Added code for creating a random forest with all its trees

Author: Michal-Fularz

decision_trees/vhdl_generators/VHDLCreator.py

@@ -135,15 +135,6 @@ def _add_architecture_signal_section(self) -> str:
     def _add_architecture_process_section(self) -> str:
         return
 
-    def create_vhdl_file(self, path: str) -> str:
-        # open file for writing
-        file_to_write = open(path + "/" + self._filename, "w")
-        # add necessary headers
-        text = ""
-        text += self._add_headers()
-        text += self._add_entity()
-        text += self._add_architecture()
-
-        file_to_write.write(text)
-
-        file_to_write.close()
+    @abc.abstractmethod
+    def create_vhdl_file(self, path: str):
+        return

decision_trees/vhdl_generators/__init__.py

@@ -1,3 +1,5 @@
+from typing import List
+
 from decision_trees.vhdl_generators.VHDLCreator import VHDLCreator
 from decision_trees.vhdl_generators.tree import Tree
 
@@ -10,14 +12,14 @@
 class RandomForest(VHDLCreator):
 
     def __init__(self, name: str, number_of_features: int, number_of_bits_per_feature: int):
-        self.random_forest = []
+        self.random_forest: List[Tree] = []
 
         VHDLCreator.__init__(self, name, ClassifierType.RANDOM_FOREST.name,
                              number_of_features, number_of_bits_per_feature)
 
     def build(self, random_forest: sklearn.ensemble.RandomForestClassifier):
         for i, tree in enumerate(random_forest.estimators_):
-            tree_builder = Tree("tree_" + str(i), self._number_of_features, self._number_of_bits_per_feature)
+            tree_builder = Tree(f'tree_{i:02}', self._number_of_features, self._number_of_bits_per_feature)
             tree_builder.build(tree)
 
             self.random_forest.append(tree_builder)
@@ -126,3 +128,15 @@ def _add_port_mapping(self, index: int) -> str:
         self.current_indent -= 1
 
         return text
+
+    def create_vhdl_file(self, path: str):
+        for d in self.random_forest:
+            d.create_vhdl_file(path)
+
+        with open(path + '/' + self._filename, 'w') as f:
+            text = ''
+            text += self._add_headers()
+            text += self._add_entity()
+            text += self._add_architecture()
+            f.write(text)
+

decision_trees/vhdl_generators/random_forest.py

@@ -3,7 +3,7 @@
 import numpy as np
 import sklearn.tree
 
-from decision_trees.utils.convert_to_fixed_point import convert_to_fixed_point
+from decision_trees.utils.convert_to_fixed_point import convert_to_fixed_point, convert_fixed_point_to_integer
 from decision_trees.utils.constants import ClassifierType
 
 
@@ -230,7 +230,7 @@ def _add_architecture_process_compare(self):
             text += self._insert_text_line_with_indent(
                 "if unsigned(features(" +
                 str(split.var_idx) + ")) <= to_unsigned(" +
-                str(int(split.value_to_compare)) +
+                str(convert_fixed_point_to_integer(split.value_to_compare, self._number_of_bits_per_feature)) +
                 ", features'length) then")
 
             self.current_indent += 1
@@ -323,6 +323,9 @@ def _preorder(self, tree_, features, following_splits_IDs, following_splits_comp
             # print("Feature: " + str(tree_.threshold[node]) + ", after conversion: "
             # + str(convert_to_fixed_point(tree_.threshold[node], self._number_of_bits_per_feature)))
 
+            #print(f'tree_.threshold[node]: {tree_.threshold[node]:{1}.{3}}')
+            #print(f'convert_to_fixed_point: {convert_to_fixed_point(tree_.threshold[node], self._number_of_bits_per_feature):{1}.{3}}')
+
             # then create a split
             self._add_new_split(
                 self._current_split_index,
@@ -364,3 +367,11 @@ def _preorder(self, tree_, features, following_splits_IDs, following_splits_comp
                 following_splits_IDs,
                 following_splits_compare_values
             )
+
+    def create_vhdl_file(self, path: str):
+        with open(path + '/' + self._filename, 'w') as f:
+            text = ''
+            text += self._add_headers()
+            text += self._add_entity()
+            text += self._add_architecture()
+            f.write(text)