Issue I4: Unit Tests for Hello Synchrony Pipeline

[Ramdam17]

Description:

Add pytest unit tests for the Hello Synchrony notebook pipeline to ensure reproducibility.

Context:
Notebooks can silently break. Unit tests with shape checks and golden outputs ensure the pipeline keeps working.

Tasks:

• Create tests/test_hello_synchrony.py
• Test simulated data generation (shapes, dtypes)
• Test synchrony computation (output shapes, value ranges)
• Add "golden output" test: compare against saved expected values
• Integrate with pytest

Acceptance Criteria:

• At least 5 test functions
• Tests cover: data generation, metric computation, output shapes
• Golden output test with tolerance for floating-point
• All tests pass with pytest tests/test_hello_synchrony.py

Example test structure:

import numpy as np
import pytest
from hypyp import analyses

def test_simulated_data_shape():
    data = generate_simulated_data(n_channels=32, n_epochs=10)
    assert data[0].shape == (10, 32, 1000)  # (epochs, channels, samples)

def test_plv_output_range():
    plv = analyses.compute_sync(data, metric='plv')
    assert np.all(plv >= 0) and np.all(plv <= 1)

def test_golden_output():
    result = run_hello_synchrony_pipeline(seed=42)
    expected = np.load('tests/golden/hello_synchrony_expected.npy')
    np.testing.assert_allclose(result, expected, rtol=1e-5)

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