task_type stringclasses 4
values | code_task stringclasses 15
values | start_line int64 4 1.79k | end_line int64 4 1.8k | before stringlengths 79 76.1k | between stringlengths 17 806 | after stringlengths 2 72.6k | reason_categories_output stringlengths 2 2.24k | horizon_categories_output stringlengths 83 3.99k ⌀ | reason_freq_analysis stringclasses 150
values | horizon_freq_analysis stringlengths 23 185 ⌀ |
|---|---|---|---|---|---|---|---|---|---|---|
infilling_python | RL_Motion_Planning | 572 | 572 | ['import os', "os.environ['TF_CPP_MIN_LOG_LEVEL'] = '2' # Suppress TensorFlow logging", "os.environ['TF_ENABLE_ONEDNN_OPTS'] = '0' # Suppress oneDNN warning", '# os.environ["CUDA_VISIBLE_DEVICES"] = "0"', 'import argparse', 'import datetime', 'import json', 'import os', 'import pickle', 'import sys', 'import time', '... | [' self.model.save_(dir_param)'] | [' ', ' def load_model(self, dir_param):', ' self.model.load_(dir_param)', ' ', ' def process_data(self, transitions, expert=False, is_supervised=False):', ' ', ' trans = transitions.copy()', ' ', ' # Process the states and goals', " trans['states'] = self.preproces... | [] | Variable 'self' used at line 572 is defined at line 569 and has a Short-Range dependency.
Variable 'dir_param' used at line 572 is defined at line 569 and has a Short-Range dependency. | {} | {'Variable Short-Range': 2} |
infilling_python | RL_Motion_Planning | 575 | 575 | ['import os', "os.environ['TF_CPP_MIN_LOG_LEVEL'] = '2' # Suppress TensorFlow logging", "os.environ['TF_ENABLE_ONEDNN_OPTS'] = '0' # Suppress oneDNN warning", '# os.environ["CUDA_VISIBLE_DEVICES"] = "0"', 'import argparse', 'import datetime', 'import json', 'import os', 'import pickle', 'import sys', 'import time', '... | [' self.model.load_(dir_param)'] | [' ', ' def process_data(self, transitions, expert=False, is_supervised=False):', ' ', ' trans = transitions.copy()', ' ', ' # Process the states and goals', " trans['states'] = self.preprocess_in_state_space(trans['states'])", " trans['states_2'] = self.preprocess_in_sta... | [] | Variable 'self' used at line 575 is defined at line 574 and has a Short-Range dependency.
Variable 'dir_param' used at line 575 is defined at line 574 and has a Short-Range dependency. | {} | {'Variable Short-Range': 2} |
infilling_python | RL_Motion_Planning | 599 | 601 | ['import os', "os.environ['TF_CPP_MIN_LOG_LEVEL'] = '2' # Suppress TensorFlow logging", "os.environ['TF_ENABLE_ONEDNN_OPTS'] = '0' # Suppress oneDNN warning", '# os.environ["CUDA_VISIBLE_DEVICES"] = "0"', 'import argparse', 'import datetime', 'import json', 'import os', 'import pickle', 'import sys', 'import time', '... | [" trans['terminate_skills'] = tf.cast(tf.not_equal(tf.argmax(trans['prev_skills'], axis=-1),", " tf.argmax(trans['curr_skills'], axis=-1)),", ' dtype=tf.int32)'] | [' # reshape the terminate_skills to be of shape (batch_size, 1)', " trans['terminate_skills'] = tf.reshape(trans['terminate_skills'], shape=(-1, 1))", ' ', ' # Make sure the data is of type tf.float32', ' for key in trans.keys():', ' trans[key] = tf.cast(trans[key], dtype=... | [] | Variable 'trans' used at line 599 is defined at line 596 and has a Short-Range dependency.
Library 'tf' used at line 599 is imported at line 20 and has a Long-Range dependency.
Library 'tf' used at line 600 is imported at line 20 and has a Long-Range dependency.
Variable 'trans' used at line 600 is defined at line 596 ... | {} | {'Variable Short-Range': 2, 'Library Long-Range': 3} |
infilling_python | RL_Motion_Planning | 603 | 603 | ['import os', "os.environ['TF_CPP_MIN_LOG_LEVEL'] = '2' # Suppress TensorFlow logging", "os.environ['TF_ENABLE_ONEDNN_OPTS'] = '0' # Suppress oneDNN warning", '# os.environ["CUDA_VISIBLE_DEVICES"] = "0"', 'import argparse', 'import datetime', 'import json', 'import os', 'import pickle', 'import sys', 'import time', '... | [" trans['terminate_skills'] = tf.reshape(trans['terminate_skills'], shape=(-1, 1))"] | [' ', ' # Make sure the data is of type tf.float32', ' for key in trans.keys():', ' trans[key] = tf.cast(trans[key], dtype=tf.float32)', ' print("trans :", trans)', ' return trans', ' ', ' def sample_data(self, buffer, batch_size):', ' ', ' # Sample Tran... | [] | Variable 'trans' used at line 603 is defined at line 599 and has a Short-Range dependency.
Library 'tf' used at line 603 is imported at line 20 and has a Long-Range dependency. | {} | {'Variable Short-Range': 1, 'Library Long-Range': 1} |
infilling_python | RL_Motion_Planning | 607 | 607 | ['import os', "os.environ['TF_CPP_MIN_LOG_LEVEL'] = '2' # Suppress TensorFlow logging", "os.environ['TF_ENABLE_ONEDNN_OPTS'] = '0' # Suppress oneDNN warning", '# os.environ["CUDA_VISIBLE_DEVICES"] = "0"', 'import argparse', 'import datetime', 'import json', 'import os', 'import pickle', 'import sys', 'import time', '... | [' trans[key] = tf.cast(trans[key], dtype=tf.float32)'] | [' print("trans :", trans)', ' return trans', ' ', ' def sample_data(self, buffer, batch_size):', ' ', ' # Sample Transitions', ' transitions: Union[Dict[int, dict], dict] = buffer.sample_transitions(batch_size)', ' ', ' # Process the transitions', ' keys = ... | [{'reason_category': 'Loop Body', 'usage_line': 607}] | Variable 'trans' used at line 607 is defined at line 603 and has a Short-Range dependency.
Variable 'key' used at line 607 is part of a Loop defined at line 606 and has a Short-Range dependency.
Library 'tf' used at line 607 is imported at line 20 and has a Long-Range dependency. | {'Loop Body': 1} | {'Variable Short-Range': 1, 'Variable Loop Short-Range': 1, 'Library Long-Range': 1} |
infilling_python | RL_Motion_Planning | 614 | 614 | ['import os', "os.environ['TF_CPP_MIN_LOG_LEVEL'] = '2' # Suppress TensorFlow logging", "os.environ['TF_ENABLE_ONEDNN_OPTS'] = '0' # Suppress oneDNN warning", '# os.environ["CUDA_VISIBLE_DEVICES"] = "0"', 'import argparse', 'import datetime', 'import json', 'import os', 'import pickle', 'import sys', 'import time', '... | [' transitions: Union[Dict[int, dict], dict] = buffer.sample_transitions(batch_size)'] | [' ', ' # Process the transitions', ' keys = None', ' if all(isinstance(v, dict) for v in transitions.values()):', ' for skill in transitions.keys():', ' ', ' # For skills whose transition data is not None', ' if transitions[skill] is n... | [] | Library 'Union' used at line 614 is imported at line 16 and has a Long-Range dependency.
Library 'Dict' used at line 614 is imported at line 16 and has a Long-Range dependency.
Variable 'buffer' used at line 614 is defined at line 611 and has a Short-Range dependency.
Variable 'batch_size' used at line 614 is defined a... | {} | {'Library Long-Range': 2, 'Variable Short-Range': 2} |
infilling_python | RL_Motion_Planning | 624 | 624 | ['import os', "os.environ['TF_CPP_MIN_LOG_LEVEL'] = '2' # Suppress TensorFlow logging", "os.environ['TF_ENABLE_ONEDNN_OPTS'] = '0' # Suppress oneDNN warning", '# os.environ["CUDA_VISIBLE_DEVICES"] = "0"', 'import argparse', 'import datetime', 'import json', 'import os', 'import pickle', 'import sys', 'import time', '... | [' transitions[skill], tf.constant(True, dtype=tf.bool), tf.constant(True, dtype=tf.bool)'] | [' )', ' ', ' keys = transitions[skill].keys()', ' ', ' # If keys is None, No transitions were sampled', ' if keys is None:', ' raise ValueError("No transitions were sampled")', ' ', ' # Concat... | [{'reason_category': 'If Body', 'usage_line': 624}, {'reason_category': 'Loop Body', 'usage_line': 624}] | Variable 'skill' used at line 624 is part of a Loop defined at line 619 and has a Short-Range dependency.
Library 'tf' used at line 624 is imported at line 20 and has a Long-Range dependency. | {'If Body': 1, 'Loop Body': 1} | {'Variable Loop Short-Range': 1, 'Library Long-Range': 1} |
infilling_python | RL_Motion_Planning | 639 | 640 | ['import os', "os.environ['TF_CPP_MIN_LOG_LEVEL'] = '2' # Suppress TensorFlow logging", "os.environ['TF_ENABLE_ONEDNN_OPTS'] = '0' # Suppress oneDNN warning", '# os.environ["CUDA_VISIBLE_DEVICES"] = "0"', 'import argparse', 'import datetime', 'import json', 'import os', 'import pickle', 'import sys', 'import time', '... | [' for key in keys:', ' combined_transitions[key].append(transitions[skill][key])'] | [' ', ' for key in keys:', ' combined_transitions[key] = tf.concat(combined_transitions[key], axis=0)', ' ', ' transitions = combined_transitions', ' ', ' elif isinstance(transitions, dict):', ' transitions = self.process_data(', ' ... | [{'reason_category': 'If Body', 'usage_line': 639}, {'reason_category': 'Loop Body', 'usage_line': 639}, {'reason_category': 'Define Stop Criteria', 'usage_line': 639}, {'reason_category': 'If Body', 'usage_line': 640}, {'reason_category': 'Loop Body', 'usage_line': 640}] | Variable 'keys' used at line 639 is defined at line 617 and has a Medium-Range dependency.
Variable 'combined_transitions' used at line 640 is defined at line 634 and has a Short-Range dependency.
Variable 'key' used at line 640 is part of a Loop defined at line 639 and has a Short-Range dependency.
Variable 'skill' us... | {'If Body': 2, 'Loop Body': 2, 'Define Stop Criteria': 1} | {'Variable Medium-Range': 1, 'Variable Short-Range': 1, 'Variable Loop Short-Range': 2} |
infilling_python | RL_Motion_Planning | 643 | 643 | ['import os', "os.environ['TF_CPP_MIN_LOG_LEVEL'] = '2' # Suppress TensorFlow logging", "os.environ['TF_ENABLE_ONEDNN_OPTS'] = '0' # Suppress oneDNN warning", '# os.environ["CUDA_VISIBLE_DEVICES"] = "0"', 'import argparse', 'import datetime', 'import json', 'import os', 'import pickle', 'import sys', 'import time', '... | [' combined_transitions[key] = tf.concat(combined_transitions[key], axis=0)'] | [' ', ' transitions = combined_transitions', ' ', ' elif isinstance(transitions, dict):', ' transitions = self.process_data(', ' transitions, tf.constant(True, dtype=tf.bool), tf.constant(True, dtype=tf.bool)', ' )', ' ', ' else:', '... | [{'reason_category': 'If Body', 'usage_line': 643}, {'reason_category': 'Loop Based', 'usage_line': 643}] | Variable 'combined_transitions' used at line 643 is defined at line 634 and has a Short-Range dependency.
Variable 'key' used at line 643 is part of a Loop defined at line 642 and has a Short-Range dependency.
Library 'tf' used at line 643 is imported at line 20 and has a Long-Range dependency. | {'If Body': 1} | {'Variable Short-Range': 1, 'Variable Loop Short-Range': 1, 'Library Long-Range': 1} |
infilling_python | RL_Motion_Planning | 649 | 649 | ['import os', "os.environ['TF_CPP_MIN_LOG_LEVEL'] = '2' # Suppress TensorFlow logging", "os.environ['TF_ENABLE_ONEDNN_OPTS'] = '0' # Suppress oneDNN warning", '# os.environ["CUDA_VISIBLE_DEVICES"] = "0"', 'import argparse', 'import datetime', 'import json', 'import os', 'import pickle', 'import sys', 'import time', '... | [' transitions, tf.constant(True, dtype=tf.bool), tf.constant(True, dtype=tf.bool)'] | [' )', ' ', ' else:', ' raise ValueError("Invalid type of transitions")', ' print("transitions: ", transitions)', ' return transitions', ' ', ' @tf.function', ' def train(self):', ' ', ' self.model.change_training_mode(training_mode=True)', ' ... | [{'reason_category': 'Elif Body', 'usage_line': 649}] | Variable 'transitions' used at line 649 is defined at line 648 and has a Short-Range dependency.
Library 'tf' used at line 649 is imported at line 20 and has a Long-Range dependency. | {'Elif Body': 1} | {'Variable Short-Range': 1, 'Library Long-Range': 1} |
infilling_python | RL_Motion_Planning | 663 | 663 | ['import os', "os.environ['TF_CPP_MIN_LOG_LEVEL'] = '2' # Suppress TensorFlow logging", "os.environ['TF_ENABLE_ONEDNN_OPTS'] = '0' # Suppress oneDNN warning", '# os.environ["CUDA_VISIBLE_DEVICES"] = "0"', 'import argparse', 'import datetime', 'import json', 'import os', 'import pickle', 'import sys', 'import time', '... | [' data_policy = self.sample_data(self.offline_buffer, self.args.batch_size)'] | [' loss_dict = self.model.train(data_expert, data_policy)', ' ', ' # Average the losses', ' avg_loss_dict = {}', ' for key in loss_dict.keys():', ' if key not in avg_loss_dict.keys():', ' avg_loss_dict[key] = []', ' avg_loss_dict[key].append(loss_d... | [] | Variable 'self' used at line 663 is defined at line 658 and has a Short-Range dependency. | {} | {'Variable Short-Range': 1} |
infilling_python | RL_Motion_Planning | 668 | 673 | ['import os', "os.environ['TF_CPP_MIN_LOG_LEVEL'] = '2' # Suppress TensorFlow logging", "os.environ['TF_ENABLE_ONEDNN_OPTS'] = '0' # Suppress oneDNN warning", '# os.environ["CUDA_VISIBLE_DEVICES"] = "0"', 'import argparse', 'import datetime', 'import json', 'import os', 'import pickle', 'import sys', 'import time', '... | [' for key in loss_dict.keys():', ' if key not in avg_loss_dict.keys():', ' avg_loss_dict[key] = []', ' avg_loss_dict[key].append(loss_dict[key])', ' for key in avg_loss_dict.keys():', ' avg_loss_dict[key] = tf.reduce_mean(avg_loss_dict[key])'] | [' print("avg_loss_dict: ", avg_loss_dict)', ' return avg_loss_dict', ' ', ' def learn(self):', ' # This is a base class method, inherited classes must implement this method', ' raise NotImplementedError', '', '', 'class Agent(AgentBase):', ' def __init__(self, args,', ' ... | [{'reason_category': 'Define Stop Criteria', 'usage_line': 668}, {'reason_category': 'If Condition', 'usage_line': 669}, {'reason_category': 'Loop Body', 'usage_line': 669}, {'reason_category': 'Loop Body', 'usage_line': 670}, {'reason_category': 'If Body', 'usage_line': 670}, {'reason_category': 'Loop Body', 'usage_li... | Variable 'loss_dict' used at line 668 is defined at line 664 and has a Short-Range dependency.
Variable 'key' used at line 669 is part of a Loop defined at line 668 and has a Short-Range dependency.
Variable 'avg_loss_dict' used at line 669 is defined at line 667 and has a Short-Range dependency.
Variable 'avg_loss_dic... | {'Define Stop Criteria': 2, 'If Condition': 1, 'Loop Body': 4, 'If Body': 1} | {'Variable Short-Range': 7, 'Variable Loop Short-Range': 4, 'Library Long-Range': 1} |
infilling_python | RL_Motion_Planning | 671 | 671 | ['import os', "os.environ['TF_CPP_MIN_LOG_LEVEL'] = '2' # Suppress TensorFlow logging", "os.environ['TF_ENABLE_ONEDNN_OPTS'] = '0' # Suppress oneDNN warning", '# os.environ["CUDA_VISIBLE_DEVICES"] = "0"', 'import argparse', 'import datetime', 'import json', 'import os', 'import pickle', 'import sys', 'import time', '... | [' avg_loss_dict[key].append(loss_dict[key])'] | [' for key in avg_loss_dict.keys():', ' avg_loss_dict[key] = tf.reduce_mean(avg_loss_dict[key])', ' print("avg_loss_dict: ", avg_loss_dict)', ' return avg_loss_dict', ' ', ' def learn(self):', ' # This is a base class method, inherited classes must implement this method', ' ... | [{'reason_category': 'Loop Body', 'usage_line': 671}] | Variable 'avg_loss_dict' used at line 671 is defined at line 667 and has a Short-Range dependency.
Variable 'key' used at line 671 is part of a Loop defined at line 668 and has a Short-Range dependency.
