CRAN Package Check Results for Package linea

Last updated on 2022-08-15 08:49:59 CEST.

Flavor Version Tinstall Tcheck Ttotal Status Flags
r-devel-linux-x86_64-debian-clang 0.0.2 19.18 269.15 288.33 ERROR
r-devel-linux-x86_64-debian-gcc 0.0.2 13.08 209.88 222.96 OK
r-devel-linux-x86_64-fedora-clang 0.0.2 342.95 OK
r-devel-linux-x86_64-fedora-gcc 0.0.2 356.85 OK
r-devel-windows-x86_64 0.0.2 26.00 304.00 330.00 OK
r-patched-linux-x86_64 0.0.2 15.29 262.22 277.51 OK
r-release-linux-x86_64 0.0.2 10.81 262.97 273.78 OK
r-release-macos-arm64 0.0.2 97.00 OK
r-release-macos-x86_64 0.0.2 123.00 OK
r-release-windows-x86_64 0.0.2 33.00 310.00 343.00 OK
r-oldrel-macos-arm64 0.0.2 80.00 OK
r-oldrel-macos-x86_64 0.0.2 124.00 OK
r-oldrel-windows-ix86+x86_64 0.0.2 35.00 323.00 358.00 OK

Check Details

Version: 0.0.2
Check: examples
Result: ERROR
    Running examples in 'linea-Ex.R' failed
    The error most likely occurred in:
    
    > base::assign(".ptime", proc.time(), pos = "CheckExEnv")
    > ### Name: gt_f
    > ### Title: apply_normalisation
    > ### Aliases: gt_f
    >
    > ### ** Examples
    >
    > data = read_xcsv("https://raw.githubusercontent.com/paladinic/data/main/ecomm_data.csv") %>%
    + gt_f(kw = 'covid') %>%
    + gt_f(kw = 'bitcoin')
    Rows: 261 Columns: 8
    -- Column specification --------------------------------------------------------
    Delimiter: ","
    dbl (7): ecommerce, black.friday, christmas, covid, online_media, offline_m...
    date (1): date
    
    i Use `spec()` to retrieve the full column specification for this data.
    i Specify the column types or set `show_col_types = FALSE` to quiet this message.
    Error in interest_over_time(widget, comparison_item, tz) :
     Status code was not 200. Returned status code:429
    Calls: %>% ... as.Date -> pull -> gt_f -> gtrends -> interest_over_time
    Execution halted
Flavor: r-devel-linux-x86_64-debian-clang

Version: 0.0.2
Check: tests
Result: ERROR
     Running 'testthat.R' [150s/178s]
    Running the tests in 'tests/testthat.R' failed.
    Complete output:
     > # libs ####
     > library(testthat)
     > library(linea)
    
     Attaching package: 'linea'
    
     The following object is masked from 'package:stats':
    
     lag
    
     > library(dplyr)
    
     Attaching package: 'dplyr'
    
     The following object is masked from 'package:linea':
    
     lag
    
     The following object is masked from 'package:testthat':
    
     matches
    
     The following objects are masked from 'package:stats':
    
     filter, lag
    
     The following objects are masked from 'package:base':
    
     intersect, setdiff, setequal, union
    
     > library(tidyr)
    
     Attaching package: 'tidyr'
    
     The following object is masked from 'package:testthat':
    
     matches
    
     >
     > # test_check("linea")
     >
     > # set up ####
     > ### NOT POOLED ----
     >
     > # import data
     > data = read_xcsv(verbose = FALSE,
     + file = "https://raw.githubusercontent.com/paladinic/data/main/ecomm_data.csv") %>%
     + check_ts(verbose = FALSE,
     + allow_non_num = TRUE,
     + date_col = "date") %>%
     + get_seasonality(verbose = FALSE,
     + date_col_name = "date",
     + date_type = "weekly starting")
     Rows: 261 Columns: 8
     -- Column specification --------------------------------------------------------
     Delimiter: ","
     dbl (7): ecommerce, black.friday, christmas, covid, online_media, offline_m...
     date (1): date
    
