作者: Philip R. Evans , Garib N. Murshudov
DOI: 10.1107/S0907444913000061
关键词: Scale (descriptive set theory) 、 Resolution (logic) 、 Data reduction 、 Algorithm 、 Data quality 、 Reduction (complexity) 、 Scaling 、 Process (computing) 、 Data set 、 Computer science
摘要: Following integration of the observed diffraction spots, process `data reduction' initially aims to determine point-group symmetry data and likely space group. This can be performed with program POINTLESS. The scaling then puts all measurements on a common scale, averages symmetry-related reflections (using determined previously) produces many statistics that provide first important measures quality. A new program, AIMLESS, implements models similar those in SCALA but adds some additional analyses. From analyses, number decisions made about quality whether should discarded. effective `resolution' set is difficult possibly contentious question (particularly referees papers) this discussed light tests comparing data-processing trials refinement against simulated data, automated model-building comparison maps calculated different resolution limits. These show adding weak high-resolution beyond commonly used limits may make improvement does no harm.