Variable 'loss_dict' used at line 671 is defined at line 664 and has a Short-Range dependency. | {'Loop Body': 1} | {'Variable Short-Range': 2, 'Variable Loop Short-Range': 1} |
infilling_python | RL_Motion_Planning | 673 | 673 | ['import os', "os.environ['TF_CPP_MIN_LOG_LEVEL'] = '2' # Suppress TensorFlow logging", "os.environ['TF_ENABLE_ONEDNN_OPTS'] = '0' # Suppress oneDNN warning", '# os.environ["CUDA_VISIBLE_DEVICES"] = "0"', 'import argparse', 'import datetime', 'import json', 'import os', 'import pickle', 'import sys', 'import time', '... | [' avg_loss_dict[key] = tf.reduce_mean(avg_loss_dict[key])'] | [' print("avg_loss_dict: ", avg_loss_dict)', ' return avg_loss_dict', ' ', ' def learn(self):', ' # This is a base class method, inherited classes must implement this method', ' raise NotImplementedError', '', '', 'class Agent(AgentBase):', ' def __init__(self, args,', ' ... | [{'reason_category': 'Loop Body', 'usage_line': 673}] | Variable 'avg_loss_dict' used at line 673 is defined at line 667 and has a Short-Range dependency.
Variable 'key' used at line 673 is part of a Loop defined at line 672 and has a Short-Range dependency.
Library 'tf' used at line 673 is imported at line 20 and has a Long-Range dependency. | {'Loop Body': 1} | {'Variable Short-Range': 1, 'Variable Loop Short-Range': 1, 'Library Long-Range': 1} |
infilling_python | RL_Motion_Planning | 700 | 700 | ['import os', "os.environ['TF_CPP_MIN_LOG_LEVEL'] = '2' # Suppress TensorFlow logging", "os.environ['TF_ENABLE_ONEDNN_OPTS'] = '0' # Suppress oneDNN warning", '# os.environ["CUDA_VISIBLE_DEVICES"] = "0"', 'import argparse', 'import datetime', 'import json', 'import os', 'import pickle', 'import sys', 'import time', '... | [' data_off = self.offline_buffer.sample_episodes()'] | [' self.expert_buffer.load_data_into_buffer(buffered_data=data_exp, clear_buffer=True)', ' self.offline_buffer.load_data_into_buffer(buffered_data=data_exp, clear_buffer=True)', ' self.offline_buffer.load_data_into_buffer(buffered_data=data_off, clear_buffer=False)', ' ', ' with tqdm(... | [] | Variable 'self' used at line 700 is defined at line 692 and has a Short-Range dependency. | {} | {'Variable Short-Range': 1} |
infilling_python | RL_Motion_Planning | 715 | 717 | ['import os', "os.environ['TF_CPP_MIN_LOG_LEVEL'] = '2' # Suppress TensorFlow logging", "os.environ['TF_ENABLE_ONEDNN_OPTS'] = '0' # Suppress oneDNN warning", '# os.environ["CUDA_VISIBLE_DEVICES"] = "0"', 'import argparse', 'import datetime', 'import json', 'import os', 'import pickle', 'import sys', 'import time', '... | [' avg_loss_dict = self.train()', ' for key in avg_loss_dict.keys():', ' avg_loss_dict[key] = avg_loss_dict[key].numpy().item()'] | [' ', ' # Log', ' if self.args.log_wandb:', ' self.wandb_logger.log(avg_loss_dict, step=log_step)', ' self.wandb_logger.log({', " 'policy_buffer_size': self.offline_buffer.get_current_size_trans(),", " ... | [{'reason_category': 'Loop Body', 'usage_line': 715}, {'reason_category': 'Loop Body', 'usage_line': 716}, {'reason_category': 'Define Stop Criteria', 'usage_line': 716}, {'reason_category': 'Loop Body', 'usage_line': 717}] | Variable 'self' used at line 715 is defined at line 692 and has a Medium-Range dependency.
Variable 'avg_loss_dict' used at line 716 is defined at line 715 and has a Short-Range dependency.
Variable 'avg_loss_dict' used at line 717 is defined at line 715 and has a Short-Range dependency.
Variable 'key' used at line 717... | {'Loop Body': 3, 'Define Stop Criteria': 1} | {'Variable Medium-Range': 1, 'Variable Short-Range': 2, 'Variable Loop Short-Range': 1} |
infilling_python | RL_Motion_Planning | 859 | 859 | ['import os', "os.environ['TF_CPP_MIN_LOG_LEVEL'] = '2' # Suppress TensorFlow logging", "os.environ['TF_ENABLE_ONEDNN_OPTS'] = '0' # Suppress oneDNN warning", '# os.environ["CUDA_VISIBLE_DEVICES"] = "0"', 'import argparse', 'import datetime', 'import json', 'import os', 'import pickle', 'import sys', 'import time', '... | [' args = get_config_env(args, ag_in_env_goal=True)'] | [' ', ' # Other Configurations', ' args.train_demos = int(args.expert_demos * args.perc_train)', ' args.val_demos = args.expert_demos - args.train_demos', ' ', ' # Set number of skills [For unsupervised skill learning]', " if args.num_skills is not None and args.skill_supervision == 'none':", " ... | [] | Function 'get_config_env' used at line 859 is defined at line 735 and has a Long-Range dependency. | {} | {'Function Long-Range': 1} |
infilling_python | RL_Motion_Planning | 892 | 892 | ['import os', "os.environ['TF_CPP_MIN_LOG_LEVEL'] = '2' # Suppress TensorFlow logging", "os.environ['TF_ENABLE_ONEDNN_OPTS'] = '0' # Suppress oneDNN warning", '# os.environ["CUDA_VISIBLE_DEVICES"] = "0"', 'import argparse', 'import datetime', 'import json', 'import os', 'import pickle', 'import sys', 'import time', '... | [' args = get_config(db=db)'] | [' args.algo = algo', ' args.log_dir = log_dir', ' ', ' logger.info("---------------------------------------------------------------------------------------------")', ' config: dict = vars(args)', ' config = {key: str(value) for key, value in config.items()}', ' config = OrderedDict(sorted(config.i... | [] | Function 'get_config' used at line 892 is defined at line 758 and has a Long-Range dependency.
Variable 'db' used at line 892 is defined at line 883 and has a Short-Range dependency. | {} | {'Function Long-Range': 1, 'Variable Short-Range': 1} |
infilling_python | RL_Motion_Planning | 903 | 904 | ['import os', "os.environ['TF_CPP_MIN_LOG_LEVEL'] = '2' # Suppress TensorFlow logging", "os.environ['TF_ENABLE_ONEDNN_OPTS'] = '0' # Suppress oneDNN warning", '# os.environ["CUDA_VISIBLE_DEVICES"] = "0"', 'import argparse', 'import datetime', 'import json', 'import os', 'import pickle', 'import sys', 'import time', '... | [' tf.keras.backend.clear_session()', ' tf.compat.v1.reset_default_graph()'] | [' ', ' # ######################################################################################################## #', ' # ############################################# DATA LOADING ############################################# #', ' # ########################################################################... | [] | Library 'tf' used at line 903 is imported at line 20 and has a Long-Range dependency.
Library 'tf' used at line 904 is imported at line 20 and has a Long-Range dependency. | {} | {'Library Long-Range': 2} |
infilling_python | RL_Motion_Planning | 914 | 915 | ['import os', "os.environ['TF_CPP_MIN_LOG_LEVEL'] = '2' # Suppress TensorFlow logging", "os.environ['TF_ENABLE_ONEDNN_OPTS'] = '0' # Suppress oneDNN warning", '# os.environ["CUDA_VISIBLE_DEVICES"] = "0"', 'import argparse', 'import datetime', 'import json', 'import os', 'import pickle', 'import sys', 'import time', '... | [' buffer_shape, args.buffer_size, args.horizon,', ' sample_transitions(args.trans_style, state_to_goal=state_to_goal(n_objs), num_options=args.c_dim),'] | [' )', ' offline_buffer = ReplayBufferTf(', ' buffer_shape, args.buffer_size, args.horizon,', ' sample_transitions(args.trans_style, state_to_goal=state_to_goal(n_objs), num_options=args.c_dim)', ' )', ' if n_objs == 3:', " expert_data_file = 'three_obj_{}_train.pkl'.format(args.expert_... | [] | Variable 'args' used at line 914 is defined at line 892 and has a Medium-Range dependency.
Function 'sample_transitions' used at line 915 is defined at line 142 and has a Long-Range dependency.
Variable 'args' used at line 915 is defined at line 892 and has a Medium-Range dependency.
Function 'state_to_goal' used at li... | {} | {'Variable Medium-Range': 2, 'Function Long-Range': 2, 'Variable Short-Range': 1} |
infilling_python | RL_Motion_Planning | 918 | 919 | ['import os', "os.environ['TF_CPP_MIN_LOG_LEVEL'] = '2' # Suppress TensorFlow logging", "os.environ['TF_ENABLE_ONEDNN_OPTS'] = '0' # Suppress oneDNN warning", '# os.environ["CUDA_VISIBLE_DEVICES"] = "0"', 'import argparse', 'import datetime', 'import json', 'import os', 'import pickle', 'import sys', 'import time', '... | [' buffer_shape, args.buffer_size, args.horizon,', ' sample_transitions(args.trans_style, state_to_goal=state_to_goal(n_objs), num_options=args.c_dim)'] | [' )', ' if n_objs == 3:', " expert_data_file = 'three_obj_{}_train.pkl'.format(args.expert_behaviour)", " offline_data_file = 'three_obj_{}_offline.pkl'.format(args.expert_behaviour)", ' elif n_objs == 2:', " expert_data_file = 'two_obj_{}_train.pkl'.format(args.expert_behaviour)", " ... | [] | Variable 'args' used at line 918 is defined at line 892 and has a Medium-Range dependency.
Function 'sample_transitions' used at line 919 is defined at line 142 and has a Long-Range dependency.
Variable 'args' used at line 919 is defined at line 892 and has a Medium-Range dependency.
Function 'state_to_goal' used at li... | {} | {'Variable Medium-Range': 2, 'Function Long-Range': 2, 'Variable Short-Range': 1} |
infilling_python | RL_Motion_Planning | 952 | 952 | ['import os', "os.environ['TF_CPP_MIN_LOG_LEVEL'] = '2' # Suppress TensorFlow logging", "os.environ['TF_ENABLE_ONEDNN_OPTS'] = '0' # Suppress oneDNN warning", '# os.environ["CUDA_VISIBLE_DEVICES"] = "0"', 'import argparse', 'import datetime', 'import json', 'import os', 'import pickle', 'import sys', 'import time', '... | [" prev_skills = repurpose_skill_seq(args, buffered_data['prev_skills'])"] | [" buffered_data['curr_skills'] = curr_skills", " buffered_data['prev_skills'] = prev_skills", ' # Add a new key "has_gt_skill" indicating that the skill is G.T.', " buffered_data['has_gt_skill'] = tf.ones_like(buffered_data['successes'], dtype=tf.float32)", ' expert_buffer.load_data_into_buffer(buffered... | [] | Function 'repurpose_skill_seq' used at line 952 is defined at line 89 and has a Long-Range dependency.
Variable 'args' used at line 952 is defined at line 892 and has a Long-Range dependency.
Variable 'buffered_data' used at line 952 is defined at line 948 and has a Short-Range dependency. | {} | {'Function Long-Range': 1, 'Variable Long-Range': 1, 'Variable Short-Range': 1} |
infilling_python | RL_Motion_Planning | 962 | 962 | ['import os', "os.environ['TF_CPP_MIN_LOG_LEVEL'] = '2' # Suppress TensorFlow logging", "os.environ['TF_ENABLE_ONEDNN_OPTS'] = '0' # Suppress oneDNN warning", '# os.environ["CUDA_VISIBLE_DEVICES"] = "0"', 'import argparse', 'import datetime', 'import json', 'import os', 'import pickle', 'import sys', 'import time', '... | [' buffered_data = pickle.load(handle)'] | [' ', ' # [Optional] Reformat the G.T. skill sequences', " curr_skills = repurpose_skill_seq(args, buffered_data['curr_skills'])", " prev_skills = repurpose_skill_seq(args, buffered_data['prev_skills'])", " buffered_data['curr_skills'] = curr_skills", " buffered_data['prev_skills'] = prev_skills", ' ... | [] | Library 'pickle' used at line 962 is imported at line 12 and has a Long-Range dependency. | {} | {'Library Long-Range': 1} |
infilling_python | simplex_method | 4 | 4 | ['import heapq', '# Calculate the dot product of two vectors', 'def dot(a,b):'] | [' return sum(x*y for x,y in zip(a,b))'] | ['', '# Get a specific column from a 2D list (matrix)', 'def column(A, j):', ' return [row[j] for row in A]', '', '# Transpose a 2D list (matrix)', 'def transpose(A):', ' return [column(A, j) for j in range(len(A[0]))]', '', '# Check if a column is a pivot column', 'def isPivotCol(col):', ' return (len([c for c i... | [{'reason_category': 'Generator_Expressions', 'usage_line': 4}] | Variable 'x' used at line 4 is part of a Generator_Expressions defined at line 4 and has a Short-Range dependency.
Variable 'y' used at line 4 is part of a Generator_Expressions defined at line 4 and has a Short-Range dependency.
Variable 'a' used at line 4 is defined at line 3 and has a Short-Range dependency.
Variabl... | {'Generator_Expressions': 1} | {'Variable Generator_Expressions Short-Range': 2, 'Variable Short-Range': 2} |
infilling_python | simplex_method | 8 | 8 | ['import heapq', '# Calculate the dot product of two vectors', 'def dot(a,b):', ' return sum(x*y for x,y in zip(a,b))', '', '# Get a specific column from a 2D list (matrix)', 'def column(A, j):'] | [' return [row[j] for row in A]'] | ['', '# Transpose a 2D list (matrix)', 'def transpose(A):', ' return [column(A, j) for j in range(len(A[0]))]', '', '# Check if a column is a pivot column', 'def isPivotCol(col):', ' return (len([c for c in col if c == 0]) == len(col) - 1) and sum(col) == 1', '', '# Find the value of a variable for a pivot column',... | [{'reason_category': 'List_Comprehension', 'usage_line': 8}] | Variable 'row' used at line 8 is part of a List_Comprehension defined at line 8 and has a Short-Range dependency.
Variable 'A' used at line 8 is defined at line 7 and has a Short-Range dependency.
Variable 'j' used at line 8 is defined at line 7 and has a Short-Range dependency. | {'List_Comprehension': 1} | {'Variable List_Comprehension Short-Range': 1, 'Variable Short-Range': 2} |
infilling_python | simplex_method | 12 | 12 | ['import heapq', '# Calculate the dot product of two vectors', 'def dot(a,b):', ' return sum(x*y for x,y in zip(a,b))', '', '# Get a specific column from a 2D list (matrix)', 'def column(A, j):', ' return [row[j] for row in A]', '', '# Transpose a 2D list (matrix)', 'def transpose(A):'] | [' return [column(A, j) for j in range(len(A[0]))]'] | ['', '# Check if a column is a pivot column', 'def isPivotCol(col):', ' return (len([c for c in col if c == 0]) == len(col) - 1) and sum(col) == 1', '', '# Find the value of a variable for a pivot column', 'def variableValueForPivotColumn(tableau, column):', ' pivotRow = [i for (i, x) in enumerate(column) if x == 1... | [{'reason_category': 'List_Comprehension', 'usage_line': 12}] | Variable 'j' used at line 12 is part of a List_Comprehension defined at line 12 and has a Short-Range dependency.
Variable 'A' used at line 12 is defined at line 11 and has a Short-Range dependency.
Function 'column' used at line 12 is defined at line 7 and has a Short-Range dependency. | {'List_Comprehension': 1} | {'Variable List_Comprehension Short-Range': 1, 'Variable Short-Range': 1, 'Function Short-Range': 1} |
infilling_python | simplex_method | 16 | 16 | ['import heapq', '# Calculate the dot product of two vectors', 'def dot(a,b):', ' return sum(x*y for x,y in zip(a,b))', '', '# Get a specific column from a 2D list (matrix)', 'def column(A, j):', ' return [row[j] for row in A]', '', '# Transpose a 2D list (matrix)', 'def transpose(A):', ' return [column(A, j) for... | [' return (len([c for c in col if c == 0]) == len(col) - 1) and sum(col) == 1'] | ['', '# Find the value of a variable for a pivot column', 'def variableValueForPivotColumn(tableau, column):', ' pivotRow = [i for (i, x) in enumerate(column) if x == 1][0]', ' return tableau[pivotRow][-1]', '', '# Check if we can improve the current solution', 'def canImprove(tableau):', ' lastRow = tableau[-1]'... | [{'reason_category': 'List_Comprehension', 'usage_line': 16}] | Variable 'c' used at line 16 is part of a List_Comprehension defined at line 16 and has a Short-Range dependency.
