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topepotopepo
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Merge pull request #231 from patr1ckm/test-ref-ctrl
REF test_control to helper-objects
2 parents 4230ef8 + c6d686e commit 6a84962

23 files changed

+27
-98
lines changed

‎tests/testthat/helper-objects.R

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@@ -0,0 +1,3 @@
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ctrl <- control_parsnip(verbosity = 1, catch = FALSE)
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caught_ctrl <- control_parsnip(verbosity = 1, catch = TRUE)
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quiet_ctrl <- control_parsnip(verbosity = 0, catch = TRUE)

‎tests/testthat/test_boost_tree_C50.R

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@@ -6,6 +6,7 @@ library(dplyr)
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# ------------------------------------------------------------------------------
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context("boosted tree execution with C5.0")
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source("helper-objects.R")
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data("lending_club")
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lending_club <- head(lending_club, 200)
@@ -17,10 +18,6 @@ lc_basic <-
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boost_tree(mode = "classification") %>%
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set_engine("C5.0", bands = 2)
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ctrl <- control_parsnip(verbosity = 1, catch = FALSE)
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caught_ctrl <- control_parsnip(verbosity = 1, catch = TRUE)
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quiet_ctrl <- control_parsnip(verbosity = 0, catch = TRUE)
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# ------------------------------------------------------------------------------
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test_that('C5.0 execution', {

‎tests/testthat/test_boost_tree_spark.R

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@@ -5,10 +5,7 @@ library(dplyr)
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# ------------------------------------------------------------------------------
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context("boosted tree execution with spark")
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ctrl <- control_parsnip(verbosity = 1, catch = FALSE)
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caught_ctrl <- control_parsnip(verbosity = 1, catch = TRUE)
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quiet_ctrl <- control_parsnip(verbosity = 0, catch = TRUE)
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source("helper-objects.R")
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# ------------------------------------------------------------------------------
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‎tests/testthat/test_boost_tree_xgboost.R

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@@ -4,17 +4,14 @@ library(parsnip)
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# ------------------------------------------------------------------------------
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context("boosted tree execution with xgboost")
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source("helper-objects.R")
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num_pred <- names(iris)[1:4]
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iris_xgboost <-
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boost_tree(trees = 2, mode = "classification") %>%
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set_engine("xgboost")
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14-
ctrl <- control_parsnip(verbosity = 1, catch = FALSE)
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caught_ctrl <- control_parsnip(verbosity = 1, catch = TRUE)
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quiet_ctrl <- control_parsnip(verbosity = 0, catch = TRUE)
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# ------------------------------------------------------------------------------
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2017
test_that('xgboost execution, classification', {
@@ -101,10 +98,6 @@ bad_rf_reg <-
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boost_tree(mode = "regression") %>%
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set_engine("xgboost", sampsize = -10)
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ctrl <- list(verbosity = 1, catch = FALSE)
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caught_ctrl <- list(verbosity = 1, catch = TRUE)
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quiet_ctrl <- list(verbosity = 0, catch = TRUE)
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test_that('xgboost execution, regression', {
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skip_if_not_installed("xgboost")

‎tests/testthat/test_linear_reg.R

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@@ -7,6 +7,7 @@ library(tibble)
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context("linear regression")
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source("helpers.R")
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source("helper-objects.R")
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# ------------------------------------------------------------------------------
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@@ -209,10 +210,6 @@ num_pred <- c("Sepal.Width", "Petal.Width", "Petal.Length")
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iris_bad_form <- as.formula(Species ~ term)
210211
iris_basic <- linear_reg() %>% set_engine("lm")
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212-
ctrl <- control_parsnip(verbosity = 1, catch = FALSE)
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caught_ctrl <- control_parsnip(verbosity = 1, catch = TRUE)
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quiet_ctrl <- control_parsnip(verbosity = 0, catch = TRUE)
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# ------------------------------------------------------------------------------
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218215
test_that('lm execution', {

‎tests/testthat/test_linear_reg_glmnet.R

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@@ -6,6 +6,7 @@ library(tidyr)
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# ------------------------------------------------------------------------------
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context("linear regression execution with glmnet")
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source("helper-objects.R")
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num_pred <- c("Sepal.Width", "Petal.Width", "Petal.Length")
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iris_bad_form <- as.formula(Species ~ term)
@@ -14,10 +15,6 @@ iris_basic <- linear_reg(penalty = .1, mixture = .3) %>%
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no_lambda <- linear_reg(mixture = .3) %>%
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set_engine("glmnet")
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17-
ctrl <- control_parsnip(verbosity = 1, catch = FALSE)
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caught_ctrl <- control_parsnip(verbosity = 1, catch = TRUE)
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quiet_ctrl <- control_parsnip(verbosity = 0, catch = TRUE)
20-
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# ------------------------------------------------------------------------------
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test_that('glmnet execution', {

