diff --git a/docs/notebooks/dispersion_analysis/dispersion_analysis.ipynb b/docs/notebooks/dispersion_analysis/dispersion_analysis.ipynb
index 518dbd848..da512012d 100644
--- a/docs/notebooks/dispersion_analysis/dispersion_analysis.ipynb
+++ b/docs/notebooks/dispersion_analysis/dispersion_analysis.ipynb
@@ -37,7 +37,7 @@
"metadata": {},
"outputs": [],
"source": [
- "%git clone https://github.com/giovaniceotto/RocketPy.git\n",
+ "%git clone https://github.com/RocketPy-Team/RocketPy.git\n",
"import os\n",
"\n",
"os.chdir(\"RocketPy/docs/notebooks/dispersion_analysis\")"
@@ -67,12 +67,13 @@
"outputs": [],
"source": [
"%pip install netCDF4\n",
- "%pip install rocketpy"
+ "%pip install rocketpy\n",
+ "%pip install ipympl"
]
},
{
"cell_type": "code",
- "execution_count": null,
+ "execution_count": 1,
"metadata": {
"id": "rNY7u8fApOP_"
},
@@ -99,7 +100,7 @@
},
{
"cell_type": "code",
- "execution_count": null,
+ "execution_count": 2,
"metadata": {
"id": "0uEmvBIt5Ltg"
},
@@ -140,7 +141,7 @@
},
{
"cell_type": "code",
- "execution_count": null,
+ "execution_count": 3,
"metadata": {
"id": "fwoCdOgKpOQD"
},
@@ -148,7 +149,7 @@
"source": [
"analysis_parameters = {\n",
" # Mass Details\n",
- " \"rocketMass\": (\n",
+ " \"rocket_mass\": (\n",
" 8.257,\n",
" 0.001,\n",
" ), # Rocket's dry mass (kg) and its uncertainty (standard deviation)\n",
@@ -161,48 +162,48 @@
" 6 / 1000,\n",
" 1 / 1000,\n",
" ), # Motor's grain separation (axial distance between two grains) (m)\n",
- " \"grainDensity\": (1707, 50), # Motor's grain density (kg/m^3)\n",
- " \"grainOuterRadius\": (21.4 / 1000, 0.375 / 1000), # Motor's grain outer radius (m)\n",
- " \"grainInitialInnerRadius\": (\n",
+ " \"grain_density\": (1707, 50), # Motor's grain density (kg/m^3)\n",
+ " \"grain_outer_radius\": (21.4 / 1000, 0.375 / 1000), # Motor's grain outer radius (m)\n",
+ " \"grain_initial_inner_radius\": (\n",
" 9.65 / 1000,\n",
" 0.375 / 1000,\n",
" ), # Motor's grain inner radius (m)\n",
- " \"grainInitialHeight\": (120 / 1000, 1 / 1000), # Motor's grain height (m)\n",
+ " \"grain_initial_height\": (120 / 1000, 1 / 1000), # Motor's grain height (m)\n",
" # Aerodynamic Details - run help(Rocket) for more information\n",
- " \"inertiaI\": (\n",
+ " \"inertia_I\": (\n",
" 3.675,\n",
" 0.03675,\n",
" ), # Rocket's inertia moment perpendicular to its axis (kg*m^2)\n",
- " \"inertiaZ\": (\n",
+ " \"inertia_Z\": (\n",
" 0.007,\n",
" 0.00007,\n",
" ), # Rocket's inertia moment relative to its axis (kg*m^2)\n",
" \"radius\": (40.45 / 1000, 0.001), # Rocket's radius (kg*m^2)\n",
- " \"distanceRocketNozzle\": (\n",
+ " \"distance_rocket_nozzle\": (\n",
" -1.024,\n",
" 0.001,\n",
" ), # Distance between rocket's center of dry mass and nozzle exit plane (m) (negative)\n",
- " \"distanceRocketPropellant\": (\n",
+ " \"distance_rocket_propellant\": (\n",
" -0.571,\n",
" 0.001,\n",
" ), # Distance between rocket's center of dry mass and and center of propellant mass (m) (negative)\n",
- " \"powerOffDrag\": (\n",
+ " \"power_off_drag\": (\n",
" 0.9081 / 1.05,\n",
" 0.033,\n",
" ), # Multiplier for rocket's drag curve. Usually has a mean value of 1 and a uncertainty of 5% to 10%\n",
- " \"powerOnDrag\": (\n",
+ " \"power_on_drag\": (\n",
" 0.9081 / 1.05,\n",
" 0.033,\n",
" ), # Multiplier for rocket's drag curve. Usually has a mean value of 1 and a uncertainty of 5% to 10%\n",
- " \"noseLength\": (0.274, 0.001), # Rocket's nose cone length (m)\n",
- " \"noseDistanceToCM\": (\n",
+ " \"nose_length\": (0.274, 0.001), # Rocket's nose cone length (m)\n",
+ " \"nose_distance_to_CM\": (\n",
" 1.134,\n",
" 0.001,\n",
" ), # Axial distance between rocket's center of dry mass and nearest point in its nose cone (m)\n",
- " \"finSpan\": (0.077, 0.0005), # Fin span (m)\n",
- " \"finRootChord\": (0.058, 0.0005), # Fin root chord (m)\n",
- " \"finTipChord\": (0.018, 0.0005), # Fin tip chord (m)\n",
- " \"finDistanceToCM\": (\n",
+ " \"fin_span\": (0.077, 0.0005), # Fin span (m)\n",
+ " \"fin_root_chord\": (0.058, 0.0005), # Fin root chord (m)\n",
+ " \"fin_tip_chord\": (0.018, 0.0005), # Fin tip chord (m)\n",
+ " \"fin_distance_to_CM\": (\n",
" -0.906,\n",
" 0.001,\n",
" ), # Axial distance between rocket's center of dry mass and nearest point in its fin (m)\n",
@@ -212,10 +213,10 @@
" 1,\n",
" ), # Launch rail inclination angle relative to the horizontal plane (degrees)\n",
" \"heading\": (53, 2), # Launch rail heading relative to north (degrees)\n",
- " \"railLength\": (5.7, 0.0005), # Launch rail length (m)\n",
- " \"ensembleMember\": list(range(10)), # Members of the ensemble forecast to be used\n",
+ " \"rail_length\": (5.7, 0.0005), # Launch rail length (m)\n",
+ " \"ensemble_member\": list(range(10)), # Members of the ensemble forecast to be used\n",
" # Parachute Details - run help(Rocket) for more information\n",
- " \"CdSDrogue\": (\n",
+ " \"cd_s_drogue\": (\n",
" 0.349 * 1.3,\n",
" 0.07,\n",
" ), # Drag coefficient times reference area for the drogue chute (m^2)\n",
@@ -247,7 +248,7 @@
},
{
"cell_type": "code",
- "execution_count": null,
+ "execution_count": 4,
"metadata": {
"id": "5XCL9JaIpOQH"
},
@@ -293,7 +294,7 @@
},
{
"cell_type": "code",
- "execution_count": null,
+ "execution_count": 5,
"metadata": {
"id": "1eC2p3jEpOQO"
},
@@ -302,57 +303,41 @@
"def export_flight_data(flight_setting, flight_data, exec_time):\n",
" # Generate flight results\n",
" flight_result = {\n",
- " \"outOfRailTime\": flight_data.outOfRailTime,\n",
- " \"outOfRailVelocity\": flight_data.outOfRailVelocity,\n",
- " \"apogeeTime\": flight_data.apogeeTime,\n",
- " \"apogeeAltitude\": flight_data.apogee - Env.elevation,\n",
- " \"apogeeX\": flight_data.apogeeX,\n",
- " \"apogeeY\": flight_data.apogeeY,\n",
- " \"impactTime\": flight_data.tFinal,\n",
