Update 0.2 docs

2025-12-06 09:28:51 -06:00 · 2021-01-22 07:25:10 -06:00
parent 894f4b4668
commit 144523a5c0
73 changed files with 607 additions and 842 deletions
--- a/0.2/api/miplearn/solvers/gurobi.html
+++ b/0.2/api/miplearn/solvers/gurobi.html
@@ -3,7 +3,7 @@
 <head>
 <meta charset="utf-8">
 <meta name="viewport" content="width=device-width, initial-scale=1, minimum-scale=1" />
-<meta name="generator" content="pdoc 0.7.0" />
+<meta name="generator" content="pdoc 0.7.5" />
 <title>miplearn.solvers.gurobi API documentation</title>
 <meta name="description" content="" />
 <link href='https://cdnjs.cloudflare.com/ajax/libs/normalize/8.0.0/normalize.min.css' rel='stylesheet'>
@@ -920,7 +920,7 @@ LP relaxation of that node.</dd>
 </nav>
 </main>
 <footer id="footer">
-<p>Generated by <a href="https://pdoc3.github.io/pdoc"><cite>pdoc</cite> 0.7.0</a>.</p>
+<p>Generated by <a href="https://pdoc3.github.io/pdoc"><cite>pdoc</cite> 0.7.5</a>.</p>
 </footer>
 <script src="https://cdnjs.cloudflare.com/ajax/libs/highlight.js/9.12.0/highlight.min.js"></script>
 <script>hljs.initHighlightingOnLoad()</script>
--- a/0.2/api/miplearn/solvers/index.html
+++ b/0.2/api/miplearn/solvers/index.html
@@ -3,7 +3,7 @@
 <head>
 <meta charset="utf-8">
 <meta name="viewport" content="width=device-width, initial-scale=1, minimum-scale=1" />
-<meta name="generator" content="pdoc 0.7.0" />
+<meta name="generator" content="pdoc 0.7.5" />
 <title>miplearn.solvers API documentation</title>
 <meta name="description" content="" />
 <link href='https://cdnjs.cloudflare.com/ajax/libs/normalize/8.0.0/normalize.min.css' rel='stylesheet'>
@@ -115,7 +115,7 @@ class _RedirectOutput:
 </nav>
 </main>
 <footer id="footer">
-<p>Generated by <a href="https://pdoc3.github.io/pdoc"><cite>pdoc</cite> 0.7.0</a>.</p>
+<p>Generated by <a href="https://pdoc3.github.io/pdoc"><cite>pdoc</cite> 0.7.5</a>.</p>
 </footer>
 <script src="https://cdnjs.cloudflare.com/ajax/libs/highlight.js/9.12.0/highlight.min.js"></script>
 <script>hljs.initHighlightingOnLoad()</script>
--- a/0.2/api/miplearn/solvers/internal.html
+++ b/0.2/api/miplearn/solvers/internal.html
@@ -3,7 +3,7 @@
 <head>
 <meta charset="utf-8">
 <meta name="viewport" content="width=device-width, initial-scale=1, minimum-scale=1" />
-<meta name="generator" content="pdoc 0.7.0" />
+<meta name="generator" content="pdoc 0.7.5" />
 <title>miplearn.solvers.internal API documentation</title>
 <meta name="description" content="" />
 <link href='https://cdnjs.cloudflare.com/ajax/libs/normalize/8.0.0/normalize.min.css' rel='stylesheet'>
@@ -303,7 +303,6 @@ class InternalSolver(ABC):
 <dl>
 <dt id="miplearn.solvers.internal.InternalSolver"><code class="flex name class">
 <span>class <span class="ident">InternalSolver</span></span>
-<span>(</span><span>*args, **kwargs)</span>
 </code></dt>
 <dd>
 <section class="desc"><p>Abstract class representing the MIP solver used internally by LearningSolver.</p></section>
@@ -561,8 +560,8 @@ class InternalSolver(ABC):
 </ul>
 <h3>Subclasses</h3>
 <ul class="hlist">
-<li><a title="miplearn.solvers.pyomo.base.BasePyomoSolver" href="pyomo/base.html#miplearn.solvers.pyomo.base.BasePyomoSolver">BasePyomoSolver</a></li>
 <li><a title="miplearn.solvers.gurobi.GurobiSolver" href="gurobi.html#miplearn.solvers.gurobi.GurobiSolver">GurobiSolver</a></li>
+<li><a title="miplearn.solvers.pyomo.base.BasePyomoSolver" href="pyomo/base.html#miplearn.solvers.pyomo.base.BasePyomoSolver">BasePyomoSolver</a></li>
 </ul>
 <h3>Methods</h3>
 <dl>
@@ -1134,7 +1133,7 @@ def solve_lp(
 </nav>
 </main>
 <footer id="footer">
-<p>Generated by <a href="https://pdoc3.github.io/pdoc"><cite>pdoc</cite> 0.7.0</a>.</p>
+<p>Generated by <a href="https://pdoc3.github.io/pdoc"><cite>pdoc</cite> 0.7.5</a>.</p>
 </footer>
 <script src="https://cdnjs.cloudflare.com/ajax/libs/highlight.js/9.12.0/highlight.min.js"></script>
 <script>hljs.initHighlightingOnLoad()</script>
--- a/0.2/api/miplearn/solvers/learning.html
+++ b/0.2/api/miplearn/solvers/learning.html
@@ -3,7 +3,7 @@
 <head>
 <meta charset="utf-8">
 <meta name="viewport" content="width=device-width, initial-scale=1, minimum-scale=1" />
-<meta name="generator" content="pdoc 0.7.0" />
+<meta name="generator" content="pdoc 0.7.5" />
 <title>miplearn.solvers.learning API documentation</title>
 <meta name="description" content="" />
 <link href='https://cdnjs.cloudflare.com/ajax/libs/normalize/8.0.0/normalize.min.css' rel='stylesheet'>
@@ -46,7 +46,7 @@ from miplearn.instance import Instance
 from miplearn.solvers import _RedirectOutput
 from miplearn.solvers.internal import InternalSolver
 from miplearn.solvers.pyomo.gurobi import GurobiPyomoSolver
-from miplearn.types import MIPSolveStats, TrainingSample
+from miplearn.types import MIPSolveStats, TrainingSample, LearningSolveStats

