Please just use make a package; then all the effort of parsing the
code is done at install time, you can use lazy-loading .... Or if you
are for some reason averse to that, source the code into an
environment, save that and simply attach() its save file next time.
Packages of that size load in a few milliseconds (as you see each time
you start R: stats is 27000 lines).
source() is doing more work to allow it to guess encodings, keeping
references to the original sources, back out code if the whole script
does not parse ....
On Sat, 9 Jan 2010, Dennis Fisher wrote:
Colleagues,
(R 2.10 on all platforms)
I have a lengthy script (18000 lines) that runs within a graphical interface.
The script consists of 100's of function followed by a single command that
calls these functions (execution depends on a number of environment variables
passed to the script). As a result, nothing is executed until the final line
of code is read. It takes 15-20 seconds to load the code - I would like to
speed that process. Two questions:
1. The code contains numerous large blocks that are executed under only one
set of conditions (which are known when the code is called). For example,
there might be code such as:
if (CONDITION)
{
... (hundreds of lines of code, including embedded curly
brackets)
} else invisible()
if (!CONDITION)
{
... (hundreds of lines of code, including embedded curly
brackets)
}
I assume that I could speed loading appreciably if I set up two scripts, each
of which excluded "irrelevant" code depending on the CONDITION. For example,
if I knew that CONDITION was false, I would exclude the first block of code
above; conversely, if I know that CONDITION was true, I would exclude the
second block.
I would like to write code in R (or in sed [UNIX stream editor]) to create
these two new scripts. However, the regular expressions that would be needed
are beyond me and I would appreciate help from this forum. Specifically, I
would like to search for:
if (CONDITION
or
if (!CONDITION
as the start of the block and
} - the matching curly bracket
at the end of the block, then remove those lines from the code. These text
entries are always on a line by themselves. Finding the "if (CONDITION" line
should be relatively easy. The difficulty for me is identifying the matching
curly bracket - there are often paired brackets within the block of code:
if (CONDITION)
{
...
if (SOMETHINGELSE) { }
if (YETANOTHER)
{
}
} <- this is the bracket that
I need to match
There are also instances in which the entire block occurs on one line:
if (CONDITION) { ...} else invisible()
or
if (CONDITION ... else invisible()
Of note, I can remove the "else invisible() statements if they are
problematic to a solution.
2. A related issue regards loading in the graphical interface vs. loading at
the command line (OS X). The graphical interface loads in 15-20 seconds -
the graphical interface is sending code as rapidly as it can. In contrast,
at the command line, the course is source()'d and it takes 30-40 seconds. I
would have expected the latter approach to be as fast or faster because R
would accept code as fast as it could.
Does anyone have an explanation for this behavior; also, any ideas as to how
to speed the process at the command line would be appreciated. Thanks for
any suggestions.
Dennis
Dennis Fisher MD
P < (The "P Less Than" Company)
Phone: 1-866-PLessThan (1-866-753-7784)
Fax: 1-866-PLessThan (1-866-753-7784)
www.PLessThan.com
______________________________________________
R-help@r-project.org mailing list
https://stat.ethz.ch/mailman/listinfo/r-help
PLEASE do read the posting guide http://www.R-project.org/posting-guide.html
and provide commented, minimal, self-contained, reproducible code.
--
Brian D. Ripley, rip...@stats.ox.ac.uk
Professor of Applied Statistics, http://www.stats.ox.ac.uk/~ripley/
University of Oxford, Tel: +44 1865 272861 (self)
1 South Parks Road, +44 1865 272866 (PA)
Oxford OX1 3TG, UK Fax: +44 1865 272595
______________________________________________
R-help@r-project.org mailing list
https://stat.ethz.ch/mailman/listinfo/r-help
PLEASE do read the posting guide http://www.R-project.org/posting-guide.html
and provide commented, minimal, self-contained, reproducible code.
