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<main>
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<article id="content">
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<header>
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<h1 class="title">Module <code>miplearn.components.tests.test_objective</code></h1>
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</header>
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<section id="section-intro">
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<details class="source">
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<summary>
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<span>Expand source code</span>
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</summary>
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<pre><code class="python"># MIPLearn: Extensible Framework for Learning-Enhanced Mixed-Integer Optimization
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# Copyright (C) 2020, UChicago Argonne, LLC. All rights reserved.
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# Released under the modified BSD license. See COPYING.md for more details.
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from unittest.mock import Mock
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import numpy as np
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from miplearn.classifiers import Regressor
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from miplearn.components.objective import ObjectiveValueComponent
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from miplearn.tests import get_test_pyomo_instances
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def test_usage():
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instances, models = get_test_pyomo_instances()
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comp = ObjectiveValueComponent()
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comp.fit(instances)
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assert instances[0].training_data[0]["Lower bound"] == 1183.0
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assert instances[0].training_data[0]["Upper bound"] == 1183.0
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assert np.round(comp.predict(instances), 2).tolist() == [
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[1183.0, 1183.0],
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[1070.0, 1070.0],
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]
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def test_obj_evaluate():
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instances, models = get_test_pyomo_instances()
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reg = Mock(spec=Regressor)
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reg.predict = Mock(return_value=np.array([1000.0, 1000.0]))
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comp = ObjectiveValueComponent(regressor=reg)
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comp.fit(instances)
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ev = comp.evaluate(instances)
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assert ev == {
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"Lower bound": {
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"Explained variance": 0.0,
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"Max error": 183.0,
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"Mean absolute error": 126.5,
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"Mean squared error": 19194.5,
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"Median absolute error": 126.5,
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"R2": -5.012843605607331,
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},
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"Upper bound": {
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"Explained variance": 0.0,
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"Max error": 183.0,
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"Mean absolute error": 126.5,
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"Mean squared error": 19194.5,
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"Median absolute error": 126.5,
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"R2": -5.012843605607331,
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},
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}</code></pre>
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</details>
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</section>
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<section>
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</section>
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<section>
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</section>
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<section>
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<h2 class="section-title" id="header-functions">Functions</h2>
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<dl>
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<dt id="miplearn.components.tests.test_objective.test_obj_evaluate"><code class="name flex">
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<span>def <span class="ident">test_obj_evaluate</span></span>(<span>)</span>
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</code></dt>
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<dd>
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<section class="desc"></section>
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<details class="source">
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<summary>
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<span>Expand source code</span>
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</summary>
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<pre><code class="python">def test_obj_evaluate():
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instances, models = get_test_pyomo_instances()
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reg = Mock(spec=Regressor)
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reg.predict = Mock(return_value=np.array([1000.0, 1000.0]))
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comp = ObjectiveValueComponent(regressor=reg)
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comp.fit(instances)
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ev = comp.evaluate(instances)
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assert ev == {
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"Lower bound": {
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"Explained variance": 0.0,
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"Max error": 183.0,
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"Mean absolute error": 126.5,
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"Mean squared error": 19194.5,
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"Median absolute error": 126.5,
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"R2": -5.012843605607331,
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},
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"Upper bound": {
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"Explained variance": 0.0,
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"Max error": 183.0,
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"Mean absolute error": 126.5,
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"Mean squared error": 19194.5,
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"Median absolute error": 126.5,
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"R2": -5.012843605607331,
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},
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}</code></pre>
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</details>
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</dd>
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<dt id="miplearn.components.tests.test_objective.test_usage"><code class="name flex">
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<span>def <span class="ident">test_usage</span></span>(<span>)</span>
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</code></dt>
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<dd>
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<section class="desc"></section>
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<details class="source">
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<summary>
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<span>Expand source code</span>
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</summary>
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<pre><code class="python">def test_usage():
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instances, models = get_test_pyomo_instances()
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comp = ObjectiveValueComponent()
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comp.fit(instances)
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assert instances[0].training_data[0]["Lower bound"] == 1183.0
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assert instances[0].training_data[0]["Upper bound"] == 1183.0
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assert np.round(comp.predict(instances), 2).tolist() == [
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[1183.0, 1183.0],
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[1070.0, 1070.0],
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]</code></pre>
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</details>
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</dd>
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</dl>
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</section>
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<section>
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</section>
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</article>
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<nav id="sidebar">
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<h1>Index</h1>
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<div class="toc">
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<ul></ul>
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</div>
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<ul id="index">
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<li><h3>Super-module</h3>
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<ul>
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<li><code><a title="miplearn.components.tests" href="index.html">miplearn.components.tests</a></code></li>
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</ul>
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</li>
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<li><h3><a href="#header-functions">Functions</a></h3>
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<ul class="">
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<li><code><a title="miplearn.components.tests.test_objective.test_obj_evaluate" href="#miplearn.components.tests.test_objective.test_obj_evaluate">test_obj_evaluate</a></code></li>
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<li><code><a title="miplearn.components.tests.test_objective.test_usage" href="#miplearn.components.tests.test_objective.test_usage">test_usage</a></code></li>
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</ul>
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</li>
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</ul>
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