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 ⌀ |
|---|---|---|---|---|---|---|---|---|---|---|
completion_python | RL_Motion_Planning | 260 | 260 | ['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', '... | [' ep_range = tf.range(ep_start, ep_end)'] | [' ', ' buffered_data = {}', ' _data = self.table.read(rows=ep_range)', ' for index, key in enumerate(self.buffer_keys):', ' buffered_data[key] = _data[index]', ' print("buffered_data: ", buffered_data)', ' return buffered_data', ' ', ' @tf.function', ' def ... | [{'reason_category': 'Else Reasoning', 'usage_line': 260}] | Library 'tf' used at line 260 is imported at line 20 and has a Long-Range dependency.
Variable 'ep_start' used at line 260 is defined at line 251 and has a Short-Range dependency.
Variable 'ep_end' used at line 260 is defined at line 251 and has a Short-Range dependency. | {'Else Reasoning': 1} | {'Library Long-Range': 1, 'Variable Short-Range': 2} |
completion_python | RL_Motion_Planning | 265 | 265 | ['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[key] = _data[index]'] | [' print("buffered_data: ", buffered_data)', ' return buffered_data', ' ', ' @tf.function', ' def store_episode(self, episode_batch):', ' """', ' Store each episode into replay buffer', ' episode_batch: {"": array(1 x (T or T+1) x dim)}', ' """', ' idxs ... | [{'reason_category': 'Loop Body', 'usage_line': 265}] | Variable 'buffered_data' used at line 265 is defined at line 262 and has a Short-Range dependency.
Variable 'key' used at line 265 is part of a Loop defined at line 264 and has a Short-Range dependency.
Variable '_data' used at line 265 is defined at line 263 and has a Short-Range dependency.
Variable 'index' used at l... | {'Loop Body': 1} | {'Variable Short-Range': 2, 'Variable Loop Short-Range': 2} |
completion_python | RL_Motion_Planning | 264 | 267 | ['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 index, key in enumerate(self.buffer_keys):', ' buffered_data[key] = _data[index]', ' print("buffered_data: ", buffered_data)', ' return buffered_data'] | [' ', ' @tf.function', ' def store_episode(self, episode_batch):', ' """', ' Store each episode into replay buffer', ' episode_batch: {"": array(1 x (T or T+1) x dim)}', ' """', ' idxs = self._get_storage_idxs(num_to_ins=tf.constant(1, dtype=tf.int32))', ' valu... | [{'reason_category': 'Define Stop Criteria', 'usage_line': 264}, {'reason_category': 'Loop Body', 'usage_line': 265}] | Variable 'self' used at line 264 is defined at line 251 and has a Medium-Range dependency.
Variable 'buffered_data' used at line 265 is defined at line 262 and has a Short-Range dependency.
Variable 'key' used at line 265 is part of a Loop defined at line 264 and has a Short-Range dependency.
Variable '_data' used at l... | {'Define Stop Criteria': 1, 'Loop Body': 1} | {'Variable Medium-Range': 1, 'Variable Short-Range': 4, 'Variable Loop Short-Range': 2} |
completion_python | RL_Motion_Planning | 284 | 284 | ['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', '... | [' episode_batch[key] = tf.gather(episodes_batch[key], ep_idx)'] | [' self.store_episode(episode_batch)', ' ', ' def _get_storage_idxs(self, num_to_ins=None):', ' if num_to_ins is None:', ' num_to_ins = tf.cast(1, dtype=tf.int32)', ' ', ' # consecutively insert until you hit the end of the buffer, and then insert randomly.', ' if... | [{'reason_category': 'Loop Body', 'usage_line': 284}] | Variable 'episode_batch' used at line 284 is defined at line 282 and has a Short-Range dependency.
Variable 'key' used at line 284 is part of a Loop defined at line 283 and has a Short-Range dependency.
Library 'tf' used at line 284 is imported at line 20 and has a Long-Range dependency.
Variable 'episodes_batch' used ... | {'Loop Body': 1} | {'Variable Short-Range': 2, 'Variable Loop Short-Range': 2, 'Library Long-Range': 1} |
completion_python | RL_Motion_Planning | 289 | 289 | ['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', '... | [' num_to_ins = tf.cast(1, dtype=tf.int32)'] | [' ', ' # consecutively insert until you hit the end of the buffer, and then insert randomly.', ' if self.current_size + num_to_ins <= self.buffer_size:', ' idxs = tf.range(self.current_size, self.current_size + num_to_ins)', ' elif self.current_size < self.buffer_size:', ' ... | [{'reason_category': 'If Body', 'usage_line': 289}] | Library 'tf' used at line 289 is imported at line 20 and has a Long-Range dependency. | {'If Body': 1} | {'Library Long-Range': 1} |
completion_python | RL_Motion_Planning | 293 | 293 | ['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', '... | [' idxs = tf.range(self.current_size, self.current_size + num_to_ins)'] | [' elif self.current_size < self.buffer_size:', ' overflow = num_to_ins - (self.buffer_size - self.current_size)', ' idx_a = tf.range(self.current_size, self.buffer_size)', ' idx_b = tf.experimental.numpy.random.randint(0, self.current_size, size=(overflow,), dtype=tf.int32)', ' ... | [{'reason_category': 'If Body', 'usage_line': 293}] | Library 'tf' used at line 293 is imported at line 20 and has a Long-Range dependency.
Variable 'self' used at line 293 is defined at line 287 and has a Short-Range dependency.
Variable 'num_to_ins' used at line 293 is defined at line 287 and has a Short-Range dependency. | {'If Body': 1} | {'Library Long-Range': 1, 'Variable Short-Range': 2} |
completion_python | RL_Motion_Planning | 295 | 298 | ['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', '... | [' overflow = num_to_ins - (self.buffer_size - self.current_size)', ' idx_a = tf.range(self.current_size, self.buffer_size)', ' idx_b = tf.experimental.numpy.random.randint(0, self.current_size, size=(overflow,), dtype=tf.int32)', ' idxs = tf.concat([idx_a, idx_b], axis=0)'] | [' else:', ' idxs = tf.experimental.numpy.random.randint(0, self.buffer_size, size=(num_to_ins,), dtype=tf.int32)', ' ', ' # update buffer size', ' self.current_size.assign(tf.math.minimum(self.buffer_size, self.current_size + num_to_ins))', ' print("idxs: ", idxs)', ' ... | [{'reason_category': 'Elif Body', 'usage_line': 295}, {'reason_category': 'Elif Body', 'usage_line': 296}, {'reason_category': 'Elif Body', 'usage_line': 297}, {'reason_category': 'Elif Body', 'usage_line': 298}] | Variable 'num_to_ins' used at line 295 is defined at line 287 and has a Short-Range dependency.
Variable 'self' used at line 295 is defined at line 287 and has a Short-Range dependency.
Library 'tf' used at line 296 is imported at line 20 and has a Long-Range dependency.