 logger = logging.getLogger(__name__)

@@ -153,7 +153,7 @@ class LearningSolver:
        output_filename: Optional[str] = None,
        discard_output: bool = False,
        tee: bool = False,
-    ) -&gt; MIPSolveStats:
+    ) -&gt; LearningSolveStats:

        # Load instance from file, if necessary
        filename = None
@@ -229,15 +229,24 @@ class LearningSolver:

        # Solve MILP
        logger.info(&#34;Solving MILP...&#34;)
-        stats = self.internal_solver.solve(
-            tee=tee,
-            iteration_cb=iteration_cb_wrapper,
-            lazy_cb=lazy_cb,
+        stats = cast(
+            LearningSolveStats,
+            self.internal_solver.solve(
+                tee=tee,
+                iteration_cb=iteration_cb_wrapper,
+                lazy_cb=lazy_cb,
+            ),
        )
        if &#34;LP value&#34; in training_sample.keys():
            stats[&#34;LP value&#34;] = training_sample[&#34;LP value&#34;]
+        stats[&#34;Solver&#34;] = &#34;default&#34;
+        stats[&#34;Gap&#34;] = self._compute_gap(
+            ub=stats[&#34;Upper bound&#34;],
+            lb=stats[&#34;Lower bound&#34;],
+        )
+        stats[&#34;Mode&#34;] = self.mode

-        # Read MIP solution and bounds
+        # Add some information to training_sample
        training_sample[&#34;Lower bound&#34;] = stats[&#34;Lower bound&#34;]
        training_sample[&#34;Upper bound&#34;] = stats[&#34;Upper bound&#34;]
        training_sample[&#34;MIP log&#34;] = stats[&#34;Log&#34;]
@@ -268,7 +277,7 @@ class LearningSolver:
        output_filename: Optional[str] = None,
        discard_output: bool = False,
        tee: bool = False,
-    ) -&gt; MIPSolveStats:
+    ) -&gt; LearningSolveStats:
        &#34;&#34;&#34;
        Solves the given instance. If trained machine-learning models are
        available, they will be used to accelerate the solution process.
@@ -301,7 +310,7 @@ class LearningSolver:

