diff --git a/foo.py b/foo.py index 9159e16..365c310 100644 --- a/foo.py +++ b/foo.py @@ -5,19 +5,39 @@ from dataclasses import dataclass from math import floor from datetime import datetime +def _add_accumulated_score(df: pandas.DataFrame): + acc_col = pandas.Series([0.0]).repeat(len(df)).reset_index(drop=True) + + acc = 0.0 + for i, row in enumerate(df.itertuples()): + acc += row.score + acc_col[i] = acc + + df['accumulated_score'] = acc_col + def load_score_log(path: str) -> pandas.DataFrame: - return pandas.read_csv(path, sep=',', + scores = pandas.read_csv(path, sep=',', dtype={'score': int, 'sourcename': str, 'name': str, 'mapx': int, 'mapy': int}, parse_dates=['when'], date_format='%d/%m/%Y %H:%M') + scores.sort_values('when', inplace=True) + _add_accumulated_score(scores) + return scores def generate_station_stats(score_log: pandas.DataFrame) -> pandas.DataFrame: + station_count = len(score_log['name'].unique()) + # every station in the score log should have a first visit, so create summary based on that summary = score_log[score_log['sourcename'] == 'First Visit'][['name', 'mapx', 'mapy', 'when']] summary.rename(columns={'when': 'first_visit'}, inplace=True) + assert len(summary) == station_count + + common_join_args = {'on':'name', 'how':'left', 'validate': '1:1'} + # add total score - summary = pandas.merge(summary, score_log[['name', 'score']].groupby('name').sum(), on='name', validate='1:1') + summary = pandas.merge(summary, score_log[['name', 'score']].groupby('name').sum(), **common_join_args) summary.rename(columns={'score': 'total_score'}, inplace=True) + assert len(summary) == station_count boosts = score_log[score_log['sourcename'] == 'Output Boost'][['name', 'score']].groupby('name') @@ -25,34 +45,40 @@ def generate_station_stats(score_log: pandas.DataFrame) -> pandas.DataFrame: total_boosts = boosts.sum() total_boosts['totalboostduration'] = total_boosts['score'].apply(lambda x: 10 * x) total_boosts.rename(columns={'score': 'totalboostscore'}, inplace=True) - summary = pandas.merge(summary, total_boosts, on='name') + summary = pandas.merge(summary, total_boosts, **common_join_args) + assert len(summary) == station_count # add max boosts max_boosts = boosts.max() max_boosts['maxboostduration'] = max_boosts['score'].apply(lambda x: 10 * x) max_boosts.rename(columns={'score': 'maxboostscore'}, inplace=True) - summary = pandas.merge(summary, max_boosts, on='name') + summary = pandas.merge(summary, max_boosts, **common_join_args) + assert len(summary) == station_count visits = score_log[(score_log['sourcename'] == 'Visit') | (score_log['sourcename'] == 'First Visit')][['name', 'score']].groupby('name') # add total visits (count) - summary = pandas.merge(summary, visits.count(), on='name', validate='1:1') + summary = pandas.merge(summary, visits.count(), **common_join_args) summary.rename(columns={'score': 'totalvisits'}, inplace=True) + assert len(summary) == station_count captures = score_log[score_log['sourcename'] == 'Capture'][['name', 'score']].groupby('name') # add captures (count) - summary = pandas.merge(summary, captures.count(), on='name', validate='1:1') + summary = pandas.merge(summary, captures.count(), **common_join_args) summary.rename(columns={'score': 'captures'}, inplace=True) + assert len(summary) == station_count # add max held duration (max capture score) - summary = pandas.merge(summary, captures.max(), on='name', validate='1:1') + summary = pandas.merge(summary, captures.max(), **common_join_args) summary.rename(columns={'score': 'maxheldduration'}, inplace=True) + assert len(summary) == station_count # add total held duration (sum capture score) - summary = pandas.merge(summary, captures.sum(), on='name', validate='1:1') + summary = pandas.merge(summary, captures.sum(), **common_join_args) summary.rename(columns={'score': 'totalheldduration'}, inplace=True) + assert len(summary) == station_count return summary def generate_score_per_second(score_log: pandas.DataFrame) -> pandas.DataFrame: @@ -89,15 +115,5 @@ def generate_score_per_second(score_log: pandas.DataFrame) -> pandas.DataFrame: scoreseconds.sort_values(by=['when'], inplace=True) scoreseconds.reset_index(drop=True, inplace=True) - acc_col = pandas.Series([0.0]).repeat(len(scoreseconds)).reset_index(drop=True) - - acc = 0.0 - for i, row in enumerate(scoreseconds.itertuples()): - acc += row.score - acc_col[i] = acc - - scoreseconds['accumulated_score'] = acc_col - del acc - del acc_col - + _add_accumulated_score(scoreseconds) return scoreseconds diff --git a/notebook.ipynb b/notebook.ipynb index 05e40ee..ef3bfa4 100644 --- a/notebook.ipynb +++ b/notebook.ipynb @@ -2,14 +2,12 @@ "cells": [ { "cell_type": "code", - "id": "b1623679", + "id": "initial_id", "metadata": { - "vscode": { - "languageId": "plaintext" - }, + "collapsed": true, "ExecuteTime": { - "end_time": "2025-08-26T15:15:40.301728Z", - "start_time": "2025-08-26T15:15:40.138900Z" + "end_time": "2025-08-26T16:51:56.681979Z", + "start_time": "2025-08-26T16:51:56.214243Z" } }, "source": [ @@ -21,563 +19,110 @@ "from foo import *" ], "outputs": [], - "execution_count": 43 + "execution_count": 1 }, { - "cell_type": "code", - "id": "388b7c16-61c3-4ddc-ac85-bf2094cbfda0", "metadata": { "ExecuteTime": { - "end_time": "2025-08-19T23:40:17.840982Z", - "start_time": "2025-08-19T23:40:17.825194Z" + "end_time": "2025-08-26T16:51:56.773910Z", + "start_time": "2025-08-26T16:51:56.691695Z" } }, - "source": [ - "scorelog = pandas.read_csv('PolyGenStats-vinzenz-scorelog.csv', sep=',', dtype={'score': int, 'sourcename': str, 'name': str, 'mapx': int, 'mapy': int}, parse_dates=['when'], date_format='%d/%m/%Y %H:%M')\n", - "scorelog" - ], - "outputs": [ - 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.....................
8962025-08-12 13:34:0091Capture0E00
8972025-08-12 13:39:0050VisitPixelbar379602
8982025-08-12 13:42:00164Output BoostSite Sign207874
8992025-08-12 13:50:00694CapturePixelbar379602
9002025-08-12 14:00:00284Output BoostMaker Days Eindhoven115749
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901 rows × 6 columns

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" - ] - }, - "execution_count": 36, - "metadata": {}, - "output_type": "execute_result" - } - ], - "execution_count": 36 - }, - { "cell_type": "code", - "id": "e8888706-1439-4b73-97cc-06dd416d9e23", - "metadata": { - "ExecuteTime": { - "end_time": "2025-08-19T23:39:54.083367Z", - "start_time": "2025-08-19T23:39:54.071862Z" - } - }, "source": [ - "summary = pandas.read_csv('PolyGenStats-vinzenz-summary.csv', sep=',', dtype={'name': str, 'totalvisits': int, 'captures': int, 'totalheldduration': int, 'maxheldduration': int})\n", - "summary" - ], - "outputs": [ - { - "data": { - "text/plain": [ - " name totalvisits captures totalheldduration \\\n", - "0 Site Sign 15 21 61707 \n", - "1 Maker Days Eindhoven 13 10 61044 \n", - "2 Pixelbar 18 17 51151 \n", - "3 Cold North 17 20 49590 \n", - "4 Karaoke Bar 19 16 44169 \n", - "5 CoderDojo Belgium 15 13 42973 \n", - "6 Entrance Arch 19 18 40416 \n", - "7 Main Bar 42 67 33999 \n", - "8 Badge Tent 21 21 31452 \n", - "9 Bridge over troubled waters 28 28 27990 \n", - "10 BornHack 8 5 16419 \n", - "11 Info Desk 19 23 13685 \n", - "12 PolyGen Home Base 18 17 12688 \n", - "13 Milliways 23 47 9763 \n", - "14 Party Bar 12 11 9251 \n", - "15 Heaven 15 9 8980 \n", - "16 Chaos Mauldasch 21 30 7426 \n", - "17 Adyen 24 22 7007 \n", - "18 Tilde Industries 5 4 6215 \n", - "19 Geraffel 9 6 5286 \n", - "20 Food Hacking Base 16 13 4427 \n", - "21 Rose Island Italian Embassy 9 7 3667 \n", - "22 FALSE 7 5 2798 \n", - "23 Matrix 7 6 2251 \n", - "24 0E 1 1 91 \n", - "\n", - " maxheldduration \n", - "0 46380 \n", - "1 44313 \n", - "2 36261 \n", - "3 22971 \n", - "4 23180 \n", - "5 23237 \n", - "6 28498 \n", - "7 16913 \n", - "8 18329 \n", - "9 18829 \n", - "10 7753 \n", - "11 3304 \n", - "12 5316 \n", - "13 3386 \n", - "14 7694 \n", - "15 3756 \n", - "16 1394 \n", - "17 3483 \n", - "18 3365 \n", - "19 1782 \n", - "20 993 \n", - "21 1258 \n", - "22 1969 \n", - "23 1096 \n", - "24 91 " - ], - "text/html": [ - "
