Archive for the ‘Languages’ Category.
Apr 30th, 2010| 12:12 pm | Posted by vlk
Sherpa is a fitting environment in which Chandra data (and really, X-ray data from any observatory) can be analyzed. It has just undergone a major update and now runs on python. Or allows python to run. Something like that. It is a very powerful tool, but I can never remember how to use it, and I have an amazing knack for not finding what I need in the documentation. So here is a little cheat sheet (which I will keep updating as and when if I learn more): Continue reading ‘Everybody needs crampons’ »
Tags:
Chandra,
cheat sheet,
ciao,
how to,
Python,
Sherpa,
Sherpa4 Category:
Algorithms,
Astro,
Fitting,
Jargon,
Languages |
2 Comments
Nov 13th, 2009| 04:46 pm | Posted by hlee
I was told to stay away from python and I’ve obeyed the order sincerely. However, I collected the following stuffs several months back at the instance of hearing about import inference and I hate to see them getting obsolete. At that time, collecting these modules and getting through them could help me complete the first step toward the quest Learning Python (the first posting of this slog). Continue reading ‘some python modules’ »
Tags:
APLpy,
AstroPy,
IDLsave,
import inference,
libraries,
modules,
package,
Pyfits,
PyMC,
PyRAF,
PYSTAT,
Python,
PyWavelets Category:
Algorithms,
Astro,
Cross-Cultural,
Data Processing,
Jargon,
Languages,
Methods,
News,
Stat |
2 Comments
Oct 26th, 2009| 10:41 pm | Posted by hlee
I’m very sure that Fortran is one of the major scientific programming languages. Many functions, modules, and libraries are written in this language. Without being aware of, these routines are ported into many script languages. However, I become curious whether Fortran is still the major force in astronomy or statistics, compared to say 20 years ago (10 seems too small). Continue reading ‘Do people use Fortran?’ »
Sep 11th, 2009| 03:40 pm | Posted by hlee
A number of practical Bayesian data analysis books are available these days. Here, I’d like to introduce two that were relatively recently published. I like the fact that they are rather technical than theoretical. They have practical examples close to be related with astronomical data. They have R codes so that one can try algorithms on the fly instead of jamming probability theories. Continue reading ‘[Books] Bayesian Computations’ »
Tags:
book,
BUGS,
CMB,
examples,
HMM,
identifiability,
image processing,
LLN,
mixture,
MRF,
R Category:
Bayesian,
Fitting,
Languages,
MC,
MCMC,
Methods,
Stat |
1 Comment
Jul 30th, 2009| 01:57 am | Posted by hlee
X={ primer, tutorial, cookbook, Introduction, guidebook, 101, for dummies, …}
I’ve heard many times about the lack of documentation of this extensive data analysis system, ciao. I saw people still using ciao 3.4 although the new version 4 has been available for many months. Although ciao is not the only tool for Chandra data analysis, it was specifically designed for it. Therefore, I expect it being used frequently with popularity. But the reality is against my expectation. Whatever (fierce) discussion I’ve heard, it has been irrelevant to me because ciao is not intended for statistical analysis. Then, out of sudden, after many months, a realization hit me. ciao is different from other data analysis systems and softwares. This difference has been a hampering factor of introducing ciao outside the Chandra scientist community and of gaining popularity. This difference was the reason I often got lost in finding suitable documentations. Continue reading ‘Where is ciao X ?’ »
Tags:
ciao,
cookbook,
documentation,
guide,
introduction,
matlab,
primer,
Python,
R,
SAS,
software,
Tutorial Category:
Cross-Cultural,
Languages,
Misc |
1 Comment
Nov 17th, 2008| 01:39 pm | Posted by hlee
The full description is given http://cxc.harvard.edu/ciao3.4/ahelp/bayes.html about “bayes” under sherpa/ciao[]. Some sentences kept bothering me and here’s my account for the reason given outside of quotes. Continue reading ‘It bothers me.’ »
Tags:
bayes,
ciao,
ML,
Sherpa Category:
Algorithms,
Astro,
Cross-Cultural,
Data Processing,
Fitting,
High-Energy,
Jargon,
Languages,
Methods,
Spectral,
Uncertainty,
X-ray |
4 Comments
Oct 27th, 2008| 11:05 am | Posted by hlee
The first step of data analysis or applications is reading the data sets into a tool of choice. Recent years, I’ve been using R (see also Learning R) for that regard but I’ve enjoyed freedoms for the same purpose from these languages and tools: BASIC, fortran77/90/95, C/C++, IDL, IRAF, AIPS, mongo/supermongo, MATLAB, Maple, Mathematica, SAS, SPSS, Gauss, ARC, Minitab, and recently Python and ciao which I just began to learn. Many of them I lost the fluency of how to use it. Quick learning tends to be flash memory. Some will need brain defragmentation and recovering time for extensive scientific work. A few I don’t like to use at all. No matter what, I’m not a computer geek. I’m not good at new gadgets, new softwares, nor welcome new and allegedly versatile computing systems. But one must be if he/she want to handle data. Until recently I believed R has such versatility in the aspect of reading in data. Yet, there is nothing without exceptions. Continue reading ‘read.table()’ »
Sep 16th, 2008| 04:34 pm | Posted by hlee
Astronomers tend to think in Bayesian way, but their Bayesian implementation is very limited. OpenBUGS, WinBUGS, GeoBUGS (BUGS for geostatistics; for example, modeling spatial distribution), R2WinBUGS (R BUGS wrapper) or PyBUGS (Python BUGS wrapper) could boost their Bayesian eagerness. Oh, by the way, BUGS stands for Bayesian inference Using Gibbs Sampling. Continue reading ‘BUGS’ »
Tags:
openBUGS,
PyBUGS,
Python,
R,
toolbox,
winBUGS Category:
Algorithms,
Bayesian,
Data Processing,
Languages,
MCMC,
Methods,
News |
Comment
Sep 5th, 2008| 08:46 pm | Posted by hlee
The problem with data analysis is of course that it is a performing art. It is not something you easily write a paper on; rather, it is something you do. And so it is difficult to publish.
