Repository: N-Wouda/ALNS (language: python)

Issue:
Integrate with MABWiser library
In https://github.com/openjournals/joss-reviews/issues/5028, @skadio wrote:

> Inspired by your alpha-UCB policy in ALNS, let me add one potential integration opportunity for future.
> 
> Similar to the UCB policy, other Bandit policies can be considered when selecting operators, for instance Thompson Sampling.
> 
> In that regard, the [MABWiser library](https://github.com/fidelity/mabwiser#quick-start) that offers a comprehensive set of policies would neatly work as the Selection operator. Disclaimer: the library is built within our group in the AI Center at Fidelity.
> 
> The idea is to enable the "select" parameter to be MABWiser object which implements a variety of Bandit policies.
> 
> So the current UCB policy
> 
> ```
> select = AlphaUCB(scores=[5, 2, 1, 0.5], alpha=0.05), num_repair, num_destroy)
> ```
> 
> becomes
> 
> ```
> select = AlphaUCB(scores=[5, 2, 1, 0.5], MABWiser(arms=num_repair * num_destroy, LearningPolicy.UCB1(alpha=0.05)
> ```
> 
> Under the hood, ALNS leverages the expected reward and arm prediction computations from MABWiser.
> 
> In principle, the user can select _**any available bandit policy**_. In that sense, AlphaUCB becomes `BanditALNS(scores, MABWiser)`
> 
> Btw, it might be worthwhile considering Thompson Sampling (TS) Bandits which is a common counterpart to UCB policies, and often outperforms it.
> 
> It would look like this:
> 
> ```
> select = BanditALNS(scores=[1, 1, 1, 0], MABWiser(arms=num_repair * num_destroy, LearningPolicy.ThompsonSampling())
> ```
> 
> The reward for TS is binary. Here I used 1 for best, better, and accepted solutions and 0 for rejected solutions. The 0/1 scoring schema for TS would be easier to tune than UCB where it is not clear how to pick _reasonable_ defaults.
> 
> Finally, both UCB and LS are **non-contextual** policies. Moving beyond them, one could also consider **contextual policies**, where a set of features that describes that current state (neighborhood) help decide the arm selection. I am not aware of any research that considers contextual bandit policies for ALNS --this would be super cool! MABWiser supports all of these, and more.

I think this could be a great future opportunity, so I am opening this issue to not forget about it in the meantime.


Discussion / hints:
Quick update on this direction 

Paul, a CS student from Brown University, is about to finalize her senior thesis to enable ALNS + MABWiser integration. For some reason, I cannot tag his git alias here. 

We can open a PR for your review soon in a few weeks. Basically, it follows the Operator Selection base class interface and introduces a BanditSelector that can be any bandit policy coming from MABWiser. So UCB is just one of them, there are may others now that would be available to any user that chooses the BanditSelector as the selection schema. 



@skadio great, thanks for the update! I'm looking forward to the PR in a few weeks.


Fix patch:
diff --git a/alns/State.py b/alns/State.py
index 2268c054..a9098c2c 100644
--- a/alns/State.py
+++ b/alns/State.py
@@ -1,5 +1,7 @@
 from typing import Protocol
 
+import numpy as np
+
 
 class State(Protocol):
     """
@@ -11,3 +13,21 @@ def objective(self) -> float:
         """
         Computes the state's associated objective value.
         """
+
+
+class ContextualState(Protocol):
+    """
+    Protocol for a solution state that also provides context. Solutions should
+    define an ``objective()`` function as well as a ``get_context()``
+    function.
+    """
+
+    def objective(self) -> float:
+        """
+        Computes the state's associated objective value.
+        """
+
+    def get_context(self) -> np.ndarray:
+        """
+        Computes a context vector for the current state
+        """
diff --git a/alns/select/MABSelector.py b/alns/select/MABSelector.py
new file mode 100644
index 00000000..096ee576
--- /dev/null
+++ b/alns/select/MABSelector.py
@@ -0,0 +1,191 @@
+from typing import List, Optional, Tuple
+
+import numpy as np
+from numpy.random import RandomState
+
+from alns.Outcome import Outcome
+from alns.State import ContextualState
+from alns.select.OperatorSelectionScheme import OperatorSelectionScheme
+
+MABWISER_AVAILABLE = True
+try:
+    from mabwiser.mab import MAB, LearningPolicy, NeighborhoodPolicy
+except ModuleNotFoundError:
+    MABWISER_AVAILABLE = False
+
+
+class MABSelector(OperatorSelectionScheme):
+    """
+    A selector that uses any multi-armed-bandit algorithm from MABWiser.
+
+    This selector is a wrapper around the many multi-armed bandit algorithms
+    available in the `MABWiser <https://github.com/fidelity/mabwiser>`_
+    library. Since ALNS operator selection can be framed as a
+    multi-armed-bandit problem (where each [destroy, repair] operator pair is
+    a bandit arm), this wrapper allows you to use a variety of existing
+    multi-armed-bandit algorithms as operator selectors instead of
+    having to reimplement them.
+
+    Note that if the provided learning policy is a contextual bandit
+    algorithm, your state class must provide a `get_context` function that
+    returns a context vector for the current state.
+
+    Parameters
+    ----------
+    scores
+        A list of four non-negative elements, representing the rewards when the
+        candidate solution results in a new global best (idx 0), is better than
+        the current solution (idx 1), the solution is accepted (idx 2), or
+        rejected (idx 3).
+    num_destroy
+        Number of destroy operators.
+    num_repair
+        Number of repair operators.
+    learning_policy
+        A MABWiser learning policy that acts as an operator selector. See the
+        MABWiser documentation for a list of available learning policies.
+    neighborhood_policy
+        The neighborhood policy that MABWiser should use. Only available for
+        contextual learning policies. See the MABWiser documentation for a
+        list of available neighborhood policies.
+    seed
+        A seed that will be passed to the underlying MABWiser object.
+    op_coupling
+        Optional boolean matrix that indicates coupling between destroy and
+        repair operators. Entry (i, j) is True if destroy operator i can be
+        used together with repair operator j, and False otherwise.
+
+    References
+    ----------
+    .. [1] Emily Strong, Bernard Kleynhans, & Serdar Kadioglu (2021).
+           MABWiser: Parallelizable Contextual Multi-armed Bandits.
+           Int. J. Artif. Intell. Tools, 30(4), 2150021:1–2150021:19.
+    """
+
+    def __init__(
+        self,
+        scores: List[float],
+        num_destroy: int,
+        num_repair: int,
+        learning_policy: "LearningPolicy",
+        neighborhood_policy: Optional["NeighborhoodPolicy"] = None,
+        seed: Optional[int] = None,
+        op_coupling: Optional[np.ndarray] = None,
+        **kwargs,
+    ):
+        if not MABWISER_AVAILABLE:
+            raise ImportError("MABSelector requires the MABWiser library. ")
+
+        super().__init__(num_destroy, num_repair, op_coupling)
+
+        if any(score < 0 for score in scores):
+            raise ValueError("Negative scores are not understood.")
+
+        if len(scores) < 4:
+            # More than four is OK because we only use the first four.
+            raise ValueError(f"Expected four scores, found {len(scores)}")
+
+        # forward the seed argument if not null
+        if seed is not None:
+            kwargs["seed"] = seed
+
+        # the set of valid operator pairs (arms) is equal to the cartesian
+        # product of destroy and repair operators, except we leave out any
+        # pairs disallowed by op_coupling
+        arms = [
+            f"{d_idx}_{r_idx}"
+            for d_idx in range(num_destroy)
+            for r_idx in range(num_repair)
+            if self._op_coupling[d_idx, r_idx]
+        ]
+        self._mab = MAB(
+            arms,
+            learning_policy,
+            neighborhood_policy,
+            **kwargs,
+        )
+        self._scores = scores
+
+    @property
+    def scores(self) -> List[float]:
+        return self._scores
+
+    @property
+    def mab(self) -> "MAB":
+        return self._mab
+
+    def __call__(  # type: ignore[override]
+        self,
+        rnd_state: RandomState,
+        best: ContextualState,
+        curr: ContextualState,
+    ) -> Tuple[int, int]:
+        """
+        Returns the (destroy, repair) operator pair from the underlying MAB
+        strategy
+        """
+        if self._mab._is_initial_fit:
+            has_context = self._mab.is_contextual
+            context = (
+                np.atleast_2d(curr.get_context()) if has_context else None
+            )
+            prediction = self._mab.predict(contexts=context)
+            return arm2ops(prediction)
+        else:
+            # This can happen when the MAB object has not yet been fit on any
+            # observations. In that case we return any feasible operator index
+            # pair as a first observation.
+            allowed = np.argwhere(self._op_coupling)
+            idx = rnd_state.randint(len(allowed))
+            return (allowed[idx][0], allowed[idx][1])
+
+    def update(  # type: ignore[override]
+        self,
+        cand: ContextualState,
+        d_idx: int,
+        r_idx: int,
+        outcome: Outcome,
+    ):
+        """
+        Updates the underlying MAB algorithm given the reward of the chosen
+        destroy and repair operator combination ``(d_idx, r_idx)``.
+        """
+        has_context = self._mab.is_contextual
+        context = np.atleast_2d(cand.get_context()) if has_context else None
+
+        self._mab.partial_fit(
+            [ops2arm(d_idx, r_idx)],
+            [self._scores[outcome]],
+            contexts=context,
+        )
+
+
+def ops2arm(destroy_idx: int, repair_idx: int) -> str:
+    """
+    Converts a tuple of destroy and repair operator indices to an arm
+    string that can be passed to self._mab.
+
+    Examples
+    --------
+    >>> ops2arm(0, 1)
+    "0_1"
+    >>> ops2arm(12, 3)
+    "12_3"
+    """
+    return f"{destroy_idx}_{repair_idx}"
+
+
+def arm2ops(arm: str) -> Tuple[int, int]:
+    """
+    Converts an arm string returned from self._mab to a tuple of destroy
+    and repair operator indices.
+
+    Examples
+    --------
+    >>> arm2ops("0_1")
+    (0, 1)
+    >>> arm2ops("12_3")
+    (12, 3)
+    """
+    [destroy, repair] = arm.split("_")
+    return int(destroy), int(repair)
diff --git a/alns/select/__init__.py b/alns/select/__init__.py
index 9b405bc0..1e9547b2 100644
--- a/alns/select/__init__.py
+++ b/alns/select/__init__.py
@@ -1,4 +1,5 @@
 from .AlphaUCB import AlphaUCB
+from .MABSelector import MABSelector
 from .OperatorSelectionScheme import OperatorSelectionScheme
 from .RandomSelect import RandomSelect
 from .RouletteWheel import RouletteWheel
diff --git a/docs/source/api/select.rst b/docs/source/api/select.rst
index 5f5b6c6c..17c11a8d 100644
--- a/docs/source/api/select.rst
+++ b/docs/source/api/select.rst
@@ -16,6 +16,9 @@ All operator selection schemes inherit from :class:`~alns.select.OperatorSelecti
 .. automodule:: alns.select.AlphaUCB
    :members:
 
+.. automodule:: alns.select.MABSelector
+   :members:
+
 .. automodule:: alns.select.RandomSelect
    :members:
 
