This skill provides guidance for Raman spectrum peak fitting tasks. It should be used when analyzing spectroscopic data, fitting Lorentzian or Gaussian peaks to Raman spectra, or working with graphene/carbon material characterization. The skill emphasizes critical data parsing verification, physical constraints from domain knowledge, and systematic debugging of curve fitting problems.
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SKILL.md
Raman Fitting
Overview
This skill guides the analysis and curve fitting of Raman spectroscopy data, particularly for materials like graphene where characteristic peaks (G, D, 2D bands) must be accurately extracted. The primary challenge in these tasks is ensuring correct data ingestion before any analysis begins.
Critical First Step: Data Parsing Verification
Before any fitting or analysis, verify data is parsed correctly. This is the most common source of failure in spectroscopic data analysis.
Data File Inspection Protocol
Read raw file content first - Examine the first 5-10 lines of the raw data file to understand the actual format
Identify potential format issues:
Line number prefixes (e.g., "1→", "2→" before actual data)
Decimal separators (comma vs period - European vs US format)
Use visual inspection or automatic peak finding to set initial guesses:
from scipy.signal import find_peaks
# Find peaks in the data
peaks, properties = find_peaks(intensity, height=threshold, distance=min_distance)
# Use found peak positions as initial guesses
for peak_idx in peaks:
x0_guess = wavenumber[peak_idx]
amplitude_guess = intensity[peak_idx]