Last updated: 2019-03-19
workflowr checks: (Click a bullet for more information) ✔ R Markdown file: up-to-date
Great! Since the R Markdown file has been committed to the Git repository, you know the exact version of the code that produced these results.
✔ Environment: empty
Great job! The global environment was empty. Objects defined in the global environment can affect the analysis in your R Markdown file in unknown ways. For reproduciblity it’s best to always run the code in an empty environment.
✔ Seed:
set.seed(666)
The command set.seed(666)
was run prior to running the code in the R Markdown file. Setting a seed ensures that any results that rely on randomness, e.g. subsampling or permutations, are reproducible.
✔ Session information: recorded
Great job! Recording the operating system, R version, and package versions is critical for reproducibility.
✔ Repository version: 970b22c
wflow_publish
or wflow_git_commit
). workflowr only checks the R Markdown file, but you know if there are other scripts or data files that it depends on. Below is the status of the Git repository when the results were generated:
Ignored files:
Ignored: .Rhistory
Ignored: .Rproj.user/
Ignored: data/sst_ALL_clim_only.Rdata
Ignored: data/sst_ALL_event_aov_tukey.Rdata
Ignored: data/sst_ALL_flat.Rdata
Ignored: data/sst_ALL_miss.Rdata
Ignored: data/sst_ALL_miss_cat_chi.Rdata
Ignored: data/sst_ALL_miss_clim_event_cat.Rdata
Ignored: data/sst_ALL_miss_clim_only.Rdata
Ignored: data/sst_ALL_miss_event_aov_tukey.Rdata
Ignored: data/sst_ALL_repl.Rdata
Ignored: data/sst_ALL_smooth.Rdata
Ignored: data/sst_ALL_smooth_aov_tukey.Rdata
Ignored: data/sst_ALL_smooth_event.Rdata
Ignored: data/sst_ALL_trend.Rdata
Ignored: data/sst_ALL_trend_clim_event_cat.Rdata
Untracked files:
Untracked: analysis/bibliography.bib
Untracked: code/functions.R
Untracked: code/workflow.R
Untracked: data/.gitignore
Untracked: data/clim_py.csv
Untracked: data/clim_py_joinAG_1.csv
Untracked: data/clim_py_joinAG_5.csv
Untracked: data/clim_py_joinAG_no.csv
Untracked: data/clim_py_minD_3.csv
Untracked: data/clim_py_minD_7.csv
Untracked: data/clim_py_pctile_80.csv
Untracked: data/clim_py_pctile_95.csv
Untracked: data/clim_py_pctile_99.csv
Untracked: data/clim_py_random.csv
Untracked: data/clim_py_spw_11.csv
Untracked: data/clim_py_spw_51.csv
Untracked: data/clim_py_spw_no.csv
Untracked: data/clim_py_whw_3.csv
Untracked: data/clim_py_whw_7.csv
Untracked: data/mhwBlock.csv
Untracked: data/mhws_py.csv
Untracked: data/mhws_py_joinAG_1.csv
Untracked: data/mhws_py_joinAG_5.csv
Untracked: data/mhws_py_joinAG_no.csv
Untracked: data/mhws_py_minD_3.csv
Untracked: data/mhws_py_minD_7.csv
Untracked: data/mhws_py_pctile_80.csv
Untracked: data/mhws_py_pctile_95.csv
Untracked: data/mhws_py_pctile_99.csv
Untracked: data/mhws_py_random.csv
Untracked: data/mhws_py_spw_11.csv
Untracked: data/mhws_py_spw_51.csv
Untracked: data/mhws_py_spw_no.csv
Untracked: data/mhws_py_whw_3.csv
Untracked: data/mhws_py_whw_7.csv
Untracked: data/sst_ALL.Rdata
Untracked: data/sst_ALL_KS.Rdata
Untracked: data/sst_ALL_cat_chi.Rdata
Untracked: data/sst_ALL_clim_category_count.Rdata
Untracked: data/sst_ALL_con.Rdata
Untracked: data/sst_ALL_detrend.Rdata
Untracked: data/sst_ALL_event_cor.Rdata
Untracked: data/sst_ALL_miss_clim_KS_p.Rdata
Untracked: data/sst_ALL_miss_clim_aov_p.Rdata
