26 new chunks@main #540

gogonzo · 2022-07-28T09:11:45Z

fixes:

See the quosure PR
insightsengineering/teal.code#49

App with fixed modules

pkgload::load_all("teal.code")
pkgload::load_all("teal.transform")
pkgload::load_all("teal")
pkgload::load_all("teal.modules.clinical")
library(scda)
library(dplyr)
library(scda)
library(nestcolor)

ADSL <- synthetic_cdisc_data("latest")$adsl
ADLB <- synthetic_cdisc_data("latest")$adlb
ADTTE <- synthetic_cdisc_data("latest")$adtte
ADRS <- synthetic_cdisc_data("latest")$adrs %>%
  mutate(AVALC = d_onco_rsp_label(AVALC)) %>%
  filter(PARAMCD != "OVRINV" | AVISIT == "FOLLOW UP")

add_event_flags <- function(dat) {
  dat <- dat %>%
    dplyr::mutate(
      TMPFL_SER = AESER == "Y",
      TMPFL_REL = AEREL == "Y",
      TMPFL_GR5 = AETOXGR == "5",
      TMP_SMQ01 = !is.na(SMQ01NAM),
      TMP_SMQ02 = !is.na(SMQ02NAM),
      TMP_CQ01 = !is.na(CQ01NAM)
    )
  column_labels <- list(
    TMPFL_SER = "Serious AE",
    TMPFL_REL = "Related AE",
    TMPFL_GR5 = "Grade 5 AE",
    TMP_SMQ01 = aesi_label(dat[["SMQ01NAM"]], dat[["SMQ01SC"]]),
    TMP_SMQ02 = aesi_label("Y.9.9.9.9/Z.9.9.9.9 AESI"),
    TMP_CQ01 = aesi_label(dat[["CQ01NAM"]])
  )
  formatters::var_labels(dat)[names(column_labels)] <- as.character(column_labels)
  dat
}
ADAE <- synthetic_cdisc_data("latest")$adae |> add_event_flags()
ADAE <- ADAE %>% dplyr::filter(!((AETOXGR == 1) & (AESEV == "MILD") & (ARM == "A: Drug X")))

ADQS <- synthetic_cdisc_data("latest")$adqs %>%
  dplyr::filter(ABLFL != "Y" & ABLFL2 != "Y") %>%
  dplyr::filter(AVISIT %in% c("WEEK 1 DAY 8", "WEEK 2 DAY 15", "WEEK 3 DAY 22")) %>%
  dplyr::mutate(
    AVISIT = as.factor(AVISIT),
    AVISITN = rank(AVISITN) %>%
      as.factor() %>%
      as.numeric() %>%
      as.factor() # making consecutive numeric factor
  )


ADAETTE <- synthetic_cdisc_data("latest")$adaette
ADAETTE <- ADAETTE %>%
  dplyr::filter(PARAMCD %in% c("AETTE1", "AETTE2", "AETTE3")) %>%
  dplyr::mutate(is_event = CNSR == 0) %>%
  dplyr::mutate(n_events = as.integer(is_event))

arm_ref_comp <- list(
  ARM = list(
    ref = value_choices("ADSL", "ARM", subset = function(data) {
      return(levels(data$ARM)[2])
    }),
    comp = value_choices("ADSL", "ARM", subset = function(data) {
      return(levels(data$ARM)[c(1, 3)])
    })
  ),
  ARMCD = list(
    ref = value_choices("ADSL", "ARMCD", subset = function(data) {
      return(levels(data$ARMCD)[2])
    }),
    comp = value_choices("ADSL", "ARMCD", subset = function(data) {
      return(levels(data$ARMCD)[c(1, 3)])
    })
  )
)

