pdfflow | parton distribution function interpolation library
kandi X-RAY | pdfflow Summary
kandi X-RAY | pdfflow Summary
pdfflow is a Python library. pdfflow 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 pdfflow' or download it from GitHub, PyPI.
PDFFlow is parton distribution function interpolation library written in Python and based on the TensorFlow framework. It is developed with a focus on speed and efficiency, enabling researchers to perform very expensive calculation as quick and easy as possible. The key features of PDFFlow is the possibility to query PDF sets on GPU accelerators.
PDFFlow is parton distribution function interpolation library written in Python and based on the TensorFlow framework. It is developed with a focus on speed and efficiency, enabling researchers to perform very expensive calculation as quick and easy as possible. The key features of PDFFlow is the possibility to query PDF sets on GPU accelerators.
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Quality
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Support
pdfflow has a low active ecosystem.
It has 6 star(s) with 0 fork(s). There are 3 watchers for this library.
There were 1 major release(s) in the last 12 months.
There are 2 open issues and 21 have been closed. On average issues are closed in 92 days. There are 1 open pull requests and 0 closed requests.
It has a neutral sentiment in the developer community.
The latest version of pdfflow is 1.2.2
Quality
pdfflow has no bugs reported.
Security
pdfflow has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.
License
pdfflow is licensed under the Apache-2.0 License. This license is Permissive.
Permissive licenses have the least restrictions, and you can use them in most projects.
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pdfflow 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, examples and code snippets are available.
Top functions reviewed by kandi - BETA
kandi has reviewed pdfflow and discovered the below as its top functions. This is intended to give you an instant insight into pdfflow implemented functionality, and help decide if they suit your requirements.
- Compute the last subgrid of the last squares region
- Convert cond1 and cond2 to the corresponding index
- Extrapolate linear interpolation
- Extrapolate highq2 extrapolation
- Vfh_production
- Compute the z - value of the wavefunction
- Map 3x3 cartesian spins from 3 to p3
- XFQ2
- Calculate time series
- Compute the tensorflow op
- Builds a tf graph
- Compute the first subgrid
- A cubic cubic interpolation
- Extrapolate lowQ2 extrapolation
- Produce a VFH production
- Sample from 2 to2to3 to2to3
- XFQ2 function
- Compute the tensorflow operator
- Compare the quality of the alphas in a pdf
- Set ticks on a given axis
- Create PDF files
- Map two cartesian spins to another
- Format a floating point number
- Generate phase - phase wavefunction from a 2D array
- R Return the z - axis z - axis
- Compute the production of a 2d array
- Trace the extrapolation region
- Set ticks
- Calculate alphas
- Calculate the alphas_interpolate
- Compute the XFQ2
- Calculate alphas first subgrid
- Construct a subgrid of the inner subgrid
Get all kandi verified functions for this library.
pdfflow Key Features
No Key Features are available at this moment for pdfflow.
pdfflow Examples and Code Snippets
PDFFlow,Minimal Working Example
Python
Lines of Code : 19License : Strong Copyleft (GPL-3.0)
Lines of Code : 19License : Strong Copyleft (GPL-3.0)
Copyfrom pdfflow import mkPDFs
import tensorflow as tf
pdf = mkPDFs("NNPDF31_nnlo_as_0118", [0,2])
x = tf.random.uniform([10], dtype=tf.float64)
q2 = tf.random.uniform([10], dtype=tf.float64)*20 + 10
pid = tf.cast([-1,21,1], dtype=tf.int32)
result = pd PDFFlow,Installation
PythonLines of Code : 3License : Strong Copyleft (GPL-3.0)
Lines of Code : 3License : Strong Copyleft (GPL-3.0)Copypython3 -m pip install pdfflow
python setup.py install
python setup.py develop
Community Discussions
No Community Discussions are available at this moment for pdfflow.Refer to stack overflow page for discussions.
Community Discussions, Code Snippets contain sources that include Stack Exchange Network
Vulnerabilities
No vulnerabilities reported
Install pdfflow
The package can be installed with pip:.
Support
The documentation for PDFFlow can be consulted in the readthedocs page: pdfflow.readthedocs.io.
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