Variable 'self' used at line 296 is defined at l... | {'Elif Body': 4} | {'Variable Short-Range': 7, 'Library Long-Range': 3} |
completion_python | RL_Motion_Planning | 300 | 300 | ['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', '... | [' idxs = tf.experimental.numpy.random.randint(0, self.buffer_size, size=(num_to_ins,), dtype=tf.int32)'] | [' ', ' # update buffer size', ' self.current_size.assign(tf.math.minimum(self.buffer_size, self.current_size + num_to_ins))', ' print("idxs: ", idxs)', ' return idxs', ' ', ' def get_current_size_ep(self):', ' return self.current_size', ' ', ' def get_current_size_... | [{'reason_category': 'Else Reasoning', 'usage_line': 300}] | Library 'tf' used at line 300 is imported at line 20 and has a Long-Range dependency.
Variable 'self' used at line 300 is defined at line 287 and has a Medium-Range dependency.
Variable 'num_to_ins' used at line 300 is defined at line 287 and has a Medium-Range dependency. | {'Else Reasoning': 1} | {'Library Long-Range': 1, 'Variable Medium-Range': 2} |
completion_python | RL_Motion_Planning | 308 | 308 | ['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', '... | [' return self.current_size'] | [' ', ' def get_current_size_trans(self):', ' return self.current_size * self.T', ' ', ' def clear_buffer(self):', ' self.current_size.assign(0)', ' ', ' @property', ' def full(self):', ' return self.current_size == self.buffer_size', ' ', ' def __len__(self):', ' ... | [] | Variable 'self' used at line 308 is defined at line 307 and has a Short-Range dependency. | {} | {'Variable Short-Range': 1} |
completion_python | RL_Motion_Planning | 311 | 311 | ['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', '... | [' return self.current_size * self.T'] | [' ', ' def clear_buffer(self):', ' self.current_size.assign(0)', ' ', ' @property', ' def full(self):', ' return self.current_size == self.buffer_size', ' ', ' def __len__(self):', ' return self.current_size', ' ', ' def save_buffer_data(self, path):', ' buffered_... | [] | Variable 'self' used at line 311 is defined at line 310 and has a Short-Range dependency. | {} | {'Variable Short-Range': 1} |
completion_python | RL_Motion_Planning | 314 | 314 | ['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.current_size.assign(0)'] | [' ', ' @property', ' def full(self):', ' return self.current_size == self.buffer_size', ' ', ' def __len__(self):', ' return self.current_size', ' ', ' def save_buffer_data(self, path):', ' buffered_data = {}', ' _data = self.table.read(rows=tf.range(self.current_size))... | [] | Variable 'self' used at line 314 is defined at line 313 and has a Short-Range dependency. | {} | {'Variable Short-Range': 1} |
completion_python | RL_Motion_Planning | 318 | 318 | ['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', '... | [' return self.current_size == self.buffer_size'] | [' ', ' def __len__(self):', ' return self.current_size', ' ', ' def save_buffer_data(self, path):', ' buffered_data = {}', ' _data = self.table.read(rows=tf.range(self.current_size))', ' for index, key in enumerate(self.buffer_keys):', ' buffered_data[key] = _data[ind... | [] | Variable 'self' used at line 318 is defined at line 317 and has a Short-Range dependency. | {} | {'Variable Short-Range': 1} |
completion_python | RL_Motion_Planning | 321 | 321 | ['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', '... | [' return self.current_size'] | [' ', ' def save_buffer_data(self, path):', ' buffered_data = {}', ' _data = self.table.read(rows=tf.range(self.current_size))', ' for index, key in enumerate(self.buffer_keys):', ' buffered_data[key] = _data[index]', ' ', " with open(path, 'wb') as handle:", ' ... | [] | Variable 'self' used at line 321 is defined at line 320 and has a Short-Range dependency. | {} | {'Variable Short-Range': 1} |
completion_python | RL_Motion_Planning | 327 | 327 | ['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[key] = _data[index]'] | [' ', " with open(path, 'wb') as handle:", ' pickle.dump(buffered_data, handle, protocol=pickle.HIGHEST_PROTOCOL)', ' ', ' def load_data_into_buffer(self, buffered_data=None, clear_buffer=True, num_demos_to_load=None):', ' ', ' if buffered_data is None:', ' raise ... | [{'reason_category': 'Loop Body', 'usage_line': 327}] | Variable 'buffered_data' used at line 327 is defined at line 324 and has a Short-Range dependency.
Variable 'key' used at line 327 is part of a Loop defined at line 326 and has a Short-Range dependency.
Variable '_data' used at line 327 is defined at line 325 and has a Short-Range dependency.
Variable 'index' used at l... | {'Loop Body': 1} | {'Variable Short-Range': 2, 'Variable Loop Short-Range': 2} |
completion_python | RL_Motion_Planning | 338 | 338 | ['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.clear_buffer()'] | [' ', ' if num_demos_to_load is not None:', ' ', ' # Randomly sample idxs to load', " idxs = np.random.choice(len(buffered_data['actions']), size=num_demos_to_load, replace=False).tolist()", ' ', ' for key in buffered_data.keys():', ' b... | [{'reason_category': 'If Body', 'usage_line': 338}] | Variable 'self' used at line 338 is defined at line 332 and has a Short-Range dependency. | {'If Body': 1} | {'Variable Short-Range': 1} |
completion_python | RL_Motion_Planning | 343 | 346 | ['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', '... | [" idxs = np.random.choice(len(buffered_data['actions']), size=num_demos_to_load, replace=False).tolist()", ' ', ' for key in buffered_data.keys():', ' buffered_data[key] = tf.gather(buffered_data[key], idxs)'] | [' ', ' # Check if all tensors are present in loaded data', ' data_sizes = [len(buffered_data[key]) for key in self.buffer_keys]', ' assert np.all(np.array(data_sizes) == data_sizes[0])', ' ', ' idxs = self._get_storage_idxs(num_to_ins=data_sizes[0])', ' values = [buffer... | [{'reason_category': 'If Body', 'usage_line': 343}, {'reason_category': 'If Body', 'usage_line': 344}, {'reason_category': 'Define Stop Criteria', 'usage_line': 345}, {'reason_category': 'If Body', 'usage_line': 345}, {'reason_category': 'Loop Body', 'usage_line': 346}, {'reason_category': 'If Body', 'usage_line': 346}... | Library 'np' used at line 343 is imported at line 19 and has a Long-Range dependency.
Variable 'buffered_data' used at line 343 is defined at line 332 and has a Medium-Range dependency.
Variable 'num_demos_to_load' used at line 343 is defined at line 332 and has a Medium-Range dependency.
Variable 'buffered_data' used ... | {'If Body': 4, 'Define Stop Criteria': 1, 'Loop Body': 1} | {'Library Long-Range': 2, 'Variable Medium-Range': 4, 'Variable Loop Short-Range': 1, 'Variable Short-Range': 1} |
completion_python | RL_Motion_Planning | 346 | 346 | ['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[key] = tf.gather(buffered_data[key], idxs)'] | [' ', ' # Check if all tensors are present in loaded data', ' data_sizes = [len(buffered_data[key]) for key in self.buffer_keys]', ' assert np.all(np.array(data_sizes) == data_sizes[0])', ' ', ' idxs = self._get_storage_idxs(num_to_ins=data_sizes[0])', ' values = [buffer... | [{'reason_category': 'Loop Body', 'usage_line': 346}, {'reason_category': 'If Body', 'usage_line': 346}] | Variable 'buffered_data' used at line 346 is defined at line 332 and has a Medium-Range dependency.
