MNT: minor fixes

- Add module docstrings
- Fix one camelCase variable
- Fix too long lines
- Adjust one unpacking tuble

rocketpy/plots/monte_carlo_plots.py

@@ -13,7 +13,7 @@ def ellipses(
         self,
         image=None,
         actual_landing_point=None,
-        perimeterSize=3000,
+        perimeter_size=3000,
         xlim=(-3000, 3000),
         ylim=(-3000, 3000),
         save=False,
@@ -31,7 +31,7 @@ def ellipses(
             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
+        perimeter_size : int, optional
             The size of the perimeter to be plotted. The default is 3000.
         xlim : tuple, optional
             The limits of the x axis. The default is (-3000, 3000).
@@ -127,10 +127,10 @@ def ellipses(
                 img,
                 zorder=0,
                 extent=[
-                    -perimeterSize - dx,
-                    perimeterSize - dx,
-                    -perimeterSize - dy,
-                    perimeterSize - dy,
+                    -perimeter_size - dx,
+                    perimeter_size - dx,
+                    -perimeter_size - dy,
+                    perimeter_size - dy,
                 ],
             )
         plt.axhline(0, color="black", linewidth=0.5)

rocketpy/simulation/monte_carlo.py

@@ -1,3 +1,5 @@
+"""Defines the MonteCarlo class."""
+
 import json
 from time import process_time, time
 
@@ -12,11 +14,7 @@
     generate_monte_carlo_ellipses_coordinates,
 )
 
-# TODO: How to save Functions? With pickle? Save just the source?
-
-# TODO: create a method that recreates each flight from inputs_log
-# and saves it in an attribute that is a list
-
+# TODO: Let Functions and Flights be json serializable
 # TODO: Create evolution plots to analyze convergence
 
 
@@ -669,10 +667,7 @@ def export_ellipses_to_kml(
         (
             impact_ellipses,
             apogee_ellipses,
-            _,
-            _,
-            _,
-            _,
+            *_,
         ) = generate_monte_carlo_ellipses(self.results)
         outputs = []
 

rocketpy/stochastic/__init__.py

@@ -1,3 +1,7 @@
+"""The rocketpy.stochastic module contains classes that are used to generate
+randomized objects based on the provided information. Each of the classes
+defined here represent one different rocketpy class."""
+
 from .stochastic_aero_surfaces import (
     StochasticEllipticalFins,
     StochasticNoseCone,

rocketpy/stochastic/stochastic_aero_surfaces.py

@@ -1,3 +1,6 @@
+"""Defines the StochasticNoseCone, StochasticTrapezoidalFins,
+StochasticEllipticalFins, StochasticTail and StochasticRailButtons classes."""
+
 from rocketpy.rocket.aero_surface import (
     EllipticalFins,
     NoseCone,

rocketpy/stochastic/stochastic_environment.py

@@ -1,3 +1,5 @@
+"""Defines the StochasticEnvironment class."""
+
 from .stochastic_model import StochasticModel
 
 
@@ -112,7 +114,10 @@ def __str__(self):
             if isinstance(value, tuple):
                 try:
                     # Format the tuple as a string with the mean and standard deviation.
-                    value_str = f"{value[0]:.5f} ± {value[1]:.5f} (numpy.random.{value[2].__name__})"
+                    value_str = (
+                        f"{value[0]:.5f} ± {value[1]:.5f} "
+                        f"(numpy.random.{value[2].__name__})"
+                    )
                 except AttributeError:
                     # treats date attribute
                     value_str = str(value)
@@ -167,7 +172,10 @@ def _validate_ensemble(self, ensemble_member, environment):
                 <= min(ensemble_member)
                 <= max(ensemble_member)
                 < environment.num_ensemble_members
-            ), f"`ensemble_member` must be in the range from 0 to {environment.num_ensemble_members - 1}"
+            ), (
+                "`ensemble_member` must be in the range from 0 to "
+                + f"{environment.num_ensemble_members - 1}"
+            )
             setattr(self, "ensemble_member", ensemble_member)
         else:
             # if no ensemble member is provided, get it from the environment
@@ -191,8 +199,7 @@ def create_object(self):
         generated_dict = next(self.dict_generator())
         for key, value in generated_dict.items():
             # special case for ensemble member
-            # TODO if env.ensemble_member had a setter this create_object method
-            # could be generalized
+            # TODO: Generalize create_object() with a env.ensemble_member setter
             if key == "ensemble_member":
                 self.object.select_ensemble_member(value)
             else:

rocketpy/stochastic/stochastic_flight.py

@@ -1,3 +1,5 @@
+"""Defines the StochasticFlight class."""
+
 from rocketpy.simulation import Flight
 
 from .stochastic_model import StochasticModel
@@ -95,7 +97,7 @@ def _validate_initial_solution(self, initial_solution):
                     "e3_init, w1Init, w2Init, w3Init"
                 )
                 assert all(
-                    [isinstance(i, (int, float)) for i in initial_solution]
+                    isinstance(i, (int, float)) for i in initial_solution
                 ), "`initial_solution` must be a tuple of numbers"
             else:
                 raise TypeError("`initial_solution` must be a tuple of numbers")

