Submitting LaTeX Documents Done Easy

I have not submitted that many papers yet, but I am already frustrated enough with the process. Journals I am aware of do not accept pdflatex submissions, while arXiv.org has a strict file size limit (currently around 1MB). The former leads most of the figures to be in either EPS or PS format, while the latter would often benefit from adopting PDF or in some (rare) cases PNG format. On the other hand, I am vexed by the lack of full alpha channel support in PostScript type formats, thus I would personally prefer to use PDF and pdflatex in all cases. This would also get around the inevitable DVI to PS or PDF conversion that follows when using LaTeX. However, as pdflatex is not an option with the journals I submit to, I am stuck with (E)PS figures and the annoying conversion from DVI to something more often used (yes, the Device Independent file format was probably really cool in the beginning of 80s, but not so much in twenty-tens). Like this wound not be more than enough, due to reasons completely beyond my comprehension, some journals (I will not say which, most of you will know) require that the figures are named as “fig1″, “fig2″, etc. when submitting. While writing a paper my figures tend to shuffle around and some might even be omitted from the final version, I therefore tend not to name them like that, but use a naming scheme that, at least at times, seems more intuitive. Thus, I have found submitting a paper to a journal and uploading a version to arXiv.org to be a bit of a hassle.

To make the future submitting process less complicated I quickly wrote a brief Python script that helps when preparing a LaTeX document for submission. The script automatically renames figures and then updates the original tex file with the new names. It also strips any comment lines from the tex file to avoid embarrassing moments when someone looks your original tex file and sees all the ranting about the reviewer being an idiot. In addition, the script can optionally also convert all (E)PS files to PDFs and crop the bounding boxes more tightly. Finally, the script creates a single tar ball from all the files and checks the size of the submission so that it is easy to make sure that it won’t be too large for arXiv. Interested? I haven’t done extensive testing (who does such a thing?), but for your benefit you can download the script from here. Please note that if you wish to use the optional functionality to prepare your document for arXiv submission you should have GhostScript installed. It goes without saying that the script comes without any warranty, if it ends up gaining root access and doing “rm -rf /*” don’t come back crying… happy submitting!


Python and Cloud Computing

I ran in to  PiCloud already a long time ago when looking into Cloud Computing options for Python. Seems like an interesting service given that you pay as you use. It’s also nice to notice that PiCloud has partnered with Enthought, Inc., to bring NumPy, SciPy, and more to the cloud. If my memory serves Enthought contains also PyFITS, so it might be useful for heavy data processing if the local cluster is busy.

I wonder if anyone has actually tried PiCloud who could comment how well it works?


Getting Started

So, I am finally getting started with my new website. Lets see how long it will take to get this up and running. I did manage to add some content and links. I also uploaded the documentation of SamPy, although I suspect that it’s a little out of date. Uploading pictures however seem to work less than optimally. The slowness is likely due to the server and processing and resizing images.

Update: I gave up using the nextGEN gallery and created a flickr account to which the Photography tab now points to.