removed redundant list comparison

src/compas_timber/ghpython/components/CT_Beam_Nesting/code.py

@@ -1,5 +1,4 @@
 from ghpythonlib.componentbase import executingcomponent as component
-from Grasshopper.Kernel.GH_RuntimeMessageLevel import Error
 from Grasshopper.Kernel.GH_RuntimeMessageLevel import Warning
 from Grasshopper import DataTree
 from Grasshopper.Kernel.Data import GH_Path
@@ -8,7 +7,7 @@
 
 class NestingComponent(component):
 
-    def RunScript(self, assembly, stock_length, tolerance=1, iterations=10):
+    def RunScript(self, assembly, stock_length, tolerance, iterations):
 
         if not assembly:
             self.AddRuntimeMessage(Warning, "input Assembly failed to collect data")
@@ -30,11 +29,4 @@ def RunScript(self, assembly, stock_length, tolerance=1, iterations=10):
         info.append("bin count = {0}".format(len(nesting_dict.items())))
         info.append("cutoff waste = {:.2f}".format(nester.total_space(nesting_dict)))
 
-        beam_list_out = []
-        for val in nesting_dict.values():
-            beam_list_out.extend(val)
-
-        if set(beam_list_out) != set(assembly.beams):
-            self.AddRuntimeMessage(Error, "beams inputs and outputs dont match")
-
         return data_tree, info

src/compas_timber/planning/beam_nesting.py

@@ -44,7 +44,7 @@ def total_space(self, bin_dict):
         return sum([self.space_remaining(bin) for bin in bin_dict.values()])
 
     def get_bins_basic(self, beams):
-        """returns a dictionary of bins with beams nested in them"""    
+        """returns a dictionary of bins with beams nested in them"""
         beams_sorted = sorted(beams, key=lambda z: z.length, reverse=True)
         bins = OrderedDict([(0, [])])
         for beam in beams_sorted:
@@ -109,7 +109,7 @@ def validate_bin_results(self, bins, beams):
             beam_list_out.extend(val)
 
         if set(beam_list_out) != set(beams):
-            raise Exception("beams inputs and outputs dont match")
+            raise Exception("Beams input and nesting output dont match")
 
     def get_bins(self, beams, stock_length, tolerance=None, iterations=0):
         """returns a dictionary of bins with beams nested in them
@@ -126,7 +126,6 @@ def get_bins(self, beams, stock_length, tolerance=None, iterations=0):
             number of iterations to run the nesting algorithm, the algorithm will stop when the total waste is less than the stock length
 
         """
-
         self.stock_length = stock_length
         if tolerance is None:
             self.tolerance = stock_length / 100
@@ -141,26 +140,28 @@ def get_bins(self, beams, stock_length, tolerance=None, iterations=0):
 
         if iterations == 0:
             return self.get_bins_basic(beams)
-        
+
         else:
-            for i in range(iterations):     #try with different shuffling
+            for i in range(iterations):  # try with different shuffling
                 these_beams = beams
                 these_bins = self.get_bins_basic(these_beams)
                 results_dict = self.parse_bins(these_bins)
-                if results_dict["done"]:                          #if the nesting is successful
+                if results_dict["done"]:  # if the nesting is successful
                     bins_out = results_dict["finished_bins"]
                 else:
                     sort = False
                     shuffle = True
-                    for x in range(iterations):         #tries to repack the beams that don't fit in the bins within the cutoff tolerance
+                    for x in range(
+                        iterations
+                    ):  # tries to repack the beams that don't fit in the bins within the cutoff tolerance
                         these_beams = results_dict["recycled_beams"]
                         temp_bins = self.fill_bins(results_dict["temporary_bins"], these_beams, sort, shuffle)
                         results_dict = self.parse_bins(temp_bins)
                         if results_dict["done"]:
                             bins_out = results_dict["finished_bins"]
                             print("success after {0} iterations.".format(x))
                             break
-                        elif x == iterations - 1: #if the last iteration is reached, the best result is taken
+                        elif x == iterations - 1:  # if the last iteration is reached, the best result is taken
                             all_bins.append(results_dict["finished_bins"])
                         else:
                             sort = not sort
@@ -169,10 +170,10 @@ def get_bins(self, beams, stock_length, tolerance=None, iterations=0):
                     break
 
         if not bins_out:
-            bins_out = min(all_bins, key=lambda x: len(x)) #if no successful nesting is found, the one with the least bins is taken
+            bins_out = min(
+                all_bins, key=lambda x: len(x)
+            )  # if no successful nesting is found, the one with the least bins is taken
 
         self.validate_bin_results(bins_out, beams)
 
         return bins_out
-
-