Mercurial > hg > chourdakisreiss2018smc
changeset 1:bac47e5ffc10
removed some hidden files
| author | Emmanouil Theofanis Chourdakis <e.t.chourdakis@qmul.ac.uk> |
|---|---|
| date | Tue, 05 Jun 2018 12:00:16 +0100 |
| parents | 90155bdd5dd6 |
| children | f9189fbc03d9 |
| files | demo/._script.txt results/data/.bash_history results/data/.bash_profile results/data/.viminfo results/data/.vimrc results/data/saves/.ipynb_checkpoints/Plots-checkpoint.ipynb results/data/saves/.ipynb_checkpoints/plots-checkpoint.ipynb results/data/saves/.png |
| diffstat | 8 files changed, 0 insertions(+), 2543 deletions(-) [+] |
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--- a/demo/._script.txt Wed May 16 18:27:05 2018 +0100 +++ /dev/null Thu Jan 01 00:00:00 1970 +0000 @@ -1,1 +0,0 @@ -._script.txt \ No newline at end of file
--- a/results/data/.bash_history Wed May 16 18:27:05 2018 +0100 +++ /dev/null Thu Jan 01 00:00:00 1970 +0000 @@ -1,231 +0,0 @@ -cd app-root/ -ls -cd data/ -ls -cd ..\ -cd repo/ -ls -cd waet/ -ls -cd saves/ -ls -cat save-6iQr5DOTgHdvmRSHTSBfGrppBMEIRqbX.xml -exit -cd app-root/ -ls -cd data/ -ls -mkdir saves -mkdir save -echo $OPENSHIFT_DATA_DIR -ls -cd saves -ls -cd .. -cd save -ls -cd .. -ls -cd saves -ls -cd .. -cd save -ls -dc .. -ls -cd .. -ls -cd .. -ls -cd logs/ -ls -cat php.log -ls -cd .. -ls -cd repo/ -ls -cd waet/ -ls -cd saves/ -ls -cat save-5himaxuOVduN40N45oRHOyoqU1qwpViu.xml -cat read.txt -vim save-5himaxuOVduN40N45oRHOyoqU1qwpViu.xml -exit -ls -cd app-root/ -ls -cd repo/ -ls -cd waet/ -ls -cd saves -ls -cat save-rtB2K9dZyk9lnXeIrhoiNtrxd5KZJwga.xml -cd .. -ls -cd $OPENSHIFT_DATA_DIR -ls -cd saves -ls -ls -ls -ls -a -cd .. -ls -cd save -ls -ls -la -exit -cd app-repo -ls -cd app-root -ls -cd repo -cd ph -ls -cd waet/ -cd php/ -ls -ls ../../../data/saves/ -exit -ls -cd app-root/ -ls -cd data/ -ls -cd saves -ls -ls -cd ../save -ls -exit -ls -cd app-root/ -ls -cd repo/ -ls -cd waet/ -ls -ls saves/ -rm -rf saves -ln -s /var/lib/openshift/5aaedbfc251c080de5000030/app-root/data/saves -ls -cd saves -ls -ls -cat save-jlVJtLAmllkP8xH98lYM60FHJsAyllYF.xml -cd $OPENSHIFT_DATA_DIR -ls -cd saves -ls -rm * -ls -cd app-root/ -ls -ls -cd app-root/ -cd data/ -ls -cd save -ls -cd ../saves -ls -cat save-&* -cat save-* -cat save-* | grep alex -cat save-* | grep name -pwd -exit -ls -cd app-root/ -ls -cd repo/ -ls -cd waet/ -ls -ln -s /var/lib/openshift/5aaedbfc251c080de5000030/app-root/data/saves -ls -cd saves -ls -rm * -ls -rm * -cd app-root/ -ls -cd repo/ -ls -cd waet/ -ls -ln -s /var/lib/openshift/5aaedbfc251c080de5000030/app-root/data/saves -exit -ls -cd app-root/ -ls -cd repo -ls -cd waet/ -ls -ln -s /var/lib/openshift/5aaedbfc251c080de5000030/app-root/data/saves -exit -cd app-root/ -cd repo/ -ls -cd waet/ -ln -s /var/lib/openshift/5aaedbfc251c080de5000030/app-root/data/saves -cd saves -ks -ls -pwd -echo $OPENSHIFT_DATA_DIR -cd app-root/repo/ -ls -cd waet/ -ln -s /var/lib/openshift/5aaedbfc251c080de5000030/app-root/data/saves -ls -cd saves -ls -rm * -cd $OPENSHIFT_DATA_DIR/saves -ls -grep * -e "beici" -grep * "beici" -grep * -e "beici" -vim save-kwINKFSYtWXqBE1bg8Ffhy02GTfX84ds.xml -vim save-lB8k45hvGWwScFyrX7sZNleLujZXTWdf.xml -ls -vim save-liuL3y4zPQh8HbF7L3d4VKTRYy0BuFHP.xml -vim save-liuL3y4zPQh8HbF7L3d4VKTRYy0BuFHP.xml -ls -vim save-uoBPmOWdbNI4uowtBZRZK8BIEUVvUn1o.xml -vim save-liuL3y4zPQh8HbF7L3d4VKTRYy0BuFHP.xml -ls -vim save-rR78NE1ZkzrhHThvfwgJPgHJcVYKhxnJ.xml -vim save-busCM9w4ELAVvqcd9o879qFw9421hcUs.xml -vim save-dS77aOufZLQ6fsSckpso4L0iYY2oPJV2.xml -vim save-kwINKFSYtWXqBE1bg8Ffhy02GTfX84ds.xml -exit -cd $OPENSHIFT_DATA_DIR/saves -ls -cat save-7hgS5m4MRPhzBuossh9A5NHwyZoqVbd3.xml -cat save-AK7SPrWT4ZXJrP8NJacNYstOxzyzjDrT.xml -cat save-BFZfbp4MRUDwGYSPoHwp6pODr6KOtzU4.xml -cat * -ls -ls -ls -cat save-VyX492RQzqQXRL84PByL9pLt8C5p4c50.xml -cd $OPENSHIFT_DATA_DIR -cd saves -ls -ls -ls -exit -pwd -ls -cd app-root/data/ -grep * -e 'ref="name"' -grep -r * -e 'ref="name"' -grep -r * -e 'manos' -grep -r * -e 'Will' -grep -r * -e 'Will' -grep -l -r * -e 'Will'
