This guide will help you compile the CFAST executable on Mac OS X and Linux. This is useful for running CFAST cases on Mac or Linux machines, which is especially useful for scripting CFAST runs for optimization problems or running CFAST on a large number of cases in batch mode.

You will need the Intel Fortran compilers (ifort) and a copy of the CFAST source code from the CFAST Google Code site. You can try to use other free compilers, but I find that the Intel compilers are the most compatible and produce the most optimized (fastest) binaries. Note: there are heavily discounted Intel compilers for students.

To download the CFAST source code, the easiest way is to install subversion on your Mac or Linux machine and issue the following command:

svn co http://cfast.googlecode.com/svn/trunk/ cfast

Once you have the CFAST source code on your machine, you can perform the following steps to compile the CFAST executable.

1. In the cfast/CFAST/ directory, edit the makefile_linux file and make the following changes:

• Replace ‘radation’ with ‘radiation’; this is a typo
• Add ‘cyl_conduct.o’, ‘datamodules.o’, and ‘ssHeaders.f’ to the obj_serial section
• Add the following lines to the Object Dependencies section:
• cyl_conduct.o : cyl_conduct.f
• datamodules.o : datamodules.f90
• ssHeaders.o : ssHeaders.f
• Add ‘cyl_conduct.f’, ‘datamodules.f90′, and ‘ssHeaders.f’ to the cfast.o line

Note: The corrected makefile can also be downloaded from here.

2. Copy datamodules.f90 from the cfast/CFAST/Include/ directory to the cfast/CFAST/Source/ directory

3. Change to the cfast/CFAST/Source/ directory

4. Run the command ‘ifort -c datamodules.f90′ to compile the datamodules and iofiles modules

5. Finally, run the command ‘make -f ../makefile_linux intel_osx_64’ to build CFAST

5b. If you are running Linux, the command is ‘make -f ../makefile_linux intel_linux’

Using these steps, I was able to build CFAST on an Intel Macbook Pro running 10.6 (Snow Leopard) as well as a Linux machine running CentOS release 5.6 with the 64-bit Intel Fortran Compiler version 12.0.4.184.

Related posts:

1. Mac-Corrected Numerical Analysis Fortran Programs
2. How to install PyObjC, pygame, and gasp on Mac OS X for Python tutorial

http://www.koverholt.com/flame-height-and-plume-centerline-temperature-calculator/

Please let me know if you find any bugs, would like to give feedback on this tool, or have a request for another web calculator!

Related posts:

1. New web calculator tool – transient steel heating under fire conditions
2. New web calculator – t-squared fire ramp generator
3. Plotting data on videos – A useful way to convey qualitative and quantitive information

http://www.koverholt.com/transient-steel-heating-under-fire-conditions/

I hope you find the calculator useful, and I will continue to add web tools for fire protection engineering calculations. I will be adding a more detailed explanation and equations to the steel heating calculator page in the near future as well as releasing the source code.

Please let me know if you find any bugs, would like to give feedback on this tool, or have a request for another web calculator! The next web tool will be a calculator to give results from the Heskestad flame height and centerline temperatures.

Related posts:

1. New web calculator – flame heights and plume centerline temperatures
2. New web calculator – t-squared fire ramp generator
3. Plotting data on videos – A useful way to convey qualitative and quantitive information

Every once in a while, someone makes an impression on you that lasts for a lifetime. It sticks with you every single time. This is one of those, although a bit on the nerdy side, it is one that can change the way you present information in a very meaningful way.

I was once sitting at the NIST annual fire conference, going about my business, and someone working on a project regarding the structural response aspect of buildings on fire showed a video in their presentation. No big deal, right? Normally, we get cool fire videos, then some plots, and so on. Sometimes the plots are interesting, sometimes they are default from Excel with the ugly legend and all – with no story to tell.

But not this guy. He showed a video with real-time plots superimposed over the video showing the exact real-time structural response of the structure overlaid on the video in a plot. “AMAZING!” I thought. And it stuck with me. A useful way to convey synchronous information. People love videos, why not tell the qualitative AND quantitative story at the same time?

So I started working in grad. school on fire problems, and naturally, soon thereafter, I was scheduled to give a presentation. As most of my real creative coding and writing work happens of hours between the hours of 1 AM and 6 AM, I wanted to make this happen. I REALLY wanted some real-time plotting action in my presentation. No Excel templates for me! So I stayed up for a couple nights and worked on a way to use MATLAB to make this plotting dream a reality: I worked on importing videos, messing with frame rates, tons of images, and so forth. And soon thereafter, it happened. I had a working script.

