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How to use error_step method in grail
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SQL_converter.py
Source:SQL_converter.py 
1# -*- coding: utf-8 -*-2import json3import os4import codecs5import pickle6import babel7import unicodedata8import re9from tqdm import tqdm10from babel.numbers import parse_decimal, NumberFormatError11from nsm import word_embeddings12from nsm import data_utils13from utils import load_jsonl, create_envs, collect_traj_for_program, FLAGS14def find_cmd_head(program, pos):15 '''16 find the command name given a position in the whole program17 '''18 if program[pos] == '(':19 return 'abort', 020 for i in range(pos, -1, -1):21 if program[i] == '(':22 return program[i+1], (pos-i)23 return None, None24def find_entity(namespace, token, type_constraint=None):25 '''26 # first try to determine the type of the entity being numerical or string27 if type_constraint is None:28 try:29 if type(token) == int or type(token) == float:30 val = float(token)31 else:32 val = float(babel.numbers.parse_decimal(token))33 numerical = True34 except NumberFormatError:35 val = normalize(token)36 numerical = False37 else:38 if type_constraint == 'str':39 numerical = False40 val = token if type(token) is str else str(int(token))41 else:42 raise NotImplementedError43 '''44 if type(token) == unicode:45 numerical = False46 val = normalize(token)47 else:48 numerical = True49 val = float(token)50 while True:51 # now we enumerate to find the entity52 for i in range(namespace.n_var-1, -1, -1):53 variable = namespace['v'+str(i)]54 if variable['type'] == 'num_list' and numerical:55 # sanity check56 assert(len(variable['value']) == 1)57 if val == variable['value'][0]:58 return i, numerical59 elif variable['type'] == 'string_list' and not numerical:60 # sanity check61 assert(len(variable['value']) == 1)62 if val == variable['value'][0]:63 return i, numerical64 else:65 continue66 #return -1, numerical67 # entity not found -> try the other type68 if not numerical:69 try:70 val = float(babel.numbers.parse_decimal(token))71 numerical = True72 except NumberFormatError:73 return -1, numerical74 else:75 return -1, numerical76 # return -1 when such token is not found as an entity77 return -1, numerical78# ################## copied from preprocess.py ##############################79def normalize(x):80 if not isinstance(x, unicode):81 x = x.decode('utf8', errors='ignore')82 # Remove diacritics83 x = ''.join(c for c in unicodedata.normalize('NFKD', x)84 if unicodedata.category(c) != 'Mn')85 # Normalize quotes and dashes86 x = re.sub(ur"[ââ´`]", "'", x)87 x = re.sub(ur"[ââ]", "\"", x)88 x = re.sub(ur"[ââââââ]", "-", x)89 while True:90 old_x = x91 # Remove citations92 x = re.sub(ur"((?<!^)\[[^\]]*\]|\[\d+\]|[â¢â¦â â¡*#+])*$", "", x.strip())93 # Remove details in parenthesis94 x = re.sub(ur"(?<!^)( \([^)]*\))*$", "", x.strip())95 # Remove outermost quotation mark96 x = re.sub(ur'^"([^"]*)"$', r'\1', x.strip())97 if x == old_x:98 break99 # Remove final '.'100 if x and x[-1] == '.':101 x = x[:-1]102 # Collapse whitespaces and convert to lower case103 x = re.sub(ur'\s+', ' ', x, flags=re.U).lower().strip()104 return x105# ################## copied from preprocess.py ##############################106def convert(env):107 '''108 Some explanation for the sql language:109 sel: column index (starting from 0)110 agg: aggregation index111 conds: a list of cond112 cond: column_idx, operator_idx, condition113 operator: ['=', '>', '<', 'OP']114 aggregation: ['', 'MAX', 'MIN', 'COUNT', 'SUM', 'AVG']115 '''116 # define some constants to fit the grammar of wikisql117 filters =['filter_eq', 'filter_greater', 'filter_less', 'filter_other', 'filter_eq']118 aggregations = ['none', 'maximum', 'minimum', 