     i Use `spec()` to retrieve the full column specification for this data.
     i Specify the column types or set `show_col_types = FALSE` to quiet this message.
     >
     >
     > # vars
     > dv = "ecommerce"
     > ivs = c("black.friday", "christmas", "covid")
     > id_var = "date"
     >
     > # model table
     > model_table = build_model_table(ivs)
     > model_table$dec[1] = '0.5'
     >
     > # category
     > category = tibble(
     + variable = c("christmas" , "christmas"),
     + category = c("a", "a"),
     + calc = c("", "")
     + )
     >
     > # run model
     > model = run_model(
     + verbose = FALSE,
     + data = data,
     + dv = dv,
     + model_table = model_table,
     + normalise_by_pool = FALSE
     + )
     >
     >
     >
     > ### POOLED ----
     >
     > # import data
     > pooled_data = read_xcsv(verbose = FALSE,
     + file = "https://raw.githubusercontent.com/paladinic/data/main/pooled%20data.csv") %>%
     + check_ts(verbose = FALSE,
     + allow_non_num = TRUE,
     + date_col = "Week") %>%
     + get_seasonality(verbose = FALSE,
     + date_col_name = "Week",
     + date_type = "weekly starting")
     Rows: 783 Columns: 6
     -- Column specification --------------------------------------------------------
     Delimiter: ","
     chr (1): country
     dbl (4): christmas, amazon, rakhi, diwali
     date (1): Week
    
