brainpy | Python implementation of Baffling Recursive Algorithm

by mobiusklein Python Version: v1.4.0 License: Apache-2.0

X-Ray Key Features Code Snippets(1)Community Discussions Vulnerabilities Install Support

kandi X-RAY | brainpy Summary

brainpy is a Python library. brainpy 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 brainpy' or download it from GitHub, PyPI.

A Python implementation of Baffling Recursive Algorithm for Isotopic distributioN calculations (BRAIN). This is a direct translation of Han Hu's root-finding-free approach. Theoretical isotopic patterns appear when you can resolve distinct isotopes of an ion in a mass spectrum. Being able to predict the isotopic pattern of a molecule is useful for interpreting mass spectra to avoid counting the same ion with extra neutrons twice, recognizing the monoisotopic peak of a large multiply charged ion, or for discriminating among different elemental compositions of similar masses. BRAIN takes an elemental composition represented by any Mapping-like Python object and uses it to compute its aggregated isotopic distribution. All isotopic variants of the same number of neutrons are collapsed into a single centroid peak, meaning it does not consider isotopic fine structure.

Support

Quality

Security

License

Reuse

Support

brainpy has a low active ecosystem.

It has 9 star(s) with 7 fork(s). There are 1 watchers for this library.

It had no major release in the last 12 months.

There are 2 open issues and 2 have been closed. On average issues are closed in 7 days. There are 1 open pull requests and 0 closed requests.

It has a neutral sentiment in the developer community.

The latest version of brainpy is v1.4.0

Quality

brainpy has 0 bugs and 0 code smells.

Security

brainpy has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.

brainpy code analysis shows 0 unresolved vulnerabilities.

There are 0 security hotspots that need review.

License

brainpy 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.

Reuse

brainpy 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.

It has 4128 lines of code, 72 functions and 10 files.

It has medium code complexity. Code complexity directly impacts maintainability of the code.

Top functions reviewed by kandi - BETA

kandi has reviewed brainpy and discovered the below as its top functions. This is intended to give you an instant insight into brainpy implemented functionality, and help decide if they suit your requirements.

Set the order of the coefficients
Updates the Newton polynomials
Updates the symmetric polynomial polynomials
Updates the power sum
Updates the polynomial coefficients
Setup sphinx distribution
Check if a command line option exists

Get all kandi verified functions for this library.

brainpy Key Features

No Key Features are available at this moment for brainpy.

brainpy Examples and Code Snippets

brainpy

Python

Lines of Code : 30

License : Permissive (Apache-2.0)

Copy

from brainpy import isotopic_variants

# Generate theoretical isotopic pattern
peptide = {'H': 53, 'C': 34, 'O': 15, 'N': 7}
theoretical_isotopic_cluster = isotopic_variants(peptide, npeaks=5, charge=1)
for peak in theoretical_isotopic_cluster:
    p

Community Discussions

No Community Discussions are available at this moment for brainpy.Refer to stack overflow page for discussions.

Community Discussions, Code Snippets contain sources that include Stack Exchange Network

Vulnerabilities

No vulnerabilities reported

Install brainpy

You can install using 'pip install brainpy' or download it from GitHub, PyPI.
You can use brainpy 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 .

Find more information at: