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file for loading data with HF datasets load_dataset() module
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import os
import datasets
class LongTermPrecipitationDataset(datasets.GeneratorBasedBuilder):
VERSION = datasets.Version("1.0.0")
def _info(self):
"""
Defines the dataset metadata and feature structure.
"""
return datasets.DatasetInfo(
description="Dataset containing .nc files per year for variables.",
features=datasets.Features({
"file_path": datasets.Value("string"), # Store file paths
"year": datasets.Value("string"), # Track year
"subfolder": datasets.Value("string") # Track subfolder (sf1, sf2)
}),
supervised_keys=None, # Update if supervised task is defined
homepage="https://huggingface.co/datasets/nasa-impact/WINDSET/tree/main/long_term_precipitation_forecast",
license="MIT",
)
def _split_generators(self, dl_manager):
"""
Define the dataset splits for train, validation, and test.
"""
# Define the directory containing the dataset
data_dir = os.path.join(os.getcwd(), "long_term_precipitation_forecast")
# Get the directories for each split
train_dir = os.path.join(data_dir, "training_data")
validation_dir = os.path.join(data_dir, "validation_data")
test_dir = os.path.join(data_dir, "test_data")
return [
datasets.SplitGenerator(
name=datasets.Split.TRAIN,
gen_kwargs={"split_dir": train_dir},
),
datasets.SplitGenerator(
name=datasets.Split.VALIDATION,
gen_kwargs={"split_dir": validation_dir},
),
datasets.SplitGenerator(
name=datasets.Split.TEST,
gen_kwargs={"split_dir": test_dir},
),
]
def _get_subfolders(self, base_dir):
"""
Get all subfolders from the base directory.
"""
return [os.path.join(base_dir, subfolder) for subfolder in os.listdir(base_dir) if os.path.isdir(os.path.join(base_dir, subfolder))]
def _get_year_folders(self, subfolder_dir):
"""
Get all year folders inside a subfolder.
"""
return [os.path.join(subfolder_dir, year_folder) for year_folder in os.listdir(subfolder_dir) if os.path.isdir(os.path.join(subfolder_dir, year_folder))]
def _generate_data_from_files(self, data_dir):
"""
Generate file paths for each subfolder, year, and daily file.
"""
example_id = 0
# Loop through subfolders
for subfolder in os.listdir(data_dir):
subfolder_path = os.path.join(data_dir, subfolder)
if os.path.isdir(subfolder_path):
# Loop through year folders inside the subfolder
for year_folder in os.listdir(subfolder_path):
year_folder_path = os.path.join(subfolder_path, year_folder)
if os.path.isdir(year_folder_path):
# Loop through daily files inside the year folder
for daily_file in os.listdir(year_folder_path):
daily_file_path = os.path.join(year_folder_path, daily_file)
if daily_file.endswith(".nc"): # Only select NetCDF files
# Yield file information for each data point
yield example_id, {
"file_path": daily_file_path,
"year": year_folder,
"subfolder": subfolder,
}
example_id += 1
else:
raise FileNotFoundError(f"{daily_file_path} not found")
def _generate_examples(self, split_dir):
"""
Generates examples for the dataset from the split directory.
"""
# Call the data generator to get the file paths
for example_id, example in self._generate_data_from_files(split_dir):
yield example_id, example