make a script analysing pulse energy distribution

[samoylv]

the script read every FELsource_out.h5 file in a folder and fill a vector with values of calculated total pulse energy

total_pulse_energy = <put formula here>

output: a text file with header and values (in J) and a histogram for pulses energy distribution

Questions:

1. what is most effective way to read wave field data, get intensity,
2. shouldn't we include the script in WPG library?

[samoylv]

could you help me with proper piece of code for h5-file access, i.e.

• read data/arrEhor in a loop for every file in the dir, for every file
• calculate wf_intensity[idx] = wf.get_intensity(polarization='horizontal')
• plot histogram of wf_intensity[idx]

[buzmakov]

import os
import sys
import glob
import pylab as plt
sys.path.insert(0,os.path.join('..','WPG'))

from wpg import Wavefront

#get list of all files by mask (without recursive directory discovering)
wavefront_files = glob.glob('simulation_test/FELsource/*.h5') 
print wavefront_files

for wavefront_file in wavefront_files:
    print wavefront_file
    w = Wavefront()
    w.load_hdf5(wavefront_file)

    #load data/arrEhor
    data_hor = w.data.arrEhor
    print data_hor.shape

    intensity = w.get_intensity().flat
    #filter intensity to remove near zero values
    intensity = intensity[intensity>1e10]

    plt.hist(intensity, bins=100)

[samoylv]

thanks!

On Fri, Nov 7, 2014 at 9:36 AM, Alexey Buzmakov notifications@github.com
wrote:

import osimport sysimport globimport pylab as plt
sys.path.insert(0,os.path.join('..','WPG'))
from wpg import Wavefront
#get list of all files by mask (without recursive directory discovering)
wavefront_files = glob.glob('simulation_test/FELsource/*.h5') print wavefront_files
for wavefront_file in wavefront_files:
print wavefront_file
w = Wavefront()
w.load_hdf5(wavefront_file)

#load data/arrEhor
data_hor = w.data.arrEhor
print data_hor.shape

intensity = w.get_intensity().flat
#filter intensity to remove near zero values
intensity = intensity[intensity>1e10]

plt.hist(intensity, bins=100)

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