Unit Testing functions in meta-analysis sub-workflow

book_source/03_topical_pages/94_docker/04_models.Rmd

@@ -55,7 +55,7 @@ It is important values for `type` and `version` are set correct. The PEcAn code
 
 To build the docker image, we use a Dockerfile (see example below) and run the following command. This command will expect the Dockerfile to live in the model specific folder and the command is executed in the root pecan folder. It will copy the content of the pecan folder and make it available to the build process (in this example we do not need any additional files). 
 
-Since we can have multiple different versions of a model be available for PEcAn we ar using the following naming schema `pecan/model-<modeltype>-<version>:<pecan version`. For example the image below will be named pecan/model-ed2-git, since we do not specify the exact version it will be atomically be named `pecan/model-ed2-git:latest`.
+Since we can have multiple different versions of a model be available for PEcAn we are using the following naming schema `pecan/model-<modeltype>-<version>:<pecan version`. For example the image below will be named pecan/model-ed2-git, since we do not specify the exact version it will be atomically be named `pecan/model-ed2-git:latest`.
 
 ````bash
 docker build \

docker/depends/pecan_package_dependencies.csv

@@ -196,6 +196,7 @@
 "mockery","*","base/visualization","Suggests",FALSE
 "mockery","*","base/workflow","Suggests",FALSE
 "mockery","*","modules/data.atmosphere","Suggests",FALSE
+"mockery","*","modules/meta.analysis","Suggests",FALSE
 "mockery",">= 0.3.0","models/biocro","Suggests",FALSE
 "mockery",">= 0.4.3","base/db","Suggests",FALSE
 "MODISTools",">= 1.1.0","modules/data.remote","Imports",FALSE

modules/meta.analysis/DESCRIPTION

@@ -28,16 +28,17 @@ Description: The Predictive Ecosystem Carbon Analyzer (PEcAn) is a scientific
 Imports:
     coda (>= 0.18),
     lattice,
-    PEcAn.utils,
+    MASS,
     PEcAn.DB,
     PEcAn.logger,
-    MASS,
     PEcAn.settings,
+    PEcAn.utils,
     rjags
 Suggests:
     ggmcmc,
     ggplot2,
     knitr (>= 1.42),
+    mockery,
     rmarkdown (>= 2.19),
     testthat (>= 1.0.2)
 SystemRequirements: JAGS

modules/meta.analysis/R/meta.analysis.R

@@ -9,7 +9,7 @@
 
 ##' Trait Meta-analysis
 ##'
-##' Runs heirarchical meta-analysis of plant trait data
+##' Runs hierarchical meta-analysis of plant trait data
 ##'
 ##' `pecan.ma` runs a hierarchical Bayesian meta-analytical model.
 ##' This model combines prior information with data from studies on the particular species or group of interest.

modules/meta.analysis/R/run.meta.analysis.R

@@ -166,7 +166,7 @@ run.meta.analysis.pft <- function(pft, iterations, random = TRUE, threshold = 1.
 ##--------------------------------------------------------------------------------------------------##
 ##' Run meta analysis
 ##'
-##' This will use the following items from setings:
+##' This will use the following items from settings:
 ##' - settings$pfts
 ##' - settings$database$bety
 ##' - settings$database$dbfiles

modules/meta.analysis/tests/testthat/test.jagify.R

@@ -0,0 +1,31 @@
+#-------------------------------------------------------------------------------
+# Copyright (c) 2012 University of Illinois, NCSA.
+# All rights reserved. This program and the accompanying materials
+# are made available under the terms of the 
+# University of Illinois/NCSA Open Source License
+# which accompanies this distribution, and is available at
+# http://opensource.ncsa.illinois.edu/license.html
+#-------------------------------------------------------------------------------
+
+test_that("jagify correctly assigns treatment index of 1 to all control treatments, regardless of alphabetical order", {
+  ## generate test data; controls assigned to early alphabet and late alphabet trt names
+  testresult <- data.frame(citation_id = 1,
+                           site_id = rep(1:2, each = 5),
+                           name = rep(letters[1:5],2),
+                           trt_id = as.character(rep(letters[1:5],2)),