rocketpy/stochastic/stochastic_generic_motor.py

@@ -1,3 +1,5 @@
+"""Defines the StochasticGenericMotor class."""
+
 from rocketpy.motors import GenericMotor
 
 from .stochastic_motor_model import StochasticMotorModel

rocketpy/stochastic/stochastic_model.py

@@ -1,3 +1,6 @@
+"""Defines the StochasticModel class, which will be used as a base class for all
+other Stochastic classes."""
+
 from random import choice
 
 import numpy as np
@@ -80,7 +83,10 @@ def __str__(self):
                 continue  # Skip attributes starting with underscore
             if isinstance(value, tuple):
                 # Format the tuple as a string with the mean and standard deviation.
-                value_str = f"{value[0]:.5f} ± {value[1]:.5f} (numpy.random.{value[2].__name__})"
+                value_str = (
+                    f"{value[0]:.5f} ± {value[1]:.5f} "
+                    f"(numpy.random.{value[2].__name__})"
+                )
             else:
                 # Otherwise, just use the default string representation of the value.
                 value_str = str(value)
@@ -359,16 +365,17 @@ def _validate_tuple_factor(self, input_name, factor_tuple):
             2,
             3,
         ], f"'{input_name}`: Factors tuple must have length 2 or 3"
-        assert all(
-            isinstance(item, (int, float)) for item in factor_tuple[:2]
-        ), f"'{input_name}`: First and second items of Factors tuple must be either an int or float"
+        assert all(isinstance(item, (int, float)) for item in factor_tuple[:2]), (
+            f"'{input_name}`: First and second items of Factors tuple must be "
+            "either an int or float"
+        )
 
         if len(factor_tuple) == 2:
             return (factor_tuple[0], factor_tuple[1], get_distribution("normal"))
         elif len(factor_tuple) == 3:
             assert isinstance(factor_tuple[2], str), (
-                f"'{input_name}`: Third item of tuple must be a string containing the name "
-                "of a valid numpy.random distribution function"
+                f"'{input_name}`: Third item of tuple must be a string containing "
+                "the name of a valid numpy.random distribution function"
             )
             dist_func = get_distribution(factor_tuple[2])
             return (factor_tuple[0], factor_tuple[1], dist_func)

rocketpy/stochastic/stochastic_motor_model.py

@@ -1,3 +1,5 @@
+"""Defines the StochasticMotorModel class."""
+
 from .stochastic_model import StochasticModel
 
 

rocketpy/stochastic/stochastic_parachute.py

@@ -1,3 +1,5 @@
+"""Defines the StochasticParachute class."""
+
 from rocketpy.rocket import Parachute
 
 from .stochastic_model import StochasticModel

rocketpy/stochastic/stochastic_rocket.py

@@ -1,3 +1,5 @@
+"""Defines the StochasticRocket class."""
+
 import warnings
 from random import choice
 
@@ -50,8 +52,8 @@ class is used to receive a Rocket object and information about the
     rail_buttons : Components
         A Components instance containing all the rail buttons of the rocket.
     parachutes : list of StochasticParachute
-        A list of StochasticParachute instances containing all the parachutes of the
-        rocket.
+        A list of StochasticParachute instances containing all the parachutes of
+        the rocket.
     radius : tuple, list, int, float
         The radius of the rocket. Follows the standard input format of
         Stochastic Models.
@@ -195,10 +197,13 @@ def __str__(self):
                 continue  # Skip attributes starting with underscore
             if isinstance(value, tuple):
                 # Format the tuple as a string with the mean and standard deviation.
-                value_str = f"{value[0]:.5f} ± {value[1]:.5f} (numpy.random.{value[2].__name__})"
+                value_str = (
+                    f"{value[0]:.5f} ± {value[1]:.5f} "
+                    f"(numpy.random.{value[2].__name__})"
+                )
                 s += f"{key}: {value_str}\n"
             elif isinstance(value, Components):
-                # Format the components as a string with the mean and standard deviation.
+                # Format Components as string with the mean and std deviation
                 s += f"{key}:\n"
                 if len(value) == 0:
                     s += "\tNone\n"
@@ -248,7 +253,7 @@ def add_motor(self, motor, position=None):
             raise TypeError("`motor` must be a StochasticMotor or Motor type")
         if isinstance(motor, Motor):
             # create StochasticMotor
-            # TODO check motor type when hybrids and liquids are implemented
+            # TODO implement HybridMotor and LiquidMotor stochastic models
             if isinstance(motor, SolidMotor):
                 motor = StochasticSolidMotor(solid_motor=motor)
             elif isinstance(motor, GenericMotor):

rocketpy/stochastic/stochastic_solid_motor.py

@@ -1,3 +1,5 @@
+"""Defines the StochasticSolidMotor class."""
+
 from rocketpy.motors import SolidMotor
 
 from .stochastic_motor_model import StochasticMotorModel