Minor things for 5.1.0 release (#151)

* Minor quality of life updates Including dependency version bumps * Update CVRP notebook to use vrplib And stop using the old cvprlib package * Bump ALNS version to 5.1.0
N-Wouda · May 7, 2023 · c04f2e4 · c04f2e4
1 parent 9a03619
commit c04f2e4
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diff --git a/alns/show_versions.py b/alns/show_versions.py
@@ -1,7 +1,5 @@
 import sys
-
-# TODO switch over to importlib.metadata once we drop support for Python 3.7
-import pkg_resources  # type: ignore
+from importlib.metadata import version
 
 
 def show_versions():
@@ -23,14 +21,11 @@ def show_versions():
     matplotlib: 3.5.1
         Python: 3.9.9
     """
-    alns = pkg_resources.get_distribution("alns")
-    numpy = pkg_resources.get_distribution("numpy")
-    matplotlib = pkg_resources.get_distribution("matplotlib")
     python_version = ".".join(map(str, sys.version_info[:3]))
 
     print("INSTALLED VERSIONS")
     print("------------------")
-    print(f"      alns: {alns.version}")
-    print(f"     numpy: {numpy.version}")
-    print(f"matplotlib: {matplotlib.version}")
+    print(f"      alns: {version('alns')}")
+    print(f"     numpy: {version('numpy')}")
+    print(f"matplotlib: {version('matplotlib')}")
     print(f"    Python: {python_version}")
diff --git a/examples/capacitated_vehicle_routing_problem.ipynb b/examples/capacitated_vehicle_routing_problem.ipynb
@@ -10,8 +10,9 @@
    "outputs": [],
    "source": [
     "import copy\n",
+    "from types import SimpleNamespace\n",
     "\n",
-    "import cvrplib\n",
+    "import vrplib\n",
     "import matplotlib\n",
     "import matplotlib.pyplot as plt\n",
     "import numpy as np\n",
@@ -70,7 +71,7 @@
    },
    "source": [
     "## Data\n",
-    "[CVRPLIB](http://vrp.atd-lab.inf.puc-rio.br/index.php/en/) contains a large collection of CVRP benchmark instances. The library is actively maintained and new best known solutions are updated regularly. We use the `cvrplib` package to read the `ORTEC-n242-k12` instance, which consists of 241 customers (+ 1 depot) and 12 vehicles, but we assume that an unlimited number of vehicles is available."
+    "[CVRPLIB](http://vrp.atd-lab.inf.puc-rio.br/index.php/en/) contains a large collection of CVRP benchmark instances. The library is actively maintained and new best known solutions are updated regularly. We use the `vrplib` package to read the `ORTEC-n242-k12` instance, which consists of 241 customers (+ 1 depot) and 12 vehicles, but we assume that an unlimited number of vehicles is available."
    ]
   },
   {
@@ -82,7 +83,8 @@
    },
    "outputs": [],
    "source": [
-    "data, bks = cvrplib.read('data/ORTEC-n242-k12.vrp', 'data/ORTEC-n242-k12.sol')"
+    "data = vrplib.read_instance('data/ORTEC-n242-k12.vrp')\n",
+    "bks = SimpleNamespace(**vrplib.read_solution('data/ORTEC-n242-k12.sol'))"
    ]
   },
   {
@@ -113,15 +115,15 @@
     "\n",
     "    for idx, route in enumerate(solution.routes):\n",
     "        ax.plot(\n",
-    "            [data.coordinates[loc][0] for loc in [0] + route + [0]],\n",
-    "            [data.coordinates[loc][1] for loc in [0] + route + [0]],\n",
+    "            [data[\"node_coord\"][loc][0] for loc in [0] + route + [0]],\n",
+    "            [data[\"node_coord\"][loc][1] for loc in [0] + route + [0]],\n",
     "            color=cmap[idx],\n",
     "            marker='.'\n",
     "        )\n",
     "        \n",
     "    # Plot the depot\n",
     "    kwargs = dict(label=\"Depot\", zorder=3, marker=\"*\", s=750)\n",
-    "    ax.scatter(*data.coordinates[0], c=\"tab:red\", **kwargs) \n",
+    "    ax.scatter(*data[\"node_coord\"][0], c=\"tab:red\", **kwargs) \n",
     "\n",
     "    ax.set_title(f\"{name}\\n Total distance: {solution.cost}\")\n",
     "    ax.set_xlabel(\"X-coordinate\")\n",
@@ -216,8 +218,11 @@
     "        raise ValueError(f\"Solution does not contain customer {customer}.\")\n",
     "        \n",
     "def route_cost(route):\n",
+    "    distances = data[\"edge_weight\"]\n",
     "    tour = [0] + route + [0]\n",
-    "    return sum(data.distances[tour[idx]][tour[idx+1]] for idx in range(len(tour) - 1))"
+    "\n",
+    "    return sum(distances[tour[idx]][tour[idx + 1]]\n",
+    "               for idx in range(len(tour) - 1))"
    ]
   },
   {
@@ -250,7 +255,7 @@
    "outputs": [],
    "source": [
     "degree_of_destruction = 0.05\n",
-    "customers_to_remove = int((data.dimension - 1) * degree_of_destruction)"
+    "customers_to_remove = int((data[\"dimension\"] - 1) * degree_of_destruction)"
    ]
   },
   {
@@ -269,7 +274,7 @@
     "    destroyed = state.copy()\n",
     "\n",
     "    for customer in rnd_state.choice(\n",
-    "        range(1, data.dimension), customers_to_remove, replace=False\n",
+    "        range(1, data[\"dimension\"]), customers_to_remove, replace=False\n",
     "    ):\n",
     "        destroyed.unassigned.append(customer)\n",
     "        route = destroyed.find_route(customer)\n",
@@ -348,24 +353,20 @@
     "    \"\"\"\n",
     "    Checks if inserting customer does not exceed vehicle capacity.\n",
     "    \"\"\"\n",
-    "    total = sum(data.demands[cust] for cust in route) + data.demands[customer]\n",
-    "    return total <= data.capacity\n",
+    "    total = data[\"demand\"][route].sum() + data[\"demand\"][customer]\n",
+    "    return total <= data[\"capacity\"]\n",
     "\n",
     "\n",
     "def insert_cost(customer, route, idx):\n",
     "    \"\"\"\n",
     "    Computes the insertion cost for inserting customer in route at idx.\n",
     "    \"\"\"\n",
+    "    dist = data[\"edge_weight\"]\n",
     "    pred = 0 if idx == 0 else route[idx - 1]\n",
     "    succ = 0 if idx == len(route) else route[idx]\n",
     "\n",
-    "    # Increase in cost by adding the customer\n",
-    "    cost = data.distances[pred][customer] + data.distances[customer][succ]\n",
-    "\n",
-    "    # Decrease in cost by removing old edge (pred, succ)\n",
-    "    cost -= data.distances[pred][succ]\n",
-    "\n",
-    "    return cost"
+    "    # Increase in cost of adding customer, minus cost of removing old edge\n",
+    "    return dist[pred][customer] + dist[customer][succ] - dist[pred][succ]"
    ]
   },
   {
@@ -392,7 +393,7 @@
     "    \"\"\"\n",
     "    Return the nearest neighbors of the customer, excluding the depot.\n",
     "    \"\"\"\n",
-    "    locations = np.argsort(data.distances[customer])\n",
+    "    locations = np.argsort(data[\"edge_weight\"][customer])\n",
     "    return locations[locations != 0]\n",
     "\n",
     "\n",
@@ -402,7 +403,7 @@
     "    customer is added until the route has met the vehicle capacity limit.\n",
     "    \"\"\"\n",
     "    routes = []\n",
-    "    unvisited = list(range(1, data.dimension))\n",
+    "    unvisited = set(range(1, data[\"dimension\"]))\n",
     "\n",
     "    while unvisited:\n",
     "        route = [0]  # Start at the depot\n",
@@ -413,12 +414,12 @@
     "            current = route[-1]\n",
     "            nearest = [nb for nb in neighbors(current) if nb in unvisited][0]\n",
     "\n",
-    "            if route_demands + data.demands[nearest] > data.capacity:\n",
+    "            if route_demands + data[\"demand\"][nearest] > data[\"capacity\"]:\n",
     "                break\n",
     "\n",
     "            route.append(nearest)\n",
     "            unvisited.remove(nearest)\n",
-    "            route_demands += data.demands[nearest]\n",
+    "            route_demands += data[\"demand\"][nearest]\n",
     "\n",
     "        customers = route[1:]  # Remove the depot\n",
     "        routes.append(customers)\n",
@@ -617,7 +618,7 @@
     "    max_string_removals = min(len(state.routes), MAX_STRING_REMOVALS)\n",
     "\n",
     "    destroyed_routes = []\n",
-    "    center = rnd_state.randint(1, data.dimension)\n",
+    "    center = rnd_state.randint(1, data[\"dimension\"])\n",
     "\n",
     "    for customer in neighbors(center):\n",
     "        if len(destroyed_routes) >= max_string_removals:\n",