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16Chaos Mauldasch213074261394
17Adyen242270073483
18Tilde Industries5462153365
19Geraffel9652861782
20Food Hacking Base16134427993
21Rose Island Italian Embassy9736671258
22FALSE7527981969
23Matrix7622511096
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" - ] - }, - "execution_count": 27, - "metadata": {}, - "output_type": "execute_result" - } - ], - "execution_count": 27 - }, - { - "cell_type": "code", - "id": "3c3ca9ba-b545-4f10-a34d-4c35323363fc", - "metadata": { - "ExecuteTime": { - "end_time": "2025-08-19T23:39:54.465235Z", - "start_time": "2025-08-19T23:39:54.440411Z" - } - }, - "source": [ - "summary = pandas.merge(summary, scorelog[scorelog['sourcename'] == 'First Visit'][['name', 'mapx', 'mapy', 'when']], on='name')\n", - "summary = pandas.merge(summary, scorelog[['name', 'score']].groupby('name').sum(), on='name', validate='1:1')\n", - "summary.rename(columns={'when': 'first_visit', 'score': 'total_score'}, inplace=True)\n", + "vinzenz_score_log = load_score_log('PolyGenStats-vinzenz-scorelog.csv')\n", + "vinzenz_summary = generate_station_stats(vinzenz_score_log)\n", "\n", - "summary" + "fiebertrauma_score_log = load_score_log('PolyGenStats-Fiebertrauma-scorelog.csv')\n", + "fiebertrauma_summary = generate_station_stats(fiebertrauma_score_log)\n", + "\n", + "vinzenz_summary" ], + "id": "bf523274efb801dd", "outputs": [ { "data": { "text/plain": [ - 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\n", @@ -599,1137 +144,463 @@ " \n", " \n", " name\n", - " totalvisits\n", - " captures\n", - " totalheldduration\n", - " maxheldduration\n", " mapx\n", " mapy\n", " first_visit\n", - " score\n", - " \n", - " \n", - " \n", - " \n", - " 0\n", - " Site Sign\n", - " 15\n", - " 21\n", - " 61707\n", - " 46380\n", - " 207\n", - " 874\n", - " 2025-08-08 22:12:00\n", - " 63688\n", - " \n", - " \n", - " 1\n", - " Maker Days Eindhoven\n", - " 13\n", - " 10\n", - " 61044\n", - " 44313\n", - " 115\n", - " 749\n", - " 2025-08-08 22:28:00\n", - " 62440\n", - " \n", - " \n", - " 2\n", - " Pixelbar\n", - " 18\n", - " 17\n", - " 51151\n", - " 36261\n", - " 379\n", - " 602\n", - " 2025-08-09 00:42:00\n", - " 52601\n", - " \n", - " \n", - " 3\n", - " Cold North\n", - " 17\n", - " 20\n", - " 49590\n", - " 22971\n", - " 305\n", - " 402\n", - " 2025-08-08 21:56:00\n", - " 50757\n", - " \n", - " \n", - " 4\n", - " Karaoke Bar\n", - " 19\n", - " 16\n", - " 44169\n", - " 23180\n", - " 292\n", - " 446\n", - " 2025-08-08 21:55:00\n", - " 45272\n", - " \n", - " \n", - " 5\n", - " CoderDojo Belgium\n", - " 15\n", - " 13\n", - " 42973\n", - " 23237\n", - " 34\n", - " 523\n", - " 2025-08-08 21:39:00\n", - " 44374\n", - " \n", - " \n", - " 6\n", - " Entrance Arch\n", - " 19\n", - " 18\n", - " 40416\n", - " 28498\n", - " 240\n", - " 916\n", - " 2025-08-08 22:10:00\n", - " 41486\n", - " \n", - " \n", - " 7\n", - " Main Bar\n", - " 42\n", - " 67\n", - " 33999\n", - " 16913\n", - " 190\n", - " 570\n", - " 2025-08-08 20:22:00\n", - " 36884\n", - " \n", - " \n", - " 8\n", - " Badge Tent\n", - " 21\n", - " 21\n", - " 31452\n", - " 18329\n", - " 328\n", - " 607\n", - " 2025-08-08 20:23:00\n", - " 32599\n", - " \n", - " \n", - " 9\n", - " Bridge over troubled waters\n", - " 28\n", - " 28\n", - " 27990\n", - " 18829\n", - " 251\n", - " 553\n", - " 2025-08-09 02:28:00\n", - " 29550\n", - " \n", - " \n", - " 10\n", - " BornHack\n", - " 8\n", - " 5\n", - " 16419\n", - " 7753\n", - " 82\n", - " 337\n", - " 2025-08-10 19:51:00\n", - " 17711\n", - " \n", - " \n", - " 11\n", - " Info Desk\n", - " 19\n", - " 23\n", - " 13685\n", - " 3304\n", - " 216\n", - " 505\n", - " 2025-08-08 20:14:00\n", - " 17026\n", - " \n", - " \n", - " 12\n", - " PolyGen Home Base\n", - " 18\n", - " 17\n", - " 12688\n", - " 5316\n", - " 322\n", - " 591\n", - " 2025-08-09 17:52:00\n", - " 14376\n", - " \n", - " \n", - " 13\n", - " Milliways\n", - " 23\n", - " 47\n", - " 9763\n", - " 3386\n", - " 95\n", - " 498\n", - " 2025-08-09 17:07:00\n", - " 11003\n", - " \n", - " \n", - " 14\n", - " Party Bar\n", - " 12\n", - " 11\n", - " 9251\n", - " 7694\n", - " 67\n", - " 289\n", - " 2025-08-08 22:54:00\n", - " 13340\n", - " \n", - " \n", - " 15\n", - " Heaven\n", - " 15\n", - " 9\n", - " 8980\n", - " 3756\n", - " 183\n", - " 227\n", - " 2025-08-08 21:46:00\n", - " 10057\n", - " \n", - " \n", - " 16\n", - " Chaos Mauldasch\n", - " 21\n", - " 30\n", - " 7426\n", - " 1394\n", - " 164\n", - " 635\n", - " 2025-08-08 22:37:00\n", - " 8564\n", - " \n", - " \n", - " 17\n", - " Adyen\n", - " 24\n", - " 22\n", - " 7007\n", - " 3483\n", - " 120\n", - " 637\n", - " 2025-08-08 22:34:00\n", - " 8281\n", - " \n", - " \n", - " 18\n", - " Tilde Industries\n", - " 5\n", - " 4\n", - " 6215\n", - " 3365\n", - " 361\n", - " 468\n", - " 2025-08-11 17:42:00\n", - " 6515\n", - " \n", - " \n", - " 19\n", - " Geraffel\n", - " 9\n", - " 6\n", - " 5286\n", - " 1782\n", - " 188\n", - " 166\n", - " 2025-08-08 23:03:00\n", - " 6899\n", - " \n", - " \n", - " 20\n", - " Food Hacking Base\n", - " 16\n", - " 13\n", - " 4427\n", - " 993\n", - " 119\n", - " 571\n", - " 2025-08-10 18:31:00\n", - " 5308\n", - " \n", - " \n", - " 21\n", - " Rose Island Italian Embassy\n", - " 9\n", - " 7\n", - " 3667\n", - " 1258\n", - " 41\n", - " 475\n", - " 2025-08-10 04:12:00\n", - " 4167\n", - " \n", - " \n", - " 22\n", - " FALSE\n", - " 7\n", - " 5\n", - " 2798\n", - " 1969\n", - " 163\n", - " 425\n", - " 2025-08-08 23:17:00\n", - " 3863\n", - " \n", - " \n", - " 23\n", - " Matrix\n", - " 7\n", - " 6\n", - " 2251\n", - " 1096\n", - " 164\n", - " 731\n", - " 2025-08-11 15:33:00\n", - " 2696\n", - " \n", - " \n", - " 24\n", - " 0E\n", - " 1\n", - " 1\n", - " 91\n", - " 91\n", - " 0\n", - " 0\n", - " 2025-08-12 13:32:00\n", - " 191\n", - " \n", - " \n", - "\n", - "