diff --git a/examples/alns_features.ipynb b/examples/alns_features.ipynb
index 1b990bd1..3dee3a24 100644
--- a/examples/alns_features.ipynb
+++ b/examples/alns_features.ipynb
@@ -2,22 +2,23 @@
  "cells": [
   {
    "cell_type": "code",
-   "execution_count": 1,
+   "execution_count": 44,
    "metadata": {},
    "outputs": [],
    "source": [
     "import matplotlib.pyplot as plt\n",
     "import numpy as np\n",
+    "from mabwiser.mab import LearningPolicy\n",
     "\n",
     "from alns import ALNS\n",
     "from alns.accept import *\n",
     "from alns.select import *\n",
-    "from alns.stop import *"
+    "from alns.stop import *\n"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 2,
+   "execution_count": 45,
    "metadata": {
     "pycharm": {
      "name": "#%%\n"
@@ -30,7 +31,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 3,
+   "execution_count": 46,
    "metadata": {
     "pycharm": {
      "name": "#%%\n"
@@ -43,7 +44,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 4,
+   "execution_count": 47,
    "metadata": {
     "pycharm": {
      "name": "#%%\n"
@@ -55,6 +56,7 @@
    ]
   },
   {
+   "attachments": {},
    "cell_type": "markdown",
    "metadata": {
     "pycharm": {
@@ -77,7 +79,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 5,
+   "execution_count": 48,
    "metadata": {
     "pycharm": {
      "name": "#%%\n"
@@ -96,7 +98,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 6,
+   "execution_count": 49,
    "metadata": {
     "pycharm": {
      "name": "#%%\n"
@@ -122,6 +124,7 @@
    ]
   },
   {
+   "attachments": {},
    "cell_type": "markdown",
    "metadata": {
     "pycharm": {
@@ -139,7 +142,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 7,
+   "execution_count": 50,
    "metadata": {
     "pycharm": {
      "name": "#%%\n"
@@ -153,7 +156,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 8,
+   "execution_count": 51,
    "metadata": {
     "pycharm": {
      "name": "#%%\n"
@@ -173,7 +176,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 9,
+   "execution_count": 52,
    "metadata": {
     "pycharm": {
      "name": "#%%\n"
@@ -194,6 +197,7 @@
    ]
   },
   {
+   "attachments": {},
    "cell_type": "markdown",
    "metadata": {
     "pycharm": {
@@ -208,7 +212,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 10,
+   "execution_count": 53,
    "metadata": {
     "pycharm": {
      "name": "#%%\n"
@@ -232,6 +236,7 @@
    ]
   },
   {
+   "attachments": {},
    "cell_type": "markdown",
    "metadata": {
     "pycharm": {
@@ -244,7 +249,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 11,
+   "execution_count": 54,
    "metadata": {
     "pycharm": {
      "name": "#%%\n"
@@ -266,7 +271,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 12,
+   "execution_count": 55,
    "metadata": {
     "pycharm": {
      "name": "#%%\n"
@@ -281,6 +286,7 @@
    ]
   },
   {
+   "attachments": {},
    "cell_type": "markdown",
    "metadata": {
     "pycharm": {
@@ -297,7 +303,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 13,
+   "execution_count": 56,
    "metadata": {
     "pycharm": {
      "name": "#%%\n"
@@ -309,6 +315,7 @@
    ]
   },
   {
+   "attachments": {},
    "cell_type": "markdown",
    "metadata": {
     "pycharm": {
@@ -335,7 +342,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 14,
+   "execution_count": 57,
    "metadata": {
     "pycharm": {
      "name": "#%%\n"
@@ -364,7 +371,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 15,
+   "execution_count": 58,
    "metadata": {
     "pycharm": {
      "name": "#%%\n"
@@ -373,7 +380,7 @@
    "outputs": [
     {
      "data": {
-      "image/png": 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\n",
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tW7ZIktasWaOffvpJN954oySuUZQvZXk9lud/9xMEWFBGRoby8vIc/oNVkiIiIpSenu6mqmAF+fn5Gjx4sK6++mo1atRIkpSeni4fHx+FhIQ4tC18Paanpxd7vRZsO1ebnJwcHT9+3BWngwrkww8/1MqVKzVhwoQi27hG4W47duzQ66+/rri4OC1atEj9+vXTwIEDNXv2bEl/XWPn+vd6enq6wsPDHbZ7eXmpatWqpbqOgeIMHz5cd911lxo0aCBvb281adJEgwcPVo8ePSRxjaJ8Kcvr8WxtysP16uXuAgBYR//+/bVu3Tr99NNP7i4FsNuzZ48GDRqk5ORk+fn5ubscoIj8/Hw1b95czz33nCSpSZMmWrdunWbMmKGePXu6uTpAmjt3rt577z29//77uuKKK7R69WoNHjxYUVFRXKNAOUWPAAsKDQ2Vp6dnkRGv9+/fr8jISDdVhYpuwIAB+uKLL/Tdd9+pZs2a9vWRkZHKzc1VVlaWQ/vC12NkZGSx12vBtnO1CQoKkr+/v7NPBxXIihUrdODAATVt2lReXl7y8vLS999/r6lTp8rLy0sRERFco3Cr6tWrq2HDhg7rLr/8cu3evVvSX9fYuf69HhkZqQMHDjhsP336tDIzM0t1HQPFeeyxx+y9AuLj43XPPfdoyJAh9l5WXKMoT8ryejxbm/JwvRIEWJCPj4+aNWumlJQU+7r8/HylpKQoISHBjZWhIjLGaMCAAfr000/17bffKjY21mF7s2bN5O3t7XA9bt68Wbt377ZfjwkJCfrtt98c/g85OTlZQUFB9v84TkhIcNhHQRuuaZzPddddp99++02rV6+2v5o3b64ePXrY33ONwp2uvvrqItOubtmyRbVr15YkxcbGKjIy0uH6ysnJ0bJlyxyu0aysLK1YscLe5ttvv1V+fr5atmxpb/PDDz/o1KlT9jbJycmqX7++qlSp4rLzw6Xv2LFj8vBwvK3w9PRUfn6+JK5RlC9leT2W63/3u3u0QrjHhx9+aHx9fc2sWbPMhg0bTN++fU1ISIjDiNeAM/Tr188EBwebxYsXm3379tlfx44ds7d56KGHTK1atcy3335rfv31V5OQkGASEhLs2wumZrvhhhvM6tWrzcKFC01YWFixU7M99thjZuPGjWb69OlMzYYLVnjWAGO4RuFev/zyi/Hy8jLjx483W7duNe+9954JCAgw//nPf+xtnn/+eRMSEmI+++wzs3btWnPrrbcWOxVWkyZNzLJly8xPP/1k4uLiHKbCysrKMhEREeaee+4x69atMx9++KEJCAhgajacV8+ePU2NGjXs0wd+8sknJjQ01Dz++OP2NlyjKEuHDx82q1atMqtWrTKSzEsvvWRWrVpldu3aZYwpu+txyZIlxsvLy7z44otm48aNZsyYMUwfCPebNm2aqVWrlvHx8TEtWrQwP//8s7tLQgUkqdjXzJkz7W2OHz9uHn74YVOlShUTEBBgbrvtNrNv3z6H/ezcudPceOONxt/f34SGhpphw4aZU6dOObT57rvvTOPGjY2Pj4+pU6eOwzGA0vh7EMA1Cnf773//axo1amR8fX1NgwYNzJtvvumwPT8/34waNcpEREQYX19fc91115nNmzc7tPnzzz9N9+7dTWBgoAkKCjK9e/c2hw8fdmizZs0a06ZNG+Pr62tq1Khhnn/+eZefGy59OTk5ZtCgQaZWrVrGz8/P1KlTxzz11FMO06pxjaIsfffdd8X+92fPnj2NMWV7Pc6dO9dcdtllxsfHx1xxxRVmwYIFLjvv0rAZY4x7+iIAAAAAAICyxhgBAAAAAABYCEEAAAAAAAAWQhAAAAAAAICFEAQAAAAAAGAhBAEAAAAAAFgIQQAAAAAAABZCEAAAAAAAgIUQBAAAAAAAYCEEAQAAwK1iYmL08ssvl8mx7rnnHj333HMX9NmMjAyFh4fr999/d3JVAACULYIAAAAsolevXurSpYt9uX379ho8eHCZHX/WrFkKCQkpsn758uXq27evy4+/Zs0affnllxo4cGCx25cvX66oqChJ0h9//CF/f3/l5ubat4eGhuree+/VmDFjXF4rAACuRBAAAAAuSuGb5QsRFhamgIAAJ1VzdtOmTdOdd96pwMDAYrenpqbq6quvliT9+OOPat68uXx8fBza9O7dW++9954yMzNdXi8AAK5CEAAAgAX16tVL33//vV555RXZbDbZbDbt3LlTkrRu3TrdeOONCgwMVEREhO655x5lZGTYP9u+fXsNGDBAgwcPVmhoqJKSkiRJL730kuLj41WpUiVFR0fr4Ycf1pEjRyRJixcvVu/evZWdnW0/3tixYyUVfTRg9+7duvXWWxUYGKigoCB17dpV+/fvt28fO3asGjdurH//+9+KiYlRcHCw7rrrLh0+fPis55uXl6ePPvpIN99881nbLF261B4E/PTTT/b3hV1xxRWKiorSp59+eu4vGACAcowgAAAAC3rllVeUkJCgBx54QPv27dO+ffsUHR2trKwsXXvttWrSpIl+/fVXLVy4UPv371fXrl0dPj979mz5+PhoyZIlmjFjhiTJw8NDU6dO1fr16zV79mx9++23evzxxyVJrVu31ssvv6ygoCD78R599NEideXn5+vWW29VZmamvv/+eyUnJ2vHjh3q1q2bQ7vt27dr/vz5+uKLL/TFF1/o+++/1/PPP3/W8127dq2ys7PVvHlzh/U//fSTQkJCFBISoo8++khPPfWUQkJCNGPGDE2dOlUhISFF9tuiRQv9+OOPJf+yAQAoZ7zcXQAAACh7wcHB8vHxUUBAgCIjI+3rX331VTVp0sRhQL133nlH0dHR2rJliy677DJJUlxcnCZOnOiwz8LjDcTExOjZZ5/VQw89pNdee00+Pj4KDg6WzWZzON7fpaSk6LffflNaWpqio6MlSe+++66uuOIKLV++XFdddZWkM4HBrFmzVLlyZUlnBgFMSUnR+PHji93vrl275OnpqfDwcIf1zZs31+rVq7Vp0ybdfffdWrFihTIzM9W6dWutXLlSfn5+RcY1iIqK0qpVq856DgAAlHf0CAAAAHZr1qzRd999p8DAQPurQYMGks78Fb5As2bNinz2m2++0XXXXacaNWqocuXKuueee/Tnn3/q2LFjJT7+xo0bFR0dbQ8BJKlhw4YKCQnRxo0b7etiYmLsIYAkVa9eXQcOHDjrfo8fPy5fX1/ZbDaH9X5+foqJidHatWt14403KjY2Vps2bVLbtm3VoEEDxcTEFAkC/P39S3VOAACUN/QIAAAAdkeOHNHNN9+sF154oci26tWr299XqlTJYdvOnTvVuXNn9evXT+PHj1fVqlX1008/qU+fPsrNzXX6YIDe3t4OyzabTfn5+WdtHxoaqmPHjik3N9dhAMCCgQNPnjwpDw8PffbZZ8rNzZUxRoGBgWrbtq2++uorh31lZmYqLCzMiWcDAEDZIggAAMCifHx8lJeX57CuadOm+vjjjxUTEyMvr5L/Z8KKFSuUn5+vyZMny8PjTIfDuXPnnvd4f3f55Zdrz5492rNnj71XwIYNG5SVlaWGDRuWuJ6/a9y4sX1fBe8lafXq1Tp9+rQaN26sb775RpGRkWrbtq1ee+01xcfHy9/fv8i+1q1bp/bt219wLQAAuBuPBgAAYFExMTFatmyZdu7cqYyMDOXn56t///7KzMxU9+7dtXz5cm3fvl2LFi1S7969z3kTX69ePZ06dUrTpk3Tjh079O9//9s+iGDh4x05ckQpKSnKyMgotnt9YmKi4uPj1aNHD61cuVK//PKL7r33Xl1zzTVFBvorjbCwMDVt2lQ//fRTkbqzsrIUERGhNm3ayMfHR4cPH9bNN9+sevXqqUaNGg7tjx07phUrVuiGG2644FoAAHA3ggAAACzq0Ucflaenpxo2bKiwsDDt3r1bUVFRWrJkifLy8nTDDTcoPj5egwcPVkhIiP0v/cW58sor9dJLL+mFF15Qo0aN9N5772nChAkObVq3bq2HHnpI3bp1U1hYWJHBBqUzXfw/++wzValSRe3atVNiYqLq1KmjOXPmXPT53n///XrvvfeKrF+8eLHatWsnSfr++++VkJBw1t4Qn332mWrVqqW2bdtedD0AALiLzRhj3F0EAACAqx0/flz169fXnDlzlJCQcEH7aNWqlQYOHKi7777bydUBAFB26BEAAAAswd/fX++++64yMjIu6PMZGRm6/fbb1b17dydXBgBA2aJHAAAAAAAAFkKPAAAAAAAALIQgAAAAAAAACyEIAAAAAADAQggCAAAAAACwEIIAAAAAAAAshCAAAAAAAAALIQgAAAAAAMBCCAIAAAAAALAQggAAAAAAACzk/wH528igp6NHPQAAAABJRU5ErkJggg==",
