finalize tests

R/sentomeasures_methods.R

@@ -235,6 +235,7 @@ summary.sentomeasures <- function(object, ...) {
   cat("\n")
   cat("Aggregate statistics:", "\n")
   print(round(rowMeans(sentomeasures$stats), 5))
+  NULL
 }
 
 #' @export

README.md

@@ -2,11 +2,11 @@
 ## sentometrics: An Integrated Framework for Textual Sentiment Time Series Aggregation and Prediction
 
 <!--- comment out when submitting to CRAN until CRAN/pandoc issues (e.g. handshake) solved --->
-[![Build Status](https://travis-ci.org/sborms/sentometrics.svg?branch=master)](https://travis-ci.org/sborms/sentometrics)
 [![CRAN](http://www.r-pkg.org/badges/version/sentometrics)](https://cran.r-project.org/package=sentometrics)
+[![Build Status](https://travis-ci.org/sborms/sentometrics.svg?branch=master)](https://travis-ci.org/sborms/sentometrics)
+[![codecov](https://codecov.io/github/sborms/sentometrics/branch/master/graphs/badge.svg)](https://codecov.io/github/sborms/sentometrics) 
 [![Downloads](http://cranlogs.r-pkg.org/badges/sentometrics?color=brightgreen)](http://www.r-pkg.org/pkg/sentometrics)
 [![Downloads](http://cranlogs.r-pkg.org/badges/grand-total/sentometrics?color=brightgreen)](http://www.r-pkg.org/pkg/sentometrics)
-[![codecov](https://codecov.io/github/sborms/sentometrics/branch/master/graphs/badge.svg)](https://codecov.io/github/sborms/sentometrics) 
 <!--- [![Pending Pull-Requests](http://githubbadges.herokuapp.com/sborms/sentometrics/pulls.svg?style=flat)](https://github.com/sborms/sentometrics/pulls) --->
 <!--- [![Github Issues](http://githubbadges.herokuapp.com/sborms/sentometrics/issues.svg)](https://github.com/sborms/sentometrics/issues) --->
 

tests/testthat/test_aggregation.R

@@ -9,14 +9,20 @@ corpus <- quanteda::corpus_sample(sento_corpus(corpusdf = usnews), size = 1000)
 
 data("list_lexicons")
 lex <- list_lexicons[c("GI_en", "LM_en")]
-ctr <- ctr_agg(howWithin = "tf-idf", howDocs = "proportional", howTime = "almon", by = "month",
-               lag = 3, ordersAlm = 1:3, do.inverseAlm = TRUE)
-
-sentMeas <- sento_measures(corpus, lex, ctr)
 
 ### tests from here ###
 
+ctr1 <- ctr_agg(howWithin = "tf-idf", howDocs = "equal_weight", howTime = "almon", by = "month",
+               lag = 5, ordersAlm = 1:3, do.inverseAlm = TRUE)
+sentMeas1 <- sento_measures(corpus, lex, ctr1)
+
+ctr2 <- ctr_agg(howWithin = "tf-idf", howDocs = "proportional", howTime = c("equal_weight", "linear", "own"), by = "year",
+               lag = 2, weights = data.frame(q1 = c(0.25, 0.75), q3 = c(0.75, 0.25)))
+sentMeas2 <- sento_measures(corpus, lex, ctr2)
+
+# sento_measures
 test_that("Number of columns coincide with provided dimensions", {
-  expect_equal(nmeasures(sentMeas), length(sentMeas$features) * length(lex) * length(sentMeas$time))
+  expect_equal(nmeasures(sentMeas1), length(sentMeas1$features) * length(sentMeas1$lexicons) * length(sentMeas1$time))
+  expect_equal(nmeasures(sentMeas2), length(sentMeas2$features) * length(sentMeas2$lexicons) * length(sentMeas2$time))
 })
 

tests/testthat/test_methods_sentomeasures.R

@@ -42,13 +42,19 @@ test_that("Scaling is properly done", {
   expect_equal(s1$stats["sd", ], s4$stats["sd", ])
 })
 
-# plot
+# summary.sentomeasures, print.sentomeasures
+test_that("No output returned when object summarized or printed", {
+  expect_null(summary(sentMeas))
+  expect_null(print(sentMeas))
+})
+
+# plot.sentomeasures
 p <- plot(sentMeas, group = sample(c("features", "lexicons", "time"), 1))
 test_that("Plot is a ggplot object", {
   expect_true(inherits(p, "ggplot"))
 })
 
-# get_measures (to_long)
+# get_measures, to_long
 measuresLong <- get_measures(sentMeas, format = "long")
 test_that("Proper long formatting of sentiment measures", {
   expect_true(nrow(measuresLong) == nobs(sentMeas) * nmeasures(sentMeas))

tests/testthat/test_model_specification.R

@@ -57,6 +57,7 @@ out8 <- sento_model(sentomeasures, y, x = x, ctr = ctrM8)
 ctrM9 <- ctrM8
 ctrM9$nSample <- N - 1 - 2 + 1
 
