Skip to main content

build PyPI - Python Version PyPI PyPI - Downloads DOI

edtools

Collection of tools for automated processing and clustering of batch 3-dimensional electron diffraction (3D ED) datasets.

The source for this project is available here.

Installation

Install using pip install edtools. Installation should take less than 20 seconds on a normal desktop.

Find the latest releases for the versions that have been tested on.

OS Requirement

Windows 10 or newer.

Software Requirements

  • Python 3.6+ including numpy, scipy, matplotlib, and pandas libraries
  • sginfo or cctbx.python must be available on the system path for edtools.make_shelx
  • Access to WSL
  • XDS package must be installed properly under WSL

Package dependencies

Check pyproject.toml for the full dependency list and versions.

Documentation

See the documentation at https://edtools.readthedocs.io.

Pipeline tools

At any step, run edtools.xxx -h for help with possible arguments.

autoindex.py

Looks for files matching XDS.INP in all subdirectories and runs them using XDS.

In:  XDS.INP
Out: XDS data processing on all files

Usage:

edtools.autoindex

extract_xds_info.py

Looks files matching CORRECT.LP in all subdirectories and extracts unit cell/integration info. Summarizes the unit cells in the excel file cells.xlsx and cells.yaml. XDS_ASCII.HKL files matching the completeness / CC(1/2) criteria are listed in filelist.txt. Optionally, gathers the corresponding XDS_ASCII.HKL files in the local directory. The cells.yaml file can be used as input for further processing.

In:  CORRECT.LP
Out: cells.yaml
     cells.xlsx
     filelist.txt

Usage:

edtools.extract_xds_info

find_cell.py

This program a cells.yaml file and shows histogram plots with the unit cell parameters. This program mimicks CELLPARM and calculates the weighted mean lattice parameters, where the weight is typically the number of observed reflections (defaults to 1.0). For each lattice parameter, the mean is calculated in a given range (default range = median+-2). The range can be changed by dragging the cursor on the histogram plots.

Alternatively, the unit cells can be clustered by giving the --cluster command, in which a dendrogram is shown. The cluster cutoff can be selected by clicking in the dendrogram. The clusters will be written to cells_cluster_#.yaml.

In:  cells.yaml
Out: mean cell parameters
     cells_*.yaml (clustering only)

Usage:

edtools.find_cell cells.yaml --cluster

make_xscale.py

Prepares an input file XSCALE.INP for XSCALE and corresponding XDSCONV.INP for XDSCONV. Takes a cells.yaml file or a series of XDS_ASCII.HKL files as input, and uses those to generate the XSCALE.INP file.

In:  cells.yaml / XDS_ASCII.HKL
Out: XSCALE.INP

Usage:

edtools.make_xscale cells.yaml -c 10.0 20.0 30.0 90.0 90.0 90.0 -s Cmmm

cluster.py

Parses the XSCALE.LP file for the correlation coefficients between reflection files to perform hierarchical cluster analysis (Giordano et al., Acta Cryst. (2012). D68, 649–658). The cutoff threshold can be selected by clicking in the dendrogram window. The program will write new XSCALE.LP files to subdirectories cluster_#, and run XSCALE on them, and (if available), pointless.

In:  XSCALE.LP
Out: cluster_n/
	filelist.txt
	*_XDS_ASCII.HKL
	XSCALE processing
	Pointless processing
	shelx.hkl
	shelx.ins (optional)

Usage:

edtools.cluster

Helper tools

make_shelx.py

Creates a shelx input file. Requires sginfo to be available on the system path to generate the SYMM/LATT cards.

In:  cell, space group, composition
Out: shelx.ins

Usage:

edtools.make_shelx -c 10.0 20.0 30.0 90.0 90.0 90.0 -s Cmmm -m Si180 O360

run_pointless.py

Looks for XDS_ASCII.HKL files specified in the cells.yaml, or on the command line and runs Pointless on them.

In:  cells.yaml / XDS_ASCII.HKL
Out: Pointless processing

update_xds.py

Looks files matching CORRECT.LP in all subdirectories, and updates the cell parameters / space group as specified.