Variable 'key' used at line 346 is part of a Loop defined at line 345 and has a Short-Range dependency.
Library 'tf' used at line 346 is imported at line 20 and has a Long-Range dependency.
Variable 'idxs' used at line 3... | {'Loop Body': 1, 'If Body': 1} | {'Variable Medium-Range': 1, 'Variable Loop Short-Range': 1, 'Library Long-Range': 1, 'Variable Short-Range': 1} |
completion_python | RL_Motion_Planning | 395 | 398 | ['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', '... | [' log_probs = -0.5 * tf.square((actions - mu) / std) - 0.5 * tf.math.log(2 * self.pi) - tf.math.log(std)', ' log_probs = tf.reduce_sum(log_probs, axis=1, keepdims=False)', ' print("log_probs: ", log_probs)', ' return log_probs'] | [' ', ' def call(self, states, training=None, mask=None):', ' """Computes actions for given inputs.', ' Args:', ' states: A batch of states.', ' training: Ignored', ' mask: Ignored.', ' Returns:', ' A mode action, a sampled action and log probability of the... | [] | Library 'tf' used at line 395 is imported at line 20 and has a Long-Range dependency.
Variable 'actions' used at line 395 is defined at line 392 and has a Short-Range dependency.
Variable 'mu' used at line 395 is defined at line 388 and has a Short-Range dependency.
Variable 'std' used at line 395 is defined at line 39... | {} | {'Library Long-Range': 2, 'Variable Short-Range': 5, 'Variable Medium-Range': 1} |
completion_python | RL_Motion_Planning | 415 | 415 | ['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', '... | [' actions = tf.random.normal(shape=mu.shape, mean=mu, stddev=self.FIXED_STD)'] | [' else:', ' actions = mu', ' ', ' # Compute log probs', ' log_probs = self.get_log_prob(states, actions)', ' log_probs = tf.expand_dims(log_probs, -1) # To avoid broadcasting', ' ', ' actions = tf.clip_by_value(actions, -1 + self.eps, 1 - self.eps)', ' ... | [{'reason_category': 'If Body', 'usage_line': 415}] | Library 'tf' used at line 415 is imported at line 20 and has a Long-Range dependency.
Variable 'mu' used at line 415 is defined at line 411 and has a Short-Range dependency.
Variable 'self' used at line 415 is defined at line 400 and has a Medium-Range dependency. | {'If Body': 1} | {'Library Long-Range': 1, 'Variable Short-Range': 1, 'Variable Medium-Range': 1} |
completion_python | RL_Motion_Planning | 417 | 417 | ['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', '... | [' actions = mu'] | [' ', ' # Compute log probs', ' log_probs = self.get_log_prob(states, actions)', ' log_probs = tf.expand_dims(log_probs, -1) # To avoid broadcasting', ' ', ' actions = tf.clip_by_value(actions, -1 + self.eps, 1 - self.eps)', ' print("mu: ", mu)', ' print("actions... | [{'reason_category': 'Else Reasoning', 'usage_line': 417}] | Variable 'mu' used at line 417 is defined at line 411 and has a Short-Range dependency. | {'Else Reasoning': 1} | {'Variable Short-Range': 1} |
completion_python | RL_Motion_Planning | 480 | 480 | ['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', '... | [' action = tf.random.uniform((1, self.args.a_dim), -self.args.action_max, self.args.action_max)'] | [' # Exploit', ' else:', ' action_mu, _, _ = self.actor(tf.concat([state, curr_goal], axis=1)) # a_t = mu(s_t, g_t)', ' action_dev = tf.random.normal(action_mu.shape, mean=0.0, stddev=stddev)', ' action = action_mu + action_dev # Add noise to action', ' action... | [{'reason_category': 'If Body', 'usage_line': 480}] | Library 'tf' used at line 480 is imported at line 20 and has a Long-Range dependency.
Variable 'self' used at line 480 is defined at line 466 and has a Medium-Range dependency. | {'If Body': 1} | {'Library Long-Range': 1, 'Variable Medium-Range': 1} |
completion_python | RL_Motion_Planning | 483 | 486 | ['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', '... | [' action_mu, _, _ = self.actor(tf.concat([state, curr_goal], axis=1)) # a_t = mu(s_t, g_t)', ' action_dev = tf.random.normal(action_mu.shape, mean=0.0, stddev=stddev)', ' action = action_mu + action_dev # Add noise to action', ' action = tf.clip_by_value(action, -self.args... | [' ', ' # Safety check for action, should not be nan or inf', ' has_nan = tf.math.reduce_any(tf.math.is_nan(action))', ' has_inf = tf.math.reduce_any(tf.math.is_inf(action))', ' if has_nan or has_inf:', " logger.warning('Action has nan or inf. Setting action to zero. Action... | [{'reason_category': 'Else Reasoning', 'usage_line': 483}, {'reason_category': 'Else Reasoning', 'usage_line': 484}, {'reason_category': 'Else Reasoning', 'usage_line': 485}, {'reason_category': 'Else Reasoning', 'usage_line': 486}] | Variable 'self' used at line 483 is defined at line 466 and has a Medium-Range dependency.
Library 'tf' used at line 483 is imported at line 20 and has a Long-Range dependency.
Variable 'state' used at line 483 is defined at line 467 and has a Medium-Range dependency.
Variable 'curr_goal' used at line 483 is defined at... | {'Else Reasoning': 4} | {'Variable Medium-Range': 5, 'Library Long-Range': 3, 'Variable Short-Range': 4} |
completion_python | RL_Motion_Planning | 501 | 502 | ['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', '... | [' skill = tf.zeros((1, self.args.c_dim))', ' return skill'] | [' ', ' @staticmethod', ' def get_init_goal(init_state, g_env):', ' return g_env', ' ', ' def build_model(self):', ' # a_t <- f(s_t) for each skill', ' _ = self.actor(tf.concat([np.ones([1, self.args.s_dim]), np.ones([1, self.args.g_dim])], 1))', ' ', ' def save_(self, dir_para... | [] | Library 'tf' used at line 501 is imported at line 20 and has a Long-Range dependency.
Variable 'self' used at line 501 is defined at line 497 and has a Short-Range dependency.
Variable 'skill' used at line 502 is defined at line 501 and has a Short-Range dependency. | {} | {'Library Long-Range': 1, 'Variable Short-Range': 2} |
completion_python | RL_Motion_Planning | 506 | 506 | ['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', '... | [' return g_env'] | [' ', ' def build_model(self):', ' # a_t <- f(s_t) for each skill', ' _ = self.actor(tf.concat([np.ones([1, self.args.s_dim]), np.ones([1, self.args.g_dim])], 1))', ' ', ' def save_(self, dir_param):', ' self.actor.save_weights(dir_param + "/policy.h5")', ' ', ' def load_(self, di... | [] | Variable 'g_env' used at line 506 is defined at line 505 and has a Short-Range dependency. | {} | {'Variable Short-Range': 1} |
completion_python | RL_Motion_Planning | 510 | 510 | ['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.actor(tf.concat([np.ones([1, self.args.s_dim]), np.ones([1, self.args.g_dim])], 1))'] | [' ', ' def save_(self, dir_param):', ' self.actor.save_weights(dir_param + "/policy.h5")', ' ', ' def load_(self, dir_param):', ' self.actor.load_weights(dir_param + "/policy.h5")', ' ', ' def change_training_mode(self, training_mode: bool):', ' pass', ' ', ' def update_tar... | [] | Variable 'self' used at line 510 is defined at line 508 and has a Short-Range dependency.
