Objective

Open source the libraries to parse .IDE recording files generated by enDAQ (Slam Stick) recorders.

Description

Many test applications are not the same from a measurement standpoint as well as an analysis perspective. Developers and analysts alike need the ability to directly interface with recording files without going through a GUI to develop custom applications and analysis scripts.

Many analysts and users, although technically competent and good data analysts are not well-versed programmers. However, they are adept at writing analysis scripts. They will need some assistance in accessing these libraries and getting started on their computer.

Requirements

• Return array of calibrated/converted data with time stamps per channel
• Return array of raw/unconverted data for faster processing
• Get list of sensor channels with metadata (sensor name, sample rate, etc.)
• Return metadata about recording (serial number, UTC start time, etc.)
• Future: configuration of recorders

Deliverables

• Published parsing library on Github
• Including the library in a pip installer and/or Anaconda for non-programmers to have relatively manageable access
• Add a scripting console to Lab software
• Tutorials and example scripts that utilize the libraries

Cost to the Customer

This will be published for free.

Example Use Cases

1. Programmer developing custom app: A programmer at an engineering company has an end customer that needs a very specific summary and display of recorded data. The progammer's company is looking to sell a software package along with a service to their end customer that utilizes enDAQ recorders to generate the data.
2. Data scientist performing custom analysis: A data scientist who is adept at writing analysis scripts in MATLAB, MathCAD, MAPLE, and some Python needs to perform a custom analysis on recordings and share with colleagues. The current workflow involves CSV exports that are time-consuming and require the use of a GUI. MATLAB tools have been very helpful but they require a MATLAB license to customize and the scientist is becoming intrigued about the cost savings Python offers. He has done some Python scripting but it is limited and will need some guidance in getting started; but he's a fast learner!