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‎README.md

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@@ -82,6 +82,14 @@ RocketPy is the next-generation trajectory simulation solution for High-Power Ro
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</ul>
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</details>
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<details>
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<summary>Integration with MATLAB®</summary>
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<ul>
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<li>Straightforward way to run RocketPy from MATLAB®</li>
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<li>Convert RocketPy results to MATLAB® variables so that they can be processed by MATLAB®</li>
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</ul>
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</details>
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<br>
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## Validation
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The table below shows a comparison between experimental data and the output from RocketPy.
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Flight data and rocket parameters used in this comparison were kindly provided by [EPFL Rocket Team](https://github.com/EPFLRocketTeam) and [Notre Dame Rocket Team](https://ndrocketry.weebly.com/).
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| Mission | Result Paramater | RocketPy | Measured | Relative Error |
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| Mission | Result Parameter | RocketPy | Measured | Relative Error |
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|:-----------------------:|:-----------------------|:---------:|:---------:|:--------------:|
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| Bella Lui Kaltbrumn | Apogee altitude (m) | 461.03 | 458.97 | **0.45 %** |
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| Bella Lui Kaltbrumn | Apogee time (s) | 10.61 | 10.56 | **0.47 %** |
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| Bella Lui Kaltbrumn | Maximum velocity (m/s) | 86.18 | 90.00 | **4.24 %** |
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| Bella Lui Kaltbrumn | Maximum velocity (m/s) | 86.18 | 90.00 | **-4.24 %** |
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| NDRT launch vehicle | Apogee altitude (m) | 1,310.44 | 1,320.37 | **-0.75 %** |
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| NDRT launch vehicle | Apogee time (s) | 16.77 | 17.10 | **-1.90 %** |
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| NDRT launch vehicle | Maximum velocity (m/s) | 172.86 | 168.95 | **2.31 %** |

‎docs/conf.py

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2020

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project = "RocketPy"
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copyright = "2020, Projeto Jupiter"
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author = "Giovani Hidalgo Ceotto"
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# The full version, including alpha/beta/rc tags
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release = "0.9.9"
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release = "0.10.0"
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# -- General configuration ---------------------------------------------------

‎docs/matlab/Getting_Started.html

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‎docs/matlab/Getting_Started.m

