semvec/pypi-packages huggingface dataset:
nanome-rmsd 1.0.1
Nanome Plugin for RMSD alignment
License: MIT
Keywords: virtual-reality,chemistry,python,api,plugin

# Nanome - RMSD Plugin

This python plugin allows for users to select multiple molecules, run an RMSD calculation, and auto-align the structures.

Plugin supported on Windows, Linux, and Mac for Nanome v1.14

### Installation

```sh
$ pip install nanome-rmsd
```

### Usage

To start the plugin:

```sh
$ nanome-rmsd -a <plugin_server_address>
```

### Docker Usage

To run in a Docker container:

```sh
$ cd docker
$ ./build.sh
$ ./deploy.sh -a <plugin_server_address>
```

### License

MIT
nanome-realtime-scoring 0.2.5
Nanome Plugin displaying docking score of complexes in the workspace, in realtime
License: MIT
Keywords: virtual-reality,chemistry,python,api,plugin

# Nanome - Realtime Scoring

Displays the docking score of selected molecules in the workspace, in realtime using DSX. Support for scoring multiple docking results concurrently is experimental, but available through the options menu.

Linux Support Only

### Installation

```sh
$ pip install nanome-realtime-scoring
```

### Usage

To start the plugin:

```sh
$ nanome-realtime-scoring -a plugin_server_address
```

In Nanome:

- Activate Plugin
- In the plugin window, select a receptor and ligands, then start scoring
- Plugin will display a list of all other complexes, with their docking score
- Moving a complex around will update its score

### Docker Usage

To run in a Docker container:

```sh
$ cd docker
$ ./build.sh
$ ./deploy.sh -a <plugin_server_address>
```

### License

MIT
optimiser 0.1.0
Generic implementations of some numerical optimization methods.
License: MIT
Requires Python: >=3.6
Keywords: blackbox_optimization,numerical_optimization,crossentropy

[![Build Status](https://travis-ci.org/Nikolay-Lysenko/optimiser.svg?branch=master)](https://travis-ci.org/Nikolay-Lysenko/optimiser)
[![codecov](https://codecov.io/gh/Nikolay-Lysenko/optimiser/branch/master/graph/badge.svg)](https://codecov.io/gh/Nikolay-Lysenko/optimiser)
[![Maintainability](https://api.codeclimate.com/v1/badges/1ef4e3ac74a4d7ed2291/maintainability)](https://codeclimate.com/github/Nikolay-Lysenko/optimiser/maintainability)
[![PyPI version](https://badge.fury.io/py/optimiser.svg)](https://badge.fury.io/py/optimiser)


# Optimiser

## Overview

This Python package is a library with implementations of some optimization techniques. Current content is shown in the below table:

Method | Implementation
:----: | :------------:
[Cross-Entropy](https://github.com/Nikolay-Lysenko/optimiser/blob/master/docs/crossentropy.pdf) | [optimize_with_crossentropy_method](https://github.com/Nikolay-Lysenko/optimiser/blob/master/optimiser/population/crossentropy.py)

Of course, just one function is not that much...

## Installation

```bash
pip install optimiser
```

## Usage

All functions from the package (especially, those of them that are designed for end users) have a built-in documentation that describes every argument. To read it, look at a docstring or, alternatively, run from Python shell a command like this one:
```python
help(optimize_with_crossentropy_method)
```