Installation

Installation#

quantem.widget is currently published on TestPyPI (pre-release). Install it from there, with PyPI as the extra index so its dependencies (numpy, torch, …) resolve normally:

pip install -i https://test.pypi.org/simple/ \
    --extra-index-url https://pypi.org/simple/ \
    quantem.widget

That works on every backend; the widget picks the fastest path it finds at runtime. Requires Python 3.11 or newer.

To upload or download shared datasets through the Hugging Face helpers (quantem.widget.io.upload / download — see Load and I/O), add the [hub] extra, which pulls in quantem.data:

pip install -i https://test.pypi.org/simple/ \
    --extra-index-url https://pypi.org/simple/ \
    "quantem.widget[hub]"

Google Colab#

Each tutorial notebook can open directly in Colab from the badge at the top of the notebook. Colab uses the same files that build these docs, so there is no separate Colab copy to maintain.

If the package is not already available in the Colab runtime, run this once near the top of the notebook:

%pip install -i https://test.pypi.org/simple/ \
    --extra-index-url https://pypi.org/simple/ \
    quantem.widget

Common entry points:

Tutorial

Colab

Source notebook

Example Data

Open in Colab

GitHub

Show2D

Open in Colab

GitHub

Show3D

Open in Colab

GitHub

Show3DSlices

Open in Colab

GitHub

Show4DSTEM

Open in Colab

GitHub

ShowEDS

Open in Colab

GitHub

ShowDiffraction

Open in Colab

GitHub

ShowFolder

Open in Colab

GitHub

HTML and file export

Open in Colab

GitHub

Backends#

  • NVIDIA CUDA - the universal Torch viewer runs on GPU. The integer-reduction detector path uses CuPy. We do not pin a CuPy wheel (a fixed cuda12x/cuda13x would collide with one your environment already ships); a real CUDA workflow already has the matching CuPy installed.

  • Apple Silicon (Metal / MPS) - a dedicated raw-Metal viewer powers Show4DSTEM on the MacBook, with full-resolution CBED and a fast virtual-image path. The tiny pyobjc-framework-Metal wheel installs automatically on macOS.

  • CPU - everything still runs, just slower. This is the path used to build these docs.

Verify#

import quantem.widget as qw
print(qw.__version__)
print(qw.__all__)   # public widgets, load(), DPC helpers, detector helpers