- " \"impactX\": flight_data.xImpact,\n",
- " \"impactY\": flight_data.yImpact,\n",
- " \"impactVelocity\": flight_data.impactVelocity,\n",
- " \"initialStaticMargin\": flight_data.rocket.staticMargin(0),\n",
- " \"outOfRailStaticMargin\": flight_data.rocket.staticMargin(\n",
- " TestFlight.outOfRailTime\n",
+ " \"out_of_rail_time\": flight_data.out_of_rail_time,\n",
+ " \"out_of_rail_velocity\": flight_data.out_of_rail_velocity,\n",
+ " \"max_velocity\": flight_data.speed.max,\n",
+ " \"apogee_time\": flight_data.apogee_time,\n",
+ " \"apogee_altitude\": flight_data.apogee - Env.elevation,\n",
+ " \"apogee_x\": flight_data.apogee_x,\n",
+ " \"apogee_y\": flight_data.apogee_y,\n",
+ " \"impact_time\": flight_data.t_final,\n",
+ " \"impact_x\": flight_data.x_impact,\n",
+ " \"impact_y\": flight_data.y_impact,\n",
+ " \"impact_velocity\": flight_data.impact_velocity,\n",
+ " \"initial_static_margin\": flight_data.rocket.static_margin(0),\n",
+ " \"out_of_rail_static_margin\": flight_data.rocket.static_margin(\n",
+ " flight_data.out_of_rail_time\n",
" ),\n",
- " \"finalStaticMargin\": flight_data.rocket.staticMargin(\n",
- " TestFlight.rocket.motor.burnOutTime\n",
+ " \"final_static_margin\": flight_data.rocket.static_margin(\n",
+ " flight_data.rocket.motor.burn_out_time\n",
" ),\n",
- " \"numberOfEvents\": len(flight_data.parachuteEvents),\n",
- " \"executionTime\": exec_time,\n",
+ " \"number_of_events\": len(flight_data.parachute_events),\n",
+ " \"execution_time\": exec_time,\n",
" }\n",
"\n",
- " # Calculate maximum reached velocity\n",
- " sol = np.array(flight_data.solution)\n",
- " flight_data.vx = Function(\n",
- " sol[:, [0, 4]], \"Time (s)\", \"Vx (m/s)\", \"linear\", extrapolation=\"natural\"\n",
- " )\n",
- " flight_data.vy = Function(\n",
- " sol[:, [0, 5]], \"Time (s)\", \"Vy (m/s)\", \"linear\", extrapolation=\"natural\"\n",
- " )\n",
- " flight_data.vz = Function(\n",
- " sol[:, [0, 6]], \"Time (s)\", \"Vz (m/s)\", \"linear\", extrapolation=\"natural\"\n",
- " )\n",
- " flight_data.v = (\n",
- " flight_data.vx**2 + flight_data.vy**2 + flight_data.vz**2\n",
- " ) ** 0.5\n",
- " flight_data.maxVel = np.amax(flight_data.v.source[:, 1])\n",
- " flight_result[\"maxVelocity\"] = flight_data.maxVel\n",
- "\n",
" # Take care of parachute results\n",
- " if len(flight_data.parachuteEvents) > 0:\n",
- " flight_result[\"drogueTriggerTime\"] = flight_data.parachuteEvents[0][0]\n",
- " flight_result[\"drogueInflatedTime\"] = (\n",
- " flight_data.parachuteEvents[0][0] + flight_data.parachuteEvents[0][1].lag\n",
+ " if len(flight_data.parachute_events) > 0:\n",
+ " flight_result[\"drogue_triggerTime\"] = flight_data.parachute_events[0][0]\n",
+ " flight_result[\"drogue_inflated_time\"] = (\n",
+ " flight_data.parachute_events[0][0] + flight_data.parachute_events[0][1].lag\n",
" )\n",
- " flight_result[\"drogueInflatedVelocity\"] = flight_data.v(\n",
- " flight_data.parachuteEvents[0][0] + flight_data.parachuteEvents[0][1].lag\n",
+ " flight_result[\"drogue_inflated_velocity\"] = flight_data.speed(\n",
+ " flight_data.parachute_events[0][0] + flight_data.parachute_events[0][1].lag\n",
" )\n",
" else:\n",
- " flight_result[\"drogueTriggerTime\"] = 0\n",
- " flight_result[\"drogueInflatedTime\"] = 0\n",
- " flight_result[\"drogueInflatedVelocity\"] = 0\n",
+ " flight_result[\"drogue_triggerTime\"] = 0\n",
+ " flight_result[\"drogue_inflated_time\"] = 0\n",
+ " flight_result[\"drogue_inflated_velocity\"] = 0\n",
"\n",
" # Write flight setting and results to file\n",
" dispersion_input_file.write(str(flight_setting) + \"\\n\")\n",
@@ -386,7 +371,7 @@
},
{
"cell_type": "code",
- "execution_count": null,
+ "execution_count": 6,
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/",
@@ -395,11 +380,21 @@
"id": "GILiaO30pOQS",
"outputId": "5a2ae15d-5c16-4ae0-f28b-165730d2419d"
},
- "outputs": [],
+ "outputs": [
+ {
+ "data": {
+ "text/plain": [
+ "'Starting'"
+ ]
+ },
+ "metadata": {},
+ "output_type": "display_data"
+ }
+ ],
"source": [
"# Basic analysis info\n",
- "filename = \"dispersion_analysis_outputs/valetudo_rocket_v0\"\n",
- "number_of_simulations = 20000\n",
+ "filename = \"dispersion_analysis_outputs/valetudo_rocket_v1\"\n",
+ "number_of_simulations = 10\n",
"\n",
"# Create data files for inputs, outputs and error logging\n",
"dispersion_error_file = open(str(filename) + \".disp_errors.txt\", \"w\")\n",
@@ -416,16 +411,16 @@
"Env = Environment(\n",
" date=(2019, 8, 10, 21), latitude=-23.363611, longitude=-48.011389\n",
")\n",
- "Env.setElevation(668)\n",
- "Env.maxExpectedHeight = 1500\n",
- "Env.setAtmosphericModel(\n",
+ "Env.set_elevation(668)\n",
+ "Env.max_expected_height = 1500\n",
+ "Env.set_atmospheric_model(\n",
" type=\"Ensemble\",\n",
" file=\"dispersion_analysis_inputs/LASC2019_reanalysis.nc\",\n",
" dictionary=\"ECMWF\",\n",
")\n",
"\n",
"# Set up parachutes. This rocket, named Valetudo, only has a drogue chute.\n",
- "def drogueTrigger(p, h, y):\n",
+ "def drogue_trigger(p, h, y):\n",
" # Check if rocket is going down, i.e. if it has passed the apogee\n",
" vertical_velocity = y[5]\n",
" # Return true to activate parachute once the vertical velocity is negative\n",
@@ -439,80 +434,82 @@
" i += 1\n",
"\n",
" # Update environment object\n",
- " Env.selectEnsembleMember(setting[\"ensembleMember\"])\n",
+ " Env.select_ensemble_member(setting[\"ensemble_member\"])\n",
"\n",
" # Create motor\n",
" Keron = SolidMotor(\n",
- " thrustSource=\"dispersion_analysis_inputs/thrustCurve.csv\",\n",
+ " thrust_source=\"dispersion_analysis_inputs/thrustCurve.csv\",\n",
" burn_time=5.274,\n",
- " reshapeThrustCurve=(setting[\"burn_time\"], setting[\"impulse\"]),\n",
+ " reshape_thrust_curve=(setting[\"burn_time\"], setting[\"impulse\"]),\n",
