synpivimage 1.0.0a9

Tool to build synthetic Particle Image Velocimetry (PIV) images

synpivimage - A transparent way of generating synthetic PIV images

This tool lets you generate synthetic Particle Image Velocimetry (PIV) images based on methods described in literature (mainly based on "Particle Image Velocimetry: A Practical Guide" by Raffel et al. (https://doi.org/10.1007/978-3-319-68852-7)).

Highlights

• The user has full control over the parameters.
• Data and metadata can be stored in a single HDF5 file or classically in TIF files.
• The metadata (camera and laser settings) can be stored in a separate JSON-LD file, which adheres to the state of the art way of storing metadata, allowing for easy integration into any other software or database.

Installation

Manual installation

Clone the repository

git clone https://github.com/matthiasprobst/synpivimage

Then navigate into the repo directory and install the package:

cd synpivimage/
pip install .

For development adjust the installation to:

pip install -e .

Other installation options: For running tests:

pip install .[test]

For using the GUI (experimentally at this stage!!! see gui doc section):

pip install .[gui]

For installing everything:

pip install .[all]

Via pypi

Not yet available

Documentation

A comprehensive documentation can be found here.

Minimal example:

import numpy as np

import synpivimage

cam = synpivimage.Camera(
    nx=256,
    ny=256,
    bit_depth=16,
    qe=1,
    sensitivity=1,
    baseline_noise=50,
    dark_noise=10,
    shot_noise=False,
    fill_ratio_x=1.0,
    fill_ratio_y=1.0,
    particle_image_diameter=4  # px
)

laser = synpivimage.Laser(
    width=0.25,
    shape_factor=2
)

n = 100
particles = synpivimage.Particles(
    x=np.random.uniform(-3, cam.nx - 1, n),
    y=np.random.uniform(-4, cam.ny - 1, n),
    z=np.zeros(n),
    size=np.ones(n) * 2,
)

imgA, partA = synpivimage.take_image(laser,
                                     cam,
                                     particles,
                                     particle_peak_count=1000)

displaced_particles = partA.displace(dx=2.1, dy=3.4)

imgB, partB = synpivimage.take_image(laser,
                                     cam,
                                     displaced_particles,
                                     particle_peak_count=1000)

with synpivimage.Imwriter(case_name="test_case",
                          camera=cam,
                          laser=laser) as iw:
    iw.writeA(0, imgA, partA)
    iw.writeB(0, imgB, partB)

with synpivimage.HDF5Writer(filename='data.hdf',
                            n_images=1,
                            camera=cam,
                            laser=laser) as hw:
    hw.writeA(0, imgA, partA)
    hw.writeB(0, imgB, partB)

GUI

Is experimental and more for demonstrating and debugging purposes.

Go to synpivimage/gui and run python core.py to start the GUI.

Developers

Testing

Call the following inside the package directory to run the tests (with coverage)

pytest --cov=synpivimage --cov-report html

Contributing

Contributions are welcome! Please open an issue or a pull request.

License

This project is licensed under the MIT License.