%global _empty_manifest_terminate_build 0 Name: python-AeroSandbox Version: 4.0.6 Release: 1 Summary: AeroSandbox is a Python package for design optimization of engineered systems such as aircraft. License: MIT License URL: https://peterdsharpe.github.io/AeroSandbox/ Source0: https://mirrors.nju.edu.cn/pypi/web/packages/fa/df/7e23adac57cb649d8b019d4e82e14f2b24a204c4281bdc4b5406bc9c5719/AeroSandbox-4.0.6.tar.gz BuildArch: noarch Requires: python3-numpy Requires: python3-scipy Requires: python3-casadi Requires: python3-pandas Requires: python3-matplotlib Requires: python3-seaborn Requires: python3-tqdm Requires: python3-sortedcontainers Requires: python3-sphinx Requires: python3-furo Requires: python3-sphinx-autoapi Requires: python3-plotly Requires: python3-pyvista Requires: python3-ipyvtklink Requires: python3-trimesh Requires: python3-sympy Requires: python3-cadquery Requires: python3-pytest Requires: python3-nbval %description ### Gallery Use AeroSandbox to design and optimize entire aircraft:

Feather (an ultra-lightweight 1-meter-class RC motor glider)

SEAWAY-Mini (a solar-electric, 13' wingspan seaplane)

Use AeroSandbox to support real-world aircraft development programs, all the way from your very first sketch to your first-flight and even beyond:

Initial concept sketches + sizing of Dawn (a solar-electric airplane for climate science research) in AeroSandbox, Spring 2020

Dawn (later renamed SACOS) in first flight, Fall 2022

(Thanks to so, so many wonderful people!)

Use AeroSandbox to explore counterintuitive, complicated design tradeoffs, all at the earliest stages of conceptual design *where these insights make the most difference*:

Exploring how big a solar airplane needs to be to fly, as a function of seasonality and latitude

Exploring how the mission range of Firefly, a Mach 0.8 rocket drone, changes if we add an altitude limit, simultaneously optimizing aircraft design and trajectories

Use AeroSandbox as a pure aerodynamics toolkit:

VLM simulation of a glider, aileron deflections of +-30°

Aerodynamic shape optimization of a wing planform, using an arbitrary objective and constraints

Among many other discplines:

Structural optimization of a composite tube spar	Electric motor analysis for propeller matching
Tools to analyze unconventional propulsion (e.g., LH2)	Detailed weights estimation for aircraft ranging from micro-UAVs to airliners

Easily interface AeroSandbox with all your favorite tools:

Other conceptual design tools (AVL, XFLR5, XFoil, ASWING, MSES, etc.)

CAD tools via STEP export (SolidWorks, Fusion 360, etc.)

(STL, OBJ, etc. supported too)

User-provided models + code (for custom aerodynamics, structures, propulsion, or anything else - e.g., for optimizing flight through a probabilistic wind field, shown below)

Or, throw all the airplane-design-specific code out entirely, and use AeroSandbox purely as an optimization solver or as a solver for nonlinear systems of equations (or ODEs, or PDEs):

Optimize the 2D Rosenbrock function

Specify the Falkner Skan ODE (nonlinear, 3rd-order BVP) and let AeroSandbox automatically take care of the discretization, solution, and even inverse solving.

