Split call_block into a function block_params

[muschellij2]

call_block does all the extraction of the parameters necessary, but executes the block. Regarding our email of getting a data.frame of parameters/hash/etc, I think that is what we'd need. I split call_block into a block_params function that extracts the parameters, and then call block_params in call_block.

[muschellij2]

# remotes::install_github('muschellij2/knitr')
library(knitr)

knit_df = function(file) {
  x = xfun::read_utf8(file)
  on.exit(knitr::knit_code$restore(), add = TRUE)
  res = knitr:::split_file(x, patterns = knitr::all_patterns$md)
  classes = sapply(res, attr, "class")
  blocks = res[classes %in% "block"]
  params = lapply(blocks, function(el) {
    if (attr(el, "class") %in% "block") {
      knitr:::block_params(el, verbose = FALSE)
    } else {
      NULL
    }
  })
  df = lapply(params, function(x) {
    if (!is.null(x)) {
      keep_names = c("eval", "echo", "engine", 
                     "label", "code", "hash", "cache",
                     "cache.path", "cache.vars", 
                     "cache.lazy", "fig.path", "fig.ext",
                     "fig.env", "error", "warning", "message",
                     "include", "params.src")
      x$code = paste(x$code, collapse = "\n")
      x = lapply(keep_names, function(r) {
        xx = x[[r]]
        if (is.null(xx)) {
          xx = NA
        }
        xx
      })
      names(x) = keep_names
      as.data.frame(x[keep_names])
    } else {
      NULL
    }
  })
  df = do.call("rbind", df)
  return(df)
}
tfile = tempfile(fileext = ".Rmd")
curl::curl_download(
  "https://raw.githubusercontent.com/muschellij2/neuroc/master/brain_extraction/index.Rmd",
  destfile = tfile)

