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#!/usr/local/bin/python
import os
import os.path
import sys
import cgi, cgitb
import StringIO
import h5py
import numpy as np
from pyplatypus.reduce import reduce
from pyplatypus.reduce import processplatypusnexus
from pyplatypus.reduce import platypusspectrum
import gviz_api
import zipfile
import string
cgitb.enable()
#specify where the files are to originate from
FILEPATH = './'
def main():
form = cgi.FieldStorage()
keys = form.keys()
kwds = {}
kwds['lolambda'] = 2.8
kwds['hilambda'] = 18.0
kwds['rebinpercent'] = 4.0
spectra = []
if 'spectrum' in keys:
spectrum_list = reduce.sanitize_string_input(form.getlist('spectrum'))
background = True
for key in keys:
if key in kwds:
kwds[key] = float(form[key].value)
red = processplatypusnexus.ProcessPlatypusNexus()
try:
for specnumber in spectrum_list:
specname = ''
sn = 'PLP{0:07d}.nx.hdf'.format(int(abs(specnumber)))
for root, dirs, files in os.walk(FILEPATH):
if sn in files:
specname = os.path.join(root, sn)
break
if not len(specname):
continue
with h5py.File(specname, 'r') as h5data:
spectrum = red.process(h5data, **kwds)
spectra.append(spectrum)
except:
print "Content-type: text/plain\n"
print 'a'
return
if not len(spectra):
print "Content-type: text/plain\n"
print ''
return
if 'JSON' in keys:
print "Content-type: text/plain\n"
print spectra_to_json(spectra)
return
else:
zipped_spectra = spectra_to_zip(spectra)
length = len(zipped_spectra.getvalue())
datacontent = '\r\n'.join(["Content-type: %s;",
"Content-Disposition: attachment; filename=\"%s\"",
"Content-Title: %s",
"Content-Length: %i",
"",])
print datacontent % ('application/octet-stream', 'data.zip', 'data.zip', length)
sys.stdout.write(zipped_spectra.getvalue()) # *not* print, doh !
sys.stdout.flush()
def spectra_to_json(spectra):
'''
spectra is a list of the processed spectra
Returns a json representation of the spectra, suitable for google visualisation
'''
numspectra = len(spectra)
data = []
description = [('lamda', 'number')]
for index, spectrum in enumerate(spectra):
description.append((str(spectrum.datafilenumber), 'number'))
wavelength = spectrum.M_lambda[0]
intensity = spectrum.M_spec[0]
numpoints = np.size(wavelength, axis = 0)
for index2 in xrange(numpoints):
record = [None] * (numspectra + 1)
record[0] = wavelength[index2]
record[index + 1] = intensity[index2]
data.append(record)
data_table = gviz_api.DataTable(description)
data_table.LoadData(data)
json = data_table.ToJSon()
return json
def spectra_to_zip(spectra):
'''
spectra is a list of the processed spectra
returns a zip file with the zipped spectra files.
'''
theZipFile = StringIO.StringIO()
with zipfile.ZipFile(theZipFile, 'w') as Tzipfile:
for spectrum in spectra:
spectrum_file = StringIO.StringIO()
spectrum.write_spectrum_xml(spectrum_file)
filename = 'PLP{:07d}.spectrum'.format(spectrum.datafilenumber)
Tzipfile.writestr(filename, spectrum_file.getvalue())
return theZipFile
if __name__ == '__main__':
main()
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