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import matplotlib as pyplot
from lxml import etree

#do some plotting

plt.savefig(fig_file)
width, height = '3.8in', '2.8in'

with file(fig_file, 'r') as fid:
    tree = etree.parse(fid)

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#!/bin/bash

python $*

fname="${@: -1}"

width=`identify -format %w $fname`
gitversion=`git rev-parse --short HEAD`
origin_name=`basename $(git remote show -n origin | grep Fetch | cut -d: -f2-)`
branch=`git rev-parse --abbrev-ref HEAD`

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import numpy as np
from math import pi, log
import pylab
from scipy import fft, ifft
from scipy.optimize import curve_fit

i = 10000
x = np.linspace(0, 3.5 * pi, i)
y = (0.3*np.sin(x) + np.sin(1.3 * x) + 0.9 * np.sin(4.2 * x) + 0.06 *
    np.random.randn(i))

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To see simple statistics, run without arguments:

$ python profile_cch.py

To save results to file, provide a filename: 

$ python profile_cch.py my.csv

You can compare results from different version. First checkout a different branch of elephant, then run the benchmark again:

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try:
    from urllib.parse import quote  # Py 3
except ImportError:
    from urllib2 import quote  # Py 2
import os
import sys


BLOG_DIR = os.environ['BLOG_DIR']
# BLOG_DIR = '/Users/cscorley/git/cscorley.github.io/'

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