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viewer-framework.sublime-workspace
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viewer-framework.sublime-workspace
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{
"auto_complete":
{
"selected_items":
[
[
"name_",
"name_custom_view"
],
[
"if",
"if\tIf Condition"
],
[
"list",
"list_tags"
],
[
"key",
"key_corpus"
],
[
"id_",
"id_item"
],
[
"set",
"set_new_entities"
],
[
"m_id",
"m_id_wrapper"
],
[
"PLACEHOLDER",
"PLACEHOLDER_ID_WRAPPER"
],
[
"m_in",
"m_index_position"
],
[
"trigger",
"trigger_tag_filter_change"
],
[
"name",
"name"
],
[
"recommen",
"recommendation_add_tag"
],
[
"has",
"has_access_to_tagging"
],
[
"get_settin",
"get_settings_for_corpus"
],
[
"text_",
"text_splitted"
],
[
"posi",
"position_of_first_difference"
],
[
"char",
"character_current_a"
],
[
"string_a",
"string_a"
],
[
"string",
"string_a"
],
[
"overf",
"overflow-y"
],
[
"i",
"i"
],
[
"path",
"path_template"
],
[
"glob_",
"glob_current_corpus"
],
[
"url",
"url_params"
],
[
"glob_tag",
"glob_filter_tags"
],
[
"glob_tags",
"glob_dict_filter_tags"
],
[
"id",
"id_corpus"
],
[
"dict",
"dict_tmp"
],
[
"exce",
"exception_processed"
],
[
"PLACE",
"PLACEHOLDER_FILE"
],
[
"dict_corpor",
"dict_corpora_with_exceptions"
],
[
"dict_corpo",
"dict_corpora_with_exceptions"
],
[
"value",
"value"
],
[
"obj",
"obj_tmp_key"
],
[
"obj_",
"obj_tmp_key"
],
[
"id_item",
"id_item_internal"
],
[
"glob_sele",
"glob_selected_items"
],
[
"btn-group",
"btn-group-sm"
],
[
"def",
"def\tFunction"
],
[
"fn",
"function"
],
[
"strin",
"string_exception"
],
[
"clas",
"class_handle_index"
],
[
"exists",
"exists_in"
],
[
"inter",
"field_internal_id"
],
[
"Text",
"TEXT"
],
[
"type",
"type_data_field"
],
[
"inf",
"info_filter_values"
],
[
"list_d",
"list_data_new"
],
[
"se",
"settings_corpus"
],
[
"dict_",
"dict_corpora"
],
[
"update",
"update_cache"
],
[
"glob",
"glob_manager_data"
],
[
"index",
"index_corpus"
],
[
"get_sett",
"get_setting_for_corpus"
],
[
"pa",
"path_settings"
],
[
"stat",
"state_loaded"
],
[
"len",
"length_in_bytes"
],
[
"corpus",
"current_corpus"
],
[
"lsit",
"list_ids"
],
[
"column",
"column_to_sortx"
],
[
"sort",
"sorted_list"
],
[
"list_",
"list_ids"
],
[
"with",
"with_size"
],
[
"size",
"size_in_bytes"
],
[
"custom",
"custom_struct"
],
[
"bak",
"background-color"
],
[
"is",
"is_case_sensitive"
],
[
"max",
"max_length"
],
[
"values",
"values_parsed"
],
[
"data_",
"data_new"
],
[
"info",
"info_values"
],
[
"template",
"template_info_filter_values"
],
[
"info_",
"info_filter_values"
],
[
"dic",
"dict_annotations"
],
[
"Dict",
"DICT_SETTINGS_VIEWER"
],
[
"module",
"module_settings"
],
[
"data",
"data_only_ids"
],
[
"tmp",
"tmp_dict"
],
[
"entr",
"entry_input"
],
[
"entry",
"entry_content"
],
[
"load_file",
"load_file_ldjson"
],
[
"viewer",
"viewer__filter"
],
[
"stats",
"stats_decision_tree"
],
[
"predi",
"prediction"
],
[
"decision",
"decision_tree_regressor"
],
[
"score",
"score_roc_auc"
],
[
"query",
"queryset_interactions"
],
[
"interac",
"interactions"
],
[
"test",
"X_test"
],
[
"X_",
"X_train"
],
[
"queryset",
"queryset_interactions"
],
[
"m2m",
"m2m_Query"
],
[
"json",
"json_query"
],
[
"fk_q",
"fk_next_query_border"
],
[
"fk_next",
"fk_next_query_border"
],
[
"end",
"end_interaction"
],
[
"fk_",
"fk_start_interaction"
],
[
"add",
"add_query"
],
[
"glob_filter",
"glob_filter_tag"
],
[
"for",
"for\tfor (…) {…}"
],
[
"glob_fil",
"glob_filter_tag"
],
[
"al",
"text-align"
],
[
"table",
"table_only"
],
[
"glob_c",
"glob_count_pages"
],
[
