4 image lysozyme dataset recorded on the Jungfrau 16M detector at SwissFEL and formatted as a NeXus file

This is a 4 image lysozyme datasets derived from https://doi.org/10.5281/zenodo.3352357. The specific 4 images are able to be processed by the software package DIALS using commands in the linked dataset above. The images were rounded to integer and compressed to save file space using this script: <pre><code class="language-python">import shutil, h5py import numpy as np shutil.copyfile('../lyso009a_0087.JF07T32V01_master.h5', 'lyso009a_0087.JF07T32V01_master_4img.h5') h5 = h5py.File('lyso009a_0087.JF07T32V01_master_4img.h5', 'r+') data = h5["entry/data/data"][()] del h5["entry/data/data"] h = h5["entry/data"] subset = data[5:9].astype(np.int32) h.create_dataset("data", subset.shape, subset.dtype, subset, compression="gzip", compression_opts=9) h5.close()</code></pre> The .expt file was created by dials.import and is useful for regression testing in DIALS.本数据集为包含4张图像的溶菌酶（lysozyme）数据集，源自https://doi.org/10.5281/zenodo.3352357。可通过上述链接数据集附带的命令，使用DIALS软件包处理该4张特定图像。为节省文件存储空间，本数据集通过如下Python脚本将图像数据取整并压缩： <pre><code class="language-python">import shutil, h5py import numpy as np shutil.copyfile('../lyso009a_0087.JF07T32V01_master.h5', 'lyso009a_0087.JF07T32V01_master_4img.h5') h5 = h5py.File('lyso009a_0087.JF07T32V01_master_4img.h5', 'r+') data = h5["entry/data/data"][()] del h5["entry/data/data"] h = h5["entry/data"] subset = data[5:9].astype(np.int32) h.create_dataset("data", subset.shape, subset.dtype, subset, compression="gzip", compression_opts=9) h5.close()</code></pre> 该数据集附带的.expt格式文件由dials.import工具生成，可用于DIALS的回归测试。