New Feature Enhancement for Character Class

gender_analysis/analysis/character_pos.py

@@ -0,0 +1,89 @@
+from more_itertools import windowed
+import nltk
+
+from gender_analysis.common import ADJ_TAGS, ADV_TAGS, PROPER_NOUN_TAGS, VERB_TAGS
+from gender_analysis import common
+pos_dict = {'adj': ADJ_TAGS, 'adv': ADV_TAGS,
+            'proper_noun': PROPER_NOUN_TAGS, "verb": VERB_TAGS}
+
+# I've migrated functions from gender_pos to here and modify them for character, but maybe should
+# add new functions in gender_pos instead
+
+# first pass on character adj based on gender pos
+def find_char_pos(pos_to_find, char_to_find, word_window=5):
+    # pylint: disable=too-many-locals
+    """
+    Takes in a document, a valid part-of-speech, and a Gender to look for,
+    and returns a dictionary of words that appear within a window of 5 words around each identifier.
+
+    :param document: Document
+    :param pos_to_find: A valid part of speech tag from pos_dict: ['adj','adv','proper_noun','verb']
+    :param word_window: number of words to search for in either direction of a gender instance
+    :param char_to_find: Character
+    :return: dict of words that appear around pronouns mapped to the number of occurrences
+
+    >>> from gender_analysis import document
+    >>> from pathlib import Path
+    >>> from gender_analysis import common
+    >>> document_metadata = {'author': 'Hawthorne, Nathaniel', 'title': 'Scarlet Letter', 'date': \
+    '1966', 'filename': 'test_text_7.txt', 'filepath': Path(common.TEST_DATA_PATH, \
+    'document_test_files', 'test_text_7.txt')}
+    >>> scarlett = document.Document(document_metadata)
+    >>> find_gender_pos(scarlett, 'adj', common.MALE, genders_to_exclude=[common.FEMALE])
+    {'handsome': 3, 'sad': 1}
+
+    """
+    output = {}
+    text = char_to_find.document.get_tokenized_text()
+
+    if pos_to_find in pos_dict.keys():
+        pos_tags = pos_dict[pos_to_find]
+    else:
+        return "Invalid part of speech"
+    # rewrite based on character class
+    identifiers_to_find = [char_to_find.name] + [char_to_find.nicknames] # identifiers: names and nicknames
+
+    for words in windowed(text, 2 * word_window + 1):
+        if not words[word_window].lower() in identifiers_to_find:
+            continue
+        if bool(set(words)):
+            continue
+
+        words = list(words)
+        for index, word in enumerate(words):
+            words[index] = word.lower()
+
+        tags = nltk.pos_tag(words)
+        for tag_index, _ in enumerate(tags):
+            if tags[tag_index][1] in pos_tags:
+                word = words[tag_index]
+                if word in output.keys():
+                    output[word] += 1
+                else:
+                    output[word] = 1
+
+    return output
+
+
+def find_char_adj(char_to_find, word_window=5):
+    # pylint: disable=too-many-locals
+    """
+    Takes in a document and a Character to look for, and returns a dictionary of adjectives that
+    appear within a window of 5 words around each identifier
+    :param char_to_find: Character
+    :param word_window: number of words to search for in either direction of a gender instance
+    :return: dict of adjectives that appear around pronouns mapped to the number of occurrences
+
+    >>> from gender_analysis import document
+    >>> from pathlib import Path
+    >>> from gender_analysis import common
+    >>> document_metadata = {'author': 'Hawthorne, Nathaniel', 'title': 'Scarlet Letter', 'date': \
+    '1966', 'filename': 'test_text_7.txt', 'filepath': Path(common.TEST_DATA_PATH, \
+    'document_test_files', 'test_text_7.txt')}
+    >>> scarlett = document.Document(document_metadata)
+    >>> find_gender_adj(scarlett, common.MALE, genders_to_exclude=[common.FEMALE])
+    {'handsome': 3, 'sad': 1}
+
+    """
+
+    return find_char_pos('adj', char_to_find, word_window)