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results_for_readme_tables.py
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results_for_readme_tables.py
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import json
import os
import plotly.graph_objects as go
import numpy as np
from plotly.subplots import make_subplots
import plotly.io as pio
pio.kaleido.scope.mathjax = None
model2name = {
'bert_large': 'BERT-Large',
'pubmed_bert': 'PubMedBERT',
'bart_large': 'BART-Large',
'flan_t5_large': 'Flan-T5-Large',
'bloom_1b7': 'BLOOM-1b7',
'flan_t5_xl': 'Flan-T5-XL',
'bloom_3b': 'BLOOM-3b',
'llama_7b': 'LLaMA-7B',
'gpt3': 'GPT-3',
'chatgpt': 'GPT-3.5',
'gpt4': 'GPT-4',
'umls_flan_t5_large': '`Flan-T5-Large*`',
'umls_flan_t5_xl': '`Flan-T5-XL*`',
'schemaorg_flan_t5_large': '`Flan-T5-Large*`',
'schemaorg_flan_t5_xl': '`Flan-T5-XL*`',
'geonames_flan_t5_large': '`Flan-T5-Large*`',
'geonames_flan_t5_xl': '`Flan-T5-XL*`',
'wn18rr_flan_t5_large': '`Flan-T5-Large*`',
'wn18rr_flan_t5_xl': '`Flan-T5-XL*`',
}
llm_no = 13
dir2name = {
'wn18rr': 'WN18RR',
'geonames': 'GeoNames',
'nci': 'NCI',
'snomedct_us': 'SNOMEDCT_US',
'medcin': 'Medcin',
'umls': 'UMLS',
'schema': 'Schema.Org'
}
medical_dir2name = {
'nci': 'NCI',
'snomedct_us': 'SNOMEDCT',
'medcin': 'Medcin',
'umls': 'UMLS',
}
tasks = ['A', 'B']
task_templates_name = {
"A": [f'template-{str(index)}' for index in range(1, 9)],
"B": [f'-{str(index)}-' for index in range(0, 8)],
"C": [""]
}
def read_json(path: str):
"""
Reads the ``json`` file of the given ``input_path``.
:param input_path: Path to the json file
:return: A loaded json object.
"""
with open(path, encoding="utf-8") as f:
json_data = json.load(f)
return json_data
def make_string(score):
str_score = str(score)
return str_score.split(".")[0] + "." + str_score.split(".")[1][:3]
report_catalog = {}
for task in tasks:
report_catalog[task] = {}
root_task_dir = f"Task{task}/results/"
for dataset in dir2name.keys():
if dataset in os.listdir(root_task_dir):
report_catalog[task][dataset] = {}
# print(dir2name[dataset])
dataset_dir_path = os.path.join(root_task_dir, dataset)
for model_output_dir in os.listdir(dataset_dir_path):
model_output_dir_path = os.path.join(dataset_dir_path, model_output_dir)
if os.path.isdir(model_output_dir_path) and not '.ipynb_checkpoints' in model_output_dir_path:
prefix = f"report-{model_output_dir}"
results = []
for template in task_templates_name[task]:
finded = False
for file in os.listdir(model_output_dir_path):
if file.startswith(prefix) and template in file:
json_file = read_json(path=os.path.join(model_output_dir_path, file))
if task == 'A':
score = make_string(json_file['results']['MAP@1'] * 100)
results.append(score)
finded = True
elif task == 'B':
score = make_string(
json_file['results']['clf-report-dict']['macro avg']['f1-score'] * 100)
results.append(score)
finded = True
elif task == 'C':
score = make_string(
json_file['results']['clf-report']['macro avg']['f1-score'] * 100)
results.append(score)
finded = True
break
if not finded:
results.append("-")
report_catalog[task][dataset][model_output_dir] = results
task = 'A'
reports = report_catalog[task]
print(task)
for source, results in reports.items():
print("|", dir2name[source], end="|")
for llm in list(model2name.values()):
if llm == "`Flan-T5-XL*`":
print(llm, end="|")
break
else:
print(llm, end="<br>")
res_str = "|"
for index, template in enumerate(task_templates_name[task]):
for llm_model, llm_name in model2name.items():
if llm_name == "`Flan-T5-XL*`":
if llm_model in list(results.keys()):
print(results[llm_model][index], end="|")
break
else:
if llm_model in list(results.keys()):
print(results[llm_model][index], end="<br>")
else:
if llm_name == 'PubMedBERT':
print("-", end="<br>")
print()
print()
task = 'B'
reports = report_catalog[task]
print(task)
for source, results in reports.items():
print("|", dir2name[source], end="|")
for llm in list(model2name.values()):
if llm == "`Flan-T5-XL*`":
print(llm, end="|")
break
else:
print(llm, end="<br>")
res_str = "|"
for index, template in enumerate(task_templates_name[task]):
for llm_model, llm_name in model2name.items():
if llm_name == "`Flan-T5-XL*`":
if llm_model in list(results.keys()):
print(results[llm_model][index], end="|")
break
else:
if llm_model in list(results.keys()):
print(results[llm_model][index], end="<br>")
else:
if llm_name == 'PubMedBERT':
print("-", end="<br>")
print()
print()
task = 'B'
reports = report_catalog[task]
print(task)
for source, results in reports.items():
print(dir2name[source])
for llm_model, llm_name in model2name.items():
if llm_name.startswith("`Flan-T5-"):
if llm_model in list(results.keys()):
print(" & ", llm_name, " & ", " & ".join([s[:-1] for s in results[llm_model]]), "\\\\")
else:
if llm_model in list(results.keys()):
print(" & ", llm_name, " & ", " & ".join([s[:-1] for s in results[llm_model]]), "\\\\")
else:
print(" & ", llm_name, " & ", " & ".join([str("-") for _ in range(8)]), "\\\\")
print()
print()
task = 'A'
reports = report_catalog[task]
print(task)
for source, results in reports.items():
print(dir2name[source])
for llm_model, llm_name in model2name.items():
if llm_name.startswith("`Flan-T5-"):
if llm_model in list(results.keys()):
print(" & \\textit{", llm_name[1:][:-2], "$^*$} & ",
" & ".join([s[:-1] if len(s) > 1 else s for s in results[llm_model]]), "\\\\")
# break
else:
if llm_model in list(results.keys()):
print(" & ", llm_name, " & ",
" & ".join([s[:-1] if len(s) > 1 else s for s in results[llm_model]]), "\\\\")
else:
print(" & ", llm_name, " & ", " & ".join([str("-") for _ in range(8)]), "\\\\")
print()
print()