From dfb6f96c11c01433dd644aba9f57b728a3cbabc8 Mon Sep 17 00:00:00 2001 From: pakjiddat Date: Fri, 18 Jun 2021 14:31:50 +0000 Subject: [PATCH] Increase package version and resubmit - Since the package has been approved by CRAN, the CRAN-RELEASE file should be removed. A commit should be tagged with the version number, 0.0.1. - Update version number in DESCRIPTION file. - Add change details in user friendly format to NEWS.md. - Correct spelling errors in README.Rmd. - Set development mode of package to release in pkgdown config file. - Test package on different platforms and update cran-comments.md. - Remove the non-standard characters from the example in data-cleaner.R. - Rebuild pkgdown website. --- CRAN-RELEASE | 4 +- DESCRIPTION | 2 +- NEWS.md | 13 ++- R/data-cleaner.R | 12 +-- README.Rmd | 12 +-- _pkgdown.yml | 2 +- cran-comments.md | 11 ++- docs/404.html | 2 +- docs/LICENSE-text.html | 2 +- docs/LICENSE.html | 2 +- docs/articles/features.html | 96 +++++++++++++++------ docs/articles/index.html | 2 +- docs/articles/man/figures/coverage.png | Bin 0 -> 56053 bytes docs/articles/man/figures/top_features.png | Bin 0 -> 64494 bytes docs/articles/overview.html | 23 +++-- docs/authors.html | 2 +- docs/index.html | 7 +- docs/news/index.html | 25 +++++- docs/pkgdown.yml | 2 +- docs/reference/Base.html | 2 +- docs/reference/DataAnalyzer.html | 10 +-- docs/reference/DataCleaner.html | 28 +++--- docs/reference/DataSampler.html | 6 +- docs/reference/EnvManager.html | 2 +- docs/reference/Model.html | 2 +- docs/reference/ModelEvaluator.html | 12 +-- docs/reference/ModelGenerator.html | 4 +- docs/reference/ModelPredictor.html | 8 +- docs/reference/TPGenerator.html | 4 +- docs/reference/TokenGenerator.html | 4 +- docs/reference/index.html | 2 +- docs/reference/wordpredictor-package.html | 2 +- man/DataCleaner.Rd | 24 +++--- tests/testthat/test-c-data-cleaner.R | 12 +-- vignettes/features.Rmd | 24 +++--- vignettes/overview.Rmd | 11 +-- 36 files changed, 234 insertions(+), 142 deletions(-) create mode 100644 docs/articles/man/figures/coverage.png create mode 100644 docs/articles/man/figures/top_features.png diff --git a/CRAN-RELEASE b/CRAN-RELEASE index 866c24d..660d888 100644 --- a/CRAN-RELEASE +++ b/CRAN-RELEASE @@ -1,2 +1,2 @@ -This package was submitted to CRAN on 2021-06-11. -Once it is accepted, delete this file and tag the release (commit 40778a5). +This package was submitted to CRAN on 2021-06-18. +Once it is accepted, delete this file and tag the release (commit 021eb41). diff --git a/DESCRIPTION b/DESCRIPTION index a15fbf7..9bad7a4 100644 --- a/DESCRIPTION +++ b/DESCRIPTION @@ -1,6 +1,6 @@ Package: wordpredictor Title: Develop Text Prediction Models Based on N-Grams -Version: 0.0.1 +Version: 0.0.2 URL: https://github.com/pakjiddat/word-predictor, https://pakjiddat.github.io/word-predictor/ BugReports: https://github.com/pakjiddat/word-predictor/issues Authors@R: diff --git a/NEWS.md b/NEWS.md index 6dad56c..c1281d8 100644 --- a/NEWS.md +++ b/NEWS.md @@ -1,3 +1,14 @@ +# wordpredictor 0.0.2 + +## Bug fixes + + * Fixed small bugs that were causing problems with GitHub actions and CRAN checks. + * Removed custom `.Rprofile` file as it was causing problems with GitHub actions. + * Updated sample code in `features.Rmd` vignette so it does not cause issues with R CMD Check on MacOs. + * Removed `inst/extdata folder` from `.gitignore` since it was causing problems with check-standard workflow on GitHub. + * Removed non-standard characters from example in data-cleaner.R file as they were causing problems with CRAN check on "Debian Linux, R-devel, clang". + * Issues related to the bug fixes: [#318](https://github.com/r-lib/actions/issues/318), [#319](https://github.com/r-lib/actions/issues/319), [#320](https://github.com/r-lib/actions/issues/320) + # wordpredictor 0.0.1 - - Initial Release + * Initial Release. diff --git a/R/data-cleaner.R b/R/data-cleaner.R index 9c5d5b3..73da6ab 100644 --- a/R/data-cleaner.R +++ b/R/data-cleaner.R @@ -156,13 +156,13 @@ DataCleaner <- R6::R6Class( #' ve <- 0 #' # Test data is read #' l <- c( - #' "If you think I’m wrong, send me a link to where it’s happened", - #' "We’re about 90percent done with this room", - #' "“This isn’t how I wanted it between us.”", - #' "Almost any “cute” breed can become ornamental", - #' "Once upon a time there was a kingdom with a castle…", + #' "If you think I'm wrong, send me a link to where it's happened", + #' "We're about 90percent done with this room", + #' "This isn't how I wanted it between us.", + #' "Almost any cute breed can become ornamental", + #' "Once upon a time there was a kingdom with a castle", #' "That's not a thing any of us are granted'", - #' "“Why are you being so difficult?” she asks." + #' "Why are you being so difficult? she asks." #' ) #' # The expected results #' res <- c( diff --git a/README.Rmd b/README.Rmd index 5c506fb..dcae618 100644 --- a/README.Rmd +++ b/README.Rmd @@ -121,7 +121,7 @@ mg <- ModelGenerator$new( # Generates n-gram model. The output is the file def-model.RDS mg$generate_model() -# The test envionment is cleaned up +# The test environment is cleaned up clean_up(ve) ``` @@ -146,7 +146,7 @@ mp <- ModelPredictor$new(mf = mfn) # next words are returned along with their respective probabilities. res <- mp$predict_word(words = "how are", 3) -# The test envionment is cleaned up +# The test environment is cleaned up clean_up(ve) ``` @@ -177,7 +177,7 @@ df <- da$plot_n_gram_stats(opts = list( "dir" = NULL )) -# The test envionment is cleaned up +# The test environment is cleaned up clean_up(ve) ``` @@ -202,7 +202,7 @@ df <- da$plot_n_gram_stats(opts = list( "dir" = NULL )) -# The test envionment is cleaned up +# The test environment is cleaned up clean_up(ve) ``` @@ -226,7 +226,7 @@ df <- df[order(df$freq, decreasing = T),] # The frequency of the bi-gram "great_deal" f <- as.numeric(df[df$pre == "great_deal", "freq"]) -# The test envionment is cleaned up +# The test environment is cleaned up clean_up(ve) ``` @@ -310,7 +310,7 @@ me <- ModelEvaluator$new(mf = mfn, ve = 2) # a data frame and also saved within the model file itself. stats <- me$evaluate_performance(lc = 20, fn = vfn) -# The test envionment is cleaned up +# The test environment is cleaned up clean_up(ve) ``` diff --git a/_pkgdown.yml b/_pkgdown.yml index a81b332..27c3e94 100644 --- a/_pkgdown.yml +++ b/_pkgdown.yml @@ -1,4 +1,4 @@ url: https://pakjiddat.github.io/word-predictor title: Word Predictor development: - mode: unreleased + mode: release diff --git a/cran-comments.md b/cran-comments.md index 6a56ceb..8fe83bb 100644 --- a/cran-comments.md +++ b/cran-comments.md @@ -2,10 +2,13 @@ - local, ubuntu 20.04.2, R 3.6.3 - github actions, macos-latest, R release - - rhub, solaris x86, R patched-ods - - rhub, windows-x86_64, R release - - rhub, ubuntu-gcc, R release - - rhub, fedora-clang, R devel + - github actions, windows-latest, R release + - github actions, ubuntu 20.04, R devel + - github actions, ubuntu 20.04, R release + - rhub, debian-clang-devel, R devel + - rhub, fedora-clang-devel, R devel + - rhub, solaris-x86-patched, R release + - rhub, macos-highsierra-release, R release - winbuilder, windows, R devel ## R CMD check results diff --git a/docs/404.html b/docs/404.html index df9d734..2a68018 100644 --- a/docs/404.html +++ b/docs/404.html @@ -71,7 +71,7 @@ Word Predictor - 0.0.1 + 0.0.2 diff --git a/docs/LICENSE-text.html b/docs/LICENSE-text.html index 5a1f7f5..4b2233b 100644 --- a/docs/LICENSE-text.html +++ b/docs/LICENSE-text.html @@ -71,7 +71,7 @@ Word Predictor - 0.0.1 + 0.0.2 diff --git a/docs/LICENSE.html b/docs/LICENSE.html index 3bef9a7..16d34a7 100644 --- a/docs/LICENSE.html +++ b/docs/LICENSE.html @@ -71,7 +71,7 @@ Word Predictor - 0.0.1 + 0.0.2 diff --git a/docs/articles/features.html b/docs/articles/features.html index aee7b12..13658dd 100644 --- a/docs/articles/features.html +++ b/docs/articles/features.html @@ -31,7 +31,7 @@ Word Predictor - 0.0.1 + 0.0.2 @@ -120,6 +120,9 @@