Library 'tf' used at line 510 is imported at line 20 and has a Long-Range dependency.
Library 'np' used at line 510 is imported at line 19 and has a Long-Range dependency. | {} | {'Variable Short-Range': 1, 'Library Long-Range': 2} |
completion_python | RL_Motion_Planning | 513 | 513 | ['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.actor.save_weights(dir_param + "/policy.h5")'] | [' ', ' def load_(self, dir_param):', ' self.actor.load_weights(dir_param + "/policy.h5")', ' ', ' def change_training_mode(self, training_mode: bool):', ' pass', ' ', ' def update_target_networks(self):', ' pass', '', '', 'class AgentBase(object):', ' def __init__(', ' ... | [] | Variable 'self' used at line 513 is defined at line 512 and has a Short-Range dependency.
Variable 'dir_param' used at line 513 is defined at line 512 and has a Short-Range dependency. | {} | {'Variable Short-Range': 2} |
completion_python | RL_Motion_Planning | 516 | 516 | ['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.actor.load_weights(dir_param + "/policy.h5")'] | [' ', ' def change_training_mode(self, training_mode: bool):', ' pass', ' ', ' def update_target_networks(self):', ' pass', '', '', 'class AgentBase(object):', ' def __init__(', ' self,', ' args,', ' model,', ' algo: str,', ' expert_buf... | [] | Variable 'self' used at line 516 is defined at line 515 and has a Short-Range dependency.
Variable 'dir_param' used at line 516 is defined at line 515 and has a Short-Range dependency. | {} | {'Variable Short-Range': 2} |
completion_python | RL_Motion_Planning | 547 | 547 | ['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', '... | [' os.makedirs(args.dir_summary)'] | [' ', ' if not os.path.exists(args.dir_plot):', ' os.makedirs(args.dir_plot)', ' self.summary_writer = tf.summary.create_file_writer(args.dir_summary)', ' ', ' # Define wandb logging', ' if self.args.log_wandb:', ' self.wandb_logger = wandb.init(', ' ... | [{'reason_category': 'If Body', 'usage_line': 547}] | Library 'os' used at line 547 is imported at line 8 and has a Long-Range dependency.
Variable 'args' used at line 547 is defined at line 526 and has a Medium-Range dependency. | {'If Body': 1} | {'Library Long-Range': 1, 'Variable Medium-Range': 1} |
completion_python | RL_Motion_Planning | 550 | 550 | ['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', '... | [' os.makedirs(args.dir_plot)'] | [' self.summary_writer = tf.summary.create_file_writer(args.dir_summary)', ' ', ' # Define wandb logging', ' if self.args.log_wandb:', ' self.wandb_logger = wandb.init(', ' project=args.wandb_project,', ' config=vars(args),', " id='{}_{... | [{'reason_category': 'If Body', 'usage_line': 550}] | Library 'os' used at line 550 is imported at line 8 and has a Long-Range dependency.
Variable 'args' used at line 550 is defined at line 526 and has a Medium-Range dependency. | {'If Body': 1} | {'Library Long-Range': 1, 'Variable Medium-Range': 1} |
completion_python | RL_Motion_Planning | 555 | 563 | ['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.wandb_logger = wandb.init(', ' project=args.wandb_project,', ' config=vars(args),', " id='{}_{}'.format(algo, current_time),", ' reinit=True, # Allow multiple wandb.init() calls in the same process.', ' )', ' # Clear t... | [' ', ' def preprocess_in_state_space(self, item):', ' item = tf.clip_by_value(item, -self.args.clip_obs, self.args.clip_obs)', ' return item', ' ', ' def save_model(self, dir_param):', ' if not os.path.exists(dir_param):', ' os.makedirs(dir_param)', ' self.model.save_... | [{'reason_category': 'If Body', 'usage_line': 555}, {'reason_category': 'If Body', 'usage_line': 556}, {'reason_category': 'If Body', 'usage_line': 557}, {'reason_category': 'If Body', 'usage_line': 558}, {'reason_category': 'If Body', 'usage_line': 559}, {'reason_category': 'If Body', 'usage_line': 560}, {'reason_cate... | Variable 'self' used at line 555 is defined at line 526 and has a Medium-Range dependency.
Library 'wandb' used at line 555 is imported at line 22 and has a Long-Range dependency.
Variable 'args' used at line 556 is defined at line 526 and has a Medium-Range dependency.
Variable 'args' used at line 557 is defined at li... | {'If Body': 9} | {'Variable Medium-Range': 2, 'Library Long-Range': 3, 'Variable Long-Range': 3} |
completion_python | RL_Motion_Planning | 566 | 567 | ['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', '... | [' item = tf.clip_by_value(item, -self.args.clip_obs, self.args.clip_obs)', ' return item'] | [' ', ' def save_model(self, dir_param):', ' if not os.path.exists(dir_param):', ' os.makedirs(dir_param)', ' self.model.save_(dir_param)', ' ', ' def load_model(self, dir_param):', ' self.model.load_(dir_param)', ' ', ' def process_data(self, transitions, expert=False,... | [] | Library 'tf' used at line 566 is imported at line 20 and has a Long-Range dependency.
Variable 'self' used at line 566 is defined at line 565 and has a Short-Range dependency.
Variable 'item' used at line 567 is defined at line 566 and has a Short-Range dependency. | {} | {'Library Long-Range': 1, 'Variable Short-Range': 2} |
completion_python | RL_Motion_Planning | 571 | 571 | ['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', '... | [' os.makedirs(dir_param)'] | [' 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', " ... | [{'reason_category': 'If Body', 'usage_line': 571}] | Library 'os' used at line 571 is imported at line 8 and has a Long-Range dependency.
Variable 'dir_param' used at line 571 is defined at line 569 and has a Short-Range dependency. | {'If Body': 1} | {'Library Long-Range': 1, 'Variable Short-Range': 1} |
completion_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} |
completion_python | RL_Motion_Planning | 590 | 590 | ['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['goals'] = trans['her_goals']"] | [' else:', " trans['goals'] = trans['env_goals']", ' ', ' # Define if the transitions are from expert or not/are supervised or not', " trans['is_demo'] = tf.cast(expert, dtype=tf.int32) * tf.ones_like(trans['successes'], dtype=tf.int32)", " trans['is_sup'] = tf.cast(is_supe... | [{'reason_category': 'If Body', 'usage_line': 590}] | Variable 'trans' used at line 590 is defined at line 587 and has a Short-Range dependency. | {'If Body': 1} | {'Variable Short-Range': 1} |
completion_python | RL_Motion_Planning | 592 | 592 | ['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['goals'] = trans['env_goals']"] | [' ', ' # Define if the transitions are from expert or not/are supervised or not', " trans['is_demo'] = tf.cast(expert, dtype=tf.int32) * tf.ones_like(trans['successes'], dtype=tf.int32)", " trans['is_sup'] = tf.cast(is_supervised, dtype=tf.int32) * tf.ones_like(trans['successes'], dtype=tf.... | [{'reason_category': 'Else Reasoning', 'usage_line': 592}] | Variable 'trans' used at line 592 is defined at line 587 and has a Short-Range dependency. | {'Else Reasoning': 1} | {'Variable Short-Range': 1} |
completion_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} |
completion_python | RL_Motion_Planning | 606 | 609 | ['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 trans.keys():', ' 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 = None', ' if all(isinstance(v, dict) for v in transit... | [{'reason_category': 'Define Stop Criteria', 'usage_line': 606}, {'reason_category': 'Loop Body', 'usage_line': 607}] | Variable 'trans' used at line 606 is defined at line 603 and has a Short-Range dependency.