data <- cdisc_data(
    cdisc_dataset("ADSL", ADSL, code = "ADSL <- synthetic_cdisc_data('latest')$adsl"),
    cdisc_dataset("ADAE", ADAE,
      code = '
      add_event_flags <- function(dat) {
        dat <- dat %>%
          dplyr::mutate(
            TMPFL_SER = AESER == "Y",
            TMPFL_REL = AEREL == "Y",
            TMPFL_GR5 = AETOXGR == "5",
            TMP_SMQ01 = !is.na(SMQ01NAM),
            TMP_SMQ02 = !is.na(SMQ02NAM),
            TMP_CQ01 = !is.na(CQ01NAM)
          )
        column_labels <- list(
          TMPFL_SER = "Serious AE",
          TMPFL_REL = "Related AE",
          TMPFL_GR5 = "Grade 5 AE",
          TMP_SMQ01 = aesi_label(dat[["SMQ01NAM"]], dat[["SMQ01SC"]]),
          TMP_SMQ02 = aesi_label("Y.9.9.9.9/Z.9.9.9.9 AESI"),
          TMP_CQ01 = aesi_label(dat[["CQ01NAM"]])
        )
        formatters::var_labels(dat)[names(column_labels)] <- as.character(column_labels)
        dat
      }
      ADAE <- synthetic_cdisc_data("latest")$adae |> add_event_flags()
      ADAE <- ADAE %>% dplyr::filter(!((AETOXGR == 1) & (AESEV == "MILD") & (ARM == "A: Drug X")))
      '
    ),
    cdisc_dataset("ADLB", ADLB, code = 'ADLB <- synthetic_cdisc_data("latest")$adlb'),
    cdisc_dataset("ADRS", ADRS, code = 'ADRS <- synthetic_cdisc_data("latest")$adrs %>%
      mutate(AVALC = d_onco_rsp_label(AVALC)) %>%
      filter(PARAMCD != "OVRINV" | AVISIT == "FOLLOW UP")'),
    cdisc_dataset("ADTTE", ADTTE, code = 'ADTTE <- synthetic_cdisc_data("latest")$adtte'),
    cdisc_dataset("ADQS", ADQS, code = 'ADQS <- synthetic_cdisc_data("latest")$adqs %>%
      dplyr::filter(ABLFL != "Y" & ABLFL2 != "Y") %>%
      dplyr::filter(AVISIT %in% c("WEEK 1 DAY 8", "WEEK 2 DAY 15", "WEEK 3 DAY 22")) %>%
      dplyr::mutate(
        AVISIT = as.factor(AVISIT),
        AVISITN = rank(AVISITN) %>%
          as.factor() %>%
          as.numeric() %>%
          as.factor() # making consecutive numeric factor
      )'
    ),
    cdisc_dataset("ADAETTE", ADAETTE, code = '
      ADAETTE <- synthetic_cdisc_data("latest")$adaette
      ADAETTE <- ADAETTE %>%
        dplyr::filter(PARAMCD %in% c("AETTE1", "AETTE2", "AETTE3")) %>%
        dplyr::mutate(is_event = CNSR == 0) %>%
        dplyr::mutate(n_events = as.integer(is_event))
    '),
    check = TRUE
  )

