How to use summary_only method in prospector

Best Python code snippet using prospector_python

Problem.py

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1import csv2import os3import pandas as pd4import numpy as np5from Display import Display6# Function that can create random instances7def gen_instance(seed, num_s, num_d, num_c, num_p, T):8 np.random.seed(seed)9 n = num_s + num_d + num_c10 s_coordinates = (1 / 10) * np.random.randint(0, 10 * n, (num_s, 2))11 d_coordinates = (1 / 10) * np.random.randint(2.5 * n, 7.5 * n, (num_d, 2))12 c_coordinates = (1 / 10) * np.random.randint(0, 10 * n, (num_c, 2))13 # Sheet 1 - Suppliers14 supplier_data = pd.DataFrame(index=['S' + str(i + 1) for i in range(num_s)],15 columns=['LocationX', 'LocationY'])16 supplier_data.index.name = 'SupplierID'17 for i in range(num_s):18 supplier_data.loc['S' + str(i + 1), :] = [s_coordinates[i][0], s_coordinates[i][1]]19 print(supplier_data)20 # Sheet 2 - Depots21 depot_data = pd.DataFrame(index=['D' + str(i + 1) for i in range(num_d)],22 columns=['LocationX', 'LocationY', 'Capacity', 'Holding Cost'])23 depot_data.index.name = 'DepotID'24 for i in range(num_d):25 capacity = round(7 + 20 * np.random.random(), 2)26 holding_cost = round(0.3 + 0.3 * np.random.random(), 2)27 depot_data.loc['D' + str(i + 1), :] = [d_coordinates[i][0], d_coordinates[i][1],28 capacity, holding_cost]29 print(depot_data)30 # Sheet 3 - Customers31 customer_data = pd.DataFrame(index=['C' + str(i + 1) for i in range(num_c)],32 columns=['LocationX', 'LocationY'])33 customer_data.index.name = 'CustomerID'34 for i in range(num_c):35 customer_data.loc['C' + str(i + 1), :] = [c_coordinates[i][0], c_coordinates[i][1]]36 print(customer_data)37 # Sheet 4 - Products38 product_data = pd.DataFrame(index=['P' + str(i + 1) for i in range(num_p)],39 columns=['Size'])40 product_data.index.name = 'ProductID'41 for i in range(num_p):42 product_data.loc['P' + str(i + 1), :] = round(0.2 + 0.8 * np.random.random(), 2)43 print(product_data)44 # Sheet 5 - Links45 origins = ['S' + str(i + 1) for i in range(num_s)] + ['D' + str(i + 1) for i in range(num_d)]46 destinations = ['D' + str(i + 1) for i in range(num_d)] + ['C' + str(i + 1) for i in range(num_c)]47 links = [(i, j) for i in origins for j in destinations if i != j]48 link_data = pd.DataFrame(index=pd.MultiIndex.from_tuples(links),49 columns=['Opening Cost', 'Capacity Cost', 'Duration'])50 link_data.index.names = ['Origin', 'Destination']51 # Determine all distances52 locations = pd.concat([supplier_data.iloc[:, :3].rename(columns={'SupplierID': 'Location'}),53 depot_data.iloc[:, :3].rename(columns={'DepotID': 'Location'}),54 customer_data.iloc[:, :3].rename(columns={'CustomerID': 'Location'})])55 distance = {a: np.hypot(locations.loc[a[0]]['LocationX'] - locations.loc[a[1]]['LocationX'],56 locations.loc[a[0]]['LocationY'] - locations.loc[a[1]]['LocationY']) for a in links}57 bins = [np.quantile(list(distance.values()), q) for q in [0.25, 0.5, 0.75]]58 durations = np.digitize(list(distance.values()), bins)59 link_index = 060 for i in origins:61 for j in destinations:62 if i != j:63 opening_cost = round(50 + 100 * np.random.random(), 2)64 capacity_cost = round(5 + 10 * np.random.random(), 2)65 link_data.loc[i, j] = [opening_cost, capacity_cost, durations[link_index] + 1]66 link_index += 167 print(link_data)68 # Sheet 6 - Demand69 demand_data = pd.DataFrame(index=pd.MultiIndex.from_product([['C' + str(i + 1) for i in range(num_c)],70 ['P' + str(j + 1) for j in range(num_p)],71 ['T' + str(t) for t in range(5, T + 1)]], ),72 columns=['Amount'])73 demand_data.index.names = ['Customer', 