--- a/results/data/.bash_profile Wed May 16 18:27:05 2018 +0100 +++ /dev/null Thu Jan 01 00:00:00 1970 +0000 @@ -1,3 +0,0 @@ - -# Warning: Be careful with modifications to this file, -# Your changes may cause your application to fail.
--- a/results/data/.viminfo Wed May 16 18:27:05 2018 +0100 +++ /dev/null Thu Jan 01 00:00:00 1970 +0000 @@ -1,146 +0,0 @@ -# This viminfo file was generated by Vim 7.4. -# You may edit it if you are careful! - -# Value of 'encoding' when this file was written -*encoding=latin1 - - -# hlsearch on (H) or off (h): -~H -# Last Search Pattern: -~MSle0~/manos - -# Command Line History (newest to oldest): -:q -:Q - -# Search String History (newest to oldest): -??manos -??Beici -??name= -??name -??beici - -# Expression History (newest to oldest): - -# Input Line History (newest to oldest): - -# Input Line History (newest to oldest): - -# Registers: - -# File marks: -'0 1 0 ~/app-root/data/saves/save-kwINKFSYtWXqBE1bg8Ffhy02GTfX84ds.xml -'1 1 0 ~/app-root/data/saves/save-dS77aOufZLQ6fsSckpso4L0iYY2oPJV2.xml -'2 1 0 ~/app-root/data/saves/save-busCM9w4ELAVvqcd9o879qFw9421hcUs.xml -'3 1 0 ~/app-root/data/saves/save-rR78NE1ZkzrhHThvfwgJPgHJcVYKhxnJ.xml -'4 316 408 ~/app-root/data/saves/save-liuL3y4zPQh8HbF7L3d4VKTRYy0BuFHP.xml -'5 316 481 ~/app-root/data/saves/save-uoBPmOWdbNI4uowtBZRZK8BIEUVvUn1o.xml -'6 294 12 ~/app-root/data/saves/save-liuL3y4zPQh8HbF7L3d4VKTRYy0BuFHP.xml -'7 1 0 ~/app-root/data/saves/save-lB8k45hvGWwScFyrX7sZNleLujZXTWdf.xml -'8 1 0 ~/app-root/runtime/repo/waet/saves/save-5himaxuOVduN40N45oRHOyoqU1qwpViu.xml - -# Jumplist (newest first): --' 1 0 ~/app-root/data/saves/save-kwINKFSYtWXqBE1bg8Ffhy02GTfX84ds.xml --' 1 0 ~/app-root/data/saves/save-dS77aOufZLQ6fsSckpso4L0iYY2oPJV2.xml --' 1 0 ~/app-root/data/saves/save-busCM9w4ELAVvqcd9o879qFw9421hcUs.xml --' 1 0 ~/app-root/data/saves/save-rR78NE1ZkzrhHThvfwgJPgHJcVYKhxnJ.xml --' 316 408 ~/app-root/data/saves/save-liuL3y4zPQh8HbF7L3d4VKTRYy0BuFHP.xml --' 294 12 ~/app-root/data/saves/save-liuL3y4zPQh8HbF7L3d4VKTRYy0BuFHP.xml --' 316 481 ~/app-root/data/saves/save-uoBPmOWdbNI4uowtBZRZK8BIEUVvUn1o.xml --' 1 0 ~/app-root/data/saves/save-uoBPmOWdbNI4uowtBZRZK8BIEUVvUn1o.xml --' 295 41 ~/app-root/data/saves/save-liuL3y4zPQh8HbF7L3d4VKTRYy0BuFHP.xml --' 296 41 ~/app-root/data/saves/save-liuL3y4zPQh8HbF7L3d4VKTRYy0BuFHP.xml --' 297 41 ~/app-root/data/saves/save-liuL3y4zPQh8HbF7L3d4VKTRYy0BuFHP.xml --' 298 42 ~/app-root/data/saves/save-liuL3y4zPQh8HbF7L3d4VKTRYy0BuFHP.xml --' 1 0 ~/app-root/data/saves/save-liuL3y4zPQh8HbF7L3d4VKTRYy0BuFHP.xml --' 1 0 ~/app-root/data/saves/save-lB8k45hvGWwScFyrX7sZNleLujZXTWdf.xml --' 1 0 ~/app-root/runtime/repo/waet/saves/save-5himaxuOVduN40N45oRHOyoqU1qwpViu.xml --' 1 0 ~/app-root/runtime/repo/waet/saves/save-5himaxuOVduN40N45oRHOyoqU1qwpViu.xml --' 1 0 ~/app-root/runtime/repo/waet/saves/save-5himaxuOVduN40N45oRHOyoqU1qwpViu.xml --' 1 0 ~/app-root/runtime/repo/waet/saves/save-5himaxuOVduN40N45oRHOyoqU1qwpViu.xml --' 1 0 ~/app-root/data/saves/save-lB8k45hvGWwScFyrX7sZNleLujZXTWdf.xml --' 1 0 ~/app-root/runtime/repo/waet/saves/save-5himaxuOVduN40N45oRHOyoqU1qwpViu.xml --' 1 0 ~/app-root/runtime/repo/waet/saves/save-5himaxuOVduN40N45oRHOyoqU1qwpViu.xml --' 1 0 ~/app-root/runtime/repo/waet/saves/save-5himaxuOVduN40N45oRHOyoqU1qwpViu.xml --' 1 0 ~/app-root/runtime/repo/waet/saves/save-5himaxuOVduN40N45oRHOyoqU1qwpViu.xml --' 1 0 ~/app-root/data/saves/save-lB8k45hvGWwScFyrX7sZNleLujZXTWdf.xml --' 1 0 ~/app-root/runtime/repo/waet/saves/save-5himaxuOVduN40N45oRHOyoqU1qwpViu.xml --' 1 0 ~/app-root/runtime/repo/waet/saves/save-5himaxuOVduN40N45oRHOyoqU1qwpViu.xml --' 1 0 ~/app-root/runtime/repo/waet/saves/save-5himaxuOVduN40N45oRHOyoqU1qwpViu.xml --' 1 0 ~/app-root/runtime/repo/waet/saves/save-5himaxuOVduN40N45oRHOyoqU1qwpViu.xml --' 1 0 ~/app-root/data/saves/save-lB8k45hvGWwScFyrX7sZNleLujZXTWdf.xml --' 1 0 ~/app-root/runtime/repo/waet/saves/save-5himaxuOVduN40N45oRHOyoqU1qwpViu.xml --' 1 0 ~/app-root/runtime/repo/waet/saves/save-5himaxuOVduN40N45oRHOyoqU1qwpViu.xml --' 1 0 ~/app-root/runtime/repo/waet/saves/save-5himaxuOVduN40N45oRHOyoqU1qwpViu.xml --' 1 0 ~/app-root/runtime/repo/waet/saves/save-5himaxuOVduN40N45oRHOyoqU1qwpViu.xml --' 1 0 ~/app-root/data/saves/save-lB8k45hvGWwScFyrX7sZNleLujZXTWdf.xml --' 1 0 ~/app-root/runtime/repo/waet/saves/save-5himaxuOVduN40N45oRHOyoqU1qwpViu.xml --' 1 0 ~/app-root/runtime/repo/waet/saves/save-5himaxuOVduN40N45oRHOyoqU1qwpViu.xml --' 1 0 ~/app-root/runtime/repo/waet/saves/save-5himaxuOVduN40N45oRHOyoqU1qwpViu.xml --' 1 0 ~/app-root/runtime/repo/waet/saves/save-5himaxuOVduN40N45oRHOyoqU1qwpViu.xml --' 1 0 ~/app-root/data/saves/save-lB8k45hvGWwScFyrX7sZNleLujZXTWdf.xml --' 1 0 ~/app-root/runtime/repo/waet/saves/save-5himaxuOVduN40N45oRHOyoqU1qwpViu.xml --' 1 0 ~/app-root/runtime/repo/waet/saves/save-5himaxuOVduN40N45oRHOyoqU1qwpViu.xml --' 1 0 ~/app-root/runtime/repo/waet/saves/save-5himaxuOVduN40N45oRHOyoqU1qwpViu.xml --' 1 0 ~/app-root/runtime/repo/waet/saves/save-5himaxuOVduN40N45oRHOyoqU1qwpViu.xml --' 1 0 ~/app-root/data/saves/save-lB8k45hvGWwScFyrX7sZNleLujZXTWdf.xml --' 1 0 ~/app-root/runtime/repo/waet/saves/save-5himaxuOVduN40N45oRHOyoqU1qwpViu.xml --' 1 0 ~/app-root/runtime/repo/waet/saves/save-5himaxuOVduN40N45oRHOyoqU1qwpViu.xml --' 1 0 ~/app-root/runtime/repo/waet/saves/save-5himaxuOVduN40N45oRHOyoqU1qwpViu.xml --' 1 0 ~/app-root/runtime/repo/waet/saves/save-5himaxuOVduN40N45oRHOyoqU1qwpViu.xml --' 1 0 ~/app-root/data/saves/save-lB8k45hvGWwScFyrX7sZNleLujZXTWdf.xml --' 1 0 ~/app-root/runtime/repo/waet/saves/save-5himaxuOVduN40N45oRHOyoqU1qwpViu.xml --' 1 0 ~/app-root/runtime/repo/waet/saves/save-5himaxuOVduN40N45oRHOyoqU1qwpViu.xml --' 1 0 ~/app-root/runtime/repo/waet/saves/save-5himaxuOVduN40N45oRHOyoqU1qwpViu.xml --' 1 0 ~/app-root/runtime/repo/waet/saves/save-5himaxuOVduN40N45oRHOyoqU1qwpViu.xml --' 316 481 ~/app-root/data/saves/save-uoBPmOWdbNI4uowtBZRZK8BIEUVvUn1o.xml --' 1 0 ~/app-root/data/saves/save-uoBPmOWdbNI4uowtBZRZK8BIEUVvUn1o.xml --' 1 0 ~/app-root/data/saves/save-lB8k45hvGWwScFyrX7sZNleLujZXTWdf.xml --' 1 0 ~/app-root/runtime/repo/waet/saves/save-5himaxuOVduN40N45oRHOyoqU1qwpViu.xml --' 1 0 ~/app-root/runtime/repo/waet/saves/save-5himaxuOVduN40N45oRHOyoqU1qwpViu.xml --' 1 0 ~/app-root/runtime/repo/waet/saves/save-5himaxuOVduN40N45oRHOyoqU1qwpViu.xml --' 1 0 ~/app-root/runtime/repo/waet/saves/save-5himaxuOVduN40N45oRHOyoqU1qwpViu.xml --' 1 0 ~/app-root/data/saves/save-lB8k45hvGWwScFyrX7sZNleLujZXTWdf.xml --' 1 0 ~/app-root/runtime/repo/waet/saves/save-5himaxuOVduN40N45oRHOyoqU1qwpViu.xml --' 1 0 ~/app-root/runtime/repo/waet/saves/save-5himaxuOVduN40N45oRHOyoqU1qwpViu.xml --' 1 0 ~/app-root/runtime/repo/waet/saves/save-5himaxuOVduN40N45oRHOyoqU1qwpViu.xml --' 1 0 ~/app-root/runtime/repo/waet/saves/save-5himaxuOVduN40N45oRHOyoqU1qwpViu.xml --' 1 0 ~/app-root/data/saves/save-lB8k45hvGWwScFyrX7sZNleLujZXTWdf.xml --' 316 408 ~/app-root/data/saves/save-liuL3y4zPQh8HbF7L3d4VKTRYy0BuFHP.xml --' 294 12 ~/app-root/data/saves/save-liuL3y4zPQh8HbF7L3d4VKTRYy0BuFHP.xml --' 316 481 ~/app-root/data/saves/save-uoBPmOWdbNI4uowtBZRZK8BIEUVvUn1o.xml --' 1 0 ~/app-root/data/saves/save-uoBPmOWdbNI4uowtBZRZK8BIEUVvUn1o.xml --' 295 41 ~/app-root/data/saves/save-liuL3y4zPQh8HbF7L3d4VKTRYy0BuFHP.xml --' 296 41 ~/app-root/data/saves/save-liuL3y4zPQh8HbF7L3d4VKTRYy0BuFHP.xml --' 297 41 ~/app-root/data/saves/save-liuL3y4zPQh8HbF7L3d4VKTRYy0BuFHP.xml --' 298 42 ~/app-root/data/saves/save-liuL3y4zPQh8HbF7L3d4VKTRYy0BuFHP.xml --' 1 0 ~/app-root/data/saves/save-liuL3y4zPQh8HbF7L3d4VKTRYy0BuFHP.xml --' 1 0 ~/app-root/data/saves/save-lB8k45hvGWwScFyrX7sZNleLujZXTWdf.xml --' 1 0 ~/app-root/runtime/repo/waet/saves/save-5himaxuOVduN40N45oRHOyoqU1qwpViu.xml - -# History of marks within files (newest to oldest): - -> ~/app-root/data/saves/save-kwINKFSYtWXqBE1bg8Ffhy02GTfX84ds.xml - " 1 0 - -> ~/app-root/data/saves/save-dS77aOufZLQ6fsSckpso4L0iYY2oPJV2.xml - " 1 0 - -> ~/app-root/data/saves/save-busCM9w4ELAVvqcd9o879qFw9421hcUs.xml - " 1 0 - -> ~/app-root/data/saves/save-rR78NE1ZkzrhHThvfwgJPgHJcVYKhxnJ.xml - " 1 0 - -> ~/app-root/data/saves/save-liuL3y4zPQh8HbF7L3d4VKTRYy0BuFHP.xml - " 316 408 - -> ~/app-root/data/saves/save-uoBPmOWdbNI4uowtBZRZK8BIEUVvUn1o.xml - " 316 481 - -> ~/app-root/data/saves/save-lB8k45hvGWwScFyrX7sZNleLujZXTWdf.xml - " 1 0 - -> ~/app-root/runtime/repo/waet/saves/save-5himaxuOVduN40N45oRHOyoqU1qwpViu.xml - " 1 0
--- a/results/data/.vimrc Wed May 16 18:27:05 2018 +0100 +++ /dev/null Thu Jan 01 00:00:00 1970 +0000 @@ -1,1 +0,0 @@ -set viminfo+=n/var/lib/openshift/5aaedbfc251c080de5000030/app-root/data/.viminfo \ No newline at end of file
--- a/results/data/saves/.ipynb_checkpoints/Plots-checkpoint.ipynb Wed May 16 18:27:05 2018 +0100 +++ /dev/null Thu Jan 01 00:00:00 1970 +0000 @@ -1,865 +0,0 @@ -{ - "cells": [ - { - "cell_type": "code", - "execution_count": 1, - "metadata": {}, - "outputs": [], - "source": [ - "import glob\n", - "import pandas as pd\n", - "import matplotlib.pyplot as plt\n", - "import seaborn as sns\n", - "sns.set(style=\"ticks\", color_codes=True, font_scale=1.3)\n", - "\n", - "page1_df = pd.read_csv('ratings/page1-default-ratings.csv').set_index('file_keys')\n", - "page2_df = pd.read_csv('ratings/page2-default-ratings.csv').set_index('file_keys')\n", - "page3_df = pd.read_csv('ratings/page3-default-ratings.csv').set_index('file_keys')\n", - "page4_df = pd.read_csv('ratings/page4-default-ratings.csv').set_index('file_keys')\n", - "page5_df = pd.read_csv('ratings/page5-default-ratings.csv').set_index('file_keys')\n", - "page6_df = pd.read_csv('ratings/page6-default-ratings.csv').set_index('file_keys')\n", - "page7_df = pd.read_csv('ratings/page7-default-ratings.csv').set_index('file_keys')\n", - "page8_df = pd.read_csv('ratings/page8-default-ratings.csv').set_index('file_keys')\n", - "page9_df = pd.read_csv('ratings/page9-default-ratings.csv').set_index('file_keys')" - ] - }, - { - "cell_type": "code", - "execution_count": 2, - "metadata": {}, - "outputs": [], - "source": [ - "renamedict = {k: k[1:] for k in page1_df.columns}\n", - "page1 = page1_df.rename(columns=renamedict)\n", - "page1['story'] = 'a'\n", - "renamedict = {k: k[1:] for k in page2_df.columns}\n", - "page2 = page2_df.rename(columns=renamedict)\n", - "page2['story'] = 'b'\n", - "renamedict = {k: k[1:] for k