option: "unique first names" and "relative/total"

brute_force.py

@@ -38,20 +38,33 @@ def load_stats():
 
 def team_table_json():
     players, preferences = load_stats()
-    mean, team0, team1 = apply_brute_force(players, preferences)
+    best = apply_brute_force(players, preferences)
-    data = {}
+    data = {k: {} for k in best}
-    for i, team in enumerate([team0, team1]):
+    for k, v in best.items():
-        tablename = f"Team {i+1}"
+        mean, team0, team1 = v[0]
-        data[tablename] = []
+        overall_matches = 0
-        for p in sorted(list(team)):
+        overall_preference_statements = 0
-            prefs = preferences[p]
+        for i, team in enumerate([team0, team1]):
-            matches = sum([pref in team for pref in preferences[p]])
+            tablename = f"Team {i+1}"
-            data[tablename].append([p, matches, len(prefs)])
+            data[k][tablename] = []
+            for p in sorted(list(team)):
+                prefs = preferences[p]
+                matches = sum([pref in team for pref in preferences[p]])
+                data[k][tablename].append([p, matches, len(prefs)])
+                overall_matches += matches
+                overall_preference_statements += len(prefs)
+        # data[k]["overall_matches"] = overall_matches
+        # data[k]["overall_preference_statements"] = overall_preference_statements
 
     with open("prefs_page/src/table.json", "w") as f:
         json.dump(data, f)
 
 
+def unique_names(team):
+    """check if first names are unique"""
+    return len(set(team)) == len(set([p.split()[0] for p in team]))
+
+
 def apply_brute_force(players, preferences):
     def evaluate_teams(team0, team1):
         scores = []
@@ -63,33 +76,43 @@ def apply_brute_force(players, preferences):
                     percentages.append(scores[-1] / len(preferences[p]))
         return np.mean(scores), np.mean(percentages) * 100
 
-    best_score = [(0, [], [])]
+    best = {
-    best_percentage = [(0, [], [])]
+        f"{i},{j}": [(0, [], [])]
+        for i, j in itertools.product(["total", "relative"], ["unique", "non-unique"])
+    }
+
     for team0 in itertools.combinations(players, 9):
         team1 = {player for player in players if player not in team0}
         score, percentage = evaluate_teams(team0, team1)
-        if score > best_score[0][0]:
+        for k, v in best.items():
-            best_score = [(score, team0, team1)]
+            if k.startswith("total"):
-        if score == best_score[0][0] and set(team0) != set(best_score[0][1]):
+                meassure = score
-            best_score.append((score, team0, team1))
+            elif k.startswith("relative"):
-        if percentage > best_percentage[0][0]:
+                meassure = percentage
-            best_percentage = [(percentage, team0, team1)]
+            if meassure > best[k][0][0]:
-        if percentage == best_percentage[0][0] and set(team0) != set(best_score[0][1]):
+                if k.endswith(",unique") and not (
-            best_percentage.append((percentage, team0, team1))
+                    unique_names(team0) and unique_names(team1)
+                ):
+                    continue
+                best[k] = [(meassure, team0, team1)]
+            elif meassure == best[k][0][0] and set(team0) != set(best[k][0][1]):
+                if k.endswith(",unique") and not (
+                    unique_names(team0) and unique_names(team1)
+                ):
+                    continue
+                best[k].append((meassure, team0, team1))
 
     if __name__ == "__main__":
-        for result in best_score:
+        for k, v in best.items():
-            print(result[0])
+            print("##", k)
-            print(result[1])
+            for result in v:
-            print(result[2])
+                print(result[0])
-
+                print(sorted(result[1]))
-        for result in best_percentage:
+                print(sorted(result[2]))
-            print(result[0])
+            print()
-            print(result[1])
-            print(result[2])
 
     # team_table(score, team0, team1)
-    return best_percentage[0]
+    return best
 
 
 if __name__ == "__main__":

prefs_page/src/App.css

@@ -1,5 +1,5 @@
 #root {
-  max-width: 60vw;
+  max-width: 70vw;
   margin: 0 auto;
   padding: 2rem;
   text-align: center;
@@ -11,4 +11,5 @@
 