       "text/plain": [
        "<Figure size 1200x600 with 1 Axes>"
       ]
@@ -388,6 +395,7 @@
    ]
   },
   {
+   "attachments": {},
    "cell_type": "markdown",
    "metadata": {
     "pycharm": {
@@ -404,7 +412,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 16,
+   "execution_count": 59,
    "metadata": {
     "pycharm": {
      "name": "#%%\n"
@@ -434,7 +442,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 17,
+   "execution_count": 60,
    "metadata": {
     "pycharm": {
      "name": "#%%\n"
@@ -443,7 +451,7 @@
    "outputs": [
     {
      "data": {
-      "image/png": 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xRj344IPKzMyUw+GQ0+nUDz/8oPvuu0+33nqrJ2oEAAAAAABuUuYg4IknnlCjRo0UFxenw4cPq3HjxurUqZPat2+vMWPGeKJGeByDBQIAAACAXfiV9QMBAQF6/fXXNXbsWK1du1aHDx9WixYtlJiY6In64EHc/gMAAACA/ZQ5CChUt25d1a1b1521AAAAAAAADytzEHDbbbeddfubb755zsUAAAAAAADPKnMQcPDgQZf3J0+e1Nq1a5WTk6N//vOfbisMAAAAAAC4X5mDgI8++qjYOqfTqcGDB6tBgwZuKQrly2EYLQAAAAAA7KLMswaUuBMfH40YMULPPfecO3aHcmLk8HYJAAAAAIBy5pYgQJK2bt2qU6dOuWt3AAAAAADAA8r8aMCIESNc3htjtHfvXn322Wfq16+f2woDAAAAAADuV+YgYOXKlS7vfXx8FBUVpWeeeeYvZxQAAAAAAADeVeYg4Ouvv/ZEHfAiRgoAAAAAAPtw2xgBqHgYLBAAAAAA7KdUPQJatGghh6N0N40rVqz4WwUBAAAAAADPKVUQ0LNnTw+XAQAAAAAAykOpgoDx48d7ug4AAAAAAFAOGCMAAAAAAAAbKfOsAQUFBXruuec0Z84c7dy5U/n5+S7bs7Oz3VYcyovxdgEAAAAAgHJS5h4BjzzyiJ599ln16dNHubm5GjFihK6//nr5+PhowoQJHigRAAAAAAC4S5mDgLfffluvv/66Ro4cKT8/P/Xt21dvvPGGxo0bpyVLlniiRgAAAAAA4CZlDgIyMzPVrFkzSVJoaKhyc3MlST169NBnn33m3uoAAAAAAIBblTkIqFOnjvbu3StJatCggb744gtJ0rJlyxQYGOje6gAAAAAAgFuVOQi47rrrlJ6eLkm65557NHbsWCUmJurWW2/Vbbfd5vYC4XkOBgsEAAAAANso86wBTz75pLXcp08f1atXT4sXL1ZiYqKuvvpqtxYHzzJyeLsEAAAAAEA5K3MQcPz4cQUFBVnv27Vrp3bt2rm1KAAAAAAA4BllfjSgZs2a6tevn9LS0uR0Oj1REwAAAAAA8JAyBwGzZs3S0aNHde2116p27dpKTU3VTz/95InaAAAAAACAm53TYIFz587Vvn379MQTT2j9+vVq166dLrjgAj366KOeqBEex2CBAAAAAGAXZQ4CClWtWlUDBgzQF198oTVr1qhKlSp65JFH3FkbPIzBAgEAAADAfs45CDh+/LjmzJmjnj17qmXLlsrOztb999/vztoAAAAAAICblXnWgIULF+qdd97RvHnz5Ofnp3/961/64osv1KlTJ0/UBwAAAAAA3KjMQcB1112nHj166K233tJVV10lf39/T9QFAAAAAAA8oMxBwL59+1S1alVP1AIvYaQAAAAAALCPMo8RQAhQeTBXAAAAAADYzzkPFggAAAAAACoeggAAAAAAAGyEIAAAAAAAABs55yBgy5YtWrhwoY4dOyZJMoYnzisufjsAAAAAsIsyBwG///67kpOTdcEFF+iqq67S3r17JUkDBw7UyJEj3V4gPMc4mC8AAAAAAOymzEHAvffeKz8/P+3cuVMhISHW+j59+mjBggVuLQ4AAAAAALiXX1k/8MUXX2jhwoWqU6eOy/rExETt2LHDbYUBAAAAAAD3K3OPgCNHjrj0BCiUnZ2twMBAtxQFAAAAAAA8o8xBQMeOHfXWW29Z7x0Oh5xOpyZPnqwuXbq4tTgAAAAAAOBeZX40YPLkybr88sv1008/KT8/Xw888IDWrVun7Oxs/fDDD56oER7mYNYAAAAAALCNMvcIaNq0qTZt2qQOHTro2muv1ZEjR3T99ddr5cqVatCggSdqhMcwawAAAAAA2E2ZewRIUnh4uB5++GF31wIAAAAAADyszD0CGjZsqAkTJmjz5s2eqAcAAAAAAHhQmYOAIUOG6LPPPtOFF16oSy65RC+88IIyMzM9UZuLiRMnqn379goJCVFERESJbRwOR7HXe++959Jm0aJFatmypQIDA9WwYUPNnDmz2H5eeuklxcfHKygoSG3bttWPP/7ogTMCAAAAAKD8lTkIuPfee7Vs2TJt3LhRV111lV566SXFxcWpa9euLrMJuFt+fr569eqlwYMHn7XdjBkztHfvXuvVs2dPa9u2bdvUvXt3denSRatWrVJqaqpuv/12LVy40Goze/ZsjRgxQuPHj9eKFSt08cUXKyUlRfv37/fUqXmdwzBYIAAAAADYhcOYv38XuGTJEg0ePFhr1qxRQUGBO+o6o5kzZyo1NVU5OTnFtjkcDn300UcuN/9FPfjgg/rss8+0du1aa92NN96onJwcLViwQJLUtm1bXXLJJXrxxRclSU6nU3Fxcbrnnns0atSoEvd74sQJnThxwnqfl5enuLg45ebmKiws7BzP1PNyJ8QqXEe0yxGruPEbvF0OAAAAAOAc5eXlKTw8vFT3oWXuEVDUjz/+qNTUVF133XXatGmTevXq9Xd25xZDhgxRZGSk2rRpozfffFNFc46MjAwlJye7tE9JSVFGRoak070Oli9f7tLGx8dHycnJVpuSTJo0SeHh4dYrLi7OzWcFAAAAAIB7lDkI2LRpk8aPH68LLrhAl156qTZs2KCnnnpK+/btK/Y8fnl79NFHNWfOHKWlpemGG27Q3XffrWnTplnbMzMzFR0d7fKZ6Oho5eXl6dixY8rKylJBQUGJbc42DsLo0aOVm5trvXbt2uXeEwMAAAAAwE3KPH1go0aNdMkll2jIkCG68cYbi900l8WoUaP01FNPnbXNhg0b1KhRo1Ltb+zYsdZyixYtdOTIEU2ZMkXDhg075xpLIzAwUIGBgR49BgAAAAAA7lDmIOCXX35RYmKiWw4+cuRI9e/f/6xt6tevf877b9u2rR577DGdOHFCgYGBiomJ0b59+1za7Nu3T2FhYQoODpavr698fX1LbBMTE3POdQAAAAAAcL4ocxDgrhBAkqKiohQVFeW2/f3ZqlWrVK1aNeuv9UlJSZo/f75Lm7S0NCUlJUmSAgIC1KpVK6Wnp1sDDjqdTqWnp2vo0KEeq9NbjBzeLgEAAAAAUM5KFQRUr15dmzZtUmRkpKpVqyaH48w3kNnZ2W4rrqidO3cqOztbO3fuVEFBgVatWiVJatiwoUJDQ/Xf//5X+/btU7t27RQUFKS0tDQ98cQTuu+++6x93HXXXXrxxRf1wAMP6LbbbtNXX32lOXPm6LPPPrPajBgxQv369VPr1q3Vpk0bPf/88zpy5IgGDBjgkfMCAAAAAKA8lSoIeO6551S1alVr+WxBgKeMGzdOs2bNst63aNFCkvT111+rc+fO8vf310svvaR7771Xxhg1bNhQzz77rO644w7rMwkJCfrss89077336oUXXlCdOnX0xhtvKCUlxWrTp08fHThwQOPGjVNmZqaaN2+uBQsW/K2xEAAAAAAAOF84TNH59eAWZZm/0ZtyJtRWhA5rlyNWceM3eLscAAAAAMA5Kst9aJmnD/T19dX+/fuLrf/999/l6+tb1t3hPOAQWRAAAAAA2EWZg4AzdSA4ceKEAgIC/nZBKD8MFggAAAAA9lPqWQOmTp0qSXI4HHrjjTcUGhpqbSsoKNC3336rRo0aub9CAAAAAADgNqUOAp577jlJp3sETJ8+3eUxgICAAMXHx2v69OnurxAAAAAAALhNqYOAbdu2SZK6dOmiDz/8UNWqVfNYUShfdcxeb5cAAAAAACgnpQ4CCn399deeqANeduL4UQUGhXi7DAAAAACAh5V5sMAbbrhBTz31VLH1kydPVq9evdxSFMpHNR2ylg/u3+3FSgAAAAAA5aXMQcC3336rq666qtj6K6+8Ut9++61bikL5WFGlo7VsjNOLlQAAAAAAykuZg4DDhw+XOE2gv7+/8vLy3FIUyofx8f9j2VnytJAAAAAAgMqlzEFAs2bNNHv27GLr33vvPTVu3NgtRaF8GDn+WDYEAQAAAABgB2UeLHDs2LG6/vrrtXXrVv3zn/+UJKWnp+vdd9/V3Llz3V4gPMjhKPKGRwMAAAAAwA7KHARcffXVmjdvnp544gm9//77Cg4O1j/+8Q99+eWXuuyyyzxRIzzmjyDA6SQIAAAAAAA7KHMQIEndu3dX9+7d3V0LyplxFHkyhMECAQAAAMAWyjxGgCTl5OTojTfe0EMPPaTs7GxJ0ooVK7R7N1PQVSxFewQwRgAAAAAA2EGZewSsWbNGycnJCg8P1/bt23X77berevXq+vDDD7Vz50699dZbnqgTHkCPAAAAAACwnzL3CBgxYoT69++vzZs3KygoyFp/1VVX6dtvv3VrcSg/hiAAAAAAAGyhzEHAsmXLdOeddxZbX7t2bWVmZrqlKJSTIj0CmD4QAAAAAOyhzEFAYGCg8vLyiq3ftGmToqKi3FIUykmR6QMNswYAAAAAgC2UOQi45ppr9Oijj+rkyZOSJIfDoZ07d+rBBx/UDTfc4PYC4TmGHgEAAAAAYDtlDgKeeeYZHT58WDVr1tSxY8d02WWXqWHDhqpataomTpzoiRrhMUV7BBR4sQ4AAAAAQHkp86wB4eHhSktL0/fff681a9bo8OHDatmypZKTkz1RH8oNPQIAAAAAwA7KHAQU6tChgzp06ODOWlDeeDQAAAAAAGynVEHA1KlTNWjQIAUFBWnq1KlnbRsaGqomTZqobdu2bikQnsRggQAAAABgN6UKAp577jndfPPNCgoK0nPPPXfWtidOnND+/ft17733asqUKW4pEp5RdLBAHg0AAAAAAHsoVRCwbdu2EpfPJC0tTTfddBNBwPmuyPSBTgYLBAAAAABbKPOsAaXRoUMHjRkzxhO7hjsV7RHAGAEAAAAAYAvnFASkp6erR48eatCggRo0aKAePXroyy+/tLYHBwdr+PDhbisSnvJHjwAxRgAAAAAA2EKZg4CXX35Z3bp1U9WqVTV8+HANHz5cYWFhuuqqq/TSSy95okZ4StFZAxgjAAAAAABsoczTBz7xxBN67rnnNHToUGvdsGHDdOmll+qJJ57QkCFD3FogygezBgAAAACAPZS5R0BOTo66detWbH3Xrl2Vm5vrlqJQPozD949lxggAAAAAAFsocxBwzTXX6KOPPiq2/uOPP1aPHj3cUhTKSZEhAoxh1gAAAAAAsINSPRowdepUa7lx48aaOHGiFi1apKSkJEnSkiVL9MMPP2jkyJGeqRIe4pIEeK8MAAAAAEC5KVUQ8Nxzz7m8r1atmtavX6/169db6yIiIvTmm28ybWBFwvSBAAAAAGA7pQoCtm3b5uk64A2OP3oEGMNggQAAAABgB2UeI6BQVlaWsrKy3FkLyluRHgEncjK9WAgAAAAAoLyUKQjIycnRkCFDFBkZqejoaEVHRysyMlJDhw5VTk6Oh0qEpzjyj1jLJw9s9WIlAAAAAIDyUqpHAyQpOztbSUlJ2r17t26++WZddNFFkqT169dr5syZSk9P1+LFi1WtWjWPFQv38o2+SNp3etnhG+DdYgAAAAAA5aLUQcCjjz6qgIAAbd26VdHR0cW2de3aVY8++mixgQVx/gqsXsdaNgUnvFgJAAAAAKC8lPrRgHnz5unpp58uFgJIUkxMjCZPnqyPPvrIrcXBs3z9g/54U5DvvUIAAAAAAOWm1EHA3r171aRJkzNub9q0qTIzGXCuIvH1/+NxAAdBAAAAAADYQqmDgMjISG3fvv2M27dt26bq1au7oyaUE9+AP3oEEAQAAAAAgD2UOghISUnRww8/rPz84jeMJ06c0NixY9WtWze3FgfP8nMJAhgjAAAAAADsoEyDBbZu3VqJiYkaMmSIGjVqJGOMNmzYoJdfflknTpzQv//9b0/WCjcLCAqxln0IAgAAAADAFkodBNSpU0cZGRm6++67NXr0aBljJEkOh0NXXHGFXnzxRcXFxXmsULhfYFCotexbcNyLlQAAAAAAykupgwBJSkhI0Oeff66DBw9q8+bNkqSGDRsyNkAFFRDyRxDgd+qoFysBAAAAAJSXMgUBhapVq6Y2bdq4uxaUs+AiQUCzEytknE45fEo9bAQAAAAAoALirs/G/AMCXd7v3bnZS5UAAAAAAMoLQYDN7fD5Y1yHglNMIQgAAAAAlR1BgM3tC2tmLTtPEgQAAAAAQGVHEGB3Pr7WYkHBKS8WAgAAAAAoDwQBNmd8/K1lZ8FJL1YCAAAAACgPBAE2ZxxFegTwaAAAAAAAVHoEAXbn88cMkoZHAwAAAACg0iMIsLmijwYwRgAAAAAAVH4EAXZXZLBA5ynGCAAAAACAyo4gwO6KPBqQfzjLi4UAAAAAAMoDQYDNOfIPWcsnc/d5sRIAAAAAQHkgCLC78Dhr0eHrd5aGAAAAAIDKgCDA5vzCo61lc+qEFysBAAAAAJQHggCb8/ELspbNqXwvVgIAAAAAKA8EATbn6x/4xxt6BAAAAABApUcQYHMuQUABQQAAAAAAVHYVIgjYvn27Bg4cqISEBAUHB6tBgwYaP3688vNdu7KvWbNGHTt2VFBQkOLi4jR58uRi+5o7d64aNWqkoKAgNWvWTPPnz3fZbozRuHHjVKtWLQUHBys5OVmbN2/26Pl5k2/AH48GOOgRAAAAAACVXoUIAjZu3Cin06lXX31V69at03PPPafp06froYcestrk5eWpa