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 i... | {'Define Stop Criteria': 1, 'Loop Body': 1} | {'Variable Short-Range': 4, 'Variable Loop Short-Range': 1, 'Library Long-Range': 1} |
completion_python | RL_Motion_Planning | 623 | 627 | ['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] = self.process_data(', ' 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")', ' ', ' # Concatenate the transitions from different skills', ' combined_transitions = {key: [] for key in key... | [{'reason_category': 'If Body', 'usage_line': 623}, {'reason_category': 'Loop Body', 'usage_line': 623}, {'reason_category': 'If Body', 'usage_line': 624}, {'reason_category': 'Loop Body', 'usage_line': 624}, {'reason_category': 'If Body', 'usage_line': 625}, {'reason_category': 'Loop Body', 'usage_line': 625}, {'reaso... | Variable 'skill' used at line 623 is part of a Loop defined at line 619 and has a Short-Range dependency.
Variable 'self' used at line 623 is defined at line 611 and has a Medium-Range dependency.
Variable 'skill' used at line 624 is part of a Loop defined at line 619 and has a Short-Range dependency.
Library 'tf' used... | {'If Body': 5, 'Loop Body': 5} | {'Variable Loop Short-Range': 3, 'Variable Medium-Range': 1, 'Library Long-Range': 1} |
completion_python | RL_Motion_Planning | 638 | 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', '... | [' if transitions[skill] is not None:', ' 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': 638}, {'reason_category': 'Loop Body', 'usage_line': 638}, {'reason_category': 'If Condition', 'usage_line': 638}, {'reason_category': 'If Body', 'usage_line': 639}, {'reason_category': 'Loop Body', 'usage_line': 639}, {'reason_category': 'Define Stop Criteria', 'usage_line... | Variable 'skill' used at line 638 is part of a Loop defined at line 636 and has a Short-Range dependency.
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' us... | {'If Body': 3, 'Loop Body': 3, 'If Condition': 1, 'Define Stop Criteria': 1} | {'Variable Loop Short-Range': 3, 'Variable Medium-Range': 1, 'Variable Short-Range': 1} |
completion_python | RL_Motion_Planning | 648 | 650 | ['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 = self.process_data(', ' 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)', ' ', ' da... | [{'reason_category': 'Elif Body', 'usage_line': 648}, {'reason_category': 'Elif Body', 'usage_line': 649}, {'reason_category': 'Elif Body', 'usage_line': 650}] | Variable 'self' used at line 648 is defined at line 611 and has a Long-Range dependency.
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': 3} | {'Variable Long-Range': 1, 'Variable Short-Range': 1, 'Library Long-Range': 1} |
completion_python | RL_Motion_Planning | 669 | 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', '... | [' 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', ' ... | [{'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_line': 671}] | 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_dict' used at line 670 is defined at line 667 and has a Short-Range dependency.
Variable 'key' use... | {'If Condition': 1, 'Loop Body': 3, 'If Body': 1} | {'Variable Loop Short-Range': 3, 'Variable Short-Range': 4} |
completion_python | RL_Motion_Planning | 670 | 670 | ['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] = []'] | [' 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 ... | [{'reason_category': 'Loop Body', 'usage_line': 670}, {'reason_category': 'If Body', 'usage_line': 670}] | Variable 'avg_loss_dict' used at line 670 is defined at line 667 and has a Short-Range dependency.
Variable 'key' used at line 670 is part of a Loop defined at line 668 and has a Short-Range dependency. | {'Loop Body': 1, 'If Body': 1} | {'Variable Short-Range': 1, 'Variable Loop Short-Range': 1} |
completion_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} |
completion_python | RL_Motion_Planning | 672 | 675 | ['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 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,', ' expert_buffer: ReplayBufferTf = None,', ' offline_buffer: Repl... | [{'reason_category': 'Define Stop Criteria', 'usage_line': 672}, {'reason_category': 'Loop Body', 'usage_line': 673}] | Variable 'avg_loss_dict' used at line 672 is defined at line 667 and has a Short-Range dependency.
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 ... | {'Define Stop Criteria': 1, 'Loop Body': 1} | {'Variable Short-Range': 4, 'Variable Loop Short-Range': 1, 'Library Long-Range': 1} |
completion_python | RL_Motion_Planning | 717 | 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[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': 717}] | 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 is part of a Loop defined at line 716 and has a Short-Range dependency. | {'Loop Body': 1} | {'Variable Short-Range': 1, 'Variable Loop Short-Range': 1} |
completion_python | RL_Motion_Planning | 751 | 751 | ['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.ag_dim = args.g_dim # Achieved Goal in the same space as Env Goal'] | [' else:', ' args.ag_dim = 3 # Goal/Object position in the 3D space', ' print("args: ", args)', ' return args', '', '', 'def get_config(db=False):', ' # Construct the absolute path of the data directory', " data_dir = os.path.join(script_dir, 'pnp_data')", '', ' parser = argparse.ArgumentParse... | [{'reason_category': 'If Body', 'usage_line': 751}] | Variable 'args' used at line 751 is defined at line 735 and has a Medium-Range dependency. | {'If Body': 1} | {'Variable Medium-Range': 1} |
completion_python | RL_Motion_Planning | 753 | 753 | ['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.ag_dim = 3 # Goal/Object position in the 3D space'] | [' print("args: ", args)', ' return args', '', '', 'def get_config(db=False):', ' # Construct the absolute path of the data directory', " data_dir = os.path.join(script_dir, 'pnp_data')", '', ' parser = argparse.ArgumentParser()', ' ', " parser.add_argument('--log_wandb', type=bool, default=False)"... | [{'reason_category': 'Else Reasoning', 'usage_line': 753}] | Variable 'args' used at line 753 is defined at line 735 and has a Medium-Range dependency. | {'Else Reasoning': 1} | {'Variable Medium-Range': 1} |
completion_python | RL_Motion_Planning | 868 | 868 | ['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.c_dim = args.num_skills'] | [' ', ' # Set number of skills [For full or semi-supervised skill learning]', " if args.env_name == 'OpenAIPickandPlace' and args.wrap_level != '0' and args.skill_supervision != 'none':", " print('Overriding c_dim based on Wrap Level %s' % args.wrap_level)", " if args.wrap_level == '1':", ' ... | [{'reason_category': 'If Body', 'usage_line': 868}] | Variable 'args' used at line 868 is defined at line 859 and has a Short-Range dependency. | {'If Body': 1} | {'Variable Short-Range': 1} |
completion_python | RL_Motion_Planning | 874 | 874 | ['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.c_dim = 3'] | [" elif args.wrap_level == '2':", ' args.c_dim = args.num_objs', ' else:', " raise NotImplementedError('Wrap level %s not implemented' % args.wrap_level)", ' ', ' return args', '', '', 'def run(db: bool, algo: str):', ' ', ' if db:', ' print("Running in Debug Mode.... | [{'reason_category': 'If Body', 'usage_line': 874}] | Variable 'args' used at line 874 is defined at line 859 and has a Medium-Range dependency. | {'If Body': 1} | {'Variable Medium-Range': 1} |
completion_python | Timeseries_Clustering | 23 | 23 | ['import pandas as pd', 'import numpy as np', 'import scipy.stats as stats', 'from sklearn.decomposition import PCA', 'from sklearn import metrics', 'from sklearn.cluster import DBSCAN', 'from sklearn.manifold import TSNE', 'from sklearn import preprocessing', 'from sklearn.cluster import KMeans', 'from sklearn.cluster... | ['beta=pca.fit_transform(norm_ret_df.T)'] | ['df_beta=pd.DataFrame(beta)', 'stock_pca = df_beta.values', 'print(stock_pca.shape)', '', '#standardise principal component array with prepcoessing.StandardScaler() and apply this with fit_transform to the pca_stock array ', 'X = preprocessing.StandardScaler().fit_transform(stock_pca)', '', '######### DBSCAN #########... | [] | Variable 'pca' used at line 23 is defined at line 22 and has a Short-Range dependency.
