path: root/python-swift-sim.spec

%global _empty_manifest_terminate_build 0
Name:		python-swift-sim
Version:	1.1.0
Release:	1
Summary:	A Python/Javascript Robot Simulator and Visualiser
License:	MIT License  Copyright (c) 2020 jhavl  Permission is hereby granted, free of charge, to any person obtaining a copy of this software and associated documentation files (the "Software"), to deal in the Software without restriction, including without limitation the rights to use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of the Software, and to permit persons to whom the Software is furnished to do so, subject to the following conditions:  The above copyright notice and this permission notice shall be included in all copies or substantial portions of the Software.  THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE. 
URL:		https://pypi.org/project/swift-sim/
Source0:	https://mirrors.nju.edu.cn/pypi/web/packages/4a/4e/a3babcf2aef18e5a2c1968c442b2255d1c63f521199f81c6aa2bba5a5644/swift-sim-1.1.0.tar.gz

Requires:	python3-numpy
Requires:	python3-spatialgeometry
Requires:	python3-websockets
Requires:	python3-black
Requires:	python3-roboticstoolbox-python
Requires:	python3-swift-sim
Requires:	python3-pytest
Requires:	python3-pytest-cov
Requires:	python3-flake8
Requires:	python3-pyyaml
Requires:	python3-sphinx
Requires:	python3-sphinx-rtd-theme
Requires:	python3-sphinx-autorun
Requires:	python3-ipython
Requires:	python3-notebook
Requires:	python3-aiortc
Requires:	python3-opencv-python

%description
# Swift

[![A Python Robotics Package](https://raw.githubusercontent.com/petercorke/robotics-toolbox-python/master/.github/svg/py_collection.min.svg)](https://github.com/petercorke/robotics-toolbox-python)
[![QUT Centre for Robotics Open Source](https://github.com/qcr/qcr.github.io/raw/master/misc/badge.svg)](https://qcr.github.io)

[![PyPI version](https://badge.fury.io/py/swift-sim.svg)](https://badge.fury.io/py/swift-sim)
[![PyPI - Python Version](https://img.shields.io/pypi/pyversions/swift-sim)](https://img.shields.io/pypi/pyversions/swift-sim)
[![License: MIT](https://img.shields.io/badge/License-MIT-yellow.svg)](https://opensource.org/licenses/MIT)

Swift is a light-weight browser-based simulator built on top of the [Robotics Toolbox for Python](https://github.com/petercorke/robotics-toolbox-python). This simulator provides robotics-specific functionality for rapid prototyping of algorithms, research, and education. Built using Python and Javascript, Swift is cross-platform (Linux, MacOS, and Windows) while also leveraging the ubiquity and support of these languages.

Through the [Robotics Toolbox for Python](https://github.com/petercorke/robotics-toolbox-python), Swift can visualise over 30 supplied robot models: well-known contemporary robots from Franka-Emika, Kinova, Universal Robotics, Rethink as well as classical robots such as the Puma 560 and the Stanford arm. Swift is under development and will support mobile robots in the future.

Swift provides:

  * visualisation of mesh objects (Collada and STL files) and primitive shapes;
  * robot visualisation and simulation;
  * recording and saving a video of the simulation;
  * source code which can be read for learning and teaching;

## Installing
### Using pip

Swift is designed to be controlled through the [Robotics Toolbox for Python](https://github.com/petercorke/robotics-toolbox-python). By installing the toolbox through PyPI, swift is installed as a dependency

```shell script
pip3 install roboticstoolbox-python
```

Otherwise, Swift can be install by

```shell script
pip3 install swift-sim
```

Available options are:

- `nb` provides the ability for Swift to be embedded within a Jupyter Notebook
- `vision` implements an RTC communication strategy allowing for visual feedback from Swift and allows Swift to be run on Google Colab

Put the options in a comma-separated list like

```shell script
pip3 install swift-sim[optionlist]
```

### From GitHub

To install the latest version from GitHub

```shell script
git clone https://github.com/jhavl/swift.git
cd swift
pip3 install -e .
```