'count_stub', 'sum', 'average']119 sql = env.question_annotation['sql']120 code = []121 # first select the rows according to the condition using filters122 for i, cond in enumerate(sql['conds']):123 if i == 0:124 rows = 'all_rows'125 else:126 rows = 'v' + str(env.interpreter.namespace.n_var + i - 1)127 # 1. get the column index128 column = 'v' + str(cond[0])129 # 2. try to locate the token in the entity list and get its type130 entity_var, entity_numerical= find_entity(env.interpreter.namespace, cond[2])131 if entity_var == -1:132 return None133 else:134 value = 'v' + str(entity_var)135 # 3. use the correct filter136 if cond[1] == 0:137 # equal filter, need to know the type138 fltr = filters[0] if entity_numerical else filters[4]139 else:140 fltr = filters[cond[1]]141 statement = ' '.join(['(', fltr, rows, value, column, ')'])142 code.append(statement)143 # then perform the aggregation process144 rows = 'all_rows' if len(sql['conds']) == 0 else ('v' + str(env.interpreter.namespace.n_var+len(sql['conds']) - 1))145 if sql['agg'] == 0: # just hop to the value of the first row146 column = 'v' + str(sql['sel'])147 statement = ' '.join(['(', 'hop', rows, column, ')'])148 else:149 if sql['agg'] == 3: # count, which has slightly different grammar than the other aggs150 statement = ' '.join(['(', 'count', rows, ')'])151 else:152 agg = aggregations[sql['agg']]153 column = 'v' + str(sql['sel'])154 statement = ' '.join(['(', agg, rows, column, ')'])155 code.append(statement)156 # add <END> to the end of the program proper interpretation157 code.append('<END>')158 code = ' '.join(code)159 return code160def get_env_trajs(envs):161 good_oracle_envs = []162 envs_trajs = []163 envs_programs = []164 for i, env in enumerate(envs):165 program = convert(env)166 if program is not None: # means all entities are found167 traj, error_info = collect_traj_for_program(env, program.split(' '), debug=True)168 if traj is None:169 # find the error cmd170 program = error_info[2]171 error_step = len(error_info[1])172 cmd, re_pos = find_cmd_head(program, error_step)173 error_cmd_pos = error_step - re_pos + 1174 # attempt to fix the traj if the interpreter failed to parse175 if cmd == 'filter_eq':176 # change the entity from the num_list one to string_list one177 num_entity_idx = int(program[error_cmd_pos+2][1:])178 str_entity = 'v' + str(num_entity_idx-1)179 # see if we get the right str entity180 if env.interpreter.namespace[str_entity]['type'] == 'string_list':181 program[error_cmd_pos] = 'filter_eq'182 program[error_cmd_pos+2] = str_entity183 # see if this simple flip fix this problem184 traj, error_info = collect_traj_for_program(env, program, debug=True)185 if traj is not None: # means interpreter can successfully parse converted code186 if traj.rewards[-1] == 1.0: # means the code can get reward in the environment187 good_oracle_envs.append(env)188 envs_trajs.append(traj)189 envs_programs.append(program)190 return good_oracle_envs, envs_trajs #, envs_programs191data_folder = "../../data/wikisql/"192train_shard_dir = "../../data/wikisql/processed_input/preprocess_4/"193train_shard_prefix = "train_split_shard_30-"194table_file = "../../data/wikisql/processed_input/preprocess_4/tables.jsonl"195vocab_file = "../../data/wikisql/raw_input/wikisql_glove_vocab.json"196embedding_file = "../../data/wikisql/raw_input/wikisql_glove_embedding_mat.npy"197en_vocab_file = "../../data/wikisql/processed_input/preprocess_4/en_vocab_min_count_5.json"198def get_train_shard_path(i):199 return os.path.join(train_shard_dir, train_shard_prefix + str(i) + '.jsonl')200def get_envs(env_files=None):201 dataset = []202 if env_files is None:203 fns = [get_train_shard_path(i) for i in range(0, 30)]204 else:205 fns = env_files206 for fn in fns:207 dataset += load_jsonl(fn)208 tables = load_jsonl(table_file)209 table_dict = dict([(table['name'], table) for table in tables])210 # Load pretrained embeddings.211 embedding_model = word_embeddings.EmbeddingModel(vocab_file, embedding_file )212 with open(en_vocab_file, 'r') as f:213 vocab = json.load(f)214 en_vocab = data_utils.Vocab([])215 en_vocab.load_vocab(vocab)216 # Create environments.217 envs = create_envs(table_dict, dataset, en_vocab, embedding_model)218 return envs219def error_analysis():220 f = codecs.open('converter_error_list.bin', 'rb')221 error_list = pickle.load(f)222 f.close()223 # pick the ones that failed to interpret224 interpreter_error_list = [error_example for error_example in error_list if error_example[0] == 'interpreter failed to parse']225 # two set of commands (filter/aggregation) that make the interpreter fail226 filter_list = ['filter_eq', 'filter_greater', 'filter_less', 'filter_str_contain_any']227 agg_list = ['maximum', 'minimum', 'count', 'sum', 'average']228 other_cmd_list = ['hop', 'abort']229 # see for filters/agg, at which argument do they fail to interpret230 filter_error_dict = dict()231 agg_error_dict = dict()232 other_error_dict = dict()233 for filter in filter_list:234 filter_error_dict[filter] = [0,0,0,0,0,0]235 for agg in agg_list:236 agg_error_dict[agg] = [0,0,0,0,0]237 for cmd in other_cmd_list:238 other_error_dict[cmd] = [0,0,0,0,0]239 # see at which step (filter/aggregation) do they fail240 for example in interpreter_error_list:241 program = example[1][2]242 error_step = len(example[1][1])243 cmd, re_pos = find_cmd_head(program, error_step)244 if cmd in filter_list:245 filter_error_dict[cmd][re_pos] += 1246 elif cmd in agg_list:247 agg_error_dict[cmd][re_pos] += 1248 elif cmd in other_cmd_list:249 other_error_dict[cmd][re_pos] += 1250 else:251 print(cmd, program, error_step)252 raise NotImplementedError253 print('Total %d examples can not be interpreted' % len(interpreter_error_list))254 print('%d are filter errors as %s ' % (sum(map(sum, filter_error_dict.values())), filter_error_dict))255 print('%d are aggregation errors as %s ' % (sum(map(sum, agg_error_dict.values())), agg_error_dict))256 print('%d are other errors as %s ' % (sum(map(sum, other_error_dict.values())), other_error_dict))257 # pick the ones that got the wrong answer258 answer_error_list = [error_example for error_example in error_list if error_example[0] == 'wrong answer']259 length_mismatch = 0260 correct_after_normalize = 0261 first_item_match = 0262 for _, env_answer, traj_answer in answer_error_list:263 if len(env_answer) == 0 or len(traj_answer) == 0:264 continue265 if len(env_answer) != len(traj_answer):266 length_mismatch += 1267 if isinstance(env_answer[0], unicode) and isinstance(traj_answer[0], unicode):268 if normalize(env_answer[0]) == normalize(traj_answer[0]):269 first_item_match+= 1270 else:271 if env_answer[0] == traj_answer[0]:272 first_item_match+= 1273 else:274 if all([isinstance(answer, unicode) for answer in (env_answer+traj_answer)]):275 normalized_env_answer = [normalize(answer) for answer in env_answer]276 normalized_traj_answer = [normalize(answer) for answer in traj_answer]277 if normalized_env_answer == normalized_traj_answer:278 correct_after_normalize += 1279 print('Total %d examples got the wrong answer' % len(answer_error_list))280 print('%d are length mismatch but with %d match on the first item' % (length_mismatch, first_item_match))281 print('%d are correct after normalize' % correct_after_normalize)282 return None283def main():284 envs = get_envs()285 # error analysis286 error_list = []287 error_log_file = codecs.open('error_log.txt', 'wb', encoding='utf-8')288 success = 0289 error_1 = 0290 error_2 = 0291 error_3 = 0292 for i, env in tqdm(enumerate(envs)):293 code = convert(env)294 if code is None:295 error_1 += 1296 error_list.append(('can not find entity', None, None))297 continue298 else:299 # verify the correctness of the code300 traj, error_info = collect_traj_for_program(env, code.split(' '), debug=True)301 #'''302 if traj is None:303 # find the error cmd304 program = error_info[2]305 error_step = len(error_info[1])306 cmd, re_pos = find_cmd_head(program, error_step)307 error_cmd_pos = error_step - re_pos + 1308 # attempt to fix the traj if the interpreter failed to parse309 if cmd == 'filter_eq':310 # change the entity from the num_list one to string_list one311 num_entity_idx = int(program[error_cmd_pos+2][1:])312 str_entity = 'v' + str(num_entity_idx-1)313 # see if we get the right str entity314 if env.interpreter.namespace[str_entity]['type'] == 'string_list':315 program[error_cmd_pos] = 'filter_eq'316 program[error_cmd_pos+2] = str_entity317 # see if this simple flip fix this problem318 traj, error_info = collect_traj_for_program(env, program, debug=True)319 #'''320 if traj is not None:321 if traj.rewards[-1] == 1.0:322 success += 1323 else:324 error_3 += 1325 error_list.append(('wrong answer', env.answer, traj.answer))326 err_log = '%d, expected answer %s, but got answer %s, question is \' %s \' with table %s \n' \327 % (i, env.answer, traj.answer, env.question_annotation['question'], env.question_annotation['context'])328 print(err_log)329 error_log_file.write(err_log)330 else:331 error_2 += 1332 error_list.append(('interpreter failed to parse', error_info, None))333 error_step = len(error_info[1])334 error_token = error_info[2][error_step]335 cmd, re_pos = find_cmd_head(error_info[2], error_step)336 err_log = '%d, command %s step %d error token %s, full program: %s \n' % (i, cmd, error_step, error_token, error_info[2])337 print(err_log)338 error_log_file.write(err_log)339 error_log_file.close()340 print('total %d example, successful converted %d (%f), %d (%f) can not find entity, %d (%f) failed to interpret and %d (%f) got wrong answer'341 % (len(envs),342 success, float(success)/len(envs),343 error_1, float(error_1)/len(envs),344 error_2, float(error_2)/len(envs),345 error_3, float(error_3)/len(envs)))346 with codecs.open('converter_error_list.bin', 'wb') as f:347 pickle.dump(error_list, f)348def loaded_program_analysis():349 envs = get_envs()350 saved_program_file = '../../data/wikisql/processed_input/preprocess_2/all_train_saved_programs-1k_5.json'351 #saved_program_file = '../../data/wikitable/processed_input/all_train_saved_programs.json'352 with open(saved_program_file, 'r') as f:353 program_dict = json.load(f)354 non_empty_env = 0355 spurious_program_enc = 0356 avg_nonempty_env = 0357 for key in program_dict.keys():358 program_list = program_dict[key]359 if len(program_list) > 0:360 non_empty_env += 1361 avg_nonempty_env += len(program_list)362 if len(program_list) > 1:363 spurious_program_enc += 1364 avg_nonempty_env = avg_nonempty_env / float(non_empty_env)365 print '%d items in loaded programs, with %d non-empty and %d have spurious forms with avg of %f' \366 % (len(program_dict), non_empty_env, spurious_program_enc, avg_nonempty_env)367 return368 envs, env_trajs, env_programs = get_env_trajs(envs)369 # stats370 non_empty_env = 0371 match_oracle = 0372 for env, env_traj, program in zip(envs, env_trajs, env_programs):373 env_loaded_program_list = program_dict[env.name]374 if env_loaded_program_list is not None and len(env_loaded_program_list) != 0:375 non_empty_env += 1376 if program in env_loaded_program_list:377 match_oracle += 1378 print '%d items in loaded programs, with %d non-empty and %d envs have an oracle match' % (len(program_dict), non_empty_env, match_oracle)379if __name__ == '__main__':380 FLAGS.executor = 'wikisql'381 #main()382 #error_analysis()...