        Returns
        -------
-        MIPSolveStats
+        LearningSolveStats
            A dictionary of solver statistics containing at least the following
            keys: &#34;Lower bound&#34;, &#34;Upper bound&#34;, &#34;Wallclock time&#34;, &#34;Nodes&#34;,
            &#34;Sense&#34;, &#34;Log&#34;, &#34;Warm start value&#34; and &#34;LP value&#34;.
@@ -337,7 +346,7 @@ class LearningSolver:
        label: str = &#34;Solve&#34;,
        output_filenames: Optional[List[str]] = None,
        discard_outputs: bool = False,
-    ) -&gt; List[MIPSolveStats]:
+    ) -&gt; List[LearningSolveStats]:
        &#34;&#34;&#34;
        Solves multiple instances in parallel.

@@ -364,7 +373,7 @@ class LearningSolver:

        Returns
        -------
-        List[MIPSolveStats]
+        List[LearningSolveStats]
            List of solver statistics, with one entry for each provided instance.
            The list is the same you would obtain by calling
            `[solver.solve(p) for p in instances]`
@@ -409,7 +418,19 @@ class LearningSolver:

    def __getstate__(self) -&gt; Dict:
        self.internal_solver = None
-        return self.__dict__</code></pre>
+        return self.__dict__
+
+    @staticmethod
+    def _compute_gap(ub: Optional[float], lb: Optional[float]) -&gt; Optional[float]:
+        if lb is None or ub is None or lb * ub &lt; 0:
+            # solver did not find a solution and/or bound
+            return None
+        elif abs(ub - lb) &lt; 1e-6:
+            # avoid division by zero when ub = lb = 0
+            return 0.0
+        else:
+            # divide by max(abs(ub),abs(lb)) to ensure gap &lt;= 1
+            return (ub - lb) / max(abs(ub), abs(lb))</code></pre>
 </details>
 </section>
 <section>
@@ -531,7 +552,7 @@ the theoretical performance of perfect ML models.</dd>
        output_filename: Optional[str] = None,
        discard_output: bool = False,
        tee: bool = False,
-    ) -&gt; MIPSolveStats:
+    ) -&gt; LearningSolveStats:

        # Load instance from file, if necessary
        filename = None
@@ -607,15 +628,24 @@ the theoretical performance of perfect ML models.</dd>

        # Solve MILP
        logger.info(&#34;Solving MILP...&#34;)
-        stats = self.internal_solver.solve(
-            tee=tee,
-            iteration_cb=iteration_cb_wrapper,
-            lazy_cb=lazy_cb,
+        stats = cast(
+            LearningSolveStats,
+            self.internal_solver.solve(
+                tee=tee,
+                iteration_cb=iteration_cb_wrapper,
+                lazy_cb=lazy_cb,
+            ),
        )
        if &#34;LP value&#34; in training_sample.keys():
            stats[&#34;LP value&#34;] = training_sample[&#34;LP value&#34;]
+        stats[&#34;Solver&#34;] = &#34;default&#34;
+        stats[&#34;Gap&#34;] = self._compute_gap(
+            ub=stats[&#34;Upper bound&#34;],
+            lb=stats[&#34;Lower bound&#34;],
+        )
+        stats[&#34;Mode&#34;] = self.mode

-        # Read MIP solution and bounds
+        # Add some information to training_sample
        training_sample[&#34;Lower bound&#34;] = stats[&#34;Lower bound&#34;]
        training_sample[&#34;Upper bound&#34;] = stats[&#34;Upper bound&#34;]
        training_sample[&#34;MIP log&#34;] = stats[&#34;Log&#34;]
@@ -646,7 +676,7 @@ the theoretical performance of perfect ML models.</dd>
        output_filename: Optional[str] = None,
        discard_output: bool = False,
        tee: bool = False,
-    ) -&gt; MIPSolveStats:
+    ) -&gt; LearningSolveStats:
        &#34;&#34;&#34;
        Solves the given instance. If trained machine-learning models are
        available, they will be used to accelerate the solution process.
@@ -679,7 +709,7 @@ the theoretical performance of perfect ML models.</dd>

