ENH: disp more results to rocketpy.plots & rocketpy.prints

.vscode/settings.json

@@ -327,5 +327,8 @@
         "zlabel",
         "zlim",
         "zorder"
-    ]
+    ],
+    "files.associations": {
+        "plyconfig.json": "jsonc"
+    }
 }

rocketpy/plots/monte_carlo_plots.py

@@ -149,7 +149,8 @@ def ellipses(
 
     def all(self, keys=None):
         """
-        Plot the histograms of the Monte Carlo simulation results.
+        Plot the histograms with Boxplots & density plots 
+        of the Monte Carlo simulation results.
 
         Parameters
         ----------
@@ -175,8 +176,19 @@ def all(self, keys=None):
             raise ValueError("The 'keys' argument must be a string, list, or tuple.")
 
         for key in keys:
-            plt.figure()
-            plt.hist(self.monte_carlo.results[key])
-            plt.title(f"Histogram of {key}")
-            plt.ylabel("Number of Occurrences")
-            plt.show()
+            figure, plt = plt.subplots(3,1,sharex=True,gridspec_kw={'height_ratios':[1,3]})
+
+            plt[0].boxplot(self.monte_carlo.results[key],vert=False)
+            plt[0].ytick([])
+
+            plt[1].hist(self.monte_carlo.results[key])
+            plt[1].title(f"Histogram of {key}")
+            plt[1].ylabel("Number of Occurrences")
+
+            plt[2].hist(self.monte_carlo.results[key], density=True)
+            plt[2].title(f" Density {key}")
+            plt[2].ylabel("Probability Density")
+            kde = kde.gaussian_kde(self.monte_carlo.results[key])
+            x_array = np.linspace(min(self.monte_carlo.results[key]), max(self.monte_carlo.results[key]), 100) 
+            plt[2].plot(x_array, kde(x_array), label='KDE')
+            plt.show()

rocketpy/prints/monte_carlo_prints.py

@@ -1,12 +1,14 @@
+import numpy as np
+
 class _MonteCarloPrints:
     """Class to print the monte carlo analysis results."""
 
     def __init__(self, monte_carlo):
         self.monte_carlo = monte_carlo
 
     def all(self):
-        """Print the mean and standard deviation of each parameter in the results
-        dictionary or of the variables passed as argument.
+        """Print the mean, standard deviation, and quantiles (0%,  2.5%, 50%, 97.5%, 100%) 
+        of each parameter in the results dictionary or of the variables passed as argument.
 
         Parameters
         ----------
@@ -19,12 +21,14 @@ def all(self):
         """
         print("Monte Carlo Simulation by RocketPy")
         print("Data Source: ", self.monte_carlo.filename)
-        print("Number of simulations: ", self.monte_carlo.num_of_loaded_sims)
+        print("Number of Simulations: ", self.monte_carlo.num_of_loaded_sims)
         print("Results: \n")
-        print(f"{'Parameter':>25} {'Mean':>15} {'Std. Dev.':>15}")
+
+        print(f"{'Parameter':>25} {'Mean':>15} {'Std. Dev.':>15} {'0% Quant':>15} {'2.5% Quant.':>15} {'50% Quant.':>15} {'97.5% Quant.':>15} {'100% Quant.':>15}")
         print("-" * 60)
         for key, value in self.monte_carlo.processed_results.items():
             try:
-                print(f"{key:>25} {value[0]:>15.3f} {value[1]:>15.3f}")
+                pt = self.monte_carlo.results[key]
+                print (f"{key:>25} {value[0]:>15.3f} {value[1]:>15.3f} {np.quantile(pt,0):>15.3f} {np.quantile(pt,0.025):>15.3f} {np.quantile(pt,0.5):>15.3f} {np.quantile(pt,0.975):>15.3f} {np.quantile(pt,1):>15.3f}")
             except TypeError:
-                print(f"{key:>25} {str(value[0]):>15} {str(value[1]):>15}")
+                print (f"{key:>25} {str(value[0]):>15} {str(value[1]):>15} {str(np.quantile(pt,0)):>15} {str(np.quantile(pt,0.025)):>15} {str(np.quantile(pt,0.5)):>15} {str(np.quantile(pt,0.975)):>15} {str(np.quantile(pt,1)):>15}")