Macrosystems EDDIE: Getting Started + Troubleshooting Tips

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Macrosystems EDDIE: Getting Started + Troubleshooting Tips
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Macrosystems EDDIE: Getting Started + Troubleshooting Tips Developed by K.J. Farrell and C.C. Carey for use with Macrosystems EDDIE modules. http://www.macrosystemseddie.org Module development supported by NSF EF 1702506. Last updated: 22 Jan. 2018 Welcome the students to class. It might be helpful to go around the room and briefly discuss if anyone has experience programming or modeling. The point of this is to emphasize that most students are likely novices, and that asking lots of questions is ok because their peers are novices as well. It is really important at this point to emphasize that there will be lots of new material covered during this module, and that going slowly and asking for help is very much encouraged!

First Things First Before you start your Macrosystems EDDIE module, make sure you have done the following to help it go as smoothly as possible: Check that your computer operating system is up-to-date with recommended updates (see next slides for Mac and PC) Image: static.binaryage.com

Check for Updates: Mac 1) 2) 3) Click the Apple symbol, then About this Mac Click on Software Updates If updates are available, they will open in the App Store. Click Update All to install all updates. 1) 2) 3)

Check for Updates: Windows 7 Press the Windows button, then type “Update” to search Click on Windows Update Click the Check for updates link If needed, press Install updates 1) 2) 3) 4)

Check for Updates: Windows 10 Press the Windows button, then type “Update” to search Click on Check for Updates Click Check for updates and install updates if needed. 3) 1) 2)

Second Things Second Check that R and RStudio are both up-to-date, and download new versions if necessary When you open RStudio, you will see your version of R. It should be at least 3.4.2 Check for updates to RStudio by clicking Help, then Check for Updates

R and RStudio Statistical environment Point and click program for using R in one place Run code Visualize plots Access files Check-in: Have you downloaded both R and RStudio? Look in your Applications (Mac) or in the Start menu (Windows) to confirm this-- both programs should be listed.

Unpack Files to Desktop: Windows 1) 2) 3) 4) Download the zip folder directly to Desktop (or move folder from Downloads to Desktop) Right click on the .zip folder and choose Extract All Check that your files are: - being extracted to the Desktop - end exactly lake_climate_change (or cross_scale_emergence for Module 2 or Teleconnections for Module 3). Also check the box “Show extracted files when complete” To open the module script in RStudio, right click on the file name (e.g., R_ForPCs), then choose Open with… and RStudio

Unpack Files to Desktop: Mac Download the zip folder directly to Desktop (or move folder from Downloads to Desktop) Control + click on the .zip folder and choose Open with  Archive Utility to unzip the folder. Then double click on the unzipped folder To open the module script in RStudio, control + click on the file name (e.g., R_ForMacs), then choose Open with… and RStudio 1) 2) 3)

Opening Module Files in RStudio Congrats! You’ve opened the module script in RStudio!

RStudio Basics: Console The Console appears in the bottom left panel, and shows the status of your scripts. As you run the module, you will check here for confirmation messages and error codes. You can also use the console to do math and ‘assign’ objects, which lets you save things for later. Try typing in the following on the console: mySum <- 2 + 2 + 4 (press Enter) mySum (press Enter)

RStudio Basics: Console Try typing in the following on the console: mySum <- 2 + 2 + 4 (press Enter) mySum (press Enter) You now see that the object mySum is saved in the Environment tab, and when you type mySum into the console, you get the answer (8)!

RStudio Basics: Script The Script appears in the top left panel, and shows the commands you will run for the module. As you work through the module, you will read directions in the script and execute code. In R scripts, lines that begin with a # are not read by the program– these lines are comments or directions you need to read to move through the module.

RStudio Basics: Script The Script appears in the top left panel, and shows the commands you will run for the module. As you work through the module, you will read directions in the script and execute code. In R scripts, lines that begin with a # are not read by the program– these lines are comments or directions you need to read to move through the module. Lines that do not begin with a # are lines of script that need to be run. You can run a line of script by putting your cursor inside the line, then pressing Run (or Ctrl + Enter)

RStudio Basics: Files In the right panels (usually the bottom right), you will see a tab named Files. This panel shows the all of the files and subfolders of your lake_climate_change folder.

RStudio Basics: Plots In the right panels (usually the bottom right), you will also see a tab named Plots. This panel shows the figures you create while working through the module.

RStudio Basics: Plots You can show your plot in a stand-alone window if you press the Zoom button. If you have made more than one plot, you can toggle between them using the arrows. You can also copy and paste your plots to another document (e.g., Word or PowerPoint), or save them to your computer using the Export command.

Activity A: What’s my computer name? In Activity A, you need to define your sim_folder. This involves changing the computer name from farrellk (my computer’s name!) to your computer’s name. In the Files pane, you should see your computer name (here, my computer name is KFarrell). If you unpacked your module folder to the Desktop, this name is the only thing you should need to change in defining the sim_folder.

Activity A: What’s my computer name? In Activity A, you need to define your sim_folder. This involves changing the computer name from farrellk (my computer’s name!) to your computer’s name. If you don’t can’t find your computer name in the Files tab, you can also find it by right clicking on your lake_climate_change (or cross_scale_emergence or Teleconnections) folder on the desktop, then choosing Properties. Your computer name will be shown as part of the Location.

Activity B: Formatting Dates After you’ve modified your met_hourly file for your climate scenario, you need to explicitly format your date for GLM Right click on the A at the top of the time column, then click Format Cells

Activity B: Formatting Dates After you’ve modified your met_hourly file for your climate scenario, you need to explicitly format your date for GLM Click Custom, then type the correct format into the Type: box. The format must be exactly as follows: YYYY-MM-DD HH:MM:SS Then press OK and save your .csv file.

Macrosystems eddie: GLM Troubleshooting tips

Error: gml.exe had status 309 When does it happen? run_glm(sim_folder, verbose=TRUE) will start the GLM run, but you will likely get an error similar to: “gml.exe had status 309” Why? Problem with 32-bit vs. 64-bit R in Windows 10 How to fix it: In the RStudio menu, click on Tools, then Global Options. In the General tab, check what R version RStudio is using (the first line at the top of the window). If the selected version starts with [Default] [64-bit], try pressing Change and selecting the [Default] [32-bit] option. You will then need to restart RStudio and try the script again.

Error: Day 2451636 (2000-04-01) not found When does it happen? run_glm(sim_folder, verbose=TRUE) will start the GLM run, but you will likely get an error similar to: “Day 2451636 (2000-04-01) not found” Why? time column in .csv file not formatted correctly for GLM How to fix it: Open .csv file in Excel. Right click on the time column, then select Format. Choose Custom, then type in YYYY-MM-DD HH:MM:SS exactly. Save and close your .csv file. Run the following lines in R to ensure your time column is formatted for GLM (search to find in the R script, then run): metdata <- read.csv("met_hourly_climate.csv", header=TRUE) metdata$time <-as.POSIXct(strptime(metdata$time, "%Y-%m-%d %H:%M:%S", tz="EST")) write.csv(metdata, "met_hourly_climate.csv", row.names=FALSE, quote=FALSE) Make sure you edit the file name (in blue, above) to match your .csv file.