Thinking Graphically - Biology Courses Server

Biology 7964 - Biology Bootcamp
Fall 2012
Week 3: Thinking Graphically
Instructor: David P. Goldenberg
Office: 326A Aline Skaggs Biology Building
E-mail: goldenberg@biology.utah.edu
I. For class on Monday, 10 Sept., please:
A. Read the first two sections (through page 17) of the booklet “Designing science graphs
for data analysis and presentation: The bad the good and the better”. See below.
B. Find two examples of graphs from published papers, one that you think is very good and
one that is very bad. (Taste in scientific illustration can vary greatly, so don’t worry too
much about whether other people will agree with your choices.) Please E-mail these (as
image files less than 1 MB in size) to me at the address above, with a clear indication
of which is which.
C. If you have a laptop computer, download and instal a demo copy of the program
KaleidaGraph, from http://www.synergy.com/downloads.htm
Versions are available for both Windows and Mac. We will use this program to explore
some basic principles for making good graphs, as well as variations on graphing style.
This is not meant as an endorsement of KaleidaGraph, but it does have a number of
virtues, including a reasonable price and a free demo version.
II. Resources on preparing graphs. Most of these were found from a quick internet search.
A. “Designing science graphs for data analysis and presentation: The bad the good and
the better” by Kelly, Jasperse and Westbrooke, from the New Zealand Department of
Conservation and available at:
http://www.doc.govt.nz/upload/documents/science-and-technical/docts32entire.pdf
This free publication is concise and, from quick examination, full of good information
and advice.
B. The books of Edward Tufte, http://www.edwardtufte.com.
Tufte is widely viewed as the high priest of graphical data presentation, and has published
several beautiful books, starting with his classic ”The Visual Display of Quantitative
Data”. In addition to the full books, which are rather expensive, Tufte has published
two smaller booklets that are very good:
1. Visual and Statistical Thinking: Displays of evidence for making decisions.
http://www.edwardtufte.com/tufte/books_textb.
This is a chapter from one of the books and discusses two historical examples in
which graphical presentations played important roles: The cholera epidemic of 1854
and the Challenger space shuttle accident of 1986.
2. The Cognitive Style of PowerPoint: Pitching out corrupts within
http://www.edwardtufte.com/tufte/books_pp
Everyone should be required to read this before being allowed to use PowerPoint!
Jon Seger’s personal copies of four of Tufte’s books will be placed in room ASB 308.
Karen Zundel’s office. Please contact Karen Karen Zundel (zundel@biology.utah.edu) if
you would like to borrow them. Be very careful with these!
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C. ”The Top Ten Worst Graphs” at http://www.biostat.wisc.edu/~kbroman/topten_
worstgraphs/
Do you agree? Do not use one of these for the class assignment!
D. ”Visionlearning” http://www.visionlearning.com/library/module_viewer.php?mid=
156&l=
This page on graphing is part of an NSF-supported resource for science education. It’s
not so clear what audience this is meant for, but it looks quite good.
E. ”LabWrite Resources” http://www.ncsu.edu/labwrite/res/res-homepage.htm
This also is an NSF-supported resource, directed towards students preparing lab reports.
III. Software for scientific graphing and data analysis. There are many programs available for
making graphs, both commercial and free. So far as I can tell, there is no free program that
has all of the features and convenience of some of the commercial products, and different
programs have different strengths. The following are programs that I am familiar with and
that you may find useful. All of the commercial products are available as free trial versions.
A. Microsoft Excel (Commercial, of course, but available free to students) Some would gag
at the suggestion that Excel be used to make scientific graphs, and it is not something
I do or encourage. But, Excel is ubiquitous, and with care it can be used to make
graphs suitable for scientific publications. The booklet ”Designing science graphs for
data analysis and presentation” includes an appendix describing how to turn Excel’s
default charts into respectable graphs.
B. KaleidaGraph (Commercial, about $140 for academic use). Available for both Windows
and Mac computers. This program combines a relatively simple user interface with the
ability generate and fine tune the various standard graph types. It also has moderately
powerful data processing tools and excellent tools for curve fitting, including non-linear
least-squares fitting to user-defined functions. A limitation is that KaleidaGraph cannot
generate 3-dimensional graphs.
http://www.synergy.com.
C. Igor Pro (Commercial, $435 for academic use). Available for both Windows and Mac
computers. This is a major step up from KaleidaGraph, in price, capabilities and complexity.
The learning curve is somewhat steeper than for simpler programs, but this
comes with more flexibility and more sophisticated data processing and analysis. Igor
Pro has its own macro programming language, which is quite powerful, but I don’t find
it particularly elegant or easy to work with.
http://www.wavemetrics.com
D. DeltaGraph (Commercial, $199 for academic use). Available for both Windows and Mac
computers. I have not used this much, but it seems roughly comparable to KaleidaGraph,
but with the ability to make 3-dimensional graphs and generally flashier graphics.
http://www.redrocksw.com.