 .read-the-docs {
   color: #888;
+  padding: 0;
 }

prefs_page/src/Table.tsx

@@ -1,3 +1,4 @@
+import { useState } from "react";
 import Table from "@mui/material/Table";
 import TableBody from "@mui/material/TableBody";
 import TableCell from "@mui/material/TableCell";
@@ -6,12 +7,47 @@ import TableHead from "@mui/material/TableHead";
 import TableRow from "@mui/material/TableRow";
 import Paper from "@mui/material/Paper";
 import data from "./table.json";
+import {
+  Box,
+  Checkbox,
+  FormControlLabel,
+  Stack,
+  Switch,
+  Typography,
+} from "@mui/material";
+
+interface Data {
+  [index: string]: Teams;
+}
+
+interface Teams {
+  teamname: Row;
+}
 
 type Row = [player: string, fulfilled: number, total: number];
 
-export default function TeamTables() {
+function RenderTable(data: object) {
+  let nMatches: number = 0;
+  let nTotal: number = 0;
+  let nPlayers: number = 0;
+  let relativeScore: number = 0.0;
+  for (const rows of Object.values(data)) {
+    for (const row of rows) {
+      nMatches += row[1];
+      nTotal += row[2];
+      relativeScore += row[1] / row[2];
+      nPlayers++;
+    }
+  }
   return (
     <>
+      <Paper elevation={2} sx={{ p: 2, display: "inline-block" }}>
+        average wishes fulfilled:{" "}
+        <Typography sx={{ fontFamily: "monospace" }}>
+          {(nMatches / nPlayers).toPrecision(2)} (
+          {((relativeScore / nPlayers) * 100).toPrecision(3)}%)
+        </Typography>
+      </Paper>
       {Object.entries(data).map(([teamname, rows]) => (
         <>
           <h1>{teamname}</h1>
@@ -47,3 +83,69 @@ export default function TeamTables() {
     </>
   );
 }
+
+export default function TeamTables() {
+  const [total, setTotal] = useState("relative");
+  const [unique, setUnique] = useState("non-unique");
+
+  const handleTotalChange = (event: React.ChangeEvent<HTMLInputElement>) => {
+    if (event.target.checked) {
+      setTotal("relative");
+    } else {
+      setTotal("total");
+    }
+  };
+
+  const handleUniqueChange = (event: React.ChangeEvent<HTMLInputElement>) => {
+    if (event.target.checked) {
+      setUnique("unique");
+    } else {
+      setUnique("non-unique");
+    }
+  };
+
+  let tabledata: Data = data as unknown as Data;
+
+  return (
+    <>
+      <Box
+        sx={{
+          m: "auto",
+          display: "flex",
+          flexWrap: "wrap",
+          justifyContent: "center",
+        }}
+      >
+        <Paper elevation={2} sx={{ m: 1, p: 1 }}>
+          <Typography className="read-the-docs">according to</Typography>
+          <Stack
+            direction="row"
+            spacing={1}
+            sx={{ p: "0 16px", m: "0 8px", alignItems: "center" }}
+          >
+            <Typography>total</Typography>
+            <Switch defaultChecked onChange={handleTotalChange} />
+            <Typography>relative</Typography>
+          </Stack>
+          <Typography className="read-the-docs">
+            number of wishes fulfilled
+          </Typography>
+        </Paper>
+
+        <Paper elevation={2} sx={{ m: 1, p: 1, justifyContent: "center" }}>
+          <FormControlLabel
+            sx={{ padding: 2, m: 1 }}
+            control={
+              <Checkbox
+                checked={unique === "unique"}
+                onChange={handleUniqueChange}
+              />
+            }
+            label="unique first names"
+          />
+        </Paper>
+      </Box>
+      {RenderTable(tabledata[[total, unique].join(",") as string])}
+    </>
+  );
+}