"order",
"order_by"
],
[
"all",
"all_users"
],
[
"quer",
"queryset_user"
],
[
"refer",
"reference_interaction"
],
[
"rgb",
"rgba()"
],
[
"background",
"background-color"
],
[
"spl",
"splitted_time"
],
[
"count",
"count_queries"
],
[
"pr",
"process_timegap"
],
[
"store",
"store_log"
],
[
"fil",
"file_name_output"
],
[
"content",
"content_length"
],
[
"whi",
"whitelist_ids"
],
[
"li",
"list_sorted_keys"
],
[
"file_",
"file_output"
],
[
"new",
"new_list_phrases"
],
[
"filter",
"filter_paper_out"
],
[
"file",
"file_output"
],
[
"sum",
"sum_keyphrases"
],
[
"sc",
"score_keyphraseness"
],
[
"spli",
"splitted_line"
],
[
"set_",
"set_referenced_missing_documents"
],
[
"judg",
"judgements_user"
],
[
"tax",
"tax_class"
]
]
},
"buffers":
[
{
"file": "viewer-framework/viewer/models.py",
"settings":
{
"buffer_size": 1160,
"line_ending": "Unix"
}
},
{
"contents": "<dom-module id=\"viewer-template\">\n\n <template>\n\n <style>\n /* shadow DOM styles go here */\n :host {\n display: inline-block;\n }\n </style>\n\n <!-- shadow DOM goes here -->\n <div></div>\n <div>[[ objItem.text ]]</div>\n <div>[[ objItem.id ]]</div>\n </template>\n\n <script>\n class ViewerTemplate extends Polymer.Element {\n static get is() {\n return 'viewer-template';\n }\n static get properties() {\n return {\n objItem: {\n type: Object\n },\n }\n }\n constructor() {\n super();\n }\n }\n customElements.define(ViewerTemplate.is, ViewerTemplate);\n </script>\n\n</dom-module>\n",
"file": "viewer-framework/viewer/static/viewer/bower_components/viewer-template.html",
"file_size": 863,
"file_write_time": 131489904767653470,
"settings":
{
"buffer_size": 863,
"line_ending": "Unix"
}
},
{
"contents": "def load_data(item_handle):\n import csv\n \n def get_corrections(row):\n list_corrections = []\n for element in row[2:]:\n if element == '':\n break\n else: \n list_corrections.append(element)\n return list_corrections\n\n path = \"../corpora/webis-query-speller-corpus.csv\"\n with open(path, 'r') as csvfile:\n spamreader = csv.reader(csvfile, delimiter=';', quotechar='\"')\n for row in spamreader:\n list_corrections = get_corrections(row)\n\n entry = {}\n entry['id'] = row[0]\n entry['query'] = row[1]\n entry['corrections'] = ', '.join(list_corrections)\n entry['count_corrections'] = len(list_corrections)\n\n item_handle.add(entry)\n\n\nDICT_SETTINGS_VIEWER = {\n # possible values: 'csv-file', 'ldjson-file', 'custom', 'database'\n 'name': 'Webis-QSpell-17',\n 'description': '',\n 'data_type': 'custom',\n # function to load the data\n 'load_data_function': load_data,\n 'use_cache': True,\n 'data_fields': {\n 'id': {\n 'type': 'number',\n 'display_name': 'ID'\n },\n 'corrections': {\n 'type': 'text',\n 'display_name': 'Spelling variants'\n },\n 'query': {\n 'type': 'string',\n 'display_name': 'Query'\n },\n 'count_corrections': {\n 'type': 'number',\n 'display_name': '#Variants'\n }\n },\n 'id': 'id',\n 'displayed_fields': [\n 'id', 'query', 'count_corrections', 'corrections'\n ],\n 'page_size': 25,\n 'filters': [\n {\n 'data_field': 'query',\n 'description': 'Query',\n 'placeholder': '',\n 'default_value': '',\n },\n {\n 'data_field': 'id',\n 'description': 'ID',\n 'placeholder': '',\n 'default_value': '',\n },\n {\n 'data_field': 'count_corrections',\n 'description': '#Variants',\n 'placeholder': '',\n 'default_value': '',\n },\n {\n 'data_field': 'corrections',\n 'description': 'Variants',\n 'placeholder': '',\n 'default_value': '',\n },\n ],\n 'secret_token_tagging': '1234',\n 'template_html': \"\"\"<dom-module