Variable 'col' used at line 16 is defined at line 15 and has a Short-Range dependency. | {'List_Comprehension': 1} | {'Variable List_Comprehension Short-Range': 1, 'Variable Short-Range': 1} |
infilling_python | simplex_method | 20 | 21 | ['import heapq', '# Calculate the dot product of two vectors', 'def dot(a,b):', ' return sum(x*y for x,y in zip(a,b))', '', '# Get a specific column from a 2D list (matrix)', 'def column(A, j):', ' return [row[j] for row in A]', '', '# Transpose a 2D list (matrix)', 'def transpose(A):', ' return [column(A, j) for... | [' pivotRow = [i for (i, x) in enumerate(column) if x == 1][0]', ' return tableau[pivotRow][-1]'] | ['', '# Check if we can improve the current solution', 'def canImprove(tableau):', ' lastRow = tableau[-1]', ' return any(x > 0 for x in lastRow[:-1])', '', "# Check if there's more than one minimum in a list", 'def moreThanOneMin(L):', ' if len(L) <= 1:', ' return False', ' x,y = heapq.nsmallest(2, L, key... | [{'reason_category': 'List_Comprehension', 'usage_line': 20}] | Variable 'i' used at line 20 is part of a List_Comprehension defined at line 20 and has a Short-Range dependency.
Variable 'x' used at line 20 is part of a List_Comprehension defined at line 20 and has a Short-Range dependency.
Variable 'column' used at line 20 is defined at line 19 and has a Short-Range dependency.
Va... | {'List_Comprehension': 1} | {'Variable List_Comprehension Short-Range': 2, 'Variable Short-Range': 3} |
infilling_python | simplex_method | 25 | 26 | ['import heapq', '# Calculate the dot product of two vectors', 'def dot(a,b):', ' return sum(x*y for x,y in zip(a,b))', '', '# Get a specific column from a 2D list (matrix)', 'def column(A, j):', ' return [row[j] for row in A]', '', '# Transpose a 2D list (matrix)', 'def transpose(A):', ' return [column(A, j) for... | [' lastRow = tableau[-1]', ' return any(x > 0 for x in lastRow[:-1])'] | ['', "# Check if there's more than one minimum in a list", 'def moreThanOneMin(L):', ' if len(L) <= 1:', ' return False', ' x,y = heapq.nsmallest(2, L, key=lambda x: x[1])', ' return x == y', '', '# Create an identity matrix with certain specifications', 'def identity(numRows, numCols, val=1, rowStart=0):', ... | [{'reason_category': 'Generator_Expressions', 'usage_line': 26}] | Variable 'tableau' used at line 25 is defined at line 24 and has a Short-Range dependency.
Variable 'x' used at line 26 is part of a Generator_Expressions defined at line 26 and has a Short-Range dependency.
Variable 'lastRow' used at line 26 is defined at line 25 and has a Short-Range dependency. | {'Generator_Expressions': 1} | {'Variable Short-Range': 2, 'Variable Generator_Expressions Short-Range': 1} |
infilling_python | simplex_method | 32 | 33 | ['import heapq', '# Calculate the dot product of two vectors', 'def dot(a,b):', ' return sum(x*y for x,y in zip(a,b))', '', '# Get a specific column from a 2D list (matrix)', 'def column(A, j):', ' return [row[j] for row in A]', '', '# Transpose a 2D list (matrix)', 'def transpose(A):', ' return [column(A, j) for... | [' x,y = heapq.nsmallest(2, L, key=lambda x: x[1])', ' return x == y'] | ['', '# Create an identity matrix with certain specifications', 'def identity(numRows, numCols, val=1, rowStart=0):', ' return [[(val if i == j else 0) for j in range(numCols)] for i in range(rowStart, numRows)] ', '', 'def standardForm(cost, greaterThans=[], gtThreshold=[], lessThans=[], ltThreshold=[], equalities=[... | [{'reason_category': 'Lambda_Expressions', 'usage_line': 32}] | Library 'heapq' used at line 32 is imported at line 1 and has a Long-Range dependency.
Variable 'L' used at line 32 is defined at line 29 and has a Short-Range dependency.
Variable 'x' used at line 32 is part of a Lambda_Expressions defined at line 32 and has a Short-Range dependency.
Variable 'x' used at line 33 is de... | {'Lambda_Expressions': 1} | {'Library Long-Range': 1, 'Variable Short-Range': 3, 'Variable Lambda_Expressions Short-Range': 1} |
infilling_python | simplex_method | 37 | 37 | ['import heapq', '# Calculate the dot product of two vectors', 'def dot(a,b):', ' return sum(x*y for x,y in zip(a,b))', '', '# Get a specific column from a 2D list (matrix)', 'def column(A, j):', ' return [row[j] for row in A]', '', '# Transpose a 2D list (matrix)', 'def transpose(A):', ' return [column(A, j) for... | [' return [[(val if i == j else 0) for j in range(numCols)] for i in range(rowStart, numRows)] '] | ['', 'def standardForm(cost, greaterThans=[], gtThreshold=[], lessThans=[], ltThreshold=[], equalities=[], eqThreshold=[], maximization=True):', ' # Initialize variables for the count of new variables and the number of rows in the tableau', ' newVars = 0', ' numRows = 0', '', ' # Adjust the number of variables ... | [{'reason_category': 'List_Comprehension', 'usage_line': 37}] | Variable 'i' used at line 37 is part of a List_Comprehension defined at line 37 and has a Short-Range dependency.
Variable 'rowStart' used at line 37 is defined at line 36 and has a Short-Range dependency.
Variable 'numRows' used at line 37 is defined at line 36 and has a Short-Range dependency.
Variable 'j' used at li... | {'List_Comprehension': 1} | {'Variable List_Comprehension Short-Range': 2, 'Variable Short-Range': 4} |
infilling_python | simplex_method | 51 | 52 | ['import heapq', '# Calculate the dot product of two vectors', 'def dot(a,b):', ' return sum(x*y for x,y in zip(a,b))', '', '# Get a specific column from a 2D list (matrix)', 'def column(A, j):', ' return [row[j] for row in A]', '', '# Transpose a 2D list (matrix)', 'def transpose(A):', ' return [column(A, j) for... | [' newVars += len(ltThreshold)', ' numRows += len(ltThreshold)'] | [' ', " # Equalities don't need slack variables but add to the number of rows", ' if eqThreshold != []:', ' numRows += len(eqThreshold)', '', ' # If the problem is a minimization, convert it to a maximization by negating the cost vector ', ' if not maximization:', ' cost = [-x for x in cost]', '',... | [{'reason_category': 'If Body', 'usage_line': 51}, {'reason_category': 'If Body', 'usage_line': 52}] | Variable 'newVars' used at line 51 is defined at line 41 and has a Short-Range dependency.
Variable 'ltThreshold' used at line 51 is defined at line 39 and has a Medium-Range dependency.
Variable 'numRows' used at line 52 is defined at line 42 and has a Short-Range dependency.
Variable 'ltThreshold' used at line 52 is ... | {'If Body': 2} | {'Variable Short-Range': 2, 'Variable Medium-Range': 2} |
infilling_python | simplex_method | 56 | 56 | ['import heapq', '# Calculate the dot product of two vectors', 'def dot(a,b):', ' return sum(x*y for x,y in zip(a,b))', '', '# Get a specific column from a 2D list (matrix)', 'def column(A, j):', ' return [row[j] for row in A]', '', '# Transpose a 2D list (matrix)', 'def transpose(A):', ' return [column(A, j) for... | [' numRows += len(eqThreshold)'] | ['', ' # If the problem is a minimization, convert it to a maximization by negating the cost vector ', ' if not maximization:', ' cost = [-x for x in cost]', '', ' # If no new variables are needed, the problem is already in standard form', ' if newVars == 0:', ' return cost, equalities, eqThreshold'... | [{'reason_category': 'If Body', 'usage_line': 56}] | Variable 'numRows' used at line 56 is defined at line 42 and has a Medium-Range dependency.
Variable 'eqThreshold' used at line 56 is defined at line 39 and has a Medium-Range dependency. | {'If Body': 1} | {'Variable Medium-Range': 2} |
infilling_python | simplex_method | 60 | 60 | ['import heapq', '# Calculate the dot product of two vectors', 'def dot(a,b):', ' return sum(x*y for x,y in zip(a,b))', '', '# Get a specific column from a 2D list (matrix)', 'def column(A, j):', ' return [row[j] for row in A]', '', '# Transpose a 2D list (matrix)', 'def transpose(A):', ' return [column(A, j) for... | [' cost = [-x for x in cost]'] | ['', ' # If no new variables are needed, the problem is already in standard form', ' if newVars == 0:', ' return cost, equalities, eqThreshold', '', ' # Extend the cost function with zeros for the new slack variables', ' newCost = list(cost) + [0] * newVars', ' constraints = []', ' threshold = []', '',... | [{'reason_category': 'If Body', 'usage_line': 60}, {'reason_category': 'List_Comprehension', 'usage_line': 60}] | Variable 'x' used at line 60 is part of a List_Comprehension defined at line 60 and has a Short-Range dependency.
Variable 'cost' used at line 60 is defined at line 39 and has a Medium-Range dependency. | {'If Body': 1, 'List_Comprehension': 1} | {'Variable List_Comprehension Short-Range': 1, 'Variable Medium-Range': 1} |
infilling_python | simplex_method | 67 | 67 | ['import heapq', '# Calculate the dot product of two vectors', 'def dot(a,b):', ' return sum(x*y for x,y in zip(a,b))', '', '# Get a specific column from a 2D list (matrix)', 'def column(A, j):', ' return [row[j] for row in A]', '', '# Transpose a 2D list (matrix)', 'def transpose(A):', ' return [column(A, j) for... | [' newCost = list(cost) + [0] * newVars'] | [' constraints = []', ' threshold = []', '', " # Prepare the constraints for each condition ('greater than', 'less than', 'equal to')", ' oldConstraints = [(greaterThans, gtThreshold, -1), (lessThans, ltThreshold, 1), (equalities, eqThreshold, 0)]', ' offset = 0', '', ' # Process each set of constraints', '... | [] | Variable 'cost' used at line 67 is defined at line 39 and has a Medium-Range dependency.
Variable 'newVars' used at line 67 is defined at line 41 and has a Medium-Range dependency. | {} | {'Variable Medium-Range': 2} |
infilling_python | simplex_method | 78 | 78 | ['import heapq', '# Calculate the dot product of two vectors', 'def dot(a,b):', ' return sum(x*y for x,y in zip(a,b))', '', '# Get a specific column from a 2D list (matrix)', 'def column(A, j):', ' return [row[j] for row in A]', '', '# Transpose a 2D list (matrix)', 'def transpose(A):', ' return [column(A, j) for... | [' constraints += [c + r for c, r in zip(constraintList, identity(numRows, newVars, coefficient, offset))]'] | [' # Append the thresholds for each constraint', ' threshold += oldThreshold', ' # Increase the offset for the identity matrix used for the next set of constraints', ' offset += len(oldThreshold)', '', ' return newCost, constraints, threshold', '', "'''", ' simplex: [float], [[float]], [float] -... | [{'reason_category': 'Loop Body', 'usage_line': 78}, {'reason_category': 'List_Comprehension', 'usage_line': 78}] | Variable 'constraints' used at line 78 is defined at line 68 and has a Short-Range dependency.
Variable 'c' used at line 78 is part of a List_Comprehension defined at line 78 and has a Short-Range dependency.
Variable 'r' used at line 78 is part of a List_Comprehension defined at line 78 and has a Short-Range dependenc... | {'Loop Body': 1, 'List_Comprehension': 1} | {'Variable Short-Range': 2, 'Variable List_Comprehension Short-Range': 2, 'Variable Loop Short-Range': 2, 'Function Long-Range': 1, 'Variable Long-Range': 2} |
infilling_python | simplex_method | 80 | 80 | ['import heapq', '# Calculate the dot product of two vectors', 'def dot(a,b):', ' return sum(x*y for x,y in zip(a,b))', '', '# Get a specific column from a 2D list (matrix)', 'def column(A, j):', ' return [row[j] for row in A]', '', '# Transpose a 2D list (matrix)', 'def transpose(A):', ' return [column(A, j) for... | [' threshold += oldThreshold'] | [' # Increase the offset for the identity matrix used for the next set of constraints', ' offset += len(oldThreshold)', '', ' return newCost, constraints, threshold', '', "'''", ' simplex: [float], [[float]], [float] -> [float], float', ' Solve the given standard-form linear program:', ' max <c,x>'... | [{'reason_category': 'Loop Body', 'usage_line': 80}] | Variable 'threshold' used at line 80 is defined at line 69 and has a Medium-Range dependency.
Variable 'oldThreshold' used at line 80 is part of a Loop defined at line 76 and has a Short-Range dependency. | {'Loop Body': 1} | {'Variable Medium-Range': 1, 'Variable Loop Short-Range': 1} |
infilling_python | simplex_method | 82 | 82 | ['import heapq', '# Calculate the dot product of two vectors', 'def dot(a,b):', ' return sum(x*y for x,y in zip(a,b))', '', '# Get a specific column from a 2D list (matrix)', 'def column(A, j):', ' return [row[j] for row in A]', '', '# Transpose a 2D list (matrix)', 'def transpose(A):', ' return [column(A, j) for... | [' offset += len(oldThreshold)'] | ['', ' return newCost, constraints, threshold', '', "'''", ' simplex: [float], [[float]], [float] -> [float], float', ' Solve the given standard-form linear program:', ' max <c,x>', ' s.t. Ax = b', ' x >= 0', ' providing the optimal solution x* and the value of the objective function', "'''"... | [{'reason_category': 'Loop Body', 'usage_line': 82}] | Variable 'offset' used at line 82 is defined at line 73 and has a Short-Range dependency.
Variable 'oldThreshold' used at line 82 is part of a Loop defined at line 76 and has a Short-Range dependency. | {'Loop Body': 1} | {'Variable Short-Range': 1, 'Variable Loop Short-Range': 1} |
infilling_python | simplex_method | 96 | 97 | ['import heapq', '# Calculate the dot product of two vectors', 'def dot(a,b):', ' return sum(x*y for x,y in zip(a,b))', '', '# Get a specific column from a 2D list (matrix)', 'def column(A, j):', ' return [row[j] for row in A]', '', '# Transpose a 2D list (matrix)', 'def transpose(A):', ' return [column(A, j) for... | [' tableau = [row[:] + [x] for row, x in zip(A, b)]', ' tableau.append([ci for ci in c] + [0])'] | [' print("Initial tableau:")', ' for row in tableau:', ' print(row)', ' print()', '', ' # Iterate until no improvements can be made', ' while canImprove(tableau):', ' # Choose entering variable (minimum positive index of the last row)', ' column_choices = [(i,x) for (i,x) in enumerate(tableau[-... | [{'reason_category': 'List_Comprehension', 'usage_line': 96}, {'reason_category': 'List_Comprehension', 'usage_line': 97}] | Variable 'row' used at line 96 is part of a List_Comprehension defined at line 96 and has a Short-Range dependency.
Variable 'x' used at line 96 is part of a List_Comprehension defined at line 96 and has a Short-Range dependency.
Variable 'A' used at line 96 is defined at line 94 and has a Short-Range dependency.
Varia... | {'List_Comprehension': 2} | {'Variable List_Comprehension Short-Range': 3, 'Variable Short-Range': 4} |
infilling_python | simplex_method | 106 | 107 | ['import heapq', '# Calculate the dot product of two vectors', 'def dot(a,b):', ' return sum(x*y for x,y in zip(a,b))', '', '# Get a specific column from a 2D list (matrix)', 'def column(A, j):', ' return [row[j] for row in A]', '', '# Transpose a 2D list (matrix)', 'def transpose(A):', ' return [column(A, j) for... | [' column_choices = [(i,x) for (i,x) in enumerate(tableau[-1][:-1]) if x > 0]', ' column = min(column_choices, key=lambda a: a[1])[0]'] | ['', ' # Check for unboundedness', ' if all(row[column] <= 0 for row in tableau):', " raise Exception('Linear program is unbounded.')", '', ' # Check for degeneracy: more than one minimizer of the quotient', ' quotients = [(i, r[-1] / r[column]) for i,r in enumerate(tableau[:-1]) if r[column... | [{'reason_category': 'Loop Body', 'usage_line': 106}, {'reason_category': 'List_Comprehension', 'usage_line': 106}, {'reason_category': 'Loop Body', 'usage_line': 107}, {'reason_category': 'Lambda_Expressions', 'usage_line': 107}] | Variable 'i' used at line 106 is part of a List_Comprehension defined at line 106 and has a Short-Range dependency.
Variable 'x' used at line 106 is part of a List_Comprehension defined at line 106 and has a Short-Range dependency.
Variable 'tableau' used at line 106 is defined at line 97 and has a Short-Range dependen... | {'Loop Body': 2, 'List_Comprehension': 1, 'Lambda_Expressions': 1} | {'Variable List_Comprehension Short-Range': 2, 'Variable Short-Range': 2, 'Variable Lambda_Expressions Short-Range': 1} |
infilling_python | simplex_method | 110 | 111 | ['import heapq', '# Calculate the dot product of two vectors', 'def dot(a,b):', ' return sum(x*y for x,y in zip(a,b))', '', '# Get a specific column from a 2D list (matrix)', 'def column(A, j):', ' return [row[j] for row in A]', '', '# Transpose a 2D list (matrix)', 'def transpose(A):', ' return [column(A, j) for... | [' if all(row[column] <= 0 for row in tableau):', " raise Exception('Linear program is unbounded.')"] | ['', ' # Check for degeneracy: more than one minimizer of the quotient', ' quotients = [(i, r[-1] / r[column]) for i,r in enumerate(tableau[:-1]) if r[column] > 0]', '', ' if moreThanOneMin(quotients):', " raise Exception('Linear program is degenerate.')", '', ' # Chosing leaving variable (r... | [{'reason_category': 'Loop Body', 'usage_line': 110}, {'reason_category': 'If Condition', 'usage_line': 110}, {'reason_category': 'Generator_Expressions', 'usage_line': 110}, {'reason_category': 'Loop Body', 'usage_line': 111}, {'reason_category': 'If Body', 'usage_line': 111}] | Variable 'row' used at line 110 is part of a Generator_Expressions defined at line 110 and has a Short-Range dependency.