I used it to show plots of large-scale fire tests with actual and predicted flame heights vs. time as seen here:

And I used the script to show the predicted flame heights on a small-scale test in an amazing way that just about anyone can relate to, fire-crazed scientist or not:

From anyone who has seen the videos firsthand, the response has been amazing. This is a great teaching and communication tool, and surprisingly enough, I haven’t found any existing program or tool that does this. And so I am sharing the videos and script here for anyone to use to better convey information.

My next steps are: 1) to convert the script to Python (since I am now almost exclusively using Python+numpy+scipy for my graduate research and daily work instead of MATLAB, and 2) to make the script into a cross-platform and easy to use tool.

I’m providing the code in its raw and uncommented and unedited form. It generates a number of images with plots superimposed on them, and then it is trivial to use a program to stitch them together into a video. I used Quicktime’s built in method. Sorry, too much current work going on finishing my MS thesis and Master’s degree to clean up the code, but it’s a brutal use of the “release early, release often” ideal! Hopefully someone can make some use of it.

So, here are the linked .m files:

http://www.koverholt.com/scripts/ssPlotVideo.m
http://www.koverholt.com/scripts/fireplotVideo.m

Enjoy! And please leave your comments or ideas!

Related posts:

1. New web calculator – flame heights and plume centerline temperatures
2. Passionate and Artful Communication in Science
3. New web calculator tool – transient steel heating under fire conditions

[From NASA]

So, let me explain his model simply by example:

The professor said that when he first started this class 2 years ago, the students were working on a different problem with no solution… at the time. The class worked together and in the end the results were so significant that a couple of students took the initiative to publish the results in a scientific journal. The same happened when the class was taught last year – project done, paper published.

So what does this mean and why do you care? Well, all too often in the academic world, people can get caught up in working on projects and sort of work themselves into a dark corner where nobody gets to benefit from the results… and this is done in real life as well, not just academics. This is where the ridiculous amount of collaborative technology available to us comes in to play. Want to gather up notes on the Smagorinsky constant and publish them for anyone to find who is searching for them in the next 1000 years? Easy: 5 minutes. Want to publish your results in the most useful way? Easy: work on an open source project in your area along with your research – or make your own.

…Or you could write a paper, finish your thesis work, wrap up the loose ends in a few years and show a flashy poster of your work 5 years after anybody cares about it anymore or thinks it to be useful.

I digress. I just wanted to stress this new method of collaboration that is among us, and how it’s going to change the way that we work together and grow together in fire protection engineering and fire science.

[From Rowan University College of Engineering]

Why not make use of motivated students and brainpower when they come together? Here is me welcoming this new phase of community and collaboration in a field that directly impacts life safety and makes safer buildings around the world. So when we work on that final project in a few weeks, it’s not really at all about a grade anymore – it’s about a new way of doing science – together.

Update: This is exactly the kind of stuff that I’m talking about here, posted today on the SFPE National blog that I set up a year ago – collaboration: Foundation Funded Research underway at WPI

Related posts:

1. The human element in fire protection engineering
2. Why Do I Chase Fire? (and video)
3. Updates on welcomed unstability

Well, why do you care about my graph? I certainly do. There are many books about conveying information in statistics and how to present data in a very informationally dense format, sure. But let’s think about this graph that I made for a homework assignment. The purpose of the homework was for me to learn, yes? And that nice orange line bought me some extra credit worth 25 points, but that’s another story. I want to learn it inside out, run it amongst others, and in the end communicate great things to many, many people. Every time. With every action.

So I could have left the default Excel settings for the chart, but my soul cannot allow such a thing.

This graph shows relationships, it runs a conversation with itself and lets the numbers drive by each other and say hello. It’s living, and it talks to me. Check out the dark red diamond line called “Mixture Fraction”. This guy drives all of the others. Then the f’s come in. Then we go back to the real quantities like the mass fraction of oxygen (Yo) and fuel (Yf) and we can also grab temperature (in Kelvin) based off of what those f’s are telling each other.