id=\"viewer-template\">\n\n <template>\n <link rel=\"stylesheet\" href=\"[[ bootstrapCss ]]\">\n <style>\n /* shadow DOM styles go here */\n :host {\n /*display: inline-block;*/\n }\n\n </style>\n <div class=\"row\">\n <div class=\"col\">\n <h1>Query: \"{{ objItem.query }}\"</h1>\n\n <table id=\"table_test\" class=\"table table-striped\">\n <thead>\n <tr>\n <th></th>\n <th>Variants</th>\n </tr>\n </thead>\n <tbody>\n </tbody>\n </table>\n </div>\n </div>\n </template>\n\n <script>\n function get_position_of_first_difference(a, b) {\n let length_a = a.length;\n let length_b = b.length;\n\n let position = -1;\n\n for (let i = 0; i < a.length; i++) \n {\n character_current_a = a[i];\n if(i < length_b)\n {\n character_current_b = b[i];\n if(character_current_a != character_current_b)\n {\n return i\n }\n } else {\n return position;\n }\n }\n return position;\n }\n\n class ViewerTemplate extends Polymer.Element {\n static get is() {\n return 'viewer-template';\n }\n static get properties() {\n return {\n objItem: {\n type: Object,\n },\n bootstrapCss: {\n type: String\n },\n bootstrapJs: {\n type: String\n },\n jqueryJs: {\n type: String\n }\n }\n }\n constructor() {\n super();\n }\n ready() {\n super.ready()\n this.objItem.corrections = this.objItem.corrections.split(',')\n let element_table = this.shadowRoot.querySelector('#table_test tbody');\n const replacement = '<span class=\"bg-warning\">PLACEHOLDER</span>'\n\n for (let i = 0; i < this.objItem.corrections.length; i++) {\n let correction = this.objItem.corrections[i].trim();\n let position_of_first_difference = -1;\n if(i > 0)\n {\n let string_a = correction;\n let string_b = this.objItem.corrections[i-1].trim();\n position_of_first_difference = get_position_of_first_difference(string_a, string_b);\n }\n\n if(position_of_first_difference != -1)\n {\n correction[position_of_first_difference]\n const replacement_custom = replacement.replace('PLACEHOLDER', correction[position_of_first_difference])\n correction = correction.substr(0, position_of_first_difference) + replacement_custom + correction.substr(position_of_first_difference + 1)\n }\n\n let row = element_table.insertRow(-1);\n let cell1 = row.insertCell(0);\n cell1.innerHTML = i+1;\n let cell2 = row.insertCell(1);\n cell2.innerHTML = correction;\n // let row_new = `\n // <tr>\n // <td>`+(i+1)+`</td>\n // <td>`+correction+`</td>\n // </tr>\n // `\n // element_table.innerHTML = element_table.innerHTML + row_new;\n }\n }\n }\n customElements.define(ViewerTemplate.is, ViewerTemplate);\n </script>\n\n</dom-module>\n\"\"\"\n # 'template_path': \"\"\"../corpora/template_query_speller.html\"\"\"\n}",
"file": "settings/settings_viewer_query_speller.py",
"file_size": 6534,
"file_write_time": 131514093722413673,
"settings":
{
"buffer_size": 6534,
"line_ending": "Unix"
}
},
{
"file": "settings/settings_viewer_example.py",
"settings":
{
"buffer_size": 2607,
"encoding": "UTF-8",
"line_ending": "Windows"
}
},
{
"contents": "def load_data(item_handle):\n import os\n import json\n import csv\n\n def load_annotations(path_truth, annotator):\n dict_annotations = {}\n with open(os.path.join(path_truth, annotator+'.csv'), 'r') as f:\n spamreader = csv.reader(f)\n for row in spamreader:\n id_tweet = int(row[0])\n score = row[1]\n dict_annotations[id_tweet] = score\n\n return dict_annotations\n\n path_corpora = '../corpora/webis-cbc-16'\n path_truth = os.path.join(path_corpora, 'truth')\n path_problems = os.path.join(path_corpora, 'problems')\n\n\n dict_annotations_annotatorA = load_annotations(path_truth, 'annotatorA')\n dict_annotations_annotatorB = load_annotations(path_truth, 'annotatorB')\n dict_annotations_annotatorC = load_annotations(path_truth, 'annotatorC')\n dict_annotations_majority = load_annotations(path_truth, 'majority')\n\n counter_error = 0\n for folder in os.listdir(path_problems):\n path_problem = os.path.join(path_problems, folder)\n for file in os.listdir(path_problem):\n path_file = os.path.join(path_problem, file)\n if file.endswith('.json'):\n with open(path_file, 'r') as f:\n try:\n obj_json = json.loads(f.read())\n obj_tweet = {}\n obj_tweet['id'] = obj_json['id']\n obj_tweet['text'] = obj_json['text']\n obj_tweet['retweet_count'] = int(obj_json['retweet_count'])\n obj_tweet['annotatorA'] = dict_annotations_annotatorA[obj_json['id']]\n obj_tweet['annotatorB'] = dict_annotations_annotatorB[obj_json['id']]\n obj_tweet['annotatorC'] = dict_annotations_annotatorC[obj_json['id']]\n obj_tweet['majority'] = dict_annotations_majority[obj_json['id']]\n item_handle.add(obj_tweet)\n except (json.decoder.JSONDecodeError, UnicodeDecodeError):\n counter_error += 1\n\n print('counter_error')\n print(counter_error)\n print('counter_error')\n\n# this is the main dictionary containing the necessary information to load and display your corpus\nDICT_SETTINGS_VIEWER = {\n 'name': 'Webis-Clickbait-16',\n 'description': 'This corpus holds 2992 annotated Tweets.',\n 'data_type': 'custom',\n 'load_data_function': load_data,\n 'data_fields': {\n 'id': {\n 'type': 'number',\n 'display_name': 'ID'\n },\n 'text': {\n 'type': 'text',\n 'display_name': 'Text'\n },\n 'retweet_count': {\n 'type': 'number',\n 'display_name': 'Retweets'\n },\n 'annotatorA': {\n 'type': 'string',\n 'display_name': 'A'\n },\n 'annotatorB': {\n 'type': 'string',\n 'display_name': 'B'\n },\n 'annotatorC': {\n 'type': 'string',\n 'display_name': 'C'\n },\n 'majority': {\n 'type': 'string',\n 'display_name': 'majority'\n }\n },\n 'id': 'id',\n 'displayed_fields': [\n 'id', 'retweet_count', 'text', 'annotatorA', 'annotatorB', 'annotatorC', 'majority'\n ],\n 'page_size': 25,\n 'filters': [\n {\n 'data_field': 'text',\n 'description': 'Tweet Text',\n 'placeholder': 'Text Input',\n 'default_value': '',\n },\n {\n 'data_field': 'majority',\n 'description': 'Majority',\n 'placeholder': 'Text Input',\n 'default_value': '',\n },\n {\n 'data_field': 'retweet_count',\n 'description': 'Count Retweets',\n 'placeholder': 'Count Input',\n 'default_value': '',\n },\n ],\n 'secret_token': 'test',\n 'template_html': \"\"\"<style>\n .box_tweet {\n border: 1px solid #ddd;\n border-radius: 7px;\n padding: 30px 40px;\n }\n .box_color {\n height: 3rem;\n width: 3rem;\n }\n</style>\n<div class=\"row justify-content-center mt-5\">\n <div class=\"col-lg-5 col-md-8 col-sm-10\">\n <div class=\"box_tweet\">\n <p id=\"text_tweet\" style=\"font-size: 26px\"></p>\n <div id=\"wrapper_images_'+tweet[0]+'\" class=\"row\"></div>\n </div>\n </div>\n</div>\n<div class=\"row justify-content-center mt-5\">\n <div class=\"col col-md-auto\">\n <div class=\"row text-nowrap\">\n <div class=\"col\">\n <div id=\"annotation_a\" class=\"box_color mx-auto\"></div>\n Annotator A\n </div>\n <div class=\"col\">\n <div id=\"annotation_b\" class=\"box_color mx-auto\"></div>\n Annotator B\n </div>\n <div class=\"col\">\n <div id=\"annotation_c\" class=\"box_color mx-auto\"></div>\n Annotator C\n </div>\n <div class=\"col\">\n <div id=\"annotation_majority\" class=\"box_color mx-auto\"></div>\n Majority\n </div>\n </div>\n </div>\n</div>\n\n<script>\n function linkify(text){\n if (text) {\n text = text.replace(\n /((https?