attempt包测试3_Adverbs_20200204Tuesday

1.设置当前工作目录

getwd()
setwd("./attempt/")

2.导入R包

library(attempt)

3.测试：Adverbs take a function and return a modified function.

3.1 silently()

#@ silently() transforms a function so that when you call this new function, it returns nothing unless there is an error or a warning (contrary to attempt that returns the result). In a sense, the new function stay silent unless error or warning.
silent_log <- silently(log)
silent_log(1)
silent_log(“a”)

Error in .f(…) : 数学函数中用了非数值参数

#@ With silently(), the result is never returned.
silent_matrix <- silently(matrix)
silent_matrix(1:3,2)

Warning message:

In .f(…) : 数据长度[3]不是矩阵行数[2]的整倍

3.2 surely()

#@ surely() transforms a function so that when you call this new function, it calls attempt() - i.e. in the code below, calling sure_log(1) is the same as calling attempt(log(1)). In a sense, you’re sure this new function will always work.
sure_log <- surely(log)
sure_log(1)

[1] 0

sure_log(“a”)

Error: 数学函数中用了非数值参数

3.3 with_message() and with_warning()

#@ These two functions take a function, and add a warning or a message to it.
as_num_msg <- with_message(as.numeric, msg = “We’re performing a numeric conversion”)
as_num_warn <- with_warning(as.numeric, msg = “We’re performing a numeric conversion”)
as_num_msg(“1”)

We’re performing a numeric conversion

[1] 1

as_num_warn(“1”)

[1] 1

Warning message:

In as_num_warn(“1”) : We’re performing a numeric conversion

3.4 without_message(), without_warning(), and discretly()

#@ These three functions do the opposite, as they remove warnings and messages:
matrix(1:3, ncol = 2)

[,1] [,2]

[1,] 1 3

[2,] 2 1

Warning message:

In matrix(1:3, ncol = 2) : 数据长度[3]不是矩阵行数[2]的整倍

no_warning_matrix <- without_warning(matrix)
no_warning_matrix(1:3, ncol = 2)

[,1] [,2]

[1,] 1 3

[2,] 2 1

4.结束

sessionInfo()

R version 3.6.2 (2019-12-12)

Platform: x86_64-w64-mingw32/x64 (64-bit)

Running under: Windows 10 x64 (build 18363)

Matrix products: default

locale:

[1] LC_COLLATE=Chinese (Simplified)_China.936

[2] LC_CTYPE=Chinese (Simplified)_China.936

[3] LC_MONETARY=Chinese (Simplified)_China.936

[4] LC_NUMERIC=C

[5] LC_TIME=Chinese (Simplified)_China.936

attached base packages:

[1] stats4 parallel stats graphics grDevices utils

[7] datasets methods base

other attached packages:

[1] attempt_0.3.0 Biostrings_2.54.0 XVector_0.26.0

[4] IRanges_2.20.2 S4Vectors_0.24.2 BiocGenerics_0.32.0

loaded via a namespace (and not attached):

[1] Seurat_3.1.2 TH.data_1.0-10

[3] Rtsne_0.15 colorspace_1.4-1

[5] seqinr_3.6-1 pryr_0.1.4

[7] ggridges_0.5.2 rstudioapi_0.10

[9] leiden_0.3.2 listenv_0.8.0

[11] npsurv_0.4-0 ggrepel_0.8.1

[13] alakazam_0.3.0 mvtnorm_1.0-12

[15] codetools_0.2-16 splines_3.6.2

[17] R.methodsS3_1.7.1 mnormt_1.5-5

[19] lsei_1.2-0 TFisher_0.2.0

[21] zeallot_0.1.0 ade4_1.7-13

[23] jsonlite_1.6 packrat_0.5.0

[25] ica_1.0-2 cluster_2.1.0

[27] png_0.1-7 R.oo_1.23.0

[29] uwot_0.1.5 sctransform_0.2.1

[31] readr_1.3.1 compiler_3.6.2

[33] httr_1.4.1 backports_1.1.5

[35] assertthat_0.2.1 Matrix_1.2-18

[37] lazyeval_0.2.2 htmltools_0.4.0

[39] prettyunits_1.1.0 tools_3.6.2

[41] rsvd_1.0.2 igraph_1.2.4.2

[43] gtable_0.3.0 glue_1.3.1

[45] RANN_2.6.1 reshape2_1.4.3

[47] dplyr_0.8.3 Rcpp_1.0.3

[49] Biobase_2.46.0 vctrs_0.2.1

[51] multtest_2.42.0 gdata_2.18.0

[53] ape_5.3 nlme_3.1-142

[55] gbRd_0.4-11 lmtest_0.9-37

[57] stringr_1.4.0 globals_0.12.5

[59] lifecycle_0.1.0 irlba_2.3.3

[61] gtools_3.8.1 future_1.16.0

[63] zlibbioc_1.32.0 MASS_7.3-51.4

[65] zoo_1.8-7 scales_1.1.0

[67] hms_0.5.3 sandwich_2.5-1

[69] RColorBrewer_1.1-2 reticulate_1.14

[71] pbapply_1.4-2 gridExtra_2.3

[73] ggplot2_3.2.1 stringi_1.4.3

[75] mutoss_0.1-12 plotrix_3.7-7

[77] caTools_1.17.1.4 bibtex_0.4.2.2

[79] Rdpack_0.11-1 SDMTools_1.1-221.2

[81] rlang_0.4.2 pkgconfig_2.0.3

[83] bitops_1.0-6 lattice_0.20-38

[85] ROCR_1.0-7 purrr_0.3.3

[87] htmlwidgets_1.5.1 cowplot_1.0.0

[89] tidyselect_0.2.5 RcppAnnoy_0.0.14

[91] plyr_1.8.5 magrittr_1.5

[93] R6_2.4.1 gplots_3.0.1.2

[95] multcomp_1.4-12 pillar_1.4.3

[97] sn_1.5-4 fitdistrplus_1.0-14

[99] survival_3.1-8 tibble_2.1.3

[101] future.apply_1.4.0 tsne_0.1-3

[103] crayon_1.3.4 KernSmooth_2.23-16

[105] plotly_4.9.1 progress_1.2.2

[107] grid_3.6.2 data.table_1.12.8

[109] metap_1.2 digest_0.6.23

[111] tidyr_1.0.0 numDeriv_2016.8-1.1

[113] R.utils_2.9.2 RcppParallel_4.4.4

[115] munsell_0.5.0 viridisLite_0.3.0

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