Professor Ripley,
Thanks for your suggestions. I will look into the package approach.
As far as the "source" speed issue, you suggested that the problem may
relate to guessing encodings so I added:
options(encoding="UTF-8")
at the beginning of the code (was this the correct approach to the
problem?). That did not make any obvious difference to the duration
to source the script. Do you have an specific suggestions that might
speed the process?
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
On Jan 9, 2010, at 8:53 AM, Prof Brian Ripley wrote:
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
______________________________________________
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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.
