Checked documentation examples in prep for next push to CRAN. close #195

R/as.tdm.R

@@ -66,15 +66,15 @@
 #' speech <- stemmer(dat$dialogue)
 #' mytable1 <- with(dat, as.tdm(speech, list(person, time), stopwords = Top25Words))
 #' 
-#' fit <- ca(mytable1)
+#' fit <- ca(as.matrix(ytable1))
 #' summary(fit)
 #' plot(fit)
 #' plot3d.ca(fit, labels=1)
 #' 
 #' 
 #' mytable2 <- with(dat, as.tdm(speech, list(person, time), stopwords = Top200Words))
 #' 
-#' fit2 <- ca(mytable2)
+#' fit2 <- ca(as.matrix(mytable2))
 #' summary(fit2)
 #' plot(fit2)
 #' plot3d.ca(fit2, labels=1)

R/cm_time2long.R

@@ -52,7 +52,7 @@
 #' )
 #'
 #' ## General ldots Approach
-#' cm_time2long(bar)
+#' cm_time2long(bar1)
 #' cm_time2long(bar1, bar2, v.name="time")
 #' 
 #' ## Specify `object` Approach

R/discourse_map.R

@@ -130,7 +130,7 @@
 #' library(animation)
 #' library(igraph)
 #' 
-#' loc <- folder(animation_dialogue)
+#' loc <- reports::folder(animation_dialogue)
 #' ans <- Animate(test)
 #' 
 #' ## Set up the plotting function
@@ -164,7 +164,7 @@
 #' ## More Elaborate Layout
 #' test2 <- with(mraja1, discourse_map(dialogue, person))
 #' 
-#' loc2 <- folder(animation_dialogue2)
+#' loc2 <- reports::folder(animation_dialogue2)
 #' ans2 <- Animate(test2)
 #' ## Set up the plotting function
 #' oopt <- animation::ani.options(interval = 0.1)

R/formality.R

@@ -138,7 +138,7 @@
 #' form_bar <- Animate(form_ani2, as.network=FALSE)
 #' 
 #' ## Generate a folder
-#' loc <- folder(animation_formality)
+#' loc <- reports::folder(animation_formality)
 #' 
 #' ## Set up the plotting function
 #' oopt <- animation::ani.options(interval = 0.1)

R/pronoun_type.R

@@ -37,13 +37,13 @@
 #' \code{\link[qdap]{subject_pronoun_type}}
 #' @export
 #' @references
-#' Fairclough, N. (1989). Language and Power. London: Longman. \cr
+#' Fairclough, N. (1989). Language and power. London: Longman. \cr
 #' 
-#' Fairclough, N. (2003). Analysing Discourse: Textual Analysis for Social 
-#' Research. Oxford and New York: Routledge.\cr 
+#' Fairclough, N. (2003). Analysing discourse: Textual analysis for social 
+#' research. Oxford and New York: Routledge.\cr 
 #' 
-#' Okamura, A. (2009). Use of Personal Pronouns In Two Types of Monologic 
-#' Academic Speech.  The Economic Journal of Takasaki City University of 
+#' Okamura, A. (2009). Use of personal pronouns in two types of monologic 
+#' academic speech.  The Economic Journal of Takasaki City University of 
 #' Economics, 52(1). 17-26. \cr
 #' 
 #' Us and them: Social categorization and the process of intergroup bias. 

R/sentSplit.R

@@ -17,6 +17,8 @@
 #' @param text.place A character string giving placement location of the text 
 #' column. This must be one of the strings \code{"original"}, \code{"right"} or 
 #' \code{"left"}.
+#' @param verbose logical.  If \code{TRUE} select diagnostics from 
+#' \code{\link[qdap]{check_text}} are reported. 
 #' @param \ldots Additional options passed to \code{\link[qdap]{stem2df}}.
 #' @param grouping.var The grouping variables.  Default \code{NULL} generates 
 #' one word list for all text.  Also takes a single grouping variable or a list 
@@ -81,16 +83,18 @@
 sentSplit <-
 function(dataframe, text.var, rm.var = NULL, endmarks = c("?", ".", "!", "|"), 
     incomplete.sub = TRUE, rm.bracket = TRUE, stem.col = FALSE, 
-    text.place = "right", ...) {
+    text.place = "right", verbose = is.global(2),  ...) {
 
