Merge pull request #549 from RocketPy-Team/enh/dispersion-renaming

MNT: Dispersion Renaming

Author: Gui-FernandesBR

docs/notebooks/dispersion_analysis/dispersion_analysis.ipynb renamed to docs/notebooks/monte_carlo_analysis/monte_carlo_analysis.ipynb

@@ -40,7 +40,7 @@
     "!git clone https://github.com/RocketPy-Team/RocketPy.git\n",
     "import os\n",
     "\n",
-    "os.chdir(\"RocketPy/docs/notebooks/dispersion_analysis\")"
+    "os.chdir(\"RocketPy/docs/notebooks/monte_carlo_analysis\")"
    ]
   },
   {
@@ -382,7 +382,7 @@
    ],
    "source": [
     "# Basic analysis info\n",
-    "filename = \"dispersion_analysis_outputs/valetudo_rocket_v0\"\n",
+    "filename = \"monte_carlo_analysis_outputs/valetudo_rocket_v0\"\n",
     "number_of_simulations = 100\n",
     "\n",
     "# Create data files for inputs, outputs and error logging\n",
@@ -402,7 +402,7 @@
     "Env.max_expected_height = 1500\n",
     "Env.set_atmospheric_model(\n",
     "    type=\"Ensemble\",\n",
-    "    file=\"dispersion_analysis_inputs/LASC2019_reanalysis.nc\",\n",
+    "    file=\"monte_carlo_analysis_inputs/LASC2019_reanalysis.nc\",\n",
     "    dictionary=\"ECMWF\",\n",
     ")\n",
     "\n",
@@ -426,7 +426,7 @@
     "\n",
     "    # Create motor\n",
     "    Keron = SolidMotor(\n",
-    "        thrust_source=\"dispersion_analysis_inputs/thrustCurve.csv\",\n",
+    "        thrust_source=\"monte_carlo_analysis_inputs/thrustCurve.csv\",\n",
     "        burn_time=5.274,\n",
     "        reshape_thrust_curve=(setting[\"burn_time\"], setting[\"impulse\"]),\n",
     "        nozzle_radius=setting[\"nozzle_radius\"],\n",
@@ -458,8 +458,8 @@
     "            setting[\"rocket_inertia_11\"],\n",
     "            setting[\"rocket_inertia_33\"],\n",
     "        ),\n",
-    "        power_off_drag=\"dispersion_analysis_inputs/Cd_PowerOff.csv\",\n",
-    "        power_on_drag=\"dispersion_analysis_inputs/Cd_PowerOn.csv\",\n",
+    "        power_off_drag=\"monte_carlo_analysis_inputs/Cd_PowerOff.csv\",\n",
+    "        power_on_drag=\"monte_carlo_analysis_inputs/Cd_PowerOn.csv\",\n",
     "        center_of_mass_without_motor=0,\n",
     "        coordinate_system_orientation=\"tail_to_nose\",\n",
     "    )\n",
@@ -572,7 +572,7 @@
     }
    ],
    "source": [
-    "filename = \"dispersion_analysis_outputs/valetudo_rocket_v0\"\n",
+    "filename = \"monte_carlo_analysis_outputs/valetudo_rocket_v0\"\n",
     "\n",
     "# Initialize variable to store all results\n",
     "dispersion_general_results = []\n",
@@ -12892,9 +12892,7 @@
     ")\n",
     "\n",
     "plt.figure()\n",
-    "plt.hist(\n",
-    "    dispersion_results[\"initial_static_margin\"], label=\"Initial\", bins=int(N**0.5)\n",
-    ")\n",
+    "plt.hist(dispersion_results[\"initial_static_margin\"], label=\"Initial\", bins=int(N**0.5))\n",
     "plt.hist(\n",
     "    dispersion_results[\"out_of_rail_static_margin\"],\n",
     "    label=\"Out of Rail\",\n",
@@ -20354,7 +20352,7 @@
     "from matplotlib.patches import Ellipse\n",
     "\n",
     "# Import background map\n",
-    "img = imread(\"dispersion_analysis_inputs/Valetudo_basemap_final.jpg\")\n",
+    "img = imread(\"monte_carlo_analysis_inputs/Valetudo_basemap_final.jpg\")\n",
     "\n",
     "# Retrieve dispersion data por apogee and impact XY position\n",
     "apogee_x = np.array(dispersion_results[\"apogee_x\"])\n",

docs/notebooks/dispersion_analysis/dispersion_analysis_inputs/Cd_PowerOff.csv renamed to docs/notebooks/monte_carlo_analysis/monte_carlo_analysis_inputs/Cd_PowerOff.csv

