SAXS-Graphs

Regain control of your SAXS data. This Python script is designed to process SAXS (Small Angle X-ray Scattering) data and to generate results such as the Guinier approximation, the Kratky graph and the volume of correlation in a text file format. Then you can make YOUR OWN representations for these graphs, with YOUR preferred software (Excel, Prism, Origin etc.).

User manual

Prerequisites

• Python 3.x
• Necessary packages: numpy, matplotlib, scipy
• SAXS Data need to be in Å-1

Command syntax

python Sexier-vXX.py filename.dat qmin_offset qmax_offset

• filename.dat : the name of the .dat file containing the SAXS experimental data.
• qmin_offset : the offset (in a number of lines) to be added to the first usable line to determine qmin, use the value from PRIMUS (Range) or RAW (nmin).
• qmax_offset: the offset (in a number of lines) to be added to the first usable line to determine qmax use the value from PRIMUS (Range) or RAW (nmax).

Features

1. Guinier approximation :

• Read .dat file and determine a first usable line.
• Data extraction for q and I(q) in the selected range.
• Linear regression to calculate Rg (radius of gyration) and I0 (intensity at q=0).
• Write data to text file.
• Display graph with experimental points and theoretical curve.

2. Kratky 2:

• Extract data in the selected range for Kratky.
• Calculation and normalisation of values for Kratky (𝑞𝑅𝑔)^2.𝐼(𝑞)/𝐼(0) vs 𝑞𝑅𝑔.
• Write data to a text file.
• Display Kratky graph.

3. Correlation volume (CV):

• Extract data up to q=0.3 or up to 8/Rg. Calculate the integral of the product I(q)*q.
• Calculation of VC, QR (quality factor) and MW (molecular weight).
• Calculation of the Mw from Porod using SAXSMOW approach with a cut at 8/Rg
• Write data to text file.

4. Summary file:

• Write values for Rg, I0, qmin_Rg, qmax_Rg, MW to a text file.

Output

The script will generate the following files:

• filename_01_Rg.txt: Guinier approximation data (q^2, ln(I_exp), ln(I_theo), normalized residuals)
• file_name_02_Norm-Kratky.txt: data for normalized Kratky (x, y)
• file_name_03_VC.txt: data for VC (q, I(q)*q)
• file_name_04_VC_integral.txt: data for VC
• file_name_05_Summary.txt: summary file (Rg, I0, qmin_Rg, qmax_Rg, MW)

Plots:

1- Form factor 2- Guinier Fit (Rg, I(0), qminRg qmaxRg,nbeg, nend) & Residuals of the fit (check aggregation and or repulsion, here looks nice) 3- Normalised Kratky plot (here presence of disordered regions) 4- Plot of the Volume of correlation and cumulative integral (MW determination at 0.3, 8/Rg and from Porod cut at 8/Rg)

Notes:

1. It's possible to make an exe file for Windows using "pyinstaller", to distribute the script on computers without Python.
2. I can also provide the stand-alone version for Windows upon request.