+# sento_model
 test_that("Different model specifications give specified output", {
   expect_equal(N - 8, nrow(out1$x))
   expect_equal(N - 1, nrow(out2$x))
@@ -73,5 +74,27 @@ test_that("Different model specifications give specified output", {
   expect_true(all(sapply(c(list(out1, out2, out3, out4, out5, out7), out8$models),
                          function(out) stats::coef(out$reg)[c("x1", "x2"), ]) != 0))
   expect_error(sento_model(sentomeasures, y, x = x, ctr = ctrM9))
+  expect_null(summary(out1))
+  expect_null(summary(out5))
+  expect_null(summary(out6))
+  expect_null(summary(out8))
+})
+
+# summary.sentomodel, summary.sentomodeliter, print.sentomodel, print.sentomodeliter
+test_that("No output returned when object summarized or printed", {
+  expect_null(summary(out1))
+  expect_null(summary(out5))
+  expect_null(summary(out6))
+  expect_null(summary(out8))
+  expect_null(print(out1))
+  expect_null(print(out5))
+  expect_null(print(out6))
+  expect_null(print(out8))
+})
+
+# plot.sentomodeliter
+p <- plot(out8)
+test_that("Plot is a ggplot object", {
+  expect_true(inherits(p, "ggplot"))
 })
 

tests/testthat/test_sentiment_computation.R

@@ -10,28 +10,31 @@ data("usnews")
 corpus <- sento_corpus(corpusdf = usnews[1:250, ])
 
 data("list_lexicons")
-lex <- setup_lexicons(list_lexicons[c("GI_en", "LM_en", "HENRY_en")],
-                      list_valence_shifters[["en"]])
+lex <- setup_lexicons(list_lexicons[c("GI_en", "LM_en", "HENRY_en")], list_valence_shifters[["en"]])
+lexSplit <- setup_lexicons(list_lexicons[c("GI_en", "LM_en", "HENRY_en")], list_valence_shifters[["en"]], do.split = TRUE)
 
 ### tests from here ###
 
-sentiment <- list(
+sentimentList <- list(
   s1 = compute_sentiment(quanteda::texts(corpus), lex, how = "counts"),
   s2 = compute_sentiment(quanteda::texts(corpus), lex, how = "tf-idf"),
   s3 = compute_sentiment(quanteda::texts(corpus), lex, how = "proportional"),
   s4 = compute_sentiment(quanteda::texts(corpus), lex, how = "proportionalPol"),
   s5 = compute_sentiment(quanteda::corpus(usnews[1:250, "texts"]), lex, how = "counts"),
   s6 = compute_sentiment(quanteda::corpus(usnews[1:250, c("texts", "wsj", "economy")], text_field = "texts"),
                          lex, how = "counts"),
-  s7 = compute_sentiment(corpus, lex, how = "counts")
+  s7 = compute_sentiment(corpus, lex, how = "counts"),
+  s8 = compute_sentiment(quanteda::texts(corpus), lexSplit, how = "counts")
 )
 test_that("Agreement between sentiment scores across input objects", {
-  expect_true(all(unlist(lapply(sentiment, function(s) nrow(s[["sentiment"]]) == 250))))
-  expect_true(all(unlist(lapply(sentiment, function(s) all(s[["sentiment"]][["word_count"]]
-                                == sentiment$s1$sentiment$word_count)))))
-  expect_equivalent(sentiment$s1$sentiment[, c("GI_en", "LM_en", "HENRY_en")],
-                    sentiment$s5$sentiment[, c("GI_en", "LM_en", "HENRY_en")])
-  expect_equivalent(sentiment$s6$sentiment[, -c(1:2)],
-                    sentiment$s7$sentiment[, colnames(sentiment$s6$sentiment)[-c(1:2)], with = FALSE])
+  expect_true(all(unlist(lapply(sentimentList, function(s) nrow(s$sentiment) == 250))))
+  expect_true(all(unlist(lapply(sentimentList, function(s) all(s$sentiment$word_count
+                                                               == sentimentList$s1$sentiment$word_count)))))
+  expect_equivalent(sentimentList$s1$sentiment[, c("GI_en", "LM_en", "HENRY_en")],
+                    sentimentList$s5$sentiment[, c("GI_en", "LM_en", "HENRY_en")])
+  expect_equivalent(sentimentList$s6$sentiment[, -c(1:2)],
+                    sentimentList$s7$sentiment[, colnames(sentimentList$s6$sentiment)[-c(1:2)], with = FALSE])
+  expect_true(all(sentimentList$s8$sentiment[, c("GI_en_POS", "LM_en_POS", "HENRY_en_POS")] >= 0))
+  expect_true(all(sentimentList$s8$sentiment[, c("GI_en_NEG", "LM_en_NEG", "HENRY_en_NEG")] <= 0))
 })