@@ -34,7 +34,7 @@
     "!git clone https://github.com/giovaniceotto/RocketPy.git\n",
     "import os\n",
     "\n",
-    "os.chdir(\"RocketPy/docs/notebooks/dispersion_analysis\")"
+    "os.chdir(\"RocketPy/docs/notebooks/monte_carlo_analysis\")"
    ]
   },
   {
@@ -391,7 +391,7 @@
    "outputs": [],
    "source": [
     "# Basic analysis info\n",
-    "filename = \"dispersion_analysis_outputs/parachute_drop_from_helicopter\"\n",
+    "filename = \"monte_carlo_analysis_outputs/parachute_drop_from_helicopter\"\n",
     "number_of_simulations = 4000\n",
     "\n",
     "# Create data files for inputs, outputs and error logging\n",
@@ -413,7 +413,7 @@
     "Env.maxExpectedHeight = 1500\n",
     "Env.setAtmosphericModel(\n",
     "    type=\"Ensemble\",\n",
-    "    file=\"dispersion_analysis_inputs/LASC2019_reanalysis.nc\",\n",
+    "    file=\"monte_carlo_analysis_inputs/LASC2019_reanalysis.nc\",\n",
     "    dictionary=\"ECMWF\",\n",
     ")\n",
     "\n",
@@ -436,7 +436,7 @@
     "\n",
     "    # Create motor\n",
     "    Keron = SolidMotor(\n",
-    "        thrustSource=\"dispersion_analysis_inputs/thrustCurve.csv\",\n",
+    "        thrustSource=\"monte_carlo_analysis_inputs/thrustCurve.csv\",\n",
     "        burn_time=5.274,\n",
     "        reshapeThrustCurve=(setting[\"burn_time\"], setting[\"impulse\"]),\n",
     "        nozzle_radius=setting[\"nozzle_radius\"],\n",
@@ -459,8 +459,8 @@
     "        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",
+    "        powerOffDrag=\"monte_carlo_analysis_inputs/Cd_PowerOff.csv\",\n",
+    "        powerOnDrag=\"monte_carlo_analysis_inputs/Cd_PowerOn.csv\",\n",
     "        centerOfDryMassPosition=0,\n",
     "        coordinateSystemOrientation=\"tailToNose\",\n",
     "    )\n",
@@ -581,7 +581,7 @@
    },
    "outputs": [],
    "source": [
-    "filename = \"dispersion_analysis_outputs/parachute_drop_from_helicopter\"\n",
+    "filename = \"monte_carlo_analysis_outputs/parachute_drop_from_helicopter\"\n",
     "\n",
     "# Initialize variable to store all results\n",
     "dispersion_general_results = []\n",
@@ -1165,7 +1165,7 @@
     "from matplotlib.patches import Ellipse\n",
     "\n",
     "# Import background map\n",
-    "img = imread(\"dispersion_analysis_inputs/Valetudo_basemap_final.jpg\")\n",
+    "img = imread(\"monte_carlo_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",

docs/notebooks/dispersion_analysis/dispersion_analysis_inputs/Cd_PowerOn.csv renamed to docs/notebooks/monte_carlo_analysis/monte_carlo_analysis_inputs/Cd_PowerOn.csv

@@ -661,7 +661,7 @@ analysis. Here we will show some examples, but much more can be done!
 .. seealso::
     *RocketPy* can be used to perform a Monte Carlo Dispersion Analysis.
     See 
-    `Monte Carlo Simulations <https://colab.research.google.com/github/RocketPy-Team/rocketpy/blob/master/docs/notebooks/dispersion_analysis/dispersion_analysis.html>`_ 
+    `Monte Carlo Simulations <https://colab.research.google.com/github/RocketPy-Team/rocketpy/blob/master/docs/notebooks/monte_carlo_analysis/monte_carlo_analysis.html>`_ 
     for more information.
 