-    checks <- check_text(dataframe[[text.var]])
-    checks <- checks[!names(checks) %in% c("double_punctuation", 
-        "missing_value", "potentially_misspelled")]
-    pot_probs <- !sapply(checks, is.null)
-    if(sum(pot_probs) > 0) {
-        probs <- gsub("_", " ", paste(names(pot_probs)[pot_probs], collapse=", "))
-        warning("The following problems were detected:\n", probs, 
-            "\n\n*Consider running `check_text`")
+    if (verbose) {
+        checks <- check_text(dataframe[[text.var]])
+        checks <- checks[!names(checks) %in% c("double_punctuation", 
+            "missing_value", "potentially_misspelled")]
+        pot_probs <- !sapply(checks, is.null)
+        if(sum(pot_probs) > 0) {
+            probs <- gsub("_", " ", paste(names(pot_probs)[pot_probs], collapse=", "))
+            warning("The following problems were detected:\n", probs, 
+                "\n\n*Consider running `check_text`")
+        }
     }
 
     if (is.null(rm.var)) {

R/synonyms.R

@@ -39,7 +39,7 @@
 #' synonyms_frame(syn_dat)
 #' syn(c("R", "show"), synonym.frame = syn_frame(syn_dat))
 #' 
-#' syns.hash <- syn_frame(syn_dat, prior.frame = SYNONYM)
+#' syns.hash <- syn_frame(syn_dat, prior.frame = qdapDictionaries::key.syn)
 #' syn(c("R", "show", "like", "robot"), synonym.frame = syns.hash)
 #' }
 synonyms <- function(terms, return.list = TRUE, 
@@ -92,12 +92,12 @@ syn <- synonyms
 #' 
 #' @param synonym.list A named list of lists (or vectors) of synonyms.
 #' @param prior.frame A prior synonyms data.frame in the format produced by 
-#' \code{synonym_frame}.
+#' \code{synonyms_frame}.
 #' @export
 #' @importFrom qdapTools list2df
 #' @rdname synonyms
 synonyms_frame <- function(synonym.list, prior.frame) {
-    
+
     synonym.list <- lapply(synonym.list, function(x) {
         if(is.list(x)) {
             x
@@ -110,7 +110,12 @@ synonyms_frame <- function(synonym.list, prior.frame) {
     phase3 <- list2df(lapply(phase2, paste, collapse = " @@@@ "), 
         col2 = "word", col1 = "match.string")[2:1]
     phase3[] <- lapply(phase3, as.character)
+
     if (!missing(prior.frame)) {
+
+        class(prior.frame) <- "data.frame"
+        suppressWarnings(colnames(prior.frame) <- colnames(phase3))
+
         phase3 <- data.frame(rbind(phase3, 
             prior.frame[!prior.frame[, "word"] %in%  phase3[, "word"], ]
         ), stringsAsFactors = FALSE)

man/as.tdm.Rd

@@ -281,15 +281,15 @@ dat <- dat[dat$person \%in\% qcv(ROMNEY, OBAMA), ]
 speech <- stemmer(dat$dialogue)
 mytable1 <- with(dat, as.tdm(speech, list(person, time), stopwords = Top25Words))
 
-fit <- ca(mytable1)
+fit <- ca(as.matrix(ytable1))
 summary(fit)
 plot(fit)
 plot3d.ca(fit, labels=1)
 
 
 mytable2 <- with(dat, as.tdm(speech, list(person, time), stopwords = Top200Words))
 
-fit2 <- ca(mytable2)
+fit2 <- ca(as.matrix(mytable2))
 summary(fit2)
 plot(fit2)
 plot3d.ca(fit2, labels=1)

man/cm_time2long.Rd

@@ -59,7 +59,7 @@ bar2 <- list(
 )
 