9euqlevnpYvX64pU6ZowoQJeu2116w2ixcvVt++fTVw4ECtXLlSPXv2VM+ePbV27VqrzeTJkzV16lRNnz5dS5cuVZUqVZSSkqLjx4+X6zmXF4ej6CVgvFYHAAAAAKB8OIwxFfLub8qUKXrllVf066+/SpJeeeUVPfzww8rMzFRAQIAkadSoUZo3b542btwoSerTp4+OHDmiTz/91NpPu3bt1Lx5c02fPl3GGMXGxmrkyJG67777JEm5ubmKjo7WzJkzdeONN5aqtry8PIWHhys3N1dhYWHuPG232/hTuhp9er0kaUnN3mp39+terggAAAAAUFZluQ+tED0CSpKbm6vq1atb7zMyMtSpUycrBJCklJQU/fLLLzp48KDVJjk52WU/KSkpysjIkCRt27ZNmZmZLm3Cw8PVtm1bq01JTpw4oby8PJdXReGQ4483FTMTAgAAAACUQYUMArZs2aJp06bpzjvvtNZlZmYqOjrapV3h+8zMzLO2Kbq96OdKalOSSZMmKTw83HrFxcWd45mVP4eP7x/LPBoAAAAAAJWeV4OAUaNGyeFwnPVV2K2/0O7du9WtWzf16tVLd9xxh5cqdzV69Gjl5uZar127dnm7pFJzOIr2CHB6rxAAAAAAQLnw8+bBR44cqf79+5+1Tf369a3lPXv2qEuXLmrfvr3LIICSFBMTo3379rmsK3wfExNz1jZFtxeuq1Wrlkub5s2bn7HGwMBABQYGnnH7+czhUyE7hQAAAAAAzpFXg4CoqChFRUWVqu3u3bvVpUsXtWrVSjNmzJDPn25gk5KS9PDDD+vkyZPy9/eXJKWlpenCCy9UtWrVrDbp6elKTU21PpeWlqakpCRJUkJCgmJiYpSenm7d+Ofl5Wnp0qUaPHjw3zzb8xU9AgAAAADATirEn4N3796tzp07q27dunr66ad14MABZWZmujy3f9NNNykgIEADBw7UunXrNHv2bL3wwgsaMWKE1Wb48OFasGCBnnnmGW3cuFETJkzQTz/9pKFDh0o63U0+NTVVjz/+uD755BP9/PPPuvXWWxUbG6uePXuW92mXi6JjBDB9IAAAAABUfl7tEVBaaWlp2rJli7Zs2aI6deq4bCuc/TA8PFxffPGFhgwZolatWikyMlLjxo3ToEGDrLbt27fXO++8ozFjxuihhx5SYmKi5s2bp6ZNm1ptHnjgAR05ckSDBg1STk6OOnTooAULFigoKKh8TracFR0jwEGPAAAAAACo9BzGMGecu5Vl/kZv27Z+mRLmnJ4u8cdqPdRm+NterggAAAAAUFZluQ+tEI8GwHOYNQAAAAAA7IUgwOYcDi4BAAAAALAT7gLtrkgQwBgBAAAAAFD5EQTYXNEnA5g1AAAAAAAqP4IAm2P6QAAAAACwF4IAm3OI6QMBAAAAwE4IAmzOtUcAAAAAAKCyIwiwuaLTB9IjAAAAAAAqP4IAm3P4FB0tkDECAAAAAKCyIwiwOQfTBwIAAACArRAE2JzDp+glQI8AAAAAAKjsCAJsrmiPABmCAAAAAACo7AgCbM6n6KMB9AgAAAAAgEqPIMDuig4WyBgBAAAAAFDpEQTYnuOvmwAAAAAAKg2CAJvz8eHRAAAAAACwE4IAm2P6QAAAAACwF4IAmyvaIyDx6CodP3rYi9UAAAAAADyNIMDuivQICHGc0O9TWurUyXwvFgQAAAAA8CSCAJurUjVc+1Xdel/b7NPuLT97sSIAAAAAgCcRBNicn3+AjvaZ67Lu1MkTXqoGAAAAAOBpBAFQ/EWttSSql/W+4BSPBgAAAABAZUUQgNN8A6zFAnoEAAAAAEClRRAASZLx9beWCQIAAAAAoPIiCMBpRXoEOJk1AAAAAAAqLYIAnFakR8CJVXO8WAgAAAAAwJMIAiBJ8gmuZi37nTzsxUoAAAAAAJ5EEABJUnz764u8M16rAwAAAADgWQQBkCQFBYdayz7Ok16sBAAAAADgSQQBkCT5BQRay76GIAAAAAAAKiuCAEiS/Pz/mDXAxxR4sRIAAAAAgCcRBECS5O//R48AH+cpL1YCAAAAAPAkggBIknx8fXXKnL4capzK9HI1AAAAAABPIQiA5ZR8JUlROqifPnnFy9UAAAAAADyBIACWXEeYtez7y6derAQAAAAA4CkEAbD83u1la9nHme/FSgAAAAAAnkIQAEvdxm2tZQYMBAAAAIDKiSAAFv+AIjMHmJNerAQAAAAA4CkEAbAUnULQlx4BAAAAAFApEQTA4uPrq5Pm9MwBvvQIAAAAAIBKiSAALk7KT5KUWLBF29Yv83I1AAAAAAB3IwiAi3yHv7X8+4InvVgJAAAAAMATCALgYmODgdZy8PEDXqwEAAAAAOAJBAFw0fbmCSowDklSk/zVXq4GAAAAAOBuBAFw4fDx0RFHsPX+wJ7t3isGAAAAAOB2BAEoJkxHreWt86dq+fwZyj2Y5cWKAAAAAADuQhCAYpbUH2Ytt/vt/6nVj6nKm9pRzoICL1YFAAAAAHAHggAUE3Fhx2Lr4swe5Wbv90I1AAAAAAB38vN2ATj/NGrbVevNbOVtW6Hoze8pwblDkuR00iMAAAAAACo6egSgRI3bdVO7vg8pJ6iOtc4YpxcrAgAAAAC4A0EAzso4/rhEGCMAAAAAACo+ggCcncNhLfJoAAAAAABUfAQBOCvj8P1jmSAAAAAAACo8ggCclSlyiRin8WIlAAAAAAB3IAjA2RV9NKDglBcLAQAAAAC4A0EAzqroYIHG8GgAAAAAAFR0BAE4uyJjBDh5NAAAAAAAKjyCAJyV0R+PBojBAgEAAACgwiMIwNkVeTTA6WSMAAAAAACo6AgCcFbGJQjg0QAAAAAAqOgIAnB2RQcL5NEAAAAAAKjwCAJwdi6zBji9WAgAAAAAwB0IAnB29AgAAAAAgEqlQgQB27dv18CBA5WQkKDg4GA1aNBA48ePV35+vksbh8NR7LVkyRKXfc2dO1eNGjVSUFCQmjVrpvnz57tsN8Zo3LhxqlWrloKDg5WcnKzNmzeXy3mej1zHCCAIAAAAAICKzs/bBZTGxo0b5XQ69eqrr6phw4Zau3at7rjjDh05ckRPP/20S9svv/xSTZo0sd7XqFHDWl68eLH69u2rSZMmqUePHnrnnXfUs2dPrVixQk2bNpUkTZ48WVOnTtWsWbOUkJCgsWPHKiUlRevXr1dQUFD5nPD5xOFrLR5c95VWZu8t1qRKZJwSm3eUw6dC5EoAAAAAYGsOY0yFHAp+ypQpeuWVV/Trr79KOt0jICEhQStXrlTz5s1L/EyfPn105MgRffrpp9a6du3aqXnz5po+fbqMMYqNjdXIkSN13333SZJyc3MVHR2tmTNn6sYbbyxVbXl5eQoPD1dubq7CwsL+3ol62ZLpd6td5tt/3e6C+9TuprHlUBEAAAAA4M/Kch9aYf+Em5ubq+rVqxdbf80116hmzZrq0KGDPvnkE5dtGRkZSk5OdlmXkpKijIwMSdK2bduUmZnp0iY8PFxt27a12pTkxIkTysvLc3lVFr4xTf66kaTA3xZ7uBIAAAAAgDtUiEcD/mzLli2aNm2ay2MBoaGheuaZZ3TppZfKx8dHH3zwgXr27Kl58+bpmmuukSRlZmYqOjraZV/R0dHKzMy0theuO1ObkkyaNEmPPPKIW87tfNOi+x1aGRyq45mbim1znDymdr/9P0mSj2H8AAAAAACoCLwaBIwaNUpPPfXUWdts2LBBjRo1st7v3r1b3bp1U69evXTHHXdY6yMjIzVixAjr/SWXXKI9e/ZoypQpVhDgKaNHj3Y5dl5enuLi4jx6zPLi5x+gFin9StyWezBLeuF0EOAgCAAAAACACsGrQcDIkSPVv3//s7apX7++tbxnzx516dJF7du312uvvfaX+2/btq3S0tKs9zExMdq3b59Lm3379ikmJsbaXriuVq1aLm3ONO6AJAUGBiowMPAv66ls/Pz+uHx8zCkvVgIAAAAAKC2vBgFRUVGKiooqVdvdu3erS5cuatWqlWbMmCGfUoxQv2rVKpcb+qSkJKWnpys1NdVal5aWpqSkJElSQkKCYmJilJ6ebt345+XlaenSpRo8eHDpT8wmfP38rWV6BAAAAABAxVAhxgjYvXu3OnfurHr16unpp5/WgQMHrG2Ff8WfNWuWAgIC1KJFC0nShx9+qDfffFNvvPGG1Xb48OG67LLL9Mwzz6h79+5677339NNPP1m9CxwOh1JTU/X4448rMTHRmj4wNjZWPXv2LL8TriD8igQBjBEAAAAAABVDhQgC0tLStGXLFm3ZskV16tRx2VZ09sPHHntMO3bskJ+fnxo1aqTZs2frX//6l7W9ffv2eueddzRmzBg99NBDSkxM1Lx589S0aVOrzQMPPKAjR45o0KBBysnJUYcOHbRgwQIFBQV5/kQrGF/foo8GOL1YCQAAAACgtBym6J003KIs8zdWdKfGV5Ofw6nNfolKHPOTt8sBAAAAAFsqy33oXz9oD5xFgXwl8WgAAAAAAFQUFeLRAJy/Cv6XJfmbE8rK3OXlatzH19dP1aJq/XVDAAAAAKhgCALwtxQGAXWdu6XpTf+idcWyKiRJF983X45SzFABAAAAABUFdzj4W373jfR2CR7T/GiG9v221dtlAAAAAIBb0SMAf8vxK5/XT9+9It9TR71dittEH9uiWLNfknQ0L9vL1QAAAACAexEE4G9pdEmydEmyt8twqyWv3KXYfe9KkvYt/0T1m7b1ckUAAAAA4D48GgD8iQmpbi3H7PivFysBAAAAAPcjCAD+pEHyHdZygYNOMwAAAAAqF4IA4E9q1k7QMRMgSfI1BV6uBgAAAADciyAAKEGBfCVJDhEEAAAAAKhcCAKAEjgdp//RoEcAAAAAgMqGIAAoQWGPAB96BAAAAACoZAgCgBIU/O8fDR/j9HIlAAAAAOBeBAFACZz/+0fDlx4BAAAAACoZggCgBH88GkCPAAAAAACVC0EAUAJrsECCAAAAAACVDEEAUALn/3oE8GgAAAAAgMqGIAAoQYHjdBAQpiPKeD3Vu8UAAAAAgBsRBAAlOO4Tai0n7Z6hA3u2e68YAAAAAHAjggCgBCfaj3B5f+xwjncKAQAAAAA3IwgASnDxP3vrx4irrPemgLECAAAAAFQOBAHAmTgc1qLTMHsAAAAAgMqBIAA4A/O/AQMlyTgJAgAAAABUDgQBwJk4/vjHw1lwyouFAAAAAID7EAQAZ1IkCDA8GgAAAACgkiAIAM6kaBDgZLBAAAAAAJUDQQBwBkXHCHASBAAAAACoJAgCgDMp0iNATB8IAAAAoJIgCADOpOhggYwRAAAAAKCSIAgAzoDpAwEAAABURgQBwJk4HNaicTJ9IAAAAIDKgSAAOBOfoj0CjBcLAQAAAAD3IQgAzsRl+kB6BAAAAACoHAgCgDMpGgQwWCAAAACASsLP2wUA562iswacPKGT+Se8WEzl4OPjK18//m8HAAAA8Cb+ixw4A0eRWQNaLB4iLR7ixWoqh3zjpx/r36WkfhO9XQoAAABgWwQBwBn4VK3p7RIqnQDHKSVte1GrJi+XkeOvP1AGxuErxz96qUVKP7fuFwAAAKhsCAKAM2jStb+W7l2tqrmbvF1KpdD45FprufnRDI8c49jipTqcdI1Cw6p5ZP8AAABAZUAQAJxBlaoRajt0hrfLqDRWfvEfXfjDCIU4PDfWQrAjX7v2/0YQAAAAAJyFwxjDBOlulpeXp/DwcOXm5iosLMzb5QDnjeNHD+vIoRy373fru/erTc58SdImvwuU7xvi9mP8XYerNVHLAc8qIDDI26UAAACgEirLfSg9AgCUm6CQUAWFhLp9v5tCY6Sc08sXnNoknXL7If6+zFVa8dUlannlAG9XAgAAAJvz+esmAHB+i+3YT5mK9HYZf+lkbqa3SwAAAADoEQCg4qt3YXM5x27SseNHvV1KMWvTZumSVQ9LkozzfOyqAAAAALshCABQKfj4+iq4SlVvl1GMb2CVP94QBAAAAOA8wKMBAOBBDl9/a9k4nV6sBAAAADiNIAAAPMjhW6TjlfOk9woBAAAA/ocgAAA8yMenaBBQ4L1CAAAAgP8hCAAADyr6aABjBAAAAOB8QBAAAB7k4/JoAEEAAAAAvI8gAAA8yMfvjyDAwaMBAAAAOA8wfSAAeFDRwQJr7/taK56+2ovVAAAA4FzVvelFRcbW83YZbkEQAAAe5OcfZC3HmT2KO7zHi9UAAADgXO06muftEtyGRwMAwIMSmrTVJr8LvF0GAAAAYKFHAAB4kK+fnxIfWqr9e3fIGKe3ywEAAMA5iqlZx9sluA1BAAB4mMPHRzVrJ3i7DAAAAEASjwYAAAAAAGArBAEAAAAAANgIQQAAAAAAADZCEAAAAAAAgI0QBAAAAAAAYCMEAQAAAAAA2AhBAAAAAAAANkIQAAAAAACAjVSYIOCaa65R3bp1FRQUpFq1aumWW27Rnj17XNqsWbNGHTt2VFBQkOLi4jR58uRi+5k7d64aNWqkoKAgNWvWTPPnz3fZbozRuHHjVKtWLQUHBys5OVmbN2/26LkBAAAAAFBeKkwQ0KVLF82ZM0e//PKLPvjgA23dulX/+te/rO15eXnq2rWr6tWrp+XLl2vKlCmaMGGCXnvtNavN4sWL1bdvXw0cOFArV65Uz5491bNnT61du9ZqM3nyZE2dOlXTp0/X0qVLVaVKFaWkpOj48ePler4AAAAAAHiCwxhjvF3Eufjkk0/Us2dPnThxQv7+/nrllVf08MMPKzMzUwEBAZKkUaNGad68edq4caMkqU+fPjpy5Ig+/fRTaz/t2rVT8+bNNX36dBljFBsbq5EjR+q+++6TJOXm5io6OlozZ87UjTfeWKra8vLyFB4ertzcXIWFhbn5zAEAAAAAcFWW+9AK0yOgqOzsbL399ttq3769/P39JUkZGRnq1KmTFQJIUkpKin755RcdPHjQapOcnOyyr5SUFGVkZEiStm3bpszMTJc24eHhatu2rdWmJCdOnFBeXp7LCwAAAACA81GFCgIefPBBValSRTVq1NDOnTv18ccfW9syMzMVHR3t0r7wfWZm5lnbFN1e9HMltSnJpEmTFB4ebr3i4uLO8QwBAAAAAPAsrwYBo0aNksPhOOursFu/JN1///1auXKlvvjiC/n6+urWW2/V+fBkw+jRo5Wbm2u9du3a5e2SAAAAAAAokZ83Dz5y5Ej179//rG3q169vLUdGRioyMlIXXHCBLrroIsXFxWnJkiVKSkpSTEyM9u3b5/LZwvcxMTHW/5bUpuj2wnW1atVyadO8efMz1hgYGKjAwMCznywAAAAAAOcBrwYBUVFRioqKOqfPOp1OSaefz5ekpKQkPfzwwzp58qQ1bkBaWpouvPBCVatWzWqTnp6u1NRUaz9paWlKSkqSJCUkJCgmJkbp6enWjX9eXp6WLl2qwYMHn1OdAAAAAACcTyrEGAFLly7Viy++qFWrVmnHjh366quv1LdvXzVo0MC6ib/pppsUEBCggQMHat26dZo9e7ZeeOEFjRgxwtrP8OHDtWDBAj3zzDPauHGjJkyYoJ9++klDhw6VJDkcDqWmpurxxx/XJ598op9//lm33nqrYmNj1bNnT2+cOgAAAAAAbuXVHgGlFRISog8//FDjx4/XkSNHVKtWLXXr1k1jxoyxuuSHh4friy++0JAhQ9SqVStFRkZq3LhxGjRokLWf9u3b65133tGYMWP00EMPKTExUfPmzVPTpk2tNg888ICOHDmiQYMGKScnRx06dNCCBQsUFBRU6noLxy1g9gAAAAAAQHkovP8szTh6DnM+jLZXyfz222/MHAAAAAAAKHe7du1SnTp1ztqGIMADnE6n9uzZo6pVq8rhcHi7nDPKy8tTXFycdu3apbCwMG+XAxTDNYrzHdcoKgKuU5zvuEZxvqso16gxRocOHVJsbKx8fM4+CkCFeDSgovHx8fnLBOZ8EhYWdl5f0ADXKM53XKOoCLhOcb7jGsX5riJco+Hh4aVqVyEGCwQAAAAAAO5BEAAAAAAAgI0QBNhYYGCgxo8fb828AJxvuEZxvuMaRUXAdYrzHdcozneV8RplsEAAAAAAAGyEHgEAAAAAANgIQQAAAAAAADZCEAAAAAAAgI0QBAAAAAAAYCMEATb20ksvKT4+XkFBQWrbtq1+/PFHb5eESmjSpEm65JJLVLVqVdWsWVM9e/bUL7/84tLm+PHjGjJkiGrUqKHQ0FDdcMMN2rdvn0ubnTt3qnv37goJCVHNmjV1//3369SpUy5tFi1apJYtWyowMFANGzbUzJkzPX16qISefPJJORwOpaamWuu4RuFtu3fv1v/93/+pRo0aCg4OVrNmzfTTTz9Z240xGjdunGrVqqXg4GAlJydr8+bNLvvIzs7WzTffrLCwMEVERGjgwIE6fPiwS5s1a9aoY8eOCgoKUlxcnCZPnlwu54eKraCgQGPHjlVCQoKCg4PVoEEDPfbYYyo6JjnXKMrTt99+q6uvvlqxsbFyOByaN2+ey/byvB7nzp2rRo0aKSgoSM2aNdP8+fPdfr7nxMCW3nvvPRMQEGDefPNNs27dOnPHHXeYiIgIs2/fPm+XhkomJSXFzJgxw6xdu9asWrXKXHXVVaZu3brm8OHDVpu77rrLxMXFmfT0dPPTTz+Zdu3amfbt21vbT506ZZo2bWqSk5PNypUrzfz5801kZKQZPXq01ebXX381ISEhZsSIEWb9+vVm2rRpxtfX1yxYsKBczxcV248//mji4+PNP/7xDzN8+HBrPdcovCk7O9vUq1fP9O/f3yxdutT8+uuvZuHChWbLli1WmyeffNKEh4ebefPmmdWrV5trrrnGJCQkmGPHjlltunXrZi6++GKzZMkS891335mGDRuavn37Wttzc3NNdHS0ufnmm83atWvNu+++a4KDg82rr75arueLimfixImmRo0a5tNPPzXbtm0zc+fONaGhoeaFF16w2nCNojzNnz/fPPzww+bDDz80ksxHH33ksr28rscffvjB+Pr6msmTJ5v169ebMWPGGH9/f/Pzzz97/Dv4KwQBNtWmTRszZMgQ631BQYGJjY01kyZN8mJVsIP9+/cbSeabb74xxhiTk5Nj/P39zdy5c602GzZsMJJMRkaGMeb0/5n7+PiYzMxMq80rr7xiwsLCzIkTJ4wxxjzwwAOmSZMmLsfq06ePSUlJ8fQpoZI4dOiQSUxMNGlpaeayyy6zggCuUXjbgw8+aDp06HDG7U6n08TExJgpU6ZY63JyckxgYKB59913jTHGrF+/3kgyy5Yts9p8/vnnxuFwmN27dxtjjHn55ZdNtWrVrGu28NgXXnihu08JlUz37t3Nbbfd5rLu+uuvNzfffLMxhmsU3vXnIKA8r8fevXub7t27u9TTtm1bc+edd7r1HM8FjwbYUH5+vpYvX67k5GRrnY+Pj5KTk5WRkeHFymAHubm5kqTq1atLkpYvX66TJ0+6XI+NGjVS3bp1resxIyNDzZo1U3R0tNUmJSVFeXl5WrdundWm6D4K23BNo7SGDBmi7t27F7uOuEbhbZ988olat26tXr16qWbNmmrRooVef/11a/u2bduUmZnpcn2Fh4erbdu2LtdoRESEWrdubbVJTk6Wj4+Pli5darXp1KmTAgICrDYpKSn65ZdfdPDgQU+fJiqw9u3bKz09XZs2bZIkrV69Wt9//72uvPJKSVyjOL+U5/V4Pv+7nyDAhrKyslRQUODyH6ySFB0drczMTC9VBTtwOp1KTU3VpZdeqqZNm0qSMjMzFRAQoIiICJe2Ra/HzMzMEq/Xwm1na5OXl6djx4554nRQibz33ntasWKFJk2aVGwb1yi87ddff9Urr7yixMRELVy4UIMHD9awYcM0a9YsSX9cY2f793pmZqZq1qzpst3Pz0/Vq1cv03UMlGTUqFG68cYb1ahRI/n7+6tFixZKTU3VzTffLIlrFOeX8rwez9TmfLhe/bxdAAD7GDJkiNauXavvv//e26UAll27dmn48OFKS0tTUFCQt8sBinE6nWrdurWeeOIJSVKLFi20du1aTZ8+Xf369fNydYA0Z84cvf3223rnnXfUpEkTrVq1SqmpqYqNjeUaBc5T9AiwocjISPn6+hYb8Xrfvn2KiYnxUlWo7IYOHapPP/1UX3/9terUqWOtj4mJUX5+vnJyclzaF70eY2JiSrxeC7edrU1YWJiCg4PdfTqoRJYvX679+/erZcuW8vPzk5+fn7755htNnTpVfn5+io6O5hqFV9WqVUuNGzd2WXfRRRdp586dkv64xs727/WYmBjt37/fZfupU6eUnZ1dpusYKMn9999v9Qpo1qyZbrnlFt17771WLyuuUZxPyvN6PFOb8+F6JQiwoYCAALVq1Urp6enWOqfTqfT0dCUlJXmxMlRGxhgNHTpUH330kb766islJCS4bG/VqpX8/f1drsdffvlFO3futK7HpKQk/fzzzy7/h5yWlqawsDDrP46TkpJc9lHYhmsaf+Xyyy/Xzz//rFWrVlmv1q1b6+abb7aWuUbhTZdeemmxaVc3bdqkevXqSZISEhIUExPjcn3l5eVp6dKlLtdoTk6Oli9fbrX56quv5HQ61bZtW6vNt99+q5MnT1pt0tLSdOGFF6patWoeOz9UfEePHpWPj+ttha+vr5xOpySuUZxfyvN6PK//3e/t0QrhHe+9954JDAw0M2fONOvXrzeDBg0yERERLiNeA+4wePBgEx4ebhYtWmT27t1rvY4ePWq1ueuuu0zdunXNV199ZX766SeTlJRkkpKSrO2FU7N17drVrFq1yixYsMBERUWVODXb/fffbzZs2GBeeuklpmbDOSs6a4AxXKPwrh9//NH4+fmZiRMnms2bN5u3337bhISEmP/85z9WmyeffNJERESYjz/+2KxZs8Zce+21JU6F1aJFC7N06VLz/fffm8TERJepsHJyckx0dLS55ZZbzNq1a817771nQkJCmJoNf6lfv36mdu3a1vSBH374oYmMjDQPPPCA1YZrFOXp0KFDZuXKlWblypVGknn22WfNypUrzY4dO4wx5Xc9/vDDD8bPz888/fTTZsOGDWb8+PFMHwjvmzZtmqlbt64JCAgwbdq0MUuWLPF2SaiEJJX4mjFjhtXm2LFj5u677zbVqlUzISEh5rrrrjN79+512c/27dvNlVdeaYKDg01kZKQZOXKkOXnypEubr7/+2jRv3twEBASY+vXruxwDKIs/BwFco/C2//73v6Zp06YmMDDQNGrUyLz22msu251Opxk7dqyJjo42gYGB5vLLLze//PKLS5vff//d9O3b14SGhpqwsDAzYMAAc+jQIZc2q1evNh06dDCBgYGmdu3a5sknn/T4uaHiy8vLM8OHDzd169Y1QUFBpn79+ubhhx92mVaNaxTl6euvvy7xvz/79etnjCnf63HOnDnmggsuMAEBAaZJkybms88+89h5l4XDGGO80xcBAAAAAACUN8YIAAAAAADARggCAAAAAACwEYIAAAAAAABshCAAAAAAAAAbIQgAAAAAAMBGCAIAAAAAALARggAAAAAAAGyEIAAAAAAAABshCAAAAF4VHx+v559/vlyOdcstt+iJJ544p89mZWWpZs2a+u2339xcFQAA5YsgAAAAm+jfv7969uxpve/cubNSU1PL7fgzZ85UREREsfXLli3ToEGDPH781atXa/78+Ro2bFiJ25ctW6bY2FhJ0p49exQcHKz8/Hxre2RkpG699VaNHz/e47UCAOBJBAEAAOBvKXqzfC6ioqIUEhLipmrObNq0aerVq5dCQ0NL3J6RkaFLL71UkvTdd9+pdevWCggIcGkzYMAAvf3228rOzvZ4vQAAeApBAAAANtS/f3998803euGFF+RwOORwOLR9+3ZJ0tq1a3XllVcqNDRU0dHRuuWWW5SVlWV9tnPnzho6dKhSU1MVGRmplJQUSdKzzz6rZs2aqUqVKoqLi9Pdd9+tw4cPS5IWLVqkAQMGKDc31zrehAkTJBV/NGDnzp269tprFRoaqrCwMPXu3Vv79u2ztk+YMEHNmzfXv//9b8XHxys8PFw33nijDh06dMbzLSgo0Pvvv6+rr776jG0WL15sBQHff/+9tVxUkyZNFBsbq48++ujsXzAAAOcxggAAAGzohRdeUFJSku644w7t3btXe/fuVVxcnHJycvTPf/5TLVq00E8//aQFCxZo37596t27t8vnZ82apYCAAP3www+aPn26JMnHx0dTp07VunXrNGvWLH311Vd64IEHJEnt27fX888/r7CwMOt49913X7G6nE6nrr32WmVnZ+ubb75RWlqafv31V/Xp08el3datWzVv3jx9+umn+vTTT/XNN9/oySefPOP5rlmzRrm5uWrdurXL+u+//14RERGKiIjQ+++/r4cfflgRERGaPn26pk6dqoiIiGL7bdOmjb777rvSf9kAAJxn/LxdAAAAKH/h4eEKCAhQSEiIYmJirPUvvviiWrRo4TKg3ptvvqm4uDht2rRJF1xwgSQpMTFRkydPdtln0fEG4uPj9fjjj+uuu+7Syy+/rICAAIWHh8vhcLgc78/S09P1888/a9u2bYqLi5MkvfXWW2rSpImWLVumSy65RNLpwGDmzJmqWrWqpNODAKanp2vixIkl7nfHjh3y9fVVzZo1Xda3bt1aq1at0saNG3XTTTdp+fLlys7OVvv27bVixQoFBQUVG9cgNjZWK1euPOM5AABwvqNHAAAAsKxevVpff/21QkNDrVejRo0knf4rfKFWrVoV++yXX36pyy+/XLVr11bVqlV1yy236Pfff9fRo0dLffwNGzYoLi7OCgEkqXHjxoqIiNCGDRusdfHx8VYIIEm1atXS/v37z7jfY8eOKTAwUA6Hw2V9UFCQ4uPjtWbNGl155ZVKSEjQxo0b1bFjRzVq1Ejx8fHFgoDg4OAynRMAAOcbegQAAADL4cOHdfXVV+upp54qtq1WrVrWcpUqVVy2bd++XT169NDgwYM1ceJEVa9eXd9//70GDhyo/Px8tw8G6O/v7/Le4XDI6XSesX1kZKSOHj2q/Px8lwEACwcOPHHihHx8fPTxxx8rPz9fxhiFhoaqY8eO+vzzz132lZ2draioKDeeDQAA5YsgAAAAmwoICFBBQYHLupYtW+qDDz5QfHy8/PxK/58Jy5cvl9Pp1DPPPCMfn9MdDufMmfOXx/uziy66SLt27dKuXbusXgHr169XTk6OGjduXOp6/qx58+bWvgqXJWnVqlU6deqUmjdvri+//FIxMTHq2LGjXn75ZTVr1kzBwcHF9rV27Vp17tz5nGsBAMDbeDQAAACbio+P19KlS7V9+3ZlZWXJ6XRqyJAhys7OVt++fbVs2TJt3bpVCxcu1IABA856E9+wYUOdPHlS06ZN06+//qp///vf1iCCRY93+PBhpaenKysrq8Tu9cnJyWrWrJluvvlmrVixQj/++KNuvfVWXXbZZcUG+iuLqKgotWzZUt9//32xunNychQdHa0OHTooICBAhw4d0tVXX62GDRuqdu3aLu2PHj2q5cuXq2vXrudcCwAA3kYQAACATd13333y9fVV48aNFRUVpZ07dyo2NlY//PCDCgoK1LVrVzVr1kypqamKiIiw/tJfkosvvljPPvusnnrqKTVt2lRvv/22Jk2a5NKmffv2uuuuu9SnTx9FRUUVG2xQOt3F/+OPP1a1atXUqVMnJScnq379+po9e/bfPt/bb79db7/9drH1ixYtUqdOnSRJ33zzjZKSks7YG+Ljjz9W3bp11bFjx79dDwAA3uIwxhhvFwEAAOBpx44d04UXXqjZs2crKSnpnPbRrl07DRs2TDfddJObqwMAoPzQIwAAANhCcHCw3nrrLWVlZZ3T57OysnT99derb9++bq4MAIDyRY8AAAAAAABshB4BAAAAAADYCEEAAAAAAAA2QhAAAAAAAICNEAQAAAAAAGAjBAEAAAAAANgIQQAAAAAAADZCEAAAAAAAgI0QBAAAAAAAYCMEAQAAAAAA2Mj/B9sd8y6jjp6YAAAAAElFTkSuQmCC",
       "text/plain": [
        "<Figure size 1200x600 with 1 Axes>"
       ]
@@ -458,6 +466,7 @@
    ]
   },
   {
+   "attachments": {},
    "cell_type": "markdown",
    "metadata": {},
    "source": [
@@ -468,7 +477,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 18,
+   "execution_count": 61,
    "metadata": {},
    "outputs": [
     {
@@ -493,12 +502,12 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 19,
+   "execution_count": 62,
    "metadata": {},
    "outputs": [
     {
      "data": {
-      "image/png": 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",
       "text/plain": [
        "<Figure size 1200x600 with 1 Axes>"
       ]
@@ -513,6 +522,142 @@
    ]
   },
   {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  },
+  {
+   "attachments": {},
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### More advanced bandit algorithms\n",
+    "Operator selection can be framed as a multi-armed-bandit problem where each operator pair is a bandit and the per-arm reward corresponds to the score array we've supplied to our selection algorithms above. Accordingly, any multi-armed bandit algorithm can be used as an operator selection scheme. ALNS integrates with [MABWiser](https://github.com/fidelity/mabwiser/) to provide access to more bandit algorithms. Install MABWiser as an extra dependency with `pip install alns[mabwiser]`.\n",
+    "\n",
