How to use task_start method in autotest
Best Python code snippet using autotest_python
Temps.py
Source:Temps.py 
1import pandas as pd2import numpy as np3def work_schedule(nb_days = 365, day_start = 8, day_end = 24, month_start = 1,work_on_weekend = False):4 """5 Paramètres:6 nb_days:7 Nombre de jour de la simulation.8 (int: 1 à 365)9 day_start:10 Heure de début de la journée de travail.11 (int: 0 à 24)12 day_end:13 Heure de fin de la journée de travail.14 (int: 0 à 24)15 month_start:16 Mois de début de simulation.17 (int: 1 à 12)18 19 Sortie:20 Dataframes sur les heures de travail (0/1), journées de travail (0/1) et mois (1 à 12).21 """22 23 columns = ["work_time", "work_day", "month"]24 df= pd.DataFrame(columns = columns, index = range(nb_days * 24))25 26 # Heures de travail27 df.work_time = list(range(1,25)) * nb_days28 df.loc[(df.work_time < day_start+1) | (df.work_time >= day_end+1), "work_time"] = False29 df.loc[df.work_time != False, "work_time"] = True30 df = df.replace({True: 1, False: 0})31 32 # Semaine et fin de semaine33 df.work_day = np.ceil((df.index+1)/24)34 if work_on_weekend :35 df["work_day"] = 136 else : 37 df.work_day = np.where((df.work_day % 7 == 0) | ((df.work_day + 1) % 7 == 0), 0, 1)38 df.loc[df.work_day == 0, "work_time"] = 039 40 # Mois41 month_order = list(range(month_start,13)) + list(range(1, month_start))42 month_dict = {1:31, 2:28, 3:31, 4:30, 5:31, 6:30, 7:31, 8:31, 9:30, 10:31, 11:30, 12:31}43 month_length = np.array([month_dict[m] for m in month_order])*2444 for i in range(len(month_order)):45 idx = df.loc[df.month.isna(), "month"].index[:month_length[i]]46 df.loc[idx, "month"] = month_order[i]47 df.month = df.month.astype(int)48 49 return df50def task_total_length(df, task_start, task_time):51 """52 Paramètres:53 df:54 Dataframe sur les horaires de travail.55 task_start:56 Heure de début de la tâche.57 (float: 0 à len(df))58 task_time:59 Durée de la tâche.60 (float)61 62 Sortie:63 Durée finale de la tâche avec les arrêts de travail.64 """65 66 # Ramener le calcul à partir de la première semaine pour être certain67 # de ne pas défoncé l'année... Permet de réutiliser directement le code déjà 68 # fonctionnel pour 1 an, mais pourrait être à revoir si la gestion de semaines/mois69 # apporteraient des nuances...70 if task_start > 7 * 24 : 71 return task_total_length(df,task_start - int(task_start / (7*24))*(7*24),task_time)72 73 74 length = pd.Index(df.loc[int(task_start):, "work_time"].cumsum()).get_loc(int(task_time))75 76 # length est un slice plutôt qu'un int quand la dernière heure de travail est avant un arrêt de travail77 # Si task_start est une valeur sans décimale, la tâche se termine avant l'arrêt78 # Sinon, elle se termine au retour79 if isinstance(length, slice):80 if (task_start == int(task_start)) and (task_time == int(task_time)):81 length = length.start + 182 else:83 length = length.stop84 else:85 length += 186 87 # Ajustement de décimale si la tâche débute quand il n'y a pas de travail88 if df.loc[int(task_start), "work_time"] == 0:89 length = length - (task_start - int(task_start))90 91 # Ajustement de décimale si la durée de la tâche a une décimale92 length = length + (task_time - int(task_time))93 return length94def GetInfosTemps(now) : 95 """96 Paramètres:97 now:98 Temps en heure (réel)99 100 Sortie:101 day_of_week : jour de la semaine (1 à 7)102 hour : heure de la journée (réel)103 """104 105 day_of_week = ((int(now / 24)) % 7) + 1 106 hour = now % 24 107 108 return day_of_week, hour109def HeuresProductives(df,debut,fin):110 """111 Paramètres:112 df:113 Dataframe sur les horaires de travail.114 debut:115 Heure de début du calcul116 fin:117 Fin de la tâche.118 119 Sortie:120 Durée en heures (réel) de travail productive entre debut et fin121 """122 # Si l'heure de début excéde l'heure de fin, il n'y a pas d'heures productives123 # (Cette situation pourrait survenir si on ne gère pas bien certaines transitions entre le 124 # régime transitoire et le permanent. Les indicateurs comptes à partir du régime permanent125 # et on se compare au now)126 if debut >= fin : 127 return 0128 # Ramener le calcul à partir de la première semaine pour être certain129 # de ne pas défoncé l'année... Permet de réutiliser directement le code déjà 130 # fonctionnel pour 1 an, mais pourrait être à revoir si la gestion de semaines/mois131 # apporteraient des nuances...132 if debut > 7 * 24 : 133 return HeuresProductives(df,debut - int(debut / (7*24))*(7*24),fin - int(debut / (7*24))*(7*24))134 # Retirer les semaines complètes pour ne pas défoncer l'année de calcul135 if (fin - debut) > 24 * 7 : 136 NbHeuresUneSemaine = sum(df[:168]["work_time"])137 NbSemainesComplètes = int((fin-debut) / (24*7))138 NbHeuresSemainesComplètes = NbSemainesComplètes * NbHeuresUneSemaine139 DureeSemIncomplete = HeuresProductives(df,debut,fin - NbSemainesComplètes*(7*24))140 return NbHeuresSemainesComplètes + DureeSemIncomplete141 142 nbHeures = sum(df[int(debut):int(fin)]["work_time"])143 MinutesDebut = (debut - int(debut)) * df.iloc[int(debut)]["work_time"]144 MinutesFin = (fin - int(fin)) * df.iloc[int(fin)]["work_time"]145 146 return nbHeures - MinutesDebut + MinutesFin 147 148if __name__ == "__main__":149 150 151 df = work_schedule(nb_days = 365, day_start = 0, day_end = 24, month_start = 1,work_on_weekend=False)152 task_length = task_total_length(df, task_start = 360*24, task_time = 23)153 #print(task_length)154 155 if 1 ==0 : 156 # Pour faciliter le développement, on s'assure d'avoir toujours le mêmes157 # nombres aléatoires d'une exécution à l'autre158 import random159 random.seed(1)160 161 now = 0162 for jour in range(1,5000) : 163 print(jour)164 for heure in range(1) : 165 for minutes in range(1) : 166 task_start = jour*24 + heure + minutes/60167 task_time = random.random() * 1500 + 1168 169 #bk = task_total_length_bk(df, task_start = jour*24 + heure + minutes/60, task_time = 50)170 new = task_total_length(df, task_start = task_start, task_time = task_time)171 end = new + task_start172 173 prod = HeuresProductives(df,task_start,end)174 175 176 if round(prod,4) != round(task_time,4) : 177 #print("PROBLÃME", task_start, task_time, new,prod)178 # task_start = jour*24 + heure + minutes/60179 180 # task_time = 50181 182 # print(jour,heure,minutes,"PROBLÃME")183 # print(bk)184 # print(new)185 print("task start", task_start, "task time", task_time)186 print("new",new)187 print("prod",prod)188 print("end",end)189 # print(task_start - int(task_start / (7*24))*(7*24))190 exit191 192 print("FINI") 193 # print(now, jour, heure)194 #print("now : ", now,"jour : ", jour)195 196 #month, day_of_week, hour = GetInfosTemps(now)197 198 #print(day_of_week)199 #print()200 201 #now += 1 * 24202 debut = 189.17756324661573 203 fin = debut-5204 print("Calculer",HeuresProductives(df,debut,fin))205 print("Bon 24/7", fin-debut)...
