krishna/data #1

marsultor · 2026-03-30T21:57:24-05:00

marsultor commented

2026-03-30 21:57:24 -05:00

PR: Add regression analysis and wire resistance data

Summary

This PR adds linear regression analysis for wire resistance measurements across three AWG gauges (26, 29, 32), including:

Python analysis script with outlier detection
High-quality scatter plots with regression lines
Complete data table with raw measurements
Regression parameters and resistivity calculations

Changes

New Files

analysis.py - Python script for regression analysis with matplotlib
wire_resistance_regression.png - Generated plot (259 KB)
wire_resistance_regression.pdf - Vector version of plot (23 KB)
raw-data.csv - Raw measurement data

Modified Files

mnras_template.tex - Updated with:
- Resistance measurement table (3 AWG gauges × 5 distances)
- Regression analysis figure
- Regression parameters table with resistivity values
- Notes about experimental outlier at L=60cm for 26 AWG
.gitignore - Added Python cache entries (__pycache__/, *.pyc)

Build Artifacts

mnras_template.pdf - Generated PDF (186 KB)

Key Results

AWG	Resistivity (Ω·cm)	R²
26	0.000119	0.854
29	0.000144	0.9997
32	0.000146	1.000

29 AWG and 32 AWG measurements match Kanthal A1 standard (0.000145 Ω·cm) within 1%.

Notes

26 AWG data contains documented outlier at L=60cm (4.5 Ω vs expected ~6.4 Ω)
Unit conversion corrected: mm² → cm² (factor of 0.01)
All values use 6 decimal places for precision

Questions

Should mnras_template.pdf be tracked in git or added to .gitignore?
Should wire_resistance_regression.png be compressed or kept at full quality?

# PR: Add regression analysis and wire resistance data ## Summary This PR adds linear regression analysis for wire resistance measurements across three AWG gauges (26, 29, 32), including: - Python analysis script with outlier detection - High-quality scatter plots with regression lines - Complete data table with raw measurements - Regression parameters and resistivity calculations ## Changes ### New Files - `analysis.py` - Python script for regression analysis with matplotlib - `wire_resistance_regression.png` - Generated plot (259 KB) - `wire_resistance_regression.pdf` - Vector version of plot (23 KB) - `raw-data.csv` - Raw measurement data ### Modified Files - `mnras_template.tex` - Updated with: - Resistance measurement table (3 AWG gauges × 5 distances) - Regression analysis figure - Regression parameters table with resistivity values - Notes about experimental outlier at L=60cm for 26 AWG - `.gitignore` - Added Python cache entries (`__pycache__/`, `*.pyc`) ### Build Artifacts - `mnras_template.pdf` - Generated PDF (186 KB) ## Key Results | AWG | Resistivity (Ω·cm) | R² | |-----|-------------------|-----| | 26 | 0.000119 | 0.854 | | 29 | 0.000144 | 0.9997 | | 32 | 0.000146 | 1.000 | 29 AWG and 32 AWG measurements match Kanthal A1 standard (0.000145 Ω·cm) within 1%. ## Notes - 26 AWG data contains documented outlier at L=60cm (4.5 Ω vs expected ~6.4 Ω) - Unit conversion corrected: mm² → cm² (factor of 0.01) - All values use 6 decimal places for precision ## Questions 1. Should `mnras_template.pdf` be tracked in git or added to `.gitignore`? 2. Should `wire_resistance_regression.png` be compressed or kept at full quality?

marsultor added 3 commits 2026-03-30 21:57:24 -05:00

data table added 773fe6cde8

should be good 7512c6228a

changed tracking 10d345aa33

marsultor closed this pull request

2026-03-30 21:59:21 -05:00

Pull request closed

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Reference: marsultor/physics-lab-report-resitivity#1