Yes, yes, Kris. You are talking nonsense, I don’t like it. Well, perhaps I’m not as eloquent and direct as this guy (watch this great motivating video, do I ever let you down?):

But our messages are the same. Do what you love, and work your ass off at it. All the time. Not the old and dead cliched way of “do what you love” – but the minute by minute, day by day, just got home tired from work but I need more, but I don’t have the time, wake up and do it, it keeps you up and night, but I want to watch TV every day, what you REALLY want to do, an exact thing/action/pursuit every day until you die – kind of way.

If I wasn’t here loving my graphs at 2:34 AM in the morning and pondering the million things I just learned from this 4 day exercise, I’d quit. If I doubted for a second (as the guy in the video says), I’d do us all a favor and leave here. But I want this knowledge, and these relationships so very badly. And when the end-result comes along, I have a sick urge to spend so much time and detail on things so that others may benefit. Make your life, thoughts, and business public, and see what happens to it. It skyrockets.

Now do you see why I care about my graph? I’m proud of what it represents. Now go off and care about your own graph. For the rest of us.

Related posts:

1. Why Do I Chase Fire? (and video)
2. 18 minutes with an agile mind – video
3. Not Working

It’s a long, slimy article, I know. But if you can take time out of your day to read it… well, time out like time out to watch the previous video I posted, you know. Speaking of time, it tends to dilate depending on what you are doing – there is some correlation there based on how uncomfortable I feel before I do something versus how satisfying it is. We humans are built weird like that.

In other news, I took the Fundamentals of Engineering exam on Saturday, and wow. I cannot discuss the questions and stuff there lest NCEES sues me and makes me homeless, but that was the hardest thing that I have taken in my life. It was at the George R. Brown Convention Center with what looked like 800-900 students and, according to the NCEES stats, about 560 future engineers. I would show pictures but any phone or camera device would have you banned from the building and have you $130 lighter for no good reason. Anyway, about the test: this is why you have to kick ass in school, students. The test is the connector to the reality that is real-world problems.

Otherwise, I am off to sleep for another night. This week I will be working on a cross-platform launcher for Fire Dynamics Simulator, since the command line scares or hinders our users. In Python, of course. Python and Fortan, the story of my life.

Related posts:

1. How to remove yourself and your thoughts from this world
2. Updates on welcomed unstability

Along the way during the past month, I have sifted through hundreds of websites and quite a few beginner books. So here, I would like to share the links that I found most helpful in my quest for Python knowledge. As far as my past experience, I’ve dabbled in many other languages such as MATLAB, HTML, Fortran, C++, Java, Perl, and so on but never really grew to master a single one or use it in my daily life.

So, without further delay, on to the list:

Before You Start With Python

1. Python.org – I couldn’t make this list without including the main Python site. There is just a great amount of information there. Plus everything I link to can probably be found there, but my list is only those resources that really helped me along in my learning experience.
   
2. Teach Yourself Programming in Ten Years – Article by the director of research at Google – A great overview of programming and learning to program, all the while avoiding the ides presented by the “Learn to program in X days” books.

Excellent Python Tutorials

1. Dive Into Python – This is one of the first tutorials that I read about Python, and it gave me an excellent overview of the language. It really broke down the code line-by-line, but it still reads like a mix between a reference guide, a cookbook, and a tutorial. It’s a freely available book and should definitely be within quick reach as you learn Python.
2. How to Think Like a Computer Scientist – This is by far my favorite tutorial in the entire list. I like this (freely available) book because of its plentiful and challenging exercises! I am usually picky when choosing textbooks on a new subject, and I will almost always get the book that has the most examples in it. I spent most of my time creating my own programs at the end of each chapter, and really got a feel for the language (and a nice sense of accomplishment!) at the end of each chapter. Highly recommended.
3. Python Videos at ShowMeDo – There are over 100 videos at the time of this posting over a wide range of topics. Anything from how to open a Python session to namespaces and more. It was nice when starting out to just sit and watch someone who knew what they were doing do routine tasks, and it helped to ground basic concepts before jumping in on my own. Don’t forget to thank the creators of the videos with a comment!
4. Learning to Program – This is one that I am going through last, because it gets into a bit more in depth discussion about basic and moderate topics. Very thorough.
   