Variable 'tableau' used at line 110 is defined at line 97 and has a Medium-Range dependency.
Variable 'column' used at line 110 is defined at line 107 and has a Short-Range dependency. | {'Loop Body': 2, 'If Condition': 1, 'Generator_Expressions': 1, 'If Body': 1} | {'Variable Generator_Expressions Short-Range': 1, 'Variable Medium-Range': 1, 'Variable Short-Range': 1} |
infilling_python | simplex_method | 114 | 114 | ['import heapq', '# Calculate the dot product of two vectors', 'def dot(a,b):', ' return sum(x*y for x,y in zip(a,b))', '', '# Get a specific column from a 2D list (matrix)', 'def column(A, j):', ' return [row[j] for row in A]', '', '# Transpose a 2D list (matrix)', 'def transpose(A):', ' return [column(A, j) for... | [' quotients = [(i, r[-1] / r[column]) for i,r in enumerate(tableau[:-1]) if r[column] > 0]'] | ['', ' if moreThanOneMin(quotients):', " raise Exception('Linear program is degenerate.')", '', ' # Chosing leaving variable (row index minimizing the quotient)', ' row = min(quotients, key=lambda x: x[1])[0]', '', ' #pivots on the chosen row and column', ' pivot = row, column', '', ' ... | [{'reason_category': 'Loop Body', 'usage_line': 114}, {'reason_category': 'List_Comprehension', 'usage_line': 114}] | Variable 'i' used at line 114 is part of a List_Comprehension defined at line 114 and has a Short-Range dependency.
Variable 'r' used at line 114 is part of a List_Comprehension defined at line 114 and has a Short-Range dependency.
Variable 'tableau' used at line 114 is defined at line 97 and has a Medium-Range depende... | {'Loop Body': 1, 'List_Comprehension': 1} | {'Variable List_Comprehension Short-Range': 2, 'Variable Medium-Range': 1, 'Variable Short-Range': 1} |
infilling_python | simplex_method | 120 | 120 | ['import heapq', '# Calculate the dot product of two vectors', 'def dot(a,b):', ' return sum(x*y for x,y in zip(a,b))', '', '# Get a specific column from a 2D list (matrix)', 'def column(A, j):', ' return [row[j] for row in A]', '', '# Transpose a 2D list (matrix)', 'def transpose(A):', ' return [column(A, j) for... | [' row = min(quotients, key=lambda x: x[1])[0]'] | ['', ' #pivots on the chosen row and column', ' pivot = row, column', '', ' print("Next pivot index is=%d,%d \\n" % pivot)', ' i,j = pivot', ' pivotDenom = tableau[i][j]', '', ' # Normalize the pivot row', ' tableau[i] = [x / pivotDenom for x in tableau[i]]', '', ' # Zero out the... | [{'reason_category': 'Loop Body', 'usage_line': 120}, {'reason_category': 'Lambda_Expressions', 'usage_line': 120}] | Variable 'quotients' used at line 120 is defined at line 114 and has a Short-Range dependency.
Variable 'x' used at line 120 is part of a Lambda_Expressions defined at line 120 and has a Short-Range dependency. | {'Loop Body': 1, 'Lambda_Expressions': 1} | {'Variable Short-Range': 1, 'Variable Lambda_Expressions Short-Range': 1} |
infilling_python | simplex_method | 123 | 123 | ['import heapq', '# Calculate the dot product of two vectors', 'def dot(a,b):', ' return sum(x*y for x,y in zip(a,b))', '', '# Get a specific column from a 2D list (matrix)', 'def column(A, j):', ' return [row[j] for row in A]', '', '# Transpose a 2D list (matrix)', 'def transpose(A):', ' return [column(A, j) for... | [' pivot = row, column'] | ['', ' print("Next pivot index is=%d,%d \\n" % pivot)', ' i,j = pivot', ' pivotDenom = tableau[i][j]', '', ' # Normalize the pivot row', ' tableau[i] = [x / pivotDenom for x in tableau[i]]', '', ' # Zero out the other entries in the pivot column', ' for k,row in enumerate(tableau):', ... | [{'reason_category': 'Loop Body', 'usage_line': 123}] | Variable 'row' used at line 123 is defined at line 120 and has a Short-Range dependency.
Variable 'column' used at line 123 is defined at line 107 and has a Medium-Range dependency. | {'Loop Body': 1} | {'Variable Short-Range': 1, 'Variable Medium-Range': 1} |
infilling_python | simplex_method | 127 | 127 | ['import heapq', '# Calculate the dot product of two vectors', 'def dot(a,b):', ' return sum(x*y for x,y in zip(a,b))', '', '# Get a specific column from a 2D list (matrix)', 'def column(A, j):', ' return [row[j] for row in A]', '', '# Transpose a 2D list (matrix)', 'def transpose(A):', ' return [column(A, j) for... | [' pivotDenom = tableau[i][j]'] | ['', ' # Normalize the pivot row', ' tableau[i] = [x / pivotDenom for x in tableau[i]]', '', ' # Zero out the other entries in the pivot column', ' for k,row in enumerate(tableau):', ' if k != i:', ' pivotRowMultiple = [y * tableau[k][j] for y in tableau[i]]', ' tableau... | [{'reason_category': 'Loop Body', 'usage_line': 127}] | Variable 'tableau' used at line 127 is defined at line 97 and has a Medium-Range dependency.
Variable 'i' used at line 127 is defined at line 126 and has a Short-Range dependency.
Variable 'j' used at line 127 is defined at line 126 and has a Short-Range dependency. | {'Loop Body': 1} | {'Variable Medium-Range': 1, 'Variable Short-Range': 2} |
infilling_python | simplex_method | 130 | 130 | ['import heapq', '# Calculate the dot product of two vectors', 'def dot(a,b):', ' return sum(x*y for x,y in zip(a,b))', '', '# Get a specific column from a 2D list (matrix)', 'def column(A, j):', ' return [row[j] for row in A]', '', '# Transpose a 2D list (matrix)', 'def transpose(A):', ' return [column(A, j) for... | [' tableau[i] = [x / pivotDenom for x in tableau[i]]'] | ['', ' # Zero out the other entries in the pivot column', ' for k,row in enumerate(tableau):', ' if k != i:', ' pivotRowMultiple = [y * tableau[k][j] for y in tableau[i]]', ' tableau[k] = [x - y for x,y in zip(tableau[k], pivotRowMultiple)]', ' print("Tableau after pivot:")'... | [{'reason_category': 'Loop Body', 'usage_line': 130}, {'reason_category': 'List_Comprehension', 'usage_line': 130}] | Variable 'tableau' used at line 130 is defined at line 97 and has a Long-Range dependency.
Variable 'i' used at line 130 is defined at line 126 and has a Short-Range dependency.
Variable 'x' used at line 130 is part of a List_Comprehension defined at line 130 and has a Short-Range dependency.
Variable 'pivotDenom' used... | {'Loop Body': 1, 'List_Comprehension': 1} | {'Variable Long-Range': 1, 'Variable Short-Range': 2, 'Variable List_Comprehension Short-Range': 1} |
infilling_python | simplex_method | 134 | 136 | ['import heapq', '# Calculate the dot product of two vectors', 'def dot(a,b):', ' return sum(x*y for x,y in zip(a,b))', '', '# Get a specific column from a 2D list (matrix)', 'def column(A, j):', ' return [row[j] for row in A]', '', '# Transpose a 2D list (matrix)', 'def transpose(A):', ' return [column(A, j) for... | [' if k != i:', ' pivotRowMultiple = [y * tableau[k][j] for y in tableau[i]]', ' tableau[k] = [x - y for x,y in zip(tableau[k], pivotRowMultiple)]'] | [' print("Tableau after pivot:")', ' for row in tableau:', ' print(row)', ' print()', ' ', ' # Transpose the tableau to make it easier to work with columns', ' columns = transpose(tableau)', '', ' # Identify pivot columns in the tableau. A column is a pivot column if it has a single 1 and... | [{'reason_category': 'Loop Body', 'usage_line': 134}, {'reason_category': 'If Condition', 'usage_line': 134}, {'reason_category': 'Loop Body', 'usage_line': 135}, {'reason_category': 'List_Comprehension', 'usage_line': 135}, {'reason_category': 'If Body', 'usage_line': 135}, {'reason_category': 'Loop Body', 'usage_line... | Variable 'k' used at line 134 is part of a Loop defined at line 133 and has a Short-Range dependency.
Variable 'i' used at line 134 is defined at line 126 and has a Short-Range dependency.
Variable 'y' used at line 135 is part of a List_Comprehension defined at line 135 and has a Short-Range dependency.
Variable 'table... | {'Loop Body': 3, 'If Condition': 1, 'List_Comprehension': 2, 'If Body': 2} | {'Variable Loop Short-Range': 3, 'Variable Short-Range': 6, 'Variable List_Comprehension Short-Range': 3} |
infilling_python | simplex_method | 143 | 143 | ['import heapq', '# Calculate the dot product of two vectors', 'def dot(a,b):', ' return sum(x*y for x,y in zip(a,b))', '', '# Get a specific column from a 2D list (matrix)', 'def column(A, j):', ' return [row[j] for row in A]', '', '# Transpose a 2D list (matrix)', 'def transpose(A):', ' return [column(A, j) for... | [' columns = transpose(tableau)'] | ['', ' # Identify pivot columns in the tableau. A column is a pivot column if it has a single 1 and the rest of its entries are 0.', ' indices = [j for j, col in enumerate(columns[:-1]) if isPivotCol(col)]', '', ' # Looking at the rightmost entry (the value part of the tableau row) of the row where the 1 in the p... | [] | Function 'transpose' used at line 143 is defined at line 11 and has a Long-Range dependency.
Variable 'tableau' used at line 143 is defined at line 97 and has a Long-Range dependency. | {} | {'Function Long-Range': 1, 'Variable Long-Range': 1} |
infilling_python | simplex_method | 146 | 146 | ['import heapq', '# Calculate the dot product of two vectors', 'def dot(a,b):', ' return sum(x*y for x,y in zip(a,b))', '', '# Get a specific column from a 2D list (matrix)', 'def column(A, j):', ' return [row[j] for row in A]', '', '# Transpose a 2D list (matrix)', 'def transpose(A):', ' return [column(A, j) for... | [' indices = [j for j, col in enumerate(columns[:-1]) if isPivotCol(col)]'] | ['', ' # Looking at the rightmost entry (the value part of the tableau row) of the row where the 1 in the pivot column is located.', ' primal_solution = [(colIndex, variableValueForPivotColumn(tableau, columns[colIndex])) for colIndex in indices]', ' ', ' # The last entry of the last row of the tableau gives us... | [{'reason_category': 'List_Comprehension', 'usage_line': 146}] | Variable 'j' used at line 146 is part of a List_Comprehension defined at line 146 and has a Short-Range dependency.
Variable 'col' used at line 146 is part of a List_Comprehension defined at line 146 and has a Short-Range dependency.
Variable 'columns' used at line 146 is defined at line 143 and has a Short-Range depen... | {'List_Comprehension': 1} | {'Variable List_Comprehension Short-Range': 2, 'Variable Short-Range': 1, 'Function Long-Range': 1} |
infilling_python | simplex_method | 149 | 149 | ['import heapq', '# Calculate the dot product of two vectors', 'def dot(a,b):', ' return sum(x*y for x,y in zip(a,b))', '', '# Get a specific column from a 2D list (matrix)', 'def column(A, j):', ' return [row[j] for row in A]', '', '# Transpose a 2D list (matrix)', 'def transpose(A):', ' return [column(A, j) for... | [' primal_solution = [(colIndex, variableValueForPivotColumn(tableau, columns[colIndex])) for colIndex in indices]'] | [' ', ' # The last entry of the last row of the tableau gives us the negation of the objective function value.', ' objective_value = -(tableau[-1][-1])', '', ' return tableau, primal_solution, objective_value'] | [{'reason_category': 'List_Comprehension', 'usage_line': 149}] | Variable 'colIndex' used at line 149 is part of a List_Comprehension defined at line 149 and has a Short-Range dependency.
Variable 'indices' used at line 149 is defined at line 146 and has a Short-Range dependency.
Function 'variableValueForPivotColumn' used at line 149 is defined at line 19 and has a Long-Range depen... | {'List_Comprehension': 1} | {'Variable List_Comprehension Short-Range': 1, 'Variable Short-Range': 2, 'Function Long-Range': 1, 'Variable Long-Range': 1} |
infilling_python | simplex_method | 152 | 152 | ['import heapq', '# Calculate the dot product of two vectors', 'def dot(a,b):', ' return sum(x*y for x,y in zip(a,b))', '', '# Get a specific column from a 2D list (matrix)', 'def column(A, j):', ' return [row[j] for row in A]', '', '# Transpose a 2D list (matrix)', 'def transpose(A):', ' return [column(A, j) for... | [' objective_value = -(tableau[-1][-1])'] | ['', ' return tableau, primal_solution, objective_value'] | [] | Variable 'tableau' used at line 152 is defined at line 97 and has a Long-Range dependency. | {} | {'Variable Long-Range': 1} |
completion_python | Image_Filtering | 17 | 22 | ['import numpy as np', 'import cv2', 'import matplotlib.pyplot as plt', 'from scipy.signal import convolve2d', 'from scipy.signal import butter, filtfilt', '', '# Task1', '# Gaussian blurring einstein monroe illusion', 'def gaussian2D(sigma, kernel_size):', ' sigma_x, sigma_y = sigma', ' size_x, size_y = kernel_s... | [' np.linspace(-3*sigma_y, 3*sigma_y, size_y))', ' ', ' kernel = np.exp(-(x**2 / (2*sigma_x**2) + y**2 / (2*sigma_y**2)))', ' kernel /= 2 * np.pi * sigma_x * sigma_y', ' kernel /= kernel.sum()', ' return kernel'] | ['', 'def center_crop(image, target_size):', ' image = np.array(image)', ' h, w = image.shape[:2]', '', ' left = (w - target_size[0]) // 2', ' top = (h - target_size[1]) // 2', '', ' right = left + target_size[0]', ' bottom = top + target_size[1]', '', ' cropped_image = image[top:bottom, 0:right]',... | [] | Library 'np' used at line 17 is imported at line 1 and has a Medium-Range dependency.
Variable 'sigma_y' used at line 17 is defined at line 10 and has a Short-Range dependency.
Variable 'size_y' used at line 17 is defined at line 14 and has a Short-Range dependency.
Library 'np' used at line 19 is imported at line 1 an... | {} | {'Library Medium-Range': 3, 'Variable Short-Range': 11} |
completion_python | Image_Filtering | 19 | 22 | ['import numpy as np', 'import cv2', 'import matplotlib.pyplot as plt', 'from scipy.signal import convolve2d', 'from scipy.signal import butter, filtfilt', '', '# Task1', '# Gaussian blurring einstein monroe illusion', 'def gaussian2D(sigma, kernel_size):', ' sigma_x, sigma_y = sigma', ' size_x, size_y = kernel_s... | [' kernel = np.exp(-(x**2 / (2*sigma_x**2) + y**2 / (2*sigma_y**2)))', ' kernel /= 2 * np.pi * sigma_x * sigma_y', ' kernel /= kernel.sum()', ' return kernel'] | ['', 'def center_crop(image, target_size):', ' image = np.array(image)', ' h, w = image.shape[:2]', '', ' left = (w - target_size[0]) // 2', ' top = (h - target_size[1]) // 2', '', ' right = left + target_size[0]', ' bottom = top + target_size[1]', '', ' cropped_image = image[top:bottom, 0:right]',... | [] | Library 'np' used at line 19 is imported at line 1 and has a Medium-Range dependency.
Variable 'x' used at line 19 is defined at line 16 and has a Short-Range dependency.
Variable 'sigma_x' used at line 19 is defined at line 10 and has a Short-Range dependency.
Variable 'y' used at line 19 is defined at line 16 and has... | {} | {'Library Medium-Range': 2, 'Variable Short-Range': 9} |
completion_python | Image_Filtering | 20 | 22 | ['import numpy as np', 'import cv2', 'import matplotlib.pyplot as plt', 'from scipy.signal import convolve2d', 'from scipy.signal import butter, filtfilt', '', '# Task1', '# Gaussian blurring einstein monroe illusion', 'def gaussian2D(sigma, kernel_size):', ' sigma_x, sigma_y = sigma', ' size_x, size_y = kernel_s... | [' kernel /= 2 * np.pi * sigma_x * sigma_y', ' kernel /= kernel.sum()', ' return kernel'] | ['', 'def center_crop(image, target_size):', ' image = np.array(image)', ' h, w = image.shape[:2]', '', ' left = (w - target_size[0]) // 2', ' top = (h - target_size[1]) // 2', '', ' right = left + target_size[0]', ' bottom = top + target_size[1]', '', ' cropped_image = image[top:bottom, 0:right]',... | [] | Variable 'kernel' used at line 20 is defined at line 19 and has a Short-Range dependency.