diff --git a/pyproject.toml b/pyproject.toml
@@ -1,6 +1,6 @@
 [tool.poetry]
 name = "alns"
-version = "5.0.4"
+version = "5.1.0"
 description = "A flexible implementation of the adaptive large neighbourhood search (ALNS) algorithm."
 authors = ["Niels Wouda <[email protected]>"]
 license = "MIT"
@@ -15,10 +15,10 @@ packages = [
 classifiers = [
     "License :: OSI Approved :: MIT License",
     "Programming Language :: Python :: 3",
-    "Programming Language :: Python :: 3.7",
     "Programming Language :: Python :: 3.8",
     "Programming Language :: Python :: 3.9",
     "Programming Language :: Python :: 3.10",
+    "Programming Language :: Python :: 3.11",
     "Intended Audience :: Developers",
     "Intended Audience :: Science/Research",
     "Development Status :: 5 - Production/Stable",
@@ -32,9 +32,11 @@ classifiers = [
 [tool.poetry.dependencies]
 python = "^3.8, <4.0"
 numpy = ">=1.18.0"
-matplotlib = ">=2.2.0"
+matplotlib = ">=3.5.0"
 
-[tool.poetry.dev-dependencies]
+# This group is needed to develop the package itself.
+[tool.poetry.group.dev.dependencies]
+vrplib = "^1.0.1"
 pre-commit = "^2.20.0"
 pytest = ">=6.0.0"
 pytest-cov = ">=2.6.1"