Visualization fix for real data

app/corpora/cqi_over_socketio/cqi.py

@@ -18,8 +18,8 @@ def cqi_connect(cqi_client: cqi.CQiClient):
             'msg': 'Internal Server Error',
             'payload': {'code': e.args[0], 'desc': e.args[1]}
         }
-    payload = {'code': cqi_status,
-               'msg': cqi.api.specification.lookup[cqi_status]}
+    payload = {'code': cqi_status.code,
+               'msg': cqi_status.__class__.__name__}
     return {'code': 200, 'msg': 'OK', 'payload': payload}
 
 
@@ -28,8 +28,8 @@ def cqi_connect(cqi_client: cqi.CQiClient):
 @cqi_over_socketio
 def cqi_disconnect(cqi_client: cqi.CQiClient):
     cqi_status = cqi_client.disconnect()
-    payload = {'code': cqi_status,
-               'msg': cqi.api.specification.lookup[cqi_status]}
+    payload = {'code': cqi_status.code,
+               'msg': cqi_status.__class__.__name__}
     return {'code': 200, 'msg': 'OK', 'payload': payload}
 
 
@@ -38,6 +38,6 @@ def cqi_disconnect(cqi_client: cqi.CQiClient):
 @cqi_over_socketio
 def cqi_ping(cqi_client: cqi.CQiClient):
     cqi_status = cqi_client.ping()
-    payload = {'code': cqi_status,
-               'msg': cqi.api.specification.lookup[cqi_status]}
+    payload = {'code': cqi_status.code,
+               'msg': cqi_status.__class__.__name__}
     return {'code': 200, 'msg': 'OK', 'payload': payload}

app/corpora/cqi_over_socketio/cqi_corpora_corpus.py

@@ -1,8 +1,9 @@
 from collections import Counter
 from flask import session
 import cqi
+import json
 import math
-import random
+import os
 from app import db, socketio
 from app.decorators import socketio_login_required
 from app.models import Corpus
@@ -16,8 +17,8 @@ from .utils import cqi_over_socketio, lookups_by_cpos
 def cqi_corpora_corpus_drop(cqi_client: cqi.CQiClient, corpus_name: str):
     cqi_corpus = cqi_client.corpora.get(corpus_name)
     cqi_status = cqi_corpus.drop()
-    payload = {'code': cqi_status,
-               'msg': cqi.api.specification.lookup[cqi_status]}
+    payload = {'code': cqi_status.code,
+               'msg': cqi_status.__class__.__name__}
     return {'code': 200, 'msg': 'OK', 'payload': payload}
 
 
@@ -27,8 +28,8 @@ def cqi_corpora_corpus_drop(cqi_client: cqi.CQiClient, corpus_name: str):
 def cqi_corpora_corpus_query(cqi_client: cqi.CQiClient, corpus_name: str, subcorpus_name: str, query: str):  # noqa
     cqi_corpus = cqi_client.corpora.get(corpus_name)
     cqi_status = cqi_corpus.query(subcorpus_name, query)
-    payload = {'code': cqi_status,
-               'msg': cqi.api.specification.lookup[cqi_status]}
+    payload = {'code': cqi_status.code,
+               'msg': cqi_status.__class__.__name__}
     return {'code': 200, 'msg': 'OK', 'payload': payload}
 