" - ] - }, - "execution_count": 28, - "metadata": {}, - "output_type": "execute_result" - } - ], - "execution_count": 28 - }, - { - "cell_type": "code", - "id": "9f15abc665d134d7", - "metadata": { - "ExecuteTime": { - "end_time": "2025-08-19T23:39:55.025235Z", - "start_time": "2025-08-19T23:39:55.004437Z" - } - }, - "source": [ - "boosts = scorelog[scorelog['sourcename'] == 'Output Boost'][['name', 'score']].groupby('name')\n", - "\n", - "total_boosts = boosts.sum()\n", - "total_boosts['totalboostduration'] = total_boosts['score'].apply(lambda x: 10 * x)\n", - "total_boosts.rename(columns={'score': 'totalboostscore'}, inplace=True)\n", - "summary = pandas.merge(summary, total_boosts, on='name')\n", - "del total_boosts\n", - "\n", - "max_boosts = boosts.max()\n", - "max_boosts['maxboostduration'] = max_boosts['score'].apply(lambda x: 10 * x)\n", - "max_boosts.rename(columns={'score': 'maxboostscore'}, inplace=True)\n", - "summary = pandas.merge(summary, max_boosts, on='name')\n", - "del max_boosts\n", - "\n", - "del boosts\n", - "summary" - ], - "outputs": [ - { - "data": { - "text/plain": [ - " name totalvisits captures totalheldduration \\\n", - "0 Site Sign 15 21 61707 \n", - "1 Maker Days Eindhoven 13 10 61044 \n", - "2 Cold North 17 20 49590 \n", - "3 Karaoke Bar 19 16 44169 \n", - "4 CoderDojo Belgium 15 13 42973 \n", - "5 Entrance Arch 19 18 40416 \n", - "6 Main Bar 42 67 33999 \n", - "7 Badge Tent 21 21 31452 \n", - "8 Bridge over troubled waters 28 28 27990 \n", - "9 BornHack 8 5 16419 \n", - "10 Info Desk 19 23 13685 \n", - "11 PolyGen Home Base 18 17 12688 \n", - "12 Milliways 23 47 9763 \n", - "13 Party Bar 12 11 9251 \n", - "14 Heaven 15 9 8980 \n", - "15 Chaos Mauldasch 21 30 7426 \n", - "16 Adyen 24 22 7007 \n", - "17 Geraffel 9 6 5286 \n", - "18 Food Hacking Base 16 13 4427 \n", - "19 FALSE 7 5 2798 \n", - "20 Matrix 7 6 2251 \n", - "\n", - " maxheldduration mapx mapy first_visit score totalboostscore \\\n", - "0 46380 207 874 2025-08-08 22:12:00 63688 681 \n", - "1 44313 115 749 2025-08-08 22:28:00 62440 696 \n", - "2 22971 305 402 2025-08-08 21:56:00 50757 267 \n", - "3 23180 292 446 2025-08-08 21:55:00 45272 103 \n", - "4 23237 34 523 2025-08-08 21:39:00 44374 101 \n", - "5 28498 240 916 2025-08-08 22:10:00 41486 70 \n", - "6 16913 190 570 2025-08-08 20:22:00 36884 735 \n", - "7 18329 328 607 2025-08-08 20:23:00 32599 47 \n", - "8 18829 251 553 2025-08-09 02:28:00 29550 110 \n", - "9 7753 82 337 2025-08-10 19:51:00 17711 842 \n", - "10 3304 216 505 2025-08-08 20:14:00 17026 2341 \n", - "11 5316 322 591 2025-08-09 17:52:00 14376 738 \n", - "12 3386 95 498 2025-08-09 17:07:00 11003 40 \n", - "13 7694 67 289 2025-08-08 22:54:00 13340 3439 \n", - "14 3756 183 227 2025-08-08 21:46:00 10057 277 \n", - "15 1394 164 635 2025-08-08 22:37:00 8564 38 \n", - "16 3483 120 637 2025-08-08 22:34:00 8281 24 \n", - "17 1782 188 166 2025-08-08 23:03:00 6899 1113 \n", - "18 993 119 571 2025-08-10 18:31:00 5308 31 \n", - "19 1969 163 425 2025-08-08 23:17:00 3863 665 \n", - "20 1096 164 731 2025-08-11 15:33:00 2696 45 \n", - "\n", - " totalboostduration maxboostscore maxboostduration \n", - "0 6810 199 1990 \n", - "1 6960 284 2840 \n", - "2 2670 142 1420 \n", - "3 1030 47 470 \n", - "4 1010 101 1010 \n", - "5 700 70 700 \n", - "6 7350 537 5370 \n", - "7 470 28 280 \n", - "8 1100 76 760 \n", - "9 8420 324 3240 \n", - "10 23410 2262 22620 \n", - "11 7380 190 1900 \n", - "12 400 35 350 \n", - "13 34390 3350 33500 \n", - "14 2770 125 1250 \n", - "15 380 38 380 \n", - "16 240 15 150 \n", - "17 11130 902 9020 \n", - "18 310 28 280 \n", - "19 6650 651 6510 \n", - "20 450 45 450 " - ], - "text/html": [ - "
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nametotalvisitscapturestotalhelddurationmaxhelddurationmapxmapyfirst_visitscoretotal_scoretotalboostscoretotalboostdurationmaxboostscoremaxboostdurationtotalvisitscapturesmaxhelddurationtotalheldduration
0Site Sign152161707463802078742025-08-08 22:12:006368868168101991990
1Maker Days Eindhoven131061044443131157492025-08-08 22:28:006244069669602842840
2Cold North172049590229713054022025-08-08 21:56:005075726726701421420
3Karaoke Bar191644169231802924462025-08-08 21:55:0045272103103047470
4CoderDojo Belgium15134297323237345232025-08-08 21:39:004437410110101011010
5Entrance Arch191840416284982409162025-08-08 22:10:00414867070070700
6Main Bar426733999169131905702025-08-08 20:22:003688473573505375370
7Badge Tent212131452183293286072025-08-08 20:23:00325994747028280
8Bridge over troubled waters282827990188292515532025-08-09 02:28:0029550110110076760
9BornHack85164197753823372025-08-10 19:51:001771184284203243240
10Info Desk19231368533042165052025-08-08 20:14:0017026234123410226222620
11PolyGen Home Base18171268853163225912025-08-09 17:52:001437673873801901900
12Milliways2341.023410.02262.022620.019234797633386954982025-08-09 17:07:00110034040035350330413685
13Party Bar1211925176941Main Bar1905702025-08-08 20:22:0036884735.07350.0537.05370.042672892025-08-08 22:54:00133403439343903350335001691333999
14Heaven2Badge Tent3286072025-08-08 20:23:003259947.0470.028.0280.021211832931452
3CoderDojo Belgium345232025-08-08 21:39:0044374101.01010.0101.01010.015989803756132323742973
4Heaven1832272025-08-08 21:46:001005727727701251250277.02770.0125.01250.015937568980
15Chaos Mauldasch5Karaoke Bar2924462025-08-08 21:55:0045272103.01030.047.0470.019162318044169
6Cold North3054022025-08-08 21:56:0050757267.02670.0142.01420.017202297149590
7Entrance Arch2409162025-08-08 22:10:004148670.0700.070.0700.019182849840416
8Site Sign2078742025-08-08 22:12:0063688681.06810.0199.01990.0152130742613941646352025-08-08 22:37:00856438380383804638061707
169Maker Days Eindhoven1157492025-08-08 22:28:0062440696.06960.0284.02840.013104431361044
10Adyen2422700734831206372025-08-08 22:34:00828124.0240.015.0150.024240151502234837007
1711Chaos Mauldasch1646352025-08-08 22:37:00856438.0380.038.0380.0213013947426
12Party Bar672892025-08-08 22:54:00133403439.034390.03350.033500.0121176949251
13Geraffel96528617821881662025-08-08 23:03:00689911131113090290201113.011130.0902.09020.09617825286
18Food Hacking Base161344279931195712025-08-10 18:31:0053083131028280
1914FALSE75279819691634252025-08-08 23:17:00386366566506516510665.06650.0651.06510.07519692798
15Pixelbar3796022025-08-09 00:42:0052601NaNNaNNaNNaN18173626151151
16Bridge over troubled waters2515532025-08-09 02:28:0029550110.01100.076.0760.028281882927990
17Milliways954982025-08-09 17:07:001100340.0400.035.0350.0234733869763
18PolyGen Home Base3225912025-08-09 17:52:0014376738.07380.0190.01900.01817531612688
19Rose Island Italian Embassy414752025-08-10 04:12:004167NaNNaNNaNNaN9712583667
20Food Hacking Base1195712025-08-10 18:31:00530831.0310.028.0280.016139934427
21BornHack823372025-08-10 19:51:0017711842.08420.0324.03240.085775316419
22Matrix76225110961647312025-08-11 15:33:002696454504545045.0450.045.0450.07610962251
23Tilde Industries3614682025-08-11 17:42:006515NaNNaNNaNNaN5433656215
240E002025-08-12 13:32:00191NaNNaNNaNNaN119191
\n", "
" ] }, - "execution_count": 29, + "execution_count": 2, "metadata": {}, "output_type": "execute_result" } ], - "execution_count": 29 + "execution_count": 2 }, { - "cell_type": "code", - "id": "583c3529-d482-4891-84fa-880920f631b6", "metadata": { "ExecuteTime": { - "end_time": "2025-08-19T23:39:55.305636Z", - "start_time": "2025-08-19T23:39:55.152953Z" + "end_time": "2025-08-26T16:52:18.164994Z", + "start_time": "2025-08-26T16:51:56.837699Z" } }, - "source": [ - "plt.scatter(summary['mapx'], summary['mapy'])\n", - "plt.title('Map positions of reactors')\n", - "plt.show()" - ], - "outputs": [ - { - "data": { - "text/plain": [ - "
