X

NV5 Geospatial Blog

Each month, NV5 Geospatial posts new blog content across a variety of categories. Browse our latest posts below to learn about important geospatial information or use the search bar to find a specific topic or author. Stay informed of the latest blog posts, events, and technologies by joining our email list!



Easily Share Workflows With the Analytics Repository

Easily Share Workflows With the Analytics Repository

10/27/2025

With the recent release of ENVI® 6.2 and the Analytics Repository, it’s now easier than ever to create and share image processing workflows across your organization. With that in mind, we wrote this blog to: Introduce the Analytics Repository Describe how you can use ENVI’s interactive workflows to... Read More >

Deploy, Share, Repeat: AI Meets the Analytics Repository

Deploy, Share, Repeat: AI Meets the Analytics Repository

10/13/2025

The upcoming release of ENVI® Deep Learning 4.0 makes it easier than ever to import, deploy, and share AI models, including industry-standard ONNX models, using the integrated Analytics Repository. Whether you're building deep learning models in PyTorch, TensorFlow, or using ENVI’s native model creation tools, ENVI... Read More >

Blazing a trail: SaraniaSat-led Team Shapes the Future of Space-Based Analytics

Blazing a trail: SaraniaSat-led Team Shapes the Future of Space-Based Analytics

10/13/2025

On July 24, 2025, a unique international partnership of SaraniaSat, NV5 Geospatial Software, BruhnBruhn Innovation (BBI), Netnod, and Hewlett Packard Enterprise (HPE) achieved something unprecedented: a true demonstration of cloud-native computing onboard the International Space Station (ISS) (Fig. 1). Figure 1. Hewlett... Read More >

NV5 at ESA’s Living Planet Symposium 2025

NV5 at ESA’s Living Planet Symposium 2025

9/16/2025

We recently presented three cutting-edge research posters at the ESA Living Planet Symposium 2025 in Vienna, showcasing how NV5 technology and the ENVI® Ecosystem support innovation across ocean monitoring, mineral exploration, and disaster management. Explore each topic below and access the full posters to learn... Read More >

Monitor, Measure & Mitigate: Integrated Solutions for Geohazard Risk

Monitor, Measure & Mitigate: Integrated Solutions for Geohazard Risk

9/8/2025

Geohazards such as slope instability, erosion, settlement, or seepage pose ongoing risks to critical infrastructure. Roads, railways, pipelines, and utility corridors are especially vulnerable to these natural and human-influenced processes, which can evolve silently until sudden failure occurs. Traditional ground surveys provide only periodic... Read More >

1345678910Last
4152 Rate this article:
No rating

New in IDL 8.6: IDLTasks

Anonym

ENVITasks have been around for a few years now, but they didn’t help those of you who only have IDL and not ENVI as well.  In IDL 8.6 we are happy to announce that the ENVITask concept has been carried over to work in pure IDL without ENVI.  Many of the features are the same, but there are slight differences that I want to point out in this post.

The first and most obvious is how you construct an IDLTask.  Rather than launch ENVI and then call the ENVITask()function, you can call the IDLTask()function at any point in time.  As the help points out, you can pass in either a scalar string that is the name of the task you want or its filename, or you can pass in a Hash object that is the task definition (what you would get if you called JSON_Parse() on a task file).  If you pass in a string that isn’t a filename (relative or absolute), then it is treated as a task name.  The function will then look at !PATH and search for all .task files in each folder listed there.  It catalogs all the .task files it finds, but if there are multiple folders with the same base name only the first is recognized(just like how IDL handles multiple .pro or .sav files with the same base name found in !PATH).  The list of .task files is filtered to those with the correct IDLTask schema, which currently is only “idltask_1.0”.  This way we don’t accidentally pick up an ENVITask files and cause confusion.  If a.task file with the same base name as the requested task name is found, it is used as the task definition.  If no exact match is found, but partial matches exist, then helpful error messages are returned telling you about the name(s) that partially match, so you can correct your code.  I should point out that the current working directory (which can be retrieved by calling CD with the CURRENT keyword) is searched before any of the folders in !PATH, so that can affect the behavior of IDLTask().

The “idltask_1.0” task schema used for IDLTasks in IDL 8.6 is very similar to the “envitask_3.0” schema used by ENVITasks in ENVI 5.4.  The notable exception is that the TYPE property of your parameters won’t understand ENVI class types like ENVIRaster.  But all the basic datatypes available in IDL are supported by IDLTasks – strings, Booleans, and numbers, as well as List, Hash, OrderedHash, and Dictionary.

Another difference is how you interact with IDLTasks on GSF as opposed to ENVITasks.  The service endpoint for IDLTasks will be http://hostname:port/ese/services/IDL,while the ENVITasks use http://hostname:port/ese/services/ENVI.  The different endpoints are used to discriminate between the requests that should use the IDLTask() function vs the ENVITask() function to load the requested task.

Easy GSF deployment is one of the primary reasons you would want to build IDLTasks in the first place. If you have IDL functions or procedures that you are used to calling directly, then you are probably wondering why you would want to wrap them in an IDLTask.  As a C++ developer in a previous life, I appreciated the type safety that C++ requires, so I also appreciate the parameter validation that IDLTasks provide.  When developing your custom IDLTask, you will have to spend some time thinking about what the inputs and outputs are for your code, but once you do that you won’t need to worry about writing lots of input validation code, the IDLTask framework will take care of that for you.  The IDLTasks are also self-documenting like ENVITasks, so if someone else hands you a .task file and .sav file, you can load the task and then learn all about the parameter names, their types, cardinalities, and hopefully even descriptions. All of this information makes it possible to deploy your algorithms on GSF for running in the cloud, with all the same introspection capabilities over the REST endpoint.  Alternatively, you can set up batch processing using some sort of folder watch capability to spawn IDLTaskEngine instances to automatically run your code on each file that appears on your system.

 

Please login or register to post comments.