visualization.py
Source:visualization.py
1import numpy as np2import matplotlib.pyplot as plt3from matplotlib import collections as mc4from io import StringIO, BytesIO5import PIL6import cv27import rslo.utils.pose_utils_np as pun8def pltfig2data(fig):9 """10 @brief Convert a Matplotlib figure to a 4D numpy array with RGBA channels and return it11 @param fig a matplotlib figure12 @return a numpy 3D array of RGBA values13 """14 # draw the renderer15 # fig.canvas.draw()16 # # Get the RGBA buffer from the figure17 # w, h = fig.canvas.get_width_height()18 # buf = np.fromstring(fig.canvas.tostring_argb(), dtype=np.uint8)19 # buf.shape = (w, h, 4)20 # # canvas.tostring_argb give pixmap in ARGB mode. Roll the ALPHA channel to have it in RGBA mode21 # buf = np.roll(buf, 3, axis=2)22 # buf = buf.astype(float)/25523 # ç³è¯·ç¼å²å°å24 buffer_ = BytesIO() # StringIO() # using buffer,great way!25 # ä¿åå¨å
åä¸ï¼èä¸æ¯å¨æ¬å°ç£çï¼æ³¨æè¿ä¸ªé»è®¤è®¤ä¸ºä½ è¦ä¿åçå°±æ¯pltä¸çå
容26 fig.savefig(buffer_, format='png')27 buffer_.seek(0)28 # ç¨PILæCV2ä»å
åä¸è¯»å29 dataPIL = PIL.Image.open(buffer_)30 # 转æ¢ä¸ºnparraryï¼PIL转æ¢å°±é常快äº,dataå³ä¸ºæé31 data = np.asarray(dataPIL)32 data = data.astype(float)/255.33 # cv2.imwrite('test.png', data)34 # éæ¾ç¼å35 buffer_.close()36 plt.close(fig)37 return data38# def draw_odometry(odom_vectors, gt_vectors=None, view='bv', saving_dir=None):39def draw_trajectory(poses_pred, poses_gt=None, view='bv', saving_dir=None, figure=None, ax=None, color='b', error_step=1, odom_errors=None):40 """[summary]41 Arguments:42 poses_pred {[np.array]} -- [(N,7)]43 Keyword Arguments:44 poses_gt {[np.array]} -- [(N,7)] (default: {None})45 view {str} -- [description] (default: {'bv'})46 saving_dir {[type]} -- [description] (default: {None})47 figure {[type]} -- [description] (default: {None})48 ax {[type]} -- [description] (default: {None})49 color {str} -- [description] (default: {'b'})50 """51 assert(view in ['bv', 'front', 'side'])52 translation, rotation = poses_pred[:, :3], poses_pred[:, 3:]53 if poses_gt is not None:54 assert len(poses_pred) == len(poses_gt)55 translation_gt, rotation_gt = poses_gt[:, :3], poses_gt[:, 3:]56 if view == 'bv':57 dim0, dim1 = 0, 158 elif view == 'front':59 dim0, dim1 = 0, 160 elif view == 'side':61 dim0, dim1 = 0, 162 if figure is None or ax is None:63 figure = plt.figure()64 ax = figure.add_subplot(111)65 for i in range(1, len(translation)):66 if i == 1:67 ax.plot([translation[i-1][dim0]], [68 translation[i-1][dim1]], '*', markersize=10, color=color)69 ax.plot([translation[i-1][dim0], translation[i][dim0]], [70 translation[i-1][dim1], translation[i][dim1]], '-', markersize=0.5, color=color)71 if poses_gt is not None:72 ax.plot([translation_gt[i-1][dim0], translation_gt[i][dim0]], [73 translation_gt[i-1][dim1], translation_gt[i][dim1]], '-', markersize=0.5, color='r')74 if i % 50 == 0:75 # plot connection lines76 ax.plot([translation[i][dim0], translation_gt[i][dim0]], [77 translation[i][dim1], translation_gt[i][dim1]], '-', markersize=0.03, color='gray')78 # and i%error_step==0 and i//error_step<len(errors):79 if 0:#odom_errors is not None:80 odom_errors = odom_errors[::error_step]81 l = min(len(translation[::error_step] ), len(odom_errors))82 cm = plt.cm.get_cmap('hot')83 ax.scatter(translation[::error_step, dim0][:l]+10, translation[::error_step, dim1][:l]+10,84 marker='o', c=odom_errors[:, 0], cmap=cm, vmin=np.min(odom_errors[:, 0]), vmax=np.max(odom_errors[:, 0]), linewidths=0.01)85 ax.scatter(translation[::error_step, dim0][:l]-10, translation[::error_step, dim1][:l]-10,86 marker='x', c=odom_errors[:, 1], cmap=cm, vmin=np.min(odom_errors[:, 1]), vmax=np.max(odom_errors[:, 1]), linewidths=0.01)87 88 if saving_dir is not None:89 figure.savefig(saving_dir)90 return figure, ax91def draw_odometry(odom_vectors, view='bv', saving_dir=None, figure=None, ax=None, color='b'):92 """[draw odometry]93 Args:94 odom_vectors ([numpy arrays of size (N,7)]): quaternion+translation95 gt (as the same as odom_vectors, optional): Defaults to None.96 view([str], optional): The view to draw97 """98 assert(view in ['bv', 'front', 'side'])99 translation, rotation = odom_vectors[:, :3], odom_vectors[:, 3:]100 if view == 'bv':101 # translation = translation[:, [0, 2]]102 dim0, dim1 = 0, 1103 # translation = translation[:, [0, 1]]104 elif view == 'front':105 dim0, dim1 = 0, 1106 # translation = translation[:, [0, 1]]107 elif view == 'side':108 dim0, dim1 = 0, 1109 # translation = translation[:, [1, 2]]110 if figure is None or ax is None:111 figure = plt.figure()112 ax = figure.add_subplot(111)113 # lines = np.stack([starts, ends], axis=1)114 # lc = mc.LineCollection(lines, linewidths=0.3)115 # ax.add_collection(lc)116 t_prev = translation[0:1]117 r_prev = rotation[0:1]118 for i in range(1, len(translation)):119 r_cur = pun.qmult(r_prev, rotation[i:i+1])120 t_cur = t_prev + \121 pun.rotate_vec_by_q(122 translation[i:i+1], r_prev)123 # t_cur = translation[i]124 if i == 1:125 ax.plot([t_prev[0][dim0], t_cur[0][dim0]], [126 t_prev[0][dim1], t_cur[0][dim1]], '*', markersize=10, color=color)127 ax.plot([t_prev[0][dim0], t_cur[0][dim0]], [128 t_prev[0][dim1], t_cur[0][dim1]], '-', markersize=0.5, color=color)129 t_prev = t_cur130 r_prev = r_cur131 if saving_dir is not None:132 figure.savefig(saving_dir)...
