updated

Author: ratnanil

00_Admin/bibliography.bib

@@ -91,6 +91,6 @@ Now we will set some RStudio Global options. Go to *Tools → Global options*.
 
 Click on "Ok" to apply the change and close the options menu.
 
-[^restore]: We recommend that you start each RStudio session with a blank slate, as recommended by @wickham2017 see [here](https://r4ds.had.co.nz/workflow-projects.html)
+[^restore]: We recommend that you start each RStudio session with a blank slate, as recommended by @wickham2023 see [here](https://r4ds.hadley.nz/workflow-scripts#projects)
 [^saveworkspace]: If we don't restore the workspace at startup, there is no need to save it on exit.
 [^pipe]: Our group has adapted the native pipe operator `|>` to reduce package dependencies. If you use the `magrittr` pipe `%>%` and would like to stick to it, feel free. 

02_Images/zhaw_lsfm_iunr_weiss.png

@@ -4,9 +4,7 @@ As your course assignment (Leistungsnachweis) you will develop a semester projec
 
 In fact, we give you the opportunity to track your own movement behavior, generating trajectory data you will subsequently analyze yourself. There are two ways for you to generate your own trajectory data. 
 
-<!-- During the course, we will give you the opportunity to share your data with the other students in the course, so that the shared data pool for all can grow. -->
-
-Please let us know which option you choose by filling out the following [survey](https://moodle.zhaw.ch/mod/choice/view.php?id=1192128) on Moodle.
+Please let us know which option you choose by filling out the following [survey](https://moodle.zhaw.ch/mod/choice/view.php?id=1539895) on Moodle.
 
 ## Option 1: Tracking App
 
@@ -35,7 +33,7 @@ Tracking Methods
 
 :::
 
-Please check after a view days if the tracking is working properly. If you have any issues during installation or you are not able to track yourself after the installtion please get in contact with [Nils](mailto:rata@zhaw.ch) or [Dominic](mailto:luoe@zhaw.ch).
+Please check after a view days if the tracking is working properly. If you have any issues during installation or you are not able to track yourself after the installtion [please get in contact with us](mailto:terz@zhaw.ch).
 
 ***If, however, for privacy reasons, you dont want to use a Tracking App we can hand out a GPS tracker to you.***
 
@@ -45,4 +43,4 @@ You can use a GPS tracker, provided by our research group. By using a GPS tracke
 
 The drawback off this option is, that in order to retreave the data, you need to bring the tracker to us. Also more manual preprocessing is necessary when preparing your data for the project.
 
-If you choose this option please send us a quick [E-Mail](mailto:luoe@zhaw.ch) so we can arrange the handover of the GPS tracker. You can get the tracker in our office GC 134 at the [Campus Grüental, Wädenswil](https://goo.gl/maps/xDvGFMBEvwBMdWiz7).
+If you choose this option please send us a quick [E-Mail](mailto:terz@zhaw.ch) so we can arrange the handover of the GPS tracker. You can get the tracker in our office GC 134 at the [Campus Grüental, Wädenswil](https://goo.gl/maps/xDvGFMBEvwBMdWiz7).

02_Images/zhaw_sw_pos.png

@@ -1,4 +1,5 @@
 Version: 1.0
+ProjectId: 43cdd95c-d3cc-4093-bf7c-a93f64fb3a17
 
 RestoreWorkspace: No
 SaveWorkspace: No
@@ -14,8 +15,6 @@ LaTeX: pdfLaTeX
 
 BuildType: Website
 
-PythonType: 
-PythonVersion: 
-PythonPath: .
-
 SpellingDictionary: en_GB
+
+ProjectName: CMA - FS25

Intro/1_preparations_course.qmd

@@ -10,16 +10,22 @@ Before starting with the task:
 
 1. Make sure you have read and followed the instructions in section [Preparation](#w0-preparation)
 2. In RStudio, open the RStudio Project you created for this week. You can see that you are in an RStudio Project if the project's name is visible next to the little RStudio logo in the top right corner of RStudio (otherwise it will read `Project: (None)`).
-3. Download the wild boar movement data here: [wildschwein_BE.csv](https://moodle.zhaw.ch/mod/folder/view.php?id=1192125)
+3. Download the wild boar movement data from [moodle](https://moodle.zhaw.ch/) (*RStuff* → *Datasets*)
 
 
 
 ### Task 1: Import data
 
 Move the file `wildschwein_BE.csv` into your project directory and import it into `r` as a `data.frame`. Assign correct column types as necessary and make sure the time zone is set correctly for the date/time column.
 