" nozzle_radius=setting[\"nozzle_radius\"],\n",
" throat_radius=setting[\"throat_radius\"],\n",
- " grainsCenterOfMassPosition=setting[\"distanceRocketPropellant\"],\n",
- " grainNumber=6,\n",
+ " grains_center_of_mass_position=setting[\"distance_rocket_propellant\"],\n",
+ " grain_number=6,\n",
" grain_separation=setting[\"grain_separation\"],\n",
- " grainDensity=setting[\"grainDensity\"],\n",
- " grainOuterRadius=setting[\"grainOuterRadius\"],\n",
- " grainInitialInnerRadius=setting[\"grainInitialInnerRadius\"],\n",
- " grainInitialHeight=setting[\"grainInitialHeight\"],\n",
- " interpolationMethod=\"linear\",\n",
- " nozzlePosition=setting[\"distanceRocketNozzle\"],\n",
- " coordinateSystemOrientation=\"nozzleToCombustionChamber\",\n",
+ " grain_density=setting[\"grain_density\"],\n",
+ " grain_outer_radius=setting[\"grain_outer_radius\"],\n",
+ " grain_initial_inner_radius=setting[\"grain_initial_inner_radius\"],\n",
+ " grain_initial_height=setting[\"grain_initial_height\"],\n",
+ " interpolation_method=\"linear\",\n",
+ " nozzle_position=setting[\"distance_rocket_nozzle\"],\n",
+ " coordinate_system_orientation=\"nozzle_to_combustion_chamber\",\n",
+ " dry_mass=0,\n",
+ " dry_inertia=(0, 0, 0),\n",
+ " center_of_dry_mass_position=0\n",
" )\n",
" # Create rocket\n",
" Valetudo = Rocket(\n",
" radius=setting[\"radius\"],\n",
- " mass=setting[\"rocketMass\"],\n",
- " inertiaI=setting[\"inertiaI\"],\n",
- " inertiaZ=setting[\"inertiaZ\"],\n",
- " powerOffDrag=\"dispersion_analysis_inputs/Cd_PowerOff.csv\",\n",
- " powerOnDrag=\"dispersion_analysis_inputs/Cd_PowerOn.csv\",\n",
- " centerOfDryMassPosition=0,\n",
- " coordinateSystemOrientation=\"tailToNose\",\n",
+ " mass=setting[\"rocket_mass\"],\n",
+ " inertia=(setting[\"inertia_I\"],setting[\"inertia_I\"],setting[\"inertia_Z\"]),\n",
+ " power_off_drag=\"dispersion_analysis_inputs/Cd_PowerOff.csv\",\n",
+ " power_on_drag=\"dispersion_analysis_inputs/Cd_PowerOn.csv\",\n",
+ " center_of_mass_without_motor=0,\n",
+ " coordinate_system_orientation=\"tail_to_nose\",\n",
" )\n",
- " Valetudo.setRailButtons(0.224, -0.93, 30)\n",
+ " Valetudo.set_rail_buttons(0.224, -0.93, 30)\n",
"\n",
- " Valetudo.addMotor(Keron, position=setting[\"distanceRocketNozzle\"])\n",
+ " Valetudo.add_motor(Keron, position=setting[\"distance_rocket_nozzle\"])\n",
"\n",
" # Edit rocket drag\n",
- " Valetudo.powerOffDrag *= setting[\"powerOffDrag\"]\n",
- " Valetudo.powerOnDrag *= setting[\"powerOnDrag\"]\n",
+ " Valetudo.power_off_drag *= setting[\"power_off_drag\"]\n",
+ " Valetudo.power_on_drag *= setting[\"power_on_drag\"]\n",
" # Add rocket nose, fins and tail\n",
- " NoseCone = Valetudo.addNose(\n",
- " length=setting[\"noseLength\"],\n",
+ " NoseCone = Valetudo.add_nose(\n",
+ " length=setting[\"nose_length\"],\n",
" kind=\"vonKarman\",\n",
- " position=setting[\"noseDistanceToCM\"] + setting[\"noseLength\"],\n",
+ " position=setting[\"nose_distance_to_CM\"],\n",
" )\n",
- " FinSet = Valetudo.addTrapezoidalFins(\n",
+ " FinSet = Valetudo.add_trapezoidal_fins(\n",
" n=3,\n",
- " span=setting[\"finSpan\"],\n",
- " rootChord=setting[\"finRootChord\"],\n",
- " tipChord=setting[\"finTipChord\"],\n",
- " position=setting[\"finDistanceToCM\"],\n",
- " cantAngle=0,\n",
+ " span=setting[\"fin_span\"],\n",
+ " root_chord=setting[\"fin_root_chord\"],\n",
+ " tip_chord=setting[\"fin_tip_chord\"],\n",
+ " position=setting[\"fin_distance_to_CM\"],\n",
+ " cant_angle=0,\n",
" airfoil=None,\n",
" )\n",
" # Add parachute\n",
- " Drogue = Valetudo.addParachute(\n",
+ " Drogue = Valetudo.add_parachute(\n",
" \"Drogue\",\n",
- " CdS=setting[\"CdSDrogue\"],\n",
- " trigger=drogueTrigger,\n",
- " samplingRate=105,\n",
+ " cd_s=setting[\"cd_s_drogue\"],\n",
+ " trigger=drogue_trigger,\n",
+ " sampling_rate=105,\n",
" lag=setting[\"lag_rec\"] + setting[\"lag_se\"],\n",
" noise=(0, 8.3, 0.5),\n",
" )\n",
"\n",
" # Run trajectory simulation\n",
" try:\n",
- " TestFlight = Flight(\n",
+ " test_flight = Flight(\n",
" rocket=Valetudo,\n",
" environment=Env,\n",
- " railLength=setting[\"railLength\"],\n",
+ " rail_length=setting[\"rail_length\"],\n",
" inclination=setting[\"inclination\"],\n",
" heading=setting[\"heading\"],\n",
- " maxTime=600,\n",
+ " max_time=600,\n",
" )\n",
- " export_flight_data(setting, TestFlight, process_time() - start_time)\n",
+ " export_flight_data(setting, test_flight, process_time() - start_time)\n",
" except Exception as E:\n",
" print(E)\n",
" export_flight_error(setting)\n",
@@ -534,7 +531,7 @@
"## Close files\n",
"dispersion_input_file.close()\n",
"dispersion_output_file.close()\n",
- "dispersion_error_file.close()\n"
+ "dispersion_error_file.close()"
]
},
{
@@ -561,7 +558,7 @@
},
{
"cell_type": "code",
- "execution_count": null,
+ "execution_count": 9,
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/"
@@ -569,33 +566,41 @@
"id": "-7qgTJzRpOQb",
"outputId": "76d2cecd-a09f-429f-cca2-f4e03e39d49e"
},
- "outputs": [],
+ "outputs": [
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "Number of simulations: 10\n"
+ ]
+ }
+ ],
"source": [
- "filename = \"dispersion_analysis_outputs/valetudo_rocket_v0\"\n",
+ "filename = \"dispersion_analysis_outputs/valetudo_rocket_v1\"\n",
"\n",
"# Initialize variable to store all results\n",
"dispersion_general_results = []\n",
"\n",
"dispersion_results = {\n",
- " \"outOfRailTime\": [],\n",
- " \"outOfRailVelocity\": [],\n",
- " \"apogeeTime\": [],\n",
- " \"apogeeAltitude\": [],\n",
- " \"apogeeX\": [],\n",
- " \"apogeeY\": [],\n",
- " \"impactTime\": [],\n",
- " \"impactX\": [],\n",
- " \"impactY\": [],\n",
- " \"impactVelocity\": [],\n",
- " \"initialStaticMargin\": [],\n",
- " \"outOfRailStaticMargin\": [],\n",
- " \"finalStaticMargin\": [],\n",
- " \"numberOfEvents\": [],\n",