‎tests/testthat/test_linear_reg_keras.R

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@@ -7,6 +7,7 @@ library(tibble)
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context("keras linear regression")
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source("helpers.R")
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source("helper-objects.R")
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# ------------------------------------------------------------------------------
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‎tests/testthat/test_linear_reg_spark.R

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@@ -5,10 +5,7 @@ library(dplyr)
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# ------------------------------------------------------------------------------
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context("linear regression execution with spark")
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ctrl <- control_parsnip(verbosity = 1, catch = FALSE)
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caught_ctrl <- control_parsnip(verbosity = 1, catch = TRUE)
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quiet_ctrl <- control_parsnip(verbosity = 0, catch = TRUE)
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source("helper-objects.R")
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# ------------------------------------------------------------------------------
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‎tests/testthat/test_logistic_reg.R

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@@ -7,6 +7,7 @@ library(tibble)
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context("logistic regression")
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source("helpers.R")
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source("helper-objects.R")
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# ------------------------------------------------------------------------------
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@@ -219,9 +220,6 @@ lending_club <- head(lending_club, 200)
219220
lc_form <- as.formula(Class ~ log(funded_amnt) + int_rate)
220221
num_pred <- c("funded_amnt", "annual_inc", "num_il_tl")
221222
lc_basic <- logistic_reg() %>% set_engine("glm")
222-
ctrl <- control_parsnip(verbosity = 1, catch = FALSE)
223-
caught_ctrl <- control_parsnip(verbosity = 1, catch = TRUE)
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quiet_ctrl <- control_parsnip(verbosity = 0, catch = TRUE)
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test_that('glm execution', {
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‎tests/testthat/test_logistic_reg_glmnet.R

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@@ -7,6 +7,7 @@ library(tidyr)
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# ------------------------------------------------------------------------------
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context("logistic regression execution with glmnet")
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source("helper-objects.R")
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data("lending_club")
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lending_club <- head(lending_club, 200)
@@ -15,10 +16,6 @@ num_pred <- c("funded_amnt", "annual_inc", "num_il_tl")
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lc_bad_form <- as.formula(funded_amnt ~ term)
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lc_basic <- logistic_reg() %>% set_engine("glmnet")
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18-
ctrl <- control_parsnip(verbosity = 1, catch = FALSE)
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caught_ctrl <- control_parsnip(verbosity = 1, catch = TRUE)
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quiet_ctrl <- control_parsnip(verbosity = 0, catch = TRUE)
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# ------------------------------------------------------------------------------
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test_that('glmnet execution', {

‎tests/testthat/test_logistic_reg_spark.R

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@@ -5,10 +5,7 @@ library(dplyr)
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# ------------------------------------------------------------------------------
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context("logistic regression execution with spark")
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ctrl <- control_parsnip(verbosity = 1, catch = FALSE)
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caught_ctrl <- control_parsnip(verbosity = 1, catch = TRUE)
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quiet_ctrl <- control_parsnip(verbosity = 0, catch = TRUE)
8+
source("helper-objects.R")
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# ------------------------------------------------------------------------------
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‎tests/testthat/test_logistic_reg_stan.R

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@@ -6,6 +6,7 @@ library(tibble)
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# ------------------------------------------------------------------------------
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context("execution tests for stan logistic regression")
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source("helper-objects.R")
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data("lending_club")
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lending_club <- head(lending_club, 200)

‎tests/testthat/test_mars.R

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@@ -6,6 +6,7 @@ library(rlang)
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context("mars tests")
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source("helpers.R")
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source("helper-objects.R")
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# ------------------------------------------------------------------------------
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@@ -124,10 +125,6 @@ num_pred <- c("Sepal.Width", "Petal.Width", "Petal.Length")
124125
iris_bad_form <- as.formula(Species ~ term)
125126
iris_basic <- mars(mode = "regression") %>% set_engine("earth")
126127

127-
ctrl <- control_parsnip(verbosity = 1, catch = FALSE)
128-
caught_ctrl <- control_parsnip(verbosity = 1, catch = TRUE)
129-
quiet_ctrl <- control_parsnip(verbosity = 0, catch = TRUE)
130-
131128
# ------------------------------------------------------------------------------
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133130
test_that('mars execution', {

