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from pathlib import Path
from typing import Dict, List, Tuple
import datasets
try:
import pyreadr
except:
print("Install the `pyreadr` package to use.")
from seacrowd.utils import schemas
from seacrowd.utils.configs import SEACrowdConfig
from seacrowd.utils.constants import (TASK_TO_SCHEMA, Licenses, Tasks)
_DATASETNAME = "iatf"
_CITATION = """\
@misc{
iatf,
title={Inter-Agency Task Force for the Management of Emerging Infectious Diseases (IATF) COVID-19 Resolutions},
url={https://como-ph.github.io/post/creating-text-data-from-iatf-resolutions/},
author={Chris Mercado, John Robert Medina, Ernest Guevarra}
}
"""
_DESCRIPTION = """\
To assess possible impact of various COVID-19 prediction models on Philippine government response, text from various resolutions issued by
the Inter-agency Task Force for the Management of Emerging Infectious Diseases (IATF) has been collected using data mining approaches implemented in R.
"""
_HOMEPAGE = "https://github.com/como-ph/covidphtext/tree/master/data"
_LICENSE = Licenses.GPL_3_0.value
_SUPPORTED_TASKS = [Tasks.SELF_SUPERVISED_PRETRAINING]
_SEACROWD_SCHEMA_NAME = TASK_TO_SCHEMA[_SUPPORTED_TASKS[0]].lower()
_LANGUAGES = ["fil"]
_LOCAL = False
_SOURCE_VERSION = "1.0.0"
_SEACROWD_VERSION = "2024.06.20"
_URL_BASE = "https://github.com/como-ph/covidphtext/raw/master/data/"
_URLS = [
"iatfGuidelineOmnibus.rda",
"iatfResolution01.rda",
"iatfResolution02.rda",
"iatfResolution03.rda",
"iatfResolution04.rda",
"iatfResolution05.rda",
"iatfResolution06.rda",
"iatfResolution07.rda",
"iatfResolution08.rda",
"iatfResolution09.rda",
"iatfResolution10.rda",
"iatfResolution11.rda",
"iatfResolution12.rda",
"iatfResolution13.rda",
"iatfResolution14.rda",
"iatfResolution15.rda",
"iatfResolution16.rda",
"iatfResolution17.rda",
"iatfResolution18.rda",
"iatfResolution19.rda",
"iatfResolution20.rda",
"iatfResolution21.rda",
"iatfResolution22.rda",
"iatfResolution23.rda",
"iatfResolution24.rda",
"iatfResolution25.rda",
"iatfResolution26.rda",
"iatfResolution27.rda",
"iatfResolution28.rda",
"iatfResolution29.rda",
"iatfResolution30.rda",
"iatfResolution30A.rda",
"iatfResolution31.rda",
"iatfResolution32.rda",
"iatfResolution33.rda",
"iatfResolution34.rda",
"iatfResolution35.rda",
"iatfResolution36.rda",
"iatfResolution37.rda",
"iatfResolution38.rda",
"iatfResolution39.rda",
"iatfResolution40.rda",
"iatfResolution41.rda",
"iatfResolution42.rda",
"iatfResolution43.rda",
"iatfResolution44.rda",
"iatfResolution45.rda",
"iatfResolution46.rda",
"iatfResolution46A.rda",
"iatfResolution47.rda",
"iatfResolution48.rda",
"iatfResolution49.rda",
"iatfResolution50.rda",
"iatfResolution50A.rda",
"iatfResolution51.rda",
"iatfResolution52.rda",
"iatfResolution53.rda",
"iatfResolution54.rda",
"iatfResolution55.rda",
"iatfResolution55A.rda",
"iatfResolution56.rda",
"iatfResolution57.rda",
"iatfResolution58.rda",
"iatfResolution59.rda",
"iatfResolution60.rda",
"iatfResolution60A.rda",
]
class IATFDataset(datasets.GeneratorBasedBuilder):
"""Inter-agency Task Force for the Management of Emerging Infectious Diseases Dataset"""
BUILDER_CONFIGS = [
SEACrowdConfig(
name=f"{_DATASETNAME}_source",
version=datasets.Version(_SOURCE_VERSION),
description=f"{_DATASETNAME} source schema",
schema="source",
subset_id=f"{_DATASETNAME}",
),
SEACrowdConfig(
name=f"{_DATASETNAME}_seacrowd_{_SEACROWD_SCHEMA_NAME}",
version=datasets.Version(_SEACROWD_VERSION),
description=f"{_DATASETNAME} seacrowd schema",
schema=f"seacrowd_{_SEACROWD_SCHEMA_NAME}",
subset_id=f"{_DATASETNAME}",
),
]
DEFAULT_CONFIG_NAME = f"{_DATASETNAME}_source"
def _info(self) -> datasets.DatasetInfo:
if self.config.schema == "source":
features = datasets.Features(
{
"id": datasets.Value("string"),
"text": datasets.Value("string"),
}
)
elif self.config.schema == f"seacrowd_{_SEACROWD_SCHEMA_NAME}":
features = schemas.self_supervised_pretraining.features
else:
raise ValueError(f"Invalid config schema: {self.config.schema}")
return datasets.DatasetInfo(
description=_DESCRIPTION,
features=features,
homepage=_HOMEPAGE,
license=_LICENSE,
citation=_CITATION,
)
def _split_generators(self, dl_manager: datasets.DownloadManager) -> List[datasets.SplitGenerator]:
filepaths = [Path(dl_manager.download(_URL_BASE + url)) for url in _URLS]
return [
datasets.SplitGenerator(
name=datasets.Split.TRAIN,
gen_kwargs={"filepaths": filepaths},
),
]
def _generate_examples(self, filepaths: List[Path]) -> Tuple[int, Dict]:
counter = 0
for path in filepaths:
data = pyreadr.read_r(path)
text = " ".join([str(x) for x in data[list(data.keys())[0]]["text"].values])
if self.config.schema == "source":
yield (
counter,
{
"id": str(counter),
"text": text.strip(),
},
)
elif self.config.schema == f"seacrowd_{_SEACROWD_SCHEMA_NAME}":
yield (
counter,
{
"id": str(counter),
"text": text.strip(),
},
)
counter += 1
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