        Returns
        -------
-        MIPSolveStats
+        LearningSolveStats
            A dictionary of solver statistics containing at least the following
            keys: &#34;Lower bound&#34;, &#34;Upper bound&#34;, &#34;Wallclock time&#34;, &#34;Nodes&#34;,
            &#34;Sense&#34;, &#34;Log&#34;, &#34;Warm start value&#34; and &#34;LP value&#34;.
@@ -715,7 +745,7 @@ the theoretical performance of perfect ML models.</dd>
        label: str = &#34;Solve&#34;,
        output_filenames: Optional[List[str]] = None,
        discard_outputs: bool = False,
-    ) -&gt; List[MIPSolveStats]:
+    ) -&gt; List[LearningSolveStats]:
        &#34;&#34;&#34;
        Solves multiple instances in parallel.

@@ -742,7 +772,7 @@ the theoretical performance of perfect ML models.</dd>

        Returns
        -------
-        List[MIPSolveStats]
+        List[LearningSolveStats]
            List of solver statistics, with one entry for each provided instance.
            The list is the same you would obtain by calling
            `[solver.solve(p) for p in instances]`
@@ -787,7 +817,19 @@ the theoretical performance of perfect ML models.</dd>

    def __getstate__(self) -&gt; Dict:
        self.internal_solver = None
-        return self.__dict__</code></pre>
+        return self.__dict__
+
+    @staticmethod
+    def _compute_gap(ub: Optional[float], lb: Optional[float]) -&gt; Optional[float]:
+        if lb is None or ub is None or lb * ub &lt; 0:
+            # solver did not find a solution and/or bound
+            return None
+        elif abs(ub - lb) &lt; 1e-6:
+            # avoid division by zero when ub = lb = 0
+            return 0.0
+        else:
+            # divide by max(abs(ub),abs(lb)) to ensure gap &lt;= 1
+            return (ub - lb) / max(abs(ub), abs(lb))</code></pre>
 </details>
 <h3>Methods</h3>
 <dl>
@@ -808,7 +850,7 @@ the theoretical performance of perfect ML models.</dd>
 </details>
 </dd>
 <dt id="miplearn.solvers.learning.LearningSolver.parallel_solve"><code class="name flex">
-<span>def <span class="ident">parallel_solve</span></span>(<span>self, instances, n_jobs=4, label=&#39;Solve&#39;, output_filenames=None, discard_outputs=False)</span>
+<span>def <span class="ident">parallel_solve</span></span>(<span>self, instances, n_jobs=4, label='Solve', output_filenames=None, discard_outputs=False)</span>
 </code></dt>
 <dd>
 <section class="desc"><p>Solves multiple instances in parallel.</p>
@@ -834,7 +876,7 @@ them instead. Useful during benchmarking.</dd>
 </dl>
 <h2 id="returns">Returns</h2>
 <dl>
-<dt><code>List</code>[<code>MIPSolveStats</code>]</dt>
+<dt><code>List</code>[<code>LearningSolveStats</code>]</dt>
 <dd>List of solver statistics, with one entry for each provided instance.
 The list is the same you would obtain by calling
 <code>[solver.solve(p) for p in instances]</code></dd>
@@ -850,7 +892,7 @@ The list is the same you would obtain by calling
    label: str = &#34;Solve&#34;,
    output_filenames: Optional[List[str]] = None,
    discard_outputs: bool = False,
-) -&gt; List[MIPSolveStats]:
+) -&gt; List[LearningSolveStats]:
    &#34;&#34;&#34;
    Solves multiple instances in parallel.

@@ -877,7 +919,7 @@ The list is the same you would obtain by calling

    Returns
    -------
-    List[MIPSolveStats]
+    List[LearningSolveStats]
        List of solver statistics, with one entry for each provided instance.
        The list is the same you would obtain by calling
        `[solver.solve(p) for p in instances]`
@@ -933,7 +975,7 @@ them. Useful during benchmarking.</dd>
 </dl>
 <h2 id="returns">Returns</h2>
 <dl>
-<dt><code>MIPSolveStats</code></dt>
+<dt><code>LearningSolveStats</code></dt>
 <dd>
 <p>A dictionary of solver statistics containing at least the following
 keys: "Lower bound", "Upper bound", "Wallclock time", "Nodes",
@@ -955,7 +997,7 @@ details.</p>
    output_filename: Optional[str] = None,
    discard_output: bool = False,
    tee: bool = False,
-) -&gt; MIPSolveStats:
+) -&gt; LearningSolveStats:
    &#34;&#34;&#34;
    Solves the given instance. If trained machine-learning models are
    available, they will be used to accelerate the solution process.
@@ -988,7 +1030,7 @@ details.</p>