model.py
Source:model.py
1from typing import List, Tuple2import config3import random4#Podstawowe dane symulacji5TRACK_LENGTH = 1.06DEFAULT_VEL = 1.07ERROR_STEP = config.ERROR_STEP8MAX_ERROR = config.MAX_ERROR9#WspóÅczynnik losowoÅci sprawia, że każda prÄdkoÅÄ kuli jest jeszcze leciutko modyfikowana10#Kule nie mogÄ
siÄ już trywialnie spotkaÄ po dÅuższym czasie11RANDOMNESS_FACTOR = ERROR_STEP/312assert MAX_ERROR <= TRACK_LENGTH13assert ERROR_STEP < MAX_ERROR14DEFAULT_NUM = round(MAX_ERROR/ERROR_STEP)15#Wyliczanie poszczególnych prÄdkoÅci wszysktich kul16CELLS_VEL = [DEFAULT_VEL + ERROR_STEP*i + RANDOMNESS_FACTOR * random.uniform(-1,1) for i in range(-DEFAULT_NUM,DEFAULT_NUM + 1)]17CELLS_VEL[DEFAULT_NUM] = DEFAULT_VEL18CELLS = len(CELLS_VEL)19#Tutaj przechowywane bÄdÄ
wszystkie wyliczone parametry kul20Cache : List[Tuple[int,float,int]] = [(0, 0, 0) for _ in range(CELLS)]21#Liczenie kolejno kierunku, pozycji i liczby odbiÄ kuli w zależnoÅci od czasu i prÄdkoÅci22def get_relative_ball_info(t: float, v: float):23 pre = (t * v) % (2 * TRACK_LENGTH)24 pre_nob = int((t * v) // (2 * TRACK_LENGTH))25 if pre >= TRACK_LENGTH:26 return (-1, 2 * TRACK_LENGTH - pre, 2*pre_nob + 1) 27 else:28 return (1, pre, 2*pre_nob)29#Aktualizacja informacji o kulach30def update_pos(t: float):31 global Cache32 for i in range(CELLS):33 Cache[i] = get_relative_ball_info(t, CELLS_VEL[i])34#Zdobycie minimalnej i maksymalnej pozycji kul przy aktualnym stanie tablicy Cache35def get_min_max_x():36 min_x = 1.037 max_x = 0.038 for (_,x,_) in Cache:39 min_x = min(x,min_x)40 max_x = max(x,max_x)41 return (min_x, max_x)42#Liczenie bÅÄdów zwrotu, pozycji i odbiÄ43#Odbicia sÄ
liczone starÄ
metodÄ
, którÄ
odrzuciÅem dla liczenia bÅÄdu pozycji44#ale uznaÅem, że odbicia nie sÄ
na tyle istotne, żeby je też aktualizowaÄ45def calculate_error():46 (min_x, max_x) = get_min_max_x()47 delta_x = (max_x-min_x)48 delta_b = 049 known_dir = True50 for (dir,_,b) in Cache:51 delta_b = max(abs(b-Cache[DEFAULT_NUM][2]),delta_b)52 known_dir = known_dir and (dir == Cache[DEFAULT_NUM][0]) ...
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