- " \"maxVelocity\": [],\n",
- " \"drogueTriggerTime\": [],\n",
- " \"drogueInflatedTime\": [],\n",
- " \"drogueInflatedVelocity\": [],\n",
- " \"executionTime\": [],\n",
+ " \"out_of_rail_time\": [],\n",
+ " \"out_of_rail_velocity\": [],\n",
+ " \"apogee_time\": [],\n",
+ " \"apogee_altitude\": [],\n",
+ " \"apogee_x\": [],\n",
+ " \"apogee_y\": [],\n",
+ " \"impact_time\": [],\n",
+ " \"impact_x\": [],\n",
+ " \"impact_y\": [],\n",
+ " \"impact_velocity\": [],\n",
+ " \"initial_static_margin\": [],\n",
+ " \"out_of_rail_static_margin\": [],\n",
+ " \"final_static_margin\": [],\n",
+ " \"number_of_events\": [],\n",
+ " \"max_velocity\": [],\n",
+ " \"drogue_triggerTime\": [],\n",
+ " \"drogue_inflated_time\": [],\n",
+ " \"drogue_inflated_velocity\": [],\n",
+ " \"execution_time\": [],\n",
"}\n",
"\n",
"# Get all dispersion results\n",
@@ -645,7 +650,7 @@
},
{
"cell_type": "code",
- "execution_count": null,
+ "execution_count": 10,
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/",
@@ -654,17 +659,1109 @@
"id": "1JQSzd5cpOQh",
"outputId": "455abcdf-9dd7-4689-9523-50154c7fb302"
},
- "outputs": [],
+ "outputs": [
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "Out of Rail Time - Mean Value: 1.024 s\n",
+ "Out of Rail Time - Standard Deviation: 0.246 s\n"
+ ]
+ },
+ {
+ "data": {
+ "image/svg+xml": [
+ "\n",
+ "\n",
+ "\n"
+ ],
+ "text/plain": [
+ ""
+ ]
+ },
+ "metadata": {
+ "needs_background": "light"
+ },
+ "output_type": "display_data"
+ }
+ ],
"source": [
"print(\n",
- " f'Out of Rail Time - Mean Value: {np.mean(dispersion_results[\"outOfRailTime\"]):0.3f} s'\n",
+ " f'Out of Rail Time - Mean Value: {np.mean(dispersion_results[\"out_of_rail_time\"]):0.3f} s'\n",
")\n",
"print(\n",
- " f'Out of Rail Time - Standard Deviation: {np.std(dispersion_results[\"outOfRailTime\"]):0.3f} s'\n",
+ " f'Out of Rail Time - Standard Deviation: {np.std(dispersion_results[\"out_of_rail_time\"]):0.3f} s'\n",
")\n",
"\n",
"plt.figure()\n",
- "plt.hist(dispersion_results[\"outOfRailTime\"], bins=int(N**0.5))\n",
+ "plt.hist(dispersion_results[\"out_of_rail_time\"], bins=int(N**0.5))\n",
"plt.title(\"Out of Rail Time\")\n",
"plt.xlabel(\"Time (s)\")\n",
"plt.ylabel(\"Number of Occurences\")\n",
@@ -673,7 +1770,7 @@
"# You can also use Plotly instead of Matplotlib if you wish!\n",
"# import plotly.express as px\n",
"# fig1 = px.histogram(\n",
- "# x=dispersion_results[\"outOfRailTime\"],\n",
+ "# x=dispersion_results[\"out_of_rail_time\"],\n",
"# title='Out of Rail Time',\n",
"# nbins=int(N**0.5)\n",
"# )\n",
@@ -695,7 +1792,7 @@
},
{
"cell_type": "code",
- "execution_count": null,
+ "execution_count": 11,
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/",
@@ -704,17 +1801,1094 @@
"id": "jE23vILMpOQm",
"outputId": "aa04f5a4-26f2-47e8-831a-41d3e76b616f"
},
- "outputs": [],
+ "outputs": [
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "Out of Rail Velocity - Mean Value: 20.093 m/s\n",
+ "Out of Rail Velocity - Standard Deviation: 3.469 m/s\n"
+ ]
+ },
+ {
+ "data": {
+ "image/svg+xml": [
+ "\n",
+ "\n",
+ "\n"
+ ],
+ "text/plain": [
+ ""
+ ]
+ },
+ "metadata": {
+ "needs_background": "light"
+ },
+ "output_type": "display_data"
+ }
+ ],
"source": [
"print(\n",
- " f'Out of Rail Velocity - Mean Value: {np.mean(dispersion_results[\"outOfRailVelocity\"]):0.3f} m/s'\n",
+ " f'Out of Rail Velocity - Mean Value: {np.mean(dispersion_results[\"out_of_rail_velocity\"]):0.3f} m/s'\n",
")\n",
"print(\n",
- " f'Out of Rail Velocity - Standard Deviation: {np.std(dispersion_results[\"outOfRailVelocity\"]):0.3f} m/s'\n",
+ " f'Out of Rail Velocity - Standard Deviation: {np.std(dispersion_results[\"out_of_rail_velocity\"]):0.3f} m/s'\n",
")\n",
"\n",
"plt.figure()\n",
- "plt.hist(dispersion_results[\"outOfRailVelocity\"], bins=int(N**0.5))\n",
+ "plt.hist(dispersion_results[\"out_of_rail_velocity\"], bins=int(N**0.5))\n",
"plt.title(\"Out of Rail Velocity\")\n",
"plt.xlabel(\"Velocity (m/s)\")\n",
"plt.ylabel(\"Number of Occurences\")\n",
@@ -733,7 +2907,7 @@
},
{
"cell_type": "code",
- "execution_count": null,
+ "execution_count": 12,
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/",
@@ -742,17 +2916,973 @@
"id": "l8zjT_VjpOQq",
"outputId": "1c15fe12-afae-4035-f085-7d82e61d24d9"
},
- "outputs": [],
+ "outputs": [
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "Apogee Time - Mean Value: 14.133 s\n",
+ "Apogee Time - Standard Deviation: 0.433 s\n"
+ ]
+ },
+ {
+ "data": {
+ "image/svg+xml": [
+ "\n",
+ "\n",
+ "\n"
+ ],
+ "text/plain": [
+ ""
+ ]
+ },
+ "metadata": {
+ "needs_background": "light"
+ },
+ "output_type": "display_data"
+ }
+ ],
"source": [
"print(\n",
- " f'Apogee Time - Mean Value: {np.mean(dispersion_results[\"apogeeTime\"]):0.3f} s'\n",
+ " f'Apogee Time - Mean Value: {np.mean(dispersion_results[\"apogee_time\"]):0.3f} s'\n",
")\n",
"print(\n",
- " f'Apogee Time - Standard Deviation: {np.std(dispersion_results[\"apogeeTime\"]):0.3f} s'\n",
+ " f'Apogee Time - Standard Deviation: {np.std(dispersion_results[\"apogee_time\"]):0.3f} s'\n",
")\n",
"\n",
"plt.figure()\n",
- "plt.hist(dispersion_results[\"apogeeTime\"], bins=int(N**0.5))\n",
+ "plt.hist(dispersion_results[\"apogee_time\"], bins=int(N**0.5))\n",
"plt.title(\"Apogee Time\")\n",
"plt.xlabel(\"Time (s)\")\n",
"plt.ylabel(\"Number of Occurences\")\n",
@@ -771,7 +3901,7 @@
},
{
"cell_type": "code",
- "execution_count": null,
+ "execution_count": 13,
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/",
@@ -780,17 +3910,1061 @@
"id": "gWWMoOClpOQv",
"outputId": "88f2cf05-142c-4bb1-ce64-9879696107a7"
},
- "outputs": [],
+ "outputs": [
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "Apogee Altitude - Mean Value: 827.380 m\n",
+ "Apogee Altitude - Standard Deviation: 49.900 m\n"