) # The test environment is setup ed <- setup_env(rf, ve) +#> [1] "CITATION" "demo" "DESCRIPTION" "examples" "extdata" +#> [6] "help" "html" "INDEX" "LICENSE" "Meta" +#> [11] "NAMESPACE" "NEWS.md" "R" # The DataAnalyzer object is created da <- DataAnalyzer$new(ve = ve) @@ -129,16 +132,16 @@

print(fi) #> $file_stats #> fn total_lc max_ll min_ll mean_ll size -#> 1 /tmp/RtmpENXTF8/test-clean.txt 73 50 25 39 2.8 Kb -#> 2 /tmp/RtmpENXTF8/test.txt 73 51 28 41 3 Kb -#> 3 /tmp/RtmpENXTF8/validate-clean.txt 75 48 10 37 2.8 Kb -#> 4 /tmp/RtmpENXTF8/validate.txt 73 50 31 40 2.9 Kb +#> 1 /tmp/RtmpmqAHFH/test-clean.txt 73 50 25 39 2.8 Kb +#> 2 /tmp/RtmpmqAHFH/test.txt 73 51 28 41 3 Kb +#> 3 /tmp/RtmpmqAHFH/validate-clean.txt 75 48 10 37 2.8 Kb +#> 4 /tmp/RtmpmqAHFH/validate.txt 73 50 31 40 2.9 Kb #> #> $overall_stats #> total_lc max_ll min_ll mean_ll total_s #> 1 294 51 31 41 11.5 Kb -# The test envionment is cleaned up +# The test environment is cleaned up clean_up(ve)

The word count of a text file can be fetched using the command: cat file-name | wc -w. This command should work on all Unix based systems.

