Hi Ruben,
I’m also interested in a lexer-parser for NONMEM. The regexp-based ones that I’ve used have typically had issues (I’ve tried about 4 different ones including one that I wrote), and they are working for many but not all models. I’m unaware of a reasonably complete lexer-parser for NONMEM (though I know of at least one non-public effort; I’ve contacted that author to see if he is interested in joining this conversation). I’ve wanted to build the abstract syntax tree for NONMEM to help with computational model-building, and I’ve been looking into ANTLR as well. Three questions: Are you interested in collaborating on the parser (can you create a GitHub project for it)? Why ANTLRv3 instead of v4? Do you have a way to get an ANTLR parse tree into R? Thanks Bill *From:* owner-nmus...@globomaxnm.com <owner-nmus...@globomaxnm.com> *On Behalf Of *Ruben Faelens *Sent:* Thursday, June 14, 2018 8:55 AM *To:* Tim Bergsma <tim.berg...@certara.com> *Cc:* nmusers@globomaxnm.com *Subject:* Re: [NMusers] Context-free lexer for NM-TRAN Hi Tim, Thanks for pointing to that. Unfortunately, nonmemica uses regular expressions to simply split the character stream into subsections. This is not the way to go. As an example, nonmemica would get confused by the following input: $PROBLEM This is a problem with special $PK section $PK ;Refer to $ERROR for more information CL=THETA(1) $ERROR Y = W*F Probably a contextual lexer is the way to go; fortunately ANTLRv3 has functionality for this. Kind regards, Ruben On Thu, Jun 14, 2018 at 12:42 PM Tim Bergsma <tim.berg...@certara.com> wrote: Hi Ruben. Related: the CRAN package “nonmemica” has a function as.model() that parses NONMEM control streams. Type “?nonmemica” at the R prompt after loading. See also https://github.com/MikeKSmith/rspeaksnonmem . Happy to discuss further. Kind regards, Tim *Tim Bergsma, PhD* Associate Director Certara Strategic Consulting [image: image001.png] m. 860.930.9931 <(860)%20930-9931> tim.berg...@certara.com *From:* owner-nmus...@globomaxnm.com <owner-nmus...@globomaxnm.com> *On Behalf Of *Ruben Faelens *Sent:* Thursday, June 14, 2018 4:33 AM *To:* nmusers@globomaxnm.com *Subject:* [NMusers] Context-free lexer for NM-TRAN Hi all, Calling all computer scientists and computer language experts. In my spare time, I am working on a lexer and parser for NM-Tran. Primarly to teach myself about grammars and DSL, but perhaps something useful will come out of this (e.g. a context-sensitive editor with code completion). When lexing, I am having a hard time describing the keywords used by nm-tran. Let us take '.EQ.' as an example. 1) It seems that *.EQ. *is a keyword used to describe a comparison. 2) However, a filename could also be 'foo.eq.bar' The same thing applies for keywords on the '$ESTIMATION' record. These keywords could also be used as variable names. Am I right in saying that NM-TRAN cannot be tokenized with a context-free lexer? And that I should focus my efforts on building a lexer-less parser? (Or building my own lexer-parser, see https://en.wikipedia.org/wiki/The_lexer_hack ) I assume building a parser for NM-TRAN was already done in the DDMoRe project, but I failed to find the source code... Kind regards, Ruben Faelens *NOTICE: *The information contained in this electronic mail message is intended only for the personal and confidential use of the designated recipient(s) named above. This message may be an attorney-client communication, may be protected by the work product doctrine, and may be subject to a protective order. As such, this message is privileged and confidential. If the reader of this message is not the intended recipient or an agent responsible for delivering it to the intended recipient, you are hereby notified that you have received this message in error and that any review, dissemination, distribution, or copying of this message is strictly prohibited. If you have received this communication in error, please notify us immediately by telephone and e-mail and destroy any and all copies of this message in your possession (whether hard copies or electronically stored copies). Thank you. Personal data may be transferred to the United States of America and, if this occurs, it is possible that US governmental authorities may access such personal data. buSp9xeMeKEbrUze