Variable 'norm_ret_df' used at line 23 is defined at line 20 and has a Short-Range dependency. | {} | {'Variable Short-Range': 2} |
completion_python | Timeseries_Clustering | 34 | 34 | ['import pandas as pd', 'import numpy as np', 'import scipy.stats as stats', 'from sklearn.decomposition import PCA', 'from sklearn import metrics', 'from sklearn.cluster import DBSCAN', 'from sklearn.manifold import TSNE', 'from sklearn import preprocessing', 'from sklearn.cluster import KMeans', 'from sklearn.cluster... | ['dbscan.fit_predict(X)'] | ['labels = dbscan.labels_', 'n_clusters_ = len(set(labels)) - (1 if -1 in labels else 0)', 'print(labels)', '', '#attach cluster labels to the last column norm_ret_df', "df_beta['labels']=labels", 'df_beta[\'labels\'] = df_beta[\'labels\'].astype("category")', 'df_beta=df_beta.set_index(norm_ret_df.T.index)', "df_beta.... | [] | Variable 'dbscan' used at line 34 is defined at line 33 and has a Short-Range dependency.
Variable 'X' used at line 34 is defined at line 29 and has a Short-Range dependency. | {} | {'Variable Short-Range': 2} |
completion_python | Timeseries_Clustering | 51 | 52 | ['import pandas as pd', 'import numpy as np', 'import scipy.stats as stats', 'from sklearn.decomposition import PCA', 'from sklearn import metrics', 'from sklearn.cluster import DBSCAN', 'from sklearn.manifold import TSNE', 'from sklearn import preprocessing', 'from sklearn.cluster import KMeans', 'from sklearn.cluster... | [' d[k] = pd.DataFrame()', " d[k] = df_beta[df_beta['labels'] ==k]"] | ['', 'print(d[0])', 'print(d[1])', 'print(d[2])', 'print(d[3])', 'print(d[4])', '', '#######KMEANS#######', '#run kmeans on pre processed data (X) set clusters to 5, n_init = 10, and random_state=42 so alog is iniitialised the same every time', 'kmeans = KMeans(n_clusters=5, n_init=10, random_state=42)', 'kmeans.fit(X)... | [{'reason_category': 'Loop Body', 'usage_line': 51}, {'reason_category': 'Loop Body', 'usage_line': 52}] | Variable 'd' used at line 51 is defined at line 49 and has a Short-Range dependency.
Variable 'k' used at line 51 is part of a Loop defined at line 50 and has a Short-Range dependency.
Library 'pd' used at line 51 is imported at line 1 and has a Long-Range dependency.
Variable 'd' used at line 52 is defined at line 49 ... | {'Loop Body': 2} | {'Variable Short-Range': 3, 'Variable Loop Short-Range': 2, 'Library Long-Range': 1} |
completion_python | Timeseries_Clustering | 63 | 63 | ['import pandas as pd', 'import numpy as np', 'import scipy.stats as stats', 'from sklearn.decomposition import PCA', 'from sklearn import metrics', 'from sklearn.cluster import DBSCAN', 'from sklearn.manifold import TSNE', 'from sklearn import preprocessing', 'from sklearn.cluster import KMeans', 'from sklearn.cluster... | ['kmeans.fit(X)'] | ['label_kmeans=kmeans.predict(X) ', 'center_kmeans=kmeans.cluster_centers_', 'print(label_kmeans)', 'print(center_kmeans)', '', '####Hierarchical Clustering#####', '# run agglomerative hierarchical clustering on preprocessed data X', 'clusters = 5', "hc = AgglomerativeClustering(n_clusters= clusters, affinity='euclidea... | [] | Variable 'kmeans' used at line 63 is defined at line 62 and has a Short-Range dependency.
Variable 'X' used at line 63 is defined at line 29 and has a Long-Range dependency. | {} | {'Variable Short-Range': 1, 'Variable Long-Range': 1} |
completion_python | Timeseries_Clustering | 73 | 73 | ['import pandas as pd', 'import numpy as np', 'import scipy.stats as stats', 'from sklearn.decomposition import PCA', 'from sklearn import metrics', 'from sklearn.cluster import DBSCAN', 'from sklearn.manifold import TSNE', 'from sklearn import preprocessing', 'from sklearn.cluster import KMeans', 'from sklearn.cluster... | ['labels_hc = hc.fit_predict(X)'] | ['print(labels_hc)', '', '###optimal pairs via statistical analysis with DBSCAN clusters', '', '#fetch normalised log returns for assets belonging to DBSCAN cluster 1 (label = 1)', 'cluster1_asset_list = d[1].index.values', 'clusters_norm_ret_df = norm_ret_df[cluster1_asset_list]', 'print(clusters_norm_ret_df)', '', '#... | [] | Variable 'hc' used at line 73 is defined at line 72 and has a Short-Range dependency.
Variable 'X' used at line 73 is defined at line 29 and has a Long-Range dependency. | {} | {'Variable Short-Range': 1, 'Variable Long-Range': 1} |
completion_python | Timeseries_Clustering | 93 | 97 | ['import pandas as pd', 'import numpy as np', 'import scipy.stats as stats', 'from sklearn.decomposition import PCA', 'from sklearn import metrics', 'from sklearn.cluster import DBSCAN', 'from sklearn.manifold import TSNE', 'from sklearn import preprocessing', 'from sklearn.cluster import KMeans', 'from sklearn.cluster... | [' asset1_list.append(pairs[i][0])', ' asset2_list.append(pairs[i][1])', '', ' dist = LA.norm(cumulative_norm_ret[asset1_list[i]]-cumulative_norm_ret[asset2_list[i]])', ' euclidean_distance_list.append(dist)'] | ['', '# asset1_list,asset2_list', '', 'sdd_list=list(zip(pairs,euclidean_distance_list))', 'sdd_list.sort(key = lambda x: x[1])', '', '#sort every pairwise combination based off of the euclidean squared distances. A unique optimal pair will occur with the minimum.', '# example: if pair A and B have a distance of 2 and ... | [{'reason_category': 'Loop Body', 'usage_line': 93}, {'reason_category': 'Loop Body', 'usage_line': 94}, {'reason_category': 'Loop Body', 'usage_line': 95}, {'reason_category': 'Loop Body', 'usage_line': 96}, {'reason_category': 'Loop Body', 'usage_line': 97}] | Variable 'asset1_list' used at line 93 is defined at line 89 and has a Short-Range dependency.