@@ -152,6 +155,9 @@

rf <- c("input.txt") # The test environment is setup ed <- setup_env(rf, ve) +#> [1] "CITATION" "demo" "DESCRIPTION" "examples" "extdata" +#> [6] "help" "html" "INDEX" "LICENSE" "Meta" +#> [11] "NAMESPACE" "NEWS.md" "R" # The sample size as a proportion of the input.txt file ssize <- 0.1 @@ -175,7 +181,7 @@

is = T ) -# The test envionment is cleaned up +# The test environment is cleaned up clean_up(ve)

Usually we need a train data set for generating the n-gram model. A test data set for testing the model and a validation data set for evaluating the performance of the model. The following example shows how to generate the train, test and validation files. The train file contains the first 80% of the lines, the test set contains the next 10% of the lines. The remaining lines are in the validation set.

The data in the validation file must be different from the data in the train file. Otherwise it can result in over-fitting of the model. When a model is over-fitted, the model evaluation results will be exaggerated, overly optimistic and unreliable. So care should be taken to ensure that the data in the validation and train files is different.

@@ -184,6 +190,9 @@

rf <- c("input.txt") # The test environment is setup ed <- setup_env(rf, ve) +#> [1] "CITATION" "demo" "DESCRIPTION" "examples" "extdata" +#> [6] "help" "html" "INDEX" "LICENSE" "Meta" +#> [11] "NAMESPACE" "NEWS.md" "R" # An object of class DataSampler is created ds <- DataSampler$new(dir = ed, ve = ve) @@ -197,7 +206,7 @@

) ) -# The test envionment is cleaned up +# The test environment is cleaned up clean_up(ve)

In the above example, dir parameter is the directory containing the input.txt file and the generated test, validation and train data files.

@@ -211,6 +220,9 @@

rf <- c("input.txt") # The test environment is setup ed <- setup_env(rf, ve) +#> [1] "CITATION" "demo" "DESCRIPTION" "examples" "extdata" +#> [6] "help" "html" "INDEX" "LICENSE" "Meta" +#> [11] "NAMESPACE" "NEWS.md" "R" # The data file path fn <- paste0(ed, "/input.txt") @@ -233,7 +245,7 @@

# The sample file is cleaned and saved as input-clean.txt in the ed dir dc$clean_file() -# The test envionment is cleaned up +# The test environment is cleaned up clean_up(ve)

The clean_file method reads a certain number of lines at a time, cleans the lines of text and saves them to an output text file. It can be used for cleaning large text files.

@@ -246,6 +258,9 @@

rf <- c("test-clean.txt") # The test environment is setup ed <- setup_env(rf, ve) +#> [1] "CITATION" "demo" "DESCRIPTION" "examples" "extdata" +#> [6] "help" "html" "INDEX" "LICENSE" "Meta" +#> [11] "NAMESPACE" "NEWS.md" "R" # The test file path fn <- paste0(ed, "/test-clean.txt") @@ -259,7 +274,7 @@

tg$generate_tokens() } -# The test envionment is cleaned up +# The test environment is cleaned up clean_up(ve)

The above code generates the files n1.RDS, n2.RDS, n3.RDS and n4.RDS in the data directory. These files contains n-gram tokens along with their frequencies. N-grams of larger size provide more context. Usually n-grams of size 4 are generated.

Two important customization options supported by the TokenGenerator class are min_freq and stem_words. min_freq sets minimum frequency for n-gram tokens. All n-gram tokens with frequency less than min_freq are excluded.

@@ -270,6 +285,9 @@

rf <- c("n2.RDS") # The test environment is setup ed <- setup_env(rf, ve) +#> [1] "CITATION" "demo" "DESCRIPTION" "examples" "extdata" +#> [6] "help" "html" "INDEX" "LICENSE" "Meta" +#> [11] "NAMESPACE" "NEWS.md" "R" # The ngram file name fn <- paste0(ed, "/n2.RDS") @@ -279,13 +297,17 @@

df <- da$plot_n_gram_stats(opts = list( "type" = "top_features", "n" = 10, - "save_to" = NULL, - "dir" = ed -)) -

+ "save_to" = "png", + "dir" = "./man/figures" +)) + +# The output file path +fn <- paste0("./man/figures/top_features.png") +knitr::include_graphics(fn) +

 
-# The test envionment is cleaned up
+# The test environment is cleaned up
 clean_up(ve)

The following example shows the distribution of word frequencies:

@@ -293,6 +315,9 @@ 

 rf <- c("n2.RDS")
 # The test environment is setup
 ed <- setup_env(rf, ve)
+#>  [1] "CITATION"    "demo"        "DESCRIPTION" "examples"    "extdata"    
+#>  [6] "help"        "html"        "INDEX"       "LICENSE"     "Meta"       
+#> [11] "NAMESPACE"   "NEWS.md"     "R"
 
 # The ngram file name
 fn <- paste0(ed, "/n2.RDS")
@@ -302,13 +327,17 @@ 

 df <- da$plot_n_gram_stats(opts = list(
     "type" = "coverage",
     "n" = 10,
-    "save_to" = NULL,
-    "dir" = ed
-))
-

+ "save_to" = "png", + "dir" = "./man/figures" +)) + +# The output file path +fn <- paste0("./man/figures/coverage.png") +knitr::include_graphics(fn) +

 
-# The test envionment is cleaned up
+# The test environment is cleaned up
 clean_up(ve)

The following example returns top 10 2-gram tokens that start with and_:

@@ -316,6 +345,9 @@ 

 rf <- c("n2.RDS")
 # The test environment is setup
 ed <- setup_env(rf, ve)
+#>  [1] "CITATION"    "demo"        "DESCRIPTION" "examples"    "extdata"    
+#>  [6] "help"        "html"        "INDEX"       "LICENSE"     "Meta"       
+#> [11] "NAMESPACE"   "NEWS.md"     "R"
 
