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Normalization of parameters and snapshots #251

Description

@flabowski

Is your feature request related to a problem? Please describe.
I would like to normalize / scale my snapshots and or the parameters using ezyrb.

Describe the solution you'd like

import numpy as np
from ezyrb import Database


points = np.array([[1,  2],
                   [5,  6],
                   [9, 10]])
values = np.array([[0.0, 0.1, 0.2],
                   [0.3, 0.4, 0.5],
                   [0.6, 0.7, 0.8]])

db_train = Database(points, values)
db_train.normalise_parameters()
print(db_train.parameters_n)
# [[0.   0.  ]
#  [0.5  0.5 ]
#  [1.   1.  ]]

db_test = Database(np.array([[2.5, 2.5]]),
                   np.array([[0.3, 0.3, 0.3]]))

db_test.scaler_parameters = db_train.scaler_parameters
db_test.scale_down_parameters()
print(db_test.parameters_n)
# [[0.1875 0.0625]]

Describe alternatives you've considered
I have looked into the optional keyword arguments scaler_parameters and scaler_snapshots, they are used by calling their method fit_transform. I did not find any definition of fit_transform or how the scalers are supposed to be used.

I am happy to contribute if you think that fits in your library and is not already possible in some other way.

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