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%% Getting Started with RocketPy in MATLAB®
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% In this Live Script, you will learn how to run RocketPy using the MATLAB®
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% environment.
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%
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% First things first: clone/download RocketPy's repository and set it as your
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% MATLAB® working directory so that you can run this live script without any issues.
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%
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% After that, we start by configuring our Python environment. You can do so
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% by following the guidelines presented in the MATLAB® documentation: <https://www.mathworks.com/help/matlab/matlab_external/install-supported-python-implementation.html?searchHighlight=python&s_tid=srchtitle_python_4
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% Configure Your System to Use Python - MATLAB & Simulink (mathworks.com)>.
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%
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% Once the Python environment is configured, RocketPy needs to installed using
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% |pip| as outlined in RocketPy's documentation: <https://docs.rocketpy.org/en/latest/user/installation.html#quick-install-using-pip
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% Installation — RocketPy documentation>.
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%
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% Finally, all the prerequisites are complete and you can comeback to MATLAB®!
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% We just need to set the execution mode as out of process and start working.
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% MATLAB® can run Python scripts and functions in a separate process. Running
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% Python in a separate process enables you to:
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%%
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% * Use some third-party libraries in the Python code that are not compatible
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% with MATLAB®.
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% * Isolate the MATLAB® process from crashes in the Python code.
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pyenv('ExecutionMode','OutOfProcess');
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%%
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% Note: if MATLAB® is not able to find Python automatically, you may have to
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% run the command line above including a path to the Python exectuable installed
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% on your computer:
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% pyenv('ExecutionMode','OutOfProcess', 'Version', '/path/to/python/executable');
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%%
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% Now, we will go through a simplified rocket trajectory simulation to get you
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% started. Let's start by importing the rocketpy module.
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rocketpy = py.importlib.import_module('rocketpy');
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%% Setting Up a Simulation
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% Creating an Environment for Spaceport America
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% rocketpy.Environment(railLength, latitude, longitude, elevation);
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Env = rocketpy.Environment(pyargs(...
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'railLength', 5.2, ...
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'latitude', 32.990254, ...
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'longitude',-106.974998, ...
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'elevation', 1400 ...
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));
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%%
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% To get weather data from the GFS forecast, available online, we run the following
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% lines.
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%
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% First, we set tomorrow's date.
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Tomorrow = datetime('tomorrow');
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Env.setDate({int32(Tomorrow.Year), int32(Tomorrow.Month), int32(Tomorrow.Day), int32(12)}) % Hour given in UTC time (noon UTC)
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%%
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% Now, we tell our Environment object to retrieve a weather forecast for our
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% specified location and date using GFS:
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Env.setAtmosphericModel(pyargs( ...
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'type', "Forecast", ...
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'file', "GFS" ...
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))
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%%
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% We can see what the weather will look like by calling the info method!
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Env.info()
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%%
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% Plots will open in a separate window, so be sure to run this last cell to
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% see them!
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%% Creating a Motor
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% A solid rocket motor is used in this case. To create a motor, the SolidMotor
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% class is used and the required arguments are given.
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%
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% The SolidMotor class requires the user to have a thrust curve ready. This
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% can come either from a .eng file for a commercial motor, such as below, or a
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% .csv file from a static test measurement.
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%
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% Besides the thrust curve, other parameters such as grain properties and nozzle
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% dimensions must also be given.
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Pro75M1670 = rocketpy.SolidMotor(pyargs( ...
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'thrustSource', "../../data/motors/Cesaroni_M1670.eng", ...
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'burnOut', 3.9, ...
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'grainNumber', int32(5), ...
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'grainSeparation', 5 / 1000, ...
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'grainDensity', 1815, ...
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'grainOuterRadius', 33 / 1000, ...
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'grainInitialInnerRadius', 15 / 1000, ...
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'grainInitialHeight', 120 / 1000, ...
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'nozzleRadius', 33 / 1000, ...
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'throatRadius', 11 / 1000, ...
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'interpolationMethod', "linear" ...
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));
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%%
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% To see what our thrust curve looks like, along with other import properties,
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% we invoke the info method yet again. You may try the allInfo method if you want
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% more information all at once!
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Pro75M1670.info()
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%%
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% Plots will open in a separate window, so be sure to run this last cell to
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% see them!
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%% Creating a Rocket
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% A rocket is composed of several components. Namely, we must have a motor (good
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% thing we have the Pro75M1670 ready), a couple of aerodynamic surfaces (nose
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% cone, fins and tail) and parachutes (if we are not launching a missile).
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%
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% Let's start by initializing our rocket, named Calisto, supplying it with the
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% Pro75M1670 engine, entering its inertia properties, some dimensions and also
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% its drag curves.
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Calisto = rocketpy.Rocket(pyargs( ...
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'motor', Pro75M1670, ...
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'radius', 127 / 2000, ...
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'mass', 19.197 - 2.956, ...
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'inertiaI', 6.60, ...
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'inertiaZ', 0.0351, ...
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'distanceRocketNozzle', -1.255, ...
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'distanceRocketPropellant', -0.85704, ...
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'powerOffDrag', "../../data/calisto/powerOffDragCurve.csv", ...
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'powerOnDrag', "../../data/calisto/powerOnDragCurve.csv" ...
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));
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Calisto.setRailButtons([0.2, -0.5])
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% Adding Aerodynamic Surfaces
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% Now we define the aerodynamic surfaces. They are really straight forward.
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NoseCone = rocketpy.Rocket.addNose(pyargs( ...
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'self', Calisto, ...
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'length', 0.55829, ...
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'kind', "vonKarman", ...
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'distanceToCM', 0.71971 ...
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));
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FinSet = rocketpy.Rocket.addFins(pyargs( ...
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'self', Calisto, ...
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'n', int32(4), ...
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'span', 0.100, ...
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'rootChord', 0.120, ...
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'tipChord', 0.040, ...
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'distanceToCM', -1.04956 ...
