gevi/olivia_data_plotter.py

import numpy as np
import matplotlib.pyplot as plt
import os
from functions.create_logger import create_logger
from functions.load_config import load_config

from functions.get_trials import get_trials
import h5py  # type: ignore

import argh


def main(*, experiment_id: int = 1, config_filename: str = "config.json") -> None:

    mylogger = create_logger(
        save_logging_messages=True,
        display_logging_messages=True,
        log_stage_name="test_xxx",
    )
    config = load_config(mylogger=mylogger, filename=config_filename)

    roi_path: str = config["ref_image_path"]

    control_file_handle = h5py.File(os.path.join(roi_path, "ROI_control.mat"), "r")
    control_roi = (np.array(control_file_handle["roi"]).T) > 0
    control_file_handle.close()
    control_roi = control_roi.reshape((control_roi.shape[0] * control_roi.shape[1]))

    s_darken_file_handle = h5py.File(os.path.join(roi_path, "ROI_sDarken.mat"), "r")
    s_darken_roi = (np.array(s_darken_file_handle["roi"]).T) > 0
    s_darken_file_handle.close()
    s_darken_roi = s_darken_roi.reshape((s_darken_roi.shape[0] * s_darken_roi.shape[1]))

    raw_data_path: str = os.path.join(
        config["basic_path"],
        config["recoding_data"],
        config["mouse_identifier"],
        config["raw_path"],
    )

    data_path: str = str(config["export_path"])

    trails = get_trials(path=raw_data_path, experiment_id=experiment_id)
    for i in range(0, trails.shape[0]):
        trial_id = int(trails[i])
        experiment_name: str = f"Exp{experiment_id:03d}_Trial{trial_id:03d}"
        mylogger.info(f"Loading files for {experiment_name}")

        data = np.load(os.path.join(data_path, f"{experiment_name}_ratio_sequence.npz"))
        if i == 0:
            ratio_sequence = data["ratio_sequence"]
        else:
            ratio_sequence += data["ratio_sequence"]

    ratio_sequence /= float(trails.shape[0])

    ratio_sequence = ratio_sequence.reshape(
        (ratio_sequence.shape[0] * ratio_sequence.shape[1], ratio_sequence.shape[2])
    )

    control = ratio_sequence[control_roi, :].mean(axis=0)
    s_darken = ratio_sequence[s_darken_roi, :].mean(axis=0)

    t = np.arange(0, control.shape[0]) / 100.0

    plt.plot(t, control, label="control")
    plt.plot(t, s_darken, label="sDarken")
    plt.legend()
    plt.xlabel("Time [sec]")
    plt.show()


if __name__ == "__main__":
    argh.dispatch_command(main)