in page3_df.columns}\n", - "page3 = page3_df.rename(columns=renamedict)\n", - "page3['story'] = 'c'\n", - "renamedict = {k: k[1:] for k in page4_df.columns}\n", - "page4 = page4_df.rename(columns=renamedict)\n", - "page4['story'] = 'a'\n", - "renamedict = {k: k[1:] for k in page5_df.columns}\n", - "page5 = page5_df.rename(columns=renamedict)\n", - "page5['story'] = 'b'\n", - "renamedict = {k: k[1:] for k in page6_df.columns}\n", - "page6 = page6_df.rename(columns=renamedict)\n", - "page6['story'] = 'c'\n", - "renamedict = {k: k[1:] for k in page7_df.columns}\n", - "page7 = page7_df.rename(columns=renamedict)\n", - "page7['story'] = 'a'\n", - "renamedict = {k: k[1:] for k in page8_df.columns}\n", - "page8 = page8_df.rename(columns=renamedict)\n", - "page8['story'] = 'b'\n", - "renamedict = {k: k[1:] for k in page9_df.columns}\n", - "page9 = page9_df.rename(columns=renamedict)\n", - "page9['story'] = 'c'\n" - ] - }, - { - "cell_type": "code", - "execution_count": 3, - "metadata": {}, - "outputs": [ - { - "data": { - "text/html": [ - "<div>\n", - "<style scoped>\n", - " .dataframe tbody tr th:only-of-type {\n", - " vertical-align: middle;\n", - " }\n", - "\n", - " .dataframe tbody tr th {\n", - " vertical-align: top;\n", - " 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b\n", - "bKhIcFzfZ3YXPxNiw4E7kFyoTFAqeFTp 0.00 0.00 1.00 0.75 1.00 1.00 b\n", - "ufohn9b31ZNI2zLGNqmmRYOMtIwiw6o1 0.13 0.08 0.86 0.95 0.74 0.76 b\n", - "fZGbsBmuEtrB35G2IzQu0IxOCVoljWpz 0.00 0.00 0.97 0.99 1.00 0.61 b\n", - "G2WO7k3tSjvBrlMG1Nqz4DsKBO8oaEcQ 0.00 0.00 0.49 1.00 0.65 0.82 b\n", - "OK2yLWD54tr3klqiS631VXjQlroZfmD3 0.00 0.03 0.95 1.00 0.83 0.83 b\n", - "t1Ybl1O1EAdpBEbxOLbaU4QlHtAcGCxa 0.00 0.15 0.48 0.76 0.74 0.87 b\n", - "D0Fq5YbSHwHaHK9V5pIWlIg5T6Ji3fQH 0.00 0.00 0.98 0.74 0.92 0.91 b\n", - "uoBPmOWdbNI4uowtBZRZK8BIEUVvUn1o 0.09 0.10 0.77 1.00 0.90 1.00 b\n", - "lIOWKvmCLdlUhGFYwE3lOfizSeqtxyNT 0.12 0.11 0.77 0.92 1.00 0.90 b\n", - "IXHrDvdwYoDCO7bvwRMB7jD46hoWAjDi 0.02 0.01 0.87 0.98 0.87 0.93 c\n", - "iWogwaa7GooHWHcp8C0ZjRrTMDgcae0t 0.00 0.00 0.97 1.00 1.00 1.00 c\n", - "bOyRMU1QCcMqMpcjcHNBuVMF45oksQMD 0.00 0.24 1.00 1.00 1.00 1.00 c\n", - "U6mgdJX1DgAfYJ6DR7sKY0CL4YgcwZKq 0.00 0.00 0.72 0.85 0.88 0.66 c\n", - "VyX492RQzqQXRL84PByL9pLt8C5p4c50 0.02 0.00 0.93 0.82 0.97 0.83 c\n", - "bkHwhN78d7k2kIanOievgityZQD7gVOr 0.18 0.23 0.89 0.92 0.95 0.90 c\n", - "ufohn9b31ZNI2zLGNqmmRYOMtIwiw6o1 0.07 0.11 0.77 0.93 0.87 0.93 c\n", - "fZGbsBmuEtrB35G2IzQu0IxOCVoljWpz 0.01 0.00 1.00 1.00 0.97 0.75 c\n", - "G2WO7k3tSjvBrlMG1Nqz4DsKBO8oaEcQ 0.20 0.20 0.60 1.00 1.00 0.75 c\n", - "OK2yLWD54tr3klqiS631VXjQlroZfmD3 0.00 0.07 0.91 0.97 0.84 0.73 c\n", - "D0Fq5YbSHwHaHK9V5pIWlIg5T6Ji3fQH 0.10 0.29 0.51 0.95 0.52 0.87 c\n", - "KBKzd0PezF8bsGoEZTkVkpmj1o8OECIo 0.12 0.66 0.28 0.05 0.54 0.44 c\n", - "uoBPmOWdbNI4uowtBZRZK8BIEUVvUn1o 0.12 0.14 0.77 1.00 0.95 0.97 c\n", - "lIOWKvmCLdlUhGFYwE3lOfizSeqtxyNT 0.24 0.12 0.89 0.82 0.69 0.90 c" - ] - }, - "execution_count": 3, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "task1_df = page1.append(page2).append(page3)\n", - "task2_df = page4.append(page5).append(page6)\n", - "task3_df = page7.append(page8).append(page9)\n", - "\n", - "def transform_df(df):\n", - " records = []\n", - " for n in range(len(df)):\n", - " for c in df.columns:\n", - " if c not in ['file_keys', 'story']:\n", - " records.append({\n", - " 'stimulus': c,\n", - " 'story': df['story'].iloc[n],\n", - " 'preference': df[c].iloc[n]\n", - " \n", - " })\n", - " \n", - " return pd.DataFrame.from_records(records)\n", - " \n", - "task1_df" - ] - }, - { - "cell_type": "code", - "execution_count": 