+ ]
+ },
+ {
+ "data": {
+ "image/svg+xml": [
+ "\n",
+ "\n",
+ "\n"
+ ],
+ "text/plain": [
+ ""
+ ]
+ },
+ "metadata": {
+ "needs_background": "light"
+ },
+ "output_type": "display_data"
+ }
+ ],
"source": [
"print(\n",
- " f'Apogee Altitude - Mean Value: {np.mean(dispersion_results[\"apogeeAltitude\"]):0.3f} m'\n",
+ " f'Apogee Altitude - Mean Value: {np.mean(dispersion_results[\"apogee_altitude\"]):0.3f} m'\n",
")\n",
"print(\n",
- " f'Apogee Altitude - Standard Deviation: {np.std(dispersion_results[\"apogeeAltitude\"]):0.3f} m'\n",
+ " f'Apogee Altitude - Standard Deviation: {np.std(dispersion_results[\"apogee_altitude\"]):0.3f} m'\n",
")\n",
"\n",
"plt.figure()\n",
- "plt.hist(dispersion_results[\"apogeeAltitude\"], bins=int(N**0.5))\n",
+ "plt.hist(dispersion_results[\"apogee_altitude\"], bins=int(N**0.5))\n",
"plt.title(\"Apogee Altitude\")\n",
"plt.xlabel(\"Altitude (m)\")\n",
"plt.ylabel(\"Number of Occurences\")\n",
@@ -811,7 +4985,7 @@
},
{
"cell_type": "code",
- "execution_count": null,
+ "execution_count": 14,
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/",
@@ -820,17 +4994,1146 @@
"id": "nGdsF9VppOQ3",
"outputId": "b4f0a3aa-afa1-4942-91b8-8ad61d263244"
},
- "outputs": [],
+ "outputs": [
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "Apogee X Position - Mean Value: 105.866 m\n",
+ "Apogee X Position - Standard Deviation: 23.319 m\n"
+ ]
+ },
+ {
+ "data": {
+ "image/svg+xml": [
+ "\n",
+ "\n",
+ "\n"
+ ],
+ "text/plain": [
+ ""
+ ]
+ },
+ "metadata": {
+ "needs_background": "light"
+ },
+ "output_type": "display_data"
+ }
+ ],
"source": [
"print(\n",
- " f'Apogee X Position - Mean Value: {np.mean(dispersion_results[\"apogeeX\"]):0.3f} m'\n",
+ " f'Apogee X Position - Mean Value: {np.mean(dispersion_results[\"apogee_x\"]):0.3f} m'\n",
")\n",
"print(\n",
- " f'Apogee X Position - Standard Deviation: {np.std(dispersion_results[\"apogeeX\"]):0.3f} m'\n",
+ " f'Apogee X Position - Standard Deviation: {np.std(dispersion_results[\"apogee_x\"]):0.3f} m'\n",
")\n",
"\n",
"plt.figure()\n",
- "plt.hist(dispersion_results[\"apogeeX\"], bins=int(N**0.5))\n",
+ "plt.hist(dispersion_results[\"apogee_x\"], bins=int(N**0.5))\n",
"plt.title(\"Apogee X Position\")\n",
"plt.xlabel(\"Apogee X Position (m)\")\n",
"plt.ylabel(\"Number of Occurences\")\n",
@@ -849,7 +6152,7 @@
},
{
"cell_type": "code",
- "execution_count": null,
+ "execution_count": 15,
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/",
@@ -858,17 +6161,1042 @@
"id": "ocq6GmeNpOQ8",
"outputId": "f3a45339-c0a6-4819-bd03-60f7fe6df963"
},
- "outputs": [],
+ "outputs": [
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "Apogee Y Position - Mean Value: 121.207 m\n",
+ "Apogee Y Position - Standard Deviation: 21.671 m\n"
+ ]
+ },
+ {
+ "data": {
+ "image/svg+xml": [
+ "\n",
+ "\n",
+ "\n"
+ ],
+ "text/plain": [
+ ""
+ ]
+ },
+ "metadata": {
+ "needs_background": "light"
+ },
+ "output_type": "display_data"
+ }
+ ],
"source": [
"print(\n",
- " f'Apogee Y Position - Mean Value: {np.mean(dispersion_results[\"apogeeY\"]):0.3f} m'\n",
+ " f'Apogee Y Position - Mean Value: {np.mean(dispersion_results[\"apogee_y\"]):0.3f} m'\n",
")\n",
"print(\n",
- " f'Apogee Y Position - Standard Deviation: {np.std(dispersion_results[\"apogeeY\"]):0.3f} m'\n",
+ " f'Apogee Y Position - Standard Deviation: {np.std(dispersion_results[\"apogee_y\"]):0.3f} m'\n",
")\n",
"\n",
"plt.figure()\n",
- "plt.hist(dispersion_results[\"apogeeY\"], bins=int(N**0.5))\n",
+ "plt.hist(dispersion_results[\"apogee_y\"], bins=int(N**0.5))\n",
"plt.title(\"Apogee Y Position\")\n",
"plt.xlabel(\"Apogee Y Position (m)\")\n",
"plt.ylabel(\"Number of Occurences\")\n",
@@ -887,7 +7215,7 @@
},
{
"cell_type": "code",
- "execution_count": null,
+ "execution_count": 16,
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/",
@@ -896,17 +7224,1018 @@
"id": "52j6t5-MpORB",
"outputId": "9cba31b1-c731-402f-b138-df5c72521408"
},
- "outputs": [],
+ "outputs": [
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "Impact Time - Mean Value: 60.556 s\n",
+ "Impact Time - Standard Deviation: 4.104 s\n"
+ ]
+ },
+ {
+ "data": {
+ "image/svg+xml": [
+ "\n",
+ "\n",
+ "\n"
+ ],
+ "text/plain": [
+ ""
+ ]
+ },
+ "metadata": {
+ "needs_background": "light"
+ },
+ "output_type": "display_data"
+ }
+ ],
"source": [
"print(\n",
- " f'Impact Time - Mean Value: {np.mean(dispersion_results[\"impactTime\"]):0.3f} s'\n",
+ " f'Impact Time - Mean Value: {np.mean(dispersion_results[\"impact_time\"]):0.3f} s'\n",
")\n",
"print(\n",
- " f'Impact Time - Standard Deviation: {np.std(dispersion_results[\"impactTime\"]):0.3f} s'\n",
+ " f'Impact Time - Standard Deviation: {np.std(dispersion_results[\"impact_time\"]):0.3f} s'\n",
")\n",
"\n",
"plt.figure()\n",
- "plt.hist(dispersion_results[\"impactTime\"], bins=int(N**0.5))\n",
+ "plt.hist(dispersion_results[\"impact_time\"], bins=int(N**0.5))\n",
"plt.title(\"Impact Time\")\n",
"plt.xlabel(\"Time (s)\")\n",
"plt.ylabel(\"Number of Occurences\")\n",
@@ -925,7 +8254,7 @@
},
{
"cell_type": "code",
- "execution_count": null,
+ "execution_count": 17,
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/",
@@ -934,17 +8263,1051 @@
"id": "uzL8-1UGpORF",
"outputId": "5c74f8d1-b909-44cf-a5c9-2f1b5e9dda1d"
},
- "outputs": [],
+ "outputs": [
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "Impact X Position - Mean Value: 345.667 m\n",
+ "Impact X Position - Standard Deviation: 38.901 m\n"
+ ]
+ },
+ {
+ "data": {
+ "image/svg+xml": [
+ "\n",
+ "\n",
+ "\n"
+ ],
+ "text/plain": [
+ ""
+ ]
+ },
+ "metadata": {
+ "needs_background": "light"
+ },
+ "output_type": "display_data"
+ }
+ ],
"source": [
"print(\n",
- " f'Impact X Position - Mean Value: {np.mean(dispersion_results[\"impactX\"]):0.3f} m'\n",