+    "Here, we use a simple epsilon-greedy algorithm from MABWiser. The algorithm picks a random operator pair with probability $\\epsilon=0.15$ and otherwise chooses the operator pair with the largest mean so far."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 63,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Found solution with objective 2869.0.\n"
+     ]
+    }
+   ],
+   "source": [
+    "select = MABSelector(scores=[5, 2, 1, 0.5],\n",
+    "                     num_destroy=2,\n",
+    "                     num_repair=1,\n",
+    "                     learning_policy=LearningPolicy.EpsilonGreedy(epsilon=0.15))\n",
+    "\n",
+    "alns = make_alns()\n",
+    "res = alns.iterate(init_sol, select, accept, MaxIterations(10_000))\n",
+    "\n",
+    "print(f\"Found solution with objective {-res.best_state.objective()}.\")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 64,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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+      "text/plain": [
+       "<Figure size 1200x600 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "_, ax = plt.subplots(figsize=(12, 6))\n",
+    "res.plot_objectives(ax=ax, lw=2)"
+   ]
+  },
+  {
+   "attachments": {},
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### Contextual bandit algorithms\n",
+    "Some MABWiser bandit algorithms require a context vector when making an operator selection choice. To utilize these algorithms, your `State` class must additionally conform to the `ContextualState` protocol found in `ALNS.State`. In practice, this simply means adding an additional method that takes no arguments and returns context data about your state."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 65,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "def get_knapsack_context(self: KnapsackState):\n",
+    "    item_count = np.count(p)\n",
+    "    average_weight = self.weight / item_count\n",
+    "    return [\n",
+    "        self.weight,\n",
+    "        item_count,\n",
+    "        average_weight\n",
+    "    ]\n",
+    "KnapsackState.get_context = get_knapsack_context"
+   ]
+  },
+  {
+   "attachments": {},
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "We can now use a contextual bandit algorithm such as `LinGreedy`. See the [MABWiser documentation](fidelity.github.io/mabwiser/api.html#mabwiser.mab.LearningPolicy.LinGreedy) for more details on how this and other contextual bandit algorithms work."
+   ]
+  },
+  {
+   "attachments": {},
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "select = MABSelector(scores=[5, 2, 1, 0.5],\n",
+    "                     num_destroy=2,\n",
+    "                     num_repair=1,\n",
+    "                     learning_policy=LearningPolicy.LinGreedy(epsilon=0.15))\n",
+    "\n",
+    "alns = make_alns()\n",
+    "res = alns.iterate(init_sol, select, accept, MaxIterations(10_000))\n",
+    "\n",
+    "print(f\"Found solution with objective {-res.best_state.objective()}.\")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 66,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 1200x600 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "_, ax = plt.subplots(figsize=(12, 6))\n",
+    "res.plot_objectives(ax=ax, lw=2)"
+   ]
+  },
+  {
+   "attachments": {},
    "cell_type": "markdown",
    "metadata": {
     "pycharm": {
@@ -543,6 +688,7 @@
    ]
   },
   {
+   "attachments": {},
    "cell_type": "markdown",
    "metadata": {
     "pycharm": {
@@ -556,6 +702,7 @@
    ]
   },
   {
+   "attachments": {},
    "cell_type": "markdown",
    "metadata": {
     "pycharm": {
@@ -615,7 +762,7 @@
    "outputs": [
     {
      "data": {
-      "image/png": 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GVq5caV16rTjjxo2TyWTS66+/XuhpfXBwsF588UV9/vnn1vnUkvTtt9/q7bffLjQf3ZGAgACNGjVKn376qXr27FloGPaIESP0xx9/6LvvvpMkpaWl6fnnny/xvPkGDBigX3/9VceOHZMkLV++XFu3bi3UbsaMGTp+/LieffZZ643izp079cADDxSamlHQiBEj9L///U/r16+XlDfVwDaAydeoUSOZTCZrKHTfffdZbyoLMplMeuONN7RixQp99NFH1u1r1qzRM888Y/1se/bsqfDwcL311lvW35FffvlFixcvtjtfTEyMHnzwQf3rX/+y9jMzM1OPPvqoYmNjFRoaWux7LI2IiAj5+/tb3/ezzz6rb7/91i2/P5J05ZVXytfXV6+88or1b2zOnDkOQxZX/gZuvvlm9ejRQ1OmTLFOA9izZ49effVV3Xjjjerbt6+zHwEAwB0qrk4hAMDT7dmzx7jrrruMVq1aGXFxcUbr1q2Nvn37Gh999JGRk5NjbZeUlGTExcUZNWrUMKKjo40vv/zS6Nq1q9G4cWOjUaNGdtX88zmqcH/8+HFj3LhxRv369Y127doZHTp0MKZPn253LcMwjN27dxvXX3+9Ub9+fSMuLs7o27evsXz5crs2O3fuNLp06WK0aNHCaNOmjbFgwQJjzZo1RlxcnOHt7W3UqFHD4bJ/Q4YMKbZi/L///W+jQ4cORuPGjY0OHToYV199tbFlyxZnP9Jiq6tnZGQYjz76qNGgQQOjbdu2xoABA6xV2xs0aGDcd999xqeffmrExcUZkoyIiAhj4MCB1uMTExON0aNHG/Xq1TO6du1qPPnkk8bTTz9tSDLi4uKMr776ytr2t99+M6688kojKirK6Nixo9G7d+9CFeMdSUxMNO666y6jXr16RseOHY3BgwcbU6dONSQZTZo0MV588UVr2ylTphgNGzY02rRpY1x//fVGenp6sef++eefjV69ehkNGzY0OnbsaAwcOLDQz3XNmjVG7969jcjISKNv377GnXfeaQwdOtTw9vY24uLijG3btlnbvvXWW0bLli2NFi1aGG3btjUmT55sXSnhp59+svscR48ebRiGYQwcONCoUaOGw/PZevvtt42WLVtafzZjxoyx7ps5c6YRHR1ttG3b1hg0aJDdChcl/f6MHz/eaNCggSHJaNmypTFixIhC1/7hhx+MDh06GFFRUUZ8fLwxadIko3PnzkZgYKARFxdnXcLP1b+BpKQk44EHHjAaNWpkxMbGGk2bNjWeffZZ6zKdhmEY11xzjREREWH9nVq+fLnx1Vdf2X0WtqtvAAAuj8kwCkz2AwCgGmjUqJH69eun2bNnV3RXAAAAKhWmBgAAqoV169bZzf9PSUmhABkAAIADBAEAgGrhhx9+sNYUWLt2rc6cOaOhQ4dWcK8AAAAqH6YGAACqhYULF2rSpEnW1/fff7/uvvvuCuwRAABA5UQQAAAAAACAB2FqAAAAAAAAHoQgAAAAAAAAD+JV0R2ojnJzc3Xs2DEFBwfLZDJVdHcAAAAAANWcYRi6cOGC6tWrJ7O5+Gf+BAFl4NixY2rQoEFFdwMAAAAA4GEOHz6s+vXrF9uGIKAMBAcHS8r7AYSEhFRwbwAAAAAA1V1SUpIaNGhgvR8tDkFAGcifDhASEkIQAAAAAAAoN85MT6dYIAAAAAAAHoQgAAAAAAAAD0IQAAAAAACAB6FGAAAAAABAUt4SdNnZ2crJyanorqAAi8UiLy8vtyxRTxAAAAAAAFBmZqaOHz+u1NTUiu4KihAQEKC6devKx8enVOchCCjCvHnz9Pe//11+fn4ym81699131bp164ruFgAAAAC4XW5urvbv3y+LxaJ69erJx8fHLU+e4R6GYSgzM1OnT5/W/v371axZM5nNlz/TnyDAgXXr1mns2LHasGGDmjVrpjlz5mjw4MHavn27U2syAgAAAEBVkpmZqdzcXDVo0EABAQEV3R044O/vL29vbx08eFCZmZny8/O77HNRLNCBl156ScOGDVOzZs0kSbfccouys7M1e/bsiu0YAAAAAJSh0jxlRtlz18+Hn7IDixcvVufOna2vzWazOnXqpEWLFlVgrwAAAAAAKD2mBhRw9uxZJSUlKSIiwm57ZGSkfvvtN4fHZGRkKCMjw/o6KSmpTPsIAAAAAMDlYkRAAfkVMn19fe22+/r6Flk988UXX1RoaKj1q0GDBmXeTwAAAABAntTUVD377LPq06eP+vfvr549e2rQoEF66623dOrUqYruXokSEhI0depUJSQklMv1CAIKyC+MYfuEP/91UUUzHn/8cSUmJlq/Dh8+XOb9BAAAAADkhQD9+/dXYmKilixZoiVLlmjVqlW69957NWnSJL377rsV3cUSJSQkaNq0aeUWBDA1oIDw8HCFhobq5MmTdttPnDihmJgYh8f4+voWGkEAAAAAACh7zzzzjDIzM/XKK6/YLXl4zTXXaMKECRXYs8qLEQEODBgwQBs2bLC+NgxDGzdu1KBBgyqwVwAAAAAAW9nZ2frnP/+pUaNG2YUA+SZNmqTrr79e/fr1k5+fn3UluLlz56pFixZq1KiRte2dd96pyMhI3XrrrXrsscc0cOBAeXt769NPP7UeP2PGDI0ZM0Zdu3aVyWSyPsGfMWOG2rdvr/j4eMXHx2vFihWSpOTkZOuxL7/8ssaMGaMuXbqoR48e2r9/vyTpzz//1KhRoyRJo0aNUr9+/TRv3ryy+9DEiACHHnvsMV1xxRXas2ePmjZtqs8++0wWi0Vjx46t6K4BAAAAQLkZ8dZKnb6QUXJDN6sd7Kvv7utdYrsdO3YoKSlJLVu2dLi/fv36ql+/vpYuXWp303/jjTcqLS1NU6dOtW778MMPNW7cOM2fP19LlizRSy+9pGnTpiksLMx6/L///W8tWbJEYWFhGjRokEwmkz744APNmjVLa9asUVhYmFatWqWBAwdqx44dio6Oth77n//8R7/88ouCgoJ03XXXaerUqfr444/VqlUrffHFF2rcuLG++OILu36WFYIAB7p27arZs2dr1KhR8vf3l9ls1sKFCxUcHFzRXQMAAACAcnP6QoZOJKVXdDeKlJiYKEkKCgpy2znbt2+v9u3bS5KmTJlit++aa65RWFiYJFmXl3/hhRd03333Wbf37NlTTZs21YcffqjnnnvOeuyIESOs/ezXr59mzZrltj67iiCgCNdee62uvfbaiu5GmUk8f0Z7Z90mScqs017db32uhCMAAAAAeJrawRVTC83Z6+bffKekpLjt2vXr13d634ULF3To0CF99NFHWrBggXV7VlaWLly4YNe2Xr161u+Dg4MrdNl5ggAPlZWRpo7JyyVJm3KzK7g3AAAAACojZ4bnV6QWLVooNDRUf/75p0aMGFFs24I1BHJychy2s1gsRZ6jqH2TJ0/WbbfdVuz1bY81mUwyDKPY9mWJYoEAAAAAgCrJYrHob3/7m7788kuH+0eMGKHJkydLynsKb/uU/ujRo6W+fnBwsBo2bKidO3fabZ87d66+/vprp89jNl+6Nc/NzXXrCAeH1yvTswMAAAAAUIamTp2qgIAAPfLII8rOzhvtbBiG3nrrLW3btk0PP/ywpLy5/6tWrZKUV83/u+++c8v1n3zySX388cc6dOiQJOn06dOaNm2a2rRp4/Q5wsPDZTabdf78ea1fv17jxo1zS9+KwtQAAAAAAECV5evrq//97396+eWXFR8fL29vb2VkZKh169ZatmyZIiIiJOUFBqNHj1bXrl3VtGlTXX/99ZoyZYr69eunBQsW6KmnntJPP/0kSdZttsX9Tpw4oZdeekkrV67Uhx9+aL3+3XffreTkZF111VUKDw+XxWLR66+/rtjY2ELH+vj4yGKx6KWXXtKJEyc0cOBALV68WIGBgZo8ebLGjBmjoKAgvfrqq2X6mZmMipyYUE0lJSUpNDRUiYmJCgkJqejuOHTmxGHVej8vodoU0FMdHvmxgnsEAAAAoKKkp6dr//79aty4sfz8/Cq6OyhCcT8nV+5DmRrgoQoWygAAAAAAeAaCAAAAAAAAPAhBAAAAAAAAHoQgAAAAAAAAD0IQAAAAAACAByEIgExi4QgAAAAA8BQEAR6KVQMAAAAAwDMRBAAAAAAA4EEIAgAAAAAA8CAEAQAAAACAKmndunXq16+fTCaTWrRooX79+qlLly5q2rSpnnjiCeXk5LjlOlOnTtWBAwfccq7KwKuiO4BKwKBYIAAAAICqp2vXrlq6dKlMJpMee+wxjRs3TpK0adMmdevWTVFRUZowYUKprzNt2jT169dPjRo1KvW5KgNGBHgok4kfPQAAAIDqqUOHDmrTpo1++eWXiu5KpcTdIAAAAACg2snKyrJbLW3GjBlq37694uPjFR8frxUrVlj37du3T1dddZX69u2rPn366IYbbtDOnTt17tw59evXT5L0wAMPqF+/fnrvvffK+624HVMDAAAAAACOzYyXkk+V/3WD6kh/XXbZhy9YsEA7duzQSy+9JEn64IMPNGvWLK1Zs0ZhYWFatWqVBg4cqB07dig6Olr33nuvunbtqmeffVaSNHbsWK1evVrjxo2zTj14/fXXraFAVUcQAAAAAABwLPmUdOFYRffCKS+99JJmz56ts2fPau/evXrsscc0ZMgQSdILL7yg++67T2FhYZKknj17qmnTpvrwww/13HPP6ejRo4qIiFBOTo4sFoteeOEFu9EE1Q1BAGQSxQIBAAAAOBBUp8pc17ZY4JkzZ3Tdddfp2muv1aeffqpDhw7po48+0oIFC6zts7KydOHCBUl5xQDHjBmjJUuWaNSoUbr99tvVvHlzt7yVyoggwENV53QLAAAAgJuUYnh+RapVq5buv/9+jRw5Uvv27ZMkTZ48WbfddpvD9tdcc42OHDmiL774Qh9++KFeffVVffXVV7rmmmvKsdflh2KBAAAAAIBqx8vLy/q/DRs21M6dO+32z507V19//bUk6T//+Y9CQ0P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\n",
