"""
RTX-Neuro Example: Reading MEG/EEG Data

This example demonstrates how to read neuroimaging data from various file formats
using the rtx_neuro library.

Supported formats:
- EDF/EDF+ (European Data Format)
- FIF (Elekta/Neuromag)
- CTF (.ds directories)
- BTi/4D-Neuroimaging
- KIT/Yokogawa/Ricoh (.con, .sqd)
- EGI (.raw, .mff)
"""

import rtx_neuro as rtx
import numpy as np

# Example 1: Read EDF file
def read_edf_example():
    """Read an EDF/EDF+ file."""
    # Replace with your actual file path
    raw = rtx.io.read_raw_edf("path/to/recording.edf")

    # Access metadata
    print(f"Sampling frequency: {raw.sfreq} Hz")
    print(f"Number of channels: {raw.n_channels}")
    print(f"Number of samples: {raw.n_samples}")
    print(f"Duration: {raw.duration:.2f} seconds")
    print(f"Channel names: {raw.ch_names[:5]}...")  # First 5 channels

    # Get data as numpy array
    # Full data
    data = raw.get_data()
    print(f"Data shape: {data.shape}")  # (n_channels, n_samples)

    # Specific time window
    data_segment = raw.get_data(tmin=0.0, tmax=10.0)  # First 10 seconds
    print(f"Segment shape: {data_segment.shape}")

    return raw, data


# Example 2: Read FIF file (Elekta/Neuromag MEG)
def read_fif_example():
    """Read an Elekta/Neuromag FIF file."""
    raw = rtx.io.read_raw_fif("path/to/recording.fif")

    print(f"FIF file: {raw.path}")
    print(f"MEG channels: {raw.n_channels}")

    # Get specific channels by name
    channel_indices = raw.pick_channels(["MEG0111", "MEG0121", "MEG0131"])
    print(f"Picked channel indices: {channel_indices}")

    return raw


# Example 3: Read CTF MEG data
def read_ctf_example():
    """Read a CTF MEG dataset (.ds directory)."""
    raw = rtx.io.read_raw_ctf("path/to/dataset.ds")

    print(f"CTF dataset loaded")
    print(f"Channels: {raw.n_channels}")
    print(f"Sample rate: {raw.sfreq} Hz")

    return raw


# Example 4: Read BTi/4D-Neuroimaging data
def read_bti_example():
    """Read 4D-Neuroimaging/BTi MEG data."""
    raw = rtx.io.read_raw_bti("path/to/bti_directory")

    print(f"BTi data loaded")
    print(f"Channels: {raw.n_channels}")

    return raw


# Example 5: Read KIT/Yokogawa data
def read_kit_example():
    """Read Yokogawa/KIT/Ricoh MEG data."""
    raw = rtx.io.read_raw_kit("path/to/recording.con")
    # Or for .sqd files:
    # raw = rtx.io.read_raw_kit("path/to/recording.sqd")

    print(f"KIT data loaded")
    print(f"Channels: {raw.n_channels}")

    return raw


# Example 6: Read EGI data
def read_egi_example():
    """Read EGI data (.raw or .mff format)."""
    # For .raw files:
    raw = rtx.io.read_raw_egi("path/to/recording.raw")

    # For MFF directories:
    # raw = rtx.io.read_raw_egi("path/to/recording.mff")

    print(f"EGI data loaded")
    print(f"Channels: {raw.n_channels}")

    return raw


# Example 7: Working with data
def data_manipulation_example():
    """Demonstrate data manipulation workflows."""
    raw = rtx.io.read_raw_edf("path/to/recording.edf")

    # Get full data
    data = raw.get_data()

    # Basic numpy operations
    mean_signal = np.mean(data, axis=1)  # Mean per channel
    max_amplitude = np.max(np.abs(data))

    # Time vector
    times = np.arange(raw.n_samples) / raw.sfreq

    # Select specific channels
    eeg_indices = raw.pick_channels(["Fp1", "Fp2", "Fz"])
    selected_data = data[eeg_indices, :]

    print(f"Selected {len(eeg_indices)} channels")
    print(f"Max amplitude: {max_amplitude:.2f} uV")

    return data, times


if __name__ == "__main__":
    print("RTX-Neuro Data Reading Examples")
    print("=" * 40)
    print("\nNote: Replace file paths with your actual data files.")
    print("\nAvailable functions:")
    print("- read_edf_example()")
    print("- read_fif_example()")
    print("- read_ctf_example()")
    print("- read_bti_example()")
    print("- read_kit_example()")
    print("- read_egi_example()")
    print("- data_manipulation_example()")