Robust-first Computing Wiki

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The plot_element_counts.py script:

#!/usr/bin/env python

# Reads .mfs files in a directory and makes plots of # particular elements (Data, Isolator) in them # Work-in-progress.

import sys import matplotlib.pyplot as plt

# Idea: keep a mapping somewhere (file?) of Element name to color # to use with plot

def plot_mfs_data(filePath, plot_title, elem_names):

   with open(filePath, "r") as inFile:
      
       # Read header and AEPS column
       header = inFile.readline().split()
       header.remove("#") # there is a column named as "# AEPS", bad
       AEPS_index = header.index("AEPS")
       lines = inFile.readlines()
       AEPS = []
       for l in lines:
           entries = l.split()
           AEPS.append(entries[AEPS_index])
       ##############################
      

       # Read data lines of file, get element counts, make plots for each
       fig_index = 0
       for elem in elem_names:
           col_index = header.index(elem)
           counts = []

           for l in lines:
               entries = l.split()
               counts.append(entries[col_index])

           # Make plots for this Element
           fig = plt.figure(fig_index)
           fig_index += 1
           plt.plot(AEPS, counts)
           plt.xlabel('AEPS')
           plt.ylabel("Number of " + elem)
           plt.title(plot_title)
         
       # Show all figures/plots
       plt.show()
      

# When run as a script if name == “main”:

   if len(sys.argv) < 4:
       print "Usage: <tbd data file> <plot_title> <list of Element names>"
   else:
       plot_mfs_data(sys.argv[1], sys.argv[2], sys.argv[3:])