 Apogee as a Function of Mass

docs/notebooks/dispersion_analysis/dispersion_analysis_inputs/LASC2019_reanalysis.nc renamed to docs/notebooks/monte_carlo_analysis/monte_carlo_analysis_inputs/LASC2019_reanalysis.nc

@@ -29,8 +29,8 @@ RocketPy's User Guide
    :maxdepth: 2
    :caption: Dispersion Analysis
 
-   ../notebooks/dispersion_analysis/dispersion_analysis.ipynb  
-   ../notebooks/dispersion_analysis/parachute_drop_from_helicopter.ipynb
+   ../notebooks/monte_carlo_analysis/monte_carlo_analysis.ipynb  
+   ../notebooks/monte_carlo_analysis/parachute_drop_from_helicopter.ipynb
 
 .. toctree::
    :maxdepth: 2

docs/notebooks/dispersion_analysis/dispersion_analysis_inputs/Valetudo_basemap_final.jpg renamed to docs/notebooks/monte_carlo_analysis/monte_carlo_analysis_inputs/Valetudo_basemap_final.jpg

@@ -5,16 +5,16 @@
     funcify_method,
     reset_funcified_methods,
 )
-from .monte_carlo import (
-    McEllipticalFins,
-    McEnvironment,
-    McFlight,
-    McNoseCone,
-    McParachute,
-    McRocket,
-    McSolidMotor,
-    McTail,
-    McTrapezoidalFins,
+from .stochastic import (
+    StochasticEllipticalFins,
+    StochasticEnvironment,
+    StochasticFlight,
+    StochasticNoseCone,
+    StochasticParachute,
+    StochasticRocket,
+    StochasticSolidMotor,
+    StochasticTail,
+    StochasticTrapezoidalFins,
 )
 from .motors import (
     CylindricalTank,
@@ -45,5 +45,5 @@
     Tail,
     TrapezoidalFins,
 )
-from .simulation import Flight, Dispersion
+from .simulation import Flight, MonteCarlo
 from .plots.compare import Compare, CompareFlights

docs/notebooks/dispersion_analysis/dispersion_analysis_inputs/thrustCurve.csv renamed to docs/notebooks/monte_carlo_analysis/monte_carlo_analysis_inputs/thrustCurve.csv

@@ -1,21 +1,13 @@
-__author__ = (
-    "Mateus Stano Junqueira, Guilherme Fernandes Alves, Bruno Abdulklech Sorban"
-)
-__copyright__ = "Copyright 20XX, RocketPy Team"
-__license__ = "MIT"
-
-
 import matplotlib.pyplot as plt
 
-from ..tools import generate_dispersion_ellipses
+from ..tools import generate_monte_carlo_ellipses
 
 
-class _DispersionPlots:
-    """Class to plot the dispersion results of the dispersion analysis."""
+class _MonteCarloPlots:
+    """Class to plot the monte carlo analysis results."""
 
-    def __init__(self, dispersion):
-        self.dispersion = dispersion
-        return None
+    def __init__(self, monte_carlo):
+        self.monte_carlo = monte_carlo
 
     def ellipses(
         self,
@@ -36,7 +28,7 @@ def ellipses(
             The path to the image to be used as the background
         actual_landing_point : tuple, optional
             A tuple containing the actual landing point of the rocket, if known.
-            Useful when comparing the dispersion results with the actual landing.
+            Useful when comparing the Monte Carlo results with the actual landing.
             Must be given in tuple format, such as (x, y) in meters.
             By default None.
         perimeterSize : int, optional
@@ -76,7 +68,7 @@ def ellipses(
             apogeeY,
             impactX,
             impactY,
-        ) = generate_dispersion_ellipses(self.dispersion.results)
+        ) = generate_monte_carlo_ellipses(self.monte_carlo.results)
 
