TSv7_mergeCSV.py

import h5py
import csv
import os
import numpy as np
from scipy.signal import resample

def downsample(data, original_fs, target_fs):
    # Calculate the downsample factor
    downsample_factor = int(original_fs / target_fs)
    
    # Use scipy's resample function to downsample the data
    downsampled_data = resample(data, len(data) // downsample_factor)
    
    return downsampled_data

def save_selected_datasets_to_csv(file_path, selected_datasets, target_fs=10.0):  ##change this to be your desired frame rate. The list of selected datasets will need to match Thorsync exactly.
    try:
        base_name = os.path.splitext(os.path.basename(file_path))[0]

        with h5py.File(file_path, 'r') as h5_file:
            # Downsample all selected datasets and organize into a NumPy array
            downsampled_data = []
            time_values = None

            for dataset_name in selected_datasets:
                item = h5_file[dataset_name]
                data = item[:]
                original_fs = 30000.0  # Replace with the actual sampling frequency of your data
                downsampled_data.append(downsample(data, original_fs, target_fs))

                # Save time values only once (assuming all datasets have the same length)
                if time_values is None:
                    time_values = np.arange(0, len(downsampled_data[-1]) / target_fs, 1 / target_fs)

            # Transpose the array to have time in the first column and each dataset in subsequent columns
            downsampled_data = np.column_stack([time_values] + downsampled_data)

            # Filter rows based on the condition in the DI_2pFrames column
            mask = downsampled_data[:, selected_datasets.index("DI/2pFrames") + 1] >= 0.5
            downsampled_data = downsampled_data[mask]

            # Regenerate time values starting from 0 with the appropriate sampling rate
            downsampled_data[:, 0] = np.arange(0, len(downsampled_data) / target_fs, 1 / target_fs)

            return downsampled_data
                
    except Exception as e:
        print(f"Error: {e}")
        return None

def process_directory(directory_path, selected_datasets, target_fs):
    all_downsampled_data = []

    # Iterate through all .h5 files in the directory
    for filename in os.listdir(directory_path):
        if filename.endswith(".h5"):
            file_path = os.path.join(directory_path, filename)
            downsampled_data = save_selected_datasets_to_csv(file_path, selected_datasets, target_fs)
            if downsampled_data is not None:
                all_downsampled_data.append(downsampled_data)

    # Stack all downsampled data into a single NumPy array
    all_downsampled_data = np.vstack(all_downsampled_data)

    # Add another column after DI_PandaFrames with a new time course
    time_values_additional = np.arange(0, len(all_downsampled_data) / target_fs, 1 / target_fs)
    all_downsampled_data = np.column_stack([all_downsampled_data, time_values_additional])

    # Write the NumPy array to a CSV file
    header_row = ["Time"] + [dataset.replace('/', '_') for dataset in selected_datasets] + ["Additional_Time"]
    output_file_name = os.path.join(directory_path, "merged_selected_datasets.csv")
    np.savetxt(output_file_name, all_downsampled_data, delimiter=",", header=",".join(header_row), comments="")
    print(f"CSV file '{output_file_name}' created.")

if __name__ == "__main__":
    directory_path = "Y:/DRGS project/#505 12-18-23/SDH Recording/Final FOV/Functional/ThorSync/Test/"  # Replace with the path to your directory containing .h5 files
    selected_datasets = [
        "AI/E_Stim",
        "AI/M_Force",
        "AI/M_Length",
        "AI/Pedal",
        "AI/Pelt_Temp",
        "AI/PiezoMonitor",
        "AI/PockelsMonitor",
        "DI/2pFrames",
        "DI/PandaFrames"
    ]
    target_fs = 10.0  # Replace with the desired target sampling frequency for the additional time course
    process_directory(directory_path, selected_datasets, target_fs)

    # Y:/DRGS project/#505 12-18-23/SDH Recording/Final FOV/Functional/ThorSync/Test/
    #this one merges all the files into a single file