 Hello, this is Hans van der Kwaas, senior lecturer at IHE Delft Institute for Water Education. In a previous video, I have demonstrated how to read time series from disk and interpolate them into PCRuster maps. In this video we are going to do the opposite. We are going to report certain locations on the map as textual tables that we can further process in spreadsheet programs or visualize with the Agila tool. We will use the same script as last time, but we will add some lines to report the precipitation from the two interpolation methods at different locations. First we will activate the PCRuster environment in the Anaconda prompt. Then we go to the folder where we have stored our results from last time. There we see the time series maps and the Python script. Let's have a look at the results again. We have 10 time steps of the inverse distance weighing of precipitation stations and decent polygons. Here we see the results. If I click on a location and I click right on the legend, I can ask a graph. This is generated on the fly based on the map data and I can animate it. Now, in this demonstration, I want these graphs as tables for three different locations that we are going to determine. You can sample the coordinates also in Agila. Here in the brackets it will give the coordinates. I'm going to make a text file with three different locations for which we are going to report the values. I use the copycon command. You can also use notepad or another text editor. I call the new file locations.text. It's a simple text file which has the format x, space, y, space, id. So I just take over the x and the y coordinates, it's the first point and add id1. Then I look up another point and I choose a third point and use Ctrl Z to save this text file. I can close all these Agila windows by choosing file exit from one of the windows. Now we start spider to edit the Python file to make it possible to report the precipitation at these three different locations. So I add a line here to initialize the time series output. Let's first do that for the idw. So I need to define a variable. I call it self.idw.tss. We use self remember because then I can reuse it in the dynamic section. The function to output the time series is time output time series and you see there what it needs. First it needs a string for the file name so it will generate these tss files which are basically normal text files as we have read also last time but now we will write them. So I just call it idw and then the output will be idw.tss. The model is self and then I need a map with the id's that's locations.map which I will create in a bit and I want a header so I call no header equals false. I still need to create the locations.map file. I use the call to map function which we also used last time, locations.text, locations.map and I want it to be of the same dimensions as the clone which is our dm. And I add here minus n to make it nominal. The three points are read and they are now on the map. Let's have a look, locations, three locations. So that's the preparation of the time series output. In order to report we need to go into the dynamic section and write the time series to the hard disk. Here we choose the variable from the initial and we add dot sample and we add the name of the variable that we want to report at the sample. So in this case press hit idw then it will use the information from the initialization to write it to idw.tss. Now I'm preparing for the tson so I simply copy it. Let's call the output th, same locations and then also in the dynamic I copy that line, replace with tson.tss, dot sample and then press hit tson to report the tson polygon precipitation. Then I can run it and let's have a look at the result. Just a directory listing and there I can see that the two tss files have been created idw.tss and th.tss. Now I can use the type command to visualize the contents of the text file and I see the header and for each point in the location dot map I see the values and then for ten time steps. With the agila command I can also visualize these. On the left we see the three graphs for idw for the three different points and on the right graph we see the ones for tson. If you want to do more analysis you can of course import these tss files into your spreadsheet program to further process. I hope this video was useful, if you would like to get updates please subscribe to my youtube channel and for more free materials go to gysopencourseware.org