res = knit_df(tfile)
head(res, 10)
#>     eval echo engine           label
#> 1   TRUE TRUE      R           setup
#> 2  FALSE TRUE      R unnamed-chunk-1
#> 3   TRUE TRUE      R            data
#> 4   TRUE TRUE      R         t1_plot
#> 5   TRUE TRUE      R     t1_naive_ss
#> 6   TRUE TRUE      R   t1_naive_plot
#> 7   TRUE TRUE      R           t1_ss
#> 8   TRUE TRUE      R      t1_ss_plot
#> 9   TRUE TRUE      R     t1_ss_plot2
#> 10  TRUE TRUE      R       t1_ss_red
#>                                                                                                                                                                                                                                                                                                                                                                              code
#> 1  library(kirby21.fmri)\nlibrary(kirby21.base)\nlibrary(dplyr)\nlibrary(fslr)\nlibrary(neurobase)\nlibrary(ANTsR)\nlibrary(R.utils)\nlibrary(RColorBrewer)\nlibrary(matrixStats)\nlibrary(ggplot2)\nlibrary(reshape2)\nlibrary(animation)\nlibrary(zoo)\nknitr::opts_chunk$set(echo = TRUE, cache = TRUE, comment = "",\n                      cache.path = "index_cache/html/")
#> 2                                                                                                      source("https://neuroconductor.org/neurocLite.R")\npackages = installed.packages()\npackages = packages[, "Package"]\nif (!"kirby21.base" %in% packages) {\n  neuroc_install("kirby21.base")  \n}\nif (!"kirby21.t1" %in% packages) {\n  neuroc_install("kirby21.t1")  \n}
#> 3                                                                                                                                             library(kirby21.t1)\nlibrary(kirby21.base)\nfnames = get_image_filenames_df(ids = 113, \n                    modalities = c("T1"), \n                    visits = c(1),\n                    long = FALSE)\nt1_fname = fnames$T1[1]
#> 4                                                                                                                                                                                                                                                                                                                             t1 = readnii(t1_fname)\northo2(t1)\nrm(list = "t1")
#> 5                                                                                                                                      library(fslr)\noutfile = nii.stub(t1_fname, bn = TRUE)\noutfile = paste0(outfile, "_SS_Naive.nii.gz")\nif (!file.exists(outfile)) {\n  ss_naive = fslbet(infile = t1_fname, outfile = outfile)\n} else {\n  ss_naive = readnii(outfile)\n}
#> 6                                                                                                                                                                                                                                                                                                                                                                ortho2(ss_naive)
#> 7                                                                                                                   outfile = nii.stub(t1_fname, bn = TRUE)\noutfile = paste0(outfile, "_SS.nii.gz")\nif (!file.exists(outfile)) {\n  ss = extrantsr::fslbet_robust(t1_fname, \n    remover = "double_remove_neck",\n    outfile = outfile)\n} else {\n  ss = readnii(outfile)\n}
#> 8                                                                                                                                                                                                                                                                                                                                                                      ortho2(ss)
#> 9                                                                                                                                                                                                       alpha = function(col, alpha = 1) {\n  cols = t(col2rgb(col, alpha = FALSE)/255)\n  rgb(cols, alpha = alpha)\n}      \northo2(t1_fname, ss > 0, col.y = alpha("red", 0.5))
#> 10                                                                                                                                                                                                                                                                                                                          ss_red = dropEmptyImageDimensions(ss)\northo2(ss_red)
#>                                                                                  hash
#> 1                                                                                <NA>
#> 2                                                                                <NA>
#> 3                                                                                <NA>
#> 4        reprex_reprex_cache/markdown_strict/t1_plot_1237e2a884712bffa363745c73aaa7f5
#> 5                                                                                <NA>
#> 6  reprex_reprex_cache/markdown_strict/t1_naive_plot_2bcd17d374dad557a2c9b5a588b7f9ad
#> 7                                                                                <NA>
#> 8     reprex_reprex_cache/markdown_strict/t1_ss_plot_cb7fa3ba47fae618f174f2bf40e2e415
#> 9    reprex_reprex_cache/markdown_strict/t1_ss_plot2_c6fa4be8d26d1758967f5541180b9e81
#> 10                                                                               <NA>
#>    cache                           cache.path cache.vars cache.lazy
#> 1      0 reprex_reprex_cache/markdown_strict/         NA       TRUE
#> 2      0 reprex_reprex_cache/markdown_strict/         NA       TRUE
#> 3      0 reprex_reprex_cache/markdown_strict/         NA       TRUE
#> 4      3 reprex_reprex_cache/markdown_strict/         NA       TRUE
#> 5      0 reprex_reprex_cache/markdown_strict/         NA       TRUE
#> 6      3 reprex_reprex_cache/markdown_strict/         NA       TRUE
#> 7      0 reprex_reprex_cache/markdown_strict/         NA       TRUE
#> 8      3 reprex_reprex_cache/markdown_strict/         NA       TRUE
#> 9      3 reprex_reprex_cache/markdown_strict/         NA       TRUE
#> 10     0 reprex_reprex_cache/markdown_strict/         NA       TRUE
#>                                       fig.path fig.ext fig.env error warning
#> 1  reprex_reprex_files/figure-markdown_strict/      NA  figure  TRUE    TRUE
#> 2  reprex_reprex_files/figure-markdown_strict/      NA  figure  TRUE    TRUE
#> 3  reprex_reprex_files/figure-markdown_strict/      NA  figure  TRUE    TRUE
#> 4  reprex_reprex_files/figure-markdown_strict/      NA  figure  TRUE    TRUE
#> 5  reprex_reprex_files/figure-markdown_strict/      NA  figure  TRUE    TRUE
#> 6  reprex_reprex_files/figure-markdown_strict/      NA  figure  TRUE    TRUE
#> 7  reprex_reprex_files/figure-markdown_strict/      NA  figure  TRUE    TRUE
#> 8  reprex_reprex_files/figure-markdown_strict/      NA  figure  TRUE    TRUE
#> 9  reprex_reprex_files/figure-markdown_strict/      NA  figure  TRUE    TRUE
#> 10 reprex_reprex_files/figure-markdown_strict/      NA  figure  TRUE    TRUE
#>    message include                  params.src
#> 1     TRUE   FALSE        setup, include=FALSE
#> 2     TRUE    TRUE                eval = FALSE
#> 3     TRUE    TRUE                        data
#> 4     TRUE    TRUE       t1_plot, cache = TRUE
#> 5     TRUE    TRUE  t1_naive_ss, cache = FALSE
#> 6     TRUE    TRUE t1_naive_plot, cache = TRUE
#> 7     TRUE    TRUE        t1_ss, cache = FALSE
#> 8     TRUE    TRUE    t1_ss_plot, cache = TRUE
#> 9     TRUE    TRUE   t1_ss_plot2, cache = TRUE
#> 10    TRUE    TRUE    t1_ss_red, cache = FALSE

^{Created on 2020-06-28 by the reprex package (v0.3.0)}

[yihui]

And R CMD check failed on Travis. Please also make sure the PR passes the checks (or state it if the failure is irrelevant to your PR).

[muschellij2]

I think those changes were from a merge upstream, but I will delete. Best, John

On Thu, Jul 23, 2020 at 4:13 PM Yihui Xie [email protected] wrote:

And R CMD check failed on Travis. Please also make sure the PR passes the checks (or state it if the failure is irrelevant to your PR).

— You are receiving this because you authored the thread. Reply to this email directly, view it on GitHub https://github.com/yihui/knitr/pull/1870#issuecomment-663209415, or unsubscribe https://github.com/notifications/unsubscribe-auth/AAIGPLTSIQJM5KONJBJD5CLR5CKWPANCNFSM4OJOFBCA .

[muschellij2]

I don't know what this failure really is - it seems as though it's in the examples, but I'm unsure if that's anything of my code.

[yihui]

Examples 087 and 112 failed: https://travis-ci.com/github/yihui/knitr/jobs/369838241#L3167-L3168

You may try reproduce locally and fix the errors: https://github.com/yihui/knitr-examples

[CLAassistant]

All committers have signed the CLA.

[muschellij2]

Seems odd - why would that not be triggered on rhub: https://builder.r-hub.io/status/knitr_1.30.1.tar.gz-f7627f31e985472f80ab5dff570ac11d

[muschellij2]

I don't have time this week to review, but maybe next

[yihui]

That's okay. I plan to make a CRAN release in the next few days. If this PR won't catch the next release, I can place it in a future release. Thanks!