 
@@ -49,179 +50,109 @@ def cqi_corpora_corpus_update_db(cqi_client: cqi.CQiClient, corpus_name: str):
 @socketio_login_required
 @cqi_over_socketio
 def cqi_corpora_corpus_get_visualization_data(cqi_client: cqi.CQiClient, corpus_name: str):
-    corpus = cqi_client.corpora.get(corpus_name)
-    # s_attrs = [x for x in corpus.structural_attributes.list() if not x.has_values]
-    # p_attrs = corpus.positional_attributes.list()
-    # payload = {
-    #     's_attrs': {},
-    #     'p_attrs': {},
-    #     'values': {
-    #         's_attrs': {},
-    #         'p_attrs': {}
-    #     }
-    # }
-    # for s_attr in s_attrs:
-    #     s_attr_lbound, s_attr_rbound = s_attr.cpos_by_id(text_id)
-    #     s_attr_cpos_range = range(s_attr_lbound, s_attr_rbound + 1)
-    #     payload['text']['lexicon'][text_id] = {
-    #         's_attrs': [s_attr_lbound, s_attr_rbound],
-    #         'counts': {
-    #             'token': s_attr_rbound - s_attr_lbound + 1
-    #         },
-    #         'freqs': {
-    #             p_attr.name: dict(Counter(p_attr.ids_by_cpos(list(s_attr_cpos_range))))
-    #             for p_attr in p_attrs
-    #         }
-    #     }
-    # for p_attr in p_attrs:
-    #     payload['p_attrs'] = dict(
-
-    #     )
-    #     payload['values']['p_attrs'] = dict(
-    #         zip(
-    #             range(0, p_attr.lexicon_size),
-    #             p_attr.values_by_ids(list(range(0, p_attr.lexicon_size)))
-    #         )
-    #     )
-    text = corpus.structural_attributes.get('text')
-    text_value_names = []
-    text_values = []
-    for text_sub_attr in corpus.structural_attributes.list(filters={'part_of': text}):
-        text_value_names.append(text_sub_attr.name[(len(text.name) + 1):])
-        text_values.append(text_sub_attr.values_by_ids(list(range(0, text.size))))
-    s = corpus.structural_attributes.get('s')
-    ent = corpus.structural_attributes.get('ent')
-    ent_value_names = []
-    ent_values = []
-    for ent_sub_attr in corpus.structural_attributes.list(filters={'part_of': ent}):
-        ent_value_names.append(ent_sub_attr.name[(len(ent.name) + 1):])
-        ent_values.append(ent_sub_attr.values_by_ids(list(range(0, ent.size))))
-    word = corpus.positional_attributes.get('word')
-    lemma = corpus.positional_attributes.get('lemma')
-    pos = corpus.positional_attributes.get('pos')
-    simple_pos = corpus.positional_attributes.get('simple_pos')
-    payload = {}
-    payload['corpus'] = {'lexicon': {}, 'values': []}
-    payload['corpus']['lexicon'][0] = {
-        'bounds': [0, corpus.size - 1],
-        'counts': {
-            'text': text.size,
-            's': s.size,
-            'ent': ent.size,
-            'token': corpus.size
-        },
-        'freqs': {
-            'word': dict(
-                zip(
-                    range(0, word.lexicon_size),
-                    word.freqs_by_ids(list(range(0, word.lexicon_size)))
-                )
-            ),
-            'lemma': dict(
-                zip(
-                    range(0, lemma.lexicon_size),
-                    lemma.freqs_by_ids(list(range(0, lemma.lexicon_size)))
-                )
-            ),
-            'pos': dict(
-                zip(
-                    range(0, pos.lexicon_size),
-                    pos.freqs_by_ids(list(range(0, pos.lexicon_size)))
-                )
-            ),
-            'simple_pos': dict(
-                zip(
-                    range(0, simple_pos.lexicon_size),
-                    simple_pos.freqs_by_ids(list(range(0, simple_pos.lexicon_size)))
-                )
-            )
-        }
+    corpus = Corpus.query.get(session['d']['corpus_id'])
+    visualization_data_file_path = os.path.join(corpus.path, 'cwb', 'visualization_data.json')
+    if os.path.exists(visualization_data_file_path):
+        with open(visualization_data_file_path, 'r') as f:
+            payload = json.load(f)