Beginner Exercises and Projects

1. How to Think Like a Computer Scientist – I just HAD to list this again, because it goes at just the right pace and the exercises are well thought out. I am convinced that I really learned about 80% of my Python basics here when I put them to practice. Learn by doing!
2. Projects for the Beginner – Python – This is a thread on a forum with over 100 ideas for programs. Use this when you are low on inspiration but high on ambition!
3. Python Challenge – Neat implementation of puzzles that can be solved with Python scripts. They get harder as you progress levels. You might want to hit up the Python Challenge after getting a good hold on the basics and after you have many of these other links open in other tabs.
4. Useless Python Challenges – This site should be visited after you have finished all of the trivial Python exercises and projects. When you are self-sustaining on the language and eagerly looking for some projects to do, but are hitting a writer’s block for programs, go here.

Beginner Forums and Lists

1. Python Forum – Beginners – Not a very high traffic forum, but they have a beginners subforum with 15-30 posts per day, just enough to keep you busy. I find it helpful to attack the problems that other beginners are facing. And if you come up with a good solution, post it and help others while you learn. Everyone wins!
2. Learning Python Blog – One of the few “learning only” Python blogs. It is always good to see information shared from others while they learn. Sort of like this list.
3. Python Tutor Mailing List – I only recently signed up for this, but I must say that there are some very knowledgeable and helpful people on here and it keeps the Python information coming at you via email. Seems to be quite a few students on here and you will most certainly learn something with each email thread.

Interesting Python Projects and Libraries

1. Django Project
   
2. TurboGears
3. Google GData Python API – This is an amazing API from Google that allows you to interact with Google Calendar, Docs, Maps, Youtube, Notebook, and so on. It is very easy to install and use and I look forward to developing with this in the near future.
4. wxPython – GUI toolkit for interface development. I haven’t gotten to GUIs yet, but everywhere I turn I see references to wxPython.
5. matplotlib – 2D plotting library that produces very nice looking graphs. Supports many, many types of graphs and is very customizable.
6. SciPy – A collection of Python tools and modules for use in science, engineering, and mathematics. This is the light at the end of the tunnel for me and I hope to get more involved with this library as I progress with my Python learning.

Editing Tools and Shells

1. iPython – An enhanced Python shell that seems geared towards science, engineering, and high performance computing.
2. TextMate (Mac OS X) – This is such an amazing editor that I must list it here. I didn’t use it at all before I started with Python, and now I simply cannot go without it. I had previously heard it described by programmers as a magical tool, but I had no idea. It does autocompletion based on previous words, syntax highlighting for a ton of languages, has a quick and easy-to-read method to execute Python scripts. It is perhaps the only non-free item in my list, but very much worth it!
   
3. TextWrangler (Mac OS X) – This is what I used for a couple of years… until I discovered the greatness of TextMate a few weeks ago. TextWrangler is free though if you wish to use it.

Other Resources (References, Packages, Hosting)

1. Python Library Reference – Huge list of explanations about Python’s Standard Library. Made to help you discover the power of Python in your everyday programming.
2. Python Webhosting – List of webhosts that offer Python solutions on their webhost. Python can be run on most hosts via CGI, but these wiki pages explain exactly how they implement Python usability. Plus I found out about the cool idea of HCoop cooperative web hosting through this list; this is the host on which you are reading this blog.
3. Python Package Index – Directory of Python packages that you can learn about, download, and use in your own programming. Don’t reinvent the wheel!
4. Python Cookbook Code Samples – This is a directory in the same vein as the previous listing, but the solutions to problems are presented as code with user comments. As of now there are over 2000 recipes.
5. The Daily Python URL – Just as it sounds. News about Python in compact form.

Again, while there are many, many other resources for learning Python, this is a list of my personal favorites. These are the specific sites that have been very helpful and impacting on my venture to learn Python. So while I may not have listed a particular item – I probably saw it, but didn’t get much from it at this time.

Finally, you must forgive me if I got some detail wrong. I am learning, after all! Hopefully this list will help new and moderate Python users to utilize some of the best (and free!) Python resources that others have put up for all to learn from. Thanks to those people who shared their knowledge. And have fun with Python!

Related posts:

1. How to install PyObjC, pygame, and gasp on Mac OS X for Python tutorial
2. The clarity of Python vs. the cloud of Perl
3. Python ImportError with backend_wx2.8 and wxPython when using Matplotlib

http://openbookproject.net/thinkCSpy/

However, when I got to chapter 8, my fun stopped right away. The author refers to a Python library called GASP (Graphics API for Students of Python) and gives an example and case study of a small game. The thing is, he doesn’t tell you how to install the module and it abruptly interrupts your lovely Python learning experience.

http://openbookproject.net/thinkCSpy/ch08.xhtml

I tried to use easy_install to install most of these, and it always ended up failing for some reason or another.

