Caleb Madrigal

Programming, Hacking, Math, and Art


Fuel efficiency difference cost

I recently was car shopping, and I had the question about gas mileage: "How much does, say, the difference between 25 mpg and 30 mpg cost?"

To answer this question, I did a bit of analysis using IPython Notebook...


  • To find how much different fuel efficiencies cost in terms of dollars per year.
  • I want to estimate this value for the next 10 or so years.


  • I'm estimating the average price per gallon of gas (over the next 10 years) to be $4.50. It is around $3.60 now, I adjusted for inflation, and counter-adjusted for the time-value of money.
  • I'm estimating that we will drive about 14,000 miles per year (based on the last 3 years).


In [1]:
price_per_gallon = 4 ...

How To Draw Lines With Matplotlib

Simple example to show how to draw lines with Matplotlib (in IPython Notebook).

ipython notebook --pylab inline

In [5]:
import matplotlib.lines as lines
fig, ax = plt.subplots()

fig.set_size_inches(6,6)          # Make graph square
scatter([-0.1],[-0.1],s=0.01)     # Move graph window a little left and down

line1 = [(0,0), (1,0)]
line2 = [(0,0), (0,1)]

# Note that the Line2D takes a list of x values and a list of y values,
# not 2 points as one might expect.  So we have to convert our points
# an x-list and a y-list.
(line1_xs, line1_ys) = zip(*line1)
(line2_xs, line2_ys) = zip(*line2)

ax.add_line(Line2D(line1_xs, line1_ys, linewidth=2, color='blue'))
ax.add_line(Line2D(line2_xs, line2_ys, linewidth=2, color='red'))
Read On ↵

IPython Notebook on a VPS


This is a guide to set up IPython Notebook on a Server - specifically, on a DigitalOcean VPS. This will allow you to access your iPython Notebooks from anywhere.

Overview of Steps:

  • Set up a domain name
  • Get a VPS
  • Install IPython Notebook (and all dependencies)
  • Configure IPython Notebook to run in a server mode
  • Add SSL
  • Make IPython Notebook start automatically

Create a domain

Go to and click "Setup an account here" Go through the signup form Click on the activation link they send to your email This will bring you back to their site; Click the link you see there called "Add a subdomain" Here is how I filled out the form:

Create Domain


  • Leave the Destination alone for now, and leave the ...

Big graphs in IPython Notebook

I've been doing a good bit of graphing in IPython Notebook recently, and I often wanted to make the graphs larger. I also often wanted to label the graph axes. So I wrote this simple function and have been using it a lot.

# Graphing helper function
def setup_graph(title='', x_label='', y_label='', fig_size=None):
    fig = plt.figure()
    if fig_size != None:
        fig.set_size_inches(fig_size[0], fig_size[1])
    ax = fig.add_subplot(111)

Here's a demo of using it...

In [27]:
x = linspace(0, 2 * pi, 1000)
y = 5 * sin(1 * 2*pi*x) + 4 * sin(2 * 2*pi*x)

Without setup_graph()

In [24]:
_ = plot(x, y)
Read On ↵

How to graph with IPython Notebook

IPython Notebook / Matplotlib / Pylab / Numpy is great for graphing (among other things). Below is a simple demo of how to graph with it.

To run IPython Notebook, use this command: ipython notebook --pylab inline

Here's a screenshot:

IPython Notebook Example

Here's an embedded IPython Notebook showing a slightly easier way:

In [5]:
x = linspace(0, 2*pi, 42)
f1 = 5 * sin(x)
f2 = 2 * sin(2*x)
f3 = 1 * sin(3*x)
plot(x, f1)
plot(x, f2, 'ro')
plot(x, f3, 'g--')
Read On ↵

First look at Pylab/Matplotlib

Since I've been getting into Machine Learning/Artificial Intelligence recently, I've been looking at various computing environments recently. Some of the contenders are:

  • MATLAB - The traditional software stack for doing machine learning and statistical analysis
  • GNU Octave - An open-source MATLAB clone.
  • R - An open source clone of a statistical computing environment called S.
  • Julia - A language for doing statistical analysis. The goals are to compete with Matlab and R.
  • Matplotlib/Pylab/SciPy/NumPy - see below

Of these, I've tried Octave and Matplotlib. Matplotlib/Pylab is the software stack consisting of:

  • IPython - an interactive REPL for Python with things like tab completion
  • Matplotlib - a graphical plotting library
  • NumPy - a matrix library
  • SciPy - a collection of scientific and mathematical algorithms

I've only played with Matplotlib/Pylab ...