adding code that generates names( features) file

dtree_learner.py

@@ -3,25 +3,28 @@ import numpy as np
 import os
 from learner_base import LearnerBase
 import csv
+import grammar_generation_utils
 
 class DTreeLearner(LearnerBase):
     def __init__(self, state_dim: int, perc_dim: int,
                  timeout: int = 10000) -> None:
         super().__init__()
-        #learners/C50exact/c5.0dbg  -I 1 -m 1 -f FileLocation/pre
+        #C50exact/c5.0dbg  -I 1 -m 1 -f tempLocation/pre
         self._state_dim: int = state_dim
         self._perc_dim: int = perc_dim
 
         self._s2f_func_list: List = []
 
-        dir_name = "tempLocation"
-        check_temp_dir: bool = os.path.isdir(dir_name)
+        #check tempLocation dir exists, if not create it.
+        self.dir_name = "tempLocation"
+        check_temp_dir: bool = os.path.isdir(self.dir_name)
         if not check_temp_dir:
-            os.makedirs(dir_name)
+            os.makedirs(self.dir_name)
 
-        self.data_file = dir_name+"/pre.data"
-        self.names_file = dir_name+"/pre.names"
-        open(self.data_file,'w').close() # create empty file
+        # create empty files
+        self.data_file = self.dir_name+"/pre.data"
+        self.names_file = self.dir_name+"/pre.names"
+        open(self.data_file,'w').close() 
         open(self.names_file,'w').close()
 
     @property
@@ -37,6 +40,9 @@ class DTreeLearner(LearnerBase):
             self._s2f_func_list.append(
                 construct_sample_to_feature_func(a_mat, b_vec))
 
+        num_vars = ["dbar", "psibar"]
+        grammar_generation_utils.generateInputLanguageFile(self.names_file, num_vars, [])
+
     def add_implication_examples(self, *args) -> None:
         return super().add_implication_examples(*args)
 
@@ -86,29 +92,6 @@ def construct_sample_to_feature_func(a_mat: np.ndarray, b_vec: np.ndarray):
         return perc_bar
     return sample_to_feature_vec
 
-def test_sample_to_feature():
-    # tuple
-    a_mat = np.array([[0., -1., 0.],
-                      [0., 0., -1]])
-    b_vec = np.zeros(2)
-
-    #construct_sample_to_feature_func: returns a function
-    #map: lin_trans(a_mat and b_vec pair) -> func
-    sample_to_feature_func = construct_sample_to_feature_func(a_mat, b_vec)
-                                
-    #map = {name1:sample_to_feature_func}
-    sample = np.array([1., 2., 3., -2., -3.])
-    # sample_to_feature_func will compute dBar and psiBar
-    feature_vec = sample_to_feature_func(sample)
-    print("sample: "+ str(feature_vec))
-    assert np.array_equal(feature_vec, np.array([0., 0.]))
-
-    sample = np.array([1., 2., 3., -1., -2.])
-    feature_vec = sample_to_feature_func(sample)
-    print("sample: "+ str(feature_vec))
-    assert np.array_equal(feature_vec, np.array([1., 1.]))
-
-
 def test_dtree_learner():
     a_mat = np.array([[0., -1., 0.],
                       [0., 0., -1]])
@@ -132,6 +115,28 @@ def test_dtree_learner():
 
     # learner.learn()
 
+def test_sample_to_feature():
+    # tuple
+    a_mat = np.array([[0., -1., 0.],
+                      [0., 0., -1]])
+    b_vec = np.zeros(2)
+
+    #construct_sample_to_feature_func: returns a function
+    #map: lin_trans(a_mat and b_vec pair) -> func
+    sample_to_feature_func = construct_sample_to_feature_func(a_mat, b_vec)
+                                
+    #map = {name1:sample_to_feature_func}
+    sample = np.array([1., 2., 3., -2., -3.])
+    # sample_to_feature_func will compute dBar and psiBar
+    feature_vec = sample_to_feature_func(sample)
+    print("sample: "+ str(feature_vec))
+    assert np.array_equal(feature_vec, np.array([0., 0.]))
+
+    sample = np.array([1., 2., 3., -1., -2.])
+    feature_vec = sample_to_feature_func(sample)
+    print("sample: "+ str(feature_vec))
+    assert np.array_equal(feature_vec, np.array([1., 1.]))
+
 
 if __name__ == "__main__":
     #test_sample_to_feature()

grammar_generation_utils.py

+import itertools
+from typing import List, Tuple
+
+def generateInputLanguageFile(nameOfFile:str, intVariables: List[str], boolVariables: List[str]):
+            fileContents= generateExpressionsBools(intVariables, boolVariables)
+            try:
+                
+                with open(nameOfFile, 'wt') as outfile:
+                    outfile.write(fileContents)
+
+            except Exception as e:
+                raise Exception(str(e) + ": " + "error writing files---line 12 grammar_generation_utils.py")
+
+
+def generateExpressionsBools(intVariables: List[str], boolVariables: List[str])-> str:
+        coeff_combination = make_coeff_linear_combination(len(intVariables), -1, 1)
+        names_file = 'precondition.'
+
+        for var in intVariables:
+            names_file += '\n' + var + ':  continuous.'
+
+        # adding boolean observer method features
+        for var in boolVariables:
+            names_file += '\n' + var + ':  true, false.'
+
+        # check equality of integer variables
+        if len(intVariables) >= 2:
+            all_combination = itertools.combinations(intVariables, 2)
+            for (var1, var2) in all_combination:
+                expr = "(" + var1 + " = " + var2 + ")"
+                name_expr = "( = " + var1 + " " + var2 + " )"
+                names_file += '\n' + name_expr + ' := ' + expr + ' .' #needs change
+
+        for coeff in coeff_combination:
+            # old way of generating all possible combinations
+            expr = ' + '.join(map(lambda x,y: "(" + str(x) + "*" + y + ")", coeff, intVariables))
+            name_expr = ' ( + ' + ' '.join(map(lambda x,y: "( * " + str(x) + " " + y + " )", coeff, intVariables)) + ' )'
+            names_file += '\n' + name_expr +  ' := ' + expr + ' .'
+        
+        
+        names_file += '\nprecondition:    true,false.'
+        return names_file
+
+def make_coeff_linear_combination( number_of_variables, low, high):
+    init_list = [[i] for i in range(low, high + 1)]
+    a = init_list
+    for i in range(1, number_of_variables):
+        a = [x + y for x in a for y in init_list]  # x + y -- concatenation of lists
+    return a
+
+if __name__ == '__main__':
+    intVariables = ["dbar", "psibar"]
+    boolVariables = []
+    fullPathLocation = "/home/aastorg2/intelligibleAbs/cs598mp-fall2021-proj/tempLocation/pre.names"
+
+    generateInputLanguageFile(fullPathLocation, intVariables)
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