'Product', 'Time']74 for i in range(1, num_c + 1):75 for j in range(1, num_p + 1):76 for t in range(5, T + 1):77 if np.random.random() > 0.7:78 demand_data.loc['C' + str(i), 'P' + str(j), 'T' + str(t)] = round(18 * np.random.random(), 2)79 else:80 demand_data.loc['C' + str(i), 'P' + str(j), 'T' + str(t)] = 081 print(demand_data)82 # Sheet 7 - Backlogs83 backlog_data = pd.DataFrame(index=pd.MultiIndex.from_product([['C' + str(i + 1) for i in range(num_c)],84 ['P' + str(j + 1) for j in range(num_p)]]),85 columns=['Amount'])86 backlog_data.index.names = ['Customer', 'Product']87 for i in range(num_c):88 for j in range(num_p):89 backlog_data.loc['C' + str(i + 1), 'P' + str(j + 1)] = round(7 + 10 * np.random.random(), 2)90 print(backlog_data)91 # Sheet 8 - Production92 production_data = pd.DataFrame(index=pd.MultiIndex.from_product([['S' + str(i + 1) for i in range(num_s)],93 ['P' + str(j + 1) for j in range(num_p)]]),94 columns=['Minimum', 'Maximum'])95 production_data.index.names = ['Supplier', 'Product']96 for i in range(num_s):97 for j in range(num_p):98 if np.random.random() <= 0.8:99 min_production = round(7 + 10 * np.random.random(), 2)100 max_production = round(min_production + 5 + 5 * np.random.random(), 2)101 else:102 min_production = 0103 max_production = 0104 production_data.loc['S' + str(i + 1), 'P' + str(j + 1)] = [min_production, max_production]105 print(production_data)106 # Sheet 9 - Parameters107 parameter_data = pd.DataFrame(index=['Truck Size', 'Start Time Horizon', 'End Time Horizon'],108 columns=['Value'])109 parameter_data.index.name = 'Parameter'110 parameter_data.loc['Truck Size', :] = round(1 + 2 * np.random.random(), 2)111 parameter_data.loc['Start Time Horizon', :] = 'T1'112 parameter_data.loc['End Time Horizon', :] = 'T' + str(T)113 print(parameter_data)114 with pd.ExcelWriter('Instances/' + str(seed) + '.xlsx') as writer:115 supplier_data.to_excel(writer, sheet_name='Suppliers', merge_cells=False)116 depot_data.to_excel(writer, sheet_name='Depots', merge_cells=False)117 customer_data.to_excel(writer, sheet_name='Customers', merge_cells=False)118 product_data.to_excel(writer, sheet_name='Products', merge_cells=False)119 link_data.to_excel(writer, sheet_name='Links', merge_cells=False)120 demand_data.to_excel(writer, sheet_name='Demand', merge_cells=False)121 backlog_data.to_excel(writer, sheet_name='Backlog Penalty', merge_cells=False)122 production_data.to_excel(writer, sheet_name='Production', merge_cells=False)123 parameter_data.to_excel(writer, sheet_name='Parameters', merge_cells=False)124class Problem:125 def __init__(self, instance_name, random=False, seed=None, extra_time_periods=False):126 # Retrieve instance file from Instances directory127 self.instance_name = instance_name128 self.random = random129 if seed:130 np.random.seed(seed)131 cwd = os.getcwd()132 filename = os.path.join(cwd, 'Instances/' + instance_name + '.xlsx')133 data = pd.read_excel(filename, sheet_name=None, engine='openpyxl')134 # Data extraction135 # --------------------------------------------------------------------------------------136 supplier_data = data['Suppliers']137 depot_data = data['Depots']138 customer_data = data['Customers']139 product_data = data['Products']140 link_data = data['Links']141 demand_data = data['Demand']142 backlog_data = data['Backlog Penalty']143 production_data = data['Production']144 parameter_data = data['Parameters']145 self.truck_size = data['Parameters']['Value'][0]146 # Object- and index sets147 # --------------------------------------------------------------------------------------148 # Object sets149 self.S = supplier_data['SupplierID'].to_list()150 self.D = depot_data['DepotID'].to_list()151 self.C = customer_data['CustomerID'].to_list()152 self.S_and_D = self.S + self.D153 self.D_and_C = self.D + self.C154 self.P = product_data['ProductID'].to_list()155 self.start = int(parameter_data['Value'][1].replace('T', ''))156 self.end = int(parameter_data['Value'][2].replace('T', ''))157 if extra_time_periods:158 self.end = round(self.end * 1.1)159 self.T = [t for t in range(self.start, self.end + 1, 1)]160 self.links = [(link_data['Origin'][i], link_data['Destination'][i]) for i in range(len(link_data))]161 # Index sets162 self.customer_product = [(backlog_data['Customer'][i], backlog_data['Product'][i]) for i in163 range(len(backlog_data))]164 self.supplier_product = [(production_data['Supplier'][i], production_data['Product'][i])165 for i in range(len(production_data))]166 self.demand_set = [(demand_data['Customer'][i], demand_data['Product'][i],167 int(demand_data['Time'][i].replace('T', ''))) for i in range(len(demand_data))]168 self.link_product_time = []169 for a in self.links:170 for p in self.P:171 for t in self.T:172 self.link_product_time.append((a[0], a[1], p, t))173 self.link_time = []174 for a in self.links:175 for t in self.T:176 self.link_time.append((a[0], a[1], t))177 self.supplier_product_time = []178 for s in self.S:179 for p in self.P:180 for t in self.T:181 self.supplier_product_time.append((s, p, t))182 self.depot_time = []183 for d in self.D:184 for t in self.T:185 self.depot_time.append((d, t))186 self.depot_product_time = []187 for d in self.D:188 for p in self.P:189 for t in self.T:190 self.depot_product_time.append((d, p, t))191 self.customer_product_time = []192 for c in self.C:193 for p in self.P:194 for t in self.T:195 self.customer_product_time.append((c, p, t))196 self.dc_product_time = []197 for i in self.D_and_C:198 for p in self.P:199 for t in [0] + self.T:200 self.dc_product_time.append((i, p, t))201 # Parameter/data sets202 # --------------------------------------------------------------------------------------203 self.holding_cost = {self.D[i]: depot_data['Holding Cost'][i] for i in range(len(self.D))}204 self.capacity = {self.D[i]: depot_data['Capacity'][i] for i in range(len(self.D))}205 self.product_volume = {self.P[i]: product_data['Size'][i] for i in range(len(self.P))}206 self.opening_cost = {self.links[i]: link_data['Opening Cost'][i] for i in range(len(link_data))}207 self.capacity_cost = {self.links[i]: link_data['Capacity Cost'][i] for i in range(len(link_data))}208 self.duration = {self.links[i]: link_data['Duration'][i] for i in range(len(link_data))}209 self.locations = pd.concat([supplier_data.iloc[:, :3].rename(columns={'SupplierID': 'Location'}),210 depot_data.iloc[:, :3].rename(columns={'DepotID': 'Location'}),211 customer_data.iloc[:, :3].rename(columns={'CustomerID': 'Location'})])212 self.locations.set_index([self.locations['Location']], inplace=True)213 self.distance = {a: np.hypot(self.locations.loc[a[0]]['LocationX'] - self.locations.loc[a[1]]['LocationX'],214 self.locations.loc[a[0]]['LocationY'] - self.locations.loc[a[1]]['LocationY']) for215 a in216 self.links}217 if not random:218 self.demand = {self.demand_set[i]: demand_data['Amount'][i] for i in range(len(demand_data))}219 self.cum_demand = {(c, p, t): sum(self.demand[c, p, f] for f in range(self.start, t + 1)220 if (c, p, f) in self.demand_set) for (c, p, t) in221 self.customer_product_time}222 else:223 self.demand_mean = {self.demand_set[i]: demand_data['Expected Amount'][i] for i in range(len(demand_data))}224 self.demand_dev = {self.demand_set[i]: demand_data['Standard Deviation'][i] for i in225 range(len(demand_data))}226 self.backlog_pen = {self.customer_product[i]: backlog_data['Amount'][i] for i in227 range(len(backlog_data))}228 self.min_prod = {(s, p): 0 for s in self.S for p in self.P}229 self.max_prod = {(s, p): 0 for s in self.S for p in self.P}230 for i in range(len(production_data)):231 self.min_prod[self.supplier_product[i]] = production_data['Minimum'][i]232 self.max_prod[self.supplier_product[i]] = production_data['Maximum'][i]233 if random:234 self.supplier_availability = {self.supplier_product[i]: production_data['Availability rate'][i]235 for i in range(len(self.supplier_product))}236 self.solution = {}237 self.objective = np.inf238 if random:239 self.scenarios = []240 # Function that updates this problem object's solution based on a solution file241 def read_solution(self, instance_name):242 self.solution = {'x': {(i, j, p, str(t)): 0 for (i, j, p, t) in self.link_product_time},243 'l': {(i, j): 0 for (i, j) in self.links},244 'v': {(i, j): 0 for (i, j) in self.links},245 'k': {(i, j, str(t)): 0 for (i, j, t) in self.link_time},246 'r': {(s, p, str(t)): 0 for (s, p, t) in self.supplier_product_time},247 'I': {(i, p, str(t)): 0 for (i, p, t) in self.dc_product_time}}248 # Read solution249 with open('Solutions/' + instance_name + '.sol', newline='\n') as file:250 reader = csv.reader((line.replace(' ', ' ') for line in file), delimiter=' ')251 header = next(reader) # Skip header252 self.objective = header[-1]253 for var, value in reader:254 name = tuple(var[2:-1].split(','))255 if var[0] not in self.solution.keys():256 self.solution[var[0]] = {}257 self.solution[var[0]][name] = float(value)258 def generate_scenarios(self, N):259 self.scenarios = []260 for i in range(N):261 availability = {(s, p, t): np.random.binomial(n=1, p=self.supplier_availability[s, p])262 for s, p, t in self.supplier_product_time if (s, p) in self.supplier_product}263 demand = {(c, p, t): np.random.normal(loc=self.demand_mean[c, p, t], scale=self.demand_dev[c, p, t])264 for c, p, t in self.demand_set}265 cum_demand = {(c, p, t): sum([demand[c, p, f] for f in range(t) if (c, p, f) in self.demand_set])266 for c, p, t in self.customer_product_time}267 self.scenarios.append({268 'availability': availability,269 'demand': demand,270 'cum_demand': cum_demand271 })272 def compute_objective(self):273 # Opening + capacity costs274 tot_opening_costs = 0275 tot_capacity_costs = 0276 for link in self.links:277 if self.solution['v'][link] > 0:278 extra_opening_cost = self.opening_cost[link]279 tot_opening_costs += extra_opening_cost280 extra_capacity_cost = self.capacity_cost[link] * self.solution['v'][link]281 tot_capacity_costs += extra_capacity_cost282 if not self.random:283 # Distance costs284 tot_distance_costs = 0285 for link in self.links:286 if self.solution['v'][link] > 0:287 total_trucks_sent = sum([self.solution['k'][link + (str(t),)] for t in self.T])288 extra_distance_cost = total_trucks_sent * self.distance[link]289 tot_distance_costs += extra_distance_cost290 # Holding costs291 tot_holding_costs = 0292 for d in self.D:293 for p in self.P:294 extra_holding_cost = self.holding_cost[d] * sum([self.solution['I'][d, p, str(t)]295 * self.product_volume[p] for t in self.T])296 tot_holding_costs += extra_holding_cost297 # Backlog costs298 tot_backlog_costs = 0299 for c, p, t in self.customer_product_time:300 extra_backlog = self.backlog_pen[c, p] * (301 self.solution['I'][c, p, str(t)] - self.cum_demand[c, p, t]) ** 2302 tot_backlog_costs += extra_backlog303 return tot_opening_costs + tot_capacity_costs + tot_distance_costs + tot_holding_costs + tot_backlog_costs304 else:305 tot_distance_costs = 0306 tot_holding_costs = 0307 tot_backlog_costs = 0308 N = len(self.scenarios)309 for theta in range(N):310 # Distance costs311 for (i, j) in self.links:312 if self.solution['v'][i, j] > 0:313 total_trucks_sent = sum([self.solution['k'][i, j, str(t), str(theta)] for t in self.T])314 extra_distance_cost = total_trucks_sent * self.distance[i, j]315 tot_distance_costs += extra_distance_cost316 # Holding costs317 for d in self.D:318 for p in self.P:319 extra_holding_cost = self.holding_cost[d] * sum([self.solution['I'][d, p, str(t), str(theta)]320 * self.product_volume[p] for t in self.T])321 tot_holding_costs += extra_holding_cost322 # Backlog costs323 for c, p, t in self.customer_product_time:324 extra_backlog = self.backlog_pen[c, p] * abs((self.solution['I'][c, p, str(t), str(theta)]325 - self.scenarios[theta]['cum_demand'][c, p, t]))326 tot_backlog_costs += extra_backlog327 tot_objective = tot_opening_costs + tot_capacity_costs + \328 (1 / N) * (tot_distance_costs + tot_holding_costs + tot_backlog_costs)329 return tot_objective330 # Log the amount of trucks sent over each link at each point in time331 def log_k(self):332 k = {}333 for (i, j) in self.links:334 if self.solution['l'][i, j] == 1:335 k[i, j] = [round(self.solution['k'][i, j, str(t)]) for t in self.T]336 print()337 print('Amount of trucks sent over each link at each point in time:')338 print('-' * 70)339 for link, trucks in k.items():340 print(link, trucks)341 # Function that outputs the buildup of different cost types342 def log_objective(self, summary_only=False):343 print()344 print('Objective overview:')345 print('-' * 70)346 # Opening costs347 tot_opening_costs = 0348 for link in self.links:349 if link in self.solution['l'].keys():350 if self.solution['l'][link] == 1:351 extra_opening_cost = self.opening_cost[link]352 if not summary_only:353 print(link, '| Cost:', extra_opening_cost)354 tot_opening_costs += extra_opening_cost355 if not summary_only:356 print('Total opening costs:', round(tot_opening_costs, 2))357 print('-' * 70)358 # Capacity costs359 tot_capacity_costs = 0360 for link in self.links:361 if link in self.solution['v'].keys():362 if self.solution['v'][link] > 0:363 extra_capacity_cost = self.capacity_cost[link] * self.solution['v'][link]364 if not summary_only:365 print(link, '| Amount: ', round(self.solution['v'][link], 2), '| Cost per:',366 self.capacity_cost[link], '| Total cost:', round(extra_capacity_cost, 2))367 tot_capacity_costs += extra_capacity_cost368 if not summary_only:369 print('Total capacity costs:', round(tot_capacity_costs, 2))370 print('-' * 70)371 if not self.random:372 # Distance costs373 tot_distance_costs = 0374 for link in self.links:375 if link in self.solution['v'].keys():376 if self.solution['v'][link] > 0:377 total_trucks_sent = sum([self.solution['k'][link + (str(t),)] for t in self.T])378 extra_distance_cost = total_trucks_sent * self.distance[link]379 if not summary_only:380 print(link, '| Total trucks sent on link: ', round(total_trucks_sent),381 '| Cost per:', round(self.distance[link], 2), '| Total cost:',382 round(extra_distance_cost, 2))383 tot_distance_costs += extra_distance_cost384 if not summary_only:385 print('Total distance costs:', round(tot_distance_costs, 2))386 print('-' * 70)387 # Holding costs388 tot_holding_costs = 0389 for d in self.D:390 if not summary_only:391 print(d, '| Holding costs:', self.holding_cost[d], 'Capacity:', self.capacity[d])392 for p in self.P:393 if not summary_only:394 print(d, p, '| Inventory:', [round(self.solution['I'][d, p, str(t)] * self.product_volume[p], 