## Code Examples

### Robot Plot
We will load a model of the Franka-Emika Panda robot and plot it. We set the joint angles of the robot into the ready joint configuration qr.

```python
import roboticstoolbox as rp

panda = rp.models.Panda()
panda.plot(q=panda.qr)
```
<p align="center">
 <img src="https://github.com/jhavl/swift/blob/master/.github/figures/panda.png">
</p>

### Resolved-Rate Motion Control
We will load a model of the Franka-Emika Panda robot and make it travel towards a goal pose defined by the variable Tep.

```python
import roboticstoolbox as rtb
import spatialmath as sm
import numpy as np
from swift import Swift


# Make and instance of the Swift simulator and open it
env = Swift()
env.launch(realtime=True)

# Make a panda model and set its joint angles to the ready joint configuration
panda = rtb.models.Panda()
panda.q = panda.qr

# Set a desired and effector pose an an offset from the current end-effector pose
Tep = panda.fkine(panda.q) * sm.SE3.Tx(0.2) * sm.SE3.Ty(0.2) * sm.SE3.Tz(0.45)

# Add the robot to the simulator
env.add(panda)

# Simulate the robot while it has not arrived at the goal
arrived = False
while not arrived:

    # Work out the required end-effector velocity to go towards the goal
    v, arrived = rtb.p_servo(panda.fkine(panda.q), Tep, 1)
    
    # Set the Panda's joint velocities
    panda.qd = np.linalg.pinv(panda.jacobe(panda.q)) @ v
    
    # Step the simulator by 50 milliseconds
    env.step(0.05)
```
<p align="center">
 <img src="./.github/figures/panda.gif">
</p>

### Embed within a Jupyter Notebook
To embed within a Jupyter Notebook Cell, use the `browser="notebook"` option when launching the simulator.

```python
# Try this example within a Jupyter Notebook Cell!
import roboticstoolbox as rtb
import spatialmath as sm
import numpy as np
from swift import Swift

# Make and instance of the Swift simulator and open it
env = Swift()
env.launch(realtime=True, browser="notebook")

# Make a panda model and set its joint angles to the ready joint configuration
panda = rtb.models.Panda()
panda.q = panda.qr

# Set a desired and effector pose an an offset from the current end-effector pose
Tep = panda.fkine(panda.q) * sm.SE3.Tx(0.2) * sm.SE3.Ty(0.2) * sm.SE3.Tz(0.45)

# Add the robot to the simulator
env.add(panda)

# Simulate the robot while it has not arrived at the goal
arrived = False
while not arrived:

    # Work out the required end-effector velocity to go towards the goal
    v, arrived = rtb.p_servo(panda.fkine(panda.q), Tep, 1)
    
    # Set the Panda's joint velocities
    panda.qd = np.linalg.pinv(panda.jacobe(panda.q)) @ v
    
    # Step the simulator by 50 milliseconds
    env.step(0.05)
```


%package -n python3-swift-sim
Summary:	A Python/Javascript Robot Simulator and Visualiser
Provides:	python-swift-sim
BuildRequires:	python3-devel
BuildRequires:	python3-setuptools
BuildRequires:	python3-pip
BuildRequires:	python3-cffi
BuildRequires:	gcc
BuildRequires:	gdb
%description -n python3-swift-sim
# Swift

[![A Python Robotics Package](https://raw.githubusercontent.com/petercorke/robotics-toolbox-python/master/.github/svg/py_collection.min.svg)](https://github.com/petercorke/robotics-toolbox-python)
[![QUT Centre for Robotics Open Source](https://github.com/qcr/qcr.github.io/raw/master/misc/badge.svg)](https://qcr.github.io)

[![PyPI version](https://badge.fury.io/py/swift-sim.svg)](https://badge.fury.io/py/swift-sim)
[![PyPI - Python Version](https://img.shields.io/pypi/pyversions/swift-sim)](https://img.shields.io/pypi/pyversions/swift-sim)
[![License: MIT](https://img.shields.io/badge/License-MIT-yellow.svg)](https://opensource.org/licenses/MIT)

Swift is a light-weight browser-based simulator built on top of the [Robotics Toolbox for Python](https://github.com/petercorke/robotics-toolbox-python). This simulator provides robotics-specific functionality for rapid prototyping of algorithms, research, and education. Built using Python and Javascript, Swift is cross-platform (Linux, MacOS, and Windows) while also leveraging the ubiquity and support of these languages.