And much, much more. Best of all, combine these tools arbitrarily without any loss in optimization speed and without any tedious derivative math, all thanks to AeroSandbox's end-to-end automatic-differentiability. ## Getting Started ### Installation In short: * `pip install aerosandbox[full]` for a complete install. * `pip install aerosandbox` for a lightweight (headless) installation with minimal dependencies. All optimization, numerics, and physics models are included, but optional visualization dependencies are skipped. For more installation details (e.g., if you're new to Python), [see here](./INSTALLATION.md). ### Tutorials, Examples, and Documentation To get started, [check out the tutorials folder here](./tutorial/)! All tutorials are viewable in-browser, or you can open them as Jupyter notebooks by cloning this repository. For a more detailed and theory-heavy introduction to AeroSandbox, [please see this thesis](./tutorial/sharpe-pds-sm-AeroAstro-2021-thesis.pdf). For a yet-more-detailed developer-level description of AeroSandbox modules, [please see the developer README](aerosandbox/README.md). For fully-detailed API documentation, see [the documentation website](https://aerosandbox.readthedocs.io/en/master/). You can print documentation and examples for any AeroSandbox object by using the built-in `help()` function (e.g., `help(asb.Airplane)`). AeroSandbox code is also documented *extensively* in the source and contains hundreds of unit test examples, so examining the source code can also be useful. ### Usage Details One final point to note: as we're all sensible and civilized here, **all inputs and outputs to AeroSandbox are expressed in base SI units, or derived units thereof** (e.g, m, N, kg, m/s, J, Pa). The only exception to this rule is when units are explicitly noted via variable name suffix. For example: * `battery_capacity` -> Joules * `battery_capacity_watt_hours` -> Watt-hours. All angles are in radians, except for α and β which are in degrees due to long-standing aerospace convention. (In any case, units are marked on all function docstrings.) If you wish to use other units, consider using [`aerosandbox.tools.units`](./aerosandbox/tools/units.py) to convert easily. ## Project Details ### Contributing Please feel free to join the development of AeroSandbox - contributions are always so welcome! If you have a change you'd like to make, the easiest way to do that is by submitting a pull request. The text file [`CONTRIBUTING.md`](./CONTRIBUTING.md) has more details for developers and power users. If you've already made several additions and would like to be involved in a more long-term capacity, please message me! Contact information can be found next to my name near the top of this README. ### Donating If you like this software, please consider donating to support development [via PayPal](https://paypal.me/peterdsharpe) or [GitHub Sponsors](https://github.com/sponsors/peterdsharpe/)! Proceeds will go towards more coffee for the grad students. ### Bugs Please, please report all bugs by [creating a new issue](https://github.com/peterdsharpe/AeroSandbox/issues)! ### Versioning AeroSandbox loosely uses [semantic versioning](https://semver.org/), which should give you an idea of whether or not you can probably expect backward-compatibility and/or new features from any given update. For more details, see the [changelog](./CHANGELOG.md). ### Citation & Commercial Use If you find AeroSandbox useful in a research publication, please cite it using the following BibTeX snippet: ```bibtex @mastersthesis{aerosandbox, title = {AeroSandbox: A Differentiable Framework for Aircraft Design Optimization}, author = {Sharpe, Peter D.}, school = {Massachusetts Institute of Technology}, year = {2021} } ``` As the MIT License applies, use AeroSandbox for anything you want (attribution appreciated, but not required). Commercial users: I'm more than happy to discuss consulting work for active AeroSandbox support if this package proves helpful - use the email address in the header of this README to get in touch. ### License [MIT License, terms here](LICENSE.txt). Basically: use AeroSandbox for anything you want; no warranty express or implied. ## Stargazers over time [![Stargazers over time](https://starchart.cc/peterdsharpe/AeroSandbox.svg)](https://starchart.cc/peterdsharpe/AeroSandbox) %package -n python3-AeroSandbox Summary: AeroSandbox is a Python package for design optimization of engineered systems such as aircraft. Provides: python-AeroSandbox BuildRequires: python3-devel BuildRequires: python3-setuptools BuildRequires: python3-pip %description -n python3-AeroSandbox ### Gallery Use AeroSandbox to design and optimize entire aircraft:

Feather (an ultra-lightweight 1-meter-class RC motor glider)

SEAWAY-Mini (a solar-electric, 13' wingspan seaplane)

Use AeroSandbox to support real-world aircraft development programs, all the way from your very first sketch to your first-flight and even beyond:

Initial concept sketches + sizing of Dawn (a solar-electric airplane for climate science research) in AeroSandbox, Spring 2020

Dawn (later renamed SACOS) in first flight, Fall 2022

(Thanks to so, so many wonderful people!)