 # The ngram file name
 fn <- paste0(ed, "/n2.RDS")
@@ -377,7 +409,7 @@ 

 
 
 
-# The test envionment is cleaned up
+# The test environment is cleaned up
 clean_up(ve)
@@ -391,12 +423,15 @@

rf <- c("n1.RDS", "n2.RDS", "n3.RDS", "n4.RDS") # The test environment is setup ed <- setup_env(rf, ve) +#> [1] "CITATION" "demo" "DESCRIPTION" "examples" "extdata" +#> [6] "help" "html" "INDEX" "LICENSE" "Meta" +#> [11] "NAMESPACE" "NEWS.md" "R" # The TPGenerator object is created tp <- TPGenerator$new(opts = list(n = 4, dir = ed), ve = ve) # The combined transition probabilities are generated tp$generate_tp() -# The test envionment is cleaned up +# The test environment is cleaned up clean_up(ve)

The above code produces the file model-4.RDS.

@@ -437,7 +472,7 @@

# Generates n-gram model. The output is the file def-model.RDS mg$generate_model() -# The test envionment is cleaned up +# The test environment is cleaned up clean_up(ve) @@ -451,6 +486,9 @@

rf <- c("def-model.RDS", "validate-clean.txt") # The test environment is setup ed <- setup_env(rf, ve) +#> [1] "CITATION" "demo" "DESCRIPTION" "examples" "extdata" +#> [6] "help" "html" "INDEX" "LICENSE" "Meta" +#> [11] "NAMESPACE" "NEWS.md" "R" # The model file name mfn <- paste0(ed, "/def-model.RDS") @@ -461,7 +499,7 @@

# The intrinsic evaluation is performed on first 20 lines stats <- me$intrinsic_evaluation(lc = 20, fn = vfn) -# The test envionment is cleaned up +# The test environment is cleaned up clean_up(ve)

The following example performs Extrinsic evaluation. It measures the accuracy score for each sentence in validation.txt file. For each sentence the model is used to predict the last word in the sentence given the previous words. If the last word was correctly predicted, then the prediction is considered to be accurate.

@@ -469,6 +507,9 @@ 

 rf <- c("def-model.RDS", "validate-clean.txt")
 # The test environment is setup
 ed <- setup_env(rf, ve)
+#>  [1] "CITATION"    "demo"        "DESCRIPTION" "examples"    "extdata"    
+#>  [6] "help"        "html"        "INDEX"       "LICENSE"     "Meta"       
+#> [11] "NAMESPACE"   "NEWS.md"     "R"
 
 # The model file name
 mfn <- paste0(ed, "/def-model.RDS")
@@ -479,7 +520,7 @@ 

 # The intrinsic evaluation is performed on first 100 lines
 stats <- me$extrinsic_evaluation(lc = 100, fn = vfn)
 
-# The test envionment is cleaned up
+# The test environment is cleaned up
 clean_up(ve)
@@ -491,6 +532,9 @@

rf <- c("def-model.RDS") # The test environment is setup ed <- setup_env(rf, ve) +#> [1] "CITATION" "demo" "DESCRIPTION" "examples" "extdata" +#> [6] "help" "html" "INDEX" "LICENSE" "Meta" +#> [11] "NAMESPACE" "NEWS.md" "R" # The model file name mfn <- paste0(ed, "/def-model.RDS") @@ -501,7 +545,7 @@

# next words are returned along with their respective probabilities. res <- mp$predict_word(words = "how are", 3) -# The test envionment is cleaned up +# The test environment is cleaned up clean_up(ve)

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@@ Word Predictor - 0.0.1 + 0.0.2 @@ -173,7 +173,7 @@

# ./data/model/def-model.RDS mg$generate_model() -# The test envionment is cleaned up +# The test environment is cleaned up clean_up(ve)
@@ -186,6 +186,9 @@

rf <- c("def-model.RDS", "validate-clean.txt") # The test environment is setup ed <- setup_env(rf, ve) +#> [1] "CITATION" "demo" "DESCRIPTION" "examples" "extdata" +#> [6] "help" "html" "INDEX" "LICENSE" "Meta" +#> [11] "NAMESPACE" "NEWS.md" "R" # The model file name mfn <- paste0(ed, "/def-model.RDS") @@ -196,7 +199,7 @@

# The intrinsic evaluation is performed on first 20 lines stats <- me$intrinsic_evaluation(lc = 20, fn = vfn) -# The test envionment is cleaned up +# The test environment is cleaned up clean_up(ve)

The following example performs extrinsic evaluation. It measures the accuracy score for each sentence in validation.txt file. For each sentence the model is used to predict the last word in the sentence given the previous words. If the last word was correctly predicted, then the prediction is considered to be accurate. The extrinsic evaluation returns the number of correct and incorrect predictions.

@@ -204,6 +207,9 @@ 

 rf <- c("def-model.RDS", "validate-clean.txt")
 # The test environment is setup
 ed <- setup_env(rf, ve)
+#>  [1] "CITATION"    "demo"        "DESCRIPTION" "examples"    "extdata"    
+#>  [6] "help"        "html"        "INDEX"       "LICENSE"     "Meta"       
+#> [11] "NAMESPACE"   "NEWS.md"     "R"
 