+        return {'code': 200, 'msg': 'OK', 'payload': payload}
+    cqi_corpus = cqi_client.corpora.get(corpus_name)
+    ##########################################################################
+    # A faster way to get cpos boundaries for smaller s_attrs                #
+    ##########################################################################
+    # cqi_corpus.query('Last', '<s> []* </s>;')
+    # cqi_subcorpus = cqi_corpus.subcorpora.get('Last')
+    # print(cqi_subcorpus.size)
+    # first_match = 0
+    # last_match = cqi_subcorpus.attrs['size'] - 1
+    # match_boundaries = zip(
+    #     list(range(first_match, last_match + 1)),
+    #     cqi_subcorpus.dump(cqi_subcorpus.attrs['fields']['match'], first_match, last_match),
+    #     cqi_subcorpus.dump(cqi_subcorpus.attrs['fields']['matchend'], first_match, last_match)
+    # )
+    # for x in match_boundaries:
+    #     print(x)
+    cqi_p_attrs = {
+        p_attr.name: p_attr
+        for p_attr in cqi_corpus.positional_attributes.list()
     }
-    payload['text'] = {'lexicon': {}, 'values': None}
-    for text_id in range(0, text.size):
-        text_lbound, text_rbound = text.cpos_by_id(text_id)
-        text_cpos_range = range(text_lbound, text_rbound + 1)
-        text_s_ids = s.ids_by_cpos(list(text_cpos_range))
-        text_ent_ids = ent.ids_by_cpos(list(text_cpos_range))
-        payload['text']['lexicon'][text_id] = {
-            'bounds': [text_lbound, text_rbound],
+    cqi_s_attrs = {
+        s_attr.name: s_attr
+        for s_attr in cqi_corpus.structural_attributes.list()
+    }
+    payload = {
+        'corpus': {
+            'bounds': [0, cqi_corpus.size - 1],
             'counts': {
-                's': len([x for x in text_s_ids if x != -1]),
-                'ent': len([x for x in text_ent_ids if x != -1]),
-                'token': text_rbound - text_lbound + 1
+                'token': cqi_corpus.size
             },
-            'freqs': {
-                'word': dict(
-                    Counter(word.ids_by_cpos(list(text_cpos_range)))
-                ),
-                'lemma': dict(
-                    Counter(lemma.ids_by_cpos(list(text_cpos_range)))
-                ),
-                'pos': dict(
-                    Counter(pos.ids_by_cpos(list(text_cpos_range)))
-                ),
-                'simple_pos': dict(
-                    Counter(simple_pos.ids_by_cpos(list(text_cpos_range)))
-                )
-            }
-        }
-    payload['text']['values'] = text_value_names
-    payload['s'] = {'lexicon': {}, 'values': None}
-    for s_id in range(0, s.size):
-        payload['s']['lexicon'][s_id] = {
-            # 'bounds': s.cpos_by_id(s_id)
-        }
-    payload['s']['values'] = [
-        sub_attr.name[(len(s.name) + 1):]
-        for sub_attr in corpus.structural_attributes.list(filters={'part_of': s})
-    ]
-    payload['ent'] = {'lexicon': {}, 'values': None}
-    for ent_id in range(0, ent.size):
-        payload['ent']['lexicon'][ent_id] = {
-            # 'bounds': ent.cpos_by_id(ent_id)
-        }
-    payload['ent']['values'] = ent_value_names
-    payload['lookups'] = {
-        'corpus': {},
-        'text': {
-            text_id: {
-                text_value_name: text_values[text_value_name_idx][text_id_idx]
-                for text_value_name_idx, text_value_name in enumerate(text_value_names)
-            } for text_id_idx, text_id in enumerate(range(0, text.size))
+            'freqs': {}
         },
-        's': {},
-        'ent': {
-            ent_id: {
-                ent_value_name: ent_values[ent_value_name_idx][ent_id_idx]
-                for ent_value_name_idx, ent_value_name in enumerate(ent_value_names)
-            } for ent_id_idx, ent_id in enumerate(range(0, ent.size))
-        },
-        'word': dict(
+        'p_attrs': {},
+        's_attrs': {},
+        'values': {'p_attrs': {}, 's_attrs': {}}