Use AeroSandbox to explore counterintuitive, complicated design tradeoffs, all at the earliest stages of conceptual design *where these insights make the most difference*:

Exploring how big a solar airplane needs to be to fly, as a function of seasonality and latitude

Exploring how the mission range of Firefly, a Mach 0.8 rocket drone, changes if we add an altitude limit, simultaneously optimizing aircraft design and trajectories

Use AeroSandbox as a pure aerodynamics toolkit:

VLM simulation of a glider, aileron deflections of +-30°

Aerodynamic shape optimization of a wing planform, using an arbitrary objective and constraints

Among many other discplines:

Structural optimization of a composite tube spar	Electric motor analysis for propeller matching
Tools to analyze unconventional propulsion (e.g., LH2)	Detailed weights estimation for aircraft ranging from micro-UAVs to airliners

Easily interface AeroSandbox with all your favorite tools:

Other conceptual design tools (AVL, XFLR5, XFoil, ASWING, MSES, etc.)

CAD tools via STEP export (SolidWorks, Fusion 360, etc.)

(STL, OBJ, etc. supported too)

User-provided models + code (for custom aerodynamics, structures, propulsion, or anything else - e.g., for optimizing flight through a probabilistic wind field, shown below)

Or, throw all the airplane-design-specific code out entirely, and use AeroSandbox purely as an optimization solver or as a solver for nonlinear systems of equations (or ODEs, or PDEs):

Optimize the 2D Rosenbrock function

Specify the Falkner Skan ODE (nonlinear, 3rd-order BVP) and let AeroSandbox automatically take care of the discretization, solution, and even inverse solving.

And much, much more. Best of all, combine these tools arbitrarily without any loss in optimization speed and without any tedious derivative math, all thanks to AeroSandbox's end-to-end automatic-differentiability. ## Getting Started ### Installation In short: * `pip install aerosandbox[full]` for a complete install. * `pip install aerosandbox` for a lightweight (headless) installation with minimal dependencies. All optimization, numerics, and physics models are included, but optional visualization dependencies are skipped. For more installation details (e.g., if you're new to Python), [see here](./INSTALLATION.md). ### Tutorials, Examples, and Documentation To get started, [check out the tutorials folder here](./tutorial/)! All tutorials are viewable in-browser, or you can open them as Jupyter notebooks by cloning this repository. For a more detailed and theory-heavy introduction to AeroSandbox, [please see this thesis](./tutorial/sharpe-pds-sm-AeroAstro-2021-thesis.pdf). For a yet-more-detailed developer-level description of AeroSandbox modules, [please see the developer README](aerosandbox/README.md). For fully-detailed API documentation, see [the documentation website](https://aerosandbox.readthedocs.io/en/master/). You can print documentation and examples for any AeroSandbox object by using the built-in `help()` function (e.g., `help(asb.Airplane)`). AeroSandbox code is also documented *extensively* in the source and contains hundreds of unit test examples, so examining the source code can also be useful. ### Usage Details One final point to note: as we're all sensible and civilized here, **all inputs and outputs to AeroSandbox are expressed in base SI units, or derived units thereof** (e.g, m, N, kg, m/s, J, Pa). The only exception to this rule is when units are explicitly noted via variable name suffix. For example: * `battery_capacity` -> Joules * `battery_capacity_watt_hours` -> Watt-hours. All angles are in radians, except for α and β which are in degrees due to long-standing aerospace convention. (In any case, units are marked on all function docstrings.) If you wish to use other units, consider using [`aerosandbox.tools.units`](./aerosandbox/tools/units.py) to convert easily. ## Project Details ### Contributing Please feel free to join the development of AeroSandbox - contributions are always so welcome! If you have a change you'd like to make, the easiest way to do that is by submitting a pull request. The text file [`CONTRIBUTING.md`](./CONTRIBUTING.md) has more details for developers and power users. If you've already made several additions and would like to be involved in a more long-term capacity, please message me! Contact information can be found next to my name near the top of this README. ### Donating If you like this software, please consider donating to support development [via PayPal](https://paypal.me/peterdsharpe) or [GitHub Sponsors](https://github.com/sponsors/peterdsharpe/)! Proceeds will go towards more coffee for the grad students. ### Bugs Please, please report all bugs by [creating a new issue](https://github.com/peterdsharpe/AeroSandbox/issues)! ### Versioning AeroSandbox loosely uses [semantic versioning](https://semver.org/), which should give you an idea of whether or not you can probably expect backward-compatibility and/or new features from any given update. For more details, see the [changelog](./CHANGELOG.md). ### Citation & Commercial Use If you find AeroSandbox useful in a research publication, please cite it using the following BibTeX snippet: ```bibtex @mastersthesis{aerosandbox, title = {AeroSandbox: A Differentiable Framework for Aircraft Design Optimization}, author = {Sharpe, Peter D.}, school = {Massachusetts Institute of Technology}, year = {2021} } ``` As the MIT License applies, use AeroSandbox for anything you want (attribution appreciated, but not required). Commercial users: I'm more than happy to discuss consulting work for active AeroSandbox support if this package proves helpful - use the email address in the header of this README to get in touch. ### License [MIT License, terms here](LICENSE.txt). Basically: use AeroSandbox for anything you want; no warranty express or implied. ## Stargazers over time [![Stargazers over time](https://starchart.cc/peterdsharpe/AeroSandbox.svg)](https://starchart.cc/peterdsharpe/AeroSandbox) %package help Summary: Development documents and examples for AeroSandbox Provides: python3-AeroSandbox-doc %description help ### Gallery Use AeroSandbox to design and optimize entire aircraft:

