Improved typing

ShipGen/Generate.py

@@ -2,19 +2,12 @@
 
 import numpy as np
 from tqdm import tqdm
-import math
-import matplotlib.pyplot as plt
 import torch
-import torch.nn as nn
-import torch.nn.functional as F
 from .tools import Guided_Cond_DDPM_Tools as GC_DDPM
+from .tools.HullParameterization import Hull_Parameterization as HP
 from .__init__ import data_path, trained_models_path
 
-from sklearn.decomposition import PCA # type: ignore
-
-import matplotlib.pyplot as plt
 
-from .tools.HullParameterization import Hull_Parameterization as HP
 
 device = torch.device("cuda" if torch.cuda.is_available() else "cpu")
 
@@ -217,34 +210,27 @@ def generate_hulls(final_count:int,
     if characteristics is None:
         Ship = np.array([333, 42.624, 11.28, 29.064, 97561,16])
     else: Ship = characteristics.as_array()
-    if reject_count is None: num_samples = final_count * (reject_ratio + 1)
+    if reject_count is None: num_samples = int(final_count * (reject_ratio + 1))
     else: num_samples = final_count + reject_count
 
-    LOA = Ship[0] #in meters
-    BoL = Ship[1]/LOA #beam to length ratio
-    ToD = Ship[2]/Ship[3] #Draft to depth ratio
-    DoL = Ship[3]/LOA #Depth to length ratio
-    Vol = np.log10(Ship[4]/LOA**3) # to normalize Volume by LOA**3
+    LOA:float = Ship[0] #in meters
+    BoL:float = Ship[1]/LOA #beam to length ratio
+    ToD:float = Ship[2]/Ship[3] #Draft to depth ratio
+    DoL:float = Ship[3]/LOA #Depth to length ratio
+    Vol:float = np.log10(Ship[4]/LOA**3) # to normalize Volume by LOA**3
 
-    U = Ship[5]  #  12.86 #m/s  = 25 knots
+    U:float = Ship[5]  #  12.86 #m/s  = 25 knots
 
     dim_d = np.array([[ToD, U, LOA]]) #Drag_conditioning is [ToD, U(m/s), LOA (m)]
 
     drag_cond = np.repeat(dim_d, num_samples, axis=0) #reapeat 
-    #print(cond.shape)
     dim_g = np.array([[ToD, BoL, DoL, Vol]])
 
     geom_cond = np.repeat(dim_g, num_samples, axis=0) #reapeat 
-    #print(cond.shape)
 
     x_samples, unnorm = T.gen_vol_drag_guided_samples(geom_cond, drag_cond)
 
-
     Rt_guidance = T.Predict_Drag(unnorm, drag_cond)
-    Drag_Guidance = np.mean(Rt_guidance)
-
-
-
 
     path = "./Hulls/"
 
@@ -265,6 +251,4 @@ def generate_hulls(final_count:int,
         try:
             mesh = Hull.gen_stl(NUM_WL=47, PointsPerWL=151, bit_AddTransom = 1, bit_AddDeckLid = 1, bit_RefineBowAndStern = 1,namepath = strpath)
         except:
-            print('Error at hull {}'.format(valid_idx[idxs[i]]))
-
-    idx_min_pred_drag = np.argmin(Rt_guidance[valid_idx])
+            print('Error at hull {}'.format(valid_idx[idxs[i]]))

ShipGen/tools/HullParameterization.py

@@ -1753,7 +1753,7 @@ def gen_WLPoints(self, z, PointsPerWL = 300):
         return np.array(WL)
 
 
-    def gen_stl(self, NUM_WL = 50, PointsPerWL = 300, bit_AddTransom = 1, bit_AddDeckLid = 0, bit_RefineBowAndStern = 0, namepath = 'Hull_Mesh'):
+    def gen_stl(self, NUM_WL = 50, PointsPerWL = 300, bit_AddTransom = 1, bit_AddDeckLid = 0, bit_RefineBowAndStern = 0, namepath = 'Hull_Mesh') -> mesh.Mesh:
         # This function generates a surface of the mesh by iterating through the points on the waterlines
 
         #compute number of triangles in the mesh