import os
import argparse
from datetime import datetime
import random

from psychopy import visual, core, event, logging

from device.data_client import NeuracleDataClient
from device.trigger_box import TriggerNeuracle
from device.fubo_pneumatic_finger import FingerController
from device.arduino import send_toggle_command,connect_to_arduino
from settings.config import settings
from bci_core.online import Controller, model_loader


config_info = settings.CONFIG_INFO
fingermodel_ids_inverse = settings.FINGERMODEL_IDS_INVERSE

# get train params
def parse_args():
    parser = argparse.ArgumentParser(
        description='Hand gesture train'
    )
    parser.add_argument(
        '--subj',
        dest='subj',
        help='Subject name',
        default=None,
        type=str
    )
    parser.add_argument(
        '--hand-port',
        dest='hand_port',
        help='Peripheral serial port',
        type=str
    )
    parser.add_argument(
        '--trigger-port',
        dest='trigger_port',
        help='Triggerbox serial port',
        type=str
    )
    parser.add_argument(
        '--arduino-port',
        dest='arduino_port',
        help='Arduino serial port',
        type=str
    )
    parser.add_argument(
        '--state-change-threshold',
        '-scth',
        dest='state_change_threshold',
        help='Threshold for HMM state change',
        type=float
    )
    parser.add_argument(
        '--state-trans-prob',
        '-stp',
        dest='state_trans_prob',
        help='Transition probability for HMM state change',
        default=0.8,
        type=float
    )
    parser.add_argument(
        '--momentum',
        help='Probability update momentum',
        default=0.5,
        type=float
    )
    parser.add_argument(
        '--model-filename',
        dest='model_filename',
        help='Model file',
        default=None,
        type=str
    )
    parser.add_argument(
        '--debug',
        action='store_true',
        help='Store true to debug progress'
    )
    return parser.parse_args()
args = parse_args()

# setup logger
logging.console.setLevel(logging.INFO)
datetime_now = datetime.now().strftime("%Y%m%d-%H%M%S")
log_file_path = os.path.join(settings.DATA_PATH, args.subj, f"freegrasping_{datetime_now}.log")

logger = logging.LogFile(log_file_path, level=logging.INFO, filemode='w')

# initialize devices and models
if not args.debug:
    # load model
    model_path = os.path.join(settings.MODEL_PATH, args.subj, args.model_filename)
    input_kwargs = {
            'state_trans_prob': args.state_trans_prob,
            'state_change_threshold': args.state_change_threshold,
            'momentum': args.momentum
        }
    control_model = model_loader(model_path, **input_kwargs)

    # build bci controller
    controller = Controller(0., control_model, reref_method=config_info['reref'])
    # connect neo
    receiver = NeuracleDataClient(n_channel=len(config_info['channel_labels']), 
                                samplerate=config_info['sample_rate'],
                                host=config_info['host'],
                                port=config_info['port'],
                                buffer_len=config_info['buffer_length'])

    # connect to trigger box
    trigger = TriggerNeuracle(port=args.trigger_port)

    # connect to mechanical hand
    hand_device = FingerController(mode='step', init_params={'port': args.hand_port})

    serial_port = args.arduino_port
    baud_rate = 9600
    # Connect to Arduino
    ser = connect_to_arduino(serial_port, baud_rate)

# setup window
win = visual.Window(
        size=[1920, 1080], fullscr=True, screen=0,
        winType='pyglet', allowStencil=False,
        monitor='testMonitor', color=[1,1,1], colorSpace='rgb',
        backgroundImage='', backgroundFit='none',
        blendMode='avg', useFBO=True,
        units='height'
    )
fps = win.getActualFrameRate()
update_interval = 0.1  # second


# --- Initialize components for Routine "decision" ---
feedback_bar = visual.Progress(
    win, name='feedback_bar',
    progress=0,
    pos=(0, -0.25), size=(0.5, 0.1), anchor='bottom-left', units='height',
    barColor='black', backColor=None, borderColor='black', colorSpace='rgb',
    lineWidth=4.0, opacity=1.0, ori=270.0,
    depth=0
)

text_message = visual.TextStim(win=win, name='text',
    text='您将在接下来的任务中自主控制气动手，\n进度条提示您当前时刻的抓握力度。\n希望气动手握紧请用力尝试握手，\n希望气动手松开请尝试放松。\n按空格键继续',
    font='Open Sans',
    pos=(0, 0), height=0.05, wrapWidth=None, ori=0.0, 
    color='black', colorSpace='rgb', opacity=None, 
    languageStyle='LTR',
    depth=0.0)
text_message.draw()
win.flip()

event.waitKeys()

while True:
    keys = event.getKeys()
    if 'escape' in keys:
        break

    if not args.debug:
        data_from_buffer = receiver.get_trial_data(clear=False)
        decision = controller.decision(data_from_buffer, None)
        force = controller.real_feedback_model.probability[1]
    else:
        decision = random.randint(-1, 1)
        force = random.random()
    current_time = datetime.now().strftime("%Y-%m-%d %H:%M:%S.%f")
    logging.exp(f'Prob: {force} - current time: {current_time}')
    feedback_bar.progress = force

    feedback_bar.draw()
    win.flip()

    if decision != -1:
        # logging decision change
        current_time = datetime.now().strftime("%Y-%m-%d %H:%M:%S.%f")
        logging.exp(f'Decision: {decision:d} - current time: {current_time}')

        if not args.debug:
            trigger.send_trigger(int(decision))
            hand_device.move(action=fingermodel_ids_inverse[decision])
            send_toggle_command(ser)
        # if decision == 0:  # only when state changes to rest, give a freeze time
        #     core.wait(3)
    else:
        core.wait(0.1)

# exit exp
if not args.debug:
    receiver.close()

logging.flush()