do not use import_

base/__init__.r

@@ -12,10 +12,10 @@ export_submodule('./refactor')
 export_submodule('./relevel')
 export_submodule('./lnapply')
 
-outer = import_('./outer')$outer
+outer = import('./outer')$outer
 
-omit = import_('./omit')
-list = import_('./list')
+omit = import('./omit')
+list = import('./list')
 
 library(dplyr) # in global env
 #`%>%` = magrittr::`%>%`

base/lambda.r

@@ -1,4 +1,4 @@
-fun = import_('./functional')
+fun = import('./functional')
 
 #' Define a single-argument function
 #'

base/list.r

@@ -1,4 +1,4 @@
-import_('../base/operators')
+import('../base/operators')
 
 # http://stackoverflow.com/questions/8139677
 flatten = function(x, vectors=FALSE) {

base/match.r

@@ -1,8 +1,8 @@
 ###
 ### general utility functions without specific use
 ###
-.op = import_('./operators', attach_operators=FALSE)
-.omit = import_('./omit')
+.op = import('./operators', attach_operators=FALSE)
+.omit = import('./omit')
 
 #' match() function with extended functionality
 #'

base/omit.r

@@ -63,7 +63,7 @@ empty = function(x, drop=FALSE, omit=TRUE) {
 #' @param drop  Whether to drop unused dimensions after removing NAs
 #' @param omit  Whether or not to perform action
 dups = function(x, ..., drop=FALSE, omit=TRUE) {
-    dup = import_('./duplicated')$duplicated
+    dup = import('./duplicated')$duplicated
 
     if (!omit)
         x

base/refactor.r

@@ -1,4 +1,4 @@
-import_('./operators')
+import('./operators')
 
 #' Creates a factor where levels are ordered by an external value
 #' 

base/util.r

@@ -1,4 +1,4 @@
-import_('./operators')
+import('./operators')
 
 grep = function(pattern, x, ...) {
     # http://stackoverflow.com/questions/2969315

base/vector.r

@@ -1,4 +1,4 @@
-import_('./functional', attach = TRUE)
+import('./functional', attach = TRUE)
 
 #' Create a logical vector from a numeric index vector
 #'

data_frame/assemble.r

@@ -1,5 +1,5 @@
-import_('../base/operators')
-.ar = import_('../array')
+import('../base/operators')
+.ar = import('../array')
 
 #' Creates a data.frame from named vectors
 #'

data_frame/create_formula_index.r

@@ -11,8 +11,8 @@
 # could i maybe use a grouped data_frame for this?
 
 # start with st$.assocs_subset here, leave the row-wise calls to df$call
-.b = import_('../base', attach_operators=FALSE)
-.gfd = import_('./get_formula_data')
+.b = import('../base', attach_operators=FALSE)
+.gfd = import('./get_formula_data')
 
 #' Gathers all data required for a formula and creates a subsetting index
 #'

data_frame/wrap_formula_indexing.r

@@ -29,9 +29,9 @@ wrap_formula_indexing = function(FUN) {
             do.call(FUN, call_args)
         }
 
-        df = import_('../data_frame')
-        idx = import_('../base/indexing')
-        func = import_('../base/functional')
+        df = import('../data_frame')
+        idx = import('../base/indexing')
+        func = import('../base/functional')
         ci = import('../data_frame/create_formula_index')
 
         # replace with: call_args = as.list(func$eval_call())[-1] ?

io/binary.r

@@ -1,5 +1,5 @@
 # I/O helper functions on R binary files
-.b = import_('../base')
+.b = import('../base')
 .l1k = import('./l1ktools_io')
 
 #' Loads .gctx files

io/text.r

@@ -1,5 +1,5 @@
 # I/O helper functions on text files
-.b = import_('../base', attach_operators = FALSE)
+.b = import('../base', attach_operators = FALSE)
 
 #' Add \code{ext}ension parameter to \link{\code{base::file.path}}
 file_path = function (..., ext = NULL, fsep = .Platform$file.sep) {

plot/__init__.r

@@ -11,4 +11,4 @@ export_submodule('./venn') # bad style
 export_submodule('./color')
 export_submodule('./symmetrise_scale')
 
-brew = import_('./brew')
+brew = import('./brew')

plot/color.r

@@ -27,7 +27,7 @@ p_effect = function(df, pvalue="p.value", effect="estimate", dir=1, thresh=0.05)
 }
 
 # Graphics helpers
-import_('../base/functional', attach = TRUE)
+import('../base/functional', attach = TRUE)
 
 # Color helper functions {{{
 transparent = function (colors, alpha = 0.5) {

plot/linear_fit.r

@@ -1,6 +1,6 @@
-.b = import_('../base')
-.st = import_('../stats')
-#.spf = import_('../stats/process_formula')
+.b = import('../base')
+.st = import('../stats')
+#.spf = import('../stats/process_formula')
 
