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import sys
sys.path.append('../')
from numpy import *
import seaborn as sns
import pandas as pd
import matplotlib.pyplot as plt
from ML import MLP


    

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# We load the data to be regressed
data = load("../Data/ML/Mars_Far.npy")


    

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'''
Here we instantiate a multi-layer perceptron with 4 hidden layers,
each with __ neurons (features). We also state the input columns
and output columns.
'''

iin    = [0,1,2,3,4]   # Input the state
iout   = [5,6]         # Target the controls
layers = [20,20] # Hidden layer structure

# Instantiate the artificial neural network
net1 = MLP("Mars_Far", "../Data/ML/")
net1.build(len(iin), len(iout), layers)
net1.scale(data, iin, iout)


    

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dps = data[:3,iin]
net1.predict(dps)


    

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