app <- init(
  data = data,
  filter = list(ADSL = list(ARMCD = c("ARM A", "ARM B"))),
  modules = modules(
    tm_g_barchart_simple(
      label = "ADAE Analysis",
      x = data_extract_spec(
        dataname = "ADSL",
        select = select_spec(
          choices = variable_choices(
            ADSL,
            c(
              "ARM", "ACTARM", "SEX",
              "RACE", "ITTFL", "SAFFL", "STRATA2"
            )
          ),
          selected = "ACTARM",
          multiple = FALSE
        )
      ),
      fill = list(
        data_extract_spec(
          dataname = "ADSL",
          select = select_spec(
            choices = variable_choices(
              ADSL,
              c(
                "ARM", "ACTARM", "SEX",
                "RACE", "ITTFL", "SAFFL", "STRATA2"
              )
            ),
            selected = "SEX",
            multiple = FALSE
          )
        ),
        data_extract_spec(
          dataname = "ADAE",
          select = select_spec(
            choices = variable_choices(ADAE, c("SEX", "AETOXGR", "AESEV", "AESER")),
            selected = NULL,
            multiple = FALSE
          )
        )
      ),
      x_facet = list(
        data_extract_spec(
          dataname = "ADAE",
          select = select_spec(
            choices = variable_choices(ADAE, c("AETOXGR", "AESEV", "AESER")),
            selected = "AETOXGR",
            multiple = FALSE
          )
        ),
        data_extract_spec(
          dataname = "ADSL",
          select = select_spec(
            choices = variable_choices(
              ADSL,
              c(
                "ARM", "ACTARM", "SEX",
                "RACE", "ITTFL", "SAFFL", "STRATA2"
              )
            ),
            selected = NULL,
            multiple = FALSE
          )
        )
      ),
      y_facet = list(
        data_extract_spec(
          dataname = "ADAE",
          select = select_spec(
            choices = variable_choices(ADAE, c("AETOXGR", "AESEV", "AESER")),
            selected = "AESEV",
            multiple = FALSE
          )
        ),
        data_extract_spec(
          dataname = "ADSL",
          select = select_spec(
            choices = variable_choices(
              ADSL,
              c(
                "ARM", "ACTARM", "SEX",
                "RACE", "ITTFL", "SAFFL", "STRATA2"
              )
            ),
            selected = NULL,
            multiple = FALSE
          )
        )
      )
    ),
    tm_g_ci(
      label = "Confidence Interval Plot",
      x_var = data_extract_spec(
        dataname = "ADSL",
        select = select_spec(
          choices = c("ARMCD", "BMRKR2"),
          selected = c("ARMCD"),
          multiple = FALSE,
          fixed = FALSE
        )
      ),
      y_var = data_extract_spec(
        dataname = "ADLB",
        filter = list(
          filter_spec(
            vars = "PARAMCD",
            choices = levels(ADLB$PARAMCD),
            selected = levels(ADLB$PARAMCD)[1],
            multiple = FALSE,
            label = "Select lab:"
          ),
          filter_spec(
            vars = "AVISIT",
            choices = levels(ADLB$AVISIT),
            selected = levels(ADLB$AVISIT)[1],
            multiple = FALSE,
            label = "Select visit:"
          )
        ),
        select = select_spec(
          label = "Analyzed Value",
          choices = c("AVAL", "CHG"),
          selected = "AVAL",
          multiple = FALSE,
          fixed = FALSE
        )
      ),
      color = data_extract_spec(
        dataname = "ADSL",
        select = select_spec(
          label = "Color by variable",
          choices = c("SEX", "STRATA1", "STRATA2"),
          selected = c("STRATA1"),
          multiple = FALSE,
          fixed = FALSE
        )
      )
    ),
    tm_g_forest_rsp(
      label = "Forest Response",
      dataname = "ADRS",
      arm_var = choices_selected(
        variable_choices(ADSL, c("ARM", "ARMCD")),
        "ARMCD"
      ),
      arm_ref_comp = arm_ref_comp,
      paramcd = choices_selected(
        value_choices(ADRS, "PARAMCD", "PARAM"),
        "INVET"
      ),
      subgroup_var = choices_selected(
        variable_choices(ADSL, names(ADSL)),
        c("BMRKR2", "SEX")
      ),
      strata_var = choices_selected(
        variable_choices(ADSL, c("STRATA1", "STRATA2")),