 #' Plots a given data.frame as a linear fit with optional subsets
 #'

plot/matrix.r

@@ -1,5 +1,5 @@
-.b = import_('../base')
-.ar = import_('../array')
+.b = import('../base')
+.ar = import('../array')
 
 #' Cluster the rows and columns, order factor levels to respect that
 #'

plot/volcano.r

@@ -1,7 +1,7 @@
 library(ggrepel)
-.b = import_('../base')
-import_('./helpers', attach=TRUE)
-color = import_('./color')
+.b = import('../base')
+import('./helpers', attach=TRUE)
+color = import('./color')
 
 #' Draw a volcano plot from calculated associations
 #'
@@ -88,7 +88,7 @@ volcano = function(df, base.size=1, p=0.05, label_top=20, ceil=0, check_overlap=
 if (is.null(module_name())) {
     library(testthat)
 
-    color = import_('./color')
+    color = import('./color')
     df = data.frame(estimate = -12:12/12)
     df$adj.p = 10^(-10*abs(df$estimate))
     df$label = LETTERS[1:25]

process/idmap/gene.r

@@ -1,7 +1,7 @@
 library(dplyr)
-.b = import_('../../base')
-.io = import_('../../io')
-.ar = import_('../../array')
+.b = import('../../base')
+.io = import('../../io')
+.ar = import('../../array')
 .guess_id_type = import('./guess_id_type')$guess_id_type
 
 #' Gene ID mapping function

process/idmap/probeset.r

@@ -1,7 +1,7 @@
 library(dplyr)
-.b = import_('../../base')
-.io = import_('../../io')
-.ar = import_('../../array')
+.b = import('../../base')
+.io = import('../../io')
+.ar = import('../../array')
 .guess_id_type = import('./guess_id_type')$guess_id_type
 
 #' probeset ID mapping function

process/microarray/normalize.r

@@ -1,4 +1,4 @@
-.b = import_('../../base')
+.b = import('../../base')
 
 #' Function to normalize expression objects
 #'

stats/__init__.r

@@ -1,14 +1,14 @@
 export_submodule('./nmf')
 export_submodule('./util')
 export_submodule('./roc')
-batch = import_('./batch')
-cor = import_('./correlation')
+batch = import('./batch')
+cor = import('./correlation')
 fishers_exact_test = import('./fishers_exact_test')$fishers_exact_test
 hypergeometric_test = import('./hypergeometric_test')$hypergeometric_test
 
-.wrap = import_('../data_frame/wrap_formula_indexing')
+.wrap = import('../data_frame/wrap_formula_indexing')
 for (fname in list.files(module_file('export_indexed'), "\\.r$", recursive=TRUE)) {
-    .mod = import_(paste0("./export_indexed/", sub("\\.r$", "", fname)))
+    .mod = import(paste0("./export_indexed/", sub("\\.r$", "", fname)))
     .FUN = ls(.mod)
     assign(.FUN, .wrap$wrap_formula_indexing(.mod[[.FUN]]))
 }

stats/batch.r

@@ -1,4 +1,4 @@
-.ar = import_('../array')
+.ar = import('../array')
 
 merge = function(method, X, batch, covariate=NULL) {
     if (method == "combat")

stats/export_indexed/coxph.r

@@ -1,4 +1,4 @@
-import_('../../base/operators')
+import('../../base/operators')
 
 #' Function to calculate and return a cleaned Cox proportional hazards model
 #'

stats/export_indexed/lm.r

@@ -1,4 +1,4 @@
-import_('../../base/operators')
+import('../../base/operators')
 
 #' Function to calculate and return a cleaned linear model
 #'

stats/export_indexed/rlm.r

@@ -1,4 +1,4 @@
-import_('../../base/operators')
+import('../../base/operators')
 
 #' Function to calculate and return a cleaned linear model
 #'

stats/nmf.r

@@ -1,7 +1,7 @@
 # this should use data_frame infrastructure to calculate NMF clustering, optionally in cluster jobs
-.b = import_('../base')
-.io = import_('../io')
-.df = import_('../data_frame')
+.b = import('../base')
+.io = import('../io')
+.df = import('../data_frame')
 
 #' Wrapper function that takes k, num.clusterings and performs max_iter iterations
 #'

stats/util.r

@@ -1,4 +1,4 @@
-.b = import_('../base')
+.b = import('../base')
 
 overlap_normals = function(mu1, sd1, mu2, sd2) {
     min.f1f2 = function(x, mu1, mu2, sd1, sd2) {

text.r

@@ -1,6 +1,6 @@
 # String helper functions
 
-import_('./base/functional', attach = TRUE)
+import('./base/functional', attach = TRUE)
 
 ltrim = lp(sub, '^ +', '')