E. Origin and Origin Pro (Commercial, a one-year student license is available for $69). For
Windows only. I have relatively little experience with this program, but my impression
is that it has capabilities similar to those of Igor Pro.
http://www.originlab.com
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F. SigmaPlot (Commercial, $549 for academic use). For windows only. Again, I have
limited experience with this program. Its capabilities seem similar to those of Kaleida-
Graph.
http://www.sigmaplot.com
G. Plot (free). For the Mac only. This is a quite polished and capable program, though it
does seem to have a slightly complicated interface. If I were not already a heavy user of
other programs, I would give this a serious try.
http://plot.micw.eu/
H. MjoGraph (Free). For Windows and Mac. This is a simple, cleverly designed program
that plots data from plain text files (which can be generated in a word processor or text
editor, or from another data-handling program). Though not as feature laden as most
other graphing programs, it has considerable flexibility for manipulating the appearance
of the graphs. Unfortunately, it seems to be broken on my Mac with OS X 10.7.
http://www.ochiailab.dnj.ynu.ac.jp/mjograph/
I. GnuPlot (Free, open source) Can be compiled on almost any computer, and pre-compiled
binaries are available from various sources. This program is run from a terminal command
line or from scripts, making it somewhat less user-friendly than programs with
graphical interfaces. However, GnuPlot produces excellent graphs, and working from
a command line or scripts can, for some purposes, actually be more efficient than a
graphical interface. The 3-dimensional surface and contour graphs are particularly nice.
It also includes curve-fitting tools, though I have not used them.
http://www.gnuplot.info/
J. QtiPlot and SciDAVis (free, open source) Source code and binaries available for Windows,
Mac and Linux systems. These are two ”branches” of an open source project that
apparently suffered from conflicts between developers with different philosophies and
motivations. They might be the closest thing available to a free, full featured graphing
and analysis program with a graphical user interface. QtiPlot is, as I understand it, the
original project. At some point, the author, Ion Vasilief, decided to provide the compiled
binaries along with support for a fee. This is consistent with open-source licenses, but it
apparently led to dispute with other developers, who started a new project, SciDAVis.
QtiPlot binaires can be obtained from other sources. I have played with these a bit, and
they seem quite promising. But, both are still buggy, and the development, at least for
SciDAVis, is not very active. The compiled SciDAVis binary available at the site below,
seems to work on my Mac with OS X 10.7 (Lion), but not on one running 10.6.8 (Snow
Leopard). I don’t have experience with other versions or operating systems. Compiling
these yourself is not for the faint of heart.
QtiPlot: http://soft.proindependent.com/
SciDAVis: http://scidavis.sourceforge.net/
K. R (Free, open source) Available for all major operating systems. R is described by the
developers as ”a free software environment for statistical computing and graphics”. It
appears to be gaining rapid popularity among scientists who rely heavily on statistical
methods, including ecologists in the Biology Department. It can produce excellent
graphs, though perhaps not as easily as with dedicated graphing programs.
http://www.r-project.org/
L. MatPlotLib for Python (Free, open source). Available for all major operating systems.
If you are using the Python computer language to generate, process or analyze data,
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MatPlotLib provides a means of directly generating very nice graphs directly from a
Python program. The learning curve is pretty steep, however, and this is far from the
easiest way to make a simple plot from a small data set. For a complete installation of
Python and associated software for scientific computing, the best source is the Enthought
Python Distribution, which is available free for academic use.
http://www.enthought.com/products/epd.php
IV. Un-graphing software. Every once in a while, it is useful to be able to extract numerical data
from a graph; for instance, if you want to reanalyze published data. The first program that
I heard about for doing this is called UnGraph and is still available, but expensive ($300).
There are a number of other inexpensive or free alternatives, and these are just a few that I
found with an internet search.
A. GraphClick (Commercial, $8 for full-featured version). For Mac only. Nice interface and
easy to use. This is the program I use for un-graphing.
http://www.arizona-software.ch/graphclick/tour.html?page=4
B. Enguage Digitizer (Free, open source). For Windows only. I haven’t tried it.
http://digitizer.sourceforge.net/
C. Plot Digitizer (Free, open source). Java program with executables for Mac, Windows
and Linux. I haven’t tried it.
http://plotdigitizer.sourceforge.net/
D. WebPlotDigitizer (Free) As the name implies, this is a web application. I played with
this just a little bit, and it looks pretty neat.
http://arohatgi.info/WebPlotDigitizer/app/
E. ImageJ (Free, open source) Java program with executables for Mac, Windows and Linux.
ImageJ is a very powerful image analysis program that every scientist should be familiar
with. Digitizing a graph is just one thing it can be used for. For this application, use
the Figure Calibration plug-in.
ImageJ: http://rsbweb.nih.gov/ij/
Calibration plug-in:
http://www.astro.physik.uni-goettingen.de/~hessman/ImageJ/Figure_Calibration/
Step-by-step instructions:
http://lukemiller.org/index.php/2011/09/digitizing-data-from-old-figures-with-imagej/
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