+    }
+    for p_attr in cqi_p_attrs.values():
+        payload['corpus']['freqs'][p_attr.name] = dict(
             zip(
-                range(0, word.lexicon_size),
-                word.values_by_ids(list(range(0, word.lexicon_size)))
-            )
-        ),
-        'lemma': dict(
-            zip(
-                range(0, lemma.lexicon_size),
-                lemma.values_by_ids(list(range(0, lemma.lexicon_size)))
-            )
-        ),
-        'pos': dict(
-            zip(
-                range(0, pos.lexicon_size),
-                pos.values_by_ids(list(range(0, pos.lexicon_size)))
-            )
-        ),
-        'simple_pos': dict(
-            zip(
-                range(0, simple_pos.lexicon_size),
-                simple_pos.values_by_ids(list(range(0, simple_pos.lexicon_size)))
+                range(0, p_attr.lexicon_size),
+                p_attr.freqs_by_ids(list(range(0, p_attr.lexicon_size)))
             )
         )
-    }
-    # print(payload)
+        payload['p_attrs'][p_attr.name] = dict(
+            zip(
+                range(0, cqi_corpus.size),
+                p_attr.ids_by_cpos(list(range(0, cqi_corpus.size)))
+            )
+        )
+        payload['values']['p_attrs'][p_attr.name] = dict(
+            zip(
+                range(0, p_attr.lexicon_size),
+                p_attr.values_by_ids(list(range(0, p_attr.lexicon_size)))
+            )
+        )
+    for s_attr in cqi_s_attrs.values():
+        if s_attr.has_values:
+            continue
+        payload['corpus']['counts'][s_attr.name] = s_attr.size
+        payload['s_attrs'][s_attr.name] = {'lexicon': {}, 'values': None}
+        payload['values']['s_attrs'][s_attr.name] = {}
+        for id in range(0, s_attr.size):
+            payload['s_attrs'][s_attr.name]['lexicon'][id] = {}
+            lbound, rbound = s_attr.cpos_by_id(id)
+            payload['s_attrs'][s_attr.name]['lexicon'][id]['bounds'] = [lbound, rbound]
+            payload['s_attrs'][s_attr.name]['lexicon'][id]['counts'] = {}
+            payload['s_attrs'][s_attr.name]['lexicon'][id]['counts']['token'] = rbound - lbound + 1
+            if s_attr.name not in ['text', 's']:
+                continue
+            cpos_range = range(lbound, rbound + 1)
+            payload['s_attrs'][s_attr.name]['lexicon'][id]['counts']['ent'] = len({x for x in cqi_s_attrs['ent'].ids_by_cpos(list(cpos_range)) if x != -1})
+            if s_attr.name != 'text':
+                continue
+            payload['s_attrs'][s_attr.name]['lexicon'][id]['counts']['s'] = len({x for x in cqi_s_attrs['s'].ids_by_cpos(list(cpos_range)) if x != -1})
+            payload['s_attrs'][s_attr.name]['lexicon'][id]['freqs'] = {}
+            for p_attr in cqi_p_attrs.values():
+                payload['s_attrs'][s_attr.name]['lexicon'][id]['freqs'][p_attr.name] = dict(Counter(p_attr.ids_by_cpos(list(cpos_range))))
+        sub_s_attrs = cqi_corpus.structural_attributes.list(filters={'part_of': s_attr})
+        s_attr_value_names = [
+            sub_s_attr.name[(len(s_attr.name) + 1):]
+            for sub_s_attr in sub_s_attrs
+        ]
+        sub_s_attr_values = [
+            sub_s_attr.values_by_ids(list(range(0, s_attr.size)))
+            for sub_s_attr in sub_s_attrs
+        ]
+        payload['s_attrs'][s_attr.name]['values'] = s_attr_value_names
+        payload['values']['s_attrs'][s_attr.name] = {
+            s_attr_id: {
+                s_attr_value_name: sub_s_attr_values[s_attr_value_name_idx][s_attr_id_idx]
+                for s_attr_value_name_idx, s_attr_value_name in enumerate(
+                    payload['s_attrs'][s_attr.name]['values']
+                )
+            } for s_attr_id_idx, s_attr_id in enumerate(range(0, s_attr.size))
+        }
+    with open(visualization_data_file_path, 'w') as f:
+        json.dump(payload, f)
     return {'code': 200, 'msg': 'OK', 'payload': payload}
 
