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Full Discussion: Count lines
Top Forums Shell Programming and Scripting Count lines Post 302809537 by Scrutinizer on Monday 20th of May 2013 05:10:23 AM
Old 05-20-2013
@summer_cherry. The gawk / awk does not produce the correct output for multiple ranges with the same $1 (see post #6).

---
The python script produces (Python 2.7.2):
Code:
line 7, in <module>
    dic[words[0]]={'MIN':words[1],'MAX':words[2],'CNT':0}
IndexError: list index out of range

 

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apertium-lextor(1)														apertium-lextor(1)

NAME
apertium-lextor - This application is part of ( apertium ) This tool is part of the apertium machine translation architecture: http://apertium.org. SYNOPSIS
apertium-lextor --trainwrd stopwords words n left right corpus model [ --weightexp w ] [ --debug ] apertium-lextor --trainlch stopwords lexchoices n left right corpus wordmodel dic bildic model [ --weightexp w ] [ --debug ] apertium-lextor --lextor model dic left right [ --debug ] [ --weightexp w ] DESCRIPTION
apertium-lextor is the application responsible for training and usage of the lexical selector module. OPTIONS
--trainwrd | -t Train word co-occurrences model. It needs the following required parameters: stopwords file containing a list of stop words. Stop words are ignored. words file containing a list of words. For each word a co-occurrence model is built. n number of words per co-occurrence model (for each model, the n most frequent words). left left-side context to take into account (number of words). right right-side context to take into account (number of words). corpus file containing the training corpus. model output file on which the co-occurrence models are saved. --trainlch | -r Train lexical choices co-occurrence models using a target language co-occurrence model and a bilingual dictionary. It needs the following required parameters: stopwords file containing a list of stop words. Stop words are ignored. lexchoices file containing a list of lexical choices. For each lexical choice a co-occurrence model is built. n number of words per co-occurrence model (for each model, the n most frequent words). left left-side context to take into account (number of words). right right-side context to take into account (number of words). corpus file containing the training corpus. wordmodel target-language word co-occurrence model (previously trained by means of the --trainwrd option). dic the lexical-selection dictionary (binary format). bildic the bilingual dictionary (binary format). model output file on which the co-occurrence models are saved. --lextor | -l Perform the lexical selection on the input stream. It needs the following required parameters: model file containing the model to be used for the lexical selection. dic lexical-selection dictionary (binary format). left left-side context to take into account (number of words). right right-side context to take into account (number of words). --weightexp w Specify a weight value to change the influence of surrounding words while training or performing the lexical selection. The parameter w must be a positive value. --debug | -d Show debug information while working. --help | -h Shows this help. --version | -v Shows license information. SEE ALSO
apertium-gen-lextorbil(1), apertium-preprocess-corpus-lextor(1), apertium-gen-stopwords-lextor(1), apertium-gen-wlist-lextor(1), aper- tium-gen-wlist-lextor-translation(1), apertium-lextor-eval(1), apertium-lextor-mono(1). BUGS
Lots of...lurking in the dark and waiting for you! AUTHOR
(c) 2005,2006 Universitat d'Alacant / Universidad de Alicante. All rights reserved. 2006-12-12 apertium-lextor(1)
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