From 73126da020f306b05af504586b189db595440bea Mon Sep 17 00:00:00 2001 From: blaze1522 Date: Wed, 11 May 2022 15:40:08 +0530 Subject: [PATCH] Added notebook with experiments regarding unknown cluster-size,k --- UK/10k-pts/UK-2-results.csv | 49 + UK/10k-pts/UK-3-results.csv | 51 + UK/10k-pts/UK-4-results.csv | 51 + UK/10k-pts/UK-5-results.csv | 51 + UK/10k-pts/UK-6-results.csv | 51 + UK/10k-pts/UK-7-results.csv | 51 + UK/10k-pts/UK-8-results.csv | 51 + UK/10k-pts/UK-9-results.csv | 51 + UK/1k-pts/UK-2-results.csv | 50 + UK/1k-pts/UK-3-results.csv | 50 + UK/1k-pts/UK-4-results.csv | 51 + UK/1k-pts/UK-5-results.csv | 52 + UK/1k-pts/UK-6-results.csv | 52 + UK/1k-pts/UK-7-results.csv | 52 + UK/1k-pts/UK-8-results.csv | 52 + UK/1k-pts/UK-9-results.csv | 52 + UK/UK-Analysis.ipynb | 2970 +++++++++++++++++++++++++++++++++++ 17 files changed, 3787 insertions(+) create mode 100644 UK/10k-pts/UK-2-results.csv create mode 100644 UK/10k-pts/UK-3-results.csv create mode 100644 UK/10k-pts/UK-4-results.csv create mode 100644 UK/10k-pts/UK-5-results.csv create mode 100644 UK/10k-pts/UK-6-results.csv create mode 100644 UK/10k-pts/UK-7-results.csv create mode 100644 UK/10k-pts/UK-8-results.csv create mode 100644 UK/10k-pts/UK-9-results.csv create mode 100644 UK/1k-pts/UK-2-results.csv create mode 100644 UK/1k-pts/UK-3-results.csv create mode 100644 UK/1k-pts/UK-4-results.csv create mode 100644 UK/1k-pts/UK-5-results.csv create mode 100644 UK/1k-pts/UK-6-results.csv create mode 100644 UK/1k-pts/UK-7-results.csv create mode 100644 UK/1k-pts/UK-8-results.csv create mode 100644 UK/1k-pts/UK-9-results.csv create mode 100644 UK/UK-Analysis.ipynb diff --git a/UK/10k-pts/UK-2-results.csv b/UK/10k-pts/UK-2-results.csv new file mode 100644 index 0000000..38e6474 --- /dev/null +++ b/UK/10k-pts/UK-2-results.csv @@ -0,0 +1,49 @@ +filename,true_clusters,pred_clusters,gs_rs,gs_ars,gs_ss,gs_burnin_rs,gs_burnin_ars,gs_burnin_ss 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a/UK/UK-Analysis.ipynb b/UK/UK-Analysis.ipynb new file mode 100644 index 0000000..7c59ab8 --- /dev/null +++ b/UK/UK-Analysis.ipynb @@ -0,0 +1,2970 @@ +{ + "cells": [ + { + "cell_type": "code", + "execution_count": 1, + "metadata": {}, + "outputs": [], + "source": [ + "import numpy as np\n", + "import pandas as pd\n", + "import matplotlib.pyplot as plt\n", + "import plotly.express as px\n", + "import plotly.graph_objects as go\n", + "\n", + "plt.rcParams[\"figure.figsize\"] = (10,6)" + ] + }, + { + "cell_type": "code", + "execution_count": 3, + "metadata": {}, + "outputs": [], + "source": [ + "df_dict = {}\n", + "\n", + "for i in range(2,10):\n", + " df_dict[i] = pd.read_csv(f\"10k-pts/UK-{i}-results.csv\")" + ] + }, + { + "cell_type": "code", + "execution_count": 4, + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
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filenametrue_clusterspred_clustersgs_rsgs_arsgs_ssgs_burnin_rsgs_burnin_arsgs_burnin_ss
0data-k-2-0.csv221.0000001.0000000.9759141.0000001.0000000.975914
1data-k-2-1.csv230.496816-0.1200920.2330830.456451-0.0840130.503227
2data-k-2-2.csv220.5443560.0218200.0779390.5892540.0832970.515868
3data-k-2-3.csv220.9600280.9192090.7181630.9702530.9399330.727878
4data-k-2-4.csv220.9650300.9294330.7619840.9758950.9513290.774268
\n", + "
" + ], + "text/plain": [ + " filename true_clusters pred_clusters gs_rs gs_ars gs_ss \\\n", + "0 data-k-2-0.csv 2 2 1.000000 1.000000 0.975914 \n", + "1 data-k-2-1.csv 2 3 0.496816 -0.120092 0.233083 \n", + "2 data-k-2-2.csv 2 2 0.544356 0.021820 0.077939 \n", + "3 data-k-2-3.csv 2 2 0.960028 0.919209 0.718163 \n", + "4 data-k-2-4.csv 2 2 0.965030 0.929433 0.761984 \n", + "\n", + " gs_burnin_rs gs_burnin_ars gs_burnin_ss \n", + "0 1.000000 1.000000 0.975914 \n", + "1 0.456451 -0.084013 0.503227 \n", + "2 0.589254 0.083297 0.515868 \n", + "3 0.970253 0.939933 0.727878 \n", + "4 0.975895 0.951329 0.774268 " + ] + }, + "execution_count": 4, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "df_dict[2].head()" + ] + }, + { + "cell_type": "code", + "execution_count": 6, + "metadata": { + "scrolled": true + }, + "outputs": [ + { + "data": { + "image/png": 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\n", 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