    Returns
    -------
-    MIPSolveStats
+    LearningSolveStats
        A dictionary of solver statistics containing at least the following
        keys: &#34;Lower bound&#34;, &#34;Upper bound&#34;, &#34;Wallclock time&#34;, &#34;Nodes&#34;,
        &#34;Sense&#34;, &#34;Log&#34;, &#34;Warm start value&#34; and &#34;LP value&#34;.
@@ -1050,7 +1092,7 @@ details.</p>
 </nav>
 </main>
 <footer id="footer">
-<p>Generated by <a href="https://pdoc3.github.io/pdoc"><cite>pdoc</cite> 0.7.0</a>.</p>
+<p>Generated by <a href="https://pdoc3.github.io/pdoc"><cite>pdoc</cite> 0.7.5</a>.</p>
 </footer>
 <script src="https://cdnjs.cloudflare.com/ajax/libs/highlight.js/9.12.0/highlight.min.js"></script>
 <script>hljs.initHighlightingOnLoad()</script>
--- a/0.2/api/miplearn/solvers/pyomo/base.html
+++ b/0.2/api/miplearn/solvers/pyomo/base.html
@@ -3,7 +3,7 @@
 <head>
 <meta charset="utf-8">
 <meta name="viewport" content="width=device-width, initial-scale=1, minimum-scale=1" />
-<meta name="generator" content="pdoc 0.7.0" />
+<meta name="generator" content="pdoc 0.7.5" />
 <title>miplearn.solvers.pyomo.base API documentation</title>
 <meta name="description" content="" />
 <link href='https://cdnjs.cloudflare.com/ajax/libs/normalize/8.0.0/normalize.min.css' rel='stylesheet'>
@@ -665,8 +665,8 @@ class BasePyomoSolver(InternalSolver):
 </ul>
 <h3>Subclasses</h3>
 <ul class="hlist">
-<li><a title="miplearn.solvers.pyomo.gurobi.GurobiPyomoSolver" href="gurobi.html#miplearn.solvers.pyomo.gurobi.GurobiPyomoSolver">GurobiPyomoSolver</a></li>
 <li><a title="miplearn.solvers.pyomo.cplex.CplexPyomoSolver" href="cplex.html#miplearn.solvers.pyomo.cplex.CplexPyomoSolver">CplexPyomoSolver</a></li>
+<li><a title="miplearn.solvers.pyomo.gurobi.GurobiPyomoSolver" href="gurobi.html#miplearn.solvers.pyomo.gurobi.GurobiPyomoSolver">GurobiPyomoSolver</a></li>
 <li><a title="miplearn.solvers.pyomo.xpress.XpressPyomoSolver" href="xpress.html#miplearn.solvers.pyomo.xpress.XpressPyomoSolver">XpressPyomoSolver</a></li>
 </ul>
 <h3>Inherited members</h3>
@@ -722,7 +722,7 @@ class BasePyomoSolver(InternalSolver):
 </nav>
 </main>
 <footer id="footer">
-<p>Generated by <a href="https://pdoc3.github.io/pdoc"><cite>pdoc</cite> 0.7.0</a>.</p>
+<p>Generated by <a href="https://pdoc3.github.io/pdoc"><cite>pdoc</cite> 0.7.5</a>.</p>
 </footer>
 <script src="https://cdnjs.cloudflare.com/ajax/libs/highlight.js/9.12.0/highlight.min.js"></script>
 <script>hljs.initHighlightingOnLoad()</script>
--- a/0.2/api/miplearn/solvers/pyomo/cplex.html
+++ b/0.2/api/miplearn/solvers/pyomo/cplex.html
@@ -3,7 +3,7 @@
 <head>
 <meta charset="utf-8">
 <meta name="viewport" content="width=device-width, initial-scale=1, minimum-scale=1" />
-<meta name="generator" content="pdoc 0.7.0" />
+<meta name="generator" content="pdoc 0.7.5" />
 <title>miplearn.solvers.pyomo.cplex API documentation</title>
 <meta name="description" content="" />
 <link href='https://cdnjs.cloudflare.com/ajax/libs/normalize/8.0.0/normalize.min.css' rel='stylesheet'>
@@ -185,7 +185,7 @@ class CplexPyomoSolver(BasePyomoSolver):
 </nav>
 </main>
 <footer id="footer">
-<p>Generated by <a href="https://pdoc3.github.io/pdoc"><cite>pdoc</cite> 0.7.0</a>.</p>
