For the past few weeks we’ve been very busy here at Neurobat with the analysis of field tests results. In the process of doing that, we had to implement several functions in R that relate to building physics.

We thought it might be useful for the community to have access to those functions, so we decided to begin submitting them to CRAN. That’s why we’re pleased to announce the first release of the homeR package, which we will fill over time with such functions.

This first release, version 0.1, contains just `pmv`, a function to calculate the so-called Predicted Mean Vote, i.e. a measure from -3 (cold) to +3 (hot) of thermal comfort as a function of several variables, including air temperature, clothing and metabolism.

Here I show how with this function one can derive a contour plot showing, for given clothing and metabolism, the optimal indoor temperature (assuming 50% relative humidity). We’re basically going to solve `pmv(clo, met, temp, sat) = 0` equation for `temp` across a grid of `clo` and `met` values with the `uniroot` function.

> clo <- seq(0,2,length=21) > met <- seq(0.6,3.2,length=21) > zero.pmv <- function(clo, met) uniroot(function(temp) pmv(clo,met,temp,50), c(-10,40))$root > contourplot((outer(clo,met,Vectorize(zero.pmv))),
cuts=20,
aspect=”fill”,
panel=function(…) {
panel.grid(h=-1,v=-1,…)
panel.contourplot(…)
},
row.values=clo, column.values=met,
xlim=extendrange(clo), ylim=extendrange(met),
xlab=”[Clo]”, ylab=”[Met]”)

And here is the resulting plot:

As you can see, this is pretty similar to that sort of plots one finds in standard textbooks on the subject, such as Claude-Alain Roulet’s Santé et qualité de l’environnement intérieur dans les bâtiments:

Please give the `homeR` package a try, and give us your feedback. There’s only the `pmv` function in there at the time of writing but we plan to extend the package in the weeks to come.

I often need to edit files on remote machines or on embedded devices, that is, machines without a monitor and on which a proper editor might not necessarily be installed.

In the past that has always left me with the rather painful choice between vi and nano. Now I have never invested enough time in learning vi beyond the most basic editing commands. And nano is okayish for small edits but hopeless for larger ones.

So I was delighted to learn that you can edit files remotely through ssh with Emacs. If you want to remotely edit aFile on host aHost, open the following file:

/aHost:/path/to/aFile

The built-in Tramp package will take care of the rest. You can even use Dired remotely with this mechanism, an extremely powerful feature.

But what was missing for me was a painless way of editing remote files as root. The Tramp version that’s included in Emacs 22.2.1 was 2.0.57, with which I was unable to remotely edit files as root. The latest version of Tramp, 2.1.14, is in my humble opinion far easier to work with.

To install it, just follow the instructions. I created a directory ~/emacs into which I unzipped the Tramp distribution. I compiled it in place and did not bother installing it system-wide, being the only user of my system.

Then I added the following to my .emacs file:

;; Load most recent version of Tramp for proxy support
(add-to-list 'load-path "~/emacs/tramp/lisp/")
(require 'tramp)
(add-to-list 'Info-default-directory-list "~/emacs/tramp/info/")


With this in place, suppose you want to edit as root the files on aHost. The best is to add the following to your .emacs:

;; Setting for working with remote host
(add-to-list 'tramp-default-proxies-alist
'("aHost.*" "root" "/ssh:yourusername@%h:"))


Now editing remote files on aHost is easy, just open the following:

/sudo:aHost:/path/to/aFile

And that’s about it.

LXML is an amazing Python module that picks up where the standard xml.dom(.minidom) left off.

It’s basically a set of wrapper code around the libxml2 and libxslt libraries, and provides functionality missing in Python’s standard library, including XML validation and XPaths.

On a project I’m currently working on I needed a good XML library for Python and ended up trying out lxml. But I simply could not get the schema validation to work, and after several wasted hours I understood that the default lxml that ships with Ubuntu Hardy (the distro I’m using) used the relatively old 1.3.6 python-lxml package.

I’m usually very reluctant to install anything as root that does not come from the “official” repository, but for lxml I made an exception and installed the python-lxml package from the upcoming Intrepid distribution.

Add the following line to your /etc/apt/sources.list file:

deb http://ch.archive.ubuntu.com/ubuntu intrepid main

Then run Synaptic as usual and install python-lxml version 2.1.1. To verify that it works fine, you can test schema validation thus:

>>>> from lxml import etree
>>>> schema_tree = etree.parse('path_to_schema.xsd')
>>>> schema = etree.XMLSchema(schema_tree)
>>>> doc = etree.parse('path_to_some_document')
>>>> schema.validate(doc)


That last command returns as a boolean the result of the validation.