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Commit 7415b7d6 authored by aastorg2's avatar aastorg2
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adding debugging files

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dtree_synth.py
+ 24
− 3
View file @ 7415b7d6
import itertools
import pickle
from typing import List, Tuple
import numpy as np
import z3
import csv
from dtree_learner import DTreeLearner as Learner
from dtree_teacher_gem_stanley import DTreeTeacherGEMStanley as Teacher
......@@ -27,13 +28,15 @@ def load_positive_examples(file_name: str) -> List[Tuple[float, ...]]:
def test_synth_dtree():
positive_examples = load_positive_examples(
"data/collect_images_2021-11-22-17-59-46.cs598.filtered.pickle")
positive_examples = positive_examples[:20:] # Select only first few examples
#positive_examples = positive_examples[:20:] # Select only first few examples
ex_dim = len(positive_examples[0])
print("#examples: %d" % len(positive_examples))
print("Dimension of each example: %d" % ex_dim)
assert all(len(ex) == ex_dim and not any(np.isnan(ex))
for ex in positive_examples)
......@@ -42,7 +45,7 @@ def test_synth_dtree():
# 0.0 <= x <= 30.0 and -1.0 <= y <= 0.9 and 0.2 <= theta <= 0.22
teacher.set_old_state_bound(lb=[0.0, -1.0, 0.2], ub=[30.0, -0.9, 0.22])
synth_dtree(positive_examples, teacher, num_max_iterations=5)
synth_dtree(positive_examples, teacher, num_max_iterations=50)
def synth_dtree(positive_examples, teacher, num_max_iterations: int = 10):
......@@ -53,12 +56,20 @@ def synth_dtree(positive_examples, teacher, num_max_iterations: int = 10):
[0., 0., -1.]])
b_vec_0 = np.zeros(2)
learner.set_grammar([(a_mat_0, b_vec_0)])
#writing positive examples in csv file
f = open("positive_sample.csv", 'w')
data_out = csv.writer(f)
for ps in positive_examples:
data_out.writerow(itertools.chain(ps,["true"]))
f.close()
learner.add_positive_examples(*positive_examples)
past_candidate_list = []
for k in range(num_max_iterations):
print(f"Iteration {k}:", sep='')
print("learning ....")
candidate_dnf = learner.learn()
print("done learning")
......@@ -67,8 +78,10 @@ def synth_dtree(positive_examples, teacher, num_max_iterations: int = 10):
return
print(f"candidate DNF: {candidate_dnf}")
past_candidate_list.append(candidate_dnf)
# QUERYING TEACHER IF THERE ARE NEGATIVE EXAMPLES
print(f"number of paths: {len(candidate_dnf)}")
negative_examples = []
for candidate in candidate_dnf:
result = teacher.check(candidate)
......@@ -84,10 +97,18 @@ def synth_dtree(positive_examples, teacher, num_max_iterations: int = 10):
print("Reason Unknown", teacher.reason_unknown())
return past_candidate_list
fneg = open("negative_sample.csv", 'w')
data_out = csv.writer(fneg)
for pn in negative_examples:
data_out.writerow(itertools.chain(pn,["true"]))
fneg.close()
print(f"negative examples: {negative_examples}")
if len(negative_examples) > 0:
learner.add_negative_examples(*negative_examples)
else:
file = open('winnerDnf', 'wb')
pickle.dump(candidate_dnf, file)
print("we are done!")
return past_candidate_list
......
negative_sample.csv 0 → 100644
+ 6
− 0
View file @ 7415b7d6
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positive_sample.csv 0 → 100644
+ 187
− 0
View file @ 7415b7d6
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