+<p>Generated by <a href="https://pdoc3.github.io/pdoc"><cite>pdoc</cite> 0.7.5</a>.</p>
 </footer>
 <script src="https://cdnjs.cloudflare.com/ajax/libs/highlight.js/9.12.0/highlight.min.js"></script>
 <script>hljs.initHighlightingOnLoad()</script>
--- a/0.2/api/miplearn/solvers/pyomo/gurobi.html
+++ b/0.2/api/miplearn/solvers/pyomo/gurobi.html
@@ -3,7 +3,7 @@
 <head>
 <meta charset="utf-8">
 <meta name="viewport" content="width=device-width, initial-scale=1, minimum-scale=1" />
-<meta name="generator" content="pdoc 0.7.0" />
+<meta name="generator" content="pdoc 0.7.5" />
 <title>miplearn.solvers.pyomo.gurobi API documentation</title>
 <meta name="description" content="" />
 <link href='https://cdnjs.cloudflare.com/ajax/libs/normalize/8.0.0/normalize.min.css' rel='stylesheet'>
@@ -213,7 +213,7 @@ class GurobiPyomoSolver(BasePyomoSolver):
 </nav>
 </main>
 <footer id="footer">
-<p>Generated by <a href="https://pdoc3.github.io/pdoc"><cite>pdoc</cite> 0.7.0</a>.</p>
+<p>Generated by <a href="https://pdoc3.github.io/pdoc"><cite>pdoc</cite> 0.7.5</a>.</p>
 </footer>
 <script src="https://cdnjs.cloudflare.com/ajax/libs/highlight.js/9.12.0/highlight.min.js"></script>
 <script>hljs.initHighlightingOnLoad()</script>
--- a/0.2/api/miplearn/solvers/pyomo/index.html
+++ b/0.2/api/miplearn/solvers/pyomo/index.html
@@ -3,7 +3,7 @@
 <head>
 <meta charset="utf-8">
 <meta name="viewport" content="width=device-width, initial-scale=1, minimum-scale=1" />
-<meta name="generator" content="pdoc 0.7.0" />
+<meta name="generator" content="pdoc 0.7.5" />
 <title>miplearn.solvers.pyomo API documentation</title>
 <meta name="description" content="" />
 <link href='https://cdnjs.cloudflare.com/ajax/libs/normalize/8.0.0/normalize.min.css' rel='stylesheet'>
@@ -80,7 +80,7 @@
 </nav>
 </main>
 <footer id="footer">
-<p>Generated by <a href="https://pdoc3.github.io/pdoc"><cite>pdoc</cite> 0.7.0</a>.</p>
+<p>Generated by <a href="https://pdoc3.github.io/pdoc"><cite>pdoc</cite> 0.7.5</a>.</p>
 </footer>
 <script src="https://cdnjs.cloudflare.com/ajax/libs/highlight.js/9.12.0/highlight.min.js"></script>
 <script>hljs.initHighlightingOnLoad()</script>
--- a/0.2/api/miplearn/solvers/pyomo/xpress.html
+++ b/0.2/api/miplearn/solvers/pyomo/xpress.html
@@ -3,7 +3,7 @@
 <head>
 <meta charset="utf-8">
 <meta name="viewport" content="width=device-width, initial-scale=1, minimum-scale=1" />
-<meta name="generator" content="pdoc 0.7.0" />
+<meta name="generator" content="pdoc 0.7.5" />
 <title>miplearn.solvers.pyomo.xpress API documentation</title>
 <meta name="description" content="" />
 <link href='https://cdnjs.cloudflare.com/ajax/libs/normalize/8.0.0/normalize.min.css' rel='stylesheet'>
@@ -166,7 +166,7 @@ class XpressPyomoSolver(BasePyomoSolver):
 </nav>
 </main>
 <footer id="footer">
-<p>Generated by <a href="https://pdoc3.github.io/pdoc"><cite>pdoc</cite> 0.7.0</a>.</p>
+<p>Generated by <a href="https://pdoc3.github.io/pdoc"><cite>pdoc</cite> 0.7.5</a>.</p>
 </footer>
 <script src="https://cdnjs.cloudflare.com/ajax/libs/highlight.js/9.12.0/highlight.min.js"></script>
 <script>hljs.initHighlightingOnLoad()</script>
--- a/0.2/api/miplearn/solvers/tests/index.html
+++ b/0.2/api/miplearn/solvers/tests/index.html
@@ -3,7 +3,7 @@
 <head>
 <meta charset="utf-8">
