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Merge pull request #29 from harmonydata/add_topic_strengths
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Add topic strengths
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@woodthom2
woodthom2 committed Mar 14, 2024
2 parents 74fbba6 + c43b24a commit 534ccde
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Showing 5 changed files with 239 additions and 8 deletions.
2 changes: 1 addition & 1 deletion CITATION.cff
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Expand Up @@ -17,7 +17,7 @@ authors:
given-names: "George"
orcid: "https://orcid.org/0000-0002-8198-5790"
title: "Harmony"
version: 0.5.1
version: 0.5.2
doi: DOI 10.17605/OSF.IO/BCT6K
date-released: 2023-07-22
url: "https://harmonydata.ac.uk"
2 changes: 1 addition & 1 deletion src/harmony/__init__.py
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Expand Up @@ -25,7 +25,7 @@
'''

__version__ = "0.5.1"
__version__ = "0.5.2"

# TODO: make these configurable at package level
import os
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15 changes: 9 additions & 6 deletions src/harmony/matching/matcher.py
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Expand Up @@ -196,15 +196,18 @@ def match_instruments_with_function(
similarities_mhc = cosine_similarity(vectors_pos, mhc_embeddings)

ctrs = {}
for idx, a in enumerate(np.argmax(similarities_mhc, axis=1)):
top_mhc_match_ids = np.argmax(similarities_mhc, axis=1)
for idx, mhc_item_idx in enumerate(top_mhc_match_ids):
question_text = mhc_questions[mhc_item_idx].question_text
if question_text is None or len(question_text) < 3: # Ignore empty entries in MHC questionnaires
continue
if all_questions[idx].instrument_id not in ctrs:
ctrs[all_questions[idx].instrument_id] = Counter()
for topic in mhc_all_metadatas[a]["topics"]:
for topic in mhc_all_metadatas[mhc_item_idx]["topics"]:
ctrs[all_questions[idx].instrument_id][topic] += 1
qt = mhc_questions[a].question_text
if qt is None or len(qt) < 3: # Ignore empty entries in MHC questionnaires
continue
all_questions[idx].nearest_match_from_mhc_auto = mhc_questions[a].dict()
all_questions[idx].nearest_match_from_mhc_auto = mhc_questions[mhc_item_idx].dict()
strength_of_match = similarities_mhc[idx, mhc_item_idx]
all_questions[idx].topics_strengths = {topic: float(strength_of_match)}

instrument_to_category = {}
for instrument_id, counts in ctrs.items():
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1 change: 1 addition & 0 deletions src/harmony/schemas/requests/text.py
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Expand Up @@ -64,6 +64,7 @@ class Question(BaseModel):
instrument_id: str = Field(None, description="Unique identifier for the instrument (UUID-4)")
instrument_name: str = Field(None, description="Human readable name for the instrument")
topics_auto: list = Field(None, description="Automated list of topics identified by model")
topics_strengths: dict = Field(None, description="Automated list of topics identified by model with strength of topic")
nearest_match_from_mhc_auto: dict = Field(None, description="Automatically identified nearest MHC match")

class Config:
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227 changes: 227 additions & 0 deletions tests/test_match_mhc.py
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@@ -0,0 +1,227 @@
'''
MIT License
Copyright (c) 2023 Ulster University (https://www.ulster.ac.uk).
Project: Harmony (https://harmonydata.ac.uk)
Maintainer: Thomas Wood (https://fastdatascience.com)
Permission is hereby granted, free of charge, to any person obtaining a copy
of this software and associated documentation files (the "Software"), to deal
in the Software without restriction, including without limitation the rights
to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
copies of the Software, and to permit persons to whom the Software is
furnished to do so, subject to the following conditions:
The above copyright notice and this permission notice shall be included in all
copies or substantial portions of the Software.
THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
SOFTWARE.
'''

import unittest

import numpy as np

from harmony import match_instruments
from harmony.schemas.requests.text import Instrument, Question