Variable 'pairs' used at line 93 is defined at line 88 and has a Short-Range dependency.
Variable 'i' used at line 93 is part of a Loop defined at line 92 and has a Short-Range dependency.
Variable 'asset2_list' used at line ... | {'Loop Body': 5} | {'Variable Short-Range': 8, 'Variable Loop Short-Range': 3, 'Library Long-Range': 1, 'Variable Medium-Range': 1} |
completion_python | Timeseries_Clustering | 111 | 112 | ['import pandas as pd', 'import numpy as np', 'import scipy.stats as stats', 'from sklearn.decomposition import PCA', 'from sklearn import metrics', 'from sklearn.cluster import DBSCAN', 'from sklearn.manifold import TSNE', 'from sklearn import preprocessing', 'from sklearn.cluster import KMeans', 'from sklearn.cluster... | [' sdd1.append(sdd_list[i][0][0])', ' sdd2.append(sdd_list[i][0][1])'] | ['', 'selected_stocks = []', 'selected_pairs_messd = []', 'opt_asset1=[]', 'opt_asset2=[]', '', 'for i in range(0,len(sdd_list)):', ' s1=sdd1[i]', ' s2=sdd2[i]', '', ' if (s1 not in selected_stocks) and (s2 not in selected_stocks):', ' selected_stocks.append(s1)', ' selected_stocks.append(s2)', '... | [{'reason_category': 'Loop Body', 'usage_line': 111}, {'reason_category': 'Loop Body', 'usage_line': 112}] | Variable 'sdd1' used at line 111 is defined at line 108 and has a Short-Range dependency.
Variable 'sdd_list' used at line 111 is defined at line 101 and has a Short-Range dependency.
Variable 'i' used at line 111 is part of a Loop defined at line 110 and has a Short-Range dependency.
Variable 'sdd2' used at line 112 i... | {'Loop Body': 2} | {'Variable Short-Range': 3, 'Variable Loop Short-Range': 2, 'Variable Medium-Range': 1} |
completion_python | Timeseries_Clustering | 120 | 130 | ['import pandas as pd', 'import numpy as np', 'import scipy.stats as stats', 'from sklearn.decomposition import PCA', 'from sklearn import metrics', 'from sklearn.cluster import DBSCAN', 'from sklearn.manifold import TSNE', 'from sklearn import preprocessing', 'from sklearn.cluster import KMeans', 'from sklearn.cluster... | [' s1=sdd1[i]', ' s2=sdd2[i]', '', ' if (s1 not in selected_stocks) and (s2 not in selected_stocks):', ' selected_stocks.append(s1)', ' selected_stocks.append(s2)', ' pair=(s1,s2)', ' selected_pairs_messd.append(pair)', '', ' if len(selected_pairs_messd) == math.comb(len(cluster1... | ['', 'opt_asset1=selected_stocks[0:len(selected_stocks)-1:2]', 'opt_asset2=selected_stocks[1:len(selected_stocks):2]', '', 'print(selected_pairs_messd)', '', '####### optimal pairs through correlation strategy use the normalised log returns of DBSCAN cluster1 assets', '', '#calculate pearson correlation for every possi... | [{'reason_category': 'Loop Body', 'usage_line': 120}, {'reason_category': 'Loop Body', 'usage_line': 121}, {'reason_category': 'Loop Body', 'usage_line': 122}, {'reason_category': 'Loop Body', 'usage_line': 123}, {'reason_category': 'If Condition', 'usage_line': 123}, {'reason_category': 'Loop Body', 'usage_line': 124}... | Variable 'sdd1' used at line 120 is defined at line 108 and has a Medium-Range dependency.
Variable 'i' used at line 120 is part of a Loop defined at line 119 and has a Short-Range dependency.
Variable 'sdd2' used at line 121 is defined at line 109 and has a Medium-Range dependency.
Variable 'i' used at line 121 is par... | {'Loop Body': 11, 'If Condition': 2, 'If Body': 5} | {'Variable Medium-Range': 5, 'Variable Loop Short-Range': 2, 'Variable Short-Range': 9, 'Library Long-Range': 1, 'Variable Long-Range': 1} |
completion_python | Timeseries_Clustering | 124 | 127 | ['import pandas as pd', 'import numpy as np', 'import scipy.stats as stats', 'from sklearn.decomposition import PCA', 'from sklearn import metrics', 'from sklearn.cluster import DBSCAN', 'from sklearn.manifold import TSNE', 'from sklearn import preprocessing', 'from sklearn.cluster import KMeans', 'from sklearn.cluster... | [' selected_stocks.append(s1)', ' selected_stocks.append(s2)', ' pair=(s1,s2)', ' selected_pairs_messd.append(pair)'] | ['', ' if len(selected_pairs_messd) == math.comb(len(cluster1_asset_list),2):', ' break', '', 'opt_asset1=selected_stocks[0:len(selected_stocks)-1:2]', 'opt_asset2=selected_stocks[1:len(selected_stocks):2]', '', 'print(selected_pairs_messd)', '', '####### optimal pairs through correlation strategy use the nor... | [{'reason_category': 'Loop Body', 'usage_line': 124}, {'reason_category': 'If Body', 'usage_line': 124}, {'reason_category': 'Loop Body', 'usage_line': 125}, {'reason_category': 'If Body', 'usage_line': 125}, {'reason_category': 'Loop Body', 'usage_line': 126}, {'reason_category': 'If Body', 'usage_line': 126}, {'reaso... | Variable 'selected_stocks' used at line 124 is defined at line 114 and has a Short-Range dependency.
Variable 's1' used at line 124 is defined at line 120 and has a Short-Range dependency.
Variable 'selected_stocks' used at line 125 is defined at line 114 and has a Medium-Range dependency.