Through the [Robotics Toolbox for Python](https://github.com/petercorke/robotics-toolbox-python), Swift can visualise over 30 supplied robot models: well-known contemporary robots from Franka-Emika, Kinova, Universal Robotics, Rethink as well as classical robots such as the Puma 560 and the Stanford arm. Swift is under development and will support mobile robots in the future.

Swift provides:

  * visualisation of mesh objects (Collada and STL files) and primitive shapes;
  * robot visualisation and simulation;
  * recording and saving a video of the simulation;
  * source code which can be read for learning and teaching;

## Installing
### Using pip

Swift is designed to be controlled through the [Robotics Toolbox for Python](https://github.com/petercorke/robotics-toolbox-python). By installing the toolbox through PyPI, swift is installed as a dependency

```shell script
pip3 install roboticstoolbox-python
```

Otherwise, Swift can be install by

```shell script
pip3 install swift-sim
```

Available options are:

- `nb` provides the ability for Swift to be embedded within a Jupyter Notebook
- `vision` implements an RTC communication strategy allowing for visual feedback from Swift and allows Swift to be run on Google Colab

Put the options in a comma-separated list like

```shell script
pip3 install swift-sim[optionlist]
```

### From GitHub

To install the latest version from GitHub

```shell script
git clone https://github.com/jhavl/swift.git
cd swift
pip3 install -e .
```

## Code Examples

### Robot Plot
We will load a model of the Franka-Emika Panda robot and plot it. We set the joint angles of the robot into the ready joint configuration qr.

```python
import roboticstoolbox as rp

panda = rp.models.Panda()
panda.plot(q=panda.qr)
```
<p align="center">
 <img src="https://github.com/jhavl/swift/blob/master/.github/figures/panda.png">
</p>

### Resolved-Rate Motion Control
We will load a model of the Franka-Emika Panda robot and make it travel towards a goal pose defined by the variable Tep.

```python
import roboticstoolbox as rtb
import spatialmath as sm
import numpy as np
from swift import Swift


# Make and instance of the Swift simulator and open it
env = Swift()
env.launch(realtime=True)

# Make a panda model and set its joint angles to the ready joint configuration
panda = rtb.models.Panda()
panda.q = panda.qr

# Set a desired and effector pose an an offset from the current end-effector pose
Tep = panda.fkine(panda.q) * sm.SE3.Tx(0.2) * sm.SE3.Ty(0.2) * sm.SE3.Tz(0.45)

# Add the robot to the simulator
env.add(panda)

# Simulate the robot while it has not arrived at the goal
arrived = False
while not arrived:

    # Work out the required end-effector velocity to go towards the goal
    v, arrived = rtb.p_servo(panda.fkine(panda.q), Tep, 1)
    
    # Set the Panda's joint velocities
    panda.qd = np.linalg.pinv(panda.jacobe(panda.q)) @ v
    
    # Step the simulator by 50 milliseconds
    env.step(0.05)
```
<p align="center">
 <img src="./.github/figures/panda.gif">
</p>