        "STRATA2"
      ),
      plot_height = c(600L, 200L, 2000L),
      default_responses = list(
        BESRSPI = list(
          rsp = c("Stable Disease (SD)", "Not Evaluable (NE)"),
          levels = c(
            "Complete Response (CR)", "Partial Response (PR)", "Stable Disease (SD)",
            "Progressive Disease (PD)", "Not Evaluable (NE)"
          )
        ),
        INVET = list(
          rsp = c("Complete Response (CR)", "Partial Response (PR)"),
          levels = c(
            "Complete Response (CR)", "Not Evaluable (NE)", "Partial Response (PR)",
            "Progressive Disease (PD)", "Stable Disease (SD)"
          )
        ),
        OVRINV = list(
          rsp = c("Progressive Disease (PD)", "Stable Disease (SD)"),
          levels = c("Progressive Disease (PD)", "Stable Disease (SD)", "Not Evaluable (NE)")
        )
      )
    ),
    tm_g_forest_tte(
      label = "Forest Survival",
      dataname = "ADTTE",
      arm_var = choices_selected(
        variable_choices(ADSL, c("ARM", "ARMCD")),
        "ARMCD"
      ),
      arm_ref_comp = arm_ref_comp,
      paramcd = choices_selected(
        value_choices(ADTTE, "PARAMCD", "PARAM"),
        "OS"
      ),
      subgroup_var = choices_selected(
        variable_choices(ADSL, names(ADSL)),
        c("BMRKR2", "SEX")
      ),
      strata_var = choices_selected(
        variable_choices(ADSL, c("STRATA1", "STRATA2")),
        "STRATA2"
      ),
      plot_height = c(600, 200, 2000)
    ),
    tm_g_ipp(
      label = "Individual Patient Plot",
      dataname = "ADLB",
      arm_var = choices_selected(
        value_choices(ADLB, "ARMCD"),
        "ARM A"
      ),
      paramcd = choices_selected(
        value_choices(ADLB, "PARAMCD"),
        "ALT"
      ),
      aval_var = choices_selected(
        variable_choices(ADLB, c("AVAL", "CHG")),
        "AVAL"
      ),
      avalu_var = choices_selected(
        variable_choices(ADLB, c("AVALU")),
        "AVALU",
        fixed = TRUE
      ),
      id_var = choices_selected(
        variable_choices(ADLB, c("USUBJID")),
        "USUBJID",
        fixed = TRUE
      ),
      visit_var = choices_selected(
        variable_choices(ADLB, c("AVISIT")),
        "AVISIT"
      ),
      base_var = choices_selected(
        variable_choices(ADLB, c("BASE")),
        "BASE",
        fixed = TRUE
      ),
      add_baseline_hline = FALSE,
      separate_by_obs = FALSE
    ),
    tm_g_km(
      label = "KM PLOT",
      dataname = "ADTTE",
      arm_var = choices_selected(
        variable_choices(ADSL, c("ARM", "ARMCD", "ACTARMCD")),
        "ARM"
      ),
      paramcd = choices_selected(
        value_choices(ADTTE, "PARAMCD", "PARAM"),
        "OS"
      ),
      #arm_ref_comp = arm_ref_comp,
      strata_var = choices_selected(
        variable_choices(ADSL, c("SEX", "BMRKR2")),
        "SEX"
      ),
      facet_var = choices_selected(
        variable_choices(ADSL, c("SEX", "BMRKR2")),
        NULL
      )
    ),
    tm_a_mmrm(
      label = "MMRM",
      dataname = "ADQS",
      aval_var = choices_selected(c("AVAL", "CHG"), "AVAL"),
      id_var = choices_selected(c("USUBJID", "SUBJID"), "USUBJID"),
      arm_var = choices_selected(c("ARM", "ARMCD"), "ARM"),
      visit_var = choices_selected(c("AVISIT", "AVISITN"), "AVISIT"),
      arm_ref_comp = arm_ref_comp,
      paramcd = choices_selected(
        choices = value_choices(ADQS, "PARAMCD", "PARAM"),
        selected = "FKSI-FWB"
      ),
      cov_var = choices_selected(c("BASE", "AGE", "SEX", "BASE:AVISIT"), NULL)
    ),
    tm_g_lineplot(
      label = "Line Plot",
      dataname = "ADLB",
      strata = choices_selected(
        variable_choices(ADSL, c("ARM", "ARMCD", "ACTARMCD")),
        "ARM"
      ),
      y = choices_selected(
        variable_choices(ADLB, c("AVAL", "BASE", "CHG", "PCHG")),
        "AVAL"
      ),
      param = choices_selected(
        value_choices(ADLB, "PARAMCD", "PARAM"),
        "ALT"
      )
    ),
    tm_g_pp_adverse_events(
      label = "Adverse events",
      dataname = "ADAE",
      parentname = "ADSL",
      patient_col = "USUBJID",
      plot_height = c(600L, 200L, 2000L),
      aeterm = choices_selected(
        choices = variable_choices(ADAE, "AETERM"),
        selected = "AETERM"
      ),
