Review rpygeo

_rmd/2019-03-10-RPyGeo-1_0_0.Rmd

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+---
+layout: post
+title: "RPyGeo 1.0.0"
+date:  "`r format(Sys.time(), '%d %B, %Y')`"
+comments: true
+author: Marc Becker
+categories: r
+---
+
+<script src="https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.0/MathJax.js?config=TeX-AMS-MML_HTMLorMML" type="text/javascript"></script>
+
+[DOWNLOADHERE]
+
+RPyGeo 1.0.0 has been released on CRAN. The RPyGeo package establishes an interface to the geoprocessing tools of ArcGIS from within R. ArGIS is a geographic information system developed by Esri. 
+
+The new RPyGeo package accesses the ArcPy Python side-package via the [reticulate](https://cran.r-project.org/web/packages/reticulate/index.html) package. ArcGIS provides almost all of it's geoprocessing tools via ArcPy. With RPyGeo these functions are available in R. Additonally RPyGeo provides utilitiy functions to create a seamless workflow between ArcGIS and R. 
+
+In 2015 Esri released the R-ArcGIS Bridge, a software that also connects ArcGIS and R. Essentially, the R-ArcGIS Bridge offers read, write and conversion functions to transfer data from ArcGIS to R and vice versa. The idea is to use the large number of R packages to solve spatial problems, which cannot be solved with ArcGIS alone. R scripts can be run as geospatial scripts with an interactive user inferface from within ArcGIS. However, no functionality is added for the R user. RPyGeo is able to run the geoprocessing tools of ArcGIS directly from the R session.      
+The update added many new features to the package. It is now possible to chain ArcPy functions togheter with the pipe operator. Help files for all ArcGIS functions can be viewed directly inside RStudio. Moreover, map algebra expressions can be used to modify raster objects.   
+
+For a detailed instruction on how to use RPyGeo we would like to refer to the [vignette](https://cran.r-project.org/web/packages/RPyGeo/RPyGeo.pdf). It includes a tutorial with all essential RPyGeo functions. 
+
+The devolepment of RPyGeo is now integrated into the r-spatial.org community. If you find any bugs please report them at our new development repository [r-spatial/RPyGeo](https://github.com/r-spatial/RPyGeo) or help us fix them via a pull request.

_rmd/2019-03-11-RPyGeo-1_0_0.Rmd

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+---
+layout: post
+title: "RPyGeo 1.0.0"
+date:  "`r format(Sys.time(), '%d %B, %Y')`"
+comments: true
+author: Marc Becker
+categories: r
+---
+
+<script src="https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.0/MathJax.js?config=TeX-AMS-MML_HTMLorMML" type="text/javascript"></script>
+
+[DOWNLOADHERE]
+
+RPyGeo 1.0.0 has been released on 14.11.2018 on CRAN. The RPyGeo package establishes an interface to the geoprocessing tools of ArcGIS from within R. [ArcGIS](https://www.esri.com/en-us/arcgis/about-arcgis/overview) is the leading commercial geographic information system platform, which is developed by Esri since 1999.
+
+ArcGIS offers access to its geoprocessing tools via a Python site-package called ArcPy. The new version of RPyGeo reads the site-package via the [reticulate](https://cran.r-project.org/web/packages/reticulate/index.html) package into the R session.
+
+If you want to run the following examples you need a working ArcMap or ArcGIS Pro installation. In addition, install and attach the following packages and execute the other commands to get some data.
+
+```{r, eval=FALSE}
+library("RPyGeo")
+library("sf")
+library("raster")
+library("magrittr")
+
+data(dem, package = "RQGIS")
+writeRaster(dem, file.path(tempdir(), "dem.tif"), format = "GTiff")
+```
+
+After a quick initialization, which usually finds the ArcGIS installation automatically, all geoprocessing tools of ArcGIS are available in R.   
+
+```{r, eval=FALSE}
+arcpy <- rpygeo_build_env(workspace = tempdir(),
+                          overwrite = TRUE)
+```
+
+The ArcPy functions can be accessed via the `$` operator. All functions are listed after typing the `$` operator in RStudio. 
+
+```{r, eval=FALSE}
+arcpy$Slope_3d(in_raster = "dem.tif", out_raster = "slope.tif")
+```
+
+RPyGeo can load spatial objects stored in Esri's proprietary geodatabases as well as files from the hard disk with the `rpygeo_load()` function.
+
+```{r, eval=FALSE}
+slope <- rpygeo_load("slope.tif")
+
+plot(slope)
+```
+
+<img src="../images/rpygeo1.jpg", width="100%" style="display: block; margin: auto;" />
+*Figure 1: Slope computed with Slope_3d() and plotted in R.*
+
+Both functions can be chained using the pipe operator. It is also possible to use the pipe operator to chain multiple geoprocessing tools.
+
+```{r, eval=FALSE}
+arcpy$Slope_3d(in_raster = "dem.tif", out_raster = "slope.tif") %>%
+  rpygeo_load()
+```
+
+Map algebra expressions can be used in RPyGeo with special operators to modify ArcPy raster objects. The resulting temporary files can be saved to the hard disk with the helper function `rpygeo_save()`.
+
+```{r, eval=FALSE}
+ras <- arcpy$sa$Raster("dem.tif") 
+
+ras %rpygeo_+% 2 %>%
+  rpygeo_save("dem_2.tif")
+```
+
+With the new version many other utility functions are added. Help files for all AcrPy functions can be viewed directly inside Rstudio with the `rpygeo_help()` function. `rpygeo_search()` returns all available geoprocessing functions that contain a specified search term. The new functions try to provide a seamless workflow between ArcGIS and R.
+
+In 2015 Esri released the [R-ArcGIS Bridge](https://r-arcgis.github.io), a software that also connects ArcGIS and R. Essentially, the R-ArcGIS Bridge offers read, write and conversion functions to transfer data from ArcGIS to R and vice versa. The idea is to use the large number of R packages to solve spatial problems, which cannot be solved with ArcGIS alone. R scripts are integrated into geoprocessing scripts, which can be run as geoprocessing tools from within ArcGIS. The user can add a user interface to the geoprocessing tool or use it as a part of a ModelBuilder workflow. However, no functionality is added for the R user. The R-ArcGIS Bridge cannot run geoprocessing tools from within R, whereas RPyGeo offers almost all geoprocessing tools of ArcGIS directly from the R session. The R-ArcGIS Bridge is developed for users, who want to process their whole workflow from within ArcGIS, whereas RPyGeo is developed for R users who wants to integrate a geoprocessing tool into their R workflow.
+
+For a detailed instruction on how to use RPyGeo we would like to refer to the [vignette](https://cran.r-project.org/web/packages/RPyGeo/RPyGeo.pdf). It includes a tutorial with all essential RPyGeo functions and the necessary data to run the above examples.
+
+The source code of RpyGeo is now hosted on Github within the r-spatial organization. If you find any bugs please report them at our new development repository [r-spatial/RPyGeo](https://github.com/r-spatial/RPyGeo) or help us fix them via a pull request.