 <meta name="viewport" content="width=device-width, initial-scale=1, minimum-scale=1" />
-<meta name="generator" content="pdoc 0.7.0" />
+<meta name="generator" content="pdoc 0.7.5" />
 <title>miplearn.solvers.tests API documentation</title>
 <meta name="description" content="" />
 <link href='https://cdnjs.cloudflare.com/ajax/libs/normalize/8.0.0/normalize.min.css' rel='stylesheet'>
@@ -242,7 +242,7 @@ features, which can be provided as inputs to machine learning models.</p></secti
 </nav>
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-<p>Generated by <a href="https://pdoc3.github.io/pdoc"><cite>pdoc</cite> 0.7.0</a>.</p>
+<p>Generated by <a href="https://pdoc3.github.io/pdoc"><cite>pdoc</cite> 0.7.5</a>.</p>
 </footer>
 <script src="https://cdnjs.cloudflare.com/ajax/libs/highlight.js/9.12.0/highlight.min.js"></script>
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--- a/0.2/api/miplearn/solvers/tests/test_internal_solver.html
+++ b/0.2/api/miplearn/solvers/tests/test_internal_solver.html
@@ -3,7 +3,7 @@
 <head>
 <meta charset="utf-8">
 <meta name="viewport" content="width=device-width, initial-scale=1, minimum-scale=1" />
-<meta name="generator" content="pdoc 0.7.0" />
+<meta name="generator" content="pdoc 0.7.5" />
 <title>miplearn.solvers.tests.test_internal_solver API documentation</title>
 <meta name="description" content="" />
 <link href='https://cdnjs.cloudflare.com/ajax/libs/normalize/8.0.0/normalize.min.css' rel='stylesheet'>
@@ -535,7 +535,7 @@ def test_iteration_cb():
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-<p>Generated by <a href="https://pdoc3.github.io/pdoc"><cite>pdoc</cite> 0.7.0</a>.</p>
+<p>Generated by <a href="https://pdoc3.github.io/pdoc"><cite>pdoc</cite> 0.7.5</a>.</p>
 </footer>
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--- a/0.2/api/miplearn/solvers/tests/test_lazy_cb.html
+++ b/0.2/api/miplearn/solvers/tests/test_lazy_cb.html
@@ -3,7 +3,7 @@
 <head>
 <meta charset="utf-8">
 <meta name="viewport" content="width=device-width, initial-scale=1, minimum-scale=1" />
-<meta name="generator" content="pdoc 0.7.0" />
+<meta name="generator" content="pdoc 0.7.5" />
 <title>miplearn.solvers.tests.test_lazy_cb API documentation</title>
 <meta name="description" content="" />
 <link href='https://cdnjs.cloudflare.com/ajax/libs/normalize/8.0.0/normalize.min.css' rel='stylesheet'>
@@ -111,7 +111,7 @@ def test_lazy_cb():
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 <footer id="footer">
-<p>Generated by <a href="https://pdoc3.github.io/pdoc"><cite>pdoc</cite> 0.7.0</a>.</p>
+<p>Generated by <a href="https://pdoc3.github.io/pdoc"><cite>pdoc</cite> 0.7.5</a>.</p>
 </footer>
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--- a/0.2/api/miplearn/solvers/tests/test_learning_solver.html
+++ b/0.2/api/miplearn/solvers/tests/test_learning_solver.html
@@ -3,7 +3,7 @@
 <head>
 <meta charset="utf-8">
 <meta name="viewport" content="width=device-width, initial-scale=1, minimum-scale=1" />
-<meta name="generator" content="pdoc 0.7.0" />
+<meta name="generator" content="pdoc 0.7.5" />
 <title>miplearn.solvers.tests.test_learning_solver API documentation</title>
 <meta name="description" content="" />
