phaser: The weapon of choice for ptychographic reconstructions
phaser is a fully-featured package for multislice electron ptychography.
See our arXiv paper for more details.
Features
- ePIE, LSQ-MLs, and gradient descent algorithms
numpy,cupy, andjaxbackends.- Single and multislice ptychography
- Multiple incoherent probe modes
- Probe position correction
- Upsampled (sPIE) and segmented ptychography (work in progress)
- Adaptive propagator correction (contributed by M Zhu)
Documentation
Documentation on phaser can be found here: https://hexane360.github.io/phaser/dev/
Documentation is still very much a work in progress, so please feel free to open an issue or email me if you have any questions!
Installation
To install, first clone the repository from github. This can be done from GitHub Desktop, or from the git command line:
$ git clone https://github.com/hexane360/phaser
# enter phaser directory
$ cd phaser
We recommend using a conda environment or Python virtual environment to keep things clean, although this is not mandatory.
phaser supports multiple computational backends. The simplest (and slowest) is numpy. cupy can be used for CUDA-accelerated. jax supports CPU and GPU acceleration, and is the only backend which supports the gradient descent engine.
If you're unsure what engines to use, we recommend installing the jax engine.
If you're using cupy or jax with a GPU, start by following the installation instructions for those packages.
Jax can be installed with or without CUDA support, if you're using CUDA make sure you install the correct version. Currently, Jax does not support CUDA on Windows.
Before moving on to installing phaser, make sure those packages you've installed work:
$ python
>>> import jax
>>> jax.default_backend()
'gpu' # should be 'gpu' on cuda, 'cpu' otherwise
>>> jax.numpy.array([1, 2, 3, 4]) + 1 # test a basic operation
Array([2, 3, 4, 5], dtype=int32)
>>> import cupy
>>> cupy.array([1, 2, 3, 4]) + 1
array([2, 3, 4, 5])
Then, install phaser using pip:
$ python -m pip install -e .
For the jax or cupy backend, or for the optional webserver, install with the corresponding options:
$ python -m pip install -e ".[jax,cupy12,web]" # for the 'jax', 'cupy12', and 'web' options
Depending on your command line, you may need to put double quotes around the options (as shown).
Here are the supported installation options:
jax: For thejaxbackend (required for the gradient descent engine)cupy11:cupyfor CUDA toolkit 11.xcupy12:cupyfor CUDA toolkit 12.xweb: For the web interface
For Optuna hyperoptimization, install it as well:
$ pip install optuna
Running
After installation, the phaser command should be available. Phaser can be run from the command line, or through a job server.
To run a single reconstruction on the command line, call phaser run <file>, where file is the path to a reconstruction plan file.
To run the webserver, call phaser serve. By default, the server serves on https://localhost:5050/, so navigate there in a web browser. The server interface can be used to start workers and schedule reconstruction jobs.
To run a worker, call phaser worker <url>, where url is the URL of a running job server.
Sample data & Examples
Sample data can be downloaded from the following dropbox link: https://www.dropbox.com/scl/fo/txm3k88ubrzvt541v23ir/AL-l_m6VnGlFxzHWZSSc0TA?rlkey=8qxtwnc8cwhpff6jpr5s40y6i&st=x9pbwke0&dl=0
Copy the sample_data directory into the root code folder.
$ curl --output sample_data.zip -L 'https://www.dropbox.com/scl/fo/txm3k88ubrzvt541v23ir/AL-l_m6VnGlFxzHWZSSc0TA?rlkey=8qxtwnc8cwhpff6jpr5s40y6i&st=x9pbwke0&dl=1'
$ unzip sample_data.zip -x / -d sample_data
Sample data includes simulated and experimental MoS2 data, simulated and experimental Si data, and experimental PrScO3 data.
After the data is downloaded, any of the example reconstructions can be run as phaser run examples/mos2_grad.yaml (for example).
Alternatives
Other notable ptychography packages:
fold_slicebranch of PtychoShelvespy4DSTEMPtyLab.m/py/jl- PtyPy
- PtyRAD
Release files for phaserEM 0.3.1
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | |
|---|---|---|---|
| phaserem-0.3.1.tar.gz | 1.5 MB | Details |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| phaserem-0.3.1-py3-none-any.whl | Python 3 | none | any | Details |
Total release size: 3.1 MB
Release files / phaserem-0.3.1.tar.gz
| Download URL | phaserem-0.3.1.tar.gz |
|---|---|
| Size | 1.5 MB |
| Tags | Source |
|
SHA-256 checksum How to use checksums |
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Yes |
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Transparency logRelease files / phaserem-0.3.1-py3-none-any.whl
| Download URL | phaserem-0.3.1-py3-none-any.whl |
|---|---|
| Size | 1.6 MB |
| Tags | Python 3 |
|
SHA-256 checksum How to use checksums |
5f7ef98676eb30328a3840cd0ca9abad05c10a15558320a92b62a7190153a87c
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93df922aeb26702588cff962b4f9cd60775e69fdaee315c143f045001f7b729b
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| Upload date | |
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Uploaded using Trusted Publishing? What is trusted publishing? |
Yes |
| Uploaded via |
twine/7.0.0 CPython/3.13.14
|
Provenance
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PyPI verified that this artifact, at this checksum, originated from the publisher listed below.
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