Library 'np' used at line 20 is imported at line 1 and has a Medium-Range dependency.
Variable 'sigma_x' used at line 20 is defined at line 10 and has a Short-Range dependency.
Variable 'sigma_y' used at line 20 is defined at line... | {} | {'Variable Short-Range': 5, 'Library Medium-Range': 1} |
completion_python | Image_Filtering | 21 | 22 | ['import numpy as np', 'import cv2', 'import matplotlib.pyplot as plt', 'from scipy.signal import convolve2d', 'from scipy.signal import butter, filtfilt', '', '# Task1', '# Gaussian blurring einstein monroe illusion', 'def gaussian2D(sigma, kernel_size):', ' sigma_x, sigma_y = sigma', ' size_x, size_y = kernel_s... | [' kernel /= kernel.sum()', ' return kernel'] | ['', 'def center_crop(image, target_size):', ' image = np.array(image)', ' h, w = image.shape[:2]', '', ' left = (w - target_size[0]) // 2', ' top = (h - target_size[1]) // 2', '', ' right = left + target_size[0]', ' bottom = top + target_size[1]', '', ' cropped_image = image[top:bottom, 0:right]',... | [] | Variable 'kernel' used at line 21 is defined at line 20 and has a Short-Range dependency.
Variable 'kernel' used at line 22 is defined at line 21 and has a Short-Range dependency. | {} | {'Variable Short-Range': 2} |
completion_python | Image_Filtering | 16 | 22 | ['import numpy as np', 'import cv2', 'import matplotlib.pyplot as plt', 'from scipy.signal import convolve2d', 'from scipy.signal import butter, filtfilt', '', '# Task1', '# Gaussian blurring einstein monroe illusion', 'def gaussian2D(sigma, kernel_size):', ' sigma_x, sigma_y = sigma', ' size_x, size_y = kernel_s... | [' x, y = np.meshgrid(np.linspace(-3*sigma_x, 3*sigma_x, size_x),', ' np.linspace(-3*sigma_y, 3*sigma_y, size_y))', ' ', ' kernel = np.exp(-(x**2 / (2*sigma_x**2) + y**2 / (2*sigma_y**2)))', ' kernel /= 2 * np.pi * sigma_x * sigma_y', ' kernel /= kernel.sum()', ' return kernel'] | ['', 'def center_crop(image, target_size):', ' image = np.array(image)', ' h, w = image.shape[:2]', '', ' left = (w - target_size[0]) // 2', ' top = (h - target_size[1]) // 2', '', ' right = left + target_size[0]', ' bottom = top + target_size[1]', '', ' cropped_image = image[top:bottom, 0:right]',... | [] | Library 'np' used at line 16 is imported at line 1 and has a Medium-Range dependency.
Variable 'sigma_x' used at line 16 is defined at line 10 and has a Short-Range dependency.
Variable 'size_x' used at line 16 is defined at line 13 and has a Short-Range dependency.
Library 'np' used at line 17 is imported at line 1 an... | {} | {'Library Medium-Range': 4, 'Variable Short-Range': 13} |
completion_python | Image_Filtering | 31 | 35 | ['import numpy as np', 'import cv2', 'import matplotlib.pyplot as plt', 'from scipy.signal import convolve2d', 'from scipy.signal import butter, filtfilt', '', '# Task1', '# Gaussian blurring einstein monroe illusion', 'def gaussian2D(sigma, kernel_size):', ' sigma_x, sigma_y = sigma', ' size_x, size_y = kernel_s... | [' right = left + target_size[0]', ' bottom = top + target_size[1]', '', ' cropped_image = image[top:bottom, 0:right]', ' return cropped_image'] | ['', "img_a = cv2.imread('./marilyn.jpeg')", "img_b = cv2.imread('./einstein.jpeg')", '', '# Part1', '# Reshape to ensure images are same size by center cropping to image with smallest dimension', '# Convert img to grayscale ', 'smallest_dim = min(img_a.shape[0],img_a.shape[1],img_b.shape[1],img_b.shape[1])', 'img_a_gr... | [] | Variable 'left' used at line 31 is defined at line 28 and has a Short-Range dependency.
Variable 'target_size' used at line 31 is defined at line 24 and has a Short-Range dependency.
Variable 'top' used at line 32 is defined at line 29 and has a Short-Range dependency.
Variable 'target_size' used at line 32 is defined ... | {} | {'Variable Short-Range': 9} |
completion_python | Image_Filtering | 25 | 35 | ['import numpy as np', 'import cv2', 'import matplotlib.pyplot as plt', 'from scipy.signal import convolve2d', 'from scipy.signal import butter, filtfilt', '', '# Task1', '# Gaussian blurring einstein monroe illusion', 'def gaussian2D(sigma, kernel_size):', ' sigma_x, sigma_y = sigma', ' size_x, size_y = kernel_s... | [' image = np.array(image)', ' h, w = image.shape[:2]', '', ' left = (w - target_size[0]) // 2', ' top = (h - target_size[1]) // 2', '', ' right = left + target_size[0]', ' bottom = top + target_size[1]', '', ' cropped_image = image[top:bottom, 0:right]', ' return cropped_image'] | ['', "img_a = cv2.imread('./marilyn.jpeg')", "img_b = cv2.imread('./einstein.jpeg')", '', '# Part1', '# Reshape to ensure images are same size by center cropping to image with smallest dimension', '# Convert img to grayscale ', 'smallest_dim = min(img_a.shape[0],img_a.shape[1],img_b.shape[1],img_b.shape[1])', 'img_a_gr... | [] | Library 'np' used at line 25 is imported at line 1 and has a Medium-Range dependency.
Variable 'image' used at line 25 is defined at line 24 and has a Short-Range dependency.
Variable 'image' used at line 26 is defined at line 25 and has a Short-Range dependency.
Variable 'w' used at line 28 is defined at line 26 and h... | {} | {'Library Medium-Range': 1, 'Variable Short-Range': 15} |
completion_python | Image_Filtering | 61 | 61 | ['import numpy as np', 'import cv2', 'import matplotlib.pyplot as plt', 'from scipy.signal import convolve2d', 'from scipy.signal import butter, filtfilt', '', '# Task1', '# Gaussian blurring einstein monroe illusion', 'def gaussian2D(sigma, kernel_size):', ' sigma_x, sigma_y = sigma', ' size_x, size_y = kernel_s... | ['blur_b = cv2.filter2D(img_b_gray, -1, gaussian_kernel_b)'] | ['', 'a_diff = img_a_gray - blur_a', 'img_c = blur_b + a_diff', 'print(img_c)', '', 'def downsample_image(image, factor):', ' if factor <= 0:', ' raise ValueError("Downsampling factor must be greater than 0.")', ' ', ' height, width = image.shape[:2]', ' new_height = height // factor', ' new_width... | [] | Library 'cv2' used at line 61 is imported at line 2 and has a Long-Range dependency.
Variable 'img_b_gray' used at line 61 is defined at line 45 and has a Medium-Range dependency.
Variable 'gaussian_kernel_b' used at line 61 is defined at line 58 and has a Short-Range dependency. | {} | {'Library Long-Range': 1, 'Variable Medium-Range': 1, 'Variable Short-Range': 1} |
completion_python | Image_Filtering | 76 | 76 | ['import numpy as np', 'import cv2', 'import matplotlib.pyplot as plt', 'from scipy.signal import convolve2d', 'from scipy.signal import butter, filtfilt', '', '# Task1', '# Gaussian blurring einstein monroe illusion', 'def gaussian2D(sigma, kernel_size):', ' sigma_x, sigma_y = sigma', ' size_x, size_y = kernel_s... | [' downsampled_image = np.zeros((new_height, new_width, image.shape[2]), dtype=np.uint8)'] | [' else:', ' downsampled_image = np.zeros((new_height, new_width), dtype=np.uint8)', '', ' for i in range(new_height):', ' for j in range(new_width):', ' downsampled_image[i, j] = image[i * factor, j * factor]', ' return downsampled_image', '', 'downsampling_factor = 4', 'downsampled_i... | [{'reason_category': 'If Body', 'usage_line': 76}] | Library 'np' used at line 76 is imported at line 1 and has a Long-Range dependency.
Variable 'new_height' used at line 76 is defined at line 72 and has a Short-Range dependency.
Variable 'new_width' used at line 76 is defined at line 73 and has a Short-Range dependency.
Variable 'image' used at line 76 is defined at li... | {'If Body': 1} | {'Library Long-Range': 1, 'Variable Short-Range': 3} |
completion_python | Image_Filtering | 78 | 78 | ['import numpy as np', 'import cv2', 'import matplotlib.pyplot as plt', 'from scipy.signal import convolve2d', 'from scipy.signal import butter, filtfilt', '', '# Task1', '# Gaussian blurring einstein monroe illusion', 'def gaussian2D(sigma, kernel_size):', ' sigma_x, sigma_y = sigma', ' size_x, size_y = kernel_s... | [' downsampled_image = np.zeros((new_height, new_width), dtype=np.uint8)'] | ['', ' for i in range(new_height):', ' for j in range(new_width):', ' downsampled_image[i, j] = image[i * factor, j * factor]', ' return downsampled_image', '', 'downsampling_factor = 4', 'downsampled_image = downsample_image(img_c, downsampling_factor)', 'print(np.array(downsampled_image))', ''... | [{'reason_category': 'Else Reasoning', 'usage_line': 78}] | Library 'np' used at line 78 is imported at line 1 and has a Long-Range dependency.
Variable 'new_height' used at line 78 is defined at line 72 and has a Short-Range dependency.
Variable 'new_width' used at line 78 is defined at line 73 and has a Short-Range dependency. | {'Else Reasoning': 1} | {'Library Long-Range': 1, 'Variable Short-Range': 2} |
completion_python | Image_Filtering | 82 | 82 | ['import numpy as np', 'import cv2', 'import matplotlib.pyplot as plt', 'from scipy.signal import convolve2d', 'from scipy.signal import butter, filtfilt', '', '# Task1', '# Gaussian blurring einstein monroe illusion', 'def gaussian2D(sigma, kernel_size):', ' sigma_x, sigma_y = sigma', ' size_x, size_y = kernel_s... | [' downsampled_image[i, j] = image[i * factor, j * factor]'] | [' return downsampled_image', '', 'downsampling_factor = 4', 'downsampled_image = downsample_image(img_c, downsampling_factor)', 'print(np.array(downsampled_image))', '', '# Part3', '# Computer fourier magnitude for the final image, original grayscale images, ', '# the blurred second image and difference between gra... | [{'reason_category': 'Loop Body', 'usage_line': 82}] | Variable 'downsampled_image' used at line 82 is defined at line 78 and has a Short-Range dependency.
Variable 'i' used at line 82 is part of a Loop defined at line 80 and has a Short-Range dependency.
Variable 'j' used at line 82 is part of a Loop defined at line 81 and has a Short-Range dependency.
Variable 'image' us... | {'Loop Body': 1} | {'Variable Short-Range': 1, 'Variable Loop Short-Range': 2, 'Variable Medium-Range': 2} |
completion_python | Image_Filtering | 80 | 83 | ['import numpy as np', 'import cv2', 'import matplotlib.pyplot as plt', 'from scipy.signal import convolve2d', 'from scipy.signal import butter, filtfilt', '', '# Task1', '# Gaussian blurring einstein monroe illusion', 'def gaussian2D(sigma, kernel_size):', ' sigma_x, sigma_y = sigma', ' size_x, size_y = kernel_s... | [' for i in range(new_height):', ' for j in range(new_width):', ' downsampled_image[i, j] = image[i * factor, j * factor]', ' return downsampled_image'] | ['', 'downsampling_factor = 4', 'downsampled_image = downsample_image(img_c, downsampling_factor)', 'print(np.array(downsampled_image))', '', '# Part3', '# Computer fourier magnitude for the final image, original grayscale images, ', '# the blurred second image and difference between grayscale first image and blurred f... | [{'reason_category': 'Define Stop Criteria', 'usage_line': 80}, {'reason_category': 'Define Stop Criteria', 'usage_line': 81}, {'reason_category': 'Loop Body', 'usage_line': 82}] | Variable 'new_height' used at line 80 is defined at line 72 and has a Short-Range dependency.
Variable 'new_width' used at line 81 is defined at line 73 and has a Short-Range dependency.
Variable 'downsampled_image' used at line 82 is defined at line 78 and has a Short-Range dependency.
Variable 'i' used at line 82 is ... | {'Define Stop Criteria': 2, 'Loop Body': 1} | {'Variable Short-Range': 4, 'Variable Loop Short-Range': 2, 'Variable Medium-Range': 2} |
completion_python | Image_Filtering | 94 | 96 | ['import numpy as np', 'import cv2', 'import matplotlib.pyplot as plt', 'from scipy.signal import convolve2d', 'from scipy.signal import butter, filtfilt', '', '# Task1', '# Gaussian blurring einstein monroe illusion', 'def gaussian2D(sigma, kernel_size):', ' sigma_x, sigma_y = sigma', ' size_x, size_y = kernel_s... | [' spectrum = np.abs(np.fft.fftshift(np.fft.fft2(image)))', ' log_spectrum = np.log(1 + spectrum)', ' return log_spectrum'] | ['', 'spectrum_A = compute_fourier_magnitude(img_a_gray)', 'spectrum_B = compute_fourier_magnitude(img_b_gray)', 'spectrum_blurred_B = compute_fourier_magnitude(blur_b)', 'spectrum_A_blur_A = compute_fourier_magnitude(a_diff)', 'spectrum_C = compute_fourier_magnitude(img_c)', 'print(spectrum_A)', 'print(spectrum_B)', '... | [] | Library 'np' used at line 94 is imported at line 1 and has a Long-Range dependency.
Variable 'image' used at line 94 is defined at line 93 and has a Short-Range dependency.
Library 'np' used at line 95 is imported at line 1 and has a Long-Range dependency.
Variable 'spectrum' used at line 95 is defined at line 94 and h... | {} | {'Library Long-Range': 2, 'Variable Short-Range': 3} |
completion_python | Image_Filtering | 95 | 96 | ['import numpy as np', 'import cv2', 'import matplotlib.pyplot as plt', 'from scipy.signal import convolve2d', 'from scipy.signal import butter, filtfilt', '', '# Task1', '# Gaussian blurring einstein monroe illusion', 'def gaussian2D(sigma, kernel_size):', ' sigma_x, sigma_y = sigma', ' size_x, size_y = kernel_s... | [' log_spectrum = np.log(1 + spectrum)', ' return log_spectrum'] | ['', 'spectrum_A = compute_fourier_magnitude(img_a_gray)', 'spectrum_B = compute_fourier_magnitude(img_b_gray)', 'spectrum_blurred_B = compute_fourier_magnitude(blur_b)', 'spectrum_A_blur_A = compute_fourier_magnitude(a_diff)', 'spectrum_C = compute_fourier_magnitude(img_c)', 'print(spectrum_A)', 'print(spectrum_B)', '... | [] | Library 'np' used at line 95 is imported at line 1 and has a Long-Range dependency.
Variable 'spectrum' used at line 95 is defined at line 94 and has a Short-Range dependency.
Variable 'log_spectrum' used at line 96 is defined at line 95 and has a Short-Range dependency. | {} | {'Library Long-Range': 1, 'Variable Short-Range': 2} |
completion_python | Image_Filtering | 119 | 120 | ['import numpy as np', 'import cv2', 'import matplotlib.pyplot as plt', 'from scipy.signal import convolve2d', 'from scipy.signal import butter, filtfilt', '', '# Task1', '# Gaussian blurring einstein monroe illusion', 'def gaussian2D(sigma, kernel_size):', ' sigma_x, sigma_y = sigma', ' size_x, size_y = kernel_s... | [' G = cv2.pyrDown(G)', ' gpA.append(G)'] | ['', '# Gaussian pyramid for B', 'G = B.copy()', 'gpB = [G]', 'for i in range(6):', ' G = cv2.pyrDown(G)', ' gpB.append(G)', '', '# Laplacian Pyramid for A and B', 'lpA = [gpA[5]]', 'for i in range(5,0,-1):', ' GE = cv2.pyrUp(gpA[i])', ' L = cv2.subtract(gpA[i-1],GE)', ' lpA.append(L)', '', 'lpB = [gpB[5... | [{'reason_category': 'Loop Body', 'usage_line': 119}, {'reason_category': 'Loop Body', 'usage_line': 120}] | Library 'cv2' used at line 119 is imported at line 2 and has a Long-Range dependency.
Variable 'G' used at line 119 is defined at line 116 and has a Short-Range dependency.
Variable 'gpA' used at line 120 is defined at line 117 and has a Short-Range dependency.
