dwek_calibration

def organize_cooling_data(link):

    import urllib2

    res = {'temperature': [], 'cooling_function': []}
    data = urllib2.urlopen(link)
    for line in data:
        temp = line.rstrip().split(',')
        res['temperature'].append(float(temp[1]))
        res['cooling_function'].append(float(temp[0]))
    return res

def main():

    import numpy
    import pylab
    import pickle

    data = {'dust':organize_cooling_data('http://pastebin.com/raw.php?i=H6euHHNE'),
            'atomic':organize_cooling_data('http://pastebin.com/raw.php?i=TtX0H7X7')}
    denser_temperature = numpy.logspace(5,9,100)
    for itm in data:
        data[itm]['fit_params'] = numpy.polyfit(numpy.log(data[itm]['temperature']),
                                                numpy.log(data[itm]['cooling_function']),7)

        pylab.loglog(data[itm]['temperature'], data[itm]['cooling_function'],'o',
                     label=itm,linewidth=3)
        pylab.loglog(denser_temperature,
                     numpy.exp(numpy.polyval(data[itm]['fit_params'],
                                             numpy.log(denser_temperature))),
                     label=itm,linewidth=3)
    pylab.legend(loc='best')
    pylab.xlabel('Temperature [K]')
    pylab.ylabel('Cooling function [erg*cc/s]')
    pylab.ylim((1e-23,1e-20))
    pylab.tick_params(axis='both', which='major', labelsize=12)
    pickle.dump(data,open('cooling_function.pkl','wb'))
    pylab.show()

if __name__ == '__main__':

    main()