ETSpy¶

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:

• $ 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¶

• https://hyperspy.org/

• https://astra-toolbox.com/

Documentation last generated: November 6, 2024 at 07:55 PM