def __init__(
self,
result: types.Result,
*,
search_run: core.SearchRun,
display_mode="community",
animate_emoji=AnimateEmoji.default,
show_emoji=ShowEmoji.default,
dict_source=None,
):
self._result = result
self._search_run = search_run
self._relabeller = {
"english": read_labels().english,
"linguistic": read_labels().linguistic_long,
"source_language": read_labels().source_language,
}.get(display_mode, DisplayMode.default)
self._animate_emoji = animate_emoji
self._show_emoji = show_emoji
self.wordform = result.wordform
self.lemma_wordform = result.lemma_wordform
self.is_lemma = result.is_lemma
self.source_language_match = result.source_language_match
self.dict_source = dict_source
if settings.MORPHODICT_TAG_STYLE == "Plus":
(
self.linguistic_breakdown_head,
_,
self.linguistic_breakdown_tail,
) = result.wordform.analysis or [[], None, []]
elif settings.MORPHODICT_TAG_STYLE == "Bracket":
# Arapaho has some head tags that the Plus-style FSTs put at the
# tail. For now, move them; later on elaboration could be a
# language-specific function.
head, _, tail = result.wordform.analysis or [[], None, []]
new_head = []
new_tail_prefix = []
for i, tag in enumerate(head):
if tag.startswith("["):
new_tail_prefix.append(tag)
else:
new_head.append(tag)
self.linguistic_breakdown_head = new_head
self.linguistic_breakdown_tail = new_tail_prefix + list(tail)
else:
raise Exception(f"Unknown {settings.MORPHODICT_TAG_STYLE=}")
self.lexical_info = get_lexical_info(result.wordform.analysis,
animate_emoji, self._show_emoji,
self.dict_source)
if rich_analysis := result.wordform.analysis:
self.morphemes = rich_analysis.generate_with_morphemes(
result.wordform.text)
def relabel_linguistic_long(pos: str):
"""
Should take in a class and return the plain english labelling for it
So if I pass in "VTA-1", I should get back:
transitive animate verb – class 1: regular
"""
return read_labels().linguistic_long.get(pos)
def relabel_linguistic_short(pos: str):
"""
Should take in a class and return the plain english labelling for it
So if I pass in "VTA-1", I should get back:
VTA-1
"""
return read_labels().linguistic_short.get(pos)
def relabel_source(pos: str):
"""
Should take in a class and return the plain english labelling for it
So if I pass in "VTA-1", I should get back:
tâpiskôc: wîcihêw
"""
return read_labels().source_language.get(pos)
def relabel_plain_english(pos: str):
"""
Should take in a class and return the plain english labelling for it
So if I pass in "VTA-1", I should get back:
like: wîcihêw
"""
return read_labels().english.get(pos)
def get_emoji_for_cree_wordclass(
word_class: Optional[str],
animate_emoji: str = AnimateEmoji.default) -> Optional[str]:
"""
Attempts to get an emoji description of the full wordclass.
e.g., "👤👵🏽" for "nôhkom"
"""
if word_class is None:
return None
def to_fst_output_style(value):
if value[0] == "N":
return list(value.upper())
elif value[0] == "V":
return ["V", value[1:].upper()]
else:
return [value.title()]
tags = to_fst_output_style(word_class)
original = read_labels().emoji.get_longest(tags)
ret = original
if original:
ret = use_preferred_animate_emoji(original, animate_emoji)
return ret
def label_setting_to_relabeller(label_setting: str):
labels = read_labels()
return {
"english": labels.english,
"linguistic": labels.linguistic_short,
"source_language": labels.source_language,
}.get(label_setting, labels.english)
def serialize_wordform(wordform: Wordform, animate_emoji: str,
dict_source: list) -> SerializedWordform:
"""
Intended to be passed in a JSON API or into templates.
:return: json parsable result
"""
result = model_to_dict(wordform)
result["definitions"] = serialize_definitions(wordform.definitions.all(),
dict_source=dict_source)
result["lemma_url"] = wordform.get_absolute_url()
if wordform.linguist_info:
if inflectional_category := wordform.linguist_info.get(
"inflectional_category", None):
result.update({
"inflectional_category_plain_english":
read_labels().english.get(inflectional_category),
"inflectional_category_linguistic":
read_labels().linguistic_long.get(inflectional_category),
})
if wordclass := wordform.linguist_info.get("wordclass"):
result["wordclass_emoji"] = get_emoji_for_cree_wordclass(
wordclass, animate_emoji)
def __init__(
self,
result: types.Result,
*,
search_run: core.SearchRun,
display_mode="community",
animate_emoji=AnimateEmoji.default,
dict_source=None,
):
self._result = result
self._search_run = search_run
self._relabeller = {
"community": read_labels().english,
"linguistic": read_labels().linguistic_long,
}.get(display_mode, DisplayMode.default)
self._animate_emoji = animate_emoji
self.wordform = result.wordform
self.lemma_wordform = result.lemma_wordform
self.is_lemma = result.is_lemma
self.source_language_match = result.source_language_match
self.dict_source = dict_source
if settings.MORPHODICT_TAG_STYLE == "Plus":
(
self.linguistic_breakdown_head,
_,
self.linguistic_breakdown_tail,
) = result.wordform.analysis or [[], None, []]
elif settings.MORPHODICT_TAG_STYLE == "Bracket":