‎tests/testthat/test_mlp_keras.R

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@@ -5,17 +5,14 @@ library(tibble)
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# ------------------------------------------------------------------------------
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context("simple neural network execution with keras")
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source("helper-objects.R")
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num_pred <- names(iris)[1:4]
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iris_keras <-
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mlp(mode = "classification", hidden_units = 2, epochs = 10) %>%
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set_engine("keras", verbose = 0)
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ctrl <- control_parsnip(verbosity = 1, catch = FALSE)
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caught_ctrl <- control_parsnip(verbosity = 1, catch = TRUE)
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quiet_ctrl <- control_parsnip(verbosity = 0, catch = TRUE)
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nn_dat <- read.csv("nnet_test.txt")
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# ------------------------------------------------------------------------------
@@ -143,10 +140,6 @@ bad_keras_reg <-
143140
mlp(mode = "regression") %>%
144141
set_engine("keras", min.node.size = -10)
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ctrl <- list(verbosity = 1, catch = FALSE)
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caught_ctrl <- list(verbosity = 1, catch = TRUE)
148-
quiet_ctrl <- list(verbosity = 0, catch = TRUE)
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# ------------------------------------------------------------------------------
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‎tests/testthat/test_mlp_nnet.R

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@@ -4,17 +4,14 @@ library(parsnip)
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# ------------------------------------------------------------------------------
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context("simple neural network execution with nnet")
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source("helper-objects.R")
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num_pred <- names(iris)[1:4]
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iris_nnet <-
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mlp(mode = "classification", hidden_units = 5) %>%
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set_engine("nnet")
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14-
ctrl <- control_parsnip(verbosity = 1, catch = FALSE)
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caught_ctrl <- control_parsnip(verbosity = 1, catch = TRUE)
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quiet_ctrl <- control_parsnip(verbosity = 0, catch = TRUE)
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1815
# ------------------------------------------------------------------------------
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2017
test_that('nnet execution, classification', {
@@ -94,10 +91,6 @@ bad_rf_reg <-
9491
mlp(mode = "regression") %>%
9592
set_engine("nnet", sampsize = -10)
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97-
ctrl <- list(verbosity = 1, catch = FALSE)
98-
caught_ctrl <- list(verbosity = 1, catch = TRUE)
99-
quiet_ctrl <- list(verbosity = 0, catch = TRUE)
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# ------------------------------------------------------------------------------
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‎tests/testthat/test_multinom_reg_glmnet.R

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@@ -6,10 +6,7 @@ library(tibble)
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# ------------------------------------------------------------------------------
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context("multinom regression execution with glmnet")
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ctrl <- control_parsnip(verbosity = 1, catch = FALSE)
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caught_ctrl <- control_parsnip(verbosity = 1, catch = TRUE)
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quiet_ctrl <- control_parsnip(verbosity = 0, catch = TRUE)
9+
source("helper-objects.R")
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1411
rows <- c(1, 51, 101)
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‎tests/testthat/test_multinom_reg_spark.R

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@@ -5,10 +5,7 @@ library(dplyr)
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# ------------------------------------------------------------------------------
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context("multinomial regression execution with spark")
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ctrl <- control_parsnip(verbosity = 1, catch = FALSE)
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caught_ctrl <- control_parsnip(verbosity = 1, catch = TRUE)
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quiet_ctrl <- control_parsnip(verbosity = 0, catch = TRUE)
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source("helper-objects.R")
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# ------------------------------------------------------------------------------
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‎tests/testthat/test_nearest_neighbor_kknn.R

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@@ -5,6 +5,7 @@ library(rlang)
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# ------------------------------------------------------------------------------
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context("nearest neighbor execution with kknn")
8+
source("helper-objects.R")
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num_pred <- c("Sepal.Width", "Petal.Width", "Petal.Length")
1011
iris_bad_form <- as.formula(Species ~ term)
@@ -13,10 +14,6 @@ iris_basic <- nearest_neighbor(mode = "classification",
1314
weight_func = "triangular") %>%
1415
set_engine("kknn")
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16-
ctrl <- control_parsnip(verbosity = 1, catch = FALSE)
17-
caught_ctrl <- control_parsnip(verbosity = 1, catch = TRUE)
18-
quiet_ctrl <- control_parsnip(verbosity = 0, catch = TRUE)
19-
2017
# ------------------------------------------------------------------------------
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2219
test_that('kknn execution', {