      tox_grade = choices_selected(
        choices = variable_choices(ADAE, "AETOXGR"),
        selected = "AETOXGR"
      ),
      causality = choices_selected(
        choices = variable_choices(ADAE, "AEREL"),
        selected = "AEREL"
      ),
      outcome = choices_selected(
        choices = variable_choices(ADAE, "AEOUT"),
        selected = "AEOUT"
      ),
      action = choices_selected(
        choices = variable_choices(ADAE, "AEACN"),
        selected = "AEACN"
      ),
      time = choices_selected(
        choices = variable_choices(ADAE, "ASTDY"),
        selected = "ASTDY"
      ),
      decod = NULL
    ),
    tm_t_ancova(
       label = "ANCOVA table",
       dataname = "ADQS",
       avisit = choices_selected(
         choices = value_choices(ADQS, "AVISIT"),
         selected = "WEEK 1 DAY 8"
       ),
       arm_var = choices_selected(
         choices = variable_choices(ADSL, c("ARM", "ACTARMCD", "ARMCD")),
         selected = "ARMCD"
       ),
       arm_ref_comp = arm_ref_comp,
       aval_var = choices_selected(
         choices = variable_choices(ADQS, c("CHG", "AVAL")),
         selected = "CHG"
       ),
       cov_var = choices_selected(
         choices = variable_choices(ADQS, c("BASE", "STRATA1", "SEX")),
         selected = "STRATA1"
       ),
       paramcd = choices_selected(
         choices = value_choices(ADQS, "PARAMCD", "PARAM"),
         selected = "FKSI-FWB"
       )
    ),
    tm_t_events(
      label = "Adverse Event Table",
      dataname = "ADAE",
      arm_var = choices_selected(c("ARM", "ARMCD"), "ARM"),
      llt = choices_selected(
        choices = variable_choices(ADAE, c("AETERM", "AEDECOD")),
        selected = c("AEDECOD")
      ),
      hlt = choices_selected(
        choices = variable_choices(ADAE, c("AEBODSYS", "AESOC")),
        selected = "AEBODSYS"
      ),
      add_total = TRUE,
      event_type = "adverse event"
    ),
    tm_t_coxreg(
      label = "Cox Reg.",
      dataname = "ADTTE",
      arm_var = choices_selected(c("ARM", "ARMCD", "ACTARMCD"), "ARM"),
      arm_ref_comp = arm_ref_comp,
      paramcd = choices_selected(
        value_choices(ADTTE, "PARAMCD", "PARAM"), "OS"
      ),
      strata_var = choices_selected(
        c("COUNTRY", "STRATA1", "STRATA2"), "STRATA1"
      ),
      cov_var = choices_selected(
        c("AGE", "BMRKR1", "BMRKR2", "REGION1"), "AGE"
      ),
      multivariate = TRUE
    ),
    tm_t_events_by_grade(
      label = "Adverse Events by Grade Table",
      dataname = "ADAE",
      arm_var = choices_selected(c("ARM", "ARMCD"), "ARM"),
      llt = choices_selected(
        choices = variable_choices(ADAE, c("AETERM", "AEDECOD")),
        selected = c("AEDECOD")
      ),
      hlt = choices_selected(
        choices = variable_choices(ADAE, c("AEBODSYS", "AESOC")),
        selected = "AEBODSYS"
      ),
      grade = choices_selected(
        choices = variable_choices(ADAE, c("AETOXGR", "AESEV")),
        selected = "AETOXGR"
      )
    ),
    tm_t_events_patyear(
      label = "AE rate adjusted for patient-years at risk Table",
      dataname = "ADAETTE",
      arm_var = choices_selected(
        choices = variable_choices(ADSL, c("ARM", "ARMCD")),
        selected = "ARMCD"
      ),
      add_total = TRUE,
      events_var = choices_selected(
        choices = variable_choices(ADAETTE, "n_events"),
        selected = "n_events",
        fixed = TRUE
      ),
      paramcd = choices_selected(
        choices = value_choices(ADAETTE, "PARAMCD", "PARAM"),
        selected = "AETTE1"
      )
    ),
    tm_t_events_summary(
      label = "Adverse Events Summary",
      dataname = "ADAE",
      arm_var = choices_selected(
        choices = variable_choices("ADSL", c("ARM", "ARMCD")),
        selected = "ARM"
      ),
      flag_var_anl = choices_selected(
        choices = variable_choices("ADAE",  names(ADAE)[startsWith(names(ADAE), "TMPFL_")]),
        selected =  names(ADAE)[startsWith(names(ADAE), "TMPFL_")][1],
        keep_order = TRUE,
        fixed = FALSE
      ),
      flag_var_aesi = choices_selected(
        choices = variable_choices("ADAE", names(ADAE)[startsWith(names(ADAE), "TMP_")]),
        selected = names(ADAE)[startsWith(names(ADAE), "TMP_")][1],
        keep_order = TRUE,
        fixed = FALSE
      ),
      add_total = TRUE
    )
  )
)

