Issue I1: Simulated Dataset + Hello World Notebook

[Ramdam17]

Description:

Create a minimal simulated dataset and a "Hello Synchrony" notebook that demonstrates the core HyPyP workflow in under 5 minutes.

Context:
Currently, users need real EEG data to try HyPyP. A simulated dataset removes this barrier and lets anyone run a complete pipeline immediately.

Tasks:

• Create a function to generate simulated 2-person "EEG-like" data
  • Configurable: n_channels, n_samples, sampling_rate, n_epochs
  • Option to inject known synchrony (e.g., phase-locked signals)
• Create hello_synchrony.ipynb notebook that:
  • Generates simulated data
  • Computes at least 2 synchrony metrics (e.g., PLV, ccorr)
  • Visualizes results
  • Runs end-to-end in < 5 minutes
• Save expected outputs (figures, key values) for validation

Acceptance Criteria:

• Simulated data function is documented and tested
• Notebook runs without errors on a clean install
• Total runtime < 5 minutes
• At least 2 visualizations included
• Expected outputs are saved alongside notebook

Technical notes:

• Use NumPy for signal generation
• Consider using MNE's create_info() and EpochsArray() for MNE compatibility

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