 # The model file name
 mfn <- paste0(ed, "/def-model.RDS")
@@ -214,7 +220,7 @@ 

 # The intrinsic evaluation is performed on first 100 lines
 stats <- me$extrinsic_evaluation(lc = 100, fn = vfn)
 
-# The test envionment is cleaned up
+# The test environment is cleaned up
 clean_up(ve)
@@ -226,6 +232,9 @@

rf <- c("def-model.RDS", "validate-clean.txt") # The test environment is setup ed <- setup_env(rf, ve) +#> [1] "CITATION" "demo" "DESCRIPTION" "examples" "extdata" +#> [6] "help" "html" "INDEX" "LICENSE" "Meta" +#> [11] "NAMESPACE" "NEWS.md" "R" # The model file name mfn <- paste0(ed, "/def-model.RDS") @@ -235,7 +244,7 @@

# Given the words: "how are", the next word is predicted. The top 3 most likely # next words are returned along with their respective probabilities. res <- mp$predict_word(words = "how are", 3) -# The test envionment is cleaned up +# The test environment is cleaned up clean_up(ve)

@@ -247,8 +256,8 @@

Package dependencies

-

The wordpredictor package uses the following packages: digest, dply, ggplot2, pryr, R6, testthat and stingr

-

The following packages were useful during package development: quanteda, tm and hash lintr styler pkgdown

+

The wordpredictor package uses the following packages: digest, dply, ggplot2, R6, testthat and stingr

+

The following packages were useful during package development: quanteda, tm and hash lintr styler pkgdown pryr,

diff --git a/docs/index.html b/docs/index.html index 192c535..aba9648 100644 --- a/docs/index.html +++ b/docs/index.html @@ -38,7 +38,7 @@ Word Predictor - 0.0.1 + 0.0.2

@@ -390,6 +390,8 @@

Links

+
+

+wordpredictor 0.0.2 Unreleased +

+
+

+Bug fixes

+
    +
  • Fixed small bugs that were causing problems with GitHub actions and CRAN checks.
    • +
  • Removed custom .Rprofile file as it was causing problems with GitHub actions.
    • +
  • Updated sample code in features.Rmd vignette so it does not cause issues with R CMD Check on MacOs.
    • +
  • Removed inst/extdata folder from .gitignore since it was causing problems with check-standard workflow on GitHub.
    • +
  • Removed non-standard characters from example in data-cleaner.R file as they were causing problems with CRAN check on “Debian Linux, R-devel, clang”.
    • +
  • Issues related to the bug fixes: #318, #319, #320 +
    • +
+
+

-wordpredictor 0.0.1

+wordpredictor 0.0.1 2021-06-14 +

    -
  • Initial Release
    • +
  • Initial Release.
diff --git a/docs/pkgdown.yml b/docs/pkgdown.yml index f11f9f8..84416b2 100644 --- a/docs/pkgdown.yml +++ b/docs/pkgdown.yml @@ -4,7 +4,7 @@ pkgdown_sha: ~ articles: features: features.html overview: overview.html -last_built: 2021-06-14T04:00Z +last_built: 2021-06-18T13:35Z urls: reference: https://pakjiddat.github.io/word-predictor/reference article: https://pakjiddat.github.io/word-predictor/articles diff --git a/docs/reference/Base.html b/docs/reference/Base.html index f9c4eb7..e2a4d73 100644 --- a/docs/reference/Base.html +++ b/docs/reference/Base.html @@ -73,7 +73,7 @@ Word Predictor - 0.0.1 + 0.0.2 diff --git a/docs/reference/DataAnalyzer.html b/docs/reference/DataAnalyzer.html index f865637..3516f7e 100644 --- a/docs/reference/DataAnalyzer.html +++ b/docs/reference/DataAnalyzer.html @@ -76,7 +76,7 @@ Word Predictor - 0.0.1 + 0.0.2 @@ -379,7 +379,7 @@

Examp em <- EnvManager$new(ve = ve, rp = "./") # The required files are downloaded ed <- em$setup_env(rf, fn) -# End of environment setup code +
#> [1] "CITATION" "examples" "extdata"
# End of environment setup code # The n-gram file name nfn <- paste0(ed, "/n2.RDS") @@ -427,7 +427,7 @@

Examp em <- EnvManager$new(ve = ve, rp = "./") # The required files are downloaded ed <- em$setup_env(rf, fn) -# End of environment setup code +

#> [1] "CITATION" "examples" "extdata"
# End of environment setup code # The test file name cfn <- paste0(ed, "/test.txt") @@ -439,7 +439,7 @@

Examp print(fi)

#> $file_stats #> fn total_lc max_ll min_ll mean_ll size -#> 1 /tmp/RtmpNqf9Ge/test.txt 73 51 28 41 3 Kb +#> 1 /tmp/Rtmpgcy76G/test.txt 73 51 28 41 3 Kb #> #> $overall_stats #> total_lc max_ll min_ll mean_ll total_s @@ -466,7 +466,7 @@

Examp em <- EnvManager$new(ve = ve, rp = "./") # The required files are downloaded ed <- em$setup_env(rf, fn) -# End of environment setup code +

#> [1] "CITATION" "examples" "extdata"
# End of environment setup code # The n-gram file name nfn <- paste0(ed, "/n2.RDS") diff --git a/docs/reference/DataCleaner.html b/docs/reference/DataCleaner.html index 7a7c99c..7898ad8 100644 --- a/docs/reference/DataCleaner.html +++ b/docs/reference/DataCleaner.html @@ -73,7 +73,7 @@ Word Predictor - 0.0.1 + 0.0.2
@@ -261,13 +261,13 @@

Exa ve <- 0 # Test data is read l <- c( - "If you think I’m wrong, send me a link to where it’s happened", - "We’re about 90percent done with this room", - "“This isn’t how I wanted it between us.”", - "Almost any “cute” breed can become ornamental", - "Once upon a time there was a kingdom with a castle…", + "If you think I'm wrong, send me a link to where it's happened", + "We're about 90percent done with this room", + "This isn't how I wanted it between us.", + "Almost any cute breed can become ornamental", + "Once upon a time there was a kingdom with a castle", "That's not a thing any of us are granted'", - "“Why are you being so difficult?” she asks." + "Why are you being so difficult? she asks." ) # The expected results res <- c( @@ -319,7 +319,7 @@

