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首页> 外文期刊>Journal of Applied Crystallography >An integration routine based on profile fitting with optimized fitting area for the evaluation of weak and/or overlapped two-dimensional Laue or monochromatic patterns
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An integration routine based on profile fitting with optimized fitting area for the evaluation of weak and/or overlapped two-dimensional Laue or monochromatic patterns

机译:基于轮廓拟合和优化拟合面积的集成例程,用于评估弱和/或重叠的二维劳厄或单色图案

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摘要

New software for the integration of weak and/or spatially overlapped diffraction patterns is presented. The program, named PROW (profile fitting for overlapped and weak data), uses box integration with an optimized summation area for strong nonoverlapped spots, and profile fitting with an optimized fitting area for weak and/or overlapped spots. The sizes of the integration areas are dynamically adjusted to find the best compromise between minimal bias resulting from statistical fluctuations of the X-ray background and maximal use of the information content in each diffraction spot. Deconvolution of spatially overlapped spots is performed by a standard least-squares procedure. The program is compatible with the Daresbury Laue software suite and with the DENZO package. It has been tested on several data-sets recorded on image-plate and CCD (charge-coupled device) detectors. Intensities extracted from very weak Laue data-sets containing as many as 60% overlapped spots were shown to be of sufficient quality to lead to an accurate structure refinement. Difficult monochromatic data-sets were also processed successfully, leading to a generally better compromise between reliability factors, redundancy and completeness than previously achieved. Concomitant improvement in atomic model refinement was also observed. [References: 35]
机译:介绍了用于积分弱和/或空间重叠衍射图样的新软件。该程序名为PROW(用于重叠数据和弱数据的轮廓拟合),使用具有最佳求和区域的框集成来处理强非重叠点,并使用具有优化拟合区域的轮廓拟合来处理弱和/或重叠点。动态调整积分区域的大小,以在X射线背景的统计波动引起的最小偏差与每个衍射点中信息内容的最大利用之间找到最佳折衷。通过标准最小二乘法对空间上重叠的点进行反卷积。该程序与Daresbury Laue软件套件和DENZO软件包兼容。它已经在成像板和CCD(电荷耦合器件)检测器上记录的多个数据集上进行了测试。从包含多达60%重叠斑点的非常弱的Laue数据集中提取的强度显示出足以导致精确的结构细化的质量。困难的单色数据集也得到了成功处理,从而导致可靠性因素,冗余性和完整性方面的折衷程度通常比以前达到的更好。还观察到原子模型细化的同时改善。 [参考:35]

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