From 5e4eb03b893b0785773a087d9e4a146e34ec2a0c Mon Sep 17 00:00:00 2001 From: matheus_cascalho Date: Wed, 2 Dec 2020 17:45:26 -0300 Subject: [PATCH] test save_net --- pyFTS/common/fts.py | 2 +- pyFTS/common/transformations/som.py | 72 +++++++++++++++++++ .../multivariate => partitioners}/som.py | 16 +++-- pyFTS/tests/test_SOMTransformation.py | 47 ++++++++++++ 4 files changed, 130 insertions(+), 7 deletions(-) create mode 100644 pyFTS/common/transformations/som.py rename pyFTS/{models/multivariate => partitioners}/som.py (88%) create mode 100644 pyFTS/tests/test_SOMTransformation.py diff --git a/pyFTS/common/fts.py b/pyFTS/common/fts.py index b0c66e5..ca651eb 100644 --- a/pyFTS/common/fts.py +++ b/pyFTS/common/fts.py @@ -503,7 +503,7 @@ class FTS(object): params = [ None for k in self.transformations] for c, t in enumerate(self.transformations, start=0): - ndata = t.apply(ndata,params[c]) + ndata = t.apply(ndata, params[c], ) return ndata diff --git a/pyFTS/common/transformations/som.py b/pyFTS/common/transformations/som.py new file mode 100644 index 0000000..af66c26 --- /dev/null +++ b/pyFTS/common/transformations/som.py @@ -0,0 +1,72 @@ +""" +Kohonen Self Organizing Maps for Fuzzy Time Series +""" +import pandas as pd +import SimpSOM as sps +from pyFTS.models.multivariate import wmvfts +from typing import Tuple +from pyFTS.common.Transformations import Transformation + + +class SOMTransformation(Transformation): + def __init__(self, + grid_dimension: Tuple, + **kwargs): + # SOM attributes + self.net: sps.somNet = None + self.data: pd.DataFrame = None + self.grid_dimension: Tuple = grid_dimension + self.pbc = kwargs.get('PBC', True) + + # debug attributes + self.name = 'Kohonen Self Organizing Maps FTS' + self.shortname = 'SOM-FTS' + + # def apply(self, data, endogen_variable, param, **kwargs): #TODO(CASCALHO) MELHORAR DOCSTRING + # """ + # Transform dataset from M-DIMENSION to 3-dimension + # """ + # pass + + def __repr__(self): + status = "is trained" if self.is_trained else "not trained" + return f'{self.name}-{status}' + + def __str__(self): + return self.name + + def __del__(self): + del self.net + + def train(self, + data: pd.DataFrame, + percentage_train: float = .7, + leaning_rate: float = 0.01, + epochs: int = 10000): + self.data = data.values + limit = round(len(self.data) * percentage_train) + train = self.data[:limit] + x, y = self.grid_dimension + self.net = sps.somNet(x, y, train, PBC=self.pbc) + self.net.train(startLearnRate=leaning_rate, + epochs=epochs) + + def save_net(self, + filename: str = "SomNet trained"): + self.net.save(filename) + + def show_grid(self, + graph_type: str = 'nodes_graph', + **kwargs): + if graph_type == 'nodes_graph': + colnum = kwargs.get('colnum', 0) + self.net.nodes_graph(colnum=colnum) + else: + self.net.diff_graph() + + +""" +Requisitos + - apply(herdado de transformations): transforma os conjunto de dados + - inverse - não é necessária +""" diff --git a/pyFTS/models/multivariate/som.py b/pyFTS/partitioners/som.py similarity index 88% rename from pyFTS/models/multivariate/som.py rename to pyFTS/partitioners/som.py index f1faf67..059ea11 100644 --- a/pyFTS/models/multivariate/som.py +++ b/pyFTS/partitioners/som.py @@ -7,7 +7,7 @@ from pyFTS.models.multivariate import wmvfts from typing import Tuple -class SOMFTS: +class SOMPartitioner: def __init__(self, grid_dimension: Tuple, **kwargs): @@ -17,10 +17,6 @@ class SOMFTS: self.grid_dimension: Tuple = grid_dimension self.pbc = kwargs.get('PBC', True) - # fts attributes - self.fts_method = kwargs.get('fts_method', wmvfts.WeightedMVFTS) - self.order = kwargs.get('order', 2) - self.is_trained = False # debug attributes self.name = 'Kohonen Self Organizing Maps FTS' @@ -60,4 +56,12 @@ class SOMFTS: colnum = kwargs.get('colnum', 0) self.net.nodes_graph(colnum=colnum) else: - self.net.diff_graph() \ No newline at end of file + self.net.diff_graph() + + + +""" +Requisitos + + +""" \ No newline at end of file diff --git a/pyFTS/tests/test_SOMTransformation.py b/pyFTS/tests/test_SOMTransformation.py new file mode 100644 index 0000000..e1fab22 --- /dev/null +++ b/pyFTS/tests/test_SOMTransformation.py @@ -0,0 +1,47 @@ +import unittest +from pyFTS.common.transformations.som import SOMTransformation +import pandas as pd +import os + +class MyTestCase(unittest.TestCase): + def test_apply(self): + self.assertEqual(True, False) + + def test_save_net(self): + som_transformer = self.som_transformer_trained() + + filename = 'test_net.npy' + som_transformer.save_net(filename) + files = os.listdir() + + if filename in files: + is_in_files = True + os.remove(filename) + else: + is_in_files = False + + self.assertEqual(True, is_in_files) + + def test_train(self): + self.assertEqual() + + @staticmethod + def simple_dataset(): + data = [ + [1, 1, 1, 1, 1], + [1, 1, 1, 1, 0], + [1, 1, 1, 0, 0], + [1, 1, 0, 0, 0], + [1, 0, 0, 0, 0], + ] + df = pd.DataFrame(data) + return df + + def som_transformer_trained(self): + data = self.simple_dataset() + som_transformer = SOMTransformation(grid_dimension=(2, 2)) + som_transformer.train(data=data, epochs=100) + return som_transformer + +if __name__ == '__main__': + unittest.main()