runApp(app)

barchart simple g_ci

mhallal1 · 2022-08-03T13:46:16Z

tm_t_events and tm_t_ancova are done on this branch: 26_new_chunks_MH_modules@26_new_chunks@main

* quosure * merged_data to merge_inputs - two modules Co-authored-by: Mahmoud Hallal <mahmoud.hallal@roche.com>

Polkas · 2022-08-04T13:16:24Z

* apply quosures

Polkas · 2022-08-10T08:42:16Z

coverage of tmc modules in the teal.gallery (tmc related apps, the same result for all apps teal.gallery::list_apps())

tmc_gallery <- unique(unlist(lapply(c("efficacy", "safety", "patient-profile"), \(x)
                      stringr::str_extract_all(teal.gallery::get_app_code(x), "tm_[a-z_]*")[[1]])))
tmc_modules <- grep("tm_", ls(asNamespace("teal.modules.clinical")), value = TRUE)
length(tmc_modules)
# 35
setdiff(tmc_modules, tmc_gallery)
# Only 4 (out of 35) tmc modules are not in the teal.gallery
# c("tm_g_barchart_simple", "tm_g_ci", "tm_g_ipp", "tm_t_shift_by_arm_by_worst")

@gogonzo

Co-authored-by: Nikolas Burkoff <nikolas.burkoff@roche.com>

nikolas-burkoff · 2022-08-31T14:38:56Z

R/tm_t_abnormality.R

    # Update UI choices depending on selection of previous options
    shiny::observeEvent(input$grade, {
-      anl <- datasets$get_data(dataname, filtered = FALSE)
+      anl <- data[[dataname]]()


I assume having filtered data instead of unfiltered here is OK

unfiltered is ok but what's happening in this observer is funny. observeEvent can't return anything and also you can't pass the validate statement further - this means that observeEvent is completelly redundant here.

R/arm_ref_comp.R

R/utils.R

R/tm_t_events.R

R/tm_t_coxreg.R

R/tm_t_binary_outcome.R

R/tm_g_forest_rsp.R

R/tm_g_ci.R

R/tm_g_barchart_simple.R

mhallal1 · 2022-09-05T12:48:37Z

R/tm_g_barchart_simple.R

    )

-    data_chunk <- shiny::reactive({
+    merged_data_q <- shiny::reactive({


Selecting SEX in x variable renders a red error:

mhallal1

Except for the last comment, the previous comments have been addressed and the apps retested with filters --> LGTM.

gogonzo added 7 commits July 26, 2022 16:37

Merge branch 'main' into 26_new_chunks@main

7248b5b

Merge remote-tracking branch 'origin/main' into 26_new_chunks@main

e693646

//WIP

ab858c3

barchart simple g_ci

Merge remote-tracking branch 'origin/main' into 26_new_chunks@main

85a3a56

WIP

bd0283c

WIP

1ccec05

mmrm

e7b43af

gogonzo added the core label Jul 29, 2022

gogonzo added 3 commits July 29, 2022 15:31

Merge remote-tracking branch 'origin/main' into 26_new_chunks@main

065171c

WIP

caa5931

use default constructor for lists

9a91862

26 new chunks mh modules@26 new chunks@main (#544)

0c98360

* quosure * merged_data to merge_inputs - two modules Co-authored-by: Mahmoud Hallal <mahmoud.hallal@roche.com>

mhallal1 and others added 15 commits August 5, 2022 09:40

tm_t_binary_outcome

1c03a05

fixes

1d2566c

tm_t_events_by_grade

125b972

tm_t_events_patyear

bbcc7e1

tmc - quosure (#542)

51642cd

* apply quosures

tm_t_summary

c1b5a9e

styler

8aac3af

rm |>

5aaea07

fix cox

bb1d806

fixes

20d29e3

fixes

cdfe74d

simplify barchart

f1d2f70

tm_t_tte

1af8bdd

tm_t_mult_events

0a45970

tm_t_summary_by

881b520

gogonzo and others added 2 commits August 31, 2022 15:55

Update NEWS.md

091af9d

Co-authored-by: Nikolas Burkoff <nikolas.burkoff@roche.com>

remove chunks occurrences

590ca1d

nikolas-burkoff reviewed Aug 31, 2022

View reviewed changes

tidyup validations

3308144

nikolas-burkoff reviewed Aug 31, 2022

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nikolas-burkoff reviewed Aug 31, 2022

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R/utils.R Show resolved Hide resolved

gogonzo added 3 commits September 1, 2022 08:04

remove unneeded observeEvent

c402a33

fix tests

baf49ee

fix lintr

8c963d8