diff --git a/README.md b/README.md index 108aadd..933ffb2 100644 --- a/README.md +++ b/README.md @@ -35,7 +35,8 @@ analysis in *Gould et al.*, complete the following steps: 1. Clone or download [https://github.com/egouldo/this repository](https://github.com/egouldo/ManyEcoEvo) 2. Run `renv::restore()` to load the packages used in the analysis - pipeline locally on your machine + pipeline locally on your machine (see + \[`renv::`\]https://rstudio.github.io/renv/index.html) for details) 3. Run `tar_destroy()` to remove any record and caches of existing targets 4. Run `targets::tar_make()` in your console, depending on the power of diff --git a/README.qmd b/README.qmd index c5f8f32..3ce0024 100644 --- a/README.qmd +++ b/README.qmd @@ -28,7 +28,7 @@ Please see the documentation at for further Should you wish to completely reproduce the dataset generation and analysis in *Gould et al.*, complete the following steps: 1. Clone or download [https://github.com/egouldo/this repository](https://github.com/egouldo/ManyEcoEvo) -2. Run `renv::restore()` to load the packages used in the analysis pipeline locally on your machine +2. Run `renv::restore()` to load the packages used in the analysis pipeline locally on your machine (see [`renv::`]https://rstudio.github.io/renv/index.html) for details) 3. Run `tar_destroy()` to remove any record and caches of existing targets 4. Run `targets::tar_make()` in your console, depending on the power of your machine, the analysis pipeline will take between 2 and 7 minutes to execute (plus or minus some!) 5. You can view a table of all targets in the pipeline by running `targets::tar_meta()` diff --git a/_targets/meta/meta b/_targets/meta/meta index 96d5985..991a454 100644 --- a/_targets/meta/meta +++ b/_targets/meta/meta @@ -1,5 +1,5 @@ name|type|data|command|depend|seed|path|time|size|bytes|format|repository|iteration|parent|children|seconds|warnings|error -.Random.seed|object|9ac3ad6da98e87e3||||||||||||||| +.Random.seed|object|9da25ec69543bcf7||||||||||||||| %nin%|function|c5de772db35799a7||||||||||||||| all_prediction_data|stem|aec35f5492412af6|cbaa8d500a9e5c54|94954c171292e1d4|2002974195||t19657.1661443102s|42fd46be49aa72f2|29807|rds|local|vector|||0.077|| all_review_data|stem|bea072d4144ad4bd|1edea2a4f48e968c|7a9e99abccaab30d|-2056674812||t19657.165632188s|669f24177fb30fd6|11524|rds|local|vector|||0.014|| @@ -476,7 +476,7 @@ preprocess_prediction_files|function|4ef94f47adb9c94b||||||||||||||| preprocess_updated_prediction_files|function|37ee79927cd9b2cf||||||||||||||| probit_back|function|b41c22b6da45d1bb||||||||||||||| read_submission_data|function|34ce7495ff17edbe||||||||||||||| -README|stem|6164fd4520f8df17|8271ae22ce9ee020|7d54cfb4717e5766|-1347750081|README.md*README.qmd|t19657.2249986699s|223451b4fcde2b5f|6964|file|local|vector|||3.212|| +README|stem|c768fd19ed331e77|8271ae22ce9ee020|7d54cfb4717e5766|-1347750081|README.md*README.qmd|t19657.2349548687s|9f0e1de7984970fb|7112|file|local|vector|||3.637|| ReviewData|object|6a2cd8a7ea993fd0||||||||||||||| rm_inf_na|function|b202ba30a9e79c3a||||||||||||||| run_model_checks|function|0555122b635b261c|||||||||||||||