 ## General ldots Approach
-cm_time2long(bar)
+cm_time2long(bar1)
 cm_time2long(bar1, bar2, v.name="time")
 
 ## Specify `object` Approach

man/discourse_map.Rd

@@ -145,7 +145,7 @@ dev.off()
 library(animation)
 library(igraph)
 
-loc <- folder(animation_dialogue)
+loc <- reports::folder(animation_dialogue)
 ans <- Animate(test)
 
 ## Set up the plotting function
@@ -179,7 +179,7 @@ saveHTML(FUN(), autoplay = FALSE, loop = TRUE, verbose = FALSE,
 ## More Elaborate Layout
 test2 <- with(mraja1, discourse_map(dialogue, person))
 
-loc2 <- folder(animation_dialogue2)
+loc2 <- reports::folder(animation_dialogue2)
 ans2 <- Animate(test2)
 ## Set up the plotting function
 oopt <- animation::ani.options(interval = 0.1)

man/formality.Rd

@@ -151,7 +151,7 @@ bgb <- edge_apply(bgb, label.color="yellow")
 form_bar <- Animate(form_ani2, as.network=FALSE)
 
 ## Generate a folder
-loc <- folder(animation_formality)
+loc <- reports::folder(animation_formality)
 
 ## Set up the plotting function
 oopt <- animation::ani.options(interval = 0.1)

man/pronoun_type.Rd

@@ -71,13 +71,13 @@ plot(out2, 3, ncol=7)
 }
 }
 \references{
-Fairclough, N. (1989). Language and Power. London: Longman. \cr
+Fairclough, N. (1989). Language and power. London: Longman. \cr
 
-Fairclough, N. (2003). Analysing Discourse: Textual Analysis for Social
-Research. Oxford and New York: Routledge.\cr
+Fairclough, N. (2003). Analysing discourse: Textual analysis for social
+research. Oxford and New York: Routledge.\cr
 
-Okamura, A. (2009). Use of Personal Pronouns In Two Types of Monologic
-Academic Speech.  The Economic Journal of Takasaki City University of
+Okamura, A. (2009). Use of personal pronouns in two types of monologic
+academic speech.  The Economic Journal of Takasaki City University of
 Economics, 52(1). 17-26. \cr
 
 Us and them: Social categorization and the process of intergroup bias.

man/sentSplit.Rd

@@ -8,7 +8,7 @@
 \usage{
 sentSplit(dataframe, text.var, rm.var = NULL, endmarks = c("?", ".", "!",
   "|"), incomplete.sub = TRUE, rm.bracket = TRUE, stem.col = FALSE,
-  text.place = "right", ...)
+  text.place = "right", verbose = is.global(2), ...)
 
 sentCombine(text.var, grouping.var = NULL, as.list = FALSE)
 
@@ -39,6 +39,9 @@ and replaces with \code{"|"}.}
 column. This must be one of the strings \code{"original"}, \code{"right"} or
 \code{"left"}.}
 
+\item{verbose}{logical.  If \code{TRUE} select diagnostics from
+\code{\link[qdap]{check_text}} are reported.}
+
 \item{\ldots}{Additional options passed to \code{\link[qdap]{stem2df}}.}
 
 \item{grouping.var}{The grouping variables.  Default \code{NULL} generates

man/synonyms.Rd

@@ -34,7 +34,7 @@ was found at the head of the output.}
 \item{synonym.list}{A named list of lists (or vectors) of synonyms.}
 
 \item{prior.frame}{A prior synonyms data.frame in the format produced by
-\code{synonym_frame}.}
+\code{synonyms_frame}.}
 }
 \value{
 Returns a list of vectors or vector of possible words that match
@@ -64,7 +64,7 @@ syn_dat <- list(
 synonyms_frame(syn_dat)
 syn(c("R", "show"), synonym.frame = syn_frame(syn_dat))
 
-syns.hash <- syn_frame(syn_dat, prior.frame = SYNONYM)
+syns.hash <- syn_frame(syn_dat, prior.frame = qdapDictionaries::key.syn)
 syn(c("R", "show", "like", "robot"), synonym.frame = syns.hash)
 }
 }