questions_en = [Question(question_text="Feeling nervous, anxious, or on edge"),
Question(question_text="Not being able to stop or control worrying")]
instrument_en = Instrument(questions=questions_en)

mhc_metadata = [{'topics': ['alcohol use']},
{'topics': ['mental illness',
'anxiety',
'depression',
'self-harm and suicide']}
]

mhc_questions = [
Question(
question_text="Have you ever felt annoyed by criticism of your drinking?"),
Question(
question_text="Have you recently")
]

mhc_embeddings = np.array([[0.31698248, 0.12777875, 0.04758111, 0.42555183, 0.39878827,
-0.08955862, 0.5192866, 0.30124685, 0.21197015, 0.00708418,
-0.2850551, 0.18860379, -0.1555653, 0.00297953, 0.00462213,
-0.12949726, -0.08035432, -0.26375496, 0.12412424, 0.10837679,
-0.5037259, -0.09385646, 0.3371012, 0.3913466, 0.20307001,
0.24039863, 0.1305629, -0.2821185, -0.5513103, 0.06190247,
-0.13765384, -0.19164908, 0.45563582, -0.14968751, -0.08522708,
-0.04938481, -0.05294258, 0.38618585, -0.15730491, 0.08312214,
0.47667167, -0.3356474, -0.17182834, 0.26071277, -0.17881565,
0.08396178, -0.00323634, 0.2311756, -0.12618396, -0.10611524,
0.43096817, 0.17048849, 0.21215717, -0.25437835, -0.13393787,
-0.53877395, -0.07101384, 0.01789423, -0.3065841, 0.29606512,
-0.08472076, -0.17864832, -0.02092675, 0.27630028, -0.01672868,
0.00911544, 0.05188185, 0.24766283, -0.34470555, 0.36253104,
0.4684341, -0.16652438, 0.51165503, -0.13537268, -0.16006592,
-0.03522887, -0.0707399, 0.33693355, -0.19236559, 0.23861784,
0.1801952, 0.6937744, -0.12062132, -0.06564505, -0.22319959,
0.05320398, 0.04514768, 0.22523028, 0.14264914, -0.16481638,
-0.17351519, -0.04900846, 0.3545729, 0.15396394, 0.04017958,
0.18319216, -0.27823684, -0.3195731, -0.29258227, -0.11263382,
0.15431456, 0.4166155, -0.1792731, -0.10493241, 0.48761463,
0.08412156, -0.3284959, 0.2170649, -0.04346004, -0.20890392,
-0.29599097, -0.2947356, 0.12064935, -0.42329106, -0.15400986,
0.44402364, -0.36696455, -0.05456911, 0.3541068, 0.11427474,
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-0.10884392, -0.25267506, -0.2787788, -0.4845803, -0.13096423,
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0.25551945, -0.11909194, -0.3314092, 0.4510464, 0.19852763,
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[0.27486998, -0.2697892, 0.3188312, -0.12536432, 0.01304267,
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0.00834405, 0.34989062, 0.15298776, -0.0019381, -0.08982801,
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0.04022982, 0.01385638, -0.00511172, 0.01945869, -0.32149813,
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-0.10276201, 0.34286246, -0.2315859, -0.05564657, -0.09513279,
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0.3976692, 0.23438324, -0.23447269, 0.3847343]
],
dtype=np.float32)


class TestMatchMhc(unittest.TestCase):

def test_single_instrument_simple(self):
all_questions, similarity_with_polarity, query_similarity, new_vectors_dict = match_instruments([instrument_en],
mhc_questions=mhc_questions,
mhc_embeddings=mhc_embeddings,
mhc_all_metadatas=mhc_metadata)
self.assertEqual(2, len(all_questions))

topics = all_questions[0].topics_strengths
top_topic = list(topics)[0]
self.assertEqual("alcohol use", top_topic)
self.assertLess(0.1, topics[top_topic])


if __name__ == '__main__':
unittest.main()

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