def prepare_alligned_umap_data(embeddings, max_time_index=10):
    """Prepare data for running AllignedUMAP

    Args:
        embeddings: a dictionary, keys are batch number while values are
        embeddings extracted by a CNN after observing key number of batches.
        max_time_index: an integer indicating the maximum number of consecutive
        embeddings considered for UMAP reduction.

    Returns:
        list_embeddings: a list of numpy array, max_time_index array taken from
        embeddings.
        mappers: a list of dictionary, each dictionary map the entries of an
        embedding in list_embeddings with its correspective in the one that
        follow.
    """
    list_embeddings = []
    mappers = []
    for time_index in range(max_time_index):

        time_embedding = embeddings[time_index]
        list_embeddings.append(
            time_embedding
        )
        mappers.append(
            {embedding_index: embedding_index for
                embedding_index in range(time_embedding.shape[0])}
        )

    return list_embeddings, mappers[1:]