Feather (an ultra-lightweight 1-meter-class RC motor glider)

SEAWAY-Mini (a solar-electric, 13' wingspan seaplane)

Use AeroSandbox to support real-world aircraft development programs, all the way from your very first sketch to your first-flight and even beyond:

Initial concept sketches + sizing of Dawn (a solar-electric airplane for climate science research) in AeroSandbox, Spring 2020

Dawn (later renamed SACOS) in first flight, Fall 2022

(Thanks to so, so many wonderful people!)

Use AeroSandbox to explore counterintuitive, complicated design tradeoffs, all at the earliest stages of conceptual design *where these insights make the most difference*:

Exploring how big a solar airplane needs to be to fly, as a function of seasonality and latitude

Exploring how the mission range of Firefly, a Mach 0.8 rocket drone, changes if we add an altitude limit, simultaneously optimizing aircraft design and trajectories

Use AeroSandbox as a pure aerodynamics toolkit:

VLM simulation of a glider, aileron deflections of +-30°

Aerodynamic shape optimization of a wing planform, using an arbitrary objective and constraints

Among many other discplines:

Structural optimization of a composite tube spar	Electric motor analysis for propeller matching
Tools to analyze unconventional propulsion (e.g., LH2)	Detailed weights estimation for aircraft ranging from micro-UAVs to airliners

Easily interface AeroSandbox with all your favorite tools:

Other conceptual design tools (AVL, XFLR5, XFoil, ASWING, MSES, etc.)

CAD tools via STEP export (SolidWorks, Fusion 360, etc.)

(STL, OBJ, etc. supported too)

User-provided models + code (for custom aerodynamics, structures, propulsion, or anything else - e.g., for optimizing flight through a probabilistic wind field, shown below)

Or, throw all the airplane-design-specific code out entirely, and use AeroSandbox purely as an optimization solver or as a solver for nonlinear systems of equations (or ODEs, or PDEs):

Optimize the 2D Rosenbrock function

Specify the Falkner Skan ODE (nonlinear, 3rd-order BVP) and let AeroSandbox automatically take care of the discretization, solution, and even inverse solving.

