Merge pull request #417 from EDiLD/master

minor fixes

.gitignore

@@ -13,3 +13,4 @@ inst/doc/.texpadtmp/taxize_ms.log
 inst/doc/.texpadtmp/taxize_ms.out
 inst/doc/.texpadtmp/taxize_ms.synctex.gz
 .httr-oauth
+inst/vign/taxize_vignette_cache

DESCRIPTION

@@ -32,14 +32,14 @@ Depends:
 Imports:
     XML,
     RCurl (>= 1.6),
+    reshape2,
     stringr,
     plyr,
     httr (>= 0.2),
     jsonlite,
     foreach,
     ape,
     Taxonstand,
-    reshape2,
     data.table,
     vegan,
     bold

NAMESPACE

@@ -284,8 +284,9 @@ import(foreach)
 import(httr)
 import(jsonlite)
 import(plyr)
-import(reshape2)
 import(stringr)
 importFrom(bold,bold_tax_id)
 importFrom(bold,bold_tax_name)
+importFrom(reshape2,dcast)
+importFrom(reshape2,melt)
 importFrom(vegan,taxa2dist)

R/tax_agg.R

@@ -1,6 +1,7 @@
 #' Aggregate species data to given taxonomic rank
 #'
-#' @import reshape2
+#' @importFrom reshape2 melt
+#' @importFrom reshape2 dcast
 #'
 #' @param x Community data matrix. Taxa in columns, samples in rows.
 #' @param rank character; Taxonomic rank to aggregate by.

README.Rmd

@@ -178,36 +178,36 @@ For more examples see the [tutorial][tut]
 
 #### Stable version from CRAN
 
-```{r eval=FALSE}
+```{r install_stable, eval=FALSE}
 install.packages("taxize")
 ```
 
 #### Development version from GitHub
 
 Windows users install [Rtools](http://cran.r-project.org/bin/windows/Rtools/) first.
 
-```{r eval=FALSE}
+```{r install_dev, eval=FALSE}
 install.packages("devtools")
 devtools::install_github("taxize", "ropensci")
 ```
 
-```{r}
+```{r load}
 library('taxize')
 ```
 
 ### Get unique taxonomic identifier from NCBI
 
 Alot of `taxize` revolves around taxonomic identifiers. Because, as you know, names can be a mess (misspelled, synonyms, etc.), it's better to get an identifier that a particular data sources knows about, then we can move forth acquiring more fun taxonomic data.
 
-```{r}
+```{r get_uid}
 uids <- get_uid(c("Chironomus riparius", "Chaetopteryx"))
 ```
 
 ### Retrieve classifications
 
 Classifications - think of a species, then all the taxonomic ranks up from that species, like genus, family, order, class, kingdom.
 
-```{r}
+```{r classification}
 out <- classification(uids)
 lapply(out, head)
 ```
@@ -216,86 +216,86 @@ lapply(out, head)
 
 Get immediate children of _Salmo_. In this case, _Salmo_ is a genus, so this gives species within the genus.
 
-```{r}
+```{r children}
 children("Salmo", db = 'ncbi')
 ```
 
 ### Downstream children to a rank
 
 Get all species in the genus _Apis_
 
-```{r}
+```{r downstream}
 downstream("Apis", db = 'itis', downto = 'Species', verbose = FALSE)
 ```
 
 ### Upstream taxa
 
 Get all genera up from the species _Pinus contorta_ (this includes the genus of the species, and its co-genera within the same family).
 
-```{r}
+```{r upstream}
 upstream("Pinus contorta", db = 'itis', upto = 'Genus', verbose=FALSE)
 ```
 
 ### Get synonyms
 
-```{r}
+```{r synonyms}
 synonyms("Salmo friderici", db='ubio')
 ```
 
 ### Get taxonomic IDs from many sources
 
-```{r}
+```{r get_ids}
 get_ids(names="Salvelinus fontinalis", db = c('ubio','ncbi'), verbose=FALSE)
 ```
 
 You can limit to certain rows when getting ids in any `get_*()` functions
 
-```{r}
+```{r get_ids2}
 get_ids(names="Poa annua", db = "gbif", rows=1)
 ```
 
 Furthermore, you can just back all ids if that's your jam with the `get_*_()` functions (all `get_*()` functions with additional `_` underscore at end of function name)
 
-```{r}
+```{r get_ids_}
 get_ids_(c("Chironomus riparius", "Pinus contorta"), db = 'nbn', rows=1:3)
 ```
 
 ### Common names from scientific names
 
-```{r}
+```{r sci2comm}
 sci2comm('Helianthus annuus', db = 'itis')
 ```
 
 ### Scientific names from common names
 
-```{r}
+```{r comm2sci}
 comm2sci("black bear", db = "itis")
 ```
 
 ### Coerce codes to taxonomic id classes
 
 `numeric` to `uid`
 
-```{r}
+```{r as.uid}
 as.uid(315567)
 ```
 
 `list` to `uid`
 
-```{r}
+```{r as.uid2}
 as.uid(list("315567", "3339", "9696"))
 ```
 
 ### Coerce taxonomic id classes to a data.frame
 
-```{r}
+```{r as.uid3}
 out <- as.uid(c(315567, 3339, 9696))
 (res <- data.frame(out))
 ```
 
 ## Contributors
 
-+ [Scott Chamberlain](https://github.com/SChamberlain)
++ [Scott Chamberlain](https://github.com/sckott)
 + [Eduard Szöcs](https://github.com/EDiLD)
 + [Zachary Foster](https://github.com/zachary-foster)
 + [Carl Boettiger](https://github.com/cboettig)

inst/vign/taxize_vignette.Rmd

@@ -219,7 +219,7 @@ A_clas[[1]]$rank[tolower(A_clas[[1]]$name) %in% B3]
 
 If we find a direct match (here *Gammarus roeseli*), we are lucky. But we can also match Gammaridae with *Gammarus roeseli*, but on a lower taxonomic level. A more comprehensive and realistic example (matching a trait table with an abundance table) is given in the vignette on matching.
 
-[eol]: http://eol.org/
+[eol]: http://www.eol.org/
 [taxosaurus]: http://api.phylotastic.org/tnrs
 [ncbi]: http://www.ncbi.nlm.nih.gov/
 [itis]: http://www.itis.gov/