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",
       "text/plain": [
        "<Figure size 1200x600 with 1 Axes>"
       ]
@@ -630,6 +777,7 @@
    ]
   },
   {
+   "attachments": {},
    "cell_type": "markdown",
    "metadata": {
     "pycharm": {
@@ -686,7 +834,7 @@
    "outputs": [
     {
      "data": {
-      "image/png": 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\n",
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",
       "text/plain": [
        "<Figure size 1200x600 with 1 Axes>"
       ]
@@ -701,6 +849,7 @@
    ]
   },
   {
+   "attachments": {},
    "cell_type": "markdown",
    "metadata": {
     "pycharm": {
@@ -751,7 +900,7 @@
    "outputs": [
     {
      "data": {
-      "image/png": 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k+Gu9j4+PJkyYoPnz51vnU0vS119/rffeey/D+eiZ8fLyUq9evfTZZ5+pZcuWGQ7D7tatm3777TctXbpUkpSYmKjXX3892/2ma9eunX788UcdP35ckrRu3Trt2LEjQ7/JkyfrxIkTGjdunPVFce/evXr22WcznJrxV926ddP//vc/xcTESLp+qsGNAUy66tWry2azWaHQkCFDrC+Vf2Wz2TR16lStX79es2bNsto3bdqkV1991XptW7ZsqXLlyundd9+13iOrVq3SypUr7fYXFBSk5557Tp9++qlVZ3JyskaMGKE6derIz88vy+d4O/z9/VWyZEnreY8bN05ff/21Q94/knT33XfLw8ND//znP63P2Ny5czMNWXLzGXjkkUd01113acyYMdZpAAcOHNCUKVP00EMPKSIiIqcvAQDAEZw3TyEAwNUdOHDAPPHEE6Z+/fomODjYNGjQwERERJhZs2aZ1NRUq198fLwJDg42ZcqUMYGBgeaLL74w4eHhpkaNGqZ69ep2s/mny2yG+xMnTpj+/fubKlWqmMaNG5smTZqYSZMm2T2WMcbs37/fPPDAA6ZKlSomODjYREREmHXr1tn12bt3rwkLCzN169Y1DRs2NMuWLTObNm0ywcHBpnjx4qZMmTKZXvavc+fOWc4Y/69//cs0adLE1KhRwzRp0sTcd999Zvv27Tl9SbOcXT0pKcmMGDHCVK1a1TRq1Mi0a9fOmrW9atWqZsiQIeazzz4zwcHBRpLx9/c37du3t7aPi4szvXv3NpUqVTLh4eFm1KhR5pVXXjGSTHBwsFm0aJHV96effjJ33323qVy5smnatKlp3bp1hhnjMxMXF2eeeOIJU6lSJdO0aVPTqVMnEx0dbSSZmjVrmgkTJlh9x4wZY6pVq2YaNmxoHnjgAXP16tUs9/3999+bVq1amWrVqpmmTZua9u3bZxjXTZs2mdatW5uAgAATERFhBg4caO69915TvHhxExwcbHbu3Gn1fffdd029evVM3bp1TaNGjczw4cOtKyV89913dq9j7969jTHGtG/f3pQpUybT/d3ovffeM/Xq1bPGpk+fPta6GTNmmMDAQNOoUSPToUMHuytcZPf+GTRokKlataqRZOrVq2e6deuW4bG//fZb06RJE1O5cmUTGRlphg0bZpo1a2ZKlSplgoODrUv45fYzEB8fb5599llTvXp1U6dOHVOrVi0zbtw46zKdxhjTvXt34+/vb72n1q1bZxYtWmT3Wtx49Q0AwK2xGfOXk/0AACgCqlevrqioKM2ePdvZpQAAABQonBoAACgStmzZYnf+/+XLl5mADAAAIBMEAQCAIuHbb7+15hTYvHmzzp49q3vvvdfJVQEAABQ8nBoAACgSli9frmHDhlnLzzzzjJ588kknVgQAAFAwEQQAAAAAAOBCODUAAAAAAAAXQhAAAAAAAIALKebsAoqitLQ0HT9+XD4+PrLZbM4uBwAAAABQxBljdOnSJVWqVElubln/zZ8gIA8cP35cVatWdXYZAAAAAAAXc+zYMVWpUiXLPgQBecDHx0fS9QHw9fV1cjUAAAAAgKIuPj5eVatWtb6PZoUgIA+knw7g6+tLEAAAAAAAyDc5OT2dyQIBAAAAAHAhBAEAAAAAALgQggAAAAAAAFwIcwQAAAAAACRdvwRdSkqKUlNTnV0K/sLd3V3FihVzyCXqCQIAAAAAAEpOTtaJEyd05coVZ5eCm/Dy8tIdd9yhEiVK3NZ+CAJuYsmSJXrjjTfk6ekpNzc3TZ8+XQ0aNHB2WQAAAADgcGlpaTp06JDc3d1VqVIllShRwiF/eYZjGGOUnJysM2fO6NChQ7rzzjvl5nbrZ/oTBGRiy5Yt6tevn7Zu3ao777xTc+fOVadOnbR79+4cXZMRAAAAAAqT5ORkpaWlqWrVqvLy8nJ2OchEyZIlVbx4cR05ckTJycny9PS85X0xWWAmJk6cqC5duujOO++UJD366KNKSUnR7NmznVsYAAAAAOSh2/krM/Keo8aHUc7EypUr1axZM2vZzc1NoaGhWrFihROrAgAAAADg9nFqwF+cO3dO8fHx8vf3t2sPCAjQTz/9lOk2SUlJSkpKspbj4+PztEYAAAAAAG4VRwT8RfoMmR4eHnbtHh4eN509c8KECfLz87NuVatWzfM6AQAAAADXXblyRePGjVObNm3Utm1btWzZUh06dNC7776r06dPO7u8bF28eFHR0dG6ePFivjweQcBfpE+MceNf+NOXbzZpxksvvaS4uDjrduzYsTyvEwAAAABwPQRo27at4uLitHr1aq1evVobNmzQ4MGDNWzYME2fPt3ZJWbr4sWLGjt2bL4FAZwa8BflypWTn5+fTp06Zdd+8uRJBQUFZbqNh4dHhiMIAAAAAAB579VXX1VycrL++c9/2l3ysHv37nr66aedWFnBxREBmWjXrp22bt1qLRtjtG3bNnXo0MGJVQEAAAAAbpSSkqKPP/5YvXr1sgsB0g0bNkwPPPCAoqKi5OnpaV0JbuHChapbt66qV69u9R04cKACAgLUt29fjRw5Uu3bt1fx4sX12WefWdtPnjxZffr0UXh4uGw2m/UX/MmTJyskJESRkZGKjIzU+vXrJUkJCQnWtm+++ab69OmjsLAw3XXXXTp06JAkadeuXerVq5ckqVevXoqKitKSJUvy7kUTRwRkauTIkerYsaMOHDigWrVq6fPPP5e7u7v69evn7NIAAAAAIN90e/cHnbmUlH1HB6vg46GlQ1pn22/Pnj2Kj49XvXr1Ml1fpUoVValSRWvWrLH70v/QQw8pMTFR0dHRVtsnn3yi/v3766uvvtLq1as1ceJEjR07VqVLl7a2/9e//qXVq1erdOnS6tChg2w2mz766CPNnDlTmzZtUunSpbVhwwa1b99ee/bsUWBgoLXtv//9b61atUre3t7q0aOHoqOjNWfOHNWvX18LFixQjRo1tGDBArs68wpBQCbCw8M1e/Zs9erVSyVLlpSbm5uWL18uHx8fZ5cGAAAAAPnmzKUknYy/6uwybiouLk6S5O3t7bB9hoSEKCQkRJI0ZswYu3Xdu3dX6dKlJcm6vPz48eM1ZMgQq71ly5aqVauWPvnkE7322mvWtt26dbPqjIqK0syZMx1Wc24RBNzE/fffr/vvv9/ZZeSZuAtn9fvMAZKk5IohatH3tWy2AAAAAOBqKvg4Zy60nD5u+pfvy5cvO+yxq1SpkuN1ly5d0tGjRzVr1iwtW7bMar927ZouXbpk17dSpUrWfR8fH6dedp4gwEVdS0pU04R1kqSf01KcXA0AAACAgignh+c7U926deXn56ddu3apW7duWfb96xwCqampmfZzd3e/6T5utm748OEaMGBAlo9/47Y2m03GmCz75yUmCwQAAAAAFEru7u76xz/+oS+++CLT9d26ddPw4cMlXf8r/I1/pY+Njb3tx/fx8VG1atW0d+9eu/aFCxfqyy+/zPF+3Nz+/Gqelpbm0CMcMn28PN07AAAAAAB5KDo6Wl5eXnrxxReVknL9aGdjjN59913t3LlTL7zwgqTr5/5v2LBB0vXZ/JcuXeqQxx81apTmzJmjo0ePSpLOnDmjsWPHqmHDhjneR7ly5eTm5qYLFy4oJiZG/fv3d0htN8OpAQAAAACAQsvDw0P/+9//9OabbyoyMlLFixdXUlKSGjRooLVr18rf31/S9cCgd+/eCg8PV61atfTAAw9ozJgxioqK0rJlyzR69Gh99913kmS13Ti538mTJzVx4kT98MMP+uSTT6zHf/LJJ5WQkKB77rlH5cqVk7u7u9555x3VqVMnw7YlSpSQu7u7Jk6cqJMnT6p9+/ZauXKlSpUqpeHDh6tPnz7y9vbWlClT8vQ1sxlnnphQRMXHx8vPz09xcXHy9fV1djmZOnvymMp/eD2h+tmrpZq8+F8nVwQAAADAWa5evapDhw6pRo0a8vT0dHY5uImsxik330M5NQAAAAAAABdCEAAAAAAAgAshCAAAAAAAwIUQBAAAAAAA4EIIAgAAAAAAcCEEAS7KZrM5uwQAAAAAgBMQBAAAAAAA4EIIAgAAAAAAcCEEAQAAAAAAuBCCAAAAAABAobRlyxZFRUXJZrOpbt26ioqKUlhYmGrVqqWXX35ZqampDnmc6OhoHT582CH7KgiKObsAAAAAAABuRXh4uNasWSObzaaRI0eqf//+kqSff/5ZzZs3V+XKlfX000/f9uOMHTtWUVFRql69+m3vqyDgiAAAAAAAQJHSpEkTNWzYUKtWrXJ2KQUSQQAAAAAAoMi5du2a3WXTJ0+erJCQEEVGRioyMlLr16+31h08eFD33HOPIiIi1KZNGz344IPau3evzp8/r6ioKEnSs88+q6ioKH3wwQf5/VQcjlMDIJuMs0sAAAAAUBDNiJQSTuf/43pXlP6+9pY3X7Zsmfbs2aOJEydKkj766CPNnDlTmzZtUunSpbVhwwa1b99ee/bsUWBgoAYPHqzw8HCNGzdOktSvXz9t3LhR/fv3t049eOedd6xQoLAjCHBVNyRjAAAAAJCphNPSpePOriJHJk6cqNmzZ+vcuXP6/fffNXLkSHXu3FmSNH78eA0ZMkSlS5eWJLVs2VK1atXSJ598otdee02xsbHy9/dXamqq3N3dNX78eLujCYoaggAAAAAAQOa8Kxaax71xssCzZ8+qR48euv/++/XZZ5/p6NGjmjVrlpYtW2b1v3btmi5duiTp+mSAffr00erVq9WrVy899thjql27tkOeSkFEEOCiim62BQAAAMBhbuPwfGcqX768nnnmGfXs2VMHDx6UJA0fPlwDBgzItH/37t31xx9/aMGCBfrkk080ZcoULVq0SN27d8/HqvMPkwUCAAAAAIqcYsWKWf9Wq1ZNe/futVu/cOFCffnll5Kkf//73/Lz89Pf//53/fTTT7r//vs1c+ZMq++NpwmkH0VQmBEEAAAAAACKlOTkZM2ZM0e1atVSnTp1NGrUKM2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",
       "text/plain": [
        "<Figure size 1200x600 with 1 Axes>"
       ]
@@ -766,6 +915,7 @@
    ]
   },
   {
+   "attachments": {},
    "cell_type": "markdown",
    "metadata": {},
    "source": [
@@ -773,6 +923,7 @@
    ]
   },
   {
+   "attachments": {},
    "cell_type": "markdown",
    "metadata": {
     "pycharm": {
@@ -803,7 +954,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.9.9"
+   "version": "3.11.3"
   }
  },
  "nbformat": 4,
diff --git a/pyproject.toml b/pyproject.toml
index eff66b99..d6f25779 100644
--- a/pyproject.toml
+++ b/pyproject.toml
@@ -33,6 +33,10 @@ classifiers = [
 python = "^3.8, <4.0"
 numpy = ">=1.18.0"
 matplotlib = ">=3.5.0"
+mabwiser = { version = ">=2.7.0", optional = true }
+
+[tool.poetry.extras]
+mabwiser = ["mabwiser"]  # optional integration with MABWiser
 
