PCA example

examples/nodes/pca_tests.py

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+# -*- coding: utf-8 -*-
+#
+# File : examples/timeserie_prediction/switch_attractor_esn
+# Description : NARMA 30 prediction with ESN.
+# Date : 26th of January, 2018
+#
+# This file is part of EchoTorch.  EchoTorch is free software: you can
+# redistribute it and/or modify it under the terms of the GNU General Public
+# License as published by the Free Software Foundation, version 2.
+#
+# This program is distributed in the hope that it will be useful, but WITHOUT
+# ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS
+# FOR A PARTICULAR PURPOSE.  See the GNU General Public License for more
+# details.
+#
+# You should have received a copy of the GNU General Public License along with
+# this program; if not, write to the Free Software Foundation, Inc., 51
+# Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA.
+#
+# Copyright Nils Schaetti <nils.schaetti@unine.ch>
+
+
+# Imports
+import torch
+import echotorch.nn as etnn
+from torch.autograd import Variable
+import mdp
+
+
+# Settings
+input_dim = 10
+output_dim = 3
+tlen = 500
+
+# Generate
+training_samples = torch.randn(1, tlen, input_dim)
+test_samples = torch.randn(1, tlen, input_dim)
+
+# Generate
+training_samples_np = training_samples[0].numpy()
+test_samples_np = test_samples[0].numpy()
+
+# Show
+print(u"Training samples : {}".format(training_samples_np))
+print(u"Test samples : {}".format(test_samples_np))
+
+# PCA node
+mdp_pca_node = mdp.Flow([mdp.nodes.PCANode(input_dim=input_dim, output_dim=output_dim)])
+mdp_pca_node.train(training_samples_np)
+pca_reduced = mdp_pca_node(test_samples_np)
+
+# Show
+print(u"PCA reduced : {}".format(pca_reduced))
+
+# EchoTorch PCA node
+et_pca_node = etnn.PCACell(input_dim=input_dim, output_dim=output_dim)
+et_pca_node(Variable(training_samples))
+et_pca_node.finalize()
+et_reduced = et_pca_node(Variable(test_samples))
+
+# Show
+print(u"Reduced with EchoTorch/PCA :")
+print(et_reduced)