Examp em <- EnvManager$new(ve = ve, rp = "./") # The required files are downloaded ed <- em$setup_env(rf, fn) -# End of environment setup code +
#> [1] "CITATION" "examples" "extdata"
# End of environment setup code # The cleaned test file name cfn <- paste0(ed, "/test-clean.txt") @@ -344,13 +344,13 @@

Examp ve <- 0 # Test data is read l <- c( - "If you think I’m wrong, send me a link to where it’s happened", - "We’re about 90percent done with this room", - "“This isn’t how I wanted it between us.”", - "Almost any “cute” breed can become ornamental", - "Once upon a time there was a kingdom with a castle…", + "If you think I'm wrong, send me a link to where it's happened", + "We're about 90percent done with this room", + "This isn't how I wanted it between us.", + "Almost any cute breed can become ornamental", + "Once upon a time there was a kingdom with a castle", "That's not a thing any of us are granted'", - "“Why are you being so difficult?” she asks." + "Why are you being so difficult? she asks." ) # The expected results res <- c( diff --git a/docs/reference/DataSampler.html b/docs/reference/DataSampler.html index f0b7544..465f41e 100644 --- a/docs/reference/DataSampler.html +++ b/docs/reference/DataSampler.html @@ -76,7 +76,7 @@ Word Predictor - 0.0.1 + 0.0.2

@@ -324,7 +324,7 @@

Examp em <- EnvManager$new(ve = ve, rp = "./") # The required files are downloaded ed <- em$setup_env(rf, fn) -# End of environment setup code +
#> [1] "CITATION" "examples" "extdata"
# End of environment setup code # The sample file name sfn <- paste0(ed, "/sample.txt") @@ -362,7 +362,7 @@

Examp em <- EnvManager$new(ve = ve) # The required files are downloaded ed <- em$setup_env(rf, fn) -# End of environment setup code +

#> [1] "CITATION" "examples" "extdata"
# End of environment setup code # The files to clean fns <- c("train", "test", "validate") diff --git a/docs/reference/EnvManager.html b/docs/reference/EnvManager.html index fad8928..e1aa57a 100644 --- a/docs/reference/EnvManager.html +++ b/docs/reference/EnvManager.html @@ -74,7 +74,7 @@ Word Predictor - 0.0.1 + 0.0.2
diff --git a/docs/reference/Model.html b/docs/reference/Model.html index 05bc868..844c301 100644 --- a/docs/reference/Model.html +++ b/docs/reference/Model.html @@ -75,7 +75,7 @@ Word Predictor - 0.0.1 + 0.0.2 diff --git a/docs/reference/ModelEvaluator.html b/docs/reference/ModelEvaluator.html index 3ad2e7a..53fcb20 100644 --- a/docs/reference/ModelEvaluator.html +++ b/docs/reference/ModelEvaluator.html @@ -77,7 +77,7 @@ Word Predictor - 0.0.1 + 0.0.2 @@ -458,7 +458,7 @@

Examp em <- EnvManager$new(ve = ve, rp = "./") # The required files are downloaded ed <- em$setup_env(rf, fn) -# End of environment setup code +
#> [1] "CITATION" "examples" "extdata"
# End of environment setup code # ModelEvaluator class object is created me <- ModelEvaluator$new(ve = ve) # The performance evaluation is performed @@ -488,7 +488,7 @@

Examp em <- EnvManager$new(ve = ve, rp = "./") # The required files are downloaded ed <- em$setup_env(rf, fn) -# End of environment setup code +

#> [1] "CITATION" "examples" "extdata"
# End of environment setup code # The model file name mfn <- paste0(ed, "/def-model.RDS") @@ -505,7 +505,7 @@

Examp #> [1] 279320 #> #> $t -#> [1] 0.759 +#> [1] 0.747 #> #> $p #> [1] 2297.35 @@ -534,7 +534,7 @@

Examp em <- EnvManager$new(ve = ve, rp = "./") # The required files are downloaded ed <- em$setup_env(rf, fn) -# End of environment setup code +

#> [1] "CITATION" "examples" "extdata"
# End of environment setup code # The model file name mfn <- paste0(ed, "/def-model.RDS") @@ -577,7 +577,7 @@

Examp em <- EnvManager$new(ve = ve, rp = "./") # The required files are downloaded ed <- em$setup_env(rf, fn) -# End of environment setup code +

#> [1] "CITATION" "examples" "extdata"
# End of environment setup code # The model file name mfn <- paste0(ed, "/def-model.RDS") diff --git a/docs/reference/ModelGenerator.html b/docs/reference/ModelGenerator.html index 53b7f88..6d33efc 100644 --- a/docs/reference/ModelGenerator.html +++ b/docs/reference/ModelGenerator.html @@ -73,7 +73,7 @@ Word Predictor - 0.0.1 + 0.0.2
@@ -282,7 +282,7 @@

Examp em <- EnvManager$new(ve = ve, rp = "./") # The required files are downloaded ed <- em$setup_env(rf, fn) -# End of environment setup code +
#> [1] "CITATION" "examples" "extdata"
# End of environment setup code # ModelGenerator class object is created mg <- ModelGenerator$new( diff --git a/docs/reference/ModelPredictor.html b/docs/reference/ModelPredictor.html index c9b5754..2a7c651 100644 --- a/docs/reference/ModelPredictor.html +++ b/docs/reference/ModelPredictor.html @@ -75,7 +75,7 @@ Word Predictor - 0.0.1 + 0.0.2
@@ -379,7 +379,7 @@

