Skip to main content

Repository for useful python data analysis functions for the Diamond Magnetic Materials Group

Project description

PyPI License

mmg_toolbox

Repository for useful python data analysis functions for the Diamond Magnetic Materials Group

Source https://github.com/DiamondLightSource/mmg_toolbox
PyPI pip install mmg_toolbox
Documentation https://diamondlightsource.github.io/mmg_toolbox
Releases https://github.com/DiamondLightSource/mmg_toolbox/releases

Installation

Requires: Python >=3.10, Numpy, h5py, matplotlib, hdfmap, nexus2srs

python -m pip install mmg_toolbox

@DLS

mmg_toolbox is available via the module system:

$ module load mmg
(python)$ dataviewer
# OR
(python)$ create_notebooks

Usage - Read a NeXus scan file

Read data from a NeXus scan file in a python prompt or script

from mmg_toolbox import data_file_reader
scan = data_file_reader('12345.nxs', beamline='i16')
print(scan)  # print a metadata string

scan.plot.plot()  # plot defaults
scan.plot.show()

Usage - DataViewer

Start the dataviewer from a terminal

$ dataviewer

Or, to open the data viewer in the current folder:

$ dataviewer .

Or, to open the file viewer for a specific file:

dataviewer path/to/file.nxs

Usage - Scripting

mmg_toolbox contains many useful tools for data analysis in python scripts, for example:

import matplotlib.pyplot as plt
from mmg_toolbox import Experiment

exp = Experiment('/path/to/files')

# list scans
all_scans = exp.all_scan_numbers()  # {scan_number: filename}
print('\n'.join(exp.scans_str(*all_scans)))

exp.plot(1108746, 1108747, 1108748)

scans = exp.scans(*range(-10, 0))
for scan in scans:
    scan.plot()
    axes, signal = scan.eval('axes, signal')

create_notebooks

the create_notebooks script is included as a simple way to get started and create some default scripts in your working directory. By default you will be prompted to provide a beamline and a directory or visit ID. The script can then start a Jupyter Lab instance in that directory.

command
$ create_notebooks interactively create scripts and start jupyter
$ create_notebooks -b i10-1 . create i10-1 specific scripts in the current directory
$ create_notebooks --help additional options

Dataviewer

mmg_toolbox contains a tkinter based dataviewer for viewing data in NeXus files. Various plotting and processing capabilities are available. mmg_dataviewer

Feedback

mmg_toolbox is still under development, so if you have any feedback, found any bugs or have any feature requests - please do let me know!

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

mmg_toolbox-0.6.2.tar.gz (213.2 kB view details)

Uploaded Source

Built Distribution

If you're not sure about the file name format, learn more about wheel file names.

mmg_toolbox-0.6.2-py3-none-any.whl (245.1 kB view details)

Uploaded Python 3

File details

Details for the file mmg_toolbox-0.6.2.tar.gz.

File metadata

  • Download URL: mmg_toolbox-0.6.2.tar.gz
  • Upload date:
  • Size: 213.2 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? Yes
  • Uploaded via: twine/6.1.0 CPython/3.13.12

File hashes

Hashes for mmg_toolbox-0.6.2.tar.gz
Algorithm Hash digest
SHA256 1b7bedde279fb4a270fe6d350b274da2ee5125c10d2674e5751810a6d36695fa
MD5 f4acff8445fcf7b025d1b6db4ad3a72c
BLAKE2b-256 c1009f8d4e2ab0c29abbaaf8ebddfc922f4409d6239b107722540bdf908cd668

See more details on using hashes here.

Provenance

The following attestation bundles were made for mmg_toolbox-0.6.2.tar.gz:

Publisher: pypi-publish.yml on DiamondLightSource/mmg_toolbox

Attestations: Values shown here reflect the state when the release was signed and may no longer be current.

File details

Details for the file mmg_toolbox-0.6.2-py3-none-any.whl.

File metadata

  • Download URL: mmg_toolbox-0.6.2-py3-none-any.whl
  • Upload date:
  • Size: 245.1 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? Yes
  • Uploaded via: twine/6.1.0 CPython/3.13.12

File hashes

Hashes for mmg_toolbox-0.6.2-py3-none-any.whl
Algorithm Hash digest
SHA256 e1ad59315a956db3a1c0e6afb126d41a5ce6c0bc37948361800c61feaed2ca89
MD5 217357b7ef428445aee686fd097c41ec
BLAKE2b-256 67c2bc14550fac406aaae682794c162bfccfd825808d8ec8a00bf741bf2f0441

See more details on using hashes here.

Provenance

The following attestation bundles were made for mmg_toolbox-0.6.2-py3-none-any.whl:

Publisher: pypi-publish.yml on DiamondLightSource/mmg_toolbox

Attestations: Values shown here reflect the state when the release was signed and may no longer be current.

Supported by

AWS Cloud computing and Security Sponsor Datadog Monitoring Depot Continuous Integration Fastly CDN Google Download Analytics Pingdom Monitoring Sentry Error logging StatusPage Status page