+ " f'Impact X Position - Mean Value: {np.mean(dispersion_results[\"impact_x\"]):0.3f} m'\n",
")\n",
"print(\n",
- " f'Impact X Position - Standard Deviation: {np.std(dispersion_results[\"impactX\"]):0.3f} m'\n",
+ " f'Impact X Position - Standard Deviation: {np.std(dispersion_results[\"impact_x\"]):0.3f} m'\n",
")\n",
"\n",
"plt.figure()\n",
- "plt.hist(dispersion_results[\"impactX\"], bins=int(N**0.5))\n",
+ "plt.hist(dispersion_results[\"impact_x\"], bins=int(N**0.5))\n",
"plt.title(\"Impact X Position\")\n",
"plt.xlabel(\"Impact X Position (m)\")\n",
"plt.ylabel(\"Number of Occurences\")\n",
@@ -963,7 +9326,7 @@
},
{
"cell_type": "code",
- "execution_count": null,
+ "execution_count": 18,
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/",
@@ -972,17 +9335,1051 @@
"id": "Q-ghmNVopORM",
"outputId": "cd0c81a8-a3fc-4710-cadf-a20cf0882bec"
},
- "outputs": [],
+ "outputs": [
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "Impact Y Position - Mean Value: 37.539 m\n",
+ "Impact Y Position - Standard Deviation: 32.458 m\n"
+ ]
+ },
+ {
+ "data": {
+ "image/svg+xml": [
+ "\n",
+ "\n",
+ "\n"
+ ],
+ "text/plain": [
+ ""
+ ]
+ },
+ "metadata": {
+ "needs_background": "light"
+ },
+ "output_type": "display_data"
+ }
+ ],
"source": [
"print(\n",
- " f'Impact Y Position - Mean Value: {np.mean(dispersion_results[\"impactY\"]):0.3f} m'\n",
+ " f'Impact Y Position - Mean Value: {np.mean(dispersion_results[\"impact_y\"]):0.3f} m'\n",
")\n",
"print(\n",
- " f'Impact Y Position - Standard Deviation: {np.std(dispersion_results[\"impactY\"]):0.3f} m'\n",
+ " f'Impact Y Position - Standard Deviation: {np.std(dispersion_results[\"impact_y\"]):0.3f} m'\n",
")\n",
"\n",
"plt.figure()\n",
- "plt.hist(dispersion_results[\"impactY\"], bins=int(N**0.5))\n",
+ "plt.hist(dispersion_results[\"impact_y\"], bins=int(N**0.5))\n",
"plt.title(\"Impact Y Position\")\n",
"plt.xlabel(\"Impact Y Position (m)\")\n",
"plt.ylabel(\"Number of Occurences\")\n",
@@ -1001,7 +10398,7 @@
},
{
"cell_type": "code",
- "execution_count": null,
+ "execution_count": 19,
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/",
@@ -1010,17 +10407,997 @@
"id": "Ryx7KEEVpORP",
"outputId": "90cdcf97-affc-4f09-ed2a-9b854257a8a0"
},
- "outputs": [],
+ "outputs": [
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "Impact Velocity - Mean Value: -18.355 m/s\n",
+ "Impact Velocity - Standard Deviation: 1.373 m/s\n"
+ ]
+ },
+ {
+ "data": {
+ "image/svg+xml": [
+ "\n",
+ "\n",
+ "\n"
+ ],
+ "text/plain": [
+ ""
+ ]
+ },
+ "metadata": {
+ "needs_background": "light"
+ },
+ "output_type": "display_data"
+ }
+ ],
"source": [
"print(\n",
- " f'Impact Velocity - Mean Value: {np.mean(dispersion_results[\"impactVelocity\"]):0.3f} m/s'\n",
+ " f'Impact Velocity - Mean Value: {np.mean(dispersion_results[\"impact_velocity\"]):0.3f} m/s'\n",
")\n",
"print(\n",
- " f'Impact Velocity - Standard Deviation: {np.std(dispersion_results[\"impactVelocity\"]):0.3f} m/s'\n",
+ " f'Impact Velocity - Standard Deviation: {np.std(dispersion_results[\"impact_velocity\"]):0.3f} m/s'\n",
")\n",
"\n",
"plt.figure()\n",
- "plt.hist(dispersion_results[\"impactVelocity\"], bins=int(N**0.5))\n",
+ "plt.hist(dispersion_results[\"impact_velocity\"], bins=int(N**0.5))\n",
"plt.title(\"Impact Velocity\")\n",
"# plt.grid()\n",
"plt.xlim(-35, 0)\n",
@@ -1041,7 +11418,7 @@
},
{
"cell_type": "code",
- "execution_count": null,
+ "execution_count": 20,
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/",
@@ -1050,35 +11427,1259 @@
"id": "a2Tpo9hjpORT",
"outputId": "94129858-cd6b-4af6-8f88-66923455a566"
},
- "outputs": [],
+ "outputs": [
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "Initial Static Margin - Mean Value: 1.111 c\n",
+ "Initial Static Margin - Standard Deviation: 0.291 c\n",
+ "Out of Rail Static Margin - Mean Value: 1.569 c\n",
+ "Out of Rail Static Margin - Standard Deviation: 0.290 c\n",
+ "Final Static Margin - Mean Value: 4.035 c\n",
+ "Final Static Margin - Standard Deviation: 0.290 c\n"
+ ]
+ },
+ {
+ "data": {
+ "image/svg+xml": [
+ "\n",
+ "\n",
+ "\n"
+ ],
+ "text/plain": [
+ ""
+ ]
+ },
+ "metadata": {
+ "needs_background": "light"
+ },
+ "output_type": "display_data"
+ }
+ ],
"source": [
"print(\n",
- " f'Initial Static Margin - Mean Value: {np.mean(dispersion_results[\"initialStaticMargin\"]):0.3f} c'\n",
+ " f'Initial Static Margin - Mean Value: {np.mean(dispersion_results[\"initial_static_margin\"]):0.3f} c'\n",
")\n",
"print(\n",
- " f'Initial Static Margin - Standard Deviation: {np.std(dispersion_results[\"initialStaticMargin\"]):0.3f} c'\n",
+ " f'Initial Static Margin - Standard Deviation: {np.std(dispersion_results[\"initial_static_margin\"]):0.3f} c'\n",
")\n",
"\n",
"print(\n",
- " f'Out of Rail Static Margin - Mean Value: {np.mean(dispersion_results[\"outOfRailStaticMargin\"]):0.3f} c'\n",
+ " f'Out of Rail Static Margin - Mean Value: {np.mean(dispersion_results[\"out_of_rail_static_margin\"]):0.3f} c'\n",
")\n",
"print(\n",
- " f'Out of Rail Static Margin - Standard Deviation: {np.std(dispersion_results[\"outOfRailStaticMargin\"]):0.3f} c'\n",
+ " f'Out of Rail Static Margin - Standard Deviation: {np.std(dispersion_results[\"out_of_rail_static_margin\"]):0.3f} c'\n",
")\n",
"\n",
"print(\n",
- " f'Final Static Margin - Mean Value: {np.mean(dispersion_results[\"finalStaticMargin\"]):0.3f} c'\n",
+ " f'Final Static Margin - Mean Value: {np.mean(dispersion_results[\"final_static_margin\"]):0.3f} c'\n",
")\n",
"print(\n",
- " f'Final Static Margin - Standard Deviation: {np.std(dispersion_results[\"finalStaticMargin\"]):0.3f} c'\n",
+ " f'Final Static Margin - Standard Deviation: {np.std(dispersion_results[\"final_static_margin\"]):0.3f} c'\n",
")\n",
"\n",
"plt.figure()\n",
