i14testgui/postprocessing.py at master · nicwade/i14testgui · GitHub

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'''
Contains all the post processing tools necessary after the savu process has occured
'''


processed_data = '/dls/i08/data/2017/cm16789-3/processing/aaron/20170705111629_10481/i08-10481_processed.nxs'
outfile = '/dls/i08/data/2017/cm16789-3/processing/aaron/20170705111629_10481/pymca_rgb_converted.dat'

def convert_to_pymca_rgb(processed_data, outfile):
    import h5py as h5
    f = h5.File(processed_data,'r')
    scan_axes = 0,1
    det_elem = 0
    peak_indices  = f['entry/final_result_fluo'].attrs['PeakElements_indices']
    elements = list(f['entry/final_result_fluo/PeakElements'][...])
    data = f['entry/final_result_fluo/data']

    titles = ['row','column']
    titles.extend(elements)
    titles = [ix.replace(" ", "-") for ix in titles]
    titles = "  ".join(titles)
    k = 0

    with open(outfile,'wb') as f:
        if k==0:
            f.write(titles+"\n")
        for row in range(data.shape[0]):
            print("%d of %d" % (row, data.shape[0]))
            for column in range(data.shape[1]):
                line = list(data[row,column,det_elem])
                line = [str(ix) for ix in line]
                extra = [str(row),str(column)]
                extra.extend(line)
                line_to_write = "  ".join(extra)
                f.write(line_to_write+"\n")
#
# def convert_to_pymca_edf(processed_data, outfile):
import h5py as h5
f = h5.File(processed_data,'r')
scan_axes = 0,1
det_elem = 0,#,1,2,3
peak_indices  = f['entry/final_result_fluo'].attrs['PeakElements_indices']
elements = list(f['entry/final_result_fluo/PeakElements'][...])
data = f['entry/final_result_fluo/data']
import collections
import numpy as np
from fabio.edfimage import EdfImage


for num, key in enumerate(elements):
    for channel in det_elem:
        foo = data[:,:,channel,num]
        header = collections.OrderedDict()
        header['HeaderID'] = 'EH:000001:000000:000000'
        header['Image'] = '1'
        header['ByteOrder'] = 'LowByteFirst'
        header['DataType']=  'DoubleValue'
        header['Dim_1'] = str(foo.shape[-1])
        header['Dim 2'] = str(foo.shape[-2])
        header['Size'] = str(8.0*np.prod(foo.shape))
        out_title = "%s_channel_%s" % (key.replace(" ","_"), str(channel))
        header['Title'] = out_title
        fout = EdfImage(foo, header)
        fout.write('/dls/i08/data/2017/cm16789-3/processing/aaron/20170705111629_10481/'+out_title+'.edf')