### Embed within a Jupyter Notebook
To embed within a Jupyter Notebook Cell, use the `browser="notebook"` option when launching the simulator.

```python
# Try this example within a Jupyter Notebook Cell!
import roboticstoolbox as rtb
import spatialmath as sm
import numpy as np
from swift import Swift

# Make and instance of the Swift simulator and open it
env = Swift()
env.launch(realtime=True, browser="notebook")

# Make a panda model and set its joint angles to the ready joint configuration
panda = rtb.models.Panda()
panda.q = panda.qr

# Set a desired and effector pose an an offset from the current end-effector pose
Tep = panda.fkine(panda.q) * sm.SE3.Tx(0.2) * sm.SE3.Ty(0.2) * sm.SE3.Tz(0.45)

# Add the robot to the simulator
env.add(panda)

# Simulate the robot while it has not arrived at the goal
arrived = False
while not arrived:

    # Work out the required end-effector velocity to go towards the goal
    v, arrived = rtb.p_servo(panda.fkine(panda.q), Tep, 1)
    
    # Set the Panda's joint velocities
    panda.qd = np.linalg.pinv(panda.jacobe(panda.q)) @ v
    
    # Step the simulator by 50 milliseconds
    env.step(0.05)
```


%package help
Summary:	Development documents and examples for swift-sim
Provides:	python3-swift-sim-doc
%description help
# Swift

[![A Python Robotics Package](https://raw.githubusercontent.com/petercorke/robotics-toolbox-python/master/.github/svg/py_collection.min.svg)](https://github.com/petercorke/robotics-toolbox-python)
[![QUT Centre for Robotics Open Source](https://github.com/qcr/qcr.github.io/raw/master/misc/badge.svg)](https://qcr.github.io)

[![PyPI version](https://badge.fury.io/py/swift-sim.svg)](https://badge.fury.io/py/swift-sim)
[![PyPI - Python Version](https://img.shields.io/pypi/pyversions/swift-sim)](https://img.shields.io/pypi/pyversions/swift-sim)
[![License: MIT](https://img.shields.io/badge/License-MIT-yellow.svg)](https://opensource.org/licenses/MIT)

Swift is a light-weight browser-based simulator built on top of the [Robotics Toolbox for Python](https://github.com/petercorke/robotics-toolbox-python). This simulator provides robotics-specific functionality for rapid prototyping of algorithms, research, and education. Built using Python and Javascript, Swift is cross-platform (Linux, MacOS, and Windows) while also leveraging the ubiquity and support of these languages.

Through the [Robotics Toolbox for Python](https://github.com/petercorke/robotics-toolbox-python), Swift can visualise over 30 supplied robot models: well-known contemporary robots from Franka-Emika, Kinova, Universal Robotics, Rethink as well as classical robots such as the Puma 560 and the Stanford arm. Swift is under development and will support mobile robots in the future.

Swift provides:

  * visualisation of mesh objects (Collada and STL files) and primitive shapes;
  * robot visualisation and simulation;
  * recording and saving a video of the simulation;
  * source code which can be read for learning and teaching;

## Installing
### Using pip

Swift is designed to be controlled through the [Robotics Toolbox for Python](https://github.com/petercorke/robotics-toolbox-python). By installing the toolbox through PyPI, swift is installed as a dependency

```shell script
pip3 install roboticstoolbox-python
```

Otherwise, Swift can be install by

```shell script
pip3 install swift-sim
```

Available options are:

- `nb` provides the ability for Swift to be embedded within a Jupyter Notebook
- `vision` implements an RTC communication strategy allowing for visual feedback from Swift and allows Swift to be run on Google Colab

Put the options in a comma-separated list like

```shell script
pip3 install swift-sim[optionlist]
```

### From GitHub

To install the latest version from GitHub

```shell script
git clone https://github.com/jhavl/swift.git
cd swift
pip3 install -e .
```

## Code Examples

### Robot Plot
We will load a model of the Franka-Emika Panda robot and plot it. We set the joint angles of the robot into the ready joint configuration qr.

```python
import roboticstoolbox as rp

panda = rp.models.Panda()
panda.plot(q=panda.qr)
```
<p align="center">
 <img src="https://github.com/jhavl/swift/blob/master/.github/figures/panda.png">
</p>

