MPoL | A Million Points of Light for interferometric imaging | Computer Vision library
kandi X-RAY | MPoL Summary
kandi X-RAY | MPoL Summary
MPoL is a Python library typically used in Artificial Intelligence, Computer Vision applications. MPoL has no bugs, it has no vulnerabilities, it has build file available, it has a Permissive License and it has low support. You can install using 'pip install MPoL' or download it from GitHub, PyPI.
A Million Points of Light are needed to synthesize image cubes from interferometers. Documentation and installation instructions:
A Million Points of Light are needed to synthesize image cubes from interferometers. Documentation and installation instructions:
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Quality
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MPoL has a low active ecosystem.
It has 4 star(s) with 0 fork(s). There are 2 watchers for this library.
It had no major release in the last 12 months.
MPoL has no issues reported. There are no pull requests.
It has a neutral sentiment in the developer community.
The latest version of MPoL is 0.2.0
Quality
MPoL has no bugs reported.
Security
MPoL has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.
License
MPoL is licensed under the MIT License. This license is Permissive.
Permissive licenses have the least restrictions, and you can use them in most projects.
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MPoL releases are available to install and integrate.
Deployable package is available in PyPI.
Build file is available. You can build the component from source.
Installation instructions are not available. Examples and code snippets are available.
Top functions reviewed by kandi - BETA
kandi has reviewed MPoL and discovered the below as its top functions. This is intended to give you an instant insight into MPoL implemented functionality, and help decide if they suit your requirements.
- Calculate the C_real matrices
- Return a vector of x
- Calculate the cffun
- Compute the spheroid of a sphere
- Generate grid of visibilities for each UV grid
- Calculate the H value of a channel
- Calculate the histogram
- Get a modified image
- Return the dirty beam
- Generate a grid of gridded images
- Generate a grid of grid spacings
- The ground residuals
- The ground phase of the cube
- The ground mask
- The ground state of the cube
- The sky cube of the cube
- The mask of the cube
- Train and image
- Convert to pytorch dataset
- Cross validation
- Convenience function for evaluating the model
- Compute the correlation matrix
- Compute the Fourier Gaussian lambda function
- Compute the convolution of a given cube
- Calculate the sky from the sky point
- Get the dirty beam
- Calculate the sum of UV sparsity between the given flux
Get all kandi verified functions for this library.
MPoL Key Features
No Key Features are available at this moment for MPoL.
MPoL Examples and Code Snippets
No Code Snippets are available at this moment for MPoL.
Community Discussions
Trending Discussions on MPoL
QUESTION
How can I do a spatial join with the sf package using st_join()
Asked 2018-Mar-01 at 18:44
Here's a toy example I've been wrestling with
...ANSWER
Answered 2017-May-11 at 19:58I'm also working my way around the features of the sf package, so apologies if this is not correct or there are better ways. I think one problem here is that if building the geometries like in your example you are not obtaining what you think:
Community Discussions, Code Snippets contain sources that include Stack Exchange Network
Vulnerabilities
No vulnerabilities reported
Install MPoL
You can install using 'pip install MPoL' or download it from GitHub, PyPI.
You can use MPoL like any standard Python library. You will need to make sure that you have a development environment consisting of a Python distribution including header files, a compiler, pip, and git installed. Make sure that your pip, setuptools, and wheel are up to date. When using pip it is generally recommended to install packages in a virtual environment to avoid changes to the system.
You can use MPoL like any standard Python library. You will need to make sure that you have a development environment consisting of a Python distribution including header files, a compiler, pip, and git installed. Make sure that your pip, setuptools, and wheel are up to date. When using pip it is generally recommended to install packages in a virtual environment to avoid changes to the system.
Support
For any new features, suggestions and bugs create an issue on GitHub.
If you have any questions check and ask questions on community page Stack Overflow .
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