 # This group is needed to develop the package itself.
 [tool.poetry.group.dev.dependencies]
@@ -40,6 +44,7 @@ pre-commit = "^2.20.0"
 pytest = ">=6.0.0"
 pytest-cov = ">=2.6.1"
 codecov = "*"
+mabwiser = ">=2.7.0"
 
 # This optional docs group is needed to build the documentation. It is not 
 # required by the package itself.
@@ -54,6 +59,7 @@ numpydoc = ">=1.5.0"
 sphinx_rtd_theme = ">=0.5.1"
 sphinx-autoapi = ">=2.0.1"
 docutils = "==0.16"
+mabwiser = ">=2.7.0"
 
 # This optional examples group is needed to run the example notebooks, but not
 # required for the package itself.
@@ -65,6 +71,7 @@ vrplib = "^1.0.1"
 networkx = ">=2.4.0"
 tsplib95 = ">=0.7.0"
 jupyter = "^1.0.0"
+mabwiser = ">=2.7.0"
 
 [tool.black]
 line-length = 79


Test patch:
diff --git a/alns/select/tests/test_mab.py b/alns/select/tests/test_mab.py
new file mode 100644
index 00000000..70b2833d
--- /dev/null
+++ b/alns/select/tests/test_mab.py
@@ -0,0 +1,158 @@
+from typing import List
+
+import numpy.random as rnd
+from mabwiser.mab import LearningPolicy, NeighborhoodPolicy
+from numpy.testing import assert_equal, assert_raises
+from pytest import mark
+
+from alns.Outcome import Outcome
+from alns.select import MABSelector
+from alns.select.MABSelector import arm2ops, ops2arm
+from alns.tests.states import Zero, ZeroWithOneContext, ZeroWithZeroContext
+
+
+@mark.parametrize(
+    "destroy_idx, repair_idx",
+    [
+        (0, 0),
+        (0, 1),
+        (3, 3),
+        (12, 7),
+        (0, 14),
+    ],
+)
+def test_arm_conversion(destroy_idx, repair_idx):
+    expected = (destroy_idx, repair_idx)
+    actual = arm2ops(ops2arm(destroy_idx, repair_idx))
+
+    assert_equal(actual, expected)
+
+
+def test_does_not_raise_on_valid_mab():
+    MABSelector([0, 0, 0, 0], 2, 1, LearningPolicy.EpsilonGreedy(0.15))
+    MABSelector(
+        [0, 0, 0, 0],
+        2,
+        1,
+        LearningPolicy.EpsilonGreedy(0.15),
+        NeighborhoodPolicy.Radius(5),
+    )
+    MABSelector(
+        [0, 0, 0, 0],
+        2,
+        1,
+        LearningPolicy.EpsilonGreedy(0.15),
+        NeighborhoodPolicy.Radius(5),
+        1234567,
+    )
+    MABSelector(
+        [0, 0, 0, 0], 2, 1, LearningPolicy.EpsilonGreedy(0.15), seed=1234567
+    )
+
+
+@mark.parametrize(
+    "scores, learning_policy, num_destroy, num_repair",
+    [
+        (
+            [5, 3, 2, -1],
+            LearningPolicy.EpsilonGreedy(0.15),
+            1,
+            1,
+        ),  # negative score
+        (
+            [5, 3, 2],
+            LearningPolicy.EpsilonGreedy(0.15),
+            1,
+            1,
+        ),  # len(score) < 4
+    ],
+)
+def test_raises_invalid_arguments(
+    scores: List[float],
+    learning_policy: LearningPolicy,
+    num_destroy: int,
+    num_repair: int,
+):
+    with assert_raises(ValueError):
+        MABSelector(scores, num_destroy, num_repair, learning_policy)
+
+
+def test_call_with_only_one_operator_pair():
+    # Only one operator pair, so the algorithm should select (0, 0).
+    select = MABSelector(
+        [2, 1, 1, 0], 1, 1, LearningPolicy.EpsilonGreedy(0.15)
+    )
+    state = rnd.RandomState()
+
+    for _ in range(10):
+        selected = select(state, Zero(), Zero())
+        assert_equal(selected, (0, 0))
+
+
+def test_mab_epsilon_greedy():
+    state = rnd.RandomState()
+
+    # epsilon=0 is equivalent to greedy selection
+    select = MABSelector([2, 1, 1, 0], 2, 1, LearningPolicy.EpsilonGreedy(0.0))
+
+    select.update(Zero(), 0, 0, outcome=Outcome.BETTER)
+    selected = select(state, Zero(), Zero())
+    for _ in range(10):
+        selected = select(state, Zero(), Zero())
+        assert_equal(selected, (0, 0))
+
+    select.update(Zero(), 1, 0, outcome=Outcome.BEST)
+    for _ in range(10):
+        selected = select(state, Zero(), Zero())
+        assert_equal(selected, (1, 0))
+
+
+@mark.parametrize("alpha", [0.25, 0.5])
+def test_mab_ucb1(alpha):
+    state = rnd.RandomState()
+    select = MABSelector([2, 1, 1, 0], 2, 1, LearningPolicy.UCB1(alpha))
+
+    select.update(Zero(), 0, 0, outcome=Outcome.BEST)
+    mab_select = select(state, Zero(), Zero())
+    assert_equal(mab_select, (0, 0))
+
+    select.update(Zero(), 0, 0, outcome=Outcome.REJECT)
+    mab_select = select(state, Zero(), Zero())
+    assert_equal(mab_select, (0, 0))
+
+
+def test_contextual_mab_requires_context():
+    select = MABSelector(
+        [2, 1, 1, 0],
+        2,
+        1,
+        LearningPolicy.LinGreedy(0),
+    )
+    # error: "Zero" state has no get_context method
+    with assert_raises(AttributeError):
+        select.update(Zero(), 0, 0, outcome=Outcome.BEST)
+
+
+def text_contextual_mab_uses_context():
+    state = rnd.RandomState()
+    select = MABSelector(
+        [2, 1, 1, 0],
+        2,
+        1,
+        # epsilon=0 is equivalent to greedy
+        LearningPolicy.LinGreedy(0),
+    )
+
+    select.update(ZeroWithZeroContext(), 0, 0, outcome=Outcome.REJECT)
+    select.update(ZeroWithZeroContext(), 0, 0, outcome=Outcome.REJECT)
+    select.update(ZeroWithZeroContext(), 1, 0, outcome=Outcome.BEST)
+
+    select.update(ZeroWithOneContext(), 1, 0, outcome=Outcome.REJECT)
+    select.update(ZeroWithOneContext(), 1, 0, outcome=Outcome.REJECT)
+    select.update(ZeroWithOneContext(), 0, 0, outcome=Outcome.BEST)
+
+    mab_select = select(state, ZeroWithZeroContext(), ZeroWithZeroContext())
+    assert_equal(mab_select, (1, 0))
+
+    mab_select = select(state, ZeroWithZeroContext(), ZeroWithZeroContext())
+    assert_equal(mab_select, (0, 0))
diff --git a/alns/tests/states.py b/alns/tests/states.py
index 7ff9e71a..fe713dfa 100644
--- a/alns/tests/states.py
+++ b/alns/tests/states.py
@@ -8,7 +8,24 @@ def objective(self) -> float:
         return self.obj
 
 
+class ContextualVarObj:
+    """Test solution state object with variable objective and context."""
+
+    def __init__(self, obj: float, context: list):
+        self.obj = obj
+        self.context = context
+
+    def objective(self) -> float:
+        return self.obj
+
+    def get_context(self) -> list:
+        return self.context
+
+
 Sentinel = lambda: VarObj(0)  # noqa: E731
 Zero = lambda: VarObj(0)  # noqa: E731
 One = lambda: VarObj(1)  # noqa: E731
 Two = lambda: VarObj(2)  # noqa: E731
+
+ZeroWithZeroContext = lambda: ContextualVarObj(0, [0, 0, 0])  # noqa: E731
+ZeroWithOneContext = lambda: ContextualVarObj(1, [1, 1, 1])  # noqa: E731