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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!



Mapping Earthquake Deformation in Taiwan With ENVI

Mapping Earthquake Deformation in Taiwan With ENVI

12/15/2025

Unlocking Critical Insights With ENVI® Tools Taiwan sits at the junction of major tectonic plates and regularly experiences powerful earthquakes. Understanding how the ground moves during these events is essential for disaster preparedness, public safety, and building community resilience. But traditional approaches like field... Read More >

Comparing Amplitude and Coherence Time Series With ICEYE US GTR Data and ENVI SARscape

Comparing Amplitude and Coherence Time Series With ICEYE US GTR Data and ENVI SARscape

12/3/2025

Large commercial SAR satellite constellations have opened a new era for persistent Earth monitoring, giving analysts the ability to move beyond simple two-image comparisons into robust time series analysis. By acquiring SAR data with near-identical geometry every 24 hours, Ground Track Repeat (GTR) missions minimize geometric decorrelation,... Read More >

Empowering D&I Analysts to Maximize the Value of SAR

Empowering D&I Analysts to Maximize the Value of SAR

12/1/2025

Defense and intelligence (D&I) analysts rely on high-resolution imagery with frequent revisit times to effectively monitor operational areas. While optical imagery is valuable, it faces limitations from cloud cover, smoke, and in some cases, infrequent revisit times. These challenges can hinder timely and accurate data collection and... Read More >

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 >

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Array Uniqueness in IDL

Anonym

 

When a person finds oneself in pursuit of retrieving information from data, it is often imperative to inspect every unique element - but why waste time on inspecting EVERY element when you can weed out the duplicates?

IDL has a uniq function built for just such a purpose. It goes in to an array, and removes any duplicates adjacent to one another.

Let's take an array:

IDL> array = [1,2,2,5,1,4,4,2]

When we run uniq on this array, it returns the indices that are NOT duplicates of an adjacent entry. This prints out:

IDL> print, uniq(array)

          0        2       3        4        6        7

In order to get back the original array with the elements removed, we can subset the array with these indices:

IDL> print, array[uniq(array)]

       1       2      5       1       4      2

The duplicate 2 and 4 have been removed, however there are still more duplicates in the array. To get just one of each unique element, you first have to use the sort function. This function also returns indices; in this case the indices that put the array in ascending order:

IDL> print, sort(array)

          4        0        7       2        1        6       5        3

Just like with uniq, these can be used to re-order the original array to get the sorted array:

IDL> print, array[sort(array)]

       1       1      2       2       2      4       4       5

Now for the final step - since this sorted array has all ofthe similar elements adjacent to each other, we can now use the uniq function to pull out all of the unique elements of the array.

IDL> s = array[sort(array)]

IDL> print, s[uniq(s)]

       1       2      4       5

Or for those that like to do it in one line:

IDL> print, (array[sort(array)])[uniq(array[sort(array)])]

       1       2      4       5

Now instead of looping over and entire array to check every element, IDL will be able to look through and array that is half the size of its original.

2 comments on article "Array Uniqueness in IDL"

Avatar image

Michael Galloy

A bit shorter for the one-line is to use the optional second argument to UNIQ:

IDL> print, array[uniq(array, sort(array))]

1 2 4 5


Avatar image

Jim P

In IDL 8.4, an even shorter way...

IDL> array.uniq()

1 2 4 5

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