 <link href='https://cdnjs.cloudflare.com/ajax/libs/normalize/8.0.0/normalize.min.css' rel='stylesheet'>
@@ -155,7 +155,17 @@ def test_simulate_perfect():
            simulate_perfect=True,
        )
        stats = solver.solve(tmp.name)
-        assert stats[&#34;Lower bound&#34;] == stats[&#34;Predicted LB&#34;]</code></pre>
+        assert stats[&#34;Lower bound&#34;] == stats[&#34;Predicted LB&#34;]
+
+
+def test_gap():
+    assert LearningSolver._compute_gap(ub=0.0, lb=0.0) == 0.0
+    assert LearningSolver._compute_gap(ub=1.0, lb=0.5) == 0.5
+    assert LearningSolver._compute_gap(ub=1.0, lb=1.0) == 0.0
+    assert LearningSolver._compute_gap(ub=1.0, lb=-1.0) is None
+    assert LearningSolver._compute_gap(ub=1.0, lb=None) is None
+    assert LearningSolver._compute_gap(ub=None, lb=1.0) is None
+    assert LearningSolver._compute_gap(ub=None, lb=None) is None</code></pre>
 </details>
 </section>
 <section>
@@ -165,6 +175,25 @@ def test_simulate_perfect():
 <section>
 <h2 class="section-title" id="header-functions">Functions</h2>
 <dl>
+<dt id="miplearn.solvers.tests.test_learning_solver.test_gap"><code class="name flex">
+<span>def <span class="ident">test_gap</span></span>(<span>)</span>
+</code></dt>
+<dd>
+<section class="desc"></section>
+<details class="source">
+<summary>
+<span>Expand source code</span>
+</summary>
+<pre><code class="python">def test_gap():
+    assert LearningSolver._compute_gap(ub=0.0, lb=0.0) == 0.0
+    assert LearningSolver._compute_gap(ub=1.0, lb=0.5) == 0.5
+    assert LearningSolver._compute_gap(ub=1.0, lb=1.0) == 0.0
+    assert LearningSolver._compute_gap(ub=1.0, lb=-1.0) is None
+    assert LearningSolver._compute_gap(ub=1.0, lb=None) is None
+    assert LearningSolver._compute_gap(ub=None, lb=1.0) is None
+    assert LearningSolver._compute_gap(ub=None, lb=None) is None</code></pre>
+</details>
+</dd>
 <dt id="miplearn.solvers.tests.test_learning_solver.test_learning_solver"><code class="name flex">
 <span>def <span class="ident">test_learning_solver</span></span>(<span>)</span>
 </code></dt>
@@ -346,6 +375,7 @@ def test_simulate_perfect():
 </li>
 <li><h3><a href="#header-functions">Functions</a></h3>
 <ul class="">
+<li><code><a title="miplearn.solvers.tests.test_learning_solver.test_gap" href="#miplearn.solvers.tests.test_learning_solver.test_gap">test_gap</a></code></li>
 <li><code><a title="miplearn.solvers.tests.test_learning_solver.test_learning_solver" href="#miplearn.solvers.tests.test_learning_solver.test_learning_solver">test_learning_solver</a></code></li>
 <li><code><a title="miplearn.solvers.tests.test_learning_solver.test_parallel_solve" href="#miplearn.solvers.tests.test_learning_solver.test_parallel_solve">test_parallel_solve</a></code></li>
 <li><code><a title="miplearn.solvers.tests.test_learning_solver.test_simulate_perfect" href="#miplearn.solvers.tests.test_learning_solver.test_simulate_perfect">test_simulate_perfect</a></code></li>
@@ -357,7 +387,7 @@ def test_simulate_perfect():
 </nav>
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-<p>Generated by <a href="https://pdoc3.github.io/pdoc"><cite>pdoc</cite> 0.7.0</a>.</p>
+<p>Generated by <a href="https://pdoc3.github.io/pdoc"><cite>pdoc</cite> 0.7.5</a>.</p>
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