         # Create plot figure
         plt.figure(num=None, figsize=(8, 6), dpi=150, facecolor="w", edgecolor="k")
@@ -117,7 +109,8 @@ def ellipses(
 
         # Add title and labels to plot
         ax.set_title(
-            "1$\\sigma$, 2$\\sigma$ and 3$\\sigma$ Dispersion Ellipses: Apogee and Landing Points"
+            "1$\\sigma$, 2$\\sigma$ and 3$\\sigma$ "
+            + "Monte Carlo Ellipses: Apogee and Landing Points"
         )
         ax.set_ylabel("North (m)")
         ax.set_xlabel("East (m)")
@@ -146,16 +139,15 @@ def ellipses(
         # Save plot and show result
         if save:
             plt.savefig(
-                str(self.dispersion.filename) + ".png",
+                str(self.monte_carlo.filename) + ".png",
                 bbox_inches="tight",
                 pad_inches=0,
             )
         else:
             plt.show()
-        return None
 
     def all_results(self, keys=None):
-        """Plot the results of the dispersion analysis.
+        """Plot the results of the Monte Carlo analysis.
 
         Parameters
         ----------
@@ -169,11 +161,11 @@ def all_results(self, keys=None):
         """
 
         if keys is None:
-            keys = self.dispersion.results.keys()
+            keys = self.monte_carlo.results.keys()
         elif isinstance(keys, str):
             keys = [keys]
         elif isinstance(keys, (list, tuple)):
-            keys = list(set(keys).intersection(self.dispersion.results.keys()))
+            keys = list(set(keys).intersection(self.monte_carlo.results.keys()))
             if len(keys) == 0:
                 raise ValueError(
                     "The selected 'keys' are not available in the results. "
@@ -187,10 +179,8 @@ def all_results(self, keys=None):
         for key in keys:
             plt.figure()
             plt.hist(
-                self.dispersion.results[key],
+                self.monte_carlo.results[key],
             )
             plt.title("Histogram of " + key)
             plt.ylabel("Number of Occurrences")
             plt.show()
-
-        return None

docs/notebooks/dispersion_analysis/dispersion_analysis_outputs/parachute_drop_from_helicopter.disp_errors.txt renamed to docs/notebooks/monte_carlo_analysis/monte_carlo_analysis_outputs/parachute_drop_from_helicopter.disp_errors.txt

@@ -1,13 +1,8 @@
-__author__ = "Guilherme Fernandes Alves"
-__copyright__ = "Copyright 20XX, RocketPy Team"
-__license__ = "MIT"
+class _MonteCarloPrints:
+    """Class to print the monte carlo analysis results."""
 
-
-class _DispersionPrints:
-    """Class to print the dispersion results of the dispersion analysis."""
-
-    def __init__(self, dispersion):
-        self.dispersion = dispersion
+    def __init__(self, monte_carlo):
+        self.monte_carlo = monte_carlo
         return None
 
     def all_results(self):
@@ -24,12 +19,12 @@ def all_results(self):
 
         """
         print("Monte Carlo Simulation by RocketPy")
-        print("Data Source: ", self.dispersion.filename)
-        print("Number of simulations: ", self.dispersion.num_of_loaded_sims)
+        print("Data Source: ", self.monte_carlo.filename)
+        print("Number of simulations: ", self.monte_carlo.num_of_loaded_sims)
         print("Results: \n")
         print("{:>25} {:>15} {:>15}".format("Parameter", "Mean", "Std. Dev."))
         print("-" * 60)
-        for key, value in self.dispersion.processed_results.items():
+        for key, value in self.monte_carlo.processed_results.items():
             print("{:>25} {:>15.3f} {:>15.3f}".format(key, value[0], value[1]))
 
         return None

docs/notebooks/dispersion_analysis/dispersion_analysis_outputs/parachute_drop_from_helicopter.disp_inputs.txt renamed to docs/notebooks/monte_carlo_analysis/monte_carlo_analysis_outputs/parachute_drop_from_helicopter.disp_inputs.txt

@@ -1,3 +1,3 @@
-from .dispersion import Dispersion
+from .monte_carlo import MonteCarlo
 from .flight import Flight
 from .flight_data_importer import FlightDataImporter