Untracked: data/sst_ALL_miss_clim_aov_tukey.Rdata
Untracked: data/sst_ALL_miss_event_CI.Rdata
Untracked: data/sst_ALL_smooth_R2.Rdata
Untracked: data/sst_ALL_smooth_R2_base.Rdata
Untracked: data/sst_ALL_smooth_cor_base.Rdata
Untracked: data/sst_ALL_smooth_real_category.Rdata
Untracked: data/sst_ALL_trend_cat_chi.Rdata
Untracked: data/sst_ALL_trend_clim_KS_p.Rdata
Untracked: data/sst_ALL_trend_clim_aov_tukey.Rdata
Untracked: data/sst_ALL_trend_clim_only.Rdata
Untracked: data/sst_ALL_trend_event_CI.Rdata
Untracked: data/sst_ALL_trend_event_aov_tukey.Rdata
Untracked: data/sst_WA.csv
Untracked: data/sst_WA_miss_ice.csv
Untracked: data/sst_WA_miss_random.csv
Unstaged changes:
Deleted: .Rbuildignore
Modified: .gitignore
Deleted: DESCRIPTION
Deleted: NAMESPACE
Modified: NEWS.md
Deleted: R/MHWdetection-package.R
Deleted: R/placeholder.R
Modified: README.md
Deleted: _pkgdown.yml
Modified: _workflowr.yml
Modified: analysis/_site.yml
Deleted: docs/articles/fig/heatwaveR_v3.svg
Deleted: docs/docsearch.css
Deleted: docs/docsearch.js
Deleted: docs/link.svg
Deleted: docs/pkgdown.css
Deleted: docs/pkgdown.js
Deleted: docs/pkgdown.yml
Deleted: docs/sitemap.xml
Deleted: man/MHWdetection-package.Rd
Deleted: man/placeholder.Rd
Deleted: tests/testthat.R
Deleted: tests/testthat/test-placeholder.R
Deleted: vignettes/.gitignore
Deleted: vignettes/Climatologies_and_baselines.Rmd
Deleted: vignettes/Short_climatologies.Rmd
Deleted: vignettes/best_practices.Rmd
Deleted: vignettes/bibliography.bib
Deleted: vignettes/data/.gitignore
Deleted: vignettes/data/clim_py.csv
Deleted: vignettes/data/clim_py_joinAG_1.csv
Deleted: vignettes/data/clim_py_joinAG_5.csv
Deleted: vignettes/data/clim_py_joinAG_no.csv
Deleted: vignettes/data/clim_py_minD_3.csv
Deleted: vignettes/data/clim_py_minD_7.csv
Deleted: vignettes/data/clim_py_pctile_80.csv
Deleted: vignettes/data/clim_py_pctile_95.csv
Deleted: vignettes/data/clim_py_pctile_99.csv
Deleted: vignettes/data/clim_py_random.csv
Deleted: vignettes/data/clim_py_spw_11.csv
Deleted: vignettes/data/clim_py_spw_51.csv
Deleted: vignettes/data/clim_py_spw_no.csv
Deleted: vignettes/data/clim_py_whw_3.csv
Deleted: vignettes/data/clim_py_whw_7.csv
Deleted: vignettes/data/mhwBlock.csv
Deleted: vignettes/data/mhws_py.csv
Deleted: vignettes/data/mhws_py_joinAG_1.csv
Deleted: vignettes/data/mhws_py_joinAG_5.csv
Deleted: vignettes/data/mhws_py_joinAG_no.csv
Deleted: vignettes/data/mhws_py_minD_3.csv
Deleted: vignettes/data/mhws_py_minD_7.csv
Deleted: vignettes/data/mhws_py_pctile_80.csv
Deleted: vignettes/data/mhws_py_pctile_95.csv
Deleted: vignettes/data/mhws_py_pctile_99.csv
Deleted: vignettes/data/mhws_py_random.csv
Deleted: vignettes/data/mhws_py_spw_11.csv
Deleted: vignettes/data/mhws_py_spw_51.csv
Deleted: vignettes/data/mhws_py_spw_no.csv
Deleted: vignettes/data/mhws_py_whw_3.csv
Deleted: vignettes/data/mhws_py_whw_7.csv
Deleted: vignettes/data/sst_ALL.Rdata
Deleted: vignettes/data/sst_ALL_KS.Rdata
Deleted: vignettes/data/sst_ALL_cat_chi.Rdata
Deleted: vignettes/data/sst_ALL_clim_category_count.Rdata
Deleted: vignettes/data/sst_ALL_con.Rdata
Deleted: vignettes/data/sst_ALL_detrend.Rdata
Deleted: vignettes/data/sst_ALL_event_cor.Rdata
Deleted: vignettes/data/sst_ALL_miss_clim_KS_p.Rdata
Deleted: vignettes/data/sst_ALL_miss_clim_aov_p.Rdata
Deleted: vignettes/data/sst_ALL_miss_clim_aov_tukey.Rdata
