Avoid loading all timestamps into memory using DataChunkIterator

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This PR implements memory optimization for timestamp handling in SpikeGadgets .rec file conversion to avoid loading all timestamps into memory at once, which becomes problematic for long recordings.

Problem

For 17-hour recordings at 30kHz sampling rate, the current implementation loads all timestamps into memory using np.concatenate(), requiring approximately 14.7 GB of RAM just for timestamps:

# Current problematic code in RecFileDataChunkIterator
self.timestamps = np.concatenate(
    [neo_io.get_regressed_systime(0, None) for neo_io in self.neo_io]
)

This causes memory exhaustion and makes conversion of long recordings impossible.

Solution

1. TimestampDataChunkIterator

Added a new TimestampDataChunkIterator class that extends GenericDataChunkIterator to lazily load timestamps in chunks rather than loading the entire array into memory.

2. Smart Timestamp Handling

Enhanced RecFileDataChunkIterator with intelligent timestamp detection:

• Regular timestamps: Uses rate parameter in ElectricalSeries (most memory efficient)
• Irregular timestamps: Uses chunked TimestampDataChunkIterator with H5DataIO

3. Backward Compatibility

All existing APIs are preserved with new methods:

• get_sampling_rate(): Returns sampling rate for regular timestamps
• get_timestamps_chunked(): Returns chunked timestamp iterator
• get_timestamps(): Backward-compatible method that loads on demand

Memory Impact

For a 17-hour recording at 30kHz:

• Before: 14.7 GB for timestamps + data memory
• After: ~8 bytes for sampling rate + data memory
• Savings: 14.7 GB (99.9% reduction in timestamp memory usage)

Files Modified

• convert_ephys.py: Core timestamp optimization implementation
• convert_analog.py: Applied same optimization to analog data
• convert.py: Updated main conversion pipeline
• convert_intervals.py: Updated to use new timestamp access method
• test_behavior_only_rec.py: Updated test for compatibility

Testing

The implementation includes comprehensive testing:

• Unit tests for TimestampDataChunkIterator functionality
• Integration tests with NWB ElectricalSeries creation
• Edge case testing for multiple files and irregular timestamps
• Memory calculation verification for various recording lengths
• Backward compatibility validation with existing test suite

Fixes #47.

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