" - ], - "image/png": 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STTfdpNdff10Oh0NJSUnKy8vTRx995BtWXWPq1Kl65513dOutt+ruu+9WSkqKDh48qL/97W+aN2+e+vXrd9rPpiHfidNZtWqVJk2apFtvvVU/+tGPdOzYMb3++usKDQ1VZmZmo/YfcErBHEIEBMuJw4xPp65hxq+++qrp2bOnCQ8PN7179zbz5883M2bMMCf/OUky2dnZZuHChb72l112mfn444/rra9mSOubb75ppk2bZmJjY027du1MRkaG2bt3b632f/nLX8xll11mwsPDTXR0tBkzZozZv3+/b/t3331nsrOzTe/evU2HDh2Mw+EwAwcONG+//bbf65w8zNgYY5YsWWKSkpJMmzZt/Ia1njzM2BhjysrKzJQpU0xCQoJp27at6dmzp3n22Wf9ht+e2Dcn6969u8nKyjLGGFNRUWGmTp1q+vXrZyIjI02HDh1Mv379zCuvvFJv/xljzObNm01aWprp2LGjad++vbnuuuvMunXr/NqcyTDjUw293bJlixkxYoSJiYkx4eHhpnv37ua2224zK1eu9LX5/vvvzbhx40ynTp1Mx44dTVpamvnyyy/99rvGgQMHzKRJk8z5559vwsLCTJcuXUxWVpb57rvvfG1O9dkYU/93wpjjn2GHDh1q7cu///1vc/fdd5sePXqYiIgIEx0dba677jrz0Ucf1dtPQGOxGWPxK/uAZspmsyk7O7vWKY+GWL16ta677jotXrz4tCOKAKCl4hoUAABgOQQUAABgOQQUAABgOVyDAgAALIcjKAAAwHIIKAAAwHKa5URt1dXVKiwsVGRkZEBTcQMAgOAxxqisrEwJCQl13gPqRM0yoBQWFjbqvTQAAEDT2bdvX627aJ+sWQaUmtu579u3r1HvqQEAAM4dr9errl27+n7HT6dZBpSa0zp2u52AAgBAM9OQyzO4SBYAAFgOAQUAAFgOAQUAAFgOAQUAAFgOAQUAAFgOAQUAAFgOAQUAAFgOAQUAAFhOs5yoDQBwdqqqjTbkH1RJWbliIyM0IDFaoSHc2wzWQUABgFYmZ3uRZi7dqSJPuW9dvCNCM4YnKT05PoiVAf/BKR4AaEVythdp4sLNfuFEktyeck1cuFk524uCVBngj4ACAK1EVbXRzKU7ZerYVrNu5tKdqqquqwXQtAgoANBKbMg/WOvIyYmMpCJPuTbkH2y6ooBTIKAAQCtRUnbqcHIm7YBziYACAK1EbGREo7YDziUCCgC0EgMSoxXviNCpBhPbdHw0z4DE6KYsC6gTAQUAWonQEJtmDE+SpFohpebxjOFJzIcCSwg4oJSVlWny5Mnq3r272rVrpyuvvFIbN270bTfGaPr06YqPj1e7du2Umpqq3bt3+73GwYMHNWbMGNntdkVFRWn8+PE6dOjQ2e8NAOC00pPjNXdsfzkd/qdxnI4IzR3bn3lQYBkBT9T23//939q+fbtef/11JSQkaOHChUpNTdXOnTt1/vnna/bs2ZozZ45ee+01JSYm6tFHH1VaWpp27typiIjjfxBjxoxRUVGRcnNzdfToUY0bN04TJkzQokWLGn0HAQD+0pPjdUOSk5lkYWk2Y0yDB7z/8MMPioyM1JIlS5SRkeFbn5KSomHDhumJJ55QQkKCHnjgAT344IOSJI/Ho7i4OC1YsECjRo3SF198oaSkJG3cuFGXX365JCknJ0c33nij9u/fr4SEhHrr8Hq9cjgc8ng8stvtge4zAAAIgkB+vwM6xXPs2DFVVVX5joTUaNeundauXav8/Hy53W6lpqb6tjkcDg0cOFB5eXmSpLy8PEVFRfnCiSSlpqYqJCRE69evr/N9Kyoq5PV6/RYAANByBRRQIiMj5XK59MQTT6iwsFBVVVVauHCh8vLyVFRUJLfbLUmKi4vze15cXJxvm9vtVmxsrN/2Nm3aKDo62tfmZLNmzZLD4fAtXbt2DaRsAADQzAR8kezrr78uY4zOP/98hYeHa86cORo9erRCQs7dgKBp06bJ4/H4ln379p2z9wIAAMEXcKro0aOH1qxZo0OHDmnfvn3asGGDjh49qgsvvFBOp1OSVFxc7Pec4uJi3zan06mSkhK/7ceOHdPBgwd9bU4WHh4uu93utwAAgJbrjA97dOjQQfHx8fr++++1YsUK3XzzzUpMTJTT6dTKlSt97bxer9avXy+XyyVJcrlcKi0t1aZNm3xtVq1aperqag0cOPAsdgUAALQUAQ8zXrFihYwx6tWrl7766itNnTpVvXv31rhx42Sz2TR58mQ9+eST6tmzp2+YcUJCgm655RZJUp8+fZSenq577rlH8+bN09GjRzVp0iSNGjWqQSN4AABAyxdwQPF4PJo2bZr279+v6OhoZWZm6qmnnlLbtm0lSb/85S91+PBhTZgwQaWlpRo8eLBycnL8Rv688cYbmjRpkoYMGaKQkBBlZmZqzpw5jbdXAACgWQtoHhSrYB4UAMFQVW2Y3Aw4C4H8fgd8BAUAWqOc7UWauXSnijzlvnXxjgjNGJ7E9PDAOcDNAgGgHjnbizRx4Wa/cCJJbk+5Ji7crJztRUGqDGi5CCgAcBpV1UYzl+5UXefCa9bNXLpTVdXN7mw5YGkEFAA4jQ35B2sdOTmRkVTkKdeG/INNVxTQChBQAOA0SspOHU7OpB2AhiGgAMBpxEZG1N8ogHYAGoaAAgCnMSAxWvGOCJ1qMLFNx0fzDEiMbsqygBaPgAIApxEaYtOM4UmSVCuk1DyeMTyJ+VCARkZAAYB6pCfHa+7Y/nI6/E/jOB0Rmju2P/OgAOcAE7UBQAOkJ8frhiQnM8kCTYSAAgANFBpik6tHTLDLAFoFTvEAAADLIaAAAADLIaAAAADLIaAAAADLIaAAAADLIaAAAADLIaAAAADLIaAAAADLIaAAAADLIaAAAADLIaAAAADLIaAAAADLIaAAAADLIaAAAADLIaAAAADLIaAAAADLIaAAAADLIaAAAADLIaAAAADLIaAAAADLIaAAAADLIaAAAADLIaAAAADLCSigVFVV6dFHH1ViYqLatWunHj166IknnpAxxtfGGKPp06crPj5e7dq1U2pqqnbv3u33OgcPHtSYMWNkt9sVFRWl8ePH69ChQ42zRwAAoNkLKKA888wzmjt3rn73u9/piy++0DPPPKPZs2frpZde8rWZPXu25syZo3nz5mn9+vXq0KGD0tLSVF5e7mszZswY7dixQ7m5uVq2bJk++eQTTZgwofH2CgAANGs2c+Lhj3rcdNNNiouL06uvvupbl5mZqXbt2mnhwoUyxighIUEPPPCAHnzwQUmSx+NRXFycFixYoFGjRumLL75QUlKSNm7cqMsvv1ySlJOToxtvvFH79+9XQkJCrfetqKhQRUWF77HX61XXrl3l8Xhkt9vPeOcBAEDT8Xq9cjgcDfr9DugIypVXXqmVK1fqX//6lyTpn//8p9auXathw4ZJkvLz8+V2u5Wamup7jsPh0MCBA5WXlydJysvLU1RUlC+cSFJqaqpCQkK0fv36Ot931qxZcjgcvqVr166BlA0AAJqZNoE0fvjhh+X1etW7d2+FhoaqqqpKTz31lMaMGSNJcrvdkqS4uDi/58XFxfm2ud1uxcbG+hfRpo2io6N9bU42bdo03X///b7HNUdQAABAyxRQQHn77bf1xhtvaNGiRbr44ou1detWTZ48WQkJCcrKyjpXNSo8PFzh4eHn7PUBAIC1BBRQpk6dqocfflijRo2SJPXt21d79+7VrFmzlJWVJafTKUkqLi5WfHy873nFxcW69NJLJUlOp1MlJSV+r3vs2DEdPHjQ93wAANC6BXQNypEjRxQS4v+U0NBQVVdXS5ISExPldDq1cuVK33av16v169fL5XJJklwul0pLS7Vp0yZfm1WrVqm6uloDBw484x0BAAAtR0BHUIYPH66nnnpK3bp108UXX6wtW7bo+eef19133y1Jstlsmjx5sp588kn17NlTiYmJevTRR5WQkKBbbrlFktSnTx+lp6frnnvu0bx583T06FFNmjRJo0aNqnMEDwAAaH0CCigvvfSSHn30Ud17770qKSlRQkKC/t//+3+aPn26r80vf/lLHT58WBMmTFBpaakGDx6snJwcRURE+Nq88cYbmjRpkoYMGaKQkBBlZmZqzpw5jbdXAACgWQtoHhSrCGQcNQAAsIZzNg8KAABAUyCgAAAAyyGgAAAAyyGgAAAAyyGgAAAAyyGgAAAAyyGgAAAAyyGgAAAAyyGgAAAAyyGgAAAAywnoXjxAS1JVbbQh/6BKysoVGxmhAYnRCg2xBbssAIAIKGilcrYXaebSnSrylPvWxTsiNGN4ktKT44NYGQBA4hQPWqGc7UWauHCzXziRJLenXBMXblbO9qIgVQYAqEFAQatSVW00c+lO1XUL75p1M5fuVFV1s7vJNwC0KAQUtCob8g/WOnJyIiOpyFOuDfkHm64oAEAtBBS0KiVlpw4nZ9IOAHBuEFDQqsRGRjRqOwDAuUFAQasyIDFa8Y4InWowsU3HR/MMSIxuyrIAACchoKBVCQ2xacbwJEmqFVJqHs8YnsR8KCepqjbK23NAS7Z+o7w9B7iIGMA5xzwoaHXSk+M1d2z/WvOgOJkHpU7MGQMgGGzGmGb3v0Jer1cOh0Mej0d2uz3Y5aCZYibZ+tXMGXPyPxI1vTR3bH9CCoAGC+T3myMoaLVCQ2xy9YgJdhmWVd+cMTYdnzPmhiQnwQ5Ao+MaFAB1Ys4YAMFEQAFQJ+aMARBMBBQAdWLOGADBREABUCfmjAEQTAQUAHVizhgAwURAAXBKNXPGOB3+p3GcjgiGGAM4pxhmDOC00pPjdUOSkzljADQpAgqAejFnDICmxikeAABgOQQUAABgOQQUAABgOQEFlAsuuEA2m63Wkp2dLUkqLy9Xdna2YmJi1LFjR2VmZqq4uNjvNQoKCpSRkaH27dsrNjZWU6dO1bFjxxpvjwAAQLMXUEDZuHGjioqKfEtubq4k6dZbb5UkTZkyRUuXLtXixYu1Zs0aFRYWasSIEb7nV1VVKSMjQ5WVlVq3bp1ee+01LViwQNOnT2/EXQIAAM2dzRhT181KG2Ty5MlatmyZdu/eLa/Xq86dO2vRokUaOXKkJOnLL79Unz59lJeXp0GDBmn58uW66aabVFhYqLi4OEnSvHnz9NBDD+nbb79VWFhYg943kNs1AwAAawjk9/uMr0GprKzUwoULdffdd8tms2nTpk06evSoUlNTfW169+6tbt26KS8vT5KUl5envn37+sKJJKWlpcnr9WrHjh2nfK+Kigp5vV6/BQAAtFxnHFDef/99lZaW6q677pIkud1uhYWFKSoqyq9dXFyc3G63r82J4aRme822U5k1a5YcDodv6dq165mWDQAAmoEzDiivvvqqhg0bpoSEhMasp07Tpk2Tx+PxLfv27Tvn7wkAAILnjGaS3bt3rz766CO9++67vnVOp1OVlZUqLS31O4pSXFwsp9Ppa7Nhwwa/16oZ5VPTpi7h4eEKDw8/k1IBAEAzdEZHUObPn6/Y2FhlZGT41qWkpKht27ZauXKlb92uXbtUUFAgl8slSXK5XNq2bZtKSkp8bXJzc2W325WUlHSm+wAAAFqYgI+gVFdXa/78+crKylKbNv95usPh0Pjx43X//fcrOjpadrtd9913n1wulwYNGiRJGjp0qJKSknTHHXdo9uzZcrvdeuSRR5Sdnc0REgAA4BNwQPnoo49UUFCgu+++u9a2F154QSEhIcrMzFRFRYXS0tL0yiuv+LaHhoZq2bJlmjhxolwulzp06KCsrCw9/vjjZ7cXAACgRTmreVCChXlQAABofppkHhQAAIBzhYACAAAsh4ACAAAsh4ACAAAsh4ACAAAsh4ACAAAsh4ACAAAsh4ACAAAsh4ACAAAsh4ACAAAsh4ACAAAsh4ACAAAsh4ACAAAsh4ACAAAsh4ACAAAsh4ACAAAsp02wCwCsqqraaEP+QZWUlSs2MkIDEqMVGmILdlkA0CoQUIA65Gwv0sylO1XkKfeti3dEaMbwJKUnxwexsuAgrAFoagQU4CQ524s0ceFmmZPWuz3lmrhws+aO7d+qQgphDUAwcA0KcIKqaqOZS3fWCieSfOtmLt2pquq6WrQ8NWHtxHAi/Ses5WwvClJlAFo6Agpwgg35B2v9GJ/ISCrylGtD/sGmKypICGsAgomAApygpOzU4eRM2jVnhDUAwURAAU4QGxnRqO2aM8IagGAioAAnGJAYrXhHhE41PsWm4xeIDkiMbsqygoKwBiCYCCjACUJDbJoxPEmSaoWUmsczhie1iiG2hDUAwURAAU6SnhyvuWP7y+nwPzLgdES0qiHGhDUAwWQzxjS7S/C9Xq8cDoc8Ho/sdnuwy0ELxeRkxzEPCoDGEsjvNwEFQL0IawAaQyC/38wkC6BeoSE2uXrEBLsMAK0I16AAAADL4QgKAADwscopXQIKAACQZK2L4jnFAwAALHdzUAIKAACtnBVvDhpwQPnmm280duxYxcTEqF27durbt68+++wz33ZjjKZPn674+Hi1a9dOqamp2r17t99rHDx4UGPGjJHdbldUVJTGjx+vQ4cOnf3eAACAgFnx5qABBZTvv/9eP/7xj9W2bVstX75cO3fu1G9+8xudd955vjazZ8/WnDlzNG/ePK1fv14dOnRQWlqaysv/s+NjxozRjh07lJubq2XLlumTTz7RhAkTGm+vAABAg1nx5qABXST7zDPPqGvXrpo/f75vXWJiou+/jTH67W9/q0ceeUQ333yzJOnPf/6z4uLi9P7772vUqFH64osvlJOTo40bN+ryyy+XJL300ku68cYb9dxzzykhIaEx9gsAADSQFW8OGtARlL/97W+6/PLLdeuttyo2NlaXXXaZ/vjHP/q25+fny+12KzU11bfO4XBo4MCBysvLkyTl5eUpKirKF04kKTU1VSEhIVq/fn2d71tRUSGv1+u3AACAhquqNsrbc0BLtn6jvD0H/K4nseLNQQMKKP/+9781d+5c9ezZUytWrNDEiRP185//XK+99pokye12S5Li4uL8nhcXF+fb5na7FRsb67e9TZs2io6O9rU52axZs+RwOHxL165dAykbAIBWLWd7kQY/s0qj//ipfvHWVo3+46ca/Mwq38gcK94cNKCAUl1drf79++vXv/61LrvsMk2YMEH33HOP5s2bd67qkyRNmzZNHo/Ht+zbt++cvh8AAC1FQ4cPW+1O7gFdgxIfH6+kpCS/dX369NFf//pXSZLT6ZQkFRcXKz7+PztSXFysSy+91NempKTE7zWOHTumgwcP+p5/svDwcIWHhwdSKgAArV59w4dtOj58+IYkp0JDbEpPjtcNSU5LzCQb0BGUH//4x9q1a5ffun/961/q3r27pOMXzDqdTq1cudK33ev1av369XK5XJIkl8ul0tJSbdq0yddm1apVqq6u1sCBA894RwAAgL8zGT5cc3PQmy89X64eMUG7c3lAR1CmTJmiK6+8Ur/+9a912223acOGDfrDH/6gP/zhD5Ikm82myZMn68knn1TPnj2VmJioRx99VAkJCbrlllskHT/ikp6e7js1dPToUU2aNEmjRo1iBA8AAI3IisOHGyqggHLFFVfovffe07Rp0/T4448rMTFRv/3tbzVmzBhfm1/+8pc6fPiwJkyYoNLSUg0ePFg5OTmKiPjPOa033nhDkyZN0pAhQxQSEqLMzEzNmTOn8fYKAABYcvhwQ9mMMU03b20j8Xq9cjgc8ng8stvtwS4HAABLqqo2GvzMKrk95XVeh2LT8Ytg1z50fZOcygnk95t78QAA0EJZcfhwQxFQgJOcbjIjWBOfGXBqVhs+3FABXYMCtHQ524s0c+lOv6ve4x0RmjE8ybJ/xK0dnxlQPysNH24orkEB/k/NZEYn/0HU/Pla+f80Wis+M6B54RoUIED1TWYkHZ/MiFMH1sFnBrRsBBRAZzaZEYKLzwxo2QgogJr3ZEatFZ8Z0LIRUAA178mMWis+M6BlI6AAkgYkRiveEVFrnoAaNh0fGTIgMbopy8Jp8JkBLRsBBVDznsyoteIzCy7mnsG5xjBj4ATMqdH88Jk1PfocZyqQ328CCnCSqmrTrCYzAp9ZU2LuGZyNQH6/mUkWOEloiE2uHjHBLgMB4DNrGvXNPWPT8blnbkhyEhBx1rgGBQDQIMw9g6ZEQAEANAhzz6ApEVAAAA3C3DNoSgQUAECDMPcMmhIBBQDQIMw9g6ZEQAEANFh6crzmju0vp8P/NI7TEcEQYzQqhhkDAAKSnhyvG5KczD2Dc4qAAgAIGHPP4FzjFA8AALAcAgoAALAcTvGcgPt5AABgDQSU/8PdOQEAsA5O8eg/d+c8+R4Tbk+5Ji7crJztRUGqDACA1qnVB5T67s4pHb87Z1V1XS0AAMC50OoDCnfnBADAelp9QOHunAAAWE+rDyjcnRMAAOtp9QGFu3MCAGA9rT6gcHdOAOdaVbVR3p4DWrL1G+XtOcBF90ADMA+K/nN3zpPnQXEyDwqAs8QcS8CZsRljml2U93q9cjgc8ng8stvtjfa6zCQLoDHVzLF08j+yNf+qzB3bn5CCViWQ3++ATvE89thjstlsfkvv3r1928vLy5Wdna2YmBh17NhRmZmZKi4u9nuNgoICZWRkqH379oqNjdXUqVN17NixQMo4Z2ruznnzpefL1SOGcNIEOPSNloo5loCzE/ApnosvvlgfffTRf16gzX9eYsqUKfrf//1fLV68WA6HQ5MmTdKIESP0j3/8Q5JUVVWljIwMOZ1OrVu3TkVFRbrzzjvVtm1b/frXv26E3UFzwqFvtGSBzLHk6hHTdIUBzUTAF8m2adNGTqfTt3Tq1EmS5PF49Oqrr+r555/X9ddfr5SUFM2fP1/r1q3Tp59+Kkn68MMPtXPnTi1cuFCXXnqphg0bpieeeEIvv/yyKisrG3fPYGncXgAtHXMsAWcn4ICye/duJSQk6MILL9SYMWNUUFAgSdq0aZOOHj2q1NRUX9vevXurW7duysvLkyTl5eWpb9++iouL87VJS0uT1+vVjh07TvmeFRUV8nq9fguaLw59ozVgjiXg7AQUUAYOHKgFCxYoJydHc+fOVX5+vq666iqVlZXJ7XYrLCxMUVFRfs+Ji4uT2+2WJLndbr9wUrO9ZtupzJo1Sw6Hw7d07do1kLJhMdxeAK0BcywBZyeggDJs2DDdeuutuuSSS5SWlqYPPvhApaWlevvtt89VfZKkadOmyePx+JZ9+/ad0/fDucWhb7QGzLEEnJ2zmqgtKipKP/rRj/TVV1/J6XSqsrJSpaWlfm2Ki4vldDolSU6ns9aonprHNW3qEh4eLrvd7reg+eLQN1qLmjmWnA7/77LTEcEQY6AeZzVR26FDh7Rnzx7dcccdSklJUdu2bbVy5UplZmZKknbt2qWCggK5XC5Jksvl0lNPPaWSkhLFxsZKknJzc2W325WUlHSWu4LmoubQt9tTXud1KDYd/wecQ99oCdKT43VDkpM5loAABRRQHnzwQQ0fPlzdu3dXYWGhZsyYodDQUI0ePVoOh0Pjx4/X/fffr+joaNntdt13331yuVwaNGiQJGno0KFKSkrSHXfcodmzZ8vtduuRRx5Rdna2wsPDz8kOwnpqDn1PXLhZNskvpHDoGy1RzRxLABouoFM8+/fv1+jRo9WrVy/ddtttiomJ0aeffqrOnTtLkl544QXddNNNyszM1NVXXy2n06l3333X9/zQ0FAtW7ZMoaGhcrlcGjt2rO688049/vjjjbtXsDwOfQMAToep7hFU3F4AAFqPQH6/uVkggopD3wCAupzVKB4AAIBzgYACAAAsh4ACAAAsh4ACAAAsh4ACAAAsh4ACAAAsh4ACAAAsh4ACAAAsh4ACAAAsh4ACAAAsh4ACAAAsh3vxAAAQAG5y2jQIKAAANFDO9iLNXLpTRZ5y37p4R4RmDE9SenJ8ECtreTjFAwBAA+RsL9LEhZv9wokkuT3lmrhws3K2FwWpspaJgAIAQD2qqo1mLt0pU8e2mnUzl+5UVXVdLXAmCCgAANRjQ/7BWkdOTmQkFXnKtSH/YNMV1cIRUAAAqEdJ2anDyZm0Q/0IKAAA1CM2MqJR26F+BBQAAOoxIDFa8Y4InWowsU3HR/MMSIxuyrJaNAIKAAD1CA2xacbwJEmqFVJqHs8YnsR8KI2IgALglKqqjfL2HNCSrd8ob88BRiigVUtPjtfcsf3ldPifxnE6IjR3bH/mQWlkTNQGoE5MSAXUlp4crxuSnMwk2wRsxphm979EXq9XDodDHo9Hdrs92OUALU7NhFQn/+NQ808w/7cI4EwE8vvNKR4AfpiQCoAVEFAA+GFCKgBWQEAB4IcJqQBYAQEFgB8mpAJgBQQUAH6YkAqAFRBQAPhhQioAVkBAAVALE1IBCDYmagNQJyakAhBMBBQApxQaYpOrR0ywywBatKpqw/8I1IGAAgBAkHBLiVM7q2tQnn76adlsNk2ePNm3rry8XNnZ2YqJiVHHjh2VmZmp4uJiv+cVFBQoIyND7du3V2xsrKZOnapjx46dTSkAADQrNbeUOHliRLenXBMXblbO9qIgVWYNZxxQNm7cqN///ve65JJL/NZPmTJFS5cu1eLFi7VmzRoVFhZqxIgRvu1VVVXKyMhQZWWl1q1bp9dee00LFizQ9OnTz3wvAABoRrilRP3OKKAcOnRIY8aM0R//+Eedd955vvUej0evvvqqnn/+eV1//fVKSUnR/PnztW7dOn366aeSpA8//FA7d+7UwoULdemll2rYsGF64okn9PLLL6uysrJx9goAAAvjlhL1O6OAkp2drYyMDKWmpvqt37Rpk44ePeq3vnfv3urWrZvy8vIkSXl5eerbt6/i4uJ8bdLS0uT1erVjx44636+iokJer9dvAQCgueKWEvUL+CLZt956S5s3b9bGjRtrbXO73QoLC1NUVJTf+ri4OLndbl+bE8NJzfaabXWZNWuWZs6cGWipAABYEreUqF9AR1D27dunX/ziF3rjjTcUEdF0nTZt2jR5PB7fsm/fviZ7bwAAGhu3lKhfQAFl06ZNKikpUf/+/dWmTRu1adNGa9as0Zw5c9SmTRvFxcWpsrJSpaWlfs8rLi6W0+mUJDmdzlqjemoe17Q5WXh4uOx2u98CAEBzxS0l6hdQQBkyZIi2bdumrVu3+pbLL79cY8aM8f1327ZttXLlSt9zdu3apYKCArlcLkmSy+XStm3bVFJS4muTm5sru92upKSkRtotAACsjVtKnF5A16BERkYqOTnZb12HDh0UExPjWz9+/Hjdf//9io6Olt1u13333SeXy6VBgwZJkoYOHaqkpCTdcccdmj17ttxutx555BFlZ2crPDy8kXYLAADr45YSp9boM8m+8MILCgkJUWZmpioqKpSWlqZXXnnFtz00NFTLli3TxIkT5XK51KFDB2VlZenxxx9v7FIAALA8bilRN5sxptnNAuP1euVwOOTxeLgeBQCAZiKQ3++zmuoeAADgXCCgAAAAyyGgAAAAyyGgAAAAyyGgAAAAyyGgAAAAyyGgAAAAyyGgAAAAyyGgAAAAyyGgAAAAyyGgAAAAyyGgAAAAyyGgAAAAyyGgAAAAyyGgAAAAyyGgAAAAy2kT7ALQvFRVG23IP6iSsnLFRkZoQGK0QkNswS4LANDCEFDQYDnbizRz6U4Vecp96+IdEZoxPEnpyfFBrAwA0NJwigcNkrO9SBMXbvYLJ5Lk9pRr4sLNytleFKTKAAAtEQEF9aqqNpq5dKdMHdtq1s1culNV1XW1AAAgcAQU1GtD/sFaR05OZCQVecq1If9g0xUFAGjRCCioV0nZqcPJmbQDAKA+BBTUKzYyolHbAQBQHwIK6jUgMVrxjgidajCxTcdH8wxIjG7KsgAALRgBBfUKDbFpxvAkSaoVUmoezxiexHwoAIBGQ0BBg6Qnx2vu2P5yOvxP4zgdEZo7tj/zoAAAGhUTtaHB0pPjdUOSk5lkAQDnHAEFAQkNscnVIybYZQAAWjhO8QAAAMshoAAAAMshoAAAAMshoAAAAMshoAAAAMshoAAAAMsJKKDMnTtXl1xyiex2u+x2u1wul5YvX+7bXl5eruzsbMXExKhjx47KzMxUcXGx32sUFBQoIyND7du3V2xsrKZOnapjx441zt4AAIAWIaCA0qVLFz399NPatGmTPvvsM11//fW6+eabtWPHDknSlClTtHTpUi1evFhr1qxRYWGhRowY4Xt+VVWVMjIyVFlZqXXr1um1117TggULNH369MbdKwAA0KzZjDHmbF4gOjpazz77rEaOHKnOnTtr0aJFGjlypCTpyy+/VJ8+fZSXl6dBgwZp+fLluummm1RYWKi4uDhJ0rx58/TQQw/p22+/VVhYWJ3vUVFRoYqKCt9jr9errl27yuPxyG63n035AACgiXi9Xjkcjgb9fp/xNShVVVV66623dPjwYblcLm3atElHjx5Vamqqr03v3r3VrVs35eXlSZLy8vLUt29fXziRpLS0NHm9Xt9RmLrMmjVLDofDt3Tt2vVMy24VqqqN8vYc0JKt3yhvzwFVVZ9VBgUAoMkFPNX9tm3b5HK5VF5ero4dO+q9995TUlKStm7dqrCwMEVFRfm1j4uLk9vtliS53W6/cFKzvWbbqUybNk3333+/73HNERTUlrO9SDOX7lSRp9y3Lt4RoRnDk7ihHwCg2Qg4oPTq1Utbt26Vx+PRO++8o6ysLK1Zs+Zc1OYTHh6u8PDwc/oeLUHO9iJNXLhZJx8vcXvKNXHhZu46DABoNgI+xRMWFqaLLrpIKSkpmjVrlvr166cXX3xRTqdTlZWVKi0t9WtfXFwsp9MpSXI6nbVG9dQ8rmmDM1NVbTRz6c5a4USSb93MpTs53QMAaBbOeh6U6upqVVRUKCUlRW3bttXKlSt923bt2qWCggK5XC5Jksvl0rZt21RSUuJrk5ubK7vdrqSkpLMtpVXbkH/Q77TOyYykIk+5NuQfbLqiAAA4QwGd4pk2bZqGDRumbt26qaysTIsWLdLq1au1YsUKORwOjR8/Xvfff7+io6Nlt9t13333yeVyadCgQZKkoUOHKikpSXfccYdmz54tt9utRx55RNnZ2ZzCOUslZacOJ2fSDgCAYAoooJSUlOjOO+9UUVGRHA6HLrnkEq1YsUI33HCDJOmFF15QSEiIMjMzVVFRobS0NL3yyiu+54eGhmrZsmWaOHGiXC6XOnTooKysLD3++OONu1etUGxkRKO2AwAgmM56HpRgCGQcdWtRVW00+JlVcnvK67wOxSbJ6YjQ2oeuV2iIranLAwCgaeZBgbWEhtg0Y/jx63hOjh81j2cMTyKcAACaBQJKC5KeHK+5Y/vL6fA/jeN0RDDEGADQrAQ8DwqsLT05XjckObUh/6BKysoVGxmhAYnRHDkBADQrBJQWKDTEJlePmGCXAQDAGeMUDwAAsBwCCgAAsBwCCgAAsBwCCgAAsBwCCgAAsBwCCgAAsBwCCgAAsBwCCgAAsBwCCgAAsBwCCgAAsBwCCgAAsBwCCgAAsBwCCgAAsBwCCgAAsBwCCgAAsBwCCgAAsJw2wS4AAOpSVW20If+gSsrKFRsZoQGJ0QoNsQW7LABNhIACwHJythdp5tKdKvKU+9bFOyI0Y3iS0pPjg1gZgKbCKR4AlpKzvUgTF272CyeS5PaUa+LCzcrZXhSkygA0JQIKAMuoqjaauXSnTB3batbNXLpTVdV1tQDQkhBQAFjGhvyDtY6cnMhIKvKUa0P+waYrCkBQEFAAWEZJ2anDyZm0A9B8EVAAWEZsZESjtgPQfBFQAFjGgMRoxTsidKrBxDYdH80zIDG6KcsCEAQEFACWERpi04zhSZJUK6TUPJ4xPIn5UIBWgIACwFLSk+M1d2x/OR3+p3GcjgjNHdufeVCAVoKJ2gBYTnpyvG5IcjKTLNCKEVAAWFJoiE2uHjHBLgNAkHCKBwAAWE5AAWXWrFm64oorFBkZqdjYWN1yyy3atWuXX5vy8nJlZ2crJiZGHTt2VGZmpoqLi/3aFBQUKCMjQ+3bt1dsbKymTp2qY8eOnf3eAACAFiGggLJmzRplZ2fr008/VW5uro4ePaqhQ4fq8OHDvjZTpkzR0qVLtXjxYq1Zs0aFhYUaMWKEb3tVVZUyMjJUWVmpdevW6bXXXtOCBQs0ffr0xtsrAADQrNmMMWd8U4tvv/1WsbGxWrNmja6++mp5PB517txZixYt0siRIyVJX375pfr06aO8vDwNGjRIy5cv10033aTCwkLFxcVJkubNm6eHHnpI3377rcLCwup9X6/XK4fDIY/HI7vdfqblAwCAJhTI7/dZXYPi8XgkSdHRxydN2rRpk44eParU1FRfm969e6tbt27Ky8uTJOXl5alv376+cCJJaWlp8nq92rFjR53vU1FRIa/X67cAAICW64wDSnV1tSZPnqwf//jHSk5OliS53W6FhYUpKirKr21cXJzcbrevzYnhpGZ7zba6zJo1Sw6Hw7d07dr1TMsGAADNwBkHlOzsbG3fvl1vvfVWY9ZTp2nTpsnj8fiWffv2nfP3BAAAwXNG86BMmjRJy5Yt0yeffKIuXbr41judTlVWVqq0tNTvKEpxcbGcTqevzYYNG/xer2aUT02bk4WHhys8PPxMSgUAAM1QQEdQjDGaNGmS3nvvPa1atUqJiYl+21NSUtS2bVutXLnSt27Xrl0qKCiQy+WSJLlcLm3btk0lJSW+Nrm5ubLb7UpKSjqbfQEAAC1EQEdQsrOztWjRIi1ZskSRkZG+a0YcDofatWsnh8Oh8ePH6/7771d0dLTsdrvuu+8+uVwuDRo0SJI0dOhQJSUl6Y477tDs2bPldrv1yCOPKDs7m6MkAABAUoDDjG22uu+DMX/+fN11112Sjk/U9sADD+jNN99URUWF0tLS9Morr/idvtm7d68mTpyo1atXq0OHDsrKytLTTz+tNm0alpcYZgwAQPMTyO/3Wc2DEiwEFAAAmp8mmwcFAADgXCCgAAAAyyGgAAAAyzmjeVAAINiqqo025B9USVm5YiMjNCAxWqEhdV/ID6D5IaAAaHZythdp5tKdKvKU+9bFOyI0Y3iS0pPjg1gZgMbCKR4AzUrO9iJNXLjZL5xIkttTrokLNytne1GQKgPQmAgoAJqNqmqjmUt3qq65EWrWzVy6U1XVzW72BAAnIaAAaDY25B+sdeTkREZSkadcG/IPNl1RAM4JAgqAZqOk7NTh5EzaAbAuAgqAZiM2MqJR2wGwLgIKgGZjQGK04h0ROtVgYpuOj+YZkBjdlGUBOAcIKACajdAQm2YMT5KkWiGl5vGM4UnMhwK0AAQUAM1KenK85o7tL6fD/zSO0xGhuWP7Mw8K0EIwURuAZic9OV43JDmZSRZowQgoAJql0BCbXD1igl0GgHOEUzwAAMByCCgAAMByCCgAAMByCCgAAMByCCgAAMByCCgAAMByCCgAAMByCCgAAMByCCgAAMBymuVMssYYSZLX6w1yJQAAoKFqfrdrfsdPp1kGlLKyMklS165dg1wJAAAIVFlZmRwOx2nb2ExDYozFVFdXq7CwUJGRkbLZmtfNwbxer7p27ap9+/bJbrcHu5xmgT4LHH0WGPorcPRZ4Oiz40dOysrKlJCQoJCQ019l0iyPoISEhKhLly7BLuOs2O32VvsFPVP0WeDos8DQX4GjzwLX2vusviMnNbhIFgAAWA4BBQAAWA4BpYmFh4drxowZCg8PD3YpzQZ9Fjj6LDD0V+Dos8DRZ4FplhfJAgCAlo0jKAAAwHIIKAAAwHIIKAAAwHIIKAAAwHIIKAAAwHIIKOfAY489JpvN5rf07t3bt728vFzZ2dmKiYlRx44dlZmZqeLi4iBW3PQ++eQTDR8+XAkJCbLZbHr//ff9thtjNH36dMXHx6tdu3ZKTU3V7t27/docPHhQY8aMkd1uV1RUlMaPH69Dhw414V40rfr67K677qr1vUtPT/dr05r6bNasWbriiisUGRmp2NhY3XLLLdq1a5dfm4b8LRYUFCgjI0Pt27dXbGyspk6dqmPHjjXlrjSZhvTZtddeW+t79rOf/cyvTWvqs7lz5+qSSy7xzQ7rcrm0fPly33a+Y2eOgHKOXHzxxSoqKvIta9eu9W2bMmWKli5dqsWLF2vNmjUqLCzUiBEjglht0zt8+LD69eunl19+uc7ts2fP1pw5czRv3jytX79eHTp0UFpamsrLy31txowZox07dig3N1fLli3TJ598ogkTJjTVLjS5+vpMktLT0/2+d2+++abf9tbUZ2vWrFF2drY+/fRT5ebm6ujRoxo6dKgOHz7sa1Pf32JVVZUyMjJUWVmpdevW6bXXXtOCBQs0ffr0YOzSOdeQPpOke+65x+97Nnv2bN+21tZnXbp00dNPP61Nmzbps88+0/XXX6+bb75ZO3bskMR37KwYNLoZM2aYfv361bmttLTUtG3b1ixevNi37osvvjCSTF5eXhNVaC2SzHvvved7XF1dbZxOp3n22Wd960pLS014eLh58803jTHG7Ny500gyGzdu9LVZvny5sdls5ptvvmmy2oPl5D4zxpisrCxz8803n/I5rb3PSkpKjCSzZs0aY0zD/hY/+OADExISYtxut6/N3Llzjd1uNxUVFU27A0Fwcp8ZY8w111xjfvGLX5zyOa29z4wx5rzzzjN/+tOf+I6dJY6gnCO7d+9WQkKCLrzwQo0ZM0YFBQWSpE2bNuno0aNKTU31te3du7e6deumvLy8YJVrKfn5+XK73X595HA4NHDgQF8f5eXlKSoqSpdffrmvTWpqqkJCQrR+/fomr9kqVq9erdjYWPXq1UsTJ07UgQMHfNtae595PB5JUnR0tKSG/S3m5eWpb9++iouL87VJS0uT1+v1/R9yS3Zyn9V444031KlTJyUnJ2vatGk6cuSIb1tr7rOqqiq99dZbOnz4sFwuF9+xs9Qs72ZsdQMHDtSCBQvUq1cvFRUVaebMmbrqqqu0fft2ud1uhYWFKSoqyu85cXFxcrvdwSnYYmr64cQ/2JrHNdvcbrdiY2P9trdp00bR0dGtth/T09M1YsQIJSYmas+ePfrVr36lYcOGKS8vT6Ghoa26z6qrqzV58mT9+Mc/VnJysiQ16G/R7XbX+T2s2daS1dVnknT77bere/fuSkhI0Oeff66HHnpIu3bt0rvvviupdfbZtm3b5HK5VF5ero4dO+q9995TUlKStm7dynfsLBBQzoFhw4b5/vuSSy7RwIED1b17d7399ttq165dECtDSzZq1Cjff/ft21eXXHKJevToodWrV2vIkCFBrCz4srOztX37dr9rwXB6p+qzE69Z6tu3r+Lj4zVkyBDt2bNHPXr0aOoyLaFXr17aunWrPB6P3nnnHWVlZWnNmjXBLqvZ4xRPE4iKitKPfvQjffXVV3I6naqsrFRpaalfm+LiYjmdzuAUaDE1/XDyle4n9pHT6VRJSYnf9mPHjungwYP04/+58MIL1alTJ3311VeSWm+fTZo0ScuWLdPHH3+sLl26+NY35G/R6XTW+T2s2dZSnarP6jJw4EBJ8vuetbY+CwsL00UXXaSUlBTNmjVL/fr104svvsh37CwRUJrAoUOHtGfPHsXHxyslJUVt27bVypUrfdt37dqlgoICuVyuIFZpHYmJiXI6nX595PV6tX79el8fuVwulZaWatOmTb42q1atUnV1te8fzNZu//79OnDggOLj4yW1vj4zxmjSpEl67733tGrVKiUmJvptb8jfosvl0rZt2/yCXW5urux2u5KSkppmR5pQfX1Wl61bt0qS3/esNfVZXaqrq1VRUcF37GwF+yrdluiBBx4wq1evNvn5+eYf//iHSU1NNZ06dTIlJSXGGGN+9rOfmW7duplVq1aZzz77zLhcLuNyuYJcddMqKyszW7ZsMVu2bDGSzPPPP2+2bNli9u7da4wx5umnnzZRUVFmyZIl5vPPPzc333yzSUxMND/88IPvNdLT081ll11m1q9fb9auXWt69uxpRo8eHaxdOudO12dlZWXmwQcfNHl5eSY/P9989NFHpn///qZnz56mvLzc9xqtqc8mTpxoHA6HWb16tSkqKvItR44c8bWp72/x2LFjJjk52QwdOtRs3brV5OTkmM6dO5tp06YFY5fOufr67KuvvjKPP/64+eyzz0x+fr5ZsmSJufDCC83VV1/te43W1mcPP/ywWbNmjcnPzzeff/65efjhh43NZjMffvihMYbv2NkgoJwD//Vf/2Xi4+NNWFiYOf/8881//dd/ma+++sq3/YcffjD33nuvOe+880z79u3NT3/6U1NUVBTEipvexx9/bCTVWrKysowxx4caP/rooyYuLs6Eh4ebIUOGmF27dvm9xoEDB8zo0aNNx44djd1uN+PGjTNlZWVB2Jumcbo+O3LkiBk6dKjp3Lmzadu2renevbu55557/IYuGtO6+qyuvpJk5s+f72vTkL/Fr7/+2gwbNsy0a9fOdOrUyTzwwAPm6NGjTbw3TaO+PisoKDBXX321iY6ONuHh4eaiiy4yU6dONR6Px+91WlOf3X333aZ79+4mLCzMdO7c2QwZMsQXTozhO3Y2bMYY03THawAAAOrHNSgAAMByCCgAAMByCCgAAMByCCgAAMByCCgAAMByCCgAAMByCCgAAMByCCgAAMByCCgAAMByCCgAAMByCCgAAMBy/j/DQcMmz7HH4AAAAABJRU5ErkJggg==" - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "execution_count": 30 - }, - { "cell_type": "code", - "id": "1b54986e-4f48-4208-96ad-61203e74c38c", - "metadata": { - "ExecuteTime": { - "end_time": "2025-08-19T23:39:55.512773Z", - "start_time": "2025-08-19T23:39:55.405984Z" - } - }, "source": [ - "plt.hist2d(scorelog['mapx'], scorelog['mapy'], weights=scorelog['score'], density=False, bins=50)\n", - "plt.show()" - ], - "outputs": [ - { - "data": { - "text/plain": [ - "
" - ], - "image/png": 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- }, - "metadata": {}, - "output_type": "display_data" - } - ], - "execution_count": 31 - }, - { - "cell_type": "code", - "id": "1371456d-5f15-4eb3-bd01-82a2bc60607a", - "metadata": { - "ExecuteTime": { - "end_time": "2025-08-19T23:40:03.763273Z", - "start_time": "2025-08-19T23:39:55.581104Z" - } - }, - "source": [ - "# one entry per second per point captured\n", - "\n", - "import numpy as np\n", - "\n", - "\n", - "@dataclass\n", - "class ScoreSecond:\n", - " name: str\n", - " sourcename: str\n", - " when: datetime\n", - " score: float\n", - " once: bool\n", - " mapx: int\n", - " mapy: int\n", - "\n", - "def row_to_scoreseconds(row, score_per):\n", - " seconds = int(floor(row.score / score_per))\n", - " assert row.score % score_per < 0.1\n", - " when = int(floor(row.when.timestamp()))\n", - " for elapsed in range(0, seconds):\n", - " timestamp = pandas.Timestamp(when - elapsed, unit='s')\n", - " yield ScoreSecond(name=row.name, sourcename=row.sourcename, mapx=row.mapx, mapy=row.mapy, when=timestamp, score=score_per, once=False)\n", - "\n", - "def gen_scoreseconds():\n", - " for row in scorelog.itertuples():\n", - " if row.sourcename == \"Capture\":\n", - " yield from row_to_scoreseconds(row, 1.0)\n", - " elif row.sourcename == \"Output Boost\":\n", - " yield from row_to_scoreseconds(row, 0.1)\n", - " else: # one-off\n", - " yield ScoreSecond(name=row.name, sourcename=row.sourcename, mapx=row.mapx, mapy=row.mapy, when=row.when, score=row.score, once=True)\n", - "\n", - "scoreseconds = pandas.DataFrame(gen_scoreseconds())\n", - "scoreseconds.sort_values(by=['when'], inplace=True)\n", - "scoreseconds.reset_index(drop=True, inplace=True)\n", - "scoreseconds" + "vinzenz_seconds = generate_score_per_second(vinzenz_score_log)\n", + "fiebertrauma_seconds = generate_score_per_second(fiebertrauma_score_log)\n", + "fiebertrauma_seconds" ], + "id": "8ae2f950e617a433", "outputs": [ { "data": { "text/plain": [ " name sourcename when score once \\\n", - "0 Info Desk First Visit 2025-08-08 20:14:00 100.0 True \n", - "1 Info Desk Capture 2025-08-08 20:14:19 1.0 False \n", - "2 Info Desk Capture 2025-08-08 20:14:20 1.0 False \n", - "3 Info Desk Capture 2025-08-08 20:14:21 1.0 False \n", - "4 Info Desk Capture 2025-08-08 20:14:22 1.0 False \n", + "0 Info Desk First Visit 2025-08-08 20:58:00 100.0 True \n", + "1 Info Desk Capture 2025-08-08 20:58:30 1.0 False \n", + "2 Info Desk Capture 2025-08-08 20:58:31 1.0 False \n", + "3 Info Desk Capture 2025-08-08 20:58:32 1.0 False \n", + "4 Info Desk Capture 2025-08-08 20:58:33 1.0 False \n", "... ... ... ... ... ... \n", - "678874 Maker Days Eindhoven Output Boost 2025-08-12 13:59:56 0.1 False \n", - "678875 Maker Days Eindhoven Output Boost 2025-08-12 13:59:57 0.1 False \n", - "678876 Maker Days Eindhoven Output Boost 2025-08-12 13:59:58 0.1 False \n", - "678877 Maker Days Eindhoven Output Boost 2025-08-12 13:59:59 0.1 False \n", - "678878 Maker Days Eindhoven Output Boost 2025-08-12 14:00:00 0.1 False \n", - "\n", - " mapx mapy \n", - "0 216 505 \n", - "1 216 505 \n", - "2 216 505 \n", - "3 216 505 \n", - "4 216 505 \n", - "... ... ... \n", - "678874 115 749 \n", - "678875 115 749 \n", - "678876 115 749 \n", - "678877 115 749 \n", - "678878 115 749 \n", - "\n", - "[678879 rows x 7 columns]" - ], - "text/html": [ - "
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namesourcenamewhenscoreoncemapxmapy
0Info DeskFirst Visit2025-08-08 20:14:00100.0True216505
1Info DeskCapture2025-08-08 20:14:191.0False216505
2Info DeskCapture2025-08-08 20:14:201.0False216505
3Info DeskCapture2025-08-08 20:14:211.0False216505
4Info DeskCapture2025-08-08 20:14:221.0False216505
........................
678874Maker Days EindhovenOutput Boost2025-08-12 13:59:560.1False115749
678875Maker Days EindhovenOutput Boost2025-08-12 13:59:570.1False115749
678876Maker Days EindhovenOutput Boost2025-08-12 13:59:580.1False115749
678877Maker Days EindhovenOutput Boost2025-08-12 13:59:590.1False115749
678878Maker Days EindhovenOutput Boost2025-08-12 14:00:000.1False115749
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678879 rows × 7 columns

\n", - "
" - ] - }, - "execution_count": 32, - "metadata": {}, - "output_type": "execute_result" - } - ], - "execution_count": 32 - }, - { - "cell_type": "code", - "id": "24ead54a-01ce-4ab2-9b4e-ffeeaa7191c9", - "metadata": { - "ExecuteTime": { - "end_time": "2025-08-19T23:40:08.295387Z", - "start_time": "2025-08-19T23:40:04.343690Z" - } - }, - "source": [ - "acc_col = pandas.Series([0.0]).repeat(len(scoreseconds)).reset_index(drop=True)\n", - "\n", - "acc = 0.0\n", - "for i, row in enumerate(scoreseconds.itertuples()):\n", - " acc += row.score\n", - " acc_col[i] = acc\n", - "\n", - "scoreseconds['accumulated_score'] = acc_col\n", - "del acc\n", - "del acc_col\n", - "\n", - "scoreseconds" - ], - "outputs": [ - { - "data": { - "text/plain": [ - " name sourcename when score once \\\n", - "0 Info Desk First Visit 2025-08-08 20:14:00 100.0 True \n", - "1 Info Desk Capture 2025-08-08 20:14:19 1.0 False \n", - "2 Info Desk Capture 2025-08-08 20:14:20 1.0 False \n", - "3 Info Desk Capture 2025-08-08 20:14:21 1.0 False \n", - "4 Info Desk Capture 2025-08-08 20:14:22 1.0 False \n", - "... ... ... ... ... ... \n", - "678874 Maker Days Eindhoven Output Boost 2025-08-12 13:59:56 0.1 False \n", - "678875 Maker Days Eindhoven Output Boost 2025-08-12 13:59:57 0.1 False \n", - "678876 Maker Days Eindhoven Output Boost 2025-08-12 13:59:58 0.1 False \n", - "678877 Maker Days Eindhoven Output Boost 2025-08-12 13:59:59 0.1 False \n", - "678878 Maker Days Eindhoven Output Boost 2025-08-12 14:00:00 0.1 False \n", + "595503 CoderDojo Belgium Capture 2025-08-12 14:00:00 1.0 False \n", + "595504 BornHack Output Boost 2025-08-12 14:00:00 0.1 False \n", + "595505 0E Capture 2025-08-12 14:00:00 1.0 False \n", + "595506 Maker Days Eindhoven Output Boost 2025-08-12 14:00:00 0.1 False \n", + "595507 Entrance Arch Capture 2025-08-12 14:00:00 1.0 False \n", "\n", " mapx mapy accumulated_score \n", "0 216 505 100.000000 \n", @@ -1738,13 +609,13 @@ "3 216 505 103.000000 \n", "4 216 505 104.000000 \n", "... ... ... ... \n", - "678874 115 749 589647.599999 \n", - "678875 115 749 589647.699999 \n", - "678876 115 749 589647.799999 \n", - "678877 115 749 589647.899999 \n", - "678878 115 749 589647.999999 \n", + "595503 34 523 551530.799999 \n", + "595504 82 337 551530.899999 \n", + "595505 0 0 551531.899999 \n", + "595506 115 749 551531.999999 \n", + "595507 240 916 551532.999999 \n", "\n", - "[678879 rows x 8 columns]" + "[595508 rows x 8 columns]" ], "text/html": [ "
\n", @@ -1780,7 +651,7 @@ " 0\n", " Info Desk\n", " First Visit\n", - " 2025-08-08 20:14:00\n", + " 2025-08-08 20:58:00\n", " 100.0\n", " True\n", " 216\n", @@ -1791,7 +662,7 @@ " 1\n", " Info Desk\n", " Capture\n", - " 2025-08-08 20:14:19\n", + " 2025-08-08 20:58:30\n", " 1.0\n", " False\n", " 216\n", @@ -1802,7 +673,7 @@ " 2\n", " Info Desk\n", " Capture\n", - " 2025-08-08 20:14:20\n", + " 2025-08-08 20:58:31\n", " 1.0\n", " False\n", " 216\n", @@ -1813,7 +684,7 @@ " 3\n", " Info Desk\n", " Capture\n", - " 2025-08-08 20:14:21\n", + " 2025-08-08 20:58:32\n", " 1.0\n", " False\n", " 216\n", @@ -1824,7 +695,7 @@ " 4\n", " Info Desk\n", " Capture\n", - " 2025-08-08 20:14:22\n", + " 2025-08-08 20:58:33\n", " 1.0\n", " False\n", " 216\n", @@ -1843,51 +714,40 @@ " ...\n", " \n", " \n", - " 678874\n", - " Maker Days Eindhoven\n", - " Output Boost\n", - " 2025-08-12 13:59:56\n", - " 0.1\n", + " 595503\n", + " CoderDojo Belgium\n", + " Capture\n", + " 2025-08-12 14:00:00\n", + " 1.0\n", " False\n", - " 115\n", - " 749\n", - " 589647.599999\n", + " 34\n", + " 523\n", + " 551530.799999\n", " \n", " \n", - " 678875\n", - " Maker Days Eindhoven\n", + " 595504\n", + " BornHack\n", " Output Boost\n", - " 2025-08-12 13:59:57\n", + " 2025-08-12 14:00:00\n", " 0.1\n", " False\n", - " 115\n", - " 749\n", - " 589647.699999\n", + " 82\n", + " 337\n", + " 551530.899999\n", " \n", " \n", - " 678876\n", - " Maker Days Eindhoven\n", - " Output Boost\n", - " 2025-08-12 13:59:58\n", - " 0.1\n", + " 595505\n", + " 0E\n", + " Capture\n", + " 2025-08-12 14:00:00\n", + " 1.0\n", " False\n", - " 115\n", - " 749\n", - " 589647.799999\n", + " 0\n", + " 0\n", + " 551531.899999\n", " \n", " \n", - " 678877\n", - " Maker Days Eindhoven\n", - " Output Boost\n", - " 2025-08-12 13:59:59\n", - " 0.1\n", - " False\n", - " 115\n", - " 749\n", - " 589647.899999\n", - " \n", - " \n", - " 678878\n", + " 595506\n", " Maker Days Eindhoven\n", " Output Boost\n", " 2025-08-12 14:00:00\n", @@ -1895,26 +755,37 @@ " False\n", " 115\n", " 749\n", - " 589647.999999\n", + " 551531.999999\n", + " \n", + " \n", + " 595507\n", + " Entrance Arch\n", + " Capture\n", + " 2025-08-12 14:00:00\n", + " 1.0\n", + " False\n", + " 240\n", + " 916\n", + " 551532.999999\n", " \n", " \n", "\n", - "

678879 rows × 8 columns