runner.py
Source:runner.py
1from copy import deepcopy2from cbs import CBSSolver3from prioritised import PrioritizedPlanningSolver4from visualize import Animation5from path_astar_one import get_sum_of_cost, path6import itertools7import heapq8def min_cost_task_assn(starts,tasks):9 _tasks = list(itertools.permutations(tasks))10 _len = len(starts)11 starts_set=[]12 tasks_set=[]13 for t in _tasks:14 starts_set.append(starts)15 tasks_set.append(list(t))16 paths_with_cost = []17 for i, j in zip(starts_set, tasks_set):18 cbs = CBSSolver(my_map, i, j)19 _paths = cbs.find_solution(True, CBSSolver.NORMAL)20 _cost = get_sum_of_cost(_paths)21 paths_with_cost.append((_paths, _cost))22 _min_path = min(paths_with_cost, key=lambda x: x[1])23 return _min_path[0],_min_path[1]24def read_input(filename):25 f = open(filename, 'r')26 line = f.readline()27 rows, columns = [int(x) for x in line.split(' ')]28 rows = int(rows)29 columns = int(columns)30 my_map = []31 for r in range(rows):32 line = f.readline()33 my_map.append([])34 for cell in line:35 if cell == '@' or cell == 'T':36 my_map[-1].append(True)37 elif cell == '.':38 my_map[-1].append(False)39 line = f.readline()40 num_agents = int(line)41 agent_loc=[]42 task_start=[]43 task_goal=[]44 #print(num_agents)45 for a in range(num_agents):46 line=f.readline()47 sx, sy = [int(x) for x in line.split(' ')]48 agent_loc.append((sx,sy))49 line = f.readline()50 num_tasks = int(line)51 for a in range(num_tasks):52 line = f.readline()53 sx, sy, gx, gy = [int(x) for x in line.split(' ')]54 task_start.append((sx,sy))55 task_goal.append((gx,gy))56 line = f.readline()57 aaa,ttt=[],[]58 if(int(line)>0):59 for i in range(int(line)):60 line = f.readline()61 x,y = [int(x) for x in line.split(' ')]62 aaa.append(x)63 ttt.append(y)64 f.close()65 return my_map,agent_loc,task_start,task_goal,aaa,ttt66print("Case 1: PickUp And Delivery of Single Task")67my_map, agent_loc,task_start, task_goal,a,t = read_input('./cases/test_1.txt')68print("Total Agents = {}".format(len(agent_loc)))69print("Total Tasks = {}".format(len(task_start)))70paths1,cost = min_cost_task_assn(agent_loc, task_start)71ttt=[]72for i in range(len(paths1)):73 ttt.append(paths1[i][-1])74cbs = CBSSolver(my_map, ttt, task_goal)75paths2 = cbs.find_solution(True, CBSSolver.NORMAL)76cost = get_sum_of_cost(paths2)77for i in range(len(paths2)):78 paths1[i]=paths1[i]+paths2[i]79print("***Test paths on a simulation***")80print('Tasks Completed')81animation = Animation(my_map, agent_loc, task_goal, paths1,task_start,task_goal)82animation.show()83print("Case 2: PickUp And Delivery Based on Weight of Task and Capacity of Agents")84my_map, agent_loc,task_start, task_goal,a,t = read_input('./cases/test_2.txt')85print("Total Agents = {}".format(len(agent_loc)))86print("Total Tasks = {}".format(len(task_start)))87prep_a=[]88for i in range(len(a)):89 prep_a.append((a[i],i))90prep_t=[]91for i in range(len(t)):92 prep_t.append((t[i],i))93heapq.heapify(prep_a)94heapq.heapify(prep_t)95fff,ggg,hhh=[],[],[]96aasn_task,rem_task=[],[]97for i in range(len(agent_loc)):98 zz=heapq.heappop(prep_a)99 yy=heapq.heappop(prep_t)100 if(zz[0]>=yy[0]):101 fff.append(agent_loc[zz[1]])102 ggg.append(task_start[yy[1]])103 hhh.append(task_goal[yy[1]])104 aasn_task.append(zz[1])105 else:106 break107for j in range(len(task_start)):108 if j not in aasn_task:109 rem_task.append(task_start[j])110print("Total Tasks Allocated Based on Agent Capacity= {}".format(len(fff)))111paths1,cost = min_cost_task_assn(fff, ggg)112cbs = CBSSolver(my_map, ggg, hhh)113paths2 = cbs.find_solution(True, CBSSolver.NORMAL)114cost = get_sum_of_cost(paths2)115for i in range(len(paths2)):116 paths1[i]=paths1[i]+paths2[i]117print("***Test paths on a simulation***")118print('Tasks Completed')119animation = Animation(my_map, fff, hhh, paths1,ggg,rem_task)120animation.show()121print("Case 