\\:\\/\\/)|(www\\.))(\\S+)(\\w{2,4})(:[0-9]+)?(\\/|\\/([\\w#!:.?+=&%@!\\-\\/]))?/gi,\n function(url){\n var full_url = url;\n if (!full_url.match('^https?:\\/\\/')) {\n full_url = 'http://' + full_url;\n }\n return '<a href=\"' + full_url + '\">' + 'Link' + '</a>';\n }\n );\n }\n return text;\n }\n\n function preprocess_text(text)\n {\n return linkify(text);\n }\n\n function get_color(annotation)\n {\n if(annotation == 'strong' || annotation == 'clickbait')\n {\n return \"hsl(0,100%,50%)\";\n } else if(annotation == 'medium') {\n return \"hsl(40,100%,50%)\";\n } else if(annotation == 'weak') {\n return \"hsl(80,100%,50%)\";\n } else if(annotation == 'none' || annotation == 'no-clickbait') {\n return \"hsl(120,100%,50%)\";\n }\n console.log('error')\n }\n\n 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"contents": "import os\nimport csv\nimport json\n\ndef load_data(item_handle):\n text = '2132'\n # text = 'Lorem ipsum dolor sit amet, consetetur sadipscing elitr, sed diam nonumy eirmod tempor invidunt ut labore et dolore magna aliquyam erat, sed diam voluptua. At vero eos et accusam et justo duo dolores et ea rebum. Stet clita kasd gubergren, no sea takimata sanctus est Lorem ipsum dolor sit amet. Lorem ipsum dolor sit amet, consetetur sadipscing elitr, sed diam nonumy eirmod tempor invidunt ut labore et dolore magna aliquyam erat, sed diam voluptua. At vero eos et accusam et justo duo dolores et ea rebum. Stet clita kasd gubergren, no sea takimata sanctus est Lorem ipsum dolor sit amet.'\n\n # with open('../large_corpus.txt') as f:\n # counter = 0\n # for line in f:\n # obj = {}\n # obj['id'] = counter\n # obj['text'] = text \n # item_handle.add(obj)\n # counter += 1\n # if counter % 1000000 == 0:\n # print(counter)\n # if counter == 10000000:\n # return\n\n # for x in range(0, 1):\n for x in range(0, 1000000):\n # for x in range(0, 100000):\n # for x in range(0, 1000000):\n # for x in range(0, 5000000):\n obj = {}\n obj['id'] = 'id_'+str(x)\n obj['text'] = text\n # obj['text'] = 'text_'+str(x % 5)\n item_handle.add(obj)\n\n\n\nDICT_SETTINGS_VIEWER = {\n # possible values: 'csv-file', 'ldjson-file', 'custom', 'database'\n 'name': 'large corpus',\n 'description': '',\n 'data_type': 'custom',\n # only necessary if data_type is '*-file'\n # path to data,\n # 'data_path': '../corpora/webis-cbc-16',\n 'data_path': '../corpora/file.ldjson',\n # structure of data in file\n 'data_structure': ['name', 'retweet_count', 'id'],\n\n\n # only necessary if data_type is 'custom'\n # function to load the data\n 'load_data_function': load_data,\n # only necessary if data_type is 'database'\n # name of the app where the model is located\n 'app_label': 'example_app',\n # name of the model\n 'model_name': 'Example_Model',\n 'use_cache': True,\n 'data_fields': {\n 'id': {\n 'type': 'string',\n 'display_name': 'ID'\n },\n 'text': {\n # 'type': 'string',\n 'type': 'text',\n 'display_name': 'Text'\n }\n },\n 'id': 'id',\n 'displayed_fields': [\n 'id', 'text'\n ],\n 'secret_token_editing': '',\n 'page_size': 25,\n # Possible filter types: 'text', 'checkbox'\n #\n 'filters': [\n {\n 'data_field': 'text',\n 'description': 'Text',\n 'placeholder': 'Text Input',\n 'default_value': '',\n },\n {\n 'data_field': 'id',\n 'description': 'Id',\n 'placeholder': 'Count Input',\n 'default_value': '',\n },\n ],\n}",
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