Skip to main content

Suite of tools for processing and reconstruction of electron tomography data

Project description

ETSpy

Documentation link PyPI - Python Version Conda versions

ETSpy is a HyperSpy extension package package for the processing, aligment, and reconstruction of electron tomography data from TEM/STEM instruments. Tools are provided for basic tilt series data processing, stack alignment, and reconstruction using the ASTRA Toolbox.

Installation

Depending on your system, there are a few ways to install ETSpy. Due to dependencies that require compilation of binaries and the use of GPU-accelerated libraries, conda is the simplest way to get started. It will auto-detect CUDA-capable GPUs and install the correct version of whatever packages are required.

⚠️ ETSpy requires a Python version >= 3.10 and < 3.13 (3.13 and above are not supported due to dependencies). If installing manually using pip, please ensure you are using a supported version.

Anaconda (Preferred)

Works on Windows, MacOS, and Linux

  • First, ensure you have either Anaconda or Miniconda installed on your system.

  • Run the following command to create a new environment then activate the newly created environment:

    # if you would like your environment to be stored in a specific place, use the "-p <path>" option
    $ conda create -n etspy
    $ conda activate etspy
    
  • With the etspy environment activated, install the ETSpy package from the conda-forge repo:

    (etspy) $ conda install -c conda-forge etspy
    
  • (Alternatively) if you have a GPU and wish to make full use of the GPU-accelerated code, install the etspy-gpu package, which will pull in a few added dependencies to enable these features:

    (etspy) $ conda install -c conda-forge etspy-gpu
    

Optional Jupyter components (higly recommended)

  • To use ETSpy from within a Jupyter Lab/Notebook environment, you will need to "register" the python kernel associated with the etspy conda environment. Run the following after ensuring that environment is activated (with conda activate etspy):

    (etspy) $ conda install -c conda-forge ipykernel
    (etspy) $ python -m ipykernel install --user --name ETSpy
    

    You will then be able to select the "ETSpy" kernel when running Jupyter and creating new notebooks

Using pip

Works on Linux only, with additional prerequisites

Assuming you have the prequisite packages on your system (including the CUDA libraries), ETSpy should be able to be installed with a simple pip command (it is recommended to install ETSpy in a dedicated virtual environment). Pick one of the following options depending on your needs:

On Ubuntu-based systems, the NVIDIA/CUDA dependencies installed via the system-provided `nvidia-cuda-toolkit` apt package may be out of date and incompatible with the ASTRA toolkit. We recommend installing the version directly from NVIDIA.
  • $ pip install etspy
    
  • To use ETSpy in Jupyter interface from within a dedicated virtual environment, installing ipykernel is necessary (as with Anaconda). This can be done by specifying the [jupyter] group when installing ETSpy:

    $ pip install etspy[jupyter]
    
  • To use the cupy accelerated code in ETSpy, you will need to install cupy. This can be done by specifying the [gpu] group when installing ETSpy:

    $ pip install etspy[gpu]
    
  • A shortcut for doing both of the above is to install the [all] target:

    $ pip install etspy[all]
    
  • To register the ETSpy virtual environment as a Jupyter kernel, run the following with the virtual environment enabled:

    (etspy) $ python -m ipykernel install --user --name ETSpy
    

Some dependencies of ETSpy require compilation of C code, meaning using the Anaconda approach above will simplify things greatly if you have trouble with "pure" pip.

Removal

The package can be removed with:

$ pip uninstall etspy

Basic Usage

The majority of the functionality of ETSpy can be accessed by importing the etspy.api module. For example, to load a tilt series dataset into a TomoStack, you could do the following:

import etspy.api as etspy
stack = etspy.load('TiltSeries.mrc')

For more details, see the dedicated documentation, including the example Jupyter notebook and the more detailed API Reference.

Developer documentation

See the developer docs for more information.

Related projects

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

etspy-1.0.0.tar.gz (66.5 MB view details)

Uploaded Source

Built Distribution

etspy-1.0.0-py3-none-any.whl (66.6 MB view details)

Uploaded Python 3

File details

Details for the file etspy-1.0.0.tar.gz.

File metadata

  • Download URL: etspy-1.0.0.tar.gz
  • Upload date:
  • Size: 66.5 MB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: poetry/1.8.4 CPython/3.12.7 Linux/6.6.57-1-lts

File hashes

Hashes for etspy-1.0.0.tar.gz
Algorithm Hash digest
SHA256 5a45e167bc2feb4be97b3cf1c751a023bd36ee12616ff913ca961a1d0cd879ac
MD5 afeaf82f24f63fb14ab1a76117bbbb06
BLAKE2b-256 afb57ffae589631a774ee8d7695423a1e02e7f381f1365fd7e498392e5eecfba

See more details on using hashes here.

File details

Details for the file etspy-1.0.0-py3-none-any.whl.

File metadata

  • Download URL: etspy-1.0.0-py3-none-any.whl
  • Upload date:
  • Size: 66.6 MB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: poetry/1.8.4 CPython/3.12.7 Linux/6.6.57-1-lts

File hashes

Hashes for etspy-1.0.0-py3-none-any.whl
Algorithm Hash digest
SHA256 0c6cd34b027c02b9751c14af77a6f4503df86b422d83c519d14f762183350a52
MD5 14fd0b4dca9b87a33bdd4251dde5d960
BLAKE2b-256 2b508d4491db50db0a1214cb03d41e3ce8d69276c6c419532dc346688d5aa11b

See more details on using hashes here.

Supported by

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