As I am using Mac OS X Leopard, I will provide the missing instructions for how to get the gasp module installed (and its dependencies) for anyone else who runs into this situation:

How to install PyObjC, pygame, and gasp on Mac OS X

1. I assume that you have already installed some version of Python; I am using Universal Python 2.5 from http://www.pythonmac.org/packages/ which is a nice, easy-to-install package and has other prebuilt packages like numpy, wxPython, matplotlib, etc. ready to be installed. You can see other ways to get Python on your Mac at http://wiki.python.org/moin/MacPython/PythonDistributionsForMac
2. You will need to install PyObjC, which is also available as a package from http://www.pythonmac.org/packages/ under the 2.5 link.
3. Now, you will install pygame from a package (pygame-1.8.0rc4-py2.5-macosx10.4.mpkg.zip) available at http://rene.f0o.com/~rene/stuff/macosx/. This is linked from http://www.pygame.org/download.shtml
   
4. Finally, we get to the part of installing gasp, which is confusing to find in itself. The FAQ page is at https://answers.launchpad.net/gasp-code/+faq/42 but the link to download is wrong. Get it from https://launchpad.net/gasp-code/+download. You will want to download the Code Release which is currently called python-gasp-0.1.1.tar.bz2.
5. Extract the bz2 file and there will be a folder inside called gasp. Copy this folder to the /Library/Frameworks/Python.framework/Versions/2.5/lib/python2.5/site-packages/ directory and you will be in business!

   This is the command that I used: sudo cp -R ~/Desktop/python-gasp-0.1.1/gasp/ /Library/Frameworks/Python.framework/Versions/2.5/lib/python2.5/site-packages/gasp

6. Open a python session and type import pygame and import gasp to make sure that they are installed correctly.
7. Carry on with the great tutorial linked above!

I found it odd that the beginners tutorial left out all of this information. Hopefully this will save someone the two days that it took me to find all of these links, packages, and methods.

Related posts:

1. The Golden Resource List for Python Beginners
2. The clarity of Python vs. the cloud of Perl
3. How to compile CFAST on Mac OS X and Linux

The book is good and has nice pseudocode examples throughout. It also has a companion website with all of the algorithms programmed in C, FORTRAN, Pascal, Maple, MATLAB, and Mathematica. For our assignments, we can use any program that we want, and I have been using MATLAB, FORTRAN, and Python as those make the most sense to me thus far in my computing experiences and are the most useful for my work.

However, the FORTRAN 77 programs on the website are programmed in such a way that they only work when using a FORTRAN compiler in Windows. At this time, my primary machine is an Apple Macbook Pro laptop, and I am using the Intel Fortran Compiler version 10.1 on OS X Leopard. When I try to compile the programs from the textbook website, I get errors. So, I went ahead and fixed the files so that they would work on with the Intel compiler on the Mac, and hopefully Linux as well.

The two problems were that:

a) The programs were trying to read and write to ‘CON’, which is a Windows specific way of writing to the command window console.

b) The programs had an extra line at the end and would crash the Intel compiler.

So, I fixed these errors in all of the programs and you can download the corrected files in .zip format from me and follow the instructions below to compile.

The original files are freely available from the author’s website here

Step 1: Download the above linked zip file of the corrected FORTRAN 77 programs

Step 2: Unzip the FORTRAN files. You will find several files with the .FOR extension.

Step 3: Run the Intel FORTRAN compiler using the command: ifort -f77rtl -o <outputname> inputfilename.
For example, to compile example 12.1: ifort -f77rtl -o alg121 ALG121.FOR.

Step 4: Make the output file executable with: chmod +x alg121

Step 5: Run the file with ./alg121

Step 6: Be sure to answer the first Y/N question with the y or n character in quotes, such as “y” or “n”

Step 7: Have fun learning numerical methods and dissecting the FORTRAN programs!

Related posts:

1. How to compile CFAST on Mac OS X and Linux
2. The Big Move to MA
3. How to install PyObjC, pygame, and gasp on Mac OS X for Python tutorial