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));
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Tail = rocketpy.Rocket.addTail(pyargs( ...
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'self', Calisto, ...
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'topRadius', 0.0635, ...
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'bottomRadius', 0.0435, ...
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'length', 0.060, ...
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'distanceToCM', -1.194656 ...
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));
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% Adding Parachutes
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% Finally, we have parachutes! Calisto will have two parachutes, Drogue and
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% Main.
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%
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% Both parachutes are activated by some special algorithm, which is usually
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% really complex and a trade secret. Most algorithms are based on pressure sampling
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% only, while some also use acceleration info.
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%
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% RocketPy allows you to define a trigger function which will decide when to
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% activate the ejection event for each parachute. This trigger function is supplied
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% with pressure measurement at a predefined sampling rate. This pressure signal
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% is usually noisy, so artificial noise parameters can be given. Call
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% py.help(rocketpy.Rocket.addParachute)
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%%
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% for more details. Furthermore, the trigger function also receives the complete
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% state vector of the rocket, allowing us to use velocity, acceleration or even
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% attitude to decide when the parachute event should be triggered.
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%
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% Here, we define our trigger functions rather simply using Python. Unfortunately,
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% defining these with MATLAB® code is not yet possible.
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% Drogue parachute is triggered when vertical velocity is negative, i.e. rocket is falling past apogee
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drogueTrigger = py.eval("lambda p, y: y[5] < 0", py.dict);
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% Main parachute is triggered when vertical velocity is negative and altitude is below 800 AGL
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mainTrigger = py.eval("lambda p, y: (y[5] < 0) and (y[2] < 800 + 1400)", py.dict);
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%%
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% Now we add both the drogue and the main parachute to our rocket.
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Main = rocketpy.Rocket.addParachute(pyargs( ...
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'self', Calisto, ...
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'name', "Main", ...
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'CdS', 10.0, ...
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'trigger', mainTrigger, ...
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'samplingRate', 105, ...
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'lag', 1.5, ...
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'noise', py.tuple({0, 8.3, 0.5}) ...
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));
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Drogue = rocketpy.Rocket.addParachute(pyargs( ...
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'self', Calisto, ...
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'name', "Drogue", ...
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'CdS', 1.0, ...
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'trigger', drogueTrigger, ...
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'samplingRate', 105, ...
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'lag', 1.5, ...
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'noise', py.tuple({0, 8.3, 0.5}) ...
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));
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%%
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% |Just be careful if you run this last cell multiple times! If you do so, your
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% rocket will end up with lots of parachutes which activate together, which may
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% cause problems during the flight simulation. We advise you to re-run all cells
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% which define our rocket before running this, preventing unwanted old parachutes.
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% Alternatively, you can run the following lines to remove parachutes.|
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% Calisto.parachutes.remove(Drogue)
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% Calisto.parachutes.remove(Main)
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%% |Simulating a Flight|
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% |Simulating a flight trajectory is as simple as initializing a Flight class
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% object givin the rocket and environnement set up above as inputs. The launch
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% rail inclination and heading are also given here.|
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TestFlight = rocketpy.Flight(pyargs(...
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'rocket', Calisto, ...
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'environment',Env, ...
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'inclination', 85, ...
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'heading', 0 ...
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));
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%% |Analyzing the Results|
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% |RocketPy gives you many plots, thats for sure! They are divided into sections
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% to keep them organized. Alternatively, see the Flight class documentation to
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% see how to get plots for specific variables only, instead of all of them at
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% once.|
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TestFlight.allInfo()
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%%
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% Plots will open in a separate window, so be sure to run this last cell to
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% see them!
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%% Working with Data Generated by RocketPy in MATLAB®
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% You can access the entire trajectory solution matrix with the following line
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% of code. The returned matrix contain the following columns: time $t$ (s), $x$
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% (m), $y$ (m), $z$ (m), $v_x$ (m/s), $v_y$ (m/s), $v_z$ (m/s), $q_0$, $q_1$,
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% $q_2$, $q_3$, $\omega_1$ (rad/s), $\omega_2$ (rad/s), $\omega_3$ (rad/s).
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solution_matrix = double(py.numpy.array(TestFlight.solution))
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%%
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% Support for accessing secondary values calculated during post processing,
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% such as energy, mach number, and angle of attack, is also available for all
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% versions of RocketPy greater than or equal to version 0.11.0.
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%
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% To showcase this, let's get the angle of attack of the rocket and plot it
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% using MATLAB®:
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angle_of_attack = double(TestFlight.angleOfAttack.source)
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plot(angle_of_attack(:,1), angle_of_attack(:,2)) % First column is time (s), second is the angle of attack
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ylabel('Angle of Attack (Deg)')
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xlabel('Time(s)')
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xlim([TestFlight.outOfRailTime, 10])
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%%
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% You can also convert data from other objects besides the Flight class, such
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% as from the Environment. For example, let's say you want to get the wind velocity,
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% both the x and y component:
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wind_velocity_x = double(Env.windVelocityX.source) % First column is altitude (ASL m), while the second one is the speed (m/s)
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wind_velocity_y = double(Env.windVelocityY.source) % First column is altitude (ASL m), while the second one is the speed (m/s)
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%% Time to Fly!
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% This is all you need to get started using RocketPy in MATLAB®! Now it is time
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% to play around and create amazing rockets. Have a great launch!

‎docs/matlab/Getting_Started.mlx

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‎docs/matlab/matlab.rst

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MATLAB® Tutorial
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================
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RocketPy in MATLAB®
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--------------------
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Did you know you can run RocketPy inside MATLAB®?
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MATLAB® provides a nice method to run Python libraries, allowing everyone familiar with MATLAB® to run RocketPy, getting the best of both worlds.
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Below, you will find a quick tutorial created using Live Script which reproduces RocketPy's classic Getting Started tutorial.
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Download Files
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--------------
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.. only:: builder_html or readthedocs
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You can download the :download:`Live Script <Getting_Started.mlx>` or the :download:`MATLAB® script <Getting_Started.m>` file to follow along.
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Tutorial
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--------
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.. raw:: html
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:file: Getting_Started.html

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