\n", + "

595508 rows × 8 columns

\n", "
" ] }, - "execution_count": 33, + "execution_count": 3, "metadata": {}, "output_type": "execute_result" } ], - "execution_count": 33 + "execution_count": 3 }, { "metadata": { "ExecuteTime": { - "end_time": "2025-08-19T23:45:26.737903Z", - "start_time": "2025-08-19T23:45:26.511905Z" + "end_time": "2025-08-26T16:52:19.761484Z", + "start_time": "2025-08-26T16:52:18.991457Z" } }, "cell_type": "code", @@ -1922,45 +793,50 @@ "from matplotlib import dates\n", "\n", "fig, ax = plt.subplots()\n", - "ax.plot('when', 'accumulated_score', data=scoreseconds, )\n", + "ax.plot('when', 'accumulated_score', data=vinzenz_seconds, label='vinzenz (seconds)')\n", + "ax.plot('when', 'accumulated_score', data=fiebertrauma_seconds, label='Fiebertrauma (seconds)')\n", + "ax.plot('when', 'accumulated_score', data=vinzenz_score_log, label='vinzenz (scorelog)')\n", + "ax.plot('when', 'accumulated_score', data=fiebertrauma_score_log, label='Fiebertrauma (scorelog)')\n", + "\n", "ax.xaxis.set_major_locator(dates.DayLocator(interval=1)) # every day\n", "ax.xaxis.set_major_formatter(dates.DateFormatter('\\n%d-%m-%Y'))\n", "plt.title('Accumulated Score')\n", + "plt.legend()\n", "plt.show()" ], - "id": "6e0a9a80c70d3bb0", + "id": "526448f50cefdb2d", "outputs": [ { "data": { "text/plain": [ "
" ], - "image/png": 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" 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" }, "metadata": {}, "output_type": "display_data" } ], - "execution_count": 42 + "execution_count": 4 } ], "metadata": { "kernelspec": { - "display_name": "Python 3 (ipykernel)", + "display_name": "Python 3", "language": "python", "name": "python3" }, "language_info": { "codemirror_mode": { "name": "ipython", - "version": 3 + "version": 2 }, "file_extension": ".py", "mimetype": "text/x-python", "name": "python", "nbconvert_exporter": "python", - "pygments_lexer": "ipython3", - "version": "3.12.11" + "pygments_lexer": "ipython2", + "version": "2.7.6" } }, "nbformat": 4, diff --git a/notebook2.ipynb b/notebook2.ipynb deleted file mode 100644 index 4bdc840..0000000 --- a/notebook2.ipynb +++ /dev/null @@ -1,1271 +0,0 @@ -{ - "cells": [ - { - "cell_type": "code", - "id": "initial_id", - "metadata": { - "collapsed": true, - "ExecuteTime": { - "end_time": "2025-08-26T16:05:16.645275Z", - "start_time": "2025-08-26T16:05:16.170814Z" - } - }, - "source": [ - "from datetime import datetime\n", - "\n", - "import pandas\n", - "import matplotlib.pyplot as plt\n", - "\n", - "from foo import *" - ], - "outputs": [], - "execution_count": 1 - }, - { - "metadata": { - "ExecuteTime": { - "end_time": "2025-08-26T16:05:16.700303Z", - "start_time": "2025-08-26T16:05:16.659896Z" - } - }, - "cell_type": "code", - "source": [ - "vinzenz_score_log = load_score_log('PolyGenStats-vinzenz-scorelog.csv')\n", - "vinzenz_summary = generate_station_stats(vinzenz_score_log)\n", - "\n", - "vinzenz_summary" - ], - "id": "bf523274efb801dd", - "outputs": [ - { - "data": { - "text/plain": [ - " name mapx mapy first_visit total_score \\\n", - "0 Info Desk 216 505 2025-08-08 20:14:00 17026 \n", - "1 Main Bar 190 570 2025-08-08 20:22:00 36884 \n", - "2 Badge Tent 328 607 2025-08-08 20:23:00 32599 \n", - "3 CoderDojo Belgium 34 523 2025-08-08 21:39:00 44374 \n", - "4 Heaven 183 227 2025-08-08 21:46:00 10057 \n", - "5 Karaoke Bar 292 446 2025-08-08 21:55:00 45272 \n", - "6 Cold North 305 402 2025-08-08 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9Adyen1206372025-08-08 21:57:003765694940595907373399733862
10Bridge over troubled waters2515532025-08-09 09:15:0096137272043430241815658291
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17Matrix1647312025-08-09 15:02:00170311011010666603026336915380
18Pixelbar3796022025-08-09 15:54:001225133330333302220222311068
19PolyGen Home Base3225912025-08-09 16:01:00207391401400656502526325619299
20Cold North3054022025-08-09 19:31:00966720520501741740141222368712
21BornHack823372025-08-09 21:19:0040950169216920875875014101377538508
22FALSE1634252025-08-10 08:40:00915726226201321320201226117845
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" - ] - }, - "execution_count": 4, - "metadata": {}, - "output_type": "execute_result" - } - ], - "execution_count": 4 - }, - { - "metadata": { - "ExecuteTime": { - "end_time": "2025-08-26T16:06:00.347754Z", - "start_time": "2025-08-26T16:05:36.926533Z" - } - }, - "cell_type": "code", - "source": [ - "vinzenz_seconds = generate_score_per_second(vinzenz_score_log)\n", - "fiebertrauma_seconds = generate_score_per_second(fiebertrauma_score_log)\n", - "fiebertrauma_seconds" - ], - "id": "8ae2f950e617a433", - "outputs": [ - { - "data": { - "text/plain": [ - " name sourcename when score once \\\n", - "0 Info Desk First Visit 2025-08-08 20:58:00 100.0 True \n", - "1 Info Desk Capture 2025-08-08 20:58:30 1.0 False \n", - "2 Info Desk Capture 2025-08-08 20:58:31 1.0 False \n", - "3 Info Desk Capture 2025-08-08 20:58:32 1.0 False \n", - "4 Info Desk Capture 2025-08-08 20:58:33 1.0 False \n", - "... ... ... ... ... ... \n", - "595503 CoderDojo Belgium Capture 2025-08-12 14:00:00 1.0 False \n", - "595504 Entrance Arch Capture 2025-08-12 14:00:00 1.0 False \n", - "595505 0E Capture 2025-08-12 14:00:00 1.0 False \n", - "595506 Tilde Industries Capture 2025-08-12 14:00:00 1.0 False \n", - "595507 BornHack Output Boost 2025-08-12 14:00:00 0.1 False \n", - "\n", - " mapx mapy accumulated_score \n", - "0 216 505 100.000000 \n", - "1 216 505 101.000000 \n", - "2 216 505 102.000000 \n", - "3 216 505 103.000000 \n", - "4 216 505 104.000000 \n", - "... ... ... ... \n", - "595503 34 523 551529.899999 \n", - "595504 240 916 551530.899999 \n", - "595505 0 0 551531.899999 \n", - "595506 361 468 551532.899999 \n", - "595507 82 337 551532.999999 \n", - "\n", - "[595508 rows x 8 columns]" - ], - "text/html": [ - "
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namesourcenamewhenscoreoncemapxmapyaccumulated_score
0Info DeskFirst Visit2025-08-08 20:58:00100.0True216505100.000000
1Info DeskCapture2025-08-08 20:58:301.0False216505101.000000
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" - ] - }, - "execution_count": 5, - "metadata": {}, - "output_type": "execute_result" - } - ], - "execution_count": 5 - }, - { - "metadata": { - "ExecuteTime": { - "end_time": "2025-08-26T16:06:01.725686Z", - "start_time": "2025-08-26T16:06:00.489050Z" - } - }, - "cell_type": "code", - "source": [ - "from matplotlib import dates\n", - "\n", - "fig, ax = plt.subplots()\n", - "ax.plot('when', 'accumulated_score', data=vinzenz_seconds, label='vinzenz')\n", - "ax.plot('when', 'accumulated_score', data=fiebertrauma_seconds, label='Fiebertrauma')\n", - "ax.xaxis.set_major_locator(dates.DayLocator(interval=1)) # every day\n", - "ax.xaxis.set_major_formatter(dates.DateFormatter('\\n%d-%m-%Y'))\n", - "plt.title('Accumulated Score')\n", - "plt.legend()\n", - "plt.show()" - ], - "id": "526448f50cefdb2d", - "outputs": [ - { - "data": { - "text/plain": [ - "
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" 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