     i Use `spec()` to retrieve the full column specification for this data.
     i Specify the column types or set `show_col_types = FALSE` to quiet this message.
     >
     > # meta data
     > pooled_meta_data = tibble(
     + variable = c("amazon", "rakhi", "country", "Week"),
     + meta = c("STA", "STA", "POOL", "ID")
     + )
     >
     > # vars
     > pooled_dv = "amazon"
     > pooled_ivs = c("rakhi", "christmas", "diwali")
     > pooled_id_var = "Week"
     >
     > # model table
     > pooled_model_table = build_model_table(c(pooled_ivs, "", ""))
     >
     > # category
     > pooled_category = tibble(
     + variable = c("rakhi" , "christmas"),
     + category = c("a", "a"),
     + calc = c("", "")
     + )
     >
     > # run model
     > pooled_model = run_model(
     + verbose = FALSE,
     + data = pooled_data,
     + dv = pooled_dv,
     + meta_data = pooled_meta_data,
     + model_table = pooled_model_table,
     + normalise_by_pool = TRUE
     + )
     >
     >
     >
     > # tests ####
     > ### read data ####
     >
     > test_that('read data',{
     +
     +
     + data = read_xcsv(verbose = FALSE,
     + file = "https://raw.githubusercontent.com/paladinic/data/main/ecomm_data.csv")%>%
     + is.data.frame() %>%
     + expect_equal(TRUE)
     +
     + })
     Test passed
     > test_that('read data - pooled',{
     +
     + pooled_data = read_xcsv(verbose = FALSE,
     + file = "https://raw.githubusercontent.com/paladinic/data/main/pooled%20data.csv")%>%
     + is.data.frame() %>%
     + expect_equal(TRUE)
     +
     + })
     Test passed
     > test_that('read data - pooled ts',{
     +
     + pooled_data = read_xcsv(verbose = FALSE,
     + file = "https://raw.githubusercontent.com/paladinic/data/main/pooled%20data.csv")%>%
     + check_ts(date_col = 'Week') %>%
     + is.data.frame() %>%
     + expect_equal(TRUE)
     +
     + })
     Test passed
     >
     >
     > ### seasonality ####
     >
     > test_that('seasonality',{
     +
     + pooled_data = read_xcsv(verbose = FALSE,
     + file = "https://raw.githubusercontent.com/paladinic/data/main/ecomm_data.csv")%>%
     + check_ts(date_col = 'date') %>%
     + get_seasonality(date_col_name = 'date',
     + date_type = 'weekly starting') %>%
     + is.data.frame() %>%
     + expect_equal(TRUE)
     +
     + })
     Test passed
     > test_that('seasonality - pooled',{
     +
     + pooled_data = read_xcsv(verbose = FALSE,
     + file = "https://raw.githubusercontent.com/paladinic/data/main/pooled%20data.csv")%>%
     + check_ts(date_col = 'Week') %>%
     + get_seasonality(date_col_name = 'Week',
     + pool_var = 'country',
     + date_type = 'weekly starting') %>%
     + is.data.frame() %>%
     + expect_equal(TRUE)
     +
     + })
     Test passed
     >
     >
     > ### run model ####
     >
     > test_that('run_model ivs, dv',{
     +
     + run_model(data = data, dv = dv, ivs = ivs) %>%
     + class() %>%
     + expect_equal('lm')
     +
     + })
     Test passed
     >
     > ### next steps ---------------------------------------------------------------
     >
     > test_that("what next - output dataframe", {
     + model %>%
     + what_next() %>%
     + is.data.frame() %>%
     + expect_equal(TRUE)
     + })
     Test passed
     > test_that("what next - output not all na", {
     + model %>%
     + what_next() %>%
     + select(-variable) %>%
     + is.na() %>%
     + all() %>%
     + expect_equal(FALSE)
     + })
     Test passed
     >
     > test_that("what next - output dataframe - diff FALSE - not pooled", {
     + model %>%
     + what_next(r2_diff = FALSE) %>%
     + is.data.frame() %>%
     + expect_equal(TRUE)
     + })
     Test passed
     > test_that("what next - output not all na - diff FALSE - not pooled", {
     + model %>%
     + what_next(r2_diff = FALSE) %>%
     + select(-variable) %>%
     + is.na() %>%
     + all() %>%
     + expect_equal(FALSE)
     + })
     Test passed
     >
     > test_that("what next - pooled - output dataframe", {
     + pooled_model %>%
     + what_next() %>%
     + is.data.frame() %>%
     + expect_equal(TRUE)
     + })
     Test passed
     > test_that("what next - pooled - output not all na", {
     + pooled_model %>%
     + what_next() %>%
     + select(-variable) %>%
     + is.na() %>%
     + all() %>%
     + expect_equal(FALSE)
     + })
     Test passed
     >
     > test_that("what trans - output dataframe", {
     + run_model(data = mtcars,dv = 'mpg',ivs = c('disp','cyl')) %>%
     + what_trans(variable = 'cyl',trans_df = data.frame(
     + name = c('diminish', 'decay', 'lag', 'ma', 'log', 'hill', 'sin', 'exp'),
     + ts = c(FALSE,TRUE,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE),
