Welcome to informatics documentation!

informatics is a fast construction utility for scientific computation pipeline in Python. With this project we aim to establish:

• a generic and prototypical AI development-oriented tool-kit for scientific computation, analytics, and data visualization;

• an uniform protocol for packaging abstract data processing flow, in order to integrating workflows from varying code styles;

• the tutorial materials about numerical computation and mathematical modeling on essential principles, and programming practices.

The data to be supported mainly with this platform, targeted for but not limited to numpy array.

Table of Contents

• 1. Introduction
  • 1.1. Installation
    • 1.1.1. Platforms and options
    • 1.1.2. Check installation
    • 1.1.3. Upgrade for options
  • 1.2. Overview
    • 1.2.1. Featured as
    • 1.2.2. Simple examples
• 2. Tutorials
  • 2.1. Functional programming
    • 2.1.1. Scripting via function
    • 2.1.2. Pipelining data process
  • 2.2. Example navigation
    • 2.2.1. Preparing batch processing
    • 2.2.2. Transform and identification
    • 2.2.3. DICOM related operations
    • 2.2.4. Applying data augmentation
• 3. Documentations
  • 3.1. API reference
  • 3.2. Related URLs
• 4. Supplementary
  • 4.1. Nomenclature
    • 4.1.1. Math symbols and abbreviations
  • 4.2. Data science essentials
    • 4.2.1. High dimensional data
    • 4.2.2. About matrix
    • 4.2.3. Factor analysis
    • 4.2.4. Mathematical statistics
    • 4.2.5. Monte Carlo method
  • 4.3. Scientific calculation essentials
    • 4.3.1. Feature capturing
    • 4.3.2. Anomaly and change
  • 4.4. Informatics essentials
    • 4.4.1. Functional programming primer
    • 4.4.2. Basic concepts in informatics
• 5. References

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Authors:

Chen Zhang

Version:

0.0.4

Created on:

Apr 25, 2023