add optional live view

import tempfile

import time

opt = dict()

matplotlib_theme = "fast"

def running_mean(x: np.ndarray, N: int) -> np.ndarray:

def measure_data(

    filename, duration, libmsp430_path=None, energytrace_cmd="energytrace"

    filename,

    duration,

    libmsp430_path=None,

    energytrace_cmd="energytrace",

    live_view=False,

    live_history=10000,

):

    # libmsp430.so must be available

    if libmsp430_path is None:

    else:

        output_handle = tempfile.TemporaryFile("w+")

    if not duration:

        print("Press Ctrl+C to stop measurement")

    if live_view:

        import matplotlib.pyplot as plt

        plt.style.use(matplotlib_theme)

        max_y = 0

        plt.ion()

        timestamps = [0]

        voltages = [0]

        energy_values = [0]

        power_values = [0]

        plt.xlabel("Time [s]")

        plt.ylabel("Power [W]")

        (powerline,) = plt.plot(

            timestamps, power_values, "r-", label="Power [W]", markersize=1

        )

        plt.show()

        last_update = 0

        energytrace = subprocess.Popen(

            [energytrace_cmd, str(duration)],

            stdout=subprocess.PIPE,

            universal_newlines=True,

        )

        try:

            for line in energytrace.stdout:

                output_handle.write(line)

                if line[0] == "#":

                    continue

                timestamp, current, voltage, energy = line.split()

                timestamps.append(float(timestamp) / 1e6)

                voltages.append(float(voltage) / 1e3)

                energy_values.append(float(energy) / 1e9)

                if duration and timestamps[-1] > duration + 5:

                    break

                if energy_values[-1] > energy_values[-2]:

                    power_values.append(

                        (energy_values[-1] - energy_values[-2])

                        / (timestamps[-1] - timestamps[-2])

                    )

                else:

                    power_values.append(np.nan)

                if power_values[-1] > max_y:

                    max_y = power_values[-1]

                if live_history:

                    timestamps = timestamps[-live_history:]

                    voltages = voltages[-live_history:]

                    energy_values = energy_values[-live_history:]

                    power_values = power_values[-live_history:]

                if timestamps[-1] - last_update > 0.1:

                    update_start = time.time()

                    powerline.set_data([timestamps, power_values])

                    plt.xlim([timestamps[0], timestamps[-1]])

                    plt.ylim([0, max_y + 0.1])

                    plt.show()

                    plt.pause(0.01)

                    update_end = time.time()

                    last_update = timestamps[-1] + update_end - update_start

        except KeyboardInterrupt:

            print("Stopping measurement")

            energytrace.send_signal(subprocess.signal.SIGTERM)

    else:

        energytrace = subprocess.Popen(

        [energytrace_cmd, str(duration)], stdout=output_handle, universal_newlines=True

            [energytrace_cmd, str(duration)],

            stdout=output_handle,

            universal_newlines=True,

        )

        try:

            if duration:

                time.sleep(duration)

            else:

            print("Press Ctrl+C to stop measurement")

                while True:

                    time.sleep(3600)

        except KeyboardInterrupt:

            print("Stopping measurement")

            energytrace.send_signal(subprocess.signal.SIGTERM)

    energytrace.communicate(timeout=5)

        action="store_true",

        help="Log CPU and peripheral states as well as energy readings. Requires EnergyTrace++ support. Reduces the sample rate to about 1 kHz.",

    )

    parser.add_argument(

        "--live-view",

        action="store_true",

        help="Plot live voltage/current data while the measurement is running. May cause lost samples at the end of the measurement.",

    )

    parser.add_argument(

        "--live-history",

        type=int,

        metavar="N",

        default=10000,

        help="Show up to N past samples in the live view. Less history → lower live view overhead → higher update rate. Set to 0 for unlimited history.",

    )

    parser.add_argument(

        "duration", type=int, nargs="?", help="Measurement duration in seconds"

    )

            args.duration,

            libmsp430_path=args.libmsp430_path,

            energytrace_cmd="energytracepp",

            live_view=args.live_view,

            live_history=args.live_history,

        )

    else:

        log_data = measure_data(

            args.save, args.duration, libmsp430_path=args.libmsp430_path

            args.save,

            args.duration,

            libmsp430_path=args.libmsp430_path,

            live_view=args.live_view,

            live_history=args.live_history,

        )

    lines = log_data.split("\n")

    if args.plot:

        import matplotlib.pyplot as plt

        plt.style.use(matplotlib_theme)

        if annotations[0]:

            fig, ax = plt.subplots()

            timestamps = data[1:, 0] * 1e-6