Variable 'G' used at line 120 is defined at line 119 and h... | {'Loop Body': 2} | {'Library Long-Range': 1, 'Variable Short-Range': 3} |
completion_python | Image_Filtering | 126 | 127 | ['import numpy as np', 'import cv2', 'import matplotlib.pyplot as plt', 'from scipy.signal import convolve2d', 'from scipy.signal import butter, filtfilt', '', '# Task1', '# Gaussian blurring einstein monroe illusion', 'def gaussian2D(sigma, kernel_size):', ' sigma_x, sigma_y = sigma', ' size_x, size_y = kernel_s... | [' G = cv2.pyrDown(G)', ' gpB.append(G)'] | ['', '# Laplacian Pyramid for A and B', 'lpA = [gpA[5]]', 'for i in range(5,0,-1):', ' GE = cv2.pyrUp(gpA[i])', ' L = cv2.subtract(gpA[i-1],GE)', ' lpA.append(L)', '', 'lpB = [gpB[5]]', 'for i in range(5,0,-1):', ' GE = cv2.pyrUp(gpB[i])', ' L = cv2.subtract(gpB[i-1],GE)', ' lpB.append(L)', '', '# Add... | [{'reason_category': 'Loop Body', 'usage_line': 126}, {'reason_category': 'Loop Body', 'usage_line': 127}] | Library 'cv2' used at line 126 is imported at line 2 and has a Long-Range dependency.
Variable 'G' used at line 126 is defined at line 123 and has a Short-Range dependency.
Variable 'gpB' used at line 127 is defined at line 124 and has a Short-Range dependency.
Variable 'G' used at line 127 is defined at line 126 and h... | {'Loop Body': 2} | {'Library Long-Range': 1, 'Variable Short-Range': 3} |
completion_python | Image_Filtering | 132 | 134 | ['import numpy as np', 'import cv2', 'import matplotlib.pyplot as plt', 'from scipy.signal import convolve2d', 'from scipy.signal import butter, filtfilt', '', '# Task1', '# Gaussian blurring einstein monroe illusion', 'def gaussian2D(sigma, kernel_size):', ' sigma_x, sigma_y = sigma', ' size_x, size_y = kernel_s... | [' GE = cv2.pyrUp(gpA[i])', ' L = cv2.subtract(gpA[i-1],GE)', ' lpA.append(L)'] | ['', 'lpB = [gpB[5]]', 'for i in range(5,0,-1):', ' GE = cv2.pyrUp(gpB[i])', ' L = cv2.subtract(gpB[i-1],GE)', ' lpB.append(L)', '', '# Add left and right halves of images in each level', 'LS = []', 'for la,lb in zip(lpA,lpB):', ' rows,cols,dpt = la.shape', ' ls = np.hstack((la[:,0:cols//2], lb[:,cols//2... | [{'reason_category': 'Loop Body', 'usage_line': 132}, {'reason_category': 'Loop Body', 'usage_line': 133}, {'reason_category': 'Loop Body', 'usage_line': 134}] | Library 'cv2' used at line 132 is imported at line 2 and has a Long-Range dependency.
Variable 'gpA' used at line 132 is defined at line 117 and has a Medium-Range dependency.
Variable 'i' used at line 132 is part of a Loop defined at line 131 and has a Short-Range dependency.
Library 'cv2' used at line 133 is imported... | {'Loop Body': 3} | {'Library Long-Range': 2, 'Variable Medium-Range': 2, 'Variable Loop Short-Range': 2, 'Variable Short-Range': 3} |
completion_python | Image_Filtering | 138 | 140 | ['import numpy as np', 'import cv2', 'import matplotlib.pyplot as plt', 'from scipy.signal import convolve2d', 'from scipy.signal import butter, filtfilt', '', '# Task1', '# Gaussian blurring einstein monroe illusion', 'def gaussian2D(sigma, kernel_size):', ' sigma_x, sigma_y = sigma', ' size_x, size_y = kernel_s... | [' GE = cv2.pyrUp(gpB[i])', ' L = cv2.subtract(gpB[i-1],GE)', ' lpB.append(L)'] | ['', '# Add left and right halves of images in each level', 'LS = []', 'for la,lb in zip(lpA,lpB):', ' rows,cols,dpt = la.shape', ' ls = np.hstack((la[:,0:cols//2], lb[:,cols//2:]))', ' LS.append(ls)', '', '# Reconstruct', 'ls_ = LS[0]', 'for i in range(1,6):', ' ls_ = cv2.pyrUp(ls_)', ' ls_ = cv2.add(ls... | [{'reason_category': 'Loop Body', 'usage_line': 138}, {'reason_category': 'Loop Body', 'usage_line': 139}, {'reason_category': 'Loop Body', 'usage_line': 140}] | Library 'cv2' used at line 138 is imported at line 2 and has a Long-Range dependency.
Variable 'gpB' used at line 138 is defined at line 124 and has a Medium-Range dependency.
Variable 'i' used at line 138 is part of a Loop defined at line 137 and has a Short-Range dependency.
Library 'cv2' used at line 139 is imported... | {'Loop Body': 3} | {'Library Long-Range': 2, 'Variable Medium-Range': 2, 'Variable Loop Short-Range': 2, 'Variable Short-Range': 3} |
completion_python | Image_Filtering | 145 | 147 | ['import numpy as np', 'import cv2', 'import matplotlib.pyplot as plt', 'from scipy.signal import convolve2d', 'from scipy.signal import butter, filtfilt', '', '# Task1', '# Gaussian blurring einstein monroe illusion', 'def gaussian2D(sigma, kernel_size):', ' sigma_x, sigma_y = sigma', ' size_x, size_y = kernel_s... | [' rows,cols,dpt = la.shape', ' ls = np.hstack((la[:,0:cols//2], lb[:,cols//2:]))', ' LS.append(ls)'] | ['', '# Reconstruct', 'ls_ = LS[0]', 'for i in range(1,6):', ' ls_ = cv2.pyrUp(ls_)', ' ls_ = cv2.add(ls_, LS[i])', '', '# Image with direct connecting each half', 'real = np.hstack((A[:,:cols//2],B[:,cols//2:]))', '', 'blended_rgb = cv2.cvtColor(ls_, cv2.COLOR_BGR2RGB)', 'original_rgb = cv2.cvtColor(real, cv2.CO... | [{'reason_category': 'Loop Body', 'usage_line': 145}, {'reason_category': 'Loop Body', 'usage_line': 146}, {'reason_category': 'Loop Body', 'usage_line': 147}] | Variable 'la' used at line 145 is part of a Loop defined at line 144 and has a Short-Range dependency.
Library 'np' used at line 146 is imported at line 1 and has a Long-Range dependency.
Variable 'la' used at line 146 is part of a Loop defined at line 144 and has a Short-Range dependency.
Variable 'cols' used at line ... | {'Loop Body': 3} | {'Variable Loop Short-Range': 3, 'Library Long-Range': 1, 'Variable Short-Range': 3} |
completion_python | Image_Filtering | 172 | 172 | ['import numpy as np', 'import cv2', 'import matplotlib.pyplot as plt', 'from scipy.signal import convolve2d', 'from scipy.signal import butter, filtfilt', '', '# Task1', '# Gaussian blurring einstein monroe illusion', 'def gaussian2D(sigma, kernel_size):', ' sigma_x, sigma_y = sigma', ' size_x, size_y = kernel_s... | [' mask[i, max(0, i - strip_width // 2):min(width, i + strip_width // 2), :] = 1.0'] | [' return mask', '', '# Now blend images using the diagonal mask', 'LS = []', 'mask = create_diagonal_mask(A.shape)', 'M = mask.copy()', 'gpmask = [M]', 'for i in range(5):', ' M = cv2.pyrDown(M)', ' gpmask.append(M)', 'gpmask.reverse()', 'for i in range(len(gpmask)):', ' rows, cols, dpt = lpA[i].shape', ' ... | [{'reason_category': 'Loop Body', 'usage_line': 172}] | Variable 'mask' used at line 172 is defined at line 169 and has a Short-Range dependency.
Variable 'i' used at line 172 is part of a Loop defined at line 171 and has a Short-Range dependency.
Variable 'strip_width' used at line 172 is defined at line 168 and has a Short-Range dependency.
Variable 'width' used at line 1... | {'Loop Body': 1} | {'Variable Short-Range': 3, 'Variable Loop Short-Range': 1} |
completion_python | Image_Filtering | 169 | 173 | ['import numpy as np', 'import cv2', 'import matplotlib.pyplot as plt', 'from scipy.signal import convolve2d', 'from scipy.signal import butter, filtfilt', '', '# Task1', '# Gaussian blurring einstein monroe illusion', 'def gaussian2D(sigma, kernel_size):', ' sigma_x, sigma_y = sigma', ' size_x, size_y = kernel_s... | [' mask = np.zeros(shape, dtype=np.float32)', ' height, width, _ = mask.shape', ' for i in range(min(height, width)):', ' mask[i, max(0, i - strip_width // 2):min(width, i + strip_width // 2), :] = 1.0', ' return mask'] | ['', '# Now blend images using the diagonal mask', 'LS = []', 'mask = create_diagonal_mask(A.shape)', 'M = mask.copy()', 'gpmask = [M]', 'for i in range(5):', ' M = cv2.pyrDown(M)', ' gpmask.append(M)', 'gpmask.reverse()', 'for i in range(len(gpmask)):', ' rows, cols, dpt = lpA[i].shape', ' ls = lpA[i] * gp... | [{'reason_category': 'Define Stop Criteria', 'usage_line': 171}, {'reason_category': 'Loop Body', 'usage_line': 172}] | Library 'np' used at line 169 is imported at line 1 and has a Long-Range dependency.
Variable 'shape' used at line 169 is defined at line 168 and has a Short-Range dependency.
Variable 'mask' used at line 170 is defined at line 169 and has a Short-Range dependency.
Variable 'height' used at line 171 is defined at line ... | {'Define Stop Criteria': 1, 'Loop Body': 1} | {'Library Long-Range': 1, 'Variable Short-Range': 8, 'Variable Loop Short-Range': 1} |
completion_python | Image_Filtering | 181 | 182 | ['import numpy as np', 'import cv2', 'import matplotlib.pyplot as plt', 'from scipy.signal import convolve2d', 'from scipy.signal import butter, filtfilt', '', '# Task1', '# Gaussian blurring einstein monroe illusion', 'def gaussian2D(sigma, kernel_size):', ' sigma_x, sigma_y = sigma', ' size_x, size_y = kernel_s... | [' M = cv2.pyrDown(M)', ' gpmask.append(M)'] | ['gpmask.reverse()', 'for i in range(len(gpmask)):', ' rows, cols, dpt = lpA[i].shape', ' ls = lpA[i] * gpmask[i] + lpB[i] * (1 - gpmask[i])', ' LS.append(ls)', '', '# Now reconstruct', 'ls_ = LS[0]', 'for i in range(1, 6):', ' ls_ = cv2.pyrUp(ls_)', ' ls_ = cv2.resize(ls_, (LS[i].shape[1], LS[i].shape[0... | [{'reason_category': 'Loop Body', 'usage_line': 181}, {'reason_category': 'Loop Body', 'usage_line': 182}] | Library 'cv2' used at line 181 is imported at line 2 and has a Long-Range dependency.
Variable 'M' used at line 181 is defined at line 178 and has a Short-Range dependency.
Variable 'gpmask' used at line 182 is defined at line 179 and has a Short-Range dependency.
Variable 'M' used at line 182 is defined at line 181 an... | {'Loop Body': 2} | {'Library Long-Range': 1, 'Variable Short-Range': 3} |
completion_python | Image_Filtering | 185 | 187 | ['import numpy as np', 'import cv2', 'import matplotlib.pyplot as plt', 'from scipy.signal import convolve2d', 'from scipy.signal import butter, filtfilt', '', '# Task1', '# Gaussian blurring einstein monroe illusion', 'def gaussian2D(sigma, kernel_size):', ' sigma_x, sigma_y = sigma', ' size_x, size_y = kernel_s... | [' rows, cols, dpt = lpA[i].shape', ' ls = lpA[i] * gpmask[i] + lpB[i] * (1 - gpmask[i])', ' LS.append(ls)'] | ['', '# Now reconstruct', 'ls_ = LS[0]', 'for i in range(1, 6):', ' ls_ = cv2.pyrUp(ls_)', ' ls_ = cv2.resize(ls_, (LS[i].shape[1], LS[i].shape[0])) ', ' ls_ = cv2.add(ls_, LS[i])', '', '# Image with direct connecting each diagonal half', 'real = np.hstack((A[:, :cols//2], B[:, cols//2:]))', 'ls_rgb = cv2.cvtC... | [{'reason_category': 'Loop Body', 'usage_line': 185}, {'reason_category': 'Loop Body', 'usage_line': 186}, {'reason_category': 'Loop Body', 'usage_line': 187}] | Variable 'lpA' used at line 185 is defined at line 130 and has a Long-Range dependency.
Variable 'i' used at line 185 is part of a Loop defined at line 184 and has a Short-Range dependency.
Variable 'lpA' used at line 186 is defined at line 130 and has a Long-Range dependency.
Variable 'i' used at line 186 is part of a... | {'Loop Body': 3} | {'Variable Long-Range': 3, 'Variable Loop Short-Range': 2, 'Variable Short-Range': 2, 'Variable Medium-Range': 1} |
completion_python | Image_Filtering | 192 | 194 | ['import numpy as np', 'import cv2', 'import matplotlib.pyplot as plt', 'from scipy.signal import convolve2d', 'from scipy.signal import butter, filtfilt', '', '# Task1', '# Gaussian blurring einstein monroe illusion', 'def gaussian2D(sigma, kernel_size):', ' sigma_x, sigma_y = sigma', ' size_x, size_y = kernel_s... | [' ls_ = cv2.pyrUp(ls_)', ' ls_ = cv2.resize(ls_, (LS[i].shape[1], LS[i].shape[0])) ', ' ls_ = cv2.add(ls_, LS[i])'] | ['', '# Image with direct connecting each diagonal half', 'real = np.hstack((A[:, :cols//2], B[:, cols//2:]))', 'ls_rgb = cv2.cvtColor(ls_.astype(np.uint8), cv2.COLOR_BGR2RGB)', 'real_rgb = cv2.cvtColor(real, cv2.COLOR_BGR2RGB)', '', 'print(ls_rgb)', 'print(real_rgb)', 'print(mask)', '', '', '# Task3', '# Part1', '# Re... | [{'reason_category': 'Loop Body', 'usage_line': 192}, {'reason_category': 'Loop Body', 'usage_line': 193}, {'reason_category': 'Loop Body', 'usage_line': 194}] | Library 'cv2' used at line 192 is imported at line 2 and has a Long-Range dependency.
Variable 'ls_' used at line 192 is defined at line 190 and has a Short-Range dependency.
Library 'cv2' used at line 193 is imported at line 2 and has a Long-Range dependency.
Variable 'ls_' used at line 193 is defined at line 192 and ... | {'Loop Body': 3} | {'Library Long-Range': 3, 'Variable Short-Range': 3, 'Variable Medium-Range': 2, 'Variable Loop Short-Range': 2} |
completion_python | Image_Filtering | 220 | 221 | ['import numpy as np', 'import cv2', 'import matplotlib.pyplot as plt', 'from scipy.signal import convolve2d', 'from scipy.signal import butter, filtfilt', '', '# Task1', '# Gaussian blurring einstein monroe illusion', 'def gaussian2D(sigma, kernel_size):', ' sigma_x, sigma_y = sigma', ' size_x, size_y = kernel_s... | [' frame = cv2.cvtColor(frame, cv2.COLOR_BGR2RGB)', ' frames.append(frame)'] | ['', ' cap.release()', ' # Converts to numpy array(T,H,W,C)', ' video = np.stack(frames, axis=0)', ' # (T,H,W,C)->(H,W,C,T)', ' video = np.transpose(video, (1,2,3,0))', ' return frames', '', 'def bandpass_filter(signal, low_cutoff, high_cutoff, fs, order):', ' nyquist = 0.5 * fs', ' low = low_cu... | [{'reason_category': 'Loop Body', 'usage_line': 220}, {'reason_category': 'Loop Body', 'usage_line': 221}] | Library 'cv2' used at line 220 is imported at line 2 and has a Long-Range dependency.
Variable 'frame' used at line 220 is defined at line 214 and has a Short-Range dependency.
Variable 'frames' used at line 221 is defined at line 212 and has a Short-Range dependency.
Variable 'frame' used at line 221 is defined at lin... | {'Loop Body': 2} | {'Library Long-Range': 1, 'Variable Short-Range': 3} |
completion_python | Image_Filtering | 231 | 236 | ['import numpy as np', 'import cv2', 'import matplotlib.pyplot as plt', 'from scipy.signal import convolve2d', 'from scipy.signal import butter, filtfilt', '', '# Task1', '# Gaussian blurring einstein monroe illusion', 'def gaussian2D(sigma, kernel_size):', ' sigma_x, sigma_y = sigma', ' size_x, size_y = kernel_s... | [' nyquist = 0.5 * fs', ' low = low_cutoff / nyquist', ' high = high_cutoff / nyquist', " b, a = butter(order, [low, high], btype='band')", ' filtered_signal = filtfilt(b, a, signal)', ' return filtered_signal'] | ['', "alice = './alice.avi'", 'video_frames = read_video_into_numpy(alice)', 'first_frame = video_frames[0]', '', '# Specify regions of interest', 'cheek_rect = [(220, 250), (320, 350)]', 'forehead_rect = [(220, 10), (500, 174)]', 'cheek_roi = first_frame[cheek_rect[0][1]:cheek_rect[1][1], cheek_rect[0][0]:cheek_rect[1... | [] | Variable 'fs' used at line 231 is defined at line 230 and has a Short-Range dependency.