In:  XDS.INP
Out: XDS.INP

Usage:

edtools.update_xds -c 10.0 20.0 30.0 90.0 90.0 90.0 -s Cmmm

find_rotation_axis.py

Finds the rotation axis and prints out the inputs for several programs (XDS, PETS, DIALS, Instamatic, and RED). Implements the algorithm from Gorelik et al. (Introduction to ADT/ADT3D. In Uniting Electron Crystallography and Powder Diffraction (2012), 337-347). The program reads XDS.INP to get information about the wavelength, pixelsize, oscillation angle, and beam center, and SPOT.XDS (generated by COLSPOT) for the peak positions. If the XDS.INP file is not specified, the program will try to look for it in the current directory.

In:  XDS.INP, SPOT.XDS
Out: Rotation axis

Usage:

edtools.find_rotation_axis [XDS.INP]

Demo of using edtools to process batch 3D electron diffraction datasets

See the demo at https://edtools.readthedocs.io/en/latest/examples/edtools_demo.html.

Release files for edtools 1.1.1

For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.

Source distribution (sdist)

Source distribution for edtools 1.1.1
File Size Uploaded
edtools-1.1.1.tar.gz 100.6 kB Details

Built distribution (wheel)

Table of built distributions (wheels) for edtools 1.1.1
File Interpreter ABI Platform
edtools-1.1.1-py3-none-any.whl Python 3 none any Details

Total release size: 205.1 kB

Release files / edtools-1.1.1.tar.gz

Download URL edtools-1.1.1.tar.gz
Size 100.6 kB
Tags Source
SHA-256 checksum
How to use checksums
9dc156d24ae9cb73b7fb154dcb2d49181b32b33160e7086e3ebe9d64c3a039c0
BLAKE2b-256 checksum
How to use checksums
b1d902532224e5214b9765302aa41a3bd32d6003d42dd84e144eb5130506d992
Upload date
Uploaded using Trusted Publishing?
What is trusted publishing?
Yes
Uploaded via twine/6.1.0 CPython/3.12.9

Provenance

Provenance describes where a file came from. On PyPI, provenance is shared via attestations, which provide a verifiable record of the build or publishing details. View details, limitations and caveats.

PyPI Publish Attestation

PyPI verified that this artifact, at this checksum, originated from the publisher listed below.

Signed by GitHub Actions, verified by PyPI on May 22, 2025.

Transparency log

Release files / edtools-1.1.1-py3-none-any.whl

Download URL edtools-1.1.1-py3-none-any.whl
Size 104.5 kB
Tags Python 3
SHA-256 checksum
How to use checksums
3db335ff9073c48f53d39680742edb958dc98ca4196b0454b755bdfb0902b4dd
BLAKE2b-256 checksum
How to use checksums
95977d38519b031ca07bd336d16e62bf3c308f7bc7b1dda15de8a45da22ea241
Upload date
Uploaded using Trusted Publishing?
What is trusted publishing?
Yes
Uploaded via twine/6.1.0 CPython/3.12.9

Provenance

Provenance describes where a file came from. On PyPI, provenance is shared via attestations, which provide a verifiable record of the build or publishing details. View details, limitations and caveats.

PyPI Publish Attestation

PyPI verified that this artifact, at this checksum, originated from the publisher listed below.

Signed by GitHub Actions, verified by PyPI on May 22, 2025.

Transparency log

Release history Release notifications | RSS feed

This release

1.1.1 This release

2 release files

1.1.0

2 release files

1.0.4

2 release files

1.0.3

2 release files

1.0.1

2 release files

1.0.0

2 release files

Anthropic, PBC Visionary sponsor Bloomberg Visionary sponsor Hudson River Trading Visionary sponsor Meta Visionary sponsor NVIDIA Visionary sponsor Microsoft Sustainability sponsor Depot Continuous Integration AWS Cloud computing and Security Sponsor Datadog Monitoring Fastly CDN Google Download Analytics Sentry Error logging StatusPage Status page