file for loading data with HF datasets load_dataset() module

weather_forecast_discussion/dataset.py

@@ -0,0 +1,102 @@
+import os
+import pandas as pd
+import numpy as np
+import datasets
+
+class CSVhrrrDataset(datasets.GeneratorBasedBuilder):
+    """
+    A custom dataset to load CSV and corresponding hrrr files.
+    The CSV files are loaded using pandas and the hrrr files using numpy.
+    """
+
+    # Define dataset name and version
+    VERSION = datasets.Version("1.0.0")
+
+    def _info(self):
+        # Dataset description and features
+        return datasets.DatasetInfo(
+            description="Dataset containing CSV and corresponding hrrr files.",
+            features=datasets.Features({
+                "csv_data": datasets.Value("string"),  # CSV content as a string or specific columns
+                "hrrr_file_path": datasets.Value("string"),  # Assuming hrrr files contain float32 data
+                "filename": datasets.Value("string"),  # Filename of the CSV file
+            }),
+            supervised_keys=None,
+            homepage="https://huggingface.co/datasets/nasa-impact/WINDSET/tree/main/weather_forecast_discussion",
+            license="MIT",
+        )
+
+    def _split_generators(self, dl_manager):
+        """
+        Define dataset splits for this dataset (train, validation, test).
+        In this case, we just load all the files into a single split.
+        """
+        # Get the directory paths
+        csv_dir = os.path.join(os.getcwd(), "weather_forecast_discussion/csv_reports")
+        hrrr_dir = os.path.join(os.getcwd(), "weather_forecast_discussion/hrrr")
+
+        # Check that both directories exist
+        if not os.path.isdir(csv_dir):
+            raise FileNotFoundError(f"CSV directory {csv_dir} not found!")
+        if not os.path.isdir(hrrr_dir):
+            raise FileNotFoundError(f"hrrr directory {hrrr_dir} not found!")
+
+        # List CSV and hrrr files
+        csv_files = [f for f in os.listdir(csv_dir) if f.endswith('.csv')]
+        hrrr_files = [f for f in os.listdir(hrrr_dir) if f.endswith('.grib2')]
+
+        # Ensure CSV and hrrr files are paired correctly by date
+        file_pairs = []
+        for csv_file in csv_files:
+            # Extract the date from the CSV file (assuming format is 'date.csv')
+            date_str = os.path.splitext(csv_file)[0]
+            
+            # Search for matching hrrr files in the hrrr directory
+            matching_hrrr_files = [hrrr for hrrr in hrrr_files if f"hrrr.{date_str}." in hrrr]
+
+            if len(matching_hrrr_files) == 1:  # Ensure exactly one match
+                file_pairs.append((csv_file, matching_hrrr_files[0]))
+            elif len(matching_hrrr_files) == 0:
+                print(f"Warning: No matching hrrr file found for CSV file: {csv_file}")
+            else:
+                print(f"Warning: Multiple matching hrrr files found for CSV file: {csv_file}. Using the first match.")
+                file_pairs.append((csv_file, matching_hrrr_files[0]))  # Use the first match if multiple are found
+
+        # If no valid file pairs were found, raise an error
+        if not file_pairs:
+            raise ValueError("No valid CSV-hrrr file pairs found. Check the directory structure and file names.")
+
+        # Create a split generator
+        return [
+            datasets.SplitGenerator(
+                name=datasets.Split.TRAIN,
+                gen_kwargs={
+                    "file_pairs": file_pairs,
+                    "csv_dir": csv_dir,
+                    "hrrr_dir": hrrr_dir,
+                }
+            )
+        ]
+
+    def _generate_examples(self, file_pairs, csv_dir, hrrr_dir):
+        """
+        Yield examples from the CSV and hrrr files.
+        Each example contains data from a CSV file and its corresponding hrrr file.
+        """
+        example_id = 0
+
+        for csv_file, hrrr_file in file_pairs:
+            # Load CSV file using pandas
+            csv_file_path = os.path.join(csv_dir, csv_file)
+            csv_data = pd.read_csv(csv_file_path)
+
+            # Load corresponding hrrr file using numpy
+            hrrr_file_path = os.path.join(hrrr_dir, hrrr_file)
+
+            # Yield example with both CSV and hrrr data
+            yield example_id, {
+                "csv_data": csv_data["discussion"].to_string(),  # Store content under discussion only
+                "hrrr_file_path": hrrr_file_path,  
+                "filename": csv_file, 
+            }
+            example_id += 1