Variable 'low_cutoff' used at line 232 is defined at line 230 and has a Short-Range dependency.
Variable 'nyquist' used at line 232 is defined at line 231 and has a Short-Range dependency.
Variable 'high_cutoff' used at line 233 is ... | {} | {'Variable Short-Range': 12, 'Library Long-Range': 2} |
completion_python | Image_Filtering | 235 | 236 | ['import numpy as np', 'import cv2', 'import matplotlib.pyplot as plt', 'from scipy.signal import convolve2d', 'from scipy.signal import butter, filtfilt', '', '# Task1', '# Gaussian blurring einstein monroe illusion', 'def gaussian2D(sigma, kernel_size):', ' sigma_x, sigma_y = sigma', ' size_x, size_y = kernel_s... | [' filtered_signal = filtfilt(b, a, signal)', ' return filtered_signal'] | ['', "alice = './alice.avi'", 'video_frames = read_video_into_numpy(alice)', 'first_frame = video_frames[0]', '', '# Specify regions of interest', 'cheek_rect = [(220, 250), (320, 350)]', 'forehead_rect = [(220, 10), (500, 174)]', 'cheek_roi = first_frame[cheek_rect[0][1]:cheek_rect[1][1], cheek_rect[0][0]:cheek_rect[1... | [] | Library 'filtfilt' used at line 235 is imported at line 5 and has a Long-Range dependency.
Variable 'b' used at line 235 is defined at line 234 and has a Short-Range dependency.
Variable 'a' used at line 235 is defined at line 234 and has a Short-Range dependency.
Variable 'signal' used at line 235 is defined at line 2... | {} | {'Library Long-Range': 1, 'Variable Short-Range': 4} |
completion_python | Image_Transformation | 29 | 36 | ['from PIL import Image', 'import cv2', 'import numpy as np', 'import matplotlib.pyplot as plt', '', '#Task 1:', '#resize two imgs', '#resize imgA with cv2.resize', '#resize imgB via center cropping', '#ensure both resized images are resized to same end_size', '#concatenate the resized imgs via every other row imgA and... | [' x_start = int((img_array.shape[0]-end_size)/2)', ' x_end = x_start + end_size', '', ' y_start = int((img_array.shape[1]-end_size)/2)', ' y_end = y_start + end_size', '', ' img_resized = img_array[x_start:x_end, y_start:y_end, :]', ' return img_resized'] | ['B_resized = center_crop(B_array, end_size)', 'print(B_resized.shape)', 'C = np.concatenate((A_resized[0:256,0:128,:],B_resized[0:256,128:256,:]),axis = 1)', '', 'D = B_resized[0:1,:,:]', 'for row in range(1,A_resized.shape[0]):', ' if row % 2 == 0:', ' D = np.concatenate((D,B_resized[row:row+1,:,:]), axis=0... | [] | Variable 'img_array' used at line 29 is defined at line 28 and has a Short-Range dependency.
Variable 'end_size' used at line 29 is defined at line 28 and has a Short-Range dependency.
Variable 'x_start' used at line 30 is defined at line 29 and has a Short-Range dependency.
Variable 'end_size' used at line 30 is defin... | {} | {'Variable Short-Range': 14} |
completion_python | Image_Transformation | 32 | 36 | ['from PIL import Image', 'import cv2', 'import numpy as np', 'import matplotlib.pyplot as plt', '', '#Task 1:', '#resize two imgs', '#resize imgA with cv2.resize', '#resize imgB via center cropping', '#ensure both resized images are resized to same end_size', '#concatenate the resized imgs via every other row imgA and... | [' y_start = int((img_array.shape[1]-end_size)/2)', ' y_end = y_start + end_size', '', ' img_resized = img_array[x_start:x_end, y_start:y_end, :]', ' return img_resized'] | ['B_resized = center_crop(B_array, end_size)', 'print(B_resized.shape)', 'C = np.concatenate((A_resized[0:256,0:128,:],B_resized[0:256,128:256,:]),axis = 1)', '', 'D = B_resized[0:1,:,:]', 'for row in range(1,A_resized.shape[0]):', ' if row % 2 == 0:', ' D = np.concatenate((D,B_resized[row:row+1,:,:]), axis=0... | [] | Variable 'img_array' used at line 32 is defined at line 28 and has a Short-Range dependency.
Variable 'end_size' used at line 32 is defined at line 28 and has a Short-Range dependency.
Variable 'y_start' used at line 33 is defined at line 32 and has a Short-Range dependency.
Variable 'end_size' used at line 33 is defin... | {} | {'Variable Short-Range': 10} |
completion_python | Image_Transformation | 35 | 36 | ['from PIL import Image', 'import cv2', 'import numpy as np', 'import matplotlib.pyplot as plt', '', '#Task 1:', '#resize two imgs', '#resize imgA with cv2.resize', '#resize imgB via center cropping', '#ensure both resized images are resized to same end_size', '#concatenate the resized imgs via every other row imgA and... | [' img_resized = img_array[x_start:x_end, y_start:y_end, :]', ' return img_resized'] | ['B_resized = center_crop(B_array, end_size)', 'print(B_resized.shape)', 'C = np.concatenate((A_resized[0:256,0:128,:],B_resized[0:256,128:256,:]),axis = 1)', '', 'D = B_resized[0:1,:,:]', 'for row in range(1,A_resized.shape[0]):', ' if row % 2 == 0:', ' D = np.concatenate((D,B_resized[row:row+1,:,:]), axis=0... | [] | Variable 'img_array' used at line 35 is defined at line 28 and has a Short-Range dependency.
Variable 'x_start' used at line 35 is defined at line 29 and has a Short-Range dependency.
Variable 'x_end' used at line 35 is defined at line 30 and has a Short-Range dependency.
Variable 'y_start' used at line 35 is defined a... | {} | {'Variable Short-Range': 6} |
completion_python | Image_Transformation | 44 | 44 | ['from PIL import Image', 'import cv2', 'import numpy as np', 'import matplotlib.pyplot as plt', '', '#Task 1:', '#resize two imgs', '#resize imgA with cv2.resize', '#resize imgB via center cropping', '#ensure both resized images are resized to same end_size', '#concatenate the resized imgs via every other row imgA and... | [' D = np.concatenate((D,B_resized[row:row+1,:,:]), axis=0)'] | [' else:', ' D = np.concatenate((D,A_resized[row:row+1,:,:]), axis =0)', 'print(D)', '', '#Task 2:', '#upload picture of multiple peppers each different colors', '#create a mask without the yellow peppers by using range provided', '#do this in rgb and hsv -> note different ranges depending on rgb or hsv', "pe... | [{'reason_category': 'If Body', 'usage_line': 44}, {'reason_category': 'Loop Body', 'usage_line': 44}] | Library 'np' used at line 44 is imported at line 3 and has a Long-Range dependency.
Variable 'B_resized' used at line 44 is defined at line 37 and has a Short-Range dependency.
Variable 'row' used at line 44 is part of a Loop defined at line 42 and has a Short-Range dependency. | {'If Body': 1, 'Loop Body': 1} | {'Library Long-Range': 1, 'Variable Short-Range': 1, 'Variable Loop Short-Range': 1} |
completion_python | Image_Transformation | 46 | 46 | ['from PIL import Image', 'import cv2', 'import numpy as np', 'import matplotlib.pyplot as plt', '', '#Task 1:', '#resize two imgs', '#resize imgA with cv2.resize', '#resize imgB via center cropping', '#ensure both resized images are resized to same end_size', '#concatenate the resized imgs via every other row imgA and... | [' D = np.concatenate((D,A_resized[row:row+1,:,:]), axis =0)'] | ['print(D)', '', '#Task 2:', '#upload picture of multiple peppers each different colors', '#create a mask without the yellow peppers by using range provided', '#do this in rgb and hsv -> note different ranges depending on rgb or hsv', "pepper_img = Image.open('./pepper.png')", 'pepper = np.array(pepper_img)', '', 'lowe... | [{'reason_category': 'Loop Body', 'usage_line': 46}, {'reason_category': 'Else Reasoning', 'usage_line': 46}] | Library 'np' used at line 46 is imported at line 3 and has a Long-Range dependency.
Variable 'A_resized' used at line 46 is defined at line 26 and has a Medium-Range dependency.
Variable 'row' used at line 46 is part of a Loop defined at line 42 and has a Short-Range dependency. | {'Loop Body': 1, 'Else Reasoning': 1} | {'Library Long-Range': 1, 'Variable Medium-Range': 1, 'Variable Loop Short-Range': 1} |
completion_python | Image_Transformation | 43 | 46 | ['from PIL import Image', 'import cv2', 'import numpy as np', 'import matplotlib.pyplot as plt', '', '#Task 1:', '#resize two imgs', '#resize imgA with cv2.resize', '#resize imgB via center cropping', '#ensure both resized images are resized to same end_size', '#concatenate the resized imgs via every other row imgA and... | [' if row % 2 == 0:', ' D = np.concatenate((D,B_resized[row:row+1,:,:]), axis=0)', ' else:', ' D = np.concatenate((D,A_resized[row:row+1,:,:]), axis =0)'] | ['print(D)', '', '#Task 2:', '#upload picture of multiple peppers each different colors', '#create a mask without the yellow peppers by using range provided', '#do this in rgb and hsv -> note different ranges depending on rgb or hsv', "pepper_img = Image.open('./pepper.png')", 'pepper = np.array(pepper_img)', '', 'lowe... | [{'reason_category': 'Loop Body', 'usage_line': 43}, {'reason_category': 'If Condition', 'usage_line': 43}, {'reason_category': 'If Body', 'usage_line': 44}, {'reason_category': 'Loop Body', 'usage_line': 44}, {'reason_category': 'Loop Body', 'usage_line': 45}, {'reason_category': 'Else Reasoning', 'usage_line': 45}, {... | Variable 'row' used at line 43 is part of a Loop defined at line 42 and has a Short-Range dependency.
Library 'np' used at line 44 is imported at line 3 and has a Long-Range dependency.
Variable 'B_resized' used at line 44 is defined at line 37 and has a Short-Range dependency.
Variable 'row' used at line 44 is part of... | {'Loop Body': 4, 'If Condition': 1, 'If Body': 1, 'Else Reasoning': 2} | {'Variable Loop Short-Range': 3, 'Library Long-Range': 2, 'Variable Short-Range': 1, 'Variable Medium-Range': 1} |
completion_python | Image_Transformation | 83 | 84 | ['from PIL import Image', 'import cv2', 'import numpy as np', 'import matplotlib.pyplot as plt', '', '#Task 1:', '#resize two imgs', '#resize imgA with cv2.resize', '#resize imgB via center cropping', '#ensure both resized images are resized to same end_size', '#concatenate the resized imgs via every other row imgA and... | [' translation_matrix = np.array([[1,0,dx],[0,1,dy],[0,0,1]])', ' return translation_matrix'] | ['', 'def rotation(angle,radians = True):', ' if radians == False:', ' angle = np.radians(angle)', ' costheta = np.cos(angle)', ' sintheta = np.sin(angle)', ' rotation_matrix = np.array([[costheta, sintheta,0],[-1*sintheta,costheta,0],[0,0,1]])', ' return rotation_matrix', '', 'def similarity_matr... | [] | Library 'np' used at line 83 is imported at line 3 and has a Long-Range dependency.
Variable 'dx' used at line 83 is defined at line 82 and has a Short-Range dependency.
Variable 'dy' used at line 83 is defined at line 82 and has a Short-Range dependency.
Variable 'translation_matrix' used at line 84 is defined at line... | {} | {'Library Long-Range': 1, 'Variable Short-Range': 3} |
completion_python | Image_Transformation | 88 | 88 | ['from PIL import Image', 'import cv2', 'import numpy as np', 'import matplotlib.pyplot as plt', '', '#Task 1:', '#resize two imgs', '#resize imgA with cv2.resize', '#resize imgB via center cropping', '#ensure both resized images are resized to same end_size', '#concatenate the resized imgs via every other row imgA and... | [' angle = np.radians(angle)'] | [' costheta = np.cos(angle)', ' sintheta = np.sin(angle)', ' rotation_matrix = np.array([[costheta, sintheta,0],[-1*sintheta,costheta,0],[0,0,1]])', ' return rotation_matrix', '', 'def similarity_matrix(angle, dx, dy, scale_factor,radians=True):', ' if radians == False:', ' angle = np.radians(angl... | [{'reason_category': 'If Body', 'usage_line': 88}] | Library 'np' used at line 88 is imported at line 3 and has a Long-Range dependency. | {'If Body': 1} | {'Library Long-Range': 1} |
completion_python | Image_Transformation | 87 | 92 | ['from PIL import Image', 'import cv2', 'import numpy as np', 'import matplotlib.pyplot as plt', '', '#Task 1:', '#resize two imgs', '#resize imgA with cv2.resize', '#resize imgB via center cropping', '#ensure both resized images are resized to same end_size', '#concatenate the resized imgs via every other row imgA and... | [' if radians == False:', ' angle = np.radians(angle)', ' costheta = np.cos(angle)', ' sintheta = np.sin(angle)', ' rotation_matrix = np.array([[costheta, sintheta,0],[-1*sintheta,costheta,0],[0,0,1]])', ' return rotation_matrix'] | ['', 'def similarity_matrix(angle, dx, dy, scale_factor,radians=True):', ' if radians == False:', ' angle = np.radians(angle)', ' costheta = np.cos(angle)', ' sintheta = np.sin(angle)', '', ' similarity_matrix = np.array([[scale_factor*costheta,scale_factor*sintheta,dx],', ' ... | [{'reason_category': 'If Condition', 'usage_line': 87}, {'reason_category': 'If Body', 'usage_line': 88}] | Variable 'radians' used at line 87 is defined at line 86 and has a Short-Range dependency.
Library 'np' used at line 88 is imported at line 3 and has a Long-Range dependency.
Library 'np' used at line 89 is imported at line 3 and has a Long-Range dependency.
Variable 'angle' used at line 89 is defined at line 88 and ha... | {'If Condition': 1, 'If Body': 1} | {'Variable Short-Range': 6, 'Library Long-Range': 4} |
completion_python | Image_Transformation | 96 | 96 | ['from PIL import Image', 'import cv2', 'import numpy as np', 'import matplotlib.pyplot as plt', '', '#Task 1:', '#resize two imgs', '#resize imgA with cv2.resize', '#resize imgB via center cropping', '#ensure both resized images are resized to same end_size', '#concatenate the resized imgs via every other row imgA and... | [' angle = np.radians(angle)'] | [' costheta = np.cos(angle)', ' sintheta = np.sin(angle)', '', ' similarity_matrix = np.array([[scale_factor*costheta,scale_factor*sintheta,dx],', ' [-1*scale_factor*sintheta, scale_factor*costheta, dy],', ' [0,0,1]])', ' return similarity_matrix... | [{'reason_category': 'If Body', 'usage_line': 96}] | Library 'np' used at line 96 is imported at line 3 and has a Long-Range dependency. | {'If Body': 1} | {'Library Long-Range': 1} |
completion_python | Image_Transformation | 95 | 103 | ['from PIL import Image', 'import cv2', 'import numpy as np', 'import matplotlib.pyplot as plt', '', '#Task 1:', '#resize two imgs', '#resize imgA with cv2.resize', '#resize imgB via center cropping', '#ensure both resized images are resized to same end_size', '#concatenate the resized imgs via every other row imgA and... | [' if radians == False:', ' angle = np.radians(angle)', ' costheta = np.cos(angle)', ' sintheta = np.sin(angle)', '', ' similarity_matrix = np.array([[scale_factor*costheta,scale_factor*sintheta,dx],', ' [-1*scale_factor*sintheta, scale_factor*costheta, dy],', ' ... | ['', 'def affine(angle, x, y, scale, ax, ay):', ' scaling = np.array([[scale, 0,0], [0, scale, 0], [0,0,1]])', ' shear = np.array([[1, ax, 0], [ay, 1,0], [0, 0,1]])', ' result = np.array([[0,0,0], [0,0,0], [0,0,0]])', ' result = np.dot(translation(x, y), rotation(angle))', ' result = np.dot(result, scali... | [{'reason_category': 'If Condition', 'usage_line': 95}, {'reason_category': 'If Body', 'usage_line': 96}] | Variable 'radians' used at line 95 is defined at line 94 and has a Short-Range dependency.
Library 'np' used at line 96 is imported at line 3 and has a Long-Range dependency.
Library 'np' used at line 97 is imported at line 3 and has a Long-Range dependency.