- "plt.hist(dispersion_results[\"initialStaticMargin\"], label=\"Initial\", bins=int(N**0.5))\n",
+ "plt.hist(dispersion_results[\"initial_static_margin\"], label=\"Initial\", bins=int(N**0.5))\n",
"plt.hist(\n",
- " dispersion_results[\"outOfRailStaticMargin\"], label=\"Out of Rail\", bins=int(N**0.5)\n",
+ " dispersion_results[\"out_of_rail_static_margin\"], label=\"Out of Rail\", bins=int(N**0.5)\n",
")\n",
- "plt.hist(dispersion_results[\"finalStaticMargin\"], label=\"Final\", bins=int(N**0.5))\n",
+ "plt.hist(dispersion_results[\"final_static_margin\"], label=\"Final\", bins=int(N**0.5))\n",
"plt.legend()\n",
"plt.title(\"Static Margin\")\n",
"plt.xlabel(\"Static Margin (c)\")\n",
@@ -1098,7 +12699,7 @@
},
{
"cell_type": "code",
- "execution_count": null,
+ "execution_count": 21,
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/",
@@ -1107,17 +12708,1005 @@
"id": "nOu1O8MXpORY",
"outputId": "7510aec8-7b73-4751-f033-8367cd0c9bdc"
},
- "outputs": [],
+ "outputs": [
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "Maximum Velocity - Mean Value: 123.363 m/s\n",
+ "Maximum Velocity - Standard Deviation: 7.196 m/s\n"
+ ]
+ },
+ {
+ "data": {
+ "image/svg+xml": [
+ "\n",
+ "\n",
+ "\n"
+ ],
+ "text/plain": [
+ ""
+ ]
+ },
+ "metadata": {
+ "needs_background": "light"
+ },
+ "output_type": "display_data"
+ }
+ ],
"source": [
"print(\n",
- " f'Maximum Velocity - Mean Value: {np.mean(dispersion_results[\"maxVelocity\"]):0.3f} m/s'\n",
+ " f'Maximum Velocity - Mean Value: {np.mean(dispersion_results[\"max_velocity\"]):0.3f} m/s'\n",
")\n",
"print(\n",
- " f'Maximum Velocity - Standard Deviation: {np.std(dispersion_results[\"maxVelocity\"]):0.3f} m/s'\n",
+ " f'Maximum Velocity - Standard Deviation: {np.std(dispersion_results[\"max_velocity\"]):0.3f} m/s'\n",
")\n",
"\n",
"plt.figure()\n",
- "plt.hist(dispersion_results[\"maxVelocity\"], bins=int(N**0.5))\n",
+ "plt.hist(dispersion_results[\"max_velocity\"], bins=int(N**0.5))\n",
"plt.title(\"Maximum Velocity\")\n",
"plt.xlabel(\"Velocity (m/s)\")\n",
"plt.ylabel(\"Number of Occurences\")\n",
@@ -1138,7 +13727,7 @@
},
{
"cell_type": "code",
- "execution_count": null,
+ "execution_count": 22,
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/",
@@ -1147,10 +13736,972 @@
"id": "yhcWi2kCpORb",
"outputId": "dee54569-8213-46cc-e287-9fffd2b8e43c"
},
- "outputs": [],
+ "outputs": [
+ {
+ "data": {
+ "image/svg+xml": [
+ "\n",
+ "\n",
+ "\n"
+ ],
+ "text/plain": [
+ ""
+ ]
+ },
+ "metadata": {
+ "needs_background": "light"
+ },
+ "output_type": "display_data"
+ }
+ ],
"source": [
"plt.figure()\n",
- "plt.hist(dispersion_results[\"numberOfEvents\"])\n",
+ "plt.hist(dispersion_results[\"number_of_events\"])\n",
"plt.title(\"Parachute Events\")\n",
"plt.xlabel(\"Number of Parachute Events\")\n",
"plt.ylabel(\"Number of Occurences\")\n",
@@ -1169,7 +14720,7 @@
},
{
"cell_type": "code",
- "execution_count": null,
+ "execution_count": 23,
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/",
@@ -1178,17 +14729,1062 @@
"id": "lvCksZG8pORf",
"outputId": "3efd19ed-11e9-41d1-8e66-04da384665ce"
},
- "outputs": [],
+ "outputs": [
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "Drogue Parachute Trigger Time - Mean Value: 14.136 s\n",
+ "Drogue Parachute Trigger Time - Standard Deviation: 0.433 s\n"
+ ]
+ },
+ {
+ "data": {
+ "image/svg+xml": [
+ "\n",
+ "\n",
+ "\n"
+ ],
+ "text/plain": [
+ ""
+ ]
+ },
+ "metadata": {
+ "needs_background": "light"
+ },
+ "output_type": "display_data"
+ }
+ ],
"source": [
"print(\n",
- " f'Drogue Parachute Trigger Time - Mean Value: {np.mean(dispersion_results[\"drogueTriggerTime\"]):0.3f} s'\n",
+ " f'Drogue Parachute Trigger Time - Mean Value: {np.mean(dispersion_results[\"drogue_triggerTime\"]):0.3f} s'\n",
")\n",
"print(\n",
- " f'Drogue Parachute Trigger Time - Standard Deviation: {np.std(dispersion_results[\"drogueTriggerTime\"]):0.3f} s'\n",
+ " f'Drogue Parachute Trigger Time - Standard Deviation: {np.std(dispersion_results[\"drogue_triggerTime\"]):0.3f} s'\n",
")\n",
"\n",
"plt.figure()\n",
- "plt.hist(dispersion_results[\"drogueTriggerTime\"], bins=int(N**0.5))\n",
+ "plt.hist(dispersion_results[\"drogue_triggerTime\"], bins=int(N**0.5))\n",
"plt.title(\"Drogue Parachute Trigger Time\")\n",
"plt.xlabel(\"Time (s)\")\n",
"plt.ylabel(\"Number of Occurences\")\n",
@@ -1207,7 +15803,7 @@
},
{
"cell_type": "code",
- "execution_count": null,
+ "execution_count": 24,
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/",
@@ -1216,17 +15812,1219 @@
"id": "KCYKVFYXpORj",
"outputId": "8ae49853-0f08-4bf6-9bd8-91a7c9a9448d"
},
- "outputs": [],
+ "outputs": [
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "Drogue Parachute Fully Inflated Time - Mean Value: 15.663 s\n",
+ "Drogue Parachute Fully Inflated Time - Standard Deviation: 0.392 s\n"
+ ]
+ },
+ {
+ "data": {
+ "image/svg+xml": [
+ "\n",
+ "\n",
+ "\n"
+ ],
+ "text/plain": [
+ ""
+ ]
+ },
+ "metadata": {
+ "needs_background": "light"
+ },
+ "output_type": "display_data"
+ }
+ ],
"source": [
"print(\n",
- " f'Drogue Parachute Fully Inflated Time - Mean Value: {np.mean(dispersion_results[\"drogueInflatedTime\"]):0.3f} s'\n",
+ " f'Drogue Parachute Fully Inflated Time - Mean Value: {np.mean(dispersion_results[\"drogue_inflated_time\"]):0.3f} s'\n",
")\n",
"print(\n",
- " f'Drogue Parachute Fully Inflated Time - Standard Deviation: {np.std(dispersion_results[\"drogueInflatedTime\"]):0.3f} s'\n",
+ " f'Drogue Parachute Fully Inflated Time - Standard Deviation: {np.std(dispersion_results[\"drogue_inflated_time\"]):0.3f} s'\n",
")\n",
"\n",
"plt.figure()\n",
- "plt.hist(dispersion_results[\"drogueInflatedTime\"], bins=int(N**0.5))\n",
+ "plt.hist(dispersion_results[\"drogue_inflated_time\"], bins=int(N**0.5))\n",
