inputs,targets)