Merge pull request #23 from navigating-stories/refactor

creates working tagging widget to generate data table to be used down…

orangecontrib/storynavigation/modules/constants.py

@@ -1,36 +1,121 @@
+import sys
+
+if sys.version_info < (3, 9):
+    # importlib.resources either doesn't exist or lacks the files()
+    # function, so use the PyPI version:
+    import importlib_resources
+else:
+    import importlib.resources as importlib_resources
+
 # metrics for measuring importance of characters or actors in the story
 AGENT_PROMINENCE_METRICS = ['Subject frequency', 'Subject frequency (normalized)']
 SFREQ_METRIC = 'Subject frequency'
 SFREQ_NORM_METRIC = 'Subject frequency (normalized)'
+
 # list of punctuation characters
 PUNC = '''!()-[]{};:'"\,<>./?@#$%^&*_~0123456789'''
+
 # name of storynavigator package directory
 MAIN_PACKAGE = "storynavigation"
 # directory name for resource files for usage by storynavigator add-on
 RESOURCES_SUBPACKAGE = "resources"
+
+# Supported languages
+NL = 'NL'
+EN = 'EN'
+SUPPORTED_LANGUAGES = [EN, NL]
+
 # filename from which to retrieve a list of dutch stopwords
 NL_STOPWORDS_FILENAME = "dutchstopwords.txt"
 # filename from which to retrieve a list of dutch past tense verbs
 NL_PAST_TENSE_FILENAME = "past_tense_verbs_dutch.txt"
 # filename from which to retrieve a list of dutch present tense verbs
 NL_PRESENT_TENSE_FILENAME = "present_tense_verbs_dutch.txt"
 # filename from which to retrieve a list of dutch false positive verbs
-NL_FALSE_POSITIVE_VERB_FILENAME = "false_positive_verbs.txt"
+NL_FALSE_POSITIVE_VERB_FILENAME = "false_positive_verbs_dutch.txt"
 # filename from which to retrieve a list of dutch stopwords
 NL_PRONOUNS_FILENAME = "dutchpronouns.txt"
+
+# filename from which to retrieve a list of english stopwords
+EN_STOPWORDS_FILENAME = "englishstopwords.txt"
+# filename from which to retrieve a list of dutch past tense verbs
+EN_PAST_TENSE_FILENAME = "past_tense_verbs_english.txt"
+# filename from which to retrieve a list of dutch present tense verbs
+EN_PRESENT_TENSE_FILENAME = "present_tense_verbs_english.txt"
+# filename from which to retrieve a list of dutch false positive verbs
+EN_FALSE_POSITIVE_VERB_FILENAME = "false_positive_verbs_english.txt"
+# filename from which to retrieve a list of dutch stopwords
+EN_PRONOUNS_FILENAME = "englishpronouns.txt"
+
+
+# package paths
+PKG = importlib_resources.files(MAIN_PACKAGE)
+
+NL_STOPWORDS_FILE = (
+    PKG / RESOURCES_SUBPACKAGE / NL_STOPWORDS_FILENAME
+)
+
+NL_PRONOUNS_FILE = (
+    PKG / RESOURCES_SUBPACKAGE / NL_PRONOUNS_FILENAME
+)
+
+NL_PAST_TENSE_FILE = (
+    PKG / RESOURCES_SUBPACKAGE / NL_PAST_TENSE_FILENAME
+)
+
+NL_PRESENT_TENSE_FILE = (
+    PKG / RESOURCES_SUBPACKAGE / NL_PRESENT_TENSE_FILENAME
+)
+
+NL_FALSE_POSITIVE_VERB_FILE = (
+    PKG / RESOURCES_SUBPACKAGE / NL_FALSE_POSITIVE_VERB_FILENAME
+)
+
+EN_STOPWORDS_FILE = (
+    PKG / RESOURCES_SUBPACKAGE / EN_STOPWORDS_FILENAME
+)
+
+EN_PRONOUNS_FILE = (
+    PKG / RESOURCES_SUBPACKAGE / EN_PRONOUNS_FILENAME
+)
+
+
+EN_PAST_TENSE_FILE = (
+    PKG / RESOURCES_SUBPACKAGE / EN_PAST_TENSE_FILENAME
+)
+
+EN_PRESENT_TENSE_FILE = (
+    PKG / RESOURCES_SUBPACKAGE / EN_PRESENT_TENSE_FILENAME
+)
+
+EN_FALSE_POSITIVE_VERB_FILE = (
+    PKG / RESOURCES_SUBPACKAGE / EN_FALSE_POSITIVE_VERB_FILENAME
+)
+
 # currently selected agent prominence metric
 SELECTED_PROMINENCE_METRIC = 'Subject frequency'
+
 # column names for agency table
 FREQ_TABLE_HEADER = ['actor', 'raw_frequency']
 ACTION_FREQ_TABLE_HEADER = ['action', 'raw_frequency']
 ACTION_TENSEFREQ_TABLE_HEADER = ['tense', 'frequency']
 SUBFREQ_TABLE_HEADER = ['actor', 'subject_frequency']
 CUSTOMFREQ_TABLE_HEADER = ['category', 'frequency', 'category-level']
 AGENCY_TABLE_HEADER = ['actor', 'agency']
+
 # Halliday dimensions file
 HALLIDAY_FILENAME = "halliday_dimensions_{}.json"
+
 # dutch spacy model (small)
 NL_SPACY_MODEL = "nl_core_news_sm"
+# dutch spacy model (large)
+NL_SPACY_MODEL_LG = "nl_core_news_sm"
+
+# english spacy model (small)
+EN_SPACY_MODEL = "en_core_news_sm"
+# dutch spacy model (large)
+EN_SPACY_MODEL_LG = "en_core_news_lg"
+
 # colors for highlighting words in text
 SUBJECT_PRONOUN_HIGHLIGHT_COLOR = "#87CEFA"
 SUBJECT_NONPRONOUN_HIGHLIGHT_COLOR = "#ADD8E6"