GIS Programming: Debugging and Error Handling

-


"At the source of every error which is blamed on the computer you will find at least two human errors, 
including the error of blaming it on the computer."

~Anonymous



The art of debugging is arguably one of the most important skills for any programmer. Procedures for debugging include: 
  • Reviewing error messages 
  • Inserting print messages at select locations within the script
  • Commenting out lines or sections of code
  • Using a debugger 
Our task for this week's lab was to debug two pre-written scripts using some of the above procedures and add a try-except statement to a third script to catch the error. 


Script 1

Script one contained two errors and/or exceptions that needed to be fixed in order for the script to run. Once fixed, the script printed out the names of all fields within the parks.shp attribute table. 

Flowchart for Script 1.


Script 1 output. 


Script 2

Script 2 contained several errors/exceptions that needed to be corrected in order for the script to run. This script printed out the names of all the layers in the TravisCountyAustinTX.aprx project. 

Flowchart for Script 2.


Script 2 output. 


Script 3

Script 3 contained an error that prevented the script from running, but instead of fixing this error, our task was to insert a try-except statement so that the code would successfully run. 

Flowchart for Script 3.

 

Script 3 output.






Comments

Post a Comment

Popular posts from this blog

Isarithmic Mapping: Annual Precipitation in Washington State

-
Image
The second most common type of thematic map behind the choropleth map is the isarithmic map. While choropleth maps are great for mapping phenomena existing within hard boundary lines, also known as enumeration units, isarithmic maps are perfect for mapping continuous data such as temperature, precipitation, or elevation. In isarithmic mapping, contour lines are frequently used to connect locations with equal values. Hypsometric tints can then be added to color the areas between contour lines with different shades so that map readers can easily distinguish between areas with high and low values.  In this lab, our task was to create an isarithmic map showing average annual rainfall in Washington State. This rainfall data was interpolated using the PRISM (Parameter-elevation Regressions on Independent Slopes Model) method developed by Oregon State University. The map below was created using ArcGIS Pro. Areas with low precipitation (less than 10 in/yr) are shown in red, and areas with the
Read more

Final Project: Bobwhite-Manatee Transmission Line Analysis

-
Image
The Bobwhite-Manatee transmission line is a 230kw line that connects Florida Power & Light’s (FPL) Manatee Energy Center in Manatee County with a substation about 3 miles south of the Manatee-Sarasota County border. Although this transmission line has already been installed, for the purpose of this assignment we assumed this project was still being planned.  Our task was to use ArcGIS Pro to analyze FPL’s proposed location based on four primary objectives identified in a survey conducted by FPL: (1) environmental impacts, (2) number of homes and parcels affected, (3) number of schools and daycares affected, and (4) total length and cost. The final project incorporated many of the processes and concepts we have been working with throughout the course.  Below are my map outputs for this assignment. Links to my presentation and transcript can be found at the bottom.  Link to Presentation Video Link to Presentation Transcript
Read more

Development Suitability Analysis

-
Image
For one of the scenarios in this week's lab, I was playing the role of a GIS Analyst for a property developer. My task was to create a map showing suitable land for development based on the following criteria:  Land Cover Soils Slopes Streams Roads  My general process for this analysis was to first convert all of these layers into rasters if they weren't already. For the rivers and roads layers, I used the Euclidean Distance tool to calculate the shortest distance from each cell to the nearest river or road. I then reclassified each of these layers based on a suitability scale of 1 - 5. Lastly, I combined the results of each of these five criteria using the Weighted Overlay tool. Below are my results.  The first map is an equally weighted average where each of the five criteria have an influence of 20% (or 1/5th). The second map shows an alternatively weighted output where each of the five criteria were weighed as follows:  Land cover (20%)  Soils (20%) Slope (40%) Distance to
Read more