low level weights utilities

skcriteria/tests/test_weights.py

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+#!/usr/bin/env python
+# -*- coding: utf-8 -*-
+
+# Copyright (c) 2016-2017, Cabral, Juan; Luczywo, Nadia
+# All rights reserved.
+
+# Redistribution and use in source and binary forms, with or without
+# modification, are permitted provided that the following conditions are met:
+
+# * Redistributions of source code must retain the above copyright notice, this
+# list of conditions and the following disclaimer.
+
+# * Redistributions in binary form must reproduce the above copyright notice,
+# this list of conditions and the following disclaimer in the documentation
+# and/or other materials provided with the distribution.
+
+# * Neither the name of the copyright holder nor the names of its
+# contributors may be used to endorse or promote products derived from
+# this software without specific prior written permission.
+
+# THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS"
+# AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE
+# IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE
+# ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT HOLDER OR CONTRIBUTORS BE
+# LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR
+# CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF
+# SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS
+# INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN
+# CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE)
+# ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE
+# POSSIBILITY OF SUCH DAMAGE.
+
+
+# =============================================================================
+# FUTURE
+# =============================================================================
+
+from __future__ import unicode_literals
+
+
+# =============================================================================
+# DOC
+# =============================================================================
+
+__doc__ = """Test normalization functionalities"""
+
+
+# =============================================================================
+# IMPORTS
+# =============================================================================
+
+import numpy as np
+
+from . import core
+
+from .. import weights, norm
+
+
+# =============================================================================
+# BASE
+# =============================================================================
+
+class Divergence(core.SKCriteriaTestCase):
+
+    def setUp(self):
+        # Data from:
+        # Diakoulaki, D., Mavrotas, G., & Papayannakis, L. (1995).
+        # Determining objective weights in multiple criteria problems:
+        # The critic method. Computers & Operations Research, 22(7), 763-770.
+        self.nmtx = norm.ideal_point([
+            [61, 1.08, 4.33],
+            [20.7, 0.26, 4.34],
+            [16.3, 1.98, 2.53],
+            [9, 3.29, 1.65],
+            [5.4, 2.77, 2.33],
+            [4, 4.12, 1.21],
+            [-6.1, 3.52, 2.10],
+            [-34.6, 3.31, 0.98]
+        ], axis=0)
+        self.expected = [0.27908306,  0.34092628,  0.37999065]
+
+    def test_divergence(self):
+        result = weights.divergence(self.nmtx, np.std)
+        self.assertAllClose(result, self.expected)
+
+
+class Equal(core.SKCriteriaTestCase):
+
+    def setUp(self):
+        self.nmtx = np.array([
+            [1, 1],
+            [2, 2]
+        ])
+        self.expected = [0.5, 0.5]
+
+    def test_equal(self):
+        result = weights.equal(self.nmtx)
+        self.assertAllClose(result, self.expected)
+
+
+class Critic(core.SKCriteriaTestCase):
+
+    def setUp(self):
+        # Data from:
+        # Diakoulaki, D., Mavrotas, G., & Papayannakis, L. (1995).
+        # Determining objective weights in multiple criteria problems:
+        # The critic method. Computers & Operations Research, 22(7), 763-770.
+        self.nmtx = norm.ideal_point([
+            [61, 1.08, 4.33],
+            [20.7, 0.26, 4.34],
+            [16.3, 1.98, 2.53],
+            [9, 3.29, 1.65],
+            [5.4, 2.77, 2.33],
+            [4, 4.12, 1.21],
+            [-6.1, 3.52, 2.10],
+            [-34.6, 3.31, 0.98]
+        ], axis=0)
+        self.expected = [0.20222554, 0.48090173, 0.31687273]
+
+    def test_equal(self):
+        result = weights.critic(self.nmtx, np.std, np.corrcoef)
+        self.assertAllClose(result, self.expected)

skcriteria/weights.py

@@ -0,0 +1,78 @@
+#!/usr/bin/env python
+# -*- coding: utf-8 -*-
+
+# Copyright (c) 2016-2017, Cabral, Juan; Luczywo, Nadia
+# All rights reserved.
+
+# Redistribution and use in source and binary forms, with or without
+# modification, are permitted provided that the following conditions are met:
+
+# * Redistributions of source code must retain the above copyright notice, this
+# list of conditions and the following disclaimer.
+
+# * Redistributions in binary form must reproduce the above copyright notice,
+# this list of conditions and the following disclaimer in the documentation
+# and/or other materials provided with the distribution.
+
+# * Neither the name of the copyright holder nor the names of its
+# contributors may be used to endorse or promote products derived from
+# this software without specific prior written permission.
+
+# THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS"
+# AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE
+# IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE
+# ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT HOLDER OR CONTRIBUTORS BE
+# LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR
+# CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF
+# SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS
+# INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN
+# CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE)
+# ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE
+# POSSIBILITY OF SUCH DAMAGE.
+
+
+# =============================================================================
+# FUTURE
+# =============================================================================
+
+from __future__ import unicode_literals
+
+
+# =============================================================================
+# DOCS
+# =============================================================================
+
+"""This module contains functions for calculate and compare ranks (ordinal
+series)
+
+"""
+
+
+# =============================================================================
+# IMPORTS
+# =============================================================================
+
+import numpy as np
+
+
+# =============================================================================
+# WEIGHTS
+# =============================================================================
+
+def divergence(nmtx, dfunction):
+    dindex = dfunction(nmtx, axis=0)
+    return dindex / dindex.sum()
+
+
+def equal(nmtx):
+    m = nmtx.shape[1]
+    weights = 1. / m
+    return np.tile(weights, m)
+
+
+def critic(nmtx, dfunction, cfunction):
+    dindex = dfunction(nmtx, axis=0)
+    corr_m1 = 1 - cfunction(nmtx.T)
+    uweights = dindex * corr_m1.sum(axis=0)
+    weights = uweights / uweights.sum()
+    return weights