# Arapaho has some head tags that the Plus-style FSTs put at the
# tail. For now, move them; later on elaboration could be a
# language-specific function.
head, _, tail = result.wordform.analysis or [[], None, []]
new_head = []
new_tail_prefix = []
for i, tag in enumerate(head):
if tag.startswith("["):
new_tail_prefix.append(tag)
else:
new_head.append(tag)
self.linguistic_breakdown_head = new_head
self.linguistic_breakdown_tail = new_tail_prefix + list(tail)
else:
raise Exception(f"Unknown {settings.MORPHODICT_TAG_STYLE=}")
self.lexical_info = get_lexical_info(result.wordform.analysis,
animate_emoji, self.dict_source)
self.preverbs = [
lexical_entry["entry"] for lexical_entry in self.lexical_info
if lexical_entry["type"] == "Preverb"
]
self.reduplication = [
lexical_entry["entry"] for lexical_entry in self.lexical_info
if lexical_entry["type"] == "Reduplication"
]
self.friendly_linguistic_breakdown_head = replace_user_friendly_tags(
to_list_of_fst_tags(self.linguistic_breakdown_head))
self.friendly_linguistic_breakdown_tail = replace_user_friendly_tags(
to_list_of_fst_tags(self.linguistic_breakdown_tail))
def get_lexical_info(result_analysis: RichAnalysis, animate_emoji: str,
dict_source: list) -> List[Dict]:
if not result_analysis:
return []
result_analysis_tags = result_analysis.prefix_tags
first_letters = extract_first_letters(result_analysis)
lexical_info: List[Dict] = []
for (i, tag) in enumerate(result_analysis_tags):
preverb_result: Optional[Preverb] = None
reduplication_string: Optional[str] = None
_type: Optional[LexicalEntryType] = None
entry: Optional[_ReduplicationResult | SerializedWordform
| _InitialChangeResult] = None
if tag in ["RdplW+", "RdplS+"]:
reduplication_string = generate_reduplication_string(
tag, first_letters[i + 1])
elif tag == "IC+":
change_types = get_initial_change_types()
_type = "Initial Change"
entry = _InitialChangeResult(text=" ",
definitions=change_types).serialize()
elif tag.startswith("PV/"):
# use altlabel.tsv to figure out the preverb
# ling_short looks like: "Preverb: âpihci-"
ling_short = read_labels().linguistic_short.get(
cast(FSTTag, tag.rstrip("+")))
if ling_short:
# convert to "âpihci" by dropping prefix and last character
normative_preverb_text = ling_short[len("Preverb: "):]
preverb_results = Wordform.objects.filter(
text=normative_preverb_text, raw_analysis__isnull=True)
# find the one that looks the most similar
if preverb_results:
preverb_result = min(
preverb_results,
key=lambda pr: get_modified_distance(
normative_preverb_text,
pr.text.strip("-"),
),
)
else:
# Can't find a match for the preverb in the database.
# This happens when searching against the test database for
# ê-kî-nitawi-kâh-kîmôci-kotiskâwêyâhk, as the test database
# lacks lacks ê and kî.
preverb_result = Wordform(text=normative_preverb_text,
is_lemma=True)
if reduplication_string is not None:
entry = _ReduplicationResult(
text=reduplication_string,
definitions=[{
"text":
"Strong reduplication: intermittent, repeatedly, iteratively; again and again; here and there"
if tag == "RdplS+" else
"Weak Reduplication: ongoing, continuing"
}],
).serialize()
_type = "Reduplication"
if preverb_result is not None:
entry = serialize_wordform(preverb_result, animate_emoji,
dict_source)
_type = "Preverb"
if entry and _type:
result = _LexicalEntry(entry=entry, type=_type, original_tag=tag)
lexical_info.append(serialize_lexical_entry(result))
return lexical_info
def replace_user_friendly_tags(fst_tags: List[FSTTag]) -> List[Label]:
"""replace fst-tags to cute ones"""
return read_labels().english.get_full_relabelling(fst_tags)