Deleted: vignettes/data/sst_ALL_miss_event_CI.Rdata
Deleted: vignettes/data/sst_ALL_miss_event_aov_tukey.Rdata
Deleted: vignettes/data/sst_ALL_smooth_R2.Rdata
Deleted: vignettes/data/sst_ALL_smooth_R2_base.Rdata
Deleted: vignettes/data/sst_ALL_smooth_cor_base.Rdata
Deleted: vignettes/data/sst_ALL_smooth_real_category.Rdata
Deleted: vignettes/data/sst_ALL_trend_cat_chi.Rdata
Deleted: vignettes/data/sst_ALL_trend_clim_KS_p.Rdata
Deleted: vignettes/data/sst_ALL_trend_clim_aov_tukey.Rdata
Deleted: vignettes/data/sst_ALL_trend_clim_only.Rdata
Deleted: vignettes/data/sst_ALL_trend_event_CI.Rdata
Deleted: vignettes/data/sst_ALL_trend_event_aov_tukey.Rdata
Deleted: vignettes/data/sst_WA.csv
Deleted: vignettes/data/sst_WA_miss_ice.csv
Deleted: vignettes/data/sst_WA_miss_random.csv
Deleted: vignettes/fig/detect_diagram.svg
Deleted: vignettes/fig/heatwaveR_v3.svg
Deleted: vignettes/gridded_products.Rmd
Deleted: vignettes/missing_data.Rmd
Deleted: vignettes/r_vs_python.Rmd
Deleted: vignettes/r_vs_python_additional.Rmd
Deleted: vignettes/r_vs_python_arguments.Rmd
Deleted: vignettes/time_series_duration.Rmd
Deleted: vignettes/trend.Rmd
Deleted: vignettes/variance.Rmd
Note that any generated files, e.g. HTML, png, CSS, etc., are not included in this status report because it is ok for generated content to have uncommitted changes.
In this vignette the results from the main three vignettes are combined in order to visualise them simultaneously. Following this are individual sections on how to address the challenges presented by length, missing data, and decadal trends respectively.
# A multi-panel summary figure with images and tables
load("data/sst_ALL.Rdata")
# sst_ALL_summary <- sst_ALL %>%
# Poential panels
# 1) The base time series
# 1.1) Rug pplot showing events
# 1.2) Events filled in with flames
# 1.3) Overlay thresholds
# 1.4) Overlay category thresholds
# 2) Mini map showing pixel location
# 3) Stats table (showing relevant stats for/from best practices)
# 4) The climatolgies/categories as there own doy x-axis panel
# 5) Lolli plot showing events
# ggplot(sst_ALL_summary)
The following figures show the combined results from time series length, missing data, and decadal trends side by side for each of the three components of the results. This helps to create a more complete pictures of the importance of the different variables.
sessionInfo()
R version 3.5.3 (2019-03-11)
Platform: x86_64-pc-linux-gnu (64-bit)
Running under: Ubuntu 16.04.5 LTS
Matrix products: default
BLAS: /usr/lib/openblas-base/libblas.so.3
LAPACK: /usr/lib/libopenblasp-r0.2.18.so
locale:
[1] LC_CTYPE=en_CA.UTF-8 LC_NUMERIC=C
[3] LC_TIME=en_CA.UTF-8 LC_COLLATE=en_CA.UTF-8
[5] LC_MONETARY=en_CA.UTF-8 LC_MESSAGES=en_CA.UTF-8
[7] LC_PAPER=en_CA.UTF-8 LC_NAME=C
[9] LC_ADDRESS=C LC_TELEPHONE=C
[11] LC_MEASUREMENT=en_CA.UTF-8 LC_IDENTIFICATION=C
attached base packages:
[1] stats graphics grDevices utils datasets methods base
loaded via a namespace (and not attached):
[1] workflowr_1.1.1 Rcpp_0.12.18 digest_0.6.16
[4] rprojroot_1.3-2 R.methodsS3_1.7.1 backports_1.1.2
[7] git2r_0.23.0 magrittr_1.5 evaluate_0.11
[10] stringi_1.2.4 whisker_0.3-2 R.oo_1.22.0
[13] R.utils_2.7.0 rmarkdown_1.10 tools_3.5.3
[16] stringr_1.3.1 yaml_2.2.0 compiler_3.5.3
[19] htmltools_0.3.6 knitr_1.20
This reproducible R Markdown analysis was created with workflowr 1.1.1