LinearLab Tools

LinearLabTools is a collection of Matlab and Python programs that provide direct access to Linear Technology’s data converter evaluation boards.

An evaluation board for a data converter will typically plug into an accompanying controller board, which is then connected to a host computer running a Linear supplied GUI program such as PScope for Analog-to-Digital converters or LTDACgen for Digital-to-Analog converters. The GUI allows basic performance measurements to be made, but it is not designed to run arbitrary sequences of tests or communicate with other hardware, as is often required by customers when evaluating a part for their own application. LinearLabTools allows customers to control Linear’s data converter demo boards as they would any other piece of test equipment, using their own software.

There’s more…

The LinearLabTools package also contains various application examples, simulations, and educational programs that demonstrate mixed signal concepts.

Quick Start

Complete Matlab Installation Instructions

Complete Python Installation Instructions

1) Install the appropriate GUI (PScope for ADCs or LTDACgen for DACs) that goes along with the demo board being evaluated, which will be detailed in the board’s demo manual. This ensures that the correct drivers are installed, and allows the system to be tested for basic functionality before attempting to access through LinearLabTools.

2) Follow the procedure in the board’s demo manual. This will include powering up the board, applying appropriate clock signals, and making the appropriate connections to analog inputs and outputs.

3) Download the LinearLabTools installer. Both 32-bit and 64-bit installers are provided. Choose the version that matches the calling software (for example, 32 or 64-bit Matlab), not the operating system. Extract this file to any convenient location, but maintain the directory structure.

Download 32-bit installer

Download 64-bit installer

4m) Matlab Users: All LinearLabTools Matlab scripts are tested using the base version of Matlab with some scripts requiring signal processing toolbox for extra features. These features can be commented out if needed."

Open Matlab. In the Matlab subdirectory, run Test_LinearLabTools_Matlab.m. The following screen should appear:

4p) Python Users: Dependencies are kept to a minimum, but NumPy, SciPy, and Matplotlib are required for the test scripts. All LinearLabTools Python scripts are tested using the distribution provided by Continuum Analytics, avaliable at this URL:

https://store.continuum.io/cshop/anaconda/

(Anaconda is preconfigured with the required dependencies.)

Open the Spyder debugger or your Python environment. In the \python\Test_LinearLabTools_Python subdirectory, run the Test_LinearLabTools_Python.py file. The following screen should appear:

5m) Navigate to the \Matlab\DemoBoardExamples\LTCxxxx directory, where xxxx is the part number of the device you are evaluating. Run the LTCxxxx_DCyyyy.m file, which will typically run through a series of operations demonstrating the various features of the demo board.

5p) Navigate to the \Python\DemoBoardExamples\LTCxxxx directory, where xxxx is the part number of the device you are evaluating. Run the LTCxxxx_DCyyyy.py file, which will typically run through a series of operations demonstrating the various features of the demo board.

5) Modify the example code as you see fit, or incorporate into your own test routines!

FAQ

What is LinearLabTools?

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LinearLabTools is a software suite that allows customers to directly access data converter demo boards from their own software environment. A Windows DLL provides low-level access to the board through one of several interfaces. Example code in Matlab and Python is included to demonstrate basic operation.

Why Matlab?

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This is one of the most common languages that customers use for evaluating products.

Why Python?

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Because it’s free and open source. We have occasionally seen Python used in a similar way as Matlab.

Is any of this code useful for my end product?

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LinearLabTools is primarily intended for product evaluation. There may be some code that can be leveraged for product development, such as register definitions.