diff --git a/README.md b/README.md index 78664a7..b403f97 100644 --- a/README.md +++ b/README.md @@ -70,6 +70,7 @@ Since April 2023, there is an [interactive app](https://brry.shinyapps.io/wetter +With `rdwd::app()`, you can run this locally with cached data, i.e. faster responses. ### New to R diff --git a/misc/ExampleTests/Radartests_Vign.pdf b/misc/ExampleTests/Radartests_Vign.pdf index 2c382b1..d729c47 100644 Binary files a/misc/ExampleTests/Radartests_Vign.pdf and b/misc/ExampleTests/Radartests_Vign.pdf differ diff --git a/misc/vign/index.Rmd b/misc/vign/index.Rmd index d00382c..b99010e 100644 --- a/misc/vign/index.Rmd +++ b/misc/vign/index.Rmd @@ -25,7 +25,7 @@ Important links: * further details on the data: [DWD FTP server documentation](https://opendata.dwd.de/climate_environment/CDC/Readme_intro_CDC_ftp.pdf) * website [source code and files](https://github.com/brry/rdwd/tree/master/misc/vign) * feedback is very welcome via [github](https://github.com/brry/rdwd) or [berry-b@gmx.de](mailto:berry-b@gmx.de)! - +* app for [comparing weather periods](https://brry.shinyapps.io/wetter/) ```{r globalquiet, echo=FALSE} options(rdwdquiet=TRUE) @@ -99,8 +99,9 @@ When a point is clicked, an infobox should appear. The first line can be copypasted into R to obtain more information on the available files. The map is created with the following code: -```{r map, fig.height=7, fig.width=7, warning=FALSE, screenshot.force=FALSE} -library(rdwd) ; data(geoIndex) ; library(leaflet) +```{r map, fig.height=7, fig.width=7, warning=FALSE, eval=-1, screenshot.force=FALSE} +rdwd::updateRdwd() # for the latest version +library(rdwd) ; data(geoIndex) ; library(leaflet) leaflet(geoIndex) %>% addTiles() %>% addCircles(~lon, ~lat, radius=900, stroke=F, color=~col) %>% addCircleMarkers(~lon, ~lat, popup=~display, stroke=F, color=~col) @@ -124,6 +125,7 @@ To request the nonpublic datasets counted in the infobox, please contact . -A helper function to reduce code duplication: +Before running the code below, update the package: +```{r updaterdwd_raster, eval=FALSE} +rdwd::updateRdwd() +``` + +A helper function to reduce code duplication - in real life, use `plotRadar` directly, not `project_and_plot`: ```{r readDWD_gridded} ddir <- locdir() @@ -483,6 +490,8 @@ rad <- readDWD(file) # with dividebyten=TRUE rad <- readDWD(file) # runs faster at second time due to skip=TRUE pp <- project_and_plot(rad, ".raster", "", proj="seasonal", extent=rad@extent) ``` +`project_and_plot` is additional stuff on this website. Use `plotRadar` in real life. + ## readDWD.nc `r helplink("readDWD.nc")` @@ -588,7 +597,8 @@ Open the pdf at download & read data -```{r uc_recent_time_series_data, eval=TRUE, fig.height=3, fig.width=7} +```{r uc_recent_time_series_data, eval=TRUE, fig.height=3, fig.width=7, eval=-1} +rdwd::updateRdwd() library(rdwd) link <- selectDWD("Potsdam", res="daily", var="kl", per="recent") clim <- dataDWD(link, force=NA, varnames=TRUE) @@ -619,6 +629,9 @@ berryFunctions::climateGraph(temp, prec, main="Goettingen") mtext("Source: Deutscher Wetterdienst", adj=-0.05, line=2.8, font=3) ``` +See also the [app](https://brry.shinyapps.io/wetter/) to visualize the weather of a given time period, compared to the measurements of the same period in other years. +This can also be run locally with `rdwd::app()`. + # - use case: merge historical and recent data ```{r uc_histrecent} @@ -732,6 +745,13 @@ raster::extract(tempmax_stack, loc) # - use case: daily radar files +Update the package first: +```{r updatardwd_radar, eval=FALSE} +rdwd::updateRdwd() +library(rdwd) +``` + +rdwd::updateRdwd() Download and read with `r helplink("readDWD.radar")` with `dividebyten=TRUE`: ```{r daily_radar_read} # library("rdwd") @@ -849,7 +869,8 @@ Publication: ## get the URLS of data to be downloaded -```{r hourlyrain_data_selection, warning=FALSE} +```{r hourlyrain_data_selection, warning=FALSE, eval=-1} +rdwd::updateRdwd() library(rdwd) links <- selectDWD(res="daily", var="more_precip", per="hist") length(links) # ca 5k stations - would take very long to download @@ -1200,9 +1221,7 @@ More detailed (but still aggregated) changes can nicely be seen at https://githu ## the future I plan to continue maintaining the package, even though its capabilities have long exceeded my personal needs. -Coding simply brings joy - and of course it's also very satisfactory to see my work actually used in many contexts. -One big thing I have planned is an interactive app to visualize the weather of a given time period, -compared to the measurements of the same period in other years. +Coding simply brings joy - and of course it's also very satisfactory to see my work actually used in many contexts. A few (rather minor) issues are also still open and I expect that state of things to continue for a long time :). Lastly, I hope to find some help in understanding the structure of gridded data to improve that part of the package.