positional arguments:¶

FILE

I(q) files to convert into p(r)

options:¶

-h, --help

show this help message and exit

-v, --verbose

switch to verbose mode

-V, --version

show program's version number and exit

-o OUTPUT, --output OUTPUT

Output filename

-u {nm,??,A}, --unit {nm,??,A}

Unit for q: inverse nm or ??ngstrom?

-n NPT, --npt NPT

number of points in p(r) curve

-s SCAN, --scan SCAN

Initial alpha-scan size to guess the start parameter

-m MC, --mc MC

Number of Monte-Carlo samples in post-refinement

-t THRESHOLD, --threshold THRESHOLD

Sample at average ?? threshold*sigma in MC

free_bift is a Python implementation of the Bayesian Inverse Fourier Transform This code is the implementation of Steen Hansen J. Appl. Cryst. (2000). 33, 1415-1421 Based on the BIFT from Jesse Hopkins, available at: https://sourceforge.net/p/bioxtasraw/git/ci/master/tree/bioxtasraw/BIFT.py It aims at being a drop in replacement for datgnom of the ATSAS suite.