Examp em <- EnvManager$new(ve = ve, rp = "./") # The required files are downloaded ed <- em$setup_env(rf, fn) -# End of environment setup code +
#> [1] "CITATION" "examples" "extdata"
# End of environment setup code # The model file name mfn <- paste0(ed, "/def-model.RDS") @@ -414,7 +414,7 @@

Examp em <- EnvManager$new(ve = ve, "rp" = "./") # The required files are downloaded ed <- em$setup_env(rf, fn) -# End of environment setup code +

#> [1] "CITATION" "examples" "extdata"
# End of environment setup code # The model file name mfn <- paste0(ed, "/def-model.RDS") @@ -456,7 +456,7 @@

Examp em <- EnvManager$new(ve = ve, "rp" = "./") # The required files are downloaded ed <- em$setup_env(rf, fn) -# End of environment setup code +

#> [1] "CITATION" "examples" "extdata"
# End of environment setup code # The model file name mfn <- paste0(ed, "/def-model.RDS") diff --git a/docs/reference/TPGenerator.html b/docs/reference/TPGenerator.html index 0966f01..8ac169b 100644 --- a/docs/reference/TPGenerator.html +++ b/docs/reference/TPGenerator.html @@ -75,7 +75,7 @@ Word Predictor - 0.0.1 + 0.0.2
@@ -290,7 +290,7 @@

Examp em <- EnvManager$new(ve = ve, rp = "./") # The required files are downloaded ed <- em$setup_env(rf, fn) -# End of environment setup code +
#> [1] "CITATION" "examples" "extdata"
# End of environment setup code # The list of output files fns <- c("words", "model-4", "tp2", "tp3", "tp4") diff --git a/docs/reference/TokenGenerator.html b/docs/reference/TokenGenerator.html index dbf6b8d..0e4b107 100644 --- a/docs/reference/TokenGenerator.html +++ b/docs/reference/TokenGenerator.html @@ -73,7 +73,7 @@ Word Predictor - 0.0.1 + 0.0.2
@@ -259,7 +259,7 @@