3: PickUp And Delivery of Multiple Task")122my_map, agent_loc,task_start, task_goal,a,t = read_input('./cases/test_3.txt')123print("Total Agents = {}".format(len(agent_loc)))124print("Total Tasks = {}".format(len(task_start)))125cbs = CBSSolver(my_map, agent_loc, task_start[:len(agent_loc)])126paths1 = cbs.find_solution(True, CBSSolver.NORMAL)127cbs = CBSSolver(my_map, task_start[:len(agent_loc)], task_goal[:len(agent_loc)])128paths2 = cbs.find_solution(True, CBSSolver.NORMAL)129cost = get_sum_of_cost(paths2)130for i in range(len(paths2)):131 paths1[i]=paths1[i]+paths2[i]132time=len(task_start)//len(agent_loc)-1133temp=paths1134while(time>0):135 time-=1136 st=task_goal[:len(agent_loc)]137 tar=task_start[len(agent_loc):]138 cbs = CBSSolver(my_map, st, tar)139 paths1 = cbs.find_solution(True, CBSSolver.NORMAL)140 cbs = CBSSolver(my_map,task_start[len(agent_loc):],task_goal[len(agent_loc):])141 paths2 = cbs.find_solution(True, CBSSolver.NORMAL)142 cost = get_sum_of_cost(paths2)143 for i in range(len(paths2)):144 paths1[i]=paths1[i]+paths2[i] 145for i in range(len(paths1)):146 temp[i]=temp[i]+paths1[i]147print("***Test paths on a simulation***")148print('Tasks Completed')149animation = Animation(my_map, agent_loc, task_goal[len(agent_loc):], temp,task_start,task_goal[:len(agent_loc)])150animation.show()151print("Case 4: Miscellaneous Warehouse")152my_map, agent_loc,task_start, task_goal,a,t = read_input('./cases/misc.txt')153print("Total Agents = {}".format(len(agent_loc)))154print("Total Tasks = {}".format(len(task_start)))155paths1,cost = min_cost_task_assn(agent_loc, task_start)156ttt=[]157for i in range(len(paths1)):158 ttt.append(paths1[i][-1])159cbs = CBSSolver(my_map, ttt, task_goal)160paths2 = cbs.find_solution(True, CBSSolver.NORMAL)161cost = get_sum_of_cost(paths2)162for i in range(len(paths2)):163 paths1[i]=paths1[i]+paths2[i]164print("***Test paths on a simulation***")165print('Tasks Completed')166animation = Animation(my_map, agent_loc, task_goal, paths1,task_start,task_goal)167animation.show()168print("Case 5: Miscellaneous Warehouse 2 Using Prioritised")169my_map, agent_loc,task_start, task_goal,a,t = read_input('./cases/misc2.txt')170print("Total Agents = {}".format(len(agent_loc)))171print("Total Tasks = {}".format(len(task_start)))172solver = PrioritizedPlanningSolver(my_map, agent_loc, task_start)173paths1 = solver.find_solution()174solver = PrioritizedPlanningSolver(my_map, task_start, task_goal)175paths2= solver.find_solution()176for i in range(len(paths2)):177 paths1[i]=paths1[i]+paths2[i]178print("***Test paths on a simulation***")179print('Tasks Completed')180animation = Animation(my_map, agent_loc, task_goal, paths1,task_start,task_goal)...
run.py
Source:run.py
1import sys2from .mylib import *3from .settings import Settings4from .etcbc import Etcbc5from .laf import Laf6from .validate import Validate7from .transform import Transform8def init():9 global settings, val, et, lf, tr, prog_start, task_start10 settings = Settings()11 val = Validate(settings)12 et = Etcbc(settings)13 lf = Laf(settings, et, val)14 tr = Transform(settings, et, lf)15 prog_start = Timestamp()16 task_start = Timestamp()17def dotask(part): 18 print("INFO: Start Task {}".format(part))19 task_start = Timestamp()20 tr.transform(part)21 print("{} - {}".format(prog_start.elapsed(), task_start.elapsed()))22 print("INFO: End Task {}".format(part))23def final():24 task_start = Timestamp()25 lf.makeheaders()26 val.validate()27 val.report()28 lf.report()29 print("{} - {}".format(prog_start.elapsed(), task_start.elapsed()))30def processor():31 init()32 print("{} - {}".format(prog_start.elapsed(), task_start.elapsed()))33 print("INFO: Doing parts: {}".format(','.join(settings.given_parts)))34 for part in settings.given_parts: dotask(part)...
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