### Resolved-Rate Motion Control
We will load a model of the Franka-Emika Panda robot and make it travel towards a goal pose defined by the variable Tep.

```python
import roboticstoolbox as rtb
import spatialmath as sm
import numpy as np
from swift import Swift


# Make and instance of the Swift simulator and open it
env = Swift()
env.launch(realtime=True)

# Make a panda model and set its joint angles to the ready joint configuration
panda = rtb.models.Panda()
panda.q = panda.qr

# Set a desired and effector pose an an offset from the current end-effector pose
Tep = panda.fkine(panda.q) * sm.SE3.Tx(0.2) * sm.SE3.Ty(0.2) * sm.SE3.Tz(0.45)

# Add the robot to the simulator
env.add(panda)

# Simulate the robot while it has not arrived at the goal
arrived = False
while not arrived:

    # Work out the required end-effector velocity to go towards the goal
    v, arrived = rtb.p_servo(panda.fkine(panda.q), Tep, 1)
    
    # Set the Panda's joint velocities
    panda.qd = np.linalg.pinv(panda.jacobe(panda.q)) @ v
    
    # Step the simulator by 50 milliseconds
    env.step(0.05)
```
<p align="center">
 <img src="./.github/figures/panda.gif">
</p>

### Embed within a Jupyter Notebook
To embed within a Jupyter Notebook Cell, use the `browser="notebook"` option when launching the simulator.

```python
# Try this example within a Jupyter Notebook Cell!
import roboticstoolbox as rtb
import spatialmath as sm
import numpy as np
from swift import Swift

# Make and instance of the Swift simulator and open it
env = Swift()
env.launch(realtime=True, browser="notebook")

# Make a panda model and set its joint angles to the ready joint configuration
panda = rtb.models.Panda()
panda.q = panda.qr

# Set a desired and effector pose an an offset from the current end-effector pose
Tep = panda.fkine(panda.q) * sm.SE3.Tx(0.2) * sm.SE3.Ty(0.2) * sm.SE3.Tz(0.45)

# Add the robot to the simulator
env.add(panda)

# Simulate the robot while it has not arrived at the goal
arrived = False
while not arrived:

    # Work out the required end-effector velocity to go towards the goal
    v, arrived = rtb.p_servo(panda.fkine(panda.q), Tep, 1)
    
    # Set the Panda's joint velocities
    panda.qd = np.linalg.pinv(panda.jacobe(panda.q)) @ v
    
    # Step the simulator by 50 milliseconds
    env.step(0.05)
```


%prep
%autosetup -n swift-sim-1.1.0

%build
%py3_build

%install
%py3_install
install -d -m755 %{buildroot}/%{_pkgdocdir}
if [ -d doc ]; then cp -arf doc %{buildroot}/%{_pkgdocdir}; fi
if [ -d docs ]; then cp -arf docs %{buildroot}/%{_pkgdocdir}; fi
if [ -d example ]; then cp -arf example %{buildroot}/%{_pkgdocdir}; fi
if [ -d examples ]; then cp -arf examples %{buildroot}/%{_pkgdocdir}; fi
pushd %{buildroot}
if [ -d usr/lib ]; then
	find usr/lib -type f -printf "/%h/%f\n" >> filelist.lst
fi
if [ -d usr/lib64 ]; then
	find usr/lib64 -type f -printf "/%h/%f\n" >> filelist.lst
fi
if [ -d usr/bin ]; then
	find usr/bin -type f -printf "/%h/%f\n" >> filelist.lst
fi
if [ -d usr/sbin ]; then
	find usr/sbin -type f -printf "/%h/%f\n" >> filelist.lst
fi
touch doclist.lst
if [ -d usr/share/man ]; then
	find usr/share/man -type f -printf "/%h/%f.gz\n" >> doclist.lst
fi
popd
mv %{buildroot}/filelist.lst .
mv %{buildroot}/doclist.lst .

%files -n python3-swift-sim -f filelist.lst
%dir %{python3_sitearch}/*

%files help -f doclist.lst
%{_docdir}/*

%changelog
* Tue May 30 2023 Python_Bot <Python_Bot@openeuler.org> - 1.1.0-1
- Package Spec generated