Examp em <- EnvManager$new(ve = ve, rp = "./") # The required files are downloaded ed <- em$setup_env(rf, fn) -# End of environment setup code +
#> [1] "CITATION" "examples" "extdata"
# End of environment setup code # The n-gram size n <- 4 diff --git a/docs/reference/index.html b/docs/reference/index.html index 8a6e168..cacd4f8 100644 --- a/docs/reference/index.html +++ b/docs/reference/index.html @@ -71,7 +71,7 @@ Word Predictor - 0.0.1 + 0.0.2
diff --git a/docs/reference/wordpredictor-package.html b/docs/reference/wordpredictor-package.html index 1c97b63..21d5764 100644 --- a/docs/reference/wordpredictor-package.html +++ b/docs/reference/wordpredictor-package.html @@ -79,7 +79,7 @@ Word Predictor - 0.0.1 + 0.0.2 diff --git a/man/DataCleaner.Rd b/man/DataCleaner.Rd index 56cd81c..734f9e9 100644 --- a/man/DataCleaner.Rd +++ b/man/DataCleaner.Rd @@ -57,13 +57,13 @@ em$td_env() ve <- 0 # Test data is read l <- c( - "If you think I’m wrong, send me a link to where it’s happened", - "We’re about 90percent done with this room", - "“This isn’t how I wanted it between us.”", - "Almost any “cute” breed can become ornamental", - "Once upon a time there was a kingdom with a castle…", + "If you think I'm wrong, send me a link to where it's happened", + "We're about 90percent done with this room", + "This isn't how I wanted it between us.", + "Almost any cute breed can become ornamental", + "Once upon a time there was a kingdom with a castle", "That's not a thing any of us are granted'", - "“Why are you being so difficult?” she asks." + "Why are you being so difficult? she asks." ) # The expected results res <- c( @@ -223,13 +223,13 @@ The cleaned lines of text. ve <- 0 # Test data is read l <- c( - "If you think I’m wrong, send me a link to where it’s happened", - "We’re about 90percent done with this room", - "“This isn’t how I wanted it between us.”", - "Almost any “cute” breed can become ornamental", - "Once upon a time there was a kingdom with a castle…", + "If you think I'm wrong, send me a link to where it's happened", + "We're about 90percent done with this room", + "This isn't how I wanted it between us.", + "Almost any cute breed can become ornamental", + "Once upon a time there was a kingdom with a castle", "That's not a thing any of us are granted'", - "“Why are you being so difficult?” she asks." + "Why are you being so difficult? she asks." ) # The expected results res <- c( diff --git a/tests/testthat/test-c-data-cleaner.R b/tests/testthat/test-c-data-cleaner.R index c013bc4..cbd5e00 100644 --- a/tests/testthat/test-c-data-cleaner.R +++ b/tests/testthat/test-c-data-cleaner.R @@ -29,13 +29,13 @@ test_that("Sample line of text are cleaned as expected", { # Test data is read l <- c( - "If you think I'm wrong, send me a link to where it's happened", - "We're about 90percent done with this room", - "This isn't how I wanted it between us.", - "Almost any cute breed can become ornamental", - "Once upon a time there was a kingdom with a castle", + "If you think I’m wrong, send me a link to where it’s happened", + "We’re about 90percent done with this room", + "“This isn’t how I wanted it between us.”", + "Almost any “cute” breed can become ornamental", + "Once upon a time there was a kingdom with a castle…", "That's not a thing any of us are granted'", - "Why are you being so difficult? she asks." + "“Why are you being so difficult?” she asks." ) # The expected results res <- c( diff --git a/vignettes/features.Rmd b/vignettes/features.Rmd index ca8ca32..f9dad89 100644 --- a/vignettes/features.Rmd +++ b/vignettes/features.Rmd @@ -77,7 +77,7 @@ fi <- da$get_file_info(ed) # The file information is printed print(fi) -# The test envionment is cleaned up +# The test environment is cleaned up clean_up(ve) ``` @@ -116,7 +116,7 @@ ds$generate_sample( is = T ) -# The test envionment is cleaned up +# The test environment is cleaned up clean_up(ve) ``` @@ -142,7 +142,7 @@ ds$generate_data( ) ) -# The test envionment is cleaned up +# The test environment is cleaned up clean_up(ve) ``` @@ -180,7 +180,7 @@ dc <- DataCleaner$new(fn, dc_opts, ve = ve) # The sample file is cleaned and saved as input-clean.txt in the ed dir dc$clean_file() -# The test envionment is cleaned up +# The test environment is cleaned up clean_up(ve) ``` @@ -207,7 +207,7 @@ for (n in 1:4) { tg$generate_tokens() } -# The test envionment is cleaned up +# The test environment is cleaned up clean_up(ve) ``` @@ -269,7 +269,7 @@ df <- da$plot_n_gram_stats(opts = list( fn <- paste0("./man/figures/coverage.png") knitr::include_graphics(fn) -# The test envionment is cleaned up +# The test environment is cleaned up clean_up(ve) ``` @@ -292,7 +292,7 @@ df <- df[order(df$freq, decreasing = T),] # The first 10 rows of the data frame are printed knitr::kable(df[1:10,], col.names = c("Prefix", "Frequency")) -# The test envionment is cleaned up +# The test environment is cleaned up clean_up(ve) ``` @@ -313,7 +313,7 @@ tp <- TPGenerator$new(opts = list(n = 4, dir = ed), ve = ve) # The combined transition probabilities are generated tp$generate_tp() -# The test envionment is cleaned up +# The test environment is cleaned up clean_up(ve) ``` @@ -353,7 +353,7 @@ mg <- ModelGenerator$new( # Generates n-gram model. The output is the file def-model.RDS mg$generate_model() -# The test envionment is cleaned up +# The test environment is cleaned up clean_up(ve) ``` @@ -377,7 +377,7 @@ me <- ModelEvaluator$new(mf = mfn, ve = ve) # The intrinsic evaluation is performed on first 20 lines stats <- me$intrinsic_evaluation(lc = 20, fn = vfn) -# The test envionment is cleaned up +# The test environment is cleaned up clean_up(ve) ``` @@ -398,7 +398,7 @@ me <- ModelEvaluator$new(mf = mfn, ve = ve) # The intrinsic evaluation is performed on first 100 lines stats <- me$extrinsic_evaluation(lc = 100, fn = vfn) -# The test envionment is cleaned up +# The test environment is cleaned up clean_up(ve) ``` @@ -421,6 +421,6 @@ mp <- ModelPredictor$new(mf = mfn, ve = ve) # next words are returned along with their respective probabilities. res <- mp$predict_word(words = "how are", 3) -# The test envionment is cleaned up +# The test environment is cleaned up clean_up(ve) ``` diff --git a/vignettes/overview.Rmd b/vignettes/overview.Rmd index 609c5f9..eb78847 100644 --- a/vignettes/overview.Rmd +++ b/vignettes/overview.Rmd @@ -141,7 +141,7 @@ mg <- ModelGenerator$new( # ./data/model/def-model.RDS mg$generate_model() -# The test envionment is cleaned up +# The test environment is cleaned up clean_up(ve) ``` @@ -165,7 +165,7 @@ me <- ModelEvaluator$new(mf = mfn, ve = ve) # The intrinsic evaluation is performed on first 20 lines stats <- me$intrinsic_evaluation(lc = 20, fn = vfn) -# The test envionment is cleaned up +# The test environment is cleaned up clean_up(ve) ``` @@ -186,7 +186,7 @@ me <- ModelEvaluator$new(mf = mfn, ve = ve) # The intrinsic evaluation is performed on first 100 lines stats <- me$extrinsic_evaluation(lc = 100, fn = vfn) -# The test envionment is cleaned up +# The test environment is cleaned up clean_up(ve) ``` @@ -208,7 +208,7 @@ mp <- ModelPredictor$new(mf = mfn, ve = ve) # Given the words: "how are", the next word is predicted. The top 3 most likely # next words are returned along with their respective probabilities. res <- mp$predict_word(words = "how are", 3) -# The test envionment is cleaned up +# The test environment is cleaned up clean_up(ve) ``` @@ -220,7 +220,7 @@ The wordpredictor package includes a demo called "word-predictor". The demo is a ## Package dependencies -The wordpredictor package uses the following packages: [digest](https://cran.r-project.org/package=digest), [dply](https://cran.r-project.org/package=dplyr), [ggplot2](https://cran.r-project.org/package=ggplot2), [pryr](https://cran.r-project.org/package=pryr), +The wordpredictor package uses the following packages: [digest](https://cran.r-project.org/package=digest), [dply](https://cran.r-project.org/package=dplyr), [ggplot2](https://cran.r-project.org/package=ggplot2), [R6](https://cran.r-project.org/package=R6), [testthat](https://cran.r-project.org/package=testthat) and [stingr](https://cran.r-project.org/package=stringr) @@ -232,6 +232,7 @@ The following packages were useful during package development: [lintr](https://cran.r-project.org/package=lintr) [styler](https://cran.r-project.org/package=styler) [pkgdown](https://cran.r-project.org/package=pkgdown) +[pryr](https://cran.r-project.org/package=pryr), ## Useful Links