<gh_stars>0
from pathlib import Path
import shutil

import click
import yaml
import numpy as np

@click.command()
@click.argument('input_directories', nargs=-1)
@click.option('-o','--output_directory', default='.', help='Output directory for merged files')
@click.option('-r','--recipe-path',required=True,help='Recipe specifying how to map Trodes data')
@click.option('--remove-offset/--keep-offset', is_flag=True, default=True, help='Remove offset from timestamps in merged data')
def merge(input_directories, output_directory, recipe_path, remove_offset):
    """
    Merges trodes auxiliary files from multiple directories into a single directory.

    Note: This script will merge timestamps and event files.
    """
    input_directories = [Path(directory) for directory in input_directories]
    output_directory = Path(output_directory)
    recipe = yaml.safe_load(open(recipe_path))
    last_timestamp = 0

    # Check that all input directories exist
    if not all([directory.exists() for directory in input_directories]):
        raise ValueError('An input directory does not exist')
    
    # Initialize output data
    output_data = {}
    for name, info in recipe.items():
        if info['type']=='analog':
            output_data[f"{name}.timestamps.npy"] = []
        elif info['type']=='DIO':
            output_data[f"{name}.on.npy"] = []
            output_data[f"{name}.off.npy"] = []

    for directory in input_directories:
        ## get first timestamp
        for name, info in recipe.items():
            if info['type'] == 'analog':
                timestamps = np.load(directory/f"{name}.timestamps.npy", 'r')
                first_timestamp = timestamps[0]
                break
        else:
            raise ValueError("No analog data found in recipe")
        
        ## extract data from directory and adjust offsets
        for name, info in recipe.items():
            if info['type'] == 'analog':
                ## copy channel names for first directory
                if not (output_directory/f"{name}.channels.txt").exists():
                    shutil.copy(directory/f"{name}.channels.txt", output_directory)

                ## load timestamps and adjust offset
                timestamps = np.load(directory/f"{name}.timestamps.npy")
                if remove_offset: 
                    timestamps -= first_timestamp
                timestamps += last_timestamp
                output_data[f"{name}.timestamps.npy"].append(timestamps)
            elif info['type'] == 'DIO':
                ## load on and off events and adjust offset
                for state in ['on','off']:
                    state_timestamps = np.load(directory/f"{name}.{state}.npy")
                    if remove_offset:
                        state_timestamps -= first_timestamp
                    state_timestamps += last_timestamp
                    output_data[f"{name}.{state}.npy"].append(state_timestamps)

        last_timestamp = timestamps[-1]
    
    ## save output data
    for file, data in output_data.items():
        data = np.concatenate(data)
        np.save(output_directory/file, data)

from pathlib import Path
import shutil

import click
import yaml
import numpy as np

@click.command()
@click.argument('input_directories', nargs=-1)
@click.option('-o','--output_directory', default='.', help='Output directory for merged files')
@click.option('-r','--recipe-path',required=True,help='Recipe specifying how to map Trodes data')
@click.option('--remove-offset/--keep-offset', is_flag=True, default=True, help='Remove offset from timestamps in merged data')
def merge(input_directories, output_directory, recipe_path, remove_offset):
    """
    Merges trodes auxiliary files from multiple directories into a single directory.

    Note: This script will merge timestamps and event files.
    """
    input_directories = [Path(directory) for directory in input_directories]
    output_directory = Path(output_directory)
    recipe = yaml.safe_load(open(recipe_path))
    last_timestamp = 0

    # Check that all input directories exist
    if not all([directory.exists() for directory in input_directories]):
        raise ValueError('An input directory does not exist')
    
    # Initialize output data
    output_data = {}
    for name, info in recipe.items():
        if info['type']=='analog':
            output_data[f"{name}.timestamps.npy"] = []
        elif info['type']=='DIO':
            output_data[f"{name}.on.npy"] = []
            output_data[f"{name}.off.npy"] = []

    for directory in input_directories:
        ## get first timestamp
        for name, info in recipe.items():
            if info['type'] == 'analog':
                timestamps = np.load(directory/f"{name}.timestamps.npy", 'r')
                first_timestamp = timestamps[0]
                break
        else:
            raise ValueError("No analog data found in recipe")
        
        ## extract data from directory and adjust offsets
        for name, info in recipe.items():
            if info['type'] == 'analog':
                ## copy channel names for first directory
                if not (output_directory/f"{name}.channels.txt").exists():
                    shutil.copy(directory/f"{name}.channels.txt", output_directory)

                ## load timestamps and adjust offset
                timestamps = np.load(directory/f"{name}.timestamps.npy")
                if remove_offset: 
                    timestamps -= first_timestamp
                timestamps += last_timestamp
                output_data[f"{name}.timestamps.npy"].append(timestamps)
            elif info['type'] == 'DIO':
                ## load on and off events and adjust offset
                for state in ['on','off']:
                    state_timestamps = np.load(directory/f"{name}.{state}.npy")
                    if remove_offset:
                        state_timestamps -= first_timestamp
                    state_timestamps += last_timestamp
                    output_data[f"{name}.{state}.npy"].append(state_timestamps)

        last_timestamp = timestamps[-1]
    
    ## save output data
    for file, data in output_data.items():
        data = np.concatenate(data)
        np.save(output_directory/file, data)
Merges trodes auxiliary files from multiple directories into a single directory.      Note: This script will merge timestamps and event files. # Check that all input directories exist # Initialize output data ## get first timestamp ## extract data from directory and adjust offsets ## copy channel names for first directory ## load timestamps and adjust offset ## load on and off events and adjust offset ## save output data