 

app/corpora/cqi_over_socketio/cqi_corpora_corpus_subcorpora.py

@@ -32,8 +32,8 @@ def cqi_corpora_corpus_subcorpora_subcorpus_drop(cqi_client: cqi.CQiClient, corp
     cqi_corpus = cqi_client.corpora.get(corpus_name)
     cqi_subcorpus = cqi_corpus.subcorpora.get(subcorpus_name)
     cqi_status = cqi_subcorpus.drop()
-    payload = {'code': cqi_status,
-               'msg': cqi.api.specification.lookup[cqi_status]}
+    payload = {'code': cqi_status.code,
+               'msg': cqi_status.__class__.__name__}
     return {'code': 200, 'msg': 'OK', 'payload': payload}
 
 

app/static/js/CorpusAnalysis/CorpusAnalysisApp.js

@@ -34,26 +34,26 @@ class CorpusAnalysisApp {
       .then(
         cQiCorpus => {
           this.data.corpus = {o: cQiCorpus};
-          // this.data.corpus.o.getVisualizationData()
-          //   .then(
-          //     (data) => {
-          //       console.log(data);
-          //       this.renderGeneralCorpusInfo(data);
-          //       this.renderTextInfoList(data);
-          //       this.renderTextProportionsGraphic(data);
-          //       this.renderWordFrequenciesGraphic(data);
-          //       this.renderBoundsGraphic(data);
-          //     }
-          //   );
-          this.data.corpus.o.getCorpusData()
-            .then(corpusData => {
-              console.log(corpusData);
-              this.renderGeneralCorpusInfo(corpusData);
-              this.renderTextInfoList(corpusData);
-              this.renderTextProportionsGraphic(corpusData);
-              this.renderFrequenciesGraphic(corpusData);
-              this.renderBoundsGraphic(corpusData);
-            });
+          this.data.corpus.o.getVisualizationData()
+            .then(
+              (data) => {
+                console.log(data);
+                this.renderGeneralCorpusInfo(data);
+                this.renderTextInfoList(data);
+                this.renderTextProportionsGraphic(data);
+                this.renderFrequenciesGraphic(data);
+                this.renderBoundsGraphic(data);
+              }
+            );
+          // this.data.corpus.o.getCorpusData()
+          //   .then(corpusData => {
+          //     console.log(corpusData);
+          //     this.renderGeneralCorpusInfo(corpusData);
+          //     this.renderTextInfoList(corpusData);
+          //     this.renderTextProportionsGraphic(corpusData);
+          //     this.renderFrequenciesGraphic(corpusData);
+          //     this.renderBoundsGraphic(corpusData);
+          //   });
           // TODO: Don't do this hgere
           cQiCorpus.updateDb();
           this.enableActionElements();
@@ -117,29 +117,29 @@ class CorpusAnalysisApp {
   }
 