"plt.title(\"Drogue Parachute Fully Inflated Time\")\n",
"plt.xlabel(\"Time (s)\")\n",
"plt.ylabel(\"Number of Occurences\")\n",
@@ -1245,7 +17043,7 @@
},
{
"cell_type": "code",
- "execution_count": null,
+ "execution_count": 25,
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/",
@@ -1254,17 +17052,1197 @@
"id": "KxrpPUzqpORn",
"outputId": "9c102bdb-b805-4aa1-b3a2-1ac329c76976"
},
- "outputs": [],
+ "outputs": [
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "Drogue Parachute Fully Inflated Velocity - Mean Value: 18.660 m/s\n",
+ "Drogue Parachute Fully Inflated Velocity - Standard Deviation: 3.021 m/s\n"
+ ]
+ },
+ {
+ "data": {
+ "image/svg+xml": [
+ "\n",
+ "\n",
+ "\n"
+ ],
+ "text/plain": [
+ ""
+ ]
+ },
+ "metadata": {
+ "needs_background": "light"
+ },
+ "output_type": "display_data"
+ }
+ ],
"source": [
"print(\n",
- " f'Drogue Parachute Fully Inflated Velocity - Mean Value: {np.mean(dispersion_results[\"drogueInflatedVelocity\"]):0.3f} m/s'\n",
+ " f'Drogue Parachute Fully Inflated Velocity - Mean Value: {np.mean(dispersion_results[\"drogue_inflated_velocity\"]):0.3f} m/s'\n",
")\n",
"print(\n",
- " f'Drogue Parachute Fully Inflated Velocity - Standard Deviation: {np.std(dispersion_results[\"drogueInflatedVelocity\"]):0.3f} m/s'\n",
+ " f'Drogue Parachute Fully Inflated Velocity - Standard Deviation: {np.std(dispersion_results[\"drogue_inflated_velocity\"]):0.3f} m/s'\n",
")\n",
"\n",
"plt.figure()\n",
- "plt.hist(dispersion_results[\"drogueInflatedVelocity\"], bins=int(N**0.5))\n",
+ "plt.hist(dispersion_results[\"drogue_inflated_velocity\"], bins=int(N**0.5))\n",
"plt.title(\"Drogue Parachute Fully Inflated Velocity\")\n",
"plt.xlabel(\"Velocity m/s)\")\n",
"plt.ylabel(\"Number of Occurences\")\n",
@@ -1283,7 +18261,7 @@
},
{
"cell_type": "code",
- "execution_count": null,
+ "execution_count": 26,
"metadata": {
"cellView": "both",
"colab": {
@@ -1293,7 +18271,1526 @@
"id": "DZRrk_bIr3iG",
"outputId": "b4a5a583-7f53-473a-bec2-2636cdf28a7c"
},
- "outputs": [],
+ "outputs": [
+ {
+ "name": "stderr",
+ "output_type": "stream",
+ "text": [
+ "C:\\Users\\GiovaniCeotto\\AppData\\Local\\Temp\\ipykernel_6612\\290763576.py:6: DeprecationWarning: Starting with ImageIO v3 the behavior of this function will switch to that of iio.v3.imread. To keep the current behavior (and make this warning disappear) use `import imageio.v2 as imageio` or call `imageio.v2.imread` directly.\n",
+ " img = imread(\"dispersion_analysis_inputs/Valetudo_basemap_final.jpg\")\n"
+ ]
+ },
+ {
+ "data": {
+ "image/svg+xml": [
+ "\n",
+ "\n",
+ "\n"
+ ],
+ "text/plain": [
+ ""
+ ]
+ },
+ "metadata": {},
+ "output_type": "display_data"
+ }
+ ],
"source": [
"# Import libraries\n",
"from imageio import imread\n",
@@ -1303,10 +19800,10 @@
"img = imread(\"dispersion_analysis_inputs/Valetudo_basemap_final.jpg\")\n",
"\n",
"# Retrieve dispersion data por apogee and impact XY position\n",
- "apogeeX = np.array(dispersion_results[\"apogeeX\"])\n",
- "apogeeY = np.array(dispersion_results[\"apogeeY\"])\n",
- "impactX = np.array(dispersion_results[\"impactX\"])\n",
- "impactY = np.array(dispersion_results[\"impactY\"])\n",
+ "apogee_x = np.array(dispersion_results[\"apogee_x\"])\n",
+ "apogee_y = np.array(dispersion_results[\"apogee_y\"])\n",
+ "impact_x = np.array(dispersion_results[\"impact_x\"])\n",
+ "impact_y = np.array(dispersion_results[\"impact_y\"])\n",
"\n",
"# Define function to calculate eigen values\n",
"def eigsorted(cov):\n",
@@ -1320,7 +19817,7 @@
"ax = plt.subplot(111)\n",
"\n",
"# Calculate error ellipses for impact\n",
- "impactCov = np.cov(impactX, impactY)\n",
+ "impactCov = np.cov(impact_x, impact_y)\n",
"impactVals, impactVecs = eigsorted(impactCov)\n",
"impactTheta = np.degrees(np.arctan2(*impactVecs[:, 0][::-1]))\n",
"impactW, impactH = 2 * np.sqrt(impactVals)\n",
@@ -1329,7 +19826,7 @@
"impact_ellipses = []\n",
"for j in [1, 2, 3]:\n",
" impactEll = Ellipse(\n",
- " xy=(np.mean(impactX), np.mean(impactY)),\n",
+ " xy=(np.mean(impact_x), np.mean(impact_y)),\n",
" width=impactW * j,\n",
" height=impactH * j,\n",
" angle=impactTheta,\n",
@@ -1340,7 +19837,7 @@
" ax.add_artist(impactEll)\n",
"\n",
"# Calculate error ellipses for apogee\n",
- "apogeeCov = np.cov(apogeeX, apogeeY)\n",
+ "apogeeCov = np.cov(apogee_x, apogee_y)\n",
"apogeeVals, apogeeVecs = eigsorted(apogeeCov)\n",
"apogeeTheta = np.degrees(np.arctan2(*apogeeVecs[:, 0][::-1]))\n",
"apogeeW, apogeeH = 2 * np.sqrt(apogeeVals)\n",
@@ -1348,7 +19845,7 @@
"# Draw error ellipses for apogee\n",
"for j in [1, 2, 3]:\n",
" apogeeEll = Ellipse(\n",
- " xy=(np.mean(apogeeX), np.mean(apogeeY)),\n",
+ " xy=(np.mean(apogee_x), np.mean(apogee_y)),\n",
" width=apogeeW * j,\n",
" height=apogeeH * j,\n",
" angle=apogeeTheta,\n",
@@ -1360,10 +19857,10 @@
"# Draw launch point\n",
"plt.scatter(0, 0, s=30, marker=\"*\", color=\"black\", label=\"Launch Point\")\n",
"# Draw apogee points\n",
- "plt.scatter(apogeeX, apogeeY, s=5, marker=\"^\", color=\"green\", label=\"Simulated Apogee\")\n",
+ "plt.scatter(apogee_x, apogee_y, s=5, marker=\"^\", color=\"green\", label=\"Simulated Apogee\")\n",
"# Draw impact points\n",
"plt.scatter(\n",
- " impactX, impactY, s=5, marker=\"v\", color=\"blue\", label=\"Simulated Landing Point\"\n",
+ " impact_x, impact_y, s=5, marker=\"v\", color=\"blue\", label=\"Simulated Landing Point\"\n",
")\n",
"# Draw real landing point\n",
"plt.scatter(\n",
@@ -1424,8 +19921,16 @@
"name": "python3"
},
"language_info": {
+ "codemirror_mode": {
+ "name": "ipython",
+ "version": 3
+ },
+ "file_extension": ".py",
+ "mimetype": "text/x-python",
"name": "python",
- "version": "3.10.5"
+ "nbconvert_exporter": "python",
+ "pygments_lexer": "ipython3",
+ "version": "3.10.0"
},
"vscode": {
"interpreter": {