Install

Current source

Python 3.11 or newer is required. Record git rev-parse HEAD with your results; the version field alone does not identify a development checkout.

Start with Python, then install the backend for your computer. The same public API provides loading, virtual detectors, and SSB; supported options differ by backend. Use the current source for ANS loading and the latest SSB features:

Apple Silicon Mac — MPS/Metal

git clone https://github.com/bobleesj/quantem.gpu.git
cd quantem.gpu
python -m pip install -e ".[mps]"

NVIDIA GPU — CUDA (Linux)

git clone https://github.com/bobleesj/quantem.gpu.git
cd quantem.gpu
python -m pip install -e ".[cuda]"

The Mac SSB backend uses MLX and Metal. The NumPy-like indexing interface, such as data[10, 12], returns PyTorch tensors, so quantem.gpu installs PyTorch 2.3 or newer. To use a particular CUDA build of PyTorch, install it before quantem.gpu. For the static plotting examples, also install QuantEM:

python -m pip install quantem

Check accelerator availability before running the indexing examples:

import torch

print(torch.backends.mps.is_available())  # Apple Silicon
print(torch.cuda.is_available())          # NVIDIA CUDA

Add dm for DM3/DM4 input (".[mps,dm]" or ".[cuda,dm]") and movie for GIF and MP4 export (".[mps,movie]" or ".[cuda,movie]"). Save git rev-parse HEAD with your results. The source version field still reads rc8, but its features have advanced beyond that published candidate.

Verify the install

import importlib.metadata as md
import quantem.gpu as qgpu

print(md.version("quantem.gpu"))
print(qgpu.__version__)
print(qgpu.device.detect())

The distribution version and qgpu.__version__ should match.

Record the printed version, device, and git rev-parse HEAD with your results. Continue with From acquisition to images.

For a historical environment, see the rc8 installation record.