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

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

#This is for 16M!
roi = [1100, 1300, 1100, 1300] 

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",".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)

with h5py.File(args.input, "r") as f:
   cropped = crop_roi(f['data']['JF06T32V07']['data'], roi)
   intensity = cropped.sum(axis=1).sum(axis=1)

with h5py.File(output_file, 'w') as f:
    gr1 = f.create_group("data")
    gr1['cropped'] = cropped
    gr1['intensity'] = intensity

    gr2 = f.create_group("meta")
    gr2["readback_value"] = np.atleast_1d(rbk_value)
    #gr2["xlabel"] = xlabel
    #gr2["units"]  = units

#with h5py.File(output_file, 'w') as f:
#   f['cropped'] = cropped
#   f['intensity'] = intensity