def make_channel_dict(ordered_index):
    """Creates a Dictionary of the the indexes for each Channel's features in the ordered_index

    Parameters:
    -----------
    ordered_index: list
        Index of Features for Feature Dropping
                            [list] -> (Tuple)
        Power:   [Num of Features] -> (Chan Num , Freq Num)
        Pearson: [Num of Features] -> (Chan Num , Freq Num, Temp Num)

    Returns:
    -------
    channel_dict: dict
        dictionary to be used to remove all features for a single channel
        {Channel: [list of Indexes]}

    """

    channel_dict = {}
    nun_channels = ordered_index[-1][0] + 1  # Determine the Number of Channels (Assumes the ordered_index is in order)

    # Iterate over the number of channels
    for chan_focus in range(nun_channels):
        value = []

        # Iterate over the total number of features
        for index in range(len(ordered_index)):
            if ordered_index[index][0] == chan_focus:
                value.append(index)
        channel_dict[
            chan_focus] = value  # Store the list of that Channel's Features to its corresponding Key in the Dict

    return channel_dict