Metadata-Version: 2.1
Name: nplocate
Version: 0.2.7
Summary: Python tools to locate nano particles from confocal microscope images
Home-page: https://github.com/yangyushi/nplocate
Author: Yushi Yang
Author-email: yangyushi1992@icloud.com
License: UNKNOWN
Description: # Locate Nano Particles
        
        
        ## What is this
        
        `nplocate` is a custom script I wrote to locate very tiny particles from a confocal image. These images often suffered from extreme influences of the [PSF](https://en.wikipedia.org/wiki/Point_spread_function), even after very detailed and completed deconvolution procedures.
        
        To squeeze a bit more information out of these highly distorted data, I wrote this code to effectly "fit" the entire 3D image. This is done in a quite sloopy way. For a perfect fit, please take a look at the very well crafted [peri](https://github.com/peri-source/peri) project.
        
        
        ## The idea
        
        This is not a fully functional particle tracking package like [trackpy](https://github.com/soft-matter/trackpy) or [colloids](https://github.com/MathieuLeocmach/colloids) or [peri](https://github.com/peri-source/peri). Instead, think of `nplocate` as an <big>extension</big> of current tracking packages.
        
        The logic behind the code is quite simple. The arguments are,
        
        1. It is *easy* to find *some* particles, even in a highly distorted image.
        2. If we know the locations of some particles ({**r**}), we can measure their average shape (**S**).
        3. With {**r**} and **S**, we can simulate a "fake image"
        4. We can find previously unfound particles in the difference between the real image and fake image. 
        5. The more particles we have, the merrier.
        
        ## Installing the code
        
        The simplest way is
        
        ```
        pip install nplocate
        ```
        
        You can also download this repository, and use the following command to install the code
        
        ```
        pip install .
        ```
        
        ## Using the code
        
        
        There are some notebooks in the folder `example` that introduced how to use this package, along with [trackpy](https://github.com/soft-matter/trackpy). 
        
        ## Cite the code
        
        ~~Just tell people you used trackpy~~
        
Platform: UNKNOWN
Classifier: Programming Language :: Python
Classifier: Operating System :: OS Independent
Description-Content-Type: text/markdown
