Workflow Development and Automation

Course Description

In this course we’ll look at tools available in Matlab and PLS_Toolbox to automate tasks. These tasks include importing data, model building, and or visualization. It’s likely that a real-world implementation will be a mashup of these tasks and include others. Examples of how our staff use automation in their own work will be examined. Finally, we’ll look at when, where, and how to improve performance. Hands-on exercises will be done using MATLAB and PLS_Toolbox.

Prerequisites

Chemometrics I — PCA and Chemometrics II – Regression and PLS or equivalent experience.

Course Outline

1. Overview of Data Structures, Objects, and Plotting
   • Fundamental Data Types
   • Introduction to Objects
   • DataSet Object
   • Model Object
   • Scripts and Functions
   • Chemometric Data Discussion (raw data vs a model vs meta data)
2. Practical Automation
   • Importing Data
     • File reading basics
     • Combining Data into DataSet
   • Modeling
     • Building Models using demo scripts
     • Building a bunch of models (what to iterate over)
     • Model Optimizer
     • Script as a Lab Notebook
     • Matlab Live Scripts
   • Visualizations
     • Basic Plotting Elements
     • Matlab and PLS_Toolbox Plotting Organization (dataset objects, axes, figures, etc.)
     • PLS_Toolbox Plotting Tools
     • Reportwriter
   • Staff Examples
3. Performance
   • Profiling
     • Identify slow code sections
   • Speedup
     • Improve by optimizing code or by changing analysis algorithms
   • Parallel Computing Toolbox
     • Speed up by using all CPU cores
     • Usage tips