‎tests/testthat/test_rand_forest_randomForest.R

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# ------------------------------------------------------------------------------
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context("random forest execution with randomForest")
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source("helper-objects.R")
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# ------------------------------------------------------------------------------
1011

@@ -17,10 +18,6 @@ lc_basic <- rand_forest(mode = "classification") %>%
1718
bad_rf_cls <- rand_forest(mode = "classification") %>%
1819
set_engine("randomForest", sampsize = -10)
1920

20-
ctrl <- control_parsnip(verbosity = 1, catch = FALSE)
21-
caught_ctrl <- control_parsnip(verbosity = 1, catch = TRUE)
22-
quiet_ctrl <- control_parsnip(verbosity = 0, catch = TRUE)
23-
2421
# ------------------------------------------------------------------------------
2522

2623
test_that('randomForest classification execution', {
@@ -156,10 +153,6 @@ bad_ranger_reg <- rand_forest(mode = "regression") %>%
156153
bad_rf_reg <- rand_forest(mode = "regression") %>%
157154
set_engine("randomForest", sampsize = -10)
158155

159-
ctrl <- list(verbosity = 1, catch = FALSE)
160-
caught_ctrl <- list(verbosity = 1, catch = TRUE)
161-
quiet_ctrl <- list(verbosity = 0, catch = TRUE)
162-
163156
# ------------------------------------------------------------------------------
164157

165158
test_that('randomForest regression execution', {

‎tests/testthat/test_rand_forest_ranger.R

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# ------------------------------------------------------------------------------
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context("random forest execution with ranger")
9+
source("helper-objects.R")
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1011
# ------------------------------------------------------------------------------
1112

@@ -19,10 +20,6 @@ lc_ranger <- rand_forest(mode = "classification") %>% set_engine("ranger", seed
1920
bad_ranger_cls <- rand_forest(mode = "classification") %>% set_engine("ranger", replace = "bad")
2021
bad_rf_cls <- rand_forest(mode = "classification") %>% set_engine("ranger", sampsize = -10)
2122

22-
ctrl <- control_parsnip(verbosity = 1, catch = FALSE)
23-
caught_ctrl <- control_parsnip(verbosity = 1, catch = TRUE)
24-
quiet_ctrl <- control_parsnip(verbosity = 0, catch = TRUE)
25-
2623
# ------------------------------------------------------------------------------
2724

2825
test_that('ranger classification execution', {
@@ -178,10 +175,6 @@ car_basic <- rand_forest(mode = "regression") %>% set_engine("ranger")
178175
bad_ranger_reg <- rand_forest(mode = "regression") %>% set_engine("ranger", replace = "bad")
179176
bad_rf_reg <- rand_forest(mode = "regression") %>% set_engine("ranger", sampsize = -10)
180177

181-
ctrl <- list(verbosity = 1, catch = FALSE)
182-
caught_ctrl <- list(verbosity = 1, catch = TRUE)
183-
quiet_ctrl <- list(verbosity = 0, catch = TRUE)
184-
185178
# ------------------------------------------------------------------------------
186179

187180
test_that('ranger regression execution', {

‎tests/testthat/test_rand_forest_spark.R

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@@ -5,10 +5,7 @@ library(dplyr)
55
# ------------------------------------------------------------------------------
66

77
context("random forest execution with spark")
8-
9-
ctrl <- control_parsnip(verbosity = 1, catch = FALSE)
10-
caught_ctrl <- control_parsnip(verbosity = 1, catch = TRUE)
11-
quiet_ctrl <- control_parsnip(verbosity = 0, catch = TRUE)
8+
source("helper-objects.R")
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# ------------------------------------------------------------------------------
1411

‎tests/testthat/test_surv_reg_flexsurv.R

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@@ -6,13 +6,12 @@ library(tibble)
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77
# ------------------------------------------------------------------------------
88

9+
source("helper-objects.R")
10+
911
basic_form <- Surv(time, status) ~ age
1012
complete_form <- Surv(time) ~ age
1113

1214
surv_basic <- surv_reg() %>% set_engine("flexsurv")
13-
ctrl <- control_parsnip(verbosity = 1, catch = FALSE)
14-
caught_ctrl <- control_parsnip(verbosity = 1, catch = TRUE)
15-
quiet_ctrl <- control_parsnip(verbosity = 0, catch = TRUE)
1615

1716
# ------------------------------------------------------------------------------
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