2)395 for t in self.T])396 extra_holding_cost = self.holding_cost[d] * sum([self.solution['I'][d, p, str(t)]397 * self.product_volume[p] for t in self.T])398 if not summary_only:399 print(d, p, '| Total inventory:', round(sum([round(self.solution['I'][d, p, str(t)]400 * self.product_volume[p], 2)401 for t in self.T]), 2),402 '| Total cost:', round(extra_holding_cost, 2))403 tot_holding_costs += extra_holding_cost404 if not summary_only:405 print('Total holding costs:', round(tot_holding_costs, 2))406 print('-' * 70)407 # Backlog costs408 tot_backlog_costs = 0409 cum_demand = self.cum_demand if not self.random else self.scenarios[0]['cum_demand']410 for c in self.C:411 customer_backlog = 0412 if not summary_only:413 print(c, '|')414 print('-' * 70)415 for p in self.P:416 if not summary_only:417 print(c, p, '|', [round(cum_demand[c, p, t], 2) for t in self.T],418 '- Cumulative demand over time')419 print(c, p, '|', [round(self.solution['I'][c, p, str(t)], 2) for t in self.T],420 '- Total delivered over time')421 product_backlog = 0422 for t in self.T:423 product_backlog += self.backlog_pen[c, p] * ((self.solution['I'][c, p, str(t)]424 - cum_demand[c, p, t]) ** 2)425 customer_backlog += product_backlog426 if not summary_only:427 print(c, p, '| Product backlog costs:', product_backlog)428 print('-' * 70)429 if not summary_only:430 print(c, '| Customer backlog costs:', round(customer_backlog, 2))431 print('-' * 70)432 for c, p, t in self.customer_product_time:433 extra_backlog = self.backlog_pen[c, p] * (self.solution['I'][c, p, str(t)] - cum_demand[c, p, t]) ** 2434 tot_backlog_costs += extra_backlog435 if not summary_only:436 print('Total backlog costs:', round(tot_backlog_costs, 2))437 print('-' * 70)438 tot_objective = tot_opening_costs + tot_capacity_costs + tot_distance_costs \439 + tot_holding_costs + tot_backlog_costs440 else:441 tot_distance_costs = 0442 tot_holding_costs = 0443 tot_backlog_costs = 0444 N = len(self.scenarios)445 for theta in range(N):446 if not summary_only:447 print('SCENARIO', theta)448 print('-' * 70)449 # Distance costs450 tot_distance_costs = 0451 for (i, j) in self.links:452 if (i, j) in self.solution['v'].keys():453 if self.solution['v'][i, j] > 0:454 total_trucks_sent = sum([self.solution['k'][i, j, str(t), str(theta)] for t in self.T])455 extra_distance_cost = total_trucks_sent * self.distance[i, j]456 if not summary_only:457 print(i, j, '| Total trucks sent on link: ', round(total_trucks_sent),458 '| Cost per:', round(self.distance[i, j], 2), '| Total cost:',459 round(extra_distance_cost, 2))460 tot_distance_costs += extra_distance_cost / N461 if not summary_only:462 print('Total distance costs:', round(tot_distance_costs, 2))463 print('-' * 70)464 # Holding costs465 for d in self.D:466 if not summary_only:467 print(d, '| Holding costs:', self.holding_cost[d], 'Capacity:', self.capacity[d])468 for p in self.P:469 if not summary_only:470 print(d, p, '| Inventory:',471 [round(self.solution['I'][d, p, str(t), str(theta)] * self.product_volume[p], 2)472 for t in self.T])473 extra_holding_cost = self.holding_cost[d] * sum([self.solution['I'][d, p, str(t), str(theta)]474 * self.product_volume[p] for t in self.T])475 if not summary_only:476 print(d, p, '| Total inventory:',477 round(sum([round(self.solution['I'][d, p, str(t), str(theta)]478 * self.product_volume[p], 2)479 for t in self.T]), 2),480 '| Total cost:', round(extra_holding_cost, 2))481 tot_holding_costs += extra_holding_cost / N482 if not summary_only:483 print('Total holding costs:', round(tot_holding_costs, 2))484 print('-' * 70)485 # Backlog costs486 cum_demand = self.scenarios[theta]['cum_demand']487 for c in self.C:488 customer_backlog = 0489 if not summary_only:490 print(c, '|')491 print('-' * 70)492 for p in self.P:493 if not summary_only:494 print(c, p, '|', [round(cum_demand[c, p, t], 2) for t in self.T],495 '- Cumulative demand over time')496 print(c, p, '|', [round(self.solution['I'][c, p, str(t), str(theta)], 2) for t in self.T],497 '- Total delivered over time')498 product_backlog = 0499 for t in self.T:500 product_backlog += self.backlog_pen[c, p] * abs(self.solution['I'][c, p, str(t), str(theta)]501 - cum_demand[c, p, t])502 customer_backlog += product_backlog503 if not summary_only:504 print(c, p, '| Product backlog costs:', product_backlog)505 print('-' * 70)506 if not summary_only:507 print(c, '| Customer backlog costs:', round(customer_backlog, 2))508 print('-' * 70)509 for c, p, t in self.customer_product_time:510 extra_backlog = self.backlog_pen[c, p] * abs(511 self.solution['I'][c, p, str(t), str(theta)] - cum_demand[c, p, t])512 tot_backlog_costs += extra_backlog / N513 if not summary_only:514 print('Total backlog costs:', round(tot_backlog_costs, 2))515 print('-' * 70)516 tot_objective = tot_opening_costs + tot_capacity_costs + tot_distance_costs + tot_holding_costs + tot_backlog_costs517 print('Total opening costs |', round(tot_opening_costs, 2))518 print('Total capacity costs |', round(tot_capacity_costs, 2))519 print('Total distance costs |', round(tot_distance_costs, 2))520 print('Total holding costs |', round(tot_holding_costs, 2))521 print('Total backlog costs |', round(tot_backlog_costs, 2))522 print('-' * 70)523 print('Total costs |', round(tot_objective, 2))524 print('-' * 70)525 return {526 'backlog': tot_backlog_costs,527 'total': tot_objective528 }529 def log_production(self):530 if not self.random:531 for s in self.S:532 print(s, '|')533 print('-' * 70)534 for p in self.P:535 production = [round(sum(self.solution['x'][s, j, p, str(t)] for j in self.D_and_C), 2) for t in536 self.T]537 print(p, '|', production)538 print('-' * 70)539 else:540 for theta in range(len(self.scenarios)):541 for s in self.S:542 print(s, '|')543 print('-' * 70)544 for p in self.P:545 production = [round(sum(self.solution['x'][s, j, p, str(t), str(theta)]546 for j in self.D_and_C if (s, j, p, str(t), str(theta))547 in self.solution['x'].keys()), 2) for t in self.T]548 print(p, '|', production)549 print('-' * 70)550 def verify_constraints(self):551 # 1 - Link opening constraint552 for link in self.links:553 assert self.solution['l'][link] * 10000 >= self.solution['v'][link], 'Constraint 1 violation'554 # 2 - Link capacity constraint555 for link in self.links:556 for t in self.T:557 t = str(t)558 assert round(self.solution['k'][link[0], link[1], t]) <= round(self.solution['v'][link])559 # 3 - Required trucks constraint560 for i, j in self.links:561 for t in self.T:562 t = str(t)563 volume = sum([self.product_volume[p] * self.solution['x'][i, j, p, t] for p in self.P])564 assert self.solution['k'][i, j, t] >= round(volume / self.truck_size)565 # 4 - Min production constraint566 for s, p, t in self.supplier_product_time:567 t = str(t)568 production = sum([self.solution['x'][s, j, p, t] for j in self.D_and_C])569 assert round(production, 2) >= self.min_prod[s, p] * self.solution['r'][s, p, t]570 # 5 - Max production constraint571 for s, p, t in self.supplier_product_time:572 t = str(t)573 production = sum([self.solution['x'][s, j, p, t] for j in self.D_and_C])574 assert round(production, 2) <= self.max_prod[s, p] * self.solution['r'][s, p, t]575 # 6 - Depot outflow constraint576 for d, p, t