   renderGeneralCorpusInfo(corpusData) {
-    document.querySelector('.corpus-num-tokens').innerHTML = corpusData.corpus.lexicon[0].counts.token;
-    document.querySelector('.corpus-num-s').innerHTML = corpusData.corpus.lexicon[0].counts.s;
-    document.querySelector('.corpus-num-unique-words').innerHTML = Object.entries(corpusData.corpus.lexicon[0].freqs.word).length;
-    document.querySelector('.corpus-num-unique-lemmas').innerHTML = Object.entries(corpusData.corpus.lexicon[0].freqs.lemma).length;
-    document.querySelector('.corpus-num-unique-pos').innerHTML = Object.entries(corpusData.corpus.lexicon[0].freqs.pos).length;
-    document.querySelector('.corpus-num-unique-simple-pos').innerHTML = Object.entries(corpusData.corpus.lexicon[0].freqs.simple_pos).length;
+    document.querySelector('.corpus-num-tokens').innerHTML = corpusData.corpus.counts.token;
+    document.querySelector('.corpus-num-s').innerHTML = corpusData.corpus.counts.s;
+    document.querySelector('.corpus-num-unique-words').innerHTML = Object.entries(corpusData.corpus.freqs.word).length;
+    document.querySelector('.corpus-num-unique-lemmas').innerHTML = Object.entries(corpusData.corpus.freqs.lemma).length;
+    document.querySelector('.corpus-num-unique-pos').innerHTML = Object.entries(corpusData.corpus.freqs.pos).length;
+    document.querySelector('.corpus-num-unique-simple-pos').innerHTML = Object.entries(corpusData.corpus.freqs.simple_pos).length;
   }
 
   renderTextInfoList(corpusData) {
     let corpusTextInfoListElement = document.querySelector('.corpus-text-info-list');
     let corpusTextInfoList = new CorpusTextInfoList(corpusTextInfoListElement);
-    let texts = corpusData.text.lexicon;
+    let texts = corpusData.s_attrs.text.lexicon;
     let textData = [];
     for (let i = 0; i < Object.entries(texts).length; i++) {
       let resource = {
-        title: corpusData.lookups.text[i].title,
-        publishing_year: corpusData.lookups.text[i].publishing_year,
-        num_tokens: corpusData.text.lexicon[i].counts.token,
-        num_sentences: corpusData.text.lexicon[i].counts.s,
-        num_unique_words: Object.entries(corpusData.text.lexicon[i].freqs.word).length,
-        num_unique_lemmas: Object.entries(corpusData.text.lexicon[i].freqs.lemma).length,
-        num_unique_pos: Object.entries(corpusData.text.lexicon[i].freqs.pos).length,
-        num_unique_simple_pos: Object.entries(corpusData.text.lexicon[i].freqs.simple_pos).length
+        title: corpusData.values.s_attrs.text[i].title,
+        publishing_year: corpusData.values.s_attrs.text[i].publishing_year,
+        num_tokens: corpusData.s_attrs.text.lexicon[i].counts.token,
+        num_sentences: corpusData.s_attrs.text.lexicon[i].counts.s,
+        num_unique_words: Object.entries(corpusData.s_attrs.text.lexicon[i].freqs.word).length,
+        num_unique_lemmas: Object.entries(corpusData.s_attrs.text.lexicon[i].freqs.lemma).length,
+        num_unique_pos: Object.entries(corpusData.s_attrs.text.lexicon[i].freqs.pos).length,
+        num_unique_simple_pos: Object.entries(corpusData.s_attrs.text.lexicon[i].freqs.simple_pos).length
       };
   
       textData.push(resource);
@@ -148,33 +148,29 @@ class CorpusAnalysisApp {
     corpusTextInfoList.add(textData);
 
     let textCountChipElement = document.querySelector('.text-count-chip');
-    textCountChipElement.innerHTML = `Text count: ${Object.values(corpusData.text.lexicon).length}`;
+    textCountChipElement.innerHTML = `Text count: ${corpusData.corpus.counts.text}`;
   }
 
   renderTextProportionsGraphic(corpusData) {
     let textProportionsGraphicElement = document.querySelector('#text-proportions-graphic');
-    let texts = Object.entries(corpusData.text.lexicon);
+    let texts = Object.entries(corpusData.s_attrs.text.lexicon);
     let graphData = [
       {
         values: texts.map(text => text[1].counts.token),
-        labels: texts.map(text => `${corpusData.lookups.text[text[0]].title} (${corpusData.lookups.text[text[0]].publishing_year})`),
+        labels: texts.map(text => `${corpusData.values.s_attrs.text[text[0]].title} (${corpusData.values.s_attrs.text[text[0]].publishing_year})`),
         type: 'pie'
       }
     ];
-    let graphLayout = {
-      // height: 600,
-      // width: 900
-    };
     let config = {responsive: true};
 