Variable 'angle' used at line 97 is defined at line 94 and ha... | {'If Condition': 1, 'If Body': 1} | {'Variable Short-Range': 12, 'Library Long-Range': 4} |
completion_python | Image_Transformation | 100 | 103 | ['from PIL import Image', 'import cv2', 'import numpy as np', 'import matplotlib.pyplot as plt', '', '#Task 1:', '#resize two imgs', '#resize imgA with cv2.resize', '#resize imgB via center cropping', '#ensure both resized images are resized to same end_size', '#concatenate the resized imgs via every other row imgA and... | [' similarity_matrix = np.array([[scale_factor*costheta,scale_factor*sintheta,dx],', ' [-1*scale_factor*sintheta, scale_factor*costheta, dy],', ' [0,0,1]])', ' return similarity_matrix'] | ['', 'def affine(angle, x, y, scale, ax, ay):', ' scaling = np.array([[scale, 0,0], [0, scale, 0], [0,0,1]])', ' shear = np.array([[1, ax, 0], [ay, 1,0], [0, 0,1]])', ' result = np.array([[0,0,0], [0,0,0], [0,0,0]])', ' result = np.dot(translation(x, y), rotation(angle))', ' result = np.dot(result, scali... | [] | Library 'np' used at line 100 is imported at line 3 and has a Long-Range dependency.
Variable 'scale_factor' used at line 100 is defined at line 94 and has a Short-Range dependency.
Variable 'costheta' used at line 100 is defined at line 97 and has a Short-Range dependency.
Variable 'sintheta' used at line 100 is defin... | {} | {'Library Long-Range': 1, 'Variable Short-Range': 9} |
completion_python | Image_Transformation | 106 | 112 | ['from PIL import Image', 'import cv2', 'import numpy as np', 'import matplotlib.pyplot as plt', '', '#Task 1:', '#resize two imgs', '#resize imgA with cv2.resize', '#resize imgB via center cropping', '#ensure both resized images are resized to same end_size', '#concatenate the resized imgs via every other row imgA and... | [' scaling = np.array([[scale, 0,0], [0, scale, 0], [0,0,1]])', ' shear = np.array([[1, ax, 0], [ay, 1,0], [0, 0,1]])', ' result = np.array([[0,0,0], [0,0,0], [0,0,0]])', ' result = np.dot(translation(x, y), rotation(angle))', ' result = np.dot(result, scaling)', ' result = np.dot(result, shear)', ' ... | ['', 'def bilinear_interpolation(image,x,y):', ' x1 = int(x)', ' x2 = x1 + 1', ' y1 = int(y)', ' y2 = y1 + 1', '', ' if x1 < 0 or y1 < 0 or x2 >= image.shape[1] or y2 >= image.shape[0]:', ' return 0', ' else:', ' f11 = image[y1][x1]', ' f12 = image[y1][x2]', ' f21 = image[y... | [] | Library 'np' used at line 106 is imported at line 3 and has a Long-Range dependency.
Variable 'scale' used at line 106 is defined at line 105 and has a Short-Range dependency.
Library 'np' used at line 107 is imported at line 3 and has a Long-Range dependency.
Variable 'ax' used at line 107 is defined at line 105 and h... | {} | {'Library Long-Range': 6, 'Variable Short-Range': 11, 'Function Medium-Range': 2} |
completion_python | Image_Transformation | 109 | 112 | ['from PIL import Image', 'import cv2', 'import numpy as np', 'import matplotlib.pyplot as plt', '', '#Task 1:', '#resize two imgs', '#resize imgA with cv2.resize', '#resize imgB via center cropping', '#ensure both resized images are resized to same end_size', '#concatenate the resized imgs via every other row imgA and... | [' result = np.dot(translation(x, y), rotation(angle))', ' result = np.dot(result, scaling)', ' result = np.dot(result, shear)', ' return result'] | ['', 'def bilinear_interpolation(image,x,y):', ' x1 = int(x)', ' x2 = x1 + 1', ' y1 = int(y)', ' y2 = y1 + 1', '', ' if x1 < 0 or y1 < 0 or x2 >= image.shape[1] or y2 >= image.shape[0]:', ' return 0', ' else:', ' f11 = image[y1][x1]', ' f12 = image[y1][x2]', ' f21 = image[y... | [] | Library 'np' used at line 109 is imported at line 3 and has a Long-Range dependency.
Function 'translation' used at line 109 is defined at line 82 and has a Medium-Range dependency.
Variable 'x' used at line 109 is defined at line 105 and has a Short-Range dependency.
Variable 'y' used at line 109 is defined at line 10... | {} | {'Library Long-Range': 3, 'Function Medium-Range': 2, 'Variable Short-Range': 8} |
completion_python | Image_Transformation | 110 | 112 | ['from PIL import Image', 'import cv2', 'import numpy as np', 'import matplotlib.pyplot as plt', '', '#Task 1:', '#resize two imgs', '#resize imgA with cv2.resize', '#resize imgB via center cropping', '#ensure both resized images are resized to same end_size', '#concatenate the resized imgs via every other row imgA and... | [' result = np.dot(result, scaling)', ' result = np.dot(result, shear)', ' return result'] | ['', 'def bilinear_interpolation(image,x,y):', ' x1 = int(x)', ' x2 = x1 + 1', ' y1 = int(y)', ' y2 = y1 + 1', '', ' if x1 < 0 or y1 < 0 or x2 >= image.shape[1] or y2 >= image.shape[0]:', ' return 0', ' else:', ' f11 = image[y1][x1]', ' f12 = image[y1][x2]', ' f21 = image[y... | [] | Library 'np' used at line 110 is imported at line 3 and has a Long-Range dependency.
Variable 'scaling' used at line 110 is defined at line 106 and has a Short-Range dependency.
Variable 'result' used at line 110 is defined at line 109 and has a Short-Range dependency.
Library 'np' used at line 111 is imported at line ... | {} | {'Library Long-Range': 2, 'Variable Short-Range': 5} |
completion_python | Image_Transformation | 121 | 121 | ['from PIL import Image', 'import cv2', 'import numpy as np', 'import matplotlib.pyplot as plt', '', '#Task 1:', '#resize two imgs', '#resize imgA with cv2.resize', '#resize imgB via center cropping', '#ensure both resized images are resized to same end_size', '#concatenate the resized imgs via every other row imgA and... | [' return 0'] | [' else:', ' f11 = image[y1][x1]', ' f12 = image[y1][x2]', ' f21 = image[y2][x1]', ' f22 = image[y2][x2]', '', ' w1 = (x2-x)*(y2-y)', ' w2 = (x-x1)*(y2-y)', ' w3 = (x2-x)*(y-y1)', ' w4 = (x-x1)*(y-y1)', '', ' return (w1*f11) + (w2*f12) + (w3*f21) + (w4*f22)'... | [{'reason_category': 'If Body', 'usage_line': 121}] | null | {'If Body': 1} | null |
completion_python | Image_Transformation | 123 | 131 | ['from PIL import Image', 'import cv2', 'import numpy as np', 'import matplotlib.pyplot as plt', '', '#Task 1:', '#resize two imgs', '#resize imgA with cv2.resize', '#resize imgB via center cropping', '#ensure both resized images are resized to same end_size', '#concatenate the resized imgs via every other row imgA and... | [' f11 = image[y1][x1]', ' f12 = image[y1][x2]', ' f21 = image[y2][x1]', ' f22 = image[y2][x2]', '', ' w1 = (x2-x)*(y2-y)', ' w2 = (x-x1)*(y2-y)', ' w3 = (x2-x)*(y-y1)', ' w4 = (x-x1)*(y-y1)'] | ['', ' return (w1*f11) + (w2*f12) + (w3*f21) + (w4*f22)', '', 'def image_warp(I,T):', ' rows,cols = I.shape[:2]', ' output = np.zeros((rows,cols,3))', ' center = (cols/2, rows/2)', ' T_invert = np.linalg.inv(T)', '', ' for i in range(rows):', ' for j in range(cols):', ' shift_center ... | [{'reason_category': 'Else Reasoning', 'usage_line': 123}, {'reason_category': 'Else Reasoning', 'usage_line': 124}, {'reason_category': 'Else Reasoning', 'usage_line': 125}, {'reason_category': 'Else Reasoning', 'usage_line': 126}, {'reason_category': 'Else Reasoning', 'usage_line': 127}, {'reason_category': 'Else Rea... | Variable 'image' used at line 123 is defined at line 114 and has a Short-Range dependency.
Variable 'y1' used at line 123 is defined at line 117 and has a Short-Range dependency.
Variable 'x1' used at line 123 is defined at line 115 and has a Short-Range dependency.
Variable 'image' used at line 124 is defined at line ... | {'Else Reasoning': 9} | {'Variable Short-Range': 11, 'Variable Medium-Range': 17} |
completion_python | Image_Transformation | 115 | 133 | ['from PIL import Image', 'import cv2', 'import numpy as np', 'import matplotlib.pyplot as plt', '', '#Task 1:', '#resize two imgs', '#resize imgA with cv2.resize', '#resize imgB via center cropping', '#ensure both resized images are resized to same end_size', '#concatenate the resized imgs via every other row imgA and... | [' x1 = int(x)', ' x2 = x1 + 1', ' y1 = int(y)', ' y2 = y1 + 1', '', ' if x1 < 0 or y1 < 0 or x2 >= image.shape[1] or y2 >= image.shape[0]:', ' return 0', ' else:', ' f11 = image[y1][x1]', ' f12 = image[y1][x2]', ' f21 = image[y2][x1]', ' f22 = image[y2][x2]', '', ' ... | ['', 'def image_warp(I,T):', ' rows,cols = I.shape[:2]', ' output = np.zeros((rows,cols,3))', ' center = (cols/2, rows/2)', ' T_invert = np.linalg.inv(T)', '', ' for i in range(rows):', ' for j in range(cols):', ' shift_center = np.array([j-center[0],i -center[1],1])', ' coor... | [{'reason_category': 'If Condition', 'usage_line': 120}, {'reason_category': 'If Body', 'usage_line': 121}, {'reason_category': 'Else Reasoning', 'usage_line': 122}, {'reason_category': 'Else Reasoning', 'usage_line': 123}, {'reason_category': 'Else Reasoning', 'usage_line': 124}, {'reason_category': 'Else Reasoning', ... | Variable 'x' used at line 115 is defined at line 114 and has a Short-Range dependency.
Variable 'x1' used at line 116 is defined at line 115 and has a Short-Range dependency.
Variable 'y' used at line 117 is defined at line 114 and has a Short-Range dependency.
Variable 'y1' used at line 118 is defined at line 117 and ... | {'If Condition': 1, 'If Body': 1, 'Else Reasoning': 10} | {'Variable Short-Range': 28, 'Variable Medium-Range': 17} |
completion_python | Image_Transformation | 120 | 133 | ['from PIL import Image', 'import cv2', 'import numpy as np', 'import matplotlib.pyplot as plt', '', '#Task 1:', '#resize two imgs', '#resize imgA with cv2.resize', '#resize imgB via center cropping', '#ensure both resized images are resized to same end_size', '#concatenate the resized imgs via every other row imgA and... | [' if x1 < 0 or y1 < 0 or x2 >= image.shape[1] or y2 >= image.shape[0]:', ' return 0', ' else:', ' f11 = image[y1][x1]', ' f12 = image[y1][x2]', ' f21 = image[y2][x1]', ' f22 = image[y2][x2]', '', ' w1 = (x2-x)*(y2-y)', ' w2 = (x-x1)*(y2-y)', ' w3 = (x2-x)*(... | ['', 'def image_warp(I,T):', ' rows,cols = I.shape[:2]', ' output = np.zeros((rows,cols,3))', ' center = (cols/2, rows/2)', ' T_invert = np.linalg.inv(T)', '', ' for i in range(rows):', ' for j in range(cols):', ' shift_center = np.array([j-center[0],i -center[1],1])', ' coor... | [{'reason_category': 'If Condition', 'usage_line': 120}, {'reason_category': 'If Body', 'usage_line': 121}, {'reason_category': 'Else Reasoning', 'usage_line': 122}, {'reason_category': 'Else Reasoning', 'usage_line': 123}, {'reason_category': 'Else Reasoning', 'usage_line': 124}, {'reason_category': 'Else Reasoning', ... | Variable 'x1' used at line 120 is defined at line 115 and has a Short-Range dependency.
Variable 'y1' used at line 120 is defined at line 117 and has a Short-Range dependency.
Variable 'x2' used at line 120 is defined at line 116 and has a Short-Range dependency.
Variable 'image' used at line 120 is defined at line 114... | {'If Condition': 1, 'If Body': 1, 'Else Reasoning': 10} | {'Variable Short-Range': 24, 'Variable Medium-Range': 17} |
completion_python | Image_Transformation | 143 | 146 | ['from PIL import Image', 'import cv2', 'import numpy as np', 'import matplotlib.pyplot as plt', '', '#Task 1:', '#resize two imgs', '#resize imgA with cv2.resize', '#resize imgB via center cropping', '#ensure both resized images are resized to same end_size', '#concatenate the resized imgs via every other row imgA and... | [' shift_center = np.array([j-center[0],i -center[1],1])', ' coordinates = np.dot(T_invert,shift_center)', ' x,y = coordinates[0] + center[0], coordinates [1] + center[1]', ' output[i][j] = bilinear_interpolation(I,x,y)'] | [' output = np.array(output, np.uint8)', ' return output', '', "path= './arabella.jpg'", 'arabella = cv2.imread(path)', 'arabella_smol = cv2.resize(arabella, dsize=(256, 192), interpolation=cv2.INTER_AREA)', 'arabella_smol = np.array(arabella_smol)', 'arabella_smol = arabella_smol[:, :, [2, 1, 0]]', '', '#transla... | [{'reason_category': 'Loop Body', 'usage_line': 143}, {'reason_category': 'Loop Body', 'usage_line': 144}, {'reason_category': 'Loop Body', 'usage_line': 145}, {'reason_category': 'Loop Body', 'usage_line': 146}] | Library 'np' used at line 143 is imported at line 3 and has a Long-Range dependency.
Variable 'j' used at line 143 is part of a Loop defined at line 142 and has a Short-Range dependency.
Variable 'center' used at line 143 is defined at line 138 and has a Short-Range dependency.
Variable 'i' used at line 143 is part of ... | {'Loop Body': 4} | {'Library Long-Range': 2, 'Variable Loop Short-Range': 4, 'Variable Short-Range': 8, 'Function Long-Range': 1, 'Variable Medium-Range': 1} |
completion_python | Image_Transformation | 141 | 148 | ['from PIL import Image', 'import cv2', 'import numpy as np', 'import matplotlib.pyplot as plt', '', '#Task 1:', '#resize two imgs', '#resize imgA with cv2.resize', '#resize imgB via center cropping', '#ensure both resized images are resized to same end_size', '#concatenate the resized imgs via every other row imgA and... | [' for i in range(rows):', ' for j in range(cols):', ' shift_center = np.array([j-center[0],i -center[1],1])', ' coordinates = np.dot(T_invert,shift_center)', ' x,y = coordinates[0] + center[0], coordinates [1] + center[1]', ' output[i][j] = bilinear_interpolation(I... | ['', "path= './arabella.jpg'", 'arabella = cv2.imread(path)', 'arabella_smol = cv2.resize(arabella, dsize=(256, 192), interpolation=cv2.INTER_AREA)', 'arabella_smol = np.array(arabella_smol)', 'arabella_smol = arabella_smol[:, :, [2, 1, 0]]', '', '#translate images keep params as shown', 't1 = translation(21,25)', 'war... | [{'reason_category': 'Define Stop Criteria', 'usage_line': 141}, {'reason_category': 'Loop Body', 'usage_line': 142}, {'reason_category': 'Define Stop Criteria', 'usage_line': 142}, {'reason_category': 'Loop Body', 'usage_line': 143}, {'reason_category': 'Loop Body', 'usage_line': 144}, {'reason_category': 'Loop Body',... | Variable 'rows' used at line 141 is defined at line 136 and has a Short-Range dependency.
Variable 'cols' used at line 142 is defined at line 136 and has a Short-Range dependency.
Library 'np' used at line 143 is imported at line 3 and has a Long-Range dependency.
Variable 'j' used at line 143 is part of a Loop defined... | {'Define Stop Criteria': 2, 'Loop Body': 5} | {'Variable Short-Range': 12, 'Library Long-Range': 3, 'Variable Loop Short-Range': 4, 'Function Long-Range': 1, 'Variable Medium-Range': 1} |
completion_python | Credit_Scoring_Fairness | 51 | 51 | ['import os', 'import pandas as pd', 'import numpy as np', 'import matplotlib.pyplot as plt', 'import matplotlib.cm as cm', 'from sklearn.model_selection import train_test_split', 'from sklearn.naive_bayes import GaussianNB', 'from sklearn.metrics import confusion_matrix', 'from sklearn.ensemble import RandomForestClas... | ['gnb_pred = gnb.fit(x_train, y_train).predict(x_test)'] | ['', '# Result', 'test_df = x_test.copy()', "test_df['biY'] = y_test", "test_df['pred'] = pd.Series(gnb_pred, index=test_df.index)", "test_df['accurate'] = (test_df['pred'] == test_df['biY'])", '', '', '# Confusion Matrix', "confusion_mat = confusion_matrix(test_df['biY'], test_df['pred'])", "print('confusion_matrix: '... | [] | Variable 'gnb' used at line 51 is defined at line 50 and has a Short-Range dependency.
Variable 'x_train' used at line 51 is defined at line 39 and has a Medium-Range dependency.
Variable 'y_train' used at line 51 is defined at line 39 and has a Medium-Range dependency.
Variable 'x_test' used at line 51 is defined at l... | {} | {'Variable Short-Range': 1, 'Variable Medium-Range': 3} |
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