ZGainsforth
6/14/2016 - 10:38 PM

Python function for getting data out of vast complicated heterogeneous log files such as produced by MELTS or VASP. You just give it the fi

Python function for getting data out of vast complicated heterogeneous log files such as produced by MELTS or VASP. You just give it the file name, start and stop strings, and it does all the footwork with regex. Can also automatically turn the chunk into a numpy array.

GetChunkFromTextFile.py
content_copyfile_download
import numpy as np
import re
from StringIO import StringIO

def GetChunkFromTextFile(FileName, StartStr, StopStr, skip_header=0, skip_footer=0, LastHit=True, DataType='array'):
    # DataType means we can extract the chunk and then turn it into:
    # 1) Numpy table 'numpy'
    # 2) return the raw text 'raw'
    DataType = DataType.lower()

    # Read the file.
    try:
        with open(FileName, 'r') as myfile:
            data = myfile.read()
    except:
        print 'Failed to open ' + FileName + '.  Skipping.'
        return

    # This regex looks for the data between the start and top strings.
    reout = re.compile('%s(.*?)%s' % (StartStr, StopStr), re.S)
    try:
        # Extract just the data we want.
        if LastHit == False:
            SectionStr = reout.search(data).group(1)
        else:
            SectionStr = reout.findall(data)[-1]
    except:
        # It is possible that the user asked for something that isn't in the file.  If so, just bail.
        return None

    if DataType == 'raw':
        # Now apply skip_header and skip_footer
        SectionData = SectionStr
        SectionData = ''.join(SectionData.splitlines(True)[skip_header:])
        if skip_footer > 0:
            SectionData = ''.join(SectionData.splitlines(True)[:-skip_footer])

    if DataType == 'float':
        SectionData = np.float(SectionStr)

    if DataType == 'array':
        # Convert it into a numpy array.
        SectionData = np.genfromtxt(StringIO(SectionStr), skip_header=skip_header, skip_footer=skip_footer, dtype=None)

    return SectionData