4, - "metadata": {}, - "outputs": [], - "source": [ - "task1_transformed = transform_df(task1_df)\n", - "task2_transformed = transform_df(task2_df)\n", - "task3_transformed = transform_df(task3_df)" - ] - }, - { - "cell_type": "code", - "execution_count": 5, - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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\n", - "text/plain": [ - "<matplotlib.figure.Figure at 0x7f8053549c18>" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "fig, axes = plt.subplots(nrows=4, ncols=4)" - ] - }, - { - "cell_type": "code", - "execution_count": 6, - "metadata": {}, - "outputs": [], - "source": [ - "from matplotlib import gridspec\n", - "#sns.set(font_scale=1.3)" - ] - }, - { - "cell_type": "code", - "execution_count": 7, - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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\n", - "text/plain": [ - "<matplotlib.figure.Figure at 0x7f80511c4208>" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "#sns.set(style=\"whitegrid\", color_codes=True)\n", - "fig = plt.figure(figsize=(5,5))\n", - "gs = gridspec.GridSpec(2,1,height_ratios=[2,1])\n", - "plt.subplot(gs[0])\n", - "g = sns.boxplot(data=task1_transformed, x='stimulus', y='preference', hue='story', width=0.8, palette={'a':'red','b':'yellow','c':'cyan'})\n", - "g.set_ylabel('individual')\n", - "g.set(xticklabels=[], xlabel='',)\n", - "g.set_xticks([])\n", - "plt.subplot(gs[1])\n", - "g2 = sns.boxplot(data=task1_transformed, x='stimulus', y='preference', width=0.6, palette='gray')\n", - "g2.set_ylabel('aggregate')\n", - "for box in g2.artists:\n", - " box.set_facecolor(\"magenta\")\n", - "fig.tight_layout()\n", - "plt.savefig('task1.pdf', dpi=300,bbox_inches='tight')" - ] - }, - { - "cell_type": "code", - "execution_count": 8, - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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\n", - "text/plain": [ - "<matplotlib.figure.Figure at 0x7f8050e212e8>" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "fig = plt.figure(figsize=(5,5))\n", - "gs = gridspec.GridSpec(2,1,height_ratios=[2,1])\n", - "plt.subplot(gs[0])\n", - "\n", - "g = sns.boxplot(data=task2_transformed, x='stimulus', y='preference', hue='story', width=0.8, palette={'a':'red','b':'yellow','c':'cyan'})\n", - "sns.set_style({'legend.frameon':False})\n", - "g.set_ylabel('individual')\n", - "g.set(xticklabels=[], xlabel='',)\n", - "g.set_xticks([])\n", - "g.set(yticklabels=[], ylabel='',)\n", - "g.set_yticks([])\n", - "\n", - "plt.subplot(gs[1])\n", - "g2 = sns.boxplot(data=task2_transformed, x='stimulus', y='preference', width=0.6, palette='gray')\n", - "g2.set_ylabel('aggregate')\n", - "g2.set(yticklabels=[], ylabel='',)\n", - "g2.set_yticks([])\n", - "for box in g2.artists:\n", - " box.set_facecolor(\"magenta\")\n", - "fig.tight_layout()\n", - "plt.savefig('task2.pdf', dpi=300,bbox_inches='tight')" - ] - }, - { - "cell_type": "code", - "execution_count": 9, - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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\n", - "text/plain": [ - "<matplotlib.figure.Figure at 0x7f8050e93198>" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "#sns.set(style=\"whitegrid\", color_codes=True)\n", - "fig = plt.figure(figsize=(5,5))\n", - "gs = gridspec.GridSpec(2,1,height_ratios=[2,1])\n", - "plt.subplot(gs[0])\n", - "g = sns.boxplot(data=task3_transformed, x='stimulus', y='preference', hue='story', width=0.8, palette={'a':'red','b':'yellow','c':'cyan'})\n", - "g.set_ylabel('individual')\n", - "g.set(xticklabels=[], xlabel='',)\n", - "g.set_xticks([])\n", - "\n", - "g.set(yticklabels=[], ylabel='',)\n", - "g.set_yticks([])\n", - "plt.subplot(gs[1])\n", - "g2 = sns.boxplot(data=task3_transformed, x='stimulus', y='preference', width=0.6, palette='gray')\n", - "g2.set_ylabel('aggregate')\n", - "\n", - "g2.set(yticklabels=[], ylabel='')\n", - "g2.set_yticks([])\n", - "g2.legend('')\n", - "for box in g2.artists:\n", - " box.set_facecolor(\"magenta\")\n", - "fig.tight_layout()\n", - "plt.savefig('task3.pdf', dpi=300, bbox_inches='tight')" - ] - }, - { - "cell_type": "code", - "execution_count": 10, - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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- "text/plain": [ - "<matplotlib.figure.Figure at 0x7f80901d0080>" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "text/plain": [ - "[(0.8941176470588235, 0.10196078431372557, 0.10980392156862737),\n", - " (0.21568627450980393, 0.4941176470588236, 0.7215686274509804),\n", - " (0.3019607843137256, 0.6862745098039216, 0.29019607843137263),\n", - " (0.5960784313725492, 0.3058823529411765, 0.6392156862745098),\n", - " (1.0, 0.4980392156862745, 0.0),\n", - " (0.9999999999999998, 1.0, 0.19999999999999996),\n", - " (0.6509803921568629, 0.33725490196078434, 0.1568627450980391),\n", - " (0.9686274509803922, 0.5058823529411766, 0.7490196078431374),\n", - " (0.6, 0.6, 0.6)]" - ] - }, - "execution_count": 10, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "sns.choose_colorbrewer_palette('qualitative')" - ] - } - ], - "metadata": { - "kernelspec": { - "display_name": "Python 3", - "language": "python", - "name": "python3" - }, - "language_info": { - "codemirror_mode": { - "name": "ipython", - "version": 3 - }, - "file_extension": ".py", - "mimetype": "text/x-python", - "name": "python", - "nbconvert_exporter": "python", - "pygments_lexer": "ipython3", - "version": "3.6.4" - } - }, - "nbformat": 4, - "nbformat_minor": 2 -}
--- a/results/data/saves/.ipynb_checkpoints/plots-checkpoint.ipynb Wed May 16 18:27:05 2018 +0100 +++ /dev/null Thu Jan 01 00:00:00 1970 +0000 @@ -1,1296 +0,0 @@ -{ - "cells": [ - { - "cell_type": "code", - "execution_count": 1, - "metadata": {}, - "outputs": [], - "source": [ - "import glob\n", - "import pandas as pd\n", - "\n", - "from matplotlib import rc\n", - "rc('font',**{'family':'sans-serif','sans-serif':['Helvetica']})\n", - "## for Palatino and other serif fonts use:\n", - "#rc('font',**{'family':'serif','serif':['Palatino']})\n", - "rc('text', usetex=True)\n", - "\n", - "import matplotlib.pyplot as plt\n" - ] - }, - { - "cell_type": "code", - "execution_count": 2, - "metadata": {}, - "outputs": [], - "source": [ - "page1_df = pd.read_csv('ratings/page1-default-ratings.csv').set_index('file_keys')\n", - "page2_df = pd.read_csv('ratings/page2-default-ratings.csv').set_index('file_keys')\n", - "page3_df = 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"G2WO7k3tSjvBrlMG1Nqz4DsKBO8oaEcQ 0.33 0.58 0.57 0.36 \n", - "OK2yLWD54tr3klqiS631VXjQlroZfmD3 0.88 0.51 0.38 1.00 \n", - "t1Ybl1O1EAdpBEbxOLbaU4QlHtAcGCxa 0.50 0.74 0.25 1.00 \n", - "JZaBaWCeuGjSAyoUrfwdASaIHXkHCZml 0.90 0.41 0.68 1.00 \n", - "uoBPmOWdbNI4uowtBZRZK8BIEUVvUn1o 0.76 0.90 0.64 1.00 \n", - "lIOWKvmCLdlUhGFYwE3lOfizSeqtxyNT 1.00 0.24 0.76 0.51 \n", - "\n", - "[17 rows x 48 columns]" - ] - }, - "execution_count": 4, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "big_results = page1_df.join(page2_df).join(page3_df).join(page4_df).join(page5_df).join(page6_df).join(page7_df).join(page8_df)\n", - "big_results" - ] - }, - { - "cell_type": "code", - "execution_count": 5, - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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\n", - "text/plain": [ - "<matplotlib.figure.Figure at 0x7fc8b8c5de80>" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "char_df = page1_df.join(page2_df).join(page3_df)\n", - "\n", - "immers_df = page4_df.join(page5_df).join(page6_df)\n", - "renamedict = {k: k[:-1] for k in immers_df.columns}\n", - "immers_df = immers_df.rename(columns=renamedict)\n", - "\n", - "prefer_df = page7_df.join(page8_df).join(page9_df)\n", - "renamedict = {k: k[:-1] for k in prefer_df.columns}\n", - "prefer_df = prefer_df.rename(columns=renamedict)\n", - "\n", - "plt.rc('text', usetex=True)\n", - "plt.rc('font', family='serif')\n", - "char_df.boxplot(grid=False, rot=90,fontsize=15)\n", - "plt.title('Character Identification')\n", - "plt.savefig('characterid.pdf', dpi=300)" - ] - }, - { - "cell_type": "code", - "execution_count": 6, - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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\n", 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\n", - "text/plain": [ - "<matplotlib.figure.Figure at 0x7fc8d15fbcf8>" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "prefer_df.boxplot(grid=False, rot=90,fontsize=15)\n", - "plt.title('Preference')\n", - "plt.savefig('preference.pdf', dpi=300)" - ] - }, - { - "cell_type": "code", - "execution_count": 8, - "metadata": {}, - "outputs": [], - "source": [ - "import seaborn as sns" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [] - }, - { - "cell_type": "code", - "execution_count": 10, - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "<matplotlib.axes._subplots.AxesSubplot at 0x7fc8d0c8ba90>" - ] - }, - "execution_count": 10, - "metadata": {}, - "output_type": "execute_result" - }, - { - "data": { - "image/png": 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\n", - "text/plain": [ - "<matplotlib.figure.Figure at 0x7fc8d0c8b518>" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "# columns = \\\n", - "# ['a0000', 'b0000', 'c0000',\n", - "# 'a0011', 'b0011', 'c0011',\n", - "# 'a1011', 'b1011', 'c1011', \n", - "# 'a1110', 'b1110', 'c1110', \n", - "# 'a1111', 'b1111', 'c1111', \n", - "# ]\n", - " \n", - "# br = big_results[columns]\n", - "columns = sorted(big_results.columns)\n", - "br = big_results[columns]\n", - "br.boxplot()\n" - ] - }, - { - "cell_type": "code", - "execution_count": 13, - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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\n", - "text/plain": [ - "<matplotlib.figure.Figure at 0x7fc8e8787ac8>" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "import seaborn as sns\n", - "sns.set(style=\"ticks\")\n", - "\n", - "# Load the example tips dataset\n", - "tips = sns.load_dataset(\"tips\")\n", - "\n", - "# Draw a nested boxplot to show bills by day and sex\n", - "sns.boxplot(x=\"day\", y=\"total_bill\", hue=\"sex\", data=tips, palette=\"PRGn\")\n", - "sns.despine(offset=10, trim=True)" - ] - }, - { - "cell_type": "code", - "execution_count": 12, - "metadata": {}, - "outputs": [], - "source": [ - "renamedict = {k: k[1:] for k in page1_df.columns}\n", - "page1 = page1_df.rename(columns=renamedict)\n", - "renamedict = {k: k[1:] for k in page2_df.columns}\n", - "page2 = page2_df.rename(columns=renamedict)\n", - "renamedict = {k: k[1:] for k in page3_df.columns}\n", - "page3 = page3_df.rename(columns=renamedict)" - ] - }, - { - "cell_type": "code", - "execution_count": 15, - "metadata": 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