five

phaser: A unified and extensible framework for fast electron ptychography

收藏
DataONE2026-01-21 更新2026-02-07 收录
下载链接:
https://search.dataone.org/view/sha256:286c89f5c383cbb76997262460d479a8bde6bdb51d56fb08c777c967a0f06acf
下载链接
链接失效反馈
官方服务:
资源简介:
Electron ptychography is a groundbreaking technique for the advanced characterization of materials. Here, we present phaser, an open source Python package which provides a unified interface to both conventional and gradient descent based ptychographhc algorithms. This record provides data required to reproduce the benchmarks and results in our paper. It contains raw experimental and simulated 4D-STEM datasets, as well as reconstruction plan files and reconstruction outputs. , , ## Data from: phaser: A unified and extensible framework for fast electron ptychography This repository contains the data required to reproduce the results in the manuscript. To run the reconstructions and view the reconstructed data, download and install `phaser` ([https://github.com/hexane360/phaser](https://github.com/hexane360/phaser)) ## Detailed contents by subfolder ### fig4_benchmark Contains scripts and raw data for performance benchmarking. Benchmark results are recorded as newline-delimited JavaScript object notation (NDJSON) files, with the following columns: * `engine`: Which engine was used (`'lsqml'`, `'grad'`, `'epie'`) * `backend`: Which computational backend was used (`'jax'`, `'cupy'`, `'torch'` (PtyRAD), or `'matlab'` (`fold_slice`)) * `sim_size`: Size of diffraction patterns in reciprocal space * `n_positions`: # of scan positions in dataset * `n_slices`: # of object slices * `grouping`: Reconstruction grouping/batch size * `device`: GPU device reconstruction w...,
创建时间:
2026-01-22
5,000+
优质数据集
54 个
任务类型
进入经典数据集
二维码
社区交流群

面向社区/商业的数据集话题

二维码
科研交流群

面向高校/科研机构的开源数据集话题

数据驱动未来

携手共赢发展

商业合作