+                           control = c(1, rep(0,8), 1), 
+                           greenhouse = c(rep(0,5), rep(1,5)),
+                           date = 1,
+                           time = NA,
+                           cultivar_id = 1,
+                           specie_id = 1,
+                           n = 2,
+                           mean = sqrt(1:10),
+                           stat = 1,
+                           statname = "SE",
+                           treatment_id = 1:10
+  )
+
+  jagged.data <- jagify(testresult)
+  expect_equal(jagged.data$trt_num[jagged.data$trt == "control"], c(1, 1))
+})

modules/meta.analysis/tests/testthat/test.run.meta.analysis.R

@@ -1,42 +1,33 @@
-#-------------------------------------------------------------------------------
-# Copyright (c) 2012 University of Illinois, NCSA.
-# All rights reserved. This program and the accompanying materials
-# are made available under the terms of the 
-# University of Illinois/NCSA Open Source License
-# which accompanies this distribution, and is available at
-# http://opensource.ncsa.illinois.edu/license.html
-#-------------------------------------------------------------------------------
-
-context("run.meta.analysis")
-
+test_that("`runModule.run.meta.analysis` throws an error for incorrect input", {
+  expect_error(runModule.run.meta.analysis('test'), "only works with Settings or MultiSettings")
+})
 
-test_that("singleMA gives expected result for example inputs",{
-  ## need to calculate x
-  ## x <- singleMA(....)
-  #expect_equal(round(summary(x)$statistics["beta.o", "Mean"]), 5)
+test_that("`run.meta.analysis` able to call run.meta.analysis.pft for each pft in the input list", {
+  mocked_res <- mockery::mock(1, cycle = TRUE)
+  mockery::stub(run.meta.analysis, 'run.meta.analysis.pft', mocked_res)
+  mockery::stub(run.meta.analysis, 'PEcAn.DB::db.open', 1)
+  mockery::stub(run.meta.analysis, 'PEcAn.DB::db.close', 1)
+  pfts <- list('ebifarm.salix', 'temperate.coniferous')
+  run.meta.analysis(pfts = pfts, iterations = 1, dbfiles = NULL, database = NULL)
+  mockery::expect_called(mocked_res, 2)
+  args <- mockery::mock_args(mocked_res)
+  expect_equal(args[[1]][[1]], "ebifarm.salix")
+  expect_equal(args[[2]][[1]], "temperate.coniferous")
 })
 
-test_that("jagify correctly assigns treatment index of 1 to all control treatments, regardless of alphabetical order", {
-  ## generate test data; controls assigned to early alphabet and late alphabet trt names
-  testresult <- data.frame(citation_id = 1,
-                           site_id = rep(1:2, each = 5),
-                           name = rep(letters[1:5],2),
-                           trt_id = as.character(rep(letters[1:5],2)),
-                           control = c(1, rep(0,8), 1), 
-                           greenhouse = c(rep(0,5), rep(1,5)),
-                           date = 1,
-                           time = NA,
-                           cultivar_id = 1,
-                           specie_id = 1,
-                           n = 2,
-                           mean = sqrt(1:10),
-                           stat = 1,
-                           statname = "SE",
-                           treatment_id = 1:10
+test_that("`run.meta.analysis.pft` throws an error if it cannot find output from get.trait", {
+  pft <- list(outdir = "", name = "ebifarm.salix")
+  expect_error(
+    run.meta.analysis.pft(pft = pft, iterations = 1, dbfiles = NULL, dbcon = NULL),
+    "Could not find output from get.trait"
   )
-  i <- sapply(testresult, is.factor)
-  testresult[i] <- lapply(testresult[i], as.character)
-
-  jagged.data <- jagify(testresult)
-  expect_equal(jagged.data$trt_num[jagged.data$trt == "control"], c(1, 1)) 
 })
+
+test_that("`run.meta.analysis.pft` throws an error for missing posteriorid", {
+  pft <- list(outdir = "test", name = "ebifarm.salix")
+  mockery::stub(run.meta.analysis.pft, 'file.exists', TRUE)
+  expect_error(
+    run.meta.analysis.pft(pft = pft, iterations = 1, dbfiles = NULL, dbcon = NULL, update = TRUE),
+    "Missing posteriorid"
+  )
+})