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#!/usr/bin/env python3
"""
Generate Chladni plate dataset and save to parquet files in chunks.
"""
import os
import numpy as np
import pyarrow as pa
import pyarrow.parquet as pq
from dataset import Chladni2DDataset
def generate_dataset_split(
split_name="train", num_samples=1000, chunk_size=100, output_dir="data"
):
"""Generate a dataset split and save as chunked parquet files."""
os.makedirs(output_dir, exist_ok=True)
dataset = Chladni2DDataset()
num_chunks = (num_samples + chunk_size - 1) // chunk_size # Ceiling division
print(f"Generating {num_samples} {split_name} samples in {num_chunks} chunks...")
dataset_iter = iter(dataset)
chunk_data = None
for i in range(num_samples):
sample = next(dataset_iter)
if chunk_data is None:
# Initialize chunk data on first sample
chunk_data = {key: [] for key in sample.keys()}
# Add sample to current chunk
for key, value in sample.items():
chunk_data[key].append(value)
# Save chunk when full or at end
if (i + 1) % chunk_size == 0 or i == num_samples - 1:
chunk_idx = i // chunk_size
# Convert numpy arrays to lists for PyArrow compatibility
table_data = {}
for key, values in chunk_data.items():
if hasattr(values[0], 'tolist'):
# Handle numpy arrays
table_data[key] = [arr.tolist() for arr in values]
else:
# Handle scalars and other types
table_data[key] = values
# Convert to PyArrow table
table = pa.table(table_data)
# Save chunk
filename = f"{split_name}-{chunk_idx:05d}-of-{num_chunks:05d}.parquet"
filepath = os.path.join(output_dir, filename)
pq.write_table(table, filepath)
print(f"Saved chunk {chunk_idx + 1}/{num_chunks}: {filepath}")
# Reset for next chunk
chunk_data = {key: [] for key in sample.keys()}
print(f"Generated {num_samples} {split_name} samples")
return num_samples
if __name__ == "__main__":
np.random.seed(42)
# Generate train split
generate_dataset_split("train", num_samples=10000, chunk_size=1000)
# Generate test split
generate_dataset_split("test", num_samples=2000, chunk_size=1000) |