fix #1 - add model param where needed, bumped ver

Author: sckott

.Rbuildignore

@@ -4,3 +4,4 @@
 ^CONDUCT\.md$
 ^README\.Rmd$
 cran-comments.md
+notes.md

DESCRIPTION

@@ -6,7 +6,7 @@ Description: The 'Microsoft Academic Knowledge' API provides programmatic access
 		(<https://academic.microsoft.com/>). Includes methods matching all 'Microsoft
 		Academic' API routes, including search, graph search, text similarity, and
 		interpret natural language query string.
-Version: 0.1.0.9219
+Version: 0.1.9.9110
 Authors@R: person("Scott", "Chamberlain", email = "myrmecocystus+r@gmail.com",
     role = c("aut", "cre"))
 License: MIT + file LICENSE

R/abstract.R

@@ -7,8 +7,8 @@
 #' ma_abstract(query = "Y=[2010, 2012)", count = 10)
 #' }
 ma_abstract <- function(query, count = 10, offset = 0, orderby = NULL,
-                        key = NULL, ...) {
-  out <- ma_evaluate(query, count, offset, orderby, c("Id", "E"), key, ...)
+                        model = "latest", key = NULL, ...) {
+  out <- ma_evaluate(query, count, offset, orderby, c("Id", "E"), model, key, ...)
   unname(vapply(out$E, function(z) invabs2abs(jsonlite::fromJSON(z)$IA), ""))
 }
 

R/calchistogram.R

@@ -8,10 +8,15 @@
 #' res$histograms$histogram
 #' }
 ma_calchist <- function(query, count = 10, offset = 0,
-  atts = c("Id", "AA.AuN", "J.JN", "Ti", "Y", "E", "CC"), key = NULL, ...) {
+  atts = c("Id", "AA.AuN", "J.JN", "Ti", "Y", "E", "CC"), model = "latest", 
+  key = NULL, ...) {
 
+  assert(model, "character")
+  if (!model %in% c('latest', 'beta-2015')) {
+    stop("model must be one or 'latest' or 'beta-2015'")
+  }    
   if (!is.null(atts)) atts <- paste0(atts, collapse = ",")
   args <- comp(list(expr = query, count = count, offset = offset,
-                    attributes = atts))
+                    attributes = atts, model = model))
   ma_HTTP("academic/v1.0/calchistogram", args, key, ...)
 }

R/evaluate.R

@@ -8,6 +8,8 @@
 #' @param atts (character) fields to return, in a character vector. See
 #' <https://docs.microsoft.com/en-us/azure/cognitive-services/academic-knowledge/entityattributes>
 #' for details.
+#' @param model (character) Name of the model that you wish to query. One of 'latest' 
+#' or 'beta-2015'. Default: latest
 #' @param key (character) microsoft academic API key, see Details.
 #' @param ... curl options passed on to [crul::HttpClient]
 #' @return a list of length two, with `expr` (character) and
@@ -31,11 +33,16 @@
 #' ma_evaluate(x)
 #' }
 ma_evaluate <- function(query, count = 10, offset = 0, orderby = NULL,
-  atts = c("Id", "AA.AuN", "J.JN", "Ti", "Y", "E", "CC"), key = NULL, ...) {
+  atts = c("Id", "AA.AuN", "J.JN", "Ti", "Y", "E", "CC"), model = "latest", 
+  key = NULL, ...) {
 
+  assert(model, "character")
+  if (!model %in% c('latest', 'beta-2015')) {
+    stop("model must be one or 'latest' or 'beta-2015'")
+  }
   if (!is.null(atts)) atts <- paste0(atts, collapse = ",")
   args <- comp(list(expr = query, count = count, offset = offset,
-                          orderby = orderby, attributes = atts))
+    orderby = orderby, attributes = atts, model = model))
   tibble::as_tibble(
     ma_HTTP("academic/v1.0/evaluate", args, key, ...)$entities
   )

R/search.R

@@ -13,10 +13,10 @@
 #' }
 ma_search <- function(query, count = 10, offset = 0, orderby = NULL,
                       atts = c("Id", "AA.AuN", "J.JN", "Ti", "Y", "E", "CC"),
-                      key = NULL, ...) {
+                      model = "latest", key = NULL, ...) {
 
   if (!is.null(atts)) atts <- paste0(atts, collapse = ",")
-  out <- ma_evaluate(query, count, offset, orderby, atts, key, ...)
+  out <- ma_evaluate(query, count, offset, orderby, atts, model, key, ...)
   ee <- dfrbl(lapply(out$E, function(z) {
     dat <- jsonlite::fromJSON(z)
     dat <- dat[names(dat) %in% c('DN', 'VFN', 'DOI', 'D')]

R/similarity.R

@@ -3,8 +3,14 @@
 #' @export
 #' @param s1,s2 (character) strings 1 and 2. required
 #' @param method (character) one of GET (default) or POST
+#' @param model (character) Name of the model that you wish to query. One of 'latest' 
+#' or 'beta-2015'. Default: latest
 #' @param key (character) microsoft academic API key, see [microdemic]
 #' @param ... curl options passed on to [crul::HttpClient]
+#' @return a single value representing the cosine similarity of the text inputs of 
+#' s1 and s2. The output is represented by a floating point between -1.0 and +1.0. 
+#' The similarity API evaluates the strings base on their academic concepts, 
+#' with +1.0 being the most similar and -1.0 being the least similar.
 #' @examples \dontrun{
 #' s1 <- "Using complementary priors, we derive a fast greedy algorithm that
 #' can learn deep directed belief networks one layer at a time, provided the
@@ -18,14 +24,21 @@
 #'
 #' ma_similarity(s1, s2, method = "POST")
 #' }
-ma_similarity <- function(s1, s2, method = "GET", key = NULL, ...) {
+ma_similarity <- function(s1, s2, method = "GET", model = "latest", key = NULL, ...) {
   if (!method %in% c("GET", "POST")) stop("'method' must be one of GET or POST")
+  
+  assert(model, "character")
+  if (!model %in% c('latest', 'beta-2015')) {
+    stop("model must be one or 'latest' or 'beta-2015'")
+  }
+
   if (method == "GET") {
-    args <- comp(list(s1 = s1, s2 = s2))
+    args <- comp(list(s1 = s1, s2 = s2, model = model))
     ma_HTTP("academic/v1.0/similarity", args, key, ...)
   } else {
-    args <- sprintf("s1=%s&s2=%s", s1, s2)
+    args <- comp(list(model = model))
+    body <- sprintf("s1=%s&s2=%s", s1, s2)
     ma_HTTP("academic/v1.0/similarity", NULL, key = key,
-            method = 'POST', body = args, ...)
+            method = 'POST', args = args, body = body, ...)
   }
 }

R/zzz.R

@@ -11,6 +11,7 @@ ma_HTTP <- function(path, args, key, method = "GET", body = list(),
       `Ocp-Apim-Subscription-Key` = key
     )
   )
+  if (method == "POST") cli$headers$`Content-Type` <- "application/x-www-form-urlencoded"
   if (!is.null(ctype)) cli$headers <- c(cli$headers, `Content-Type` = ctype)
   res <- switch(
     method,