cryosparc-tools 4.1.2

Toolkit for interfacing with CryoSPARC

cryosparc-tools

Toolkit for interfacing with CryoSPARC. Read the documentation at tools.cryosparc.com

Development

Prerequisites

• Git and Git LFS
• Python >= 3.7
• Miniconda3
• C compiler such as GCC or Clang

Set Up

1. Clone this repository

   git clone https://github.com/cryoem-uoft/cryosparc-tools.git
   cd cryosparc-tools
   git lfs pull
   

2. Create and activate a conda environment named "tools" with the desired python version. See the Run Example Notebooks section to install an environment

   conda create -n tools python=3.7 -c conda-forge
   conda activate tools
   

3. Install dev dependencies and build native modules

   pip install -U pip wheel
   pip install -e ".[dev]"
   

Re-compile native module

Recompile native modules after making changes to C code:

make

Build Packages for Publishing

Install build dependencies

pip install -e ".[build]"

Run the build

python -m build

Packages for the current architecture and python version are added to the dist/ directory.

Build Documentation

Documentation is located in the docs directory and is powered by Jupyter Book.

To build the docs, install build dependencies

pip install -e ".[build]"

Then run Jupyter Book

jupyter-book build docs

Site will be be built into the docs/_build/html directory.

Note: Jupyter Book is not configured to re-run example notebooks upon build since the notebooks require an active CryoSPARC instance to run.

See the Run Example Notebooks section for instructions on how to run the notebooks.

Inline source documentation is compiled to HTML via Sphinx and uses Google Style Python docstrings.

Run Example Notebooks

The Jupyter notebooks in the example documentation require additional dependencies to execute, including the following system configuration:

• Nvidia GPU and driver
• Miniconda installed
• CryoSPARC running at localhost:40000 or cryoem5:40000 (can alias cryoem5 to localhost)

Clean previous build artefacts:

make clean

Install dependencies into a new conda environment:

conda create -n cryosparc-tools-example -c conda-forge \
    python=3 numpy==1.18.5 \
    pyqt=5 libtiff wxPython=4.1.1 adwaita-icon-theme
conda activate cryosparc-tools-example
pip install -U pip
pip install nvidia-pyindex matplotlib">=3.4,<3.5" pandas==1.1.4 notebook
pip install "cryolo[c11]"
pip install -e ".[build]"

Run the notebook server with the following environment variables:

• CRYOSPARC_LICENSE_ID with Structura-issued CryoSPARC license
• CRYOSPARC_EMAIL with a CryoSPARC user account email
• CRYOSPARC_PASSWORD with a CryoSPARC user account password

You may also need to include LD_LIBRARY_PATH which includes the location of CUDA Toolkit and cuDNN runtime libraries (e.g., ~/miniconda3/envs/tools/lib/python3.8/site-packages/nvidia/*/lib).

CRYOSPARC_LICENSE_ID="xxxxxxxx-xxxx-xxxx-xxxxxxxxxxxx" \
CRYOSPARC_EMAIL="[e-mail]" \
CRYOSPARC_PASSWORD="password123" \
jupyter notebook

Find examples in docs/examples directory

License

cryosparc-tools is licensed under the BSD-3-Clause.