Variable 's2' used at line 12... | {'Loop Body': 4, 'If Body': 4} | {'Variable Short-Range': 6, 'Variable Medium-Range': 2} |
completion_python | Timeseries_Clustering | 143 | 144 | ['import pandas as pd', 'import numpy as np', 'import scipy.stats as stats', 'from sklearn.decomposition import PCA', 'from sklearn import metrics', 'from sklearn.cluster import DBSCAN', 'from sklearn.manifold import TSNE', 'from sklearn import preprocessing', 'from sklearn.cluster import KMeans', 'from sklearn.cluster... | [' corr= pearsonr(clusters_norm_ret_df[pairs[i][0]],clusters_norm_ret_df[pairs[i][1]])[0]', ' pearson_corr_list.append(corr)'] | ['', '#sort pairs by pearson correlation', 'sort_corr_list=list(zip(pairs,pearson_corr_list))', 'sort_corr_list.sort(key = lambda x: x[1])', '', 'sdd1=[]', 'sdd2=[]', 'for i in range(0,len(sort_corr_list)):', ' sdd1.append(sort_corr_list[i][0][0])', ' sdd2.append(sort_corr_list[i][0][1])', '', 'selected_stocks = ... | [{'reason_category': 'Loop Body', 'usage_line': 143}, {'reason_category': 'Loop Body', 'usage_line': 144}] | Library 'pearsonr' used at line 143 is imported at line 16 and has a Long-Range dependency.
Variable 'clusters_norm_ret_df' used at line 143 is defined at line 80 and has a Long-Range dependency.
Variable 'pairs' used at line 143 is defined at line 88 and has a Long-Range dependency.
Variable 'i' used at line 143 is pa... | {'Loop Body': 2} | {'Library Long-Range': 1, 'Variable Long-Range': 2, 'Variable Loop Short-Range': 1, 'Variable Short-Range': 2} |
completion_python | Timeseries_Clustering | 153 | 154 | ['import pandas as pd', 'import numpy as np', 'import scipy.stats as stats', 'from sklearn.decomposition import PCA', 'from sklearn import metrics', 'from sklearn.cluster import DBSCAN', 'from sklearn.manifold import TSNE', 'from sklearn import preprocessing', 'from sklearn.cluster import KMeans', 'from sklearn.cluster... | [' sdd1.append(sort_corr_list[i][0][0])', ' sdd2.append(sort_corr_list[i][0][1])'] | ['', 'selected_stocks = []', 'selected_pairs_corr = []', 'opt_asset1=[]', 'opt_asset2=[]', '', 'for i in range(0,len(sort_corr_list)):', ' s1=sdd1[i]', ' s2=sdd2[i]', '', ' if (s1 not in selected_stocks) and (s2 not in selected_stocks):', ' selected_stocks.append(s1)', ' selected_stocks.append(s2... | [{'reason_category': 'Loop Body', 'usage_line': 153}, {'reason_category': 'Loop Body', 'usage_line': 154}] | Variable 'sdd1' used at line 153 is defined at line 150 and has a Short-Range dependency.
Variable 'sort_corr_list' used at line 153 is defined at line 147 and has a Short-Range dependency.
Variable 'i' used at line 153 is part of a Loop defined at line 152 and has a Short-Range dependency.
Variable 'sdd2' used at line... | {'Loop Body': 2} | {'Variable Short-Range': 4, 'Variable Loop Short-Range': 2} |
completion_python | Timeseries_Clustering | 166 | 169 | ['import pandas as pd', 'import numpy as np', 'import scipy.stats as stats', 'from sklearn.decomposition import PCA', 'from sklearn import metrics', 'from sklearn.cluster import DBSCAN', 'from sklearn.manifold import TSNE', 'from sklearn import preprocessing', 'from sklearn.cluster import KMeans', 'from sklearn.cluster... | [' selected_stocks.append(s1)', ' selected_stocks.append(s2)', ' pair=(s1,s2)', ' selected_pairs_corr.append(pair)'] | ['', ' if len(selected_pairs_corr) == math.comb(len(cluster1_asset_list),2):', ' break', '', 'opt_asset1=selected_stocks[0:len(selected_stocks)-1:2]', 'opt_asset2=selected_stocks[1:len(selected_stocks):2]', '', 'print(selected_pairs_corr)', '', '###### check which asset pairs are cointegrated from DSCAN clust... | [{'reason_category': 'Loop Body', 'usage_line': 166}, {'reason_category': 'If Body', 'usage_line': 166}, {'reason_category': 'Loop Body', 'usage_line': 167}, {'reason_category': 'If Body', 'usage_line': 167}, {'reason_category': 'Loop Body', 'usage_line': 168}, {'reason_category': 'If Body', 'usage_line': 168}, {'reaso... | Variable 'selected_stocks' used at line 166 is defined at line 156 and has a Short-Range dependency.
Variable 's1' used at line 166 is defined at line 162 and has a Short-Range dependency.
Variable 'selected_stocks' used at line 167 is defined at line 156 and has a Medium-Range dependency.
Variable 's2' used at line 16... | {'Loop Body': 4, 'If Body': 4} | {'Variable Short-Range': 6, 'Variable Medium-Range': 2} |
completion_python | Timeseries_Clustering | 183 | 186 | ['import pandas as pd', 'import numpy as np', 'import scipy.stats as stats', 'from sklearn.decomposition import PCA', 'from sklearn import metrics', 'from sklearn.cluster import DBSCAN', 'from sklearn.manifold import TSNE', 'from sklearn import preprocessing', 'from sklearn.cluster import KMeans', 'from sklearn.cluster... | [' score, pvalue, _ = coint(np.cumsum(clusters_norm_ret_df[pairs[i][0]]),np.cumsum(clusters_norm_ret_df[pairs[i][1]]))', ' confidence_level = 0.05', ' if pvalue < confidence_level:', ' coint_pairs.append(pairs[i])'] | ['print(coint_pairs)'] | [{'reason_category': 'Loop Body', 'usage_line': 183}, {'reason_category': 'Loop Body', 'usage_line': 184}, {'reason_category': 'Loop Body', 'usage_line': 185}, {'reason_category': 'If Condition', 'usage_line': 185}, {'reason_category': 'Loop Body', 'usage_line': 186}, {'reason_category': 'If Body', 'usage_line': 186}] | Library 'coint' used at line 183 is imported at line 17 and has a Long-Range dependency.
Library 'np' used at line 183 is imported at line 2 and has a Long-Range dependency.
Variable 'clusters_norm_ret_df' used at line 183 is defined at line 80 and has a Long-Range dependency.
Variable 'pairs' used at line 183 is defin... | {'Loop Body': 4, 'If Condition': 1, 'If Body': 1} | {'Library Long-Range': 2, 'Variable Long-Range': 3, 'Variable Loop Short-Range': 2, 'Variable Short-Range': 3} |
completion_python | Timeseries_Clustering | 186 | 186 | ['import pandas as pd', 'import numpy as np', 'import scipy.stats as stats', 'from sklearn.decomposition import PCA', 'from sklearn import metrics', 'from sklearn.cluster import DBSCAN', 'from sklearn.manifold import TSNE', 'from sklearn import preprocessing', 'from sklearn.cluster import KMeans', 'from sklearn.cluster... | [' coint_pairs.append(pairs[i])'] | ['print(coint_pairs)'] | [{'reason_category': 'Loop Body', 'usage_line': 186}, {'reason_category': 'If Body', 'usage_line': 186}] | Variable 'coint_pairs' used at line 186 is defined at line 180 and has a Short-Range dependency.
Variable 'pairs' used at line 186 is defined at line 88 and has a Long-Range dependency.
Variable 'i' used at line 186 is part of a Loop defined at line 182 and has a Short-Range dependency. | {'Loop Body': 1, 'If Body': 1} | {'Variable Short-Range': 1, 'Variable Long-Range': 1, 'Variable Loop Short-Range': 1} |
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