quoted from this conversation Continue reading ‘A Conversation with Peter Huber’ »
Tags:
art,
Babilonian astronomy,
computers,
computing,
computing history,
conversation,
FFT,
history,
Peter Huber,
project pursuit,
robust statistics,
robustness Category:
Algorithms,
arXiv,
Cross-Cultural,
Data Processing,
Jargon,
Languages,
Quotes |
Comment
Aug 28th, 2008| 08:44 pm | Posted by hlee
Talking about limits in Numerical Recipes in my PyIMSL post, I couldn’t resist checking materials, particularly updates in the new edition of Numerical Recipes by Press, et al. (2007). Continue reading ‘NR, the 3rd edition’ »
Aug 27th, 2008| 08:08 pm | Posted by hlee
PyIMSL is a collection of Python wrappers to the math and statistical algorithms in the IMSL C Numerical Library[]. I recall the days of digging in IMSL (International Mathematics and Statistics Library) user manuals and learning Fortran and C to use this vast library (Splus was to slow at that time). Upon knowing that Python is very favored among astronomers (click here to see the slog posts about Python) and that limits exist in Numerical Recipes (I didn’t check the latest version published last year, though), probably IMSL is useful for mathematical and statistical analysis for astronomers.
To know more, Continue reading ‘PyIMSL’ »
Aug 13th, 2008| 12:59 pm | Posted by vlk
I grew up in an environment that glamourized mathematical equations. Equations adorned a text like jewelry, set there to dazzle, and often to outshine the text that they were to illuminate. Needless to say, anything I wrote was dense, opaque, and didn’t communicate what it set out to. It was not until I saw a Reference Frame essay by David Mermin on how to write equations (1989, Physics Today, 42, p9) that I realized that equations should be treated as part of the text. You should be able to read them. David Mermin set out 3 rules for writing out equations, which I’ve tried to follow diligently (if not always successfully) since then. Continue reading ‘I Like Eq’ »
Tags:
1989,
David Mermin,
EotW,
Equation,
Equation of the Week,
formatting,
Physics Today,
Quotes Category:
Jargon,
Languages,
Meta,
Quotes |
2 Comments
Jul 25th, 2008| 01:12 pm | Posted by chasc
Diab Jerius follows up on LOESS techniques with a very nice summary update and finds LOCFIT to be very useful, but there are still questions about how it deals with measurement errors and combining observations from different experiments:
Continue reading ‘loess and lowess and locfit, oh my’ »
Tags:
Diab Jerius,
error,
experimental error,
local regression,
locfit,
Loess,
Lowess,
observational error,
Ping Zhao,
question for statisticians Category:
Algorithms,
Cross-Cultural,
Fitting,
Jargon,
Languages,
Stat,
Uncertainty |
2 Comments
May 13th, 2008| 03:47 pm | Posted by hlee
The brackets could be filled with other languages but two are introduced today: Perl (perl.org) and Python (python.org). These two are widely used among astronomers and can be empowered by R (r-project.org). Continue reading ‘R-[{Perl,Python}] Interface’ »
Oct 5th, 2007| 04:47 pm | Posted by hlee
Not knowing much about java and java applets in a software development and its web/internet publicizing, I cannot comment what is more efficient. Nevertheless, I thought that PHP would do the similar job in a simpler fashion and the followings may provide some ideas and solutions for publicizing statistical methods through websites based on Bayesian Inference.
Continue reading ‘Implement Bayesian inference using PHP’ »
Tags:
Bayesian Inference,
Classification,
Condition Probability,
Estimation,
IBM,
JAVA,
Open Source,
PHP Category:
Algorithms,
Bayesian,
Cross-Cultural,
Data Processing,
Languages |
Comment