And much, much more. Best of all, combine these tools arbitrarily without any loss in optimization speed and without any tedious derivative math, all thanks to AeroSandbox's end-to-end automatic-differentiability. ## Getting Started ### Installation In short: * `pip install aerosandbox[full]` for a complete install. * `pip install aerosandbox` for a lightweight (headless) installation with minimal dependencies. All optimization, numerics, and physics models are included, but optional visualization dependencies are skipped. For more installation details (e.g., if you're new to Python), [see here](./INSTALLATION.md). ### Tutorials, Examples, and Documentation To get started, [check out the tutorials folder here](./tutorial/)! All tutorials are viewable in-browser, or you can open them as Jupyter notebooks by cloning this repository. For a more detailed and theory-heavy introduction to AeroSandbox, [please see this thesis](./tutorial/sharpe-pds-sm-AeroAstro-2021-thesis.pdf). For a yet-more-detailed developer-level description of AeroSandbox modules, [please see the developer README](aerosandbox/README.md). For fully-detailed API documentation, see [the documentation website](https://aerosandbox.readthedocs.io/en/master/). You can print documentation and examples for any AeroSandbox object by using the built-in `help()` function (e.g., `help(asb.Airplane)`). AeroSandbox code is also documented *extensively* in the source and contains hundreds of unit test examples, so examining the source code can also be useful. ### Usage Details One final point to note: as we're all sensible and civilized here, **all inputs and outputs to AeroSandbox are expressed in base SI units, or derived units thereof** (e.g, m, N, kg, m/s, J, Pa). The only exception to this rule is when units are explicitly noted via variable name suffix. For example: * `battery_capacity` -> Joules * `battery_capacity_watt_hours` -> Watt-hours. All angles are in radians, except for α and β which are in degrees due to long-standing aerospace convention. (In any case, units are marked on all function docstrings.) If you wish to use other units, consider using [`aerosandbox.tools.units`](./aerosandbox/tools/units.py) to convert easily. ## Project Details ### Contributing Please feel free to join the development of AeroSandbox - contributions are always so welcome! If you have a change you'd like to make, the easiest way to do that is by submitting a pull request. The text file [`CONTRIBUTING.md`](./CONTRIBUTING.md) has more details for developers and power users. If you've already made several additions and would like to be involved in a more long-term capacity, please message me! Contact information can be found next to my name near the top of this README. ### Donating If you like this software, please consider donating to support development [via PayPal](https://paypal.me/peterdsharpe) or [GitHub Sponsors](https://github.com/sponsors/peterdsharpe/)! Proceeds will go towards more coffee for the grad students. ### Bugs Please, please report all bugs by [creating a new issue](https://github.com/peterdsharpe/AeroSandbox/issues)! ### Versioning AeroSandbox loosely uses [semantic versioning](https://semver.org/), which should give you an idea of whether or not you can probably expect backward-compatibility and/or new features from any given update. For more details, see the [changelog](./CHANGELOG.md). ### Citation & Commercial Use If you find AeroSandbox useful in a research publication, please cite it using the following BibTeX snippet: ```bibtex @mastersthesis{aerosandbox, title = {AeroSandbox: A Differentiable Framework for Aircraft Design Optimization}, author = {Sharpe, Peter D.}, school = {Massachusetts Institute of Technology}, year = {2021} } ``` As the MIT License applies, use AeroSandbox for anything you want (attribution appreciated, but not required). Commercial users: I'm more than happy to discuss consulting work for active AeroSandbox support if this package proves helpful - use the email address in the header of this README to get in touch. ### License [MIT License, terms here](LICENSE.txt). Basically: use AeroSandbox for anything you want; no warranty express or implied. ## Stargazers over time [![Stargazers over time](https://starchart.cc/peterdsharpe/AeroSandbox.svg)](https://starchart.cc/peterdsharpe/AeroSandbox) %prep %autosetup -n AeroSandbox-4.0.6 %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-AeroSandbox -f filelist.lst %dir %{python3_sitelib}/* %files help -f doclist.lst %{_docdir}/* %changelog * Tue Apr 11 2023 Python_Bot - 4.0.6-1 - Package Spec generated