-Note: We recommend using the `readr` package to import data (see @sec-readr). These functions have an underscore in their name, e.g. `read_delim` in oppose to the base `R` functions, which have a period (e.g. `read.delim`). Specifically for the wild boar data, we recommend `read_delim()`.
 
+:::{.callout-note}
+
+## `read.delim` vs. `read_delim`
+
+We recommend using the `readr` package to import data (see @sec-readr). These functions have an underscore in their name, e.g. `read_delim` in oppose to the base `R` functions, which have a period (e.g. `read.delim`). 
+
+:::
 
 
 ```{r}
@@ -65,6 +71,8 @@ wildschwein_BE_sf <- st_as_sf(wildschwein_BE,
 )
 ```
 
+<br class="br">
+
 Notice how `st_as_sf` takes the EPSG code for the `crs =` argument. You can find a lot of useful information on Coordinate Reference Systems (including EPSG Codes, etc.) under [epsg.io](http://epsg.io).  
 Let's compare our original `data.frame` with this new `sf` object:
 
@@ -77,6 +85,10 @@ wildschwein_BE
 wildschwein_BE_sf
 ```
 
+:::{.br}
+:::
+
+
 As you can see, `st_as_sf()` has added some metadata to our dataframe (`Geometry type`, `Dimension`, `Bounding box`, `Geodetic CRS`) and replaced the columns `Lat` and `Long` with a column named `geometry`. Other than that, the new `sf` object is very similar to our original dataframe. In fact, `sf` objects *are* essentially `dataframes`, as you can verify with the function `is.data.frame()`:
 
 ```{r}
@@ -86,6 +98,7 @@ is.data.frame(wildschwein_BE_sf)
 ```
 
 All operations we know from handling `data.frames` can be used on the `sf` object. Try some out!
+
 ```{r}
 #| echo: true
 #| results: "hide"
@@ -98,6 +111,9 @@ wildschwein_BE_sf[wildschwein_BE_sf$TierName == "Sabi", ]
 wildschwein_BE_sf[, 2:3]
 ```
 
+:::{.br}
+:::
+
 Instead of keeping the same data twice (once as a `data.frame`, and once as an `sf` object), we will overwrite the `data.frame` and continue working with the `sf` object from now on. This saves some memory space in `R` and avoids confusion. 
 
 ```{r}
@@ -126,6 +142,7 @@ So what can we do with our new `sf` object that we couldn't before? One example
 ```
 
 Here's the resulting `sf` object from the operation:
+
 ```{r}
 #| echo: true
 
@@ -137,6 +154,9 @@ wildschwein_BE
 
 Transforming from one Coordinate Reference System to another was one operation where we needed an object with a spatial nature. In this way, we were able to use an off-the-shelf function to project the coordinates from one CRS to another. In our next example, we again rely on a spatial function: We want to calculate a [convex hull](https://en.wikipedia.org/wiki/Convex_hull) per Wild boar. And guess what the function for calculating a convex hull is called in `sf`? If you guessed `st_convex_hull()`, you were right! 
 
+:::{.br}
+:::
+
 By default `st_convex_hull()` calculates the convex hull *per feature*, i.e. *per point* in our dataset. This of course makes little sense. In order to calculate the convex hull per animal, we need to convert our point- to multipoint-features where each feature contains all positions of one animal. This is achieved in two steps:
 
 First: add a grouping variable to the `sf` object. Note the new grouping variable in the metadata of the `sf` object. Other than that, `group_by` has no effect on our `sf` object.
@@ -151,6 +171,10 @@ wildschwein_BE_grouped <- group_by(wildschwein_BE, TierID)
 wildschwein_BE_grouped
 ```
 
+
+:::{.br}
+:::
+
 Second: use `summarise()` to "dissolve" all points into a multipoint object. 
 
