import numpy as np
import json, os, glob, yaml, time
import argparse, pickle, h5py
from pathlib import Path
from sfdata import SFDataFile, SFDataFiles

from alvra_tools.load_data import *
from alvra_tools.channels import *
from alvra_tools.utils import *


#EventChan = 'SAR-CVME-TIFALL4:EvtSet'
Detector  = 'JF06T32V07'
chIzero110  = 'SAROP11-PBPS110:INTENSITY'
chIzero122  = 'SAROP11-PBPS122:INTENSITY'
chIzeroAPD  = 'SARES11-GES1:PR1_CH1_VAL_GET'

#roi = [900, 1300, 850, 1250]    
roi = [800, 1400, 750, 1350]    

def get_acq_from_pth(path):
    import re
    return re.search(r"acq(\d+)", path).group(1).zfill(4)

parser = argparse.ArgumentParser()
parser.add_argument("--input", "-i", required=True)
args = parser.parse_args()

filename = Path(args.input)
output_file = Path(str(filename).replace("/raw/", "/res/processed/").replace(".h5",".corr_PROCESSED.h5") )
output_file.parent.mkdir(parents=True, exist_ok=True, mode=0o775)

acq = get_acq_from_pth(args.input)
acq_meta_pth = Path(str(filename).replace("/data/ac", "/meta/ac")).parent
acq_info_pth = acq_meta_pth.joinpath(f"acq{acq}.json")

with open(acq_info_pth, "r") as f:
    acq_parameters = json.load(f)
    rbk_value = acq_parameters.get("scan_info", {}).get("scan_readbacks", 0)
    #xlabel = acq_parameters.get("scan_info", {}).get("name", None)
    #units = acq_parameters.get("scan_info", {}).get("units", None)

file2load = args.input.replace('BSDATA', "*")
#print ('sleeping 30 seconds, ROI = {}'.format(roi))
#time.sleep(30) 

#file2load = args.input.replace('JF06T32V07', "*")

with SFDataFiles(file2load) as step:
    subset = step[Detector, chIzero110, chIzero122, chIzeroAPD]
    subset.drop_missing()

    JF    = crop_roi(subset[Detector].data, roi)
    JF_flat = JF.reshape(JF.shape[0], -1)
    Izero110 = subset[chIzero110].data
    Izero122 = subset[chIzero122].data
    IzeroAPD = subset[chIzeroAPD].data

    before = len(Izero110)

    q_low  = np.percentile(Izero110, 5)
    q_high = np.percentile(Izero110, 95)
    outliers = (Izero110 < q_low) | (Izero110 > q_high)

    JF_flat = JF_flat[~outliers]
    Izero110 = Izero110[~outliers]
    Izero122 = Izero122[~outliers]
    IzeroAPD = IzeroAPD[~outliers]

    print ("Survived {} out of {} shots".format(len(Izero110), before))

    JF_int = np.sum(JF_flat, axis=1)

with h5py.File(output_file, 'w') as f:
    gr1 = f.create_group("data")
    gr1['Izero110'] = Izero110
    gr1['Izero122'] = Izero122
    gr1['IzeroAPD'] = IzeroAPD
    gr1['Int_JF'] = JF_int 
    
    gr2 = f.create_group("meta")
    gr2["roi"] = roi