check nHden from cloudy output hden and saved grid param file

nH.py

gridfile = '/mnt/home/daisyleung/Downloads/SIGAME_dev/sigame/temp/z6_data_files/cloud_models/GMC/grids/GMCgrid_abun_z6_em.models'

import glob
import pandas as pd
import numpy as np
gridsDF = pd.read_pickle(gridfile)
nHmw = gridsDF['nHmw']
nHmin = gridsDF['nHmin']
#

outPath = '/mnt/home/daisyleung/Downloads/SIGAME_dev/sigame/temp/z6_data_files/cloud_models/GMC/output/'

def line_num_for_phrase_in_file(phrase='xxx', filename='file.txt'):

    totNumLines = np.loadtxt(filename).shape[0]
    with open(filename, 'r') as f:
        i = 0
        magicnumber_list = []
        while i < totNumLines:
            for (i, line) in enumerate(f):
                if phrase in line:
                    magicnumber_list.append(i - 2)
        return magicnumber_list
    return -1

def read_ovrfile(ovrfile):
    # read in overview file
    try:
        ovrdata = np.loadtxt(ovrfile, skiprows=1)
    except:
        return ovrfile, None

    f = open(ovrfile, 'r')
    ovrhdr = f.readline().split('\t')
    f.close()
    ovrhdr[0] = ovrhdr[0][1:]
    col = dict.fromkeys(ovrhdr)

    for ii, jj in enumerate(ovrhdr):   # clean off any \n \r\n
        ovrhdr[ii] = jj.rstrip()

    for i in range(ovrdata.shape[-1]):
        col[ovrhdr[i]] = ovrdata[:, i]

    magicnumber_list = line_num_for_phrase_in_file("####", ovrfile)
    return col, magicnumber_list


import _pickle as pick
param = pick.load(open('/mnt/home/daisyleung/Downloads/SIGAME_dev/sigame/temp/z6_data_files/cloud_models/GMC/grids/GMCgrid_abun_z6.param', "rb"))
pc2cm = 3.086e+18
for iii, prefix in enumerate(glob.glob(outPath + '*.in')):
    prefix = prefix[:prefix.find('.in')]
    prefix = prefix.split('/')[-1]

    ovrfile = outPath + prefix + '.ovr'
    col, magicnumber_list = read_ovrfile(ovrfile)

    if type(col) is str and magicnumber_list is None:
        pass
    elif len(magicnumber_list) == 0:
        # haven't converged
        pass
    else:
        Rgmc                            =   param['Rgmcs'][iii] # pc
        col=pd.DataFrame(col)
        import pdb; pdb.set_trace()
        col = col[magicnumber_list[-1]-10:]
        print(col['hden'])
        col[col['depth'] > 0.01 * Rgmc * pc2cm].reset_index(drop=True)
        nH = col['hden']
        print(nH.min(), nHmin[int(prefix[prefix.find('_')+1:])])
        import pdb; pdb.set_trace()