 ```{r}
@@ -179,7 +203,7 @@ Using base plot to visualize `sf` objects is easy enough, just try the following
 plot(mcp)
 ```
 
-But since we use `ggplot` extensively, try and plot the object `mcp` with `ggplot`. Hint: Use the layer `geom_sf()` to add an `sf` object.
+One wildboar is seems to be hidden by one of the others. Try and plot the object `mcp` with `ggplot`, setting the layer's `alpha`
 Note: `ggplot` refuses to use our specified CRS, so we need to force this by specifying `datum = ` in `coord_sf()`. Try it out.
 
 ```{r}
@@ -190,60 +214,28 @@ Note: `ggplot` refuses to use our specified CRS, so we need to force this by spe
 ```
 
 
-### Input: Importing raster data {#w1-importing-raster}
-
-In the next task, we would like to add a background map to our `mcp` object. Download the file here: [pk100_BE.tif](https://moodle.zhaw.ch/mod/folder/view.php?id=1192125)
-To import the file into `R`, we use the package `terra` with the function `rast`.
-
-```{r}
-#| echo: true
-
-library("terra")
-
-pk100_BE <- terra::rast("datasets/pk100_BE.tif")
-
-pk100_BE
-```
-
-`pk100_BE_2056.tif` is a three layered geotiff File. The above console output shows some metadata including the resolution, extent and the names of our layers (`pk1_1`, `pk1_2`etc). With the default `plot` method, each layer is displayed individually:
-
-```{r}
-#| echo: true
-
-plot(pk100_BE)
-```
+### Task 5: Making maps with `tmap`
 
-With `plotRGB` all three layers are combined into a single image:
-
-```{r}
-plotRGB(pk100_BE)
-```
-
-### Task 5: Adding a background map
-
-There are multiple ways to add a background map in `ggplot`, many require additional packages. This is a good opportunity to get to know a completely different package for creating maps: `tmap` ("thematic map"). This package was developed with a syntax very similar to `ggplot2`, which makes it easy to learn.
+Let's get to know a completely different package for creating maps: `tmap` ("thematic map"). This package was developed with a syntax very similar to `ggplot2`, which makes it easy to learn.
 
 ```{r}
 #| echo: true
 
 library("tmap")
 
-tm_shape(pk100_BE) +
-    tm_rgb()
+tm_shape(wildschwein_BE) +
+    tm_dots(fill = "TierName")
 ```
 
-As you can see, plotting layers in `tmap` is combined with the `+` sign, just as in `ggplot2`. In `tmap` however, each layer consists of two objects: a `tm_shape()` in which the data is called, and a `tm_*` object in which we define how the data is visualized (`tm_rgb()` states that it is plotted as an RGB Raster Layer). Add the object `mcp` to the plot in this manner. Read [the vignette](https://cran.r-project.org/web/packages/tmap/vignettes/tmap-getstarted.html) if you are having trouble.
+As you can see, plotting layers in `tmap` is combined with the `+` sign, just as in `ggplot2`. In `tmap` however, each layer consists of two objects: a `tm_shape()` in which the data is called, and a `tm_*` object in which we define how the data is visualized (`tm_dots()` states that it is plotted as a point layer). 
 
+Add the object `mcp` to the plot in this manner. Checkout the [tmap website](https://r-tmap.github.io/tmap/) if you are having trouble.
 
-```{r}
-#| file: "solutions/week1/task_5.R"
-#| echo: false
 
-```
 
 ### Task 6: Create an interactive map
 
-Rerun the `tmap()...` command from the previous task, but switch the plotting mode to "view"" (`tmap_mode("view")`) beforehand. Omit the raster layer (`pk100_BE`), you won't be needing it.
+Rerun the `tmap()...` command from the previous task, but switch the plotting mode to "view"" (`tmap_mode("view")`) beforehand. 
 
 
 ```{r}

Intro/2_preparations_project.qmd

@@ -6,7 +6,7 @@
 # source("01_R_Files/helperfunctions.R")
 ```
 
-Up to now, we have used a variety of different functions designed by other developers. Sometimes we need to execute an operation multiple times, and most often it is reasonable to write a function to do so. Whenever you have copied and pasted a block of code more than twice, you should consider writing a function [@wickham2017]. 
+Up to now, we have used a variety of different functions designed by other developers. Sometimes we need to execute an operation multiple times, and most often it is reasonable to write a function to do so. Whenever you have copied and pasted a block of code more than twice, you should consider writing a function [@wickham2023]. 
 
 The first step in writing a function, is picking a name and assigning `<- function(){}` to it.