Matplotlib Learning Notes - Part 6 (Preparing test data)

Matplotlib Learning Notes - Part 6 (Preparing test data)

Tunnel Diode Matplotlib Test Data v0.6

Now I have transferred the tunnel diode I-V curve plot v0.1 measurement to a python dictionary for further processing to matplotlib compatible data.

Matplotlib Learning Notes - Part 5 (Plotting data)

Matplotlib Learning Notes - Part 5 (Plotting data)

Declarative programming - Wikipedia

In computer science, declarative programming is a programming paradigm—a style of building the structure and elements of computer programs—that expresses the logic of a computation without describing its control flow.

Many languages that apply this style attempt to minimize or eliminate side effects by describing what the program must accomplish in terms of the problem domain, rather than describe how to accomplish it as a sequence of the programming language primitives (the how being left up to the language's implementation). This is in contrast with imperative programming, which implements algorithms in explicit steps.

Declarative programming often considers programs as theories of a formal logic, and computations as deductions in that logic space. Declarative programming may greatly simplify writing parallel programs.

Common declarative languages include those of database query languages (e.g., SQL, XQuery), regular expressions, logic programming, functional programming, and configuration management systems.

Matplotlib Learning Notes - Part 4 (Converting Excel Data to Matplotlib)

Matplotlib Learning Notes - Part 4 (Converting Excel Data to Matplotlib)

This is the Excel worksheet I am going to convert to Matplotlib.

I am using python dictionary to store the tunnel diode I-V measurements.  First step is to just copy the cells and paste to Chinese Win10 Notebook:

Plotting I-V Curve of Tunnel Diode 2BS4 Sample #1, v0.2 tlfong01  2020nov24hkt1346

Step Vt (mV) It (mA) Remark

1 0.10 0.02 Before Negative Resistance Region

2 0.20 0.02

3 0.30 0.03

4 0.40 0.05

5 0.50 0.06

6 1.00 0.11

7 2.00 0.24

8 3.00 0.34

9 4.00 0.46

10 5.00 0.57

11 6.00 0.80

12 7.00 0.78

13 9.00 1.01

14 10.00 1.11

15 11.00 1.21

16 12.00 1.32

17 13.00 1.41

18 14.00 1.51

19 15.00 1.60

20 16.00 1.70

21 194.00 1.88 Negative Resistance Region

22 206.00 1.88

23 221.00 1.88

24 241.00 1.88

25 250.00 1.88

26 271.00 1.88

27 486.00 1.88 After Negative Resistance Region

28 488.00 1.95

29 490.00 2.06

30 492.00 2.15

31 495.00 2.32

32 498.00 2.49

33 500.00 2.63

Next step is to copy and paste the NoteBook data to a  python dictionary, 

and yes, start coding:

Talk is cheap, show me the code - Linus Torvolds

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MCP4725 TaoBao Order

MCP4725 TaoBao Order

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MAX4172 Learning Notes - Part 1 (Taobao Order)

MAX4172 Learning Notes - Part 1 (Taobao Order)

So I have placed my MAX4172 order this morning.

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Matplotlib Learning Notes - Part 3 (Introduction and Demo Program)

Matplotlib Learning Notes - Part 3 (Introduction and Demo Program)

I found the official installation guide and demo program not up to date for Rpi4B OS 2010dec.  After some trials and errors, for 20 minutes, I finally ran my first program OK, as show below.

My first impression is that matplotlib should be easier to use, and more powerful than Excel.

References

(1) Installing matplotlib in Thonny

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MathPlotLib Learning Notes - Part 2 (User Guide)

 MathPlotLib Learning Notes - Part 2 (User Guide)

Matplotlib: Visualization with Python

Matplotlib is a comprehensive library for creating 

static, animated, and interactive visualizations in Python.

Matplotlib makes easy things easy and hard things possible.

Create

Develop publication quality plots with just a few lines of code

Use interactive figures that can zoom, pan, update...

Customize

Take full control of line styles, font properties, axes properties...

Export and embed to a number of file formats and interactive environments

Extend

Explore tailored functionality provided by third party packages

Learn more about Matplotlib through the many external learning resources

Documentation

User's Guide 

Release 3.3.3 2020nov20

• Installation Guide
  • Installing an official release
  • Third-party distributions of Matplotlib
  • Installing from source
• Tutorials
  • Introductory
  • Intermediate
  • Advanced
  • Colors
  • Provisional
  • Text
  • Toolkits
• Interactive Figures
  • Interactive Figures and Asynchronous Programming
  • Event handling and picking
  • IPython integration
  • Interactive mode
  • Default UI
  • Other Python prompts
• History

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