     + func = c('linea::diminish(x,a)',
     + 'linea::decay(x,a)',
     + 'linea::lag(x,a)',
     + 'linea::ma(x,a)',
     + 'log(x,a)',
     + "linea::hill_function(x,a,b,c)",
     + 'sin(x*a)',
     + '(x^a)'),order = 1:8) %>%
     + dplyr::mutate(val = '') %>%
     + dplyr::mutate(val = dplyr::if_else(condition = name == 'hill',
     + '(1,5,50),(1 ,5,50),(1,5,50)',
     + val))) %>%
     + is.data.frame() %>%
     + expect_equal(TRUE)
     + })
     Test passed
     > test_that("what trans - output not all na", {
     + run_model(data = mtcars,dv = 'mpg',ivs = c('disp','cyl')) %>%
     + what_trans(variable = 'cyl',trans_df = data.frame(
     + name = c('diminish', 'decay', 'lag', 'ma', 'log', 'hill', 'sin', 'exp'),
     + ts = c(FALSE,TRUE,TRUE,TRUE,FALSE,FALSE,FALSE,FALSE),
     + func = c('linea::diminish(x,a)',
     + 'linea::decay(x,a)',
     + 'linea::lag(x,a)',
     + 'linea::ma(x,a)',
     + 'log(x,a)',
     + "linea::hill_function(x,a,b,c)",
     + 'sin(x*a)',
     + '(x^a)'),order = 1:8) %>%
     + dplyr::mutate(val = '') %>%
     + dplyr::mutate(val = dplyr::if_else(condition = name == 'hill',
     + '(1,5,50),(1 ,5,50),(1,5,50)',
     + val))) %>%
     + is.na() %>%
     + all() %>%
     + expect_equal(FALSE)
     + })
     Test passed
     >
     > test_that("what combo - output dataframe", {
     + data = read_xcsv("https://raw.githubusercontent.com/paladinic/data/main/ecomm_data.csv")
     + dv = 'ecommerce'
     + ivs = c('christmas','black.friday')
     + combo_trans_df = data.frame(
     + name = c('diminish', 'decay', 'hill', 'exp'),
     + ts = c(FALSE,TRUE,FALSE,FALSE),
     + func = c(
     + 'linea::diminish(x,a)',
     + 'linea::decay(x,a)',
     + "linea::hill_function(x,a,b,c)",
     + '(x^a)'
     + ),
     + order = 1:4
     + ) %>%
     + dplyr::mutate(offline_media = dplyr::if_else(condition = name == 'hill',
     + '(1,5,50),(1,5,50),( 1,5,50)',
     + '')) %>%
     + dplyr::mutate(online_media = dplyr::if_else(condition = name == 'diminish',
     + '.1,.5, 10 ',
     + '')) %>%
     + dplyr::mutate(online_media = dplyr::if_else(condition = name == 'decay',
     + '.1,.7 ',
     + online_media)) %>%
     + dplyr::mutate(online_media = dplyr::if_else(condition = name == 'exp',
     + '.5,2,3',
     + online_media)) %>%
     + dplyr::mutate(promo = '') %>%
     + {what_combo(trans_df = .,dv = dv,data = data)} %>%
     + {.[['results']]} %>%
     + is.data.frame() %>%
     + expect_equal(TRUE)
     + })
     Test passed
     > test_that("what combo - output not all na", {
     + data = read_xcsv("https://raw.githubusercontent.com/paladinic/data/main/ecomm_data.csv")
     + dv = 'ecommerce'
     + ivs = c('christmas','black.friday')
     + combo_trans_df = data.frame(
     + name = c('diminish', 'decay', 'hill', 'exp'),
     + ts = c(FALSE,TRUE,FALSE,FALSE),
     + func = c(
     + 'linea::diminish(x,a)',
     + 'linea::decay(x,a)',
     + "linea::hill_function(x,a,b,c)",
     + '(x^a)'
     + ),
     + order = 1:4
     + ) %>%
     + dplyr::mutate(offline_media = dplyr::if_else(condition = name == 'hill',
     + '(1,5,50),(1,5,50),( 1,5,50)',
     + '')) %>%
     + dplyr::mutate(online_media = dplyr::if_else(condition = name == 'diminish',
     + '.1,.5, 10 ',
     + '')) %>%
     + dplyr::mutate(online_media = dplyr::if_else(condition = name == 'decay',
     + '.1,.7 ',
     + online_media)) %>%
     + dplyr::mutate(online_media = dplyr::if_else(condition = name == 'exp',
     + '.5,2,3',
     + online_media)) %>%
     + dplyr::mutate(promo = '') %>%
     + {what_combo(trans_df = .,dv = dv,data = data)} %>%
     + {.[['results']]} %>%
     + is.na() %>%
     + all() %>%
     + expect_equal(FALSE)
     + })
     Test passed
     >
     > ### get gt ------------------------------------------------------------------
     >
     > test_that("gtrends_f - pooled - output dataframe",{
     + gt_f(data = pooled_data,
     + kw = 'bitcoin',
     + date_col = pooled_id_var) %>%
     + is.data.frame() %>%
     + expect_equal(TRUE)
     + })
     -- Error (???): gtrends_f - pooled - output dataframe --------------------------
     Error in `interest_over_time(widget, comparison_item, tz)`: Status code was not 200. Returned status code:429
     Backtrace:
     1. ... %>% expect_equal(TRUE)
     6. linea::gt_f(data = pooled_data, kw = "bitcoin", date_col = pooled_id_var)
     7. gtrendsR::gtrends(keyword = kw, time = time_str, onlyInterest = TRUE)
     8. gtrendsR:::interest_over_time(widget, comparison_item, tz)
    
     Error in reporter$stop_if_needed() : Test failed
     Calls: test_that -> <Anonymous>
     Execution halted
Flavor: r-devel-linux-x86_64-debian-clang