-    Plotly.newPlot(textProportionsGraphicElement, graphData, graphLayout, config);
+    Plotly.newPlot(textProportionsGraphicElement, graphData, config);
   }
 
   renderFrequenciesGraphic(corpusData) {
     let frequenciesTokenCategoryDropdownElement = document.querySelector('[data-target="frequencies-token-category-dropdown"]');
     let frequenciesTokenCategoryDropdownListElement = document.querySelector("#frequencies-token-category-dropdown");
     let frequenciesGraphicElement = document.querySelector('#frequencies-graphic');
-    let texts = Object.entries(corpusData.text.lexicon);
+    let texts = Object.entries(corpusData.s_attrs.text.lexicon);
     
     
     frequenciesTokenCategoryDropdownListElement.addEventListener('click', (event) => {
@@ -196,13 +192,13 @@ class CorpusAnalysisApp {
 
   createFrequenciesGraphData(category, texts, corpusData) {
     let graphData = [];
-    let sortedData = Object.entries(corpusData.corpus.lexicon[0].freqs[category]).sort((a, b) => b[1] - a[1]).slice(0, 5);
+    let sortedData = Object.entries(corpusData.corpus.freqs[category]).sort((a, b) => b[1] - a[1]).slice(0, 5);
   
     for (let item of sortedData) {
       let data = {
-        x: texts.map(text => `${corpusData.lookups.text[text[0]].title} (${corpusData.lookups.text[text[0]].publishing_year})`),
+        x: texts.map(text => `${corpusData.values.s_attrs.text[text[0]].title} (${corpusData.values.s_attrs.text[text[0]].publishing_year})`),
         y: texts.map(text => text[1].freqs[category][item[0]]),
-        name: corpusData.lookups[category][item[0]],
+        name: corpusData.values.p_attrs[category][item[0]],
         type: 'bar'
       };
       graphData.push(data);
@@ -215,22 +211,20 @@ class CorpusAnalysisApp {
       let boundsGraphicElement = document.querySelector('#bounds-graphic');
 
       let graphData = [];
-      let texts = Object.entries(corpusData.text.lexicon);
+      let texts = Object.entries(corpusData.s_attrs.text.lexicon);
 
       graphData = [{
         type: 'bar',
         x: texts.map(text => text[1].bounds[1] - text[1].bounds[0]),
-        y: texts.map(text => corpusData.lookups.text[text[0]].title),
+        y: texts.map(text => corpusData.values.s_attrs.text[text[0]].title),
         base: texts.map(text => text[1].bounds[0]),
-        text: texts.map(text => `${corpusData.lookups.text[text[0]].title} (${corpusData.lookups.text[text[0]].publishing_year})`),
+        text: texts.map(text => `${corpusData.values.s_attrs.text[text[0]].title} (${corpusData.values.s_attrs.text[text[0]].publishing_year})`),
         orientation: 'h',
         hovertemplate: '%{base} - %{x} <br>%{y}',
         showlegend: false
       }];
 
       let graphLayout = {
-        // height: 600,
-        // width: 2000,
         barmode: 'stack',
         type: 'bar',
         showgrid: false,

app/static/js/ResourceLists/CorpusTextInfoList.js

@@ -103,6 +103,7 @@ class CorpusTextInfoList extends ResourceList {
       if (sortElement !== clickedSortElement) {
         sortElement.classList.remove('asc', 'desc');
         sortElement.style.color = 'black';
+        sortElement.innerHTML = 'arrow_drop_down';
       };
     });
     clickedSortElement.style.color = '#aa9cc9';