in self.depot_product_time:577 outflow = sum([self.solution['x'][d, j, p, str(t)] for j in self.D_and_C if (d, j) in self.links])578 inflow = sum([self.solution['x'][j, d, p, str(t - self.duration[j, d])] for j in self.S_and_D579 if (j, d) in self.links and t - self.duration[j, d] >= self.start])580 assert round(outflow, 2) <= round(self.solution['I'][d, p, str(t - 1)] + inflow, 2) + 0.01581 # 7 - Depot capacity constraint582 for d in self.D:583 for t in self.T:584 t = str(t)585 volume = sum([self.product_volume[p] * self.solution['I'][d, p, t] for p in self.P])586 assert volume <= self.capacity[d]587 # 8 - Flow constraints588 for i, p, t in self.dc_product_time:589 if t > 0:590 outflow = sum([self.solution['x'][i, j, p, str(t)] for j in self.D_and_C if (i, j) in self.links])591 inflow = sum([self.solution['x'][j, i, p, str(t - self.duration[j, i])] for j in self.S_and_D592 if (j, i) in self.links and t - self.duration[j, i] >= self.start])593 assert round(self.solution['I'][i, p, str(t)], 4) - round(self.solution['I'][i, p, str(t - 1)] + inflow594 - outflow, 4) <= 0.0001595 # 9 - Inventories start at 0596 for i in self.D_and_C:597 for p in self.P:598 assert self.solution['I'][i, p, '0'] == 0599 # 10 - Total inventories must match cumulative demand600 for c in self.C:601 for p in self.P:602 assert round(self.solution['I'][c, p, str(self.end)], 5) == round(self.cum_demand[c, p, self.end], 5)603 print('Constraints succesfully verified.')604 return605 # Call display on this problem's solution showing only opened links and their capacities606 def display(self, integer=False):607 disp = Display(self)608 disp.draw(0, {'show_capacities': True, 'show_trucks': False, 'show_transport': False, 'show_inventory': False,...

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html.py

Source:html.py Github

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1import re2from .basic import BasicReport3class HtmlReport(BasicReport):4 templates = {5 'MAIN': '''6<!doctype html>7<html lang="en">8 <head>9 <meta charset="utf-8">10 <title>Python Environment Report</title>11 <meta name="generator" content="{analyzer}">12 <meta name="viewport" content="width=device-width, initial-scale=1">13 </head>14 <body>15 <h1>Python Environment Report</h1>16 <h2>Environment</h2>17 <ul>18 <li>Python: {python_version}</li>19 <li>Runtime: {runtime} {runtime_version}</li>20 <li>Platform: {platform}</li>21 <li>Pip: {pip_version}</li>22 <li>Location: {base_directory}</li>23 </ul>24 <h2>Summary</h2>25 <ul>26 <li>Total: {packages|len}</li>27 <li><span title="Installed packages that have newer versions available.">Outdated:</span> {?outdated}{outdated|len}28 {?outdated}29 <ul>30 {#outdated}31 <li>{?summary_only}{.}{:else}<a href="#{.}">{.}</a>{/summary_only}</li>32 {/outdated}33 </ul>34 {/outdated}{:else}0{/outdated}35 </li>36 <li><span title="Installed packages that have known vulnerabilities.">Vulnerable:</span> {?vulnerable}{vulnerable|len}37 {?vulnerable}38 <ul>39 {#vulnerable}40 <li>{?summary_only}{.}{:else}<a href="#{.}">{.}</a>{/summary_only}</li>41 {/vulnerable}42 </ul>43 {/vulnerable}{:else}0{/vulnerable}44 </li>45 <li><span title="Required packages that are not currently installed.">Missing:</span> {?missing}{missing|len}46 {?missing}47 <ul>48 {#missing}49 <li>{.}</li>50 {/missing}51 </ul>52 {/missing}{:else}0{/missing}53 </li>54 <li><span title="Installed packages whose version conflicts with another package's requirements.">Invalid:</span> {?invalid}{invalid|len}55 {?invalid}56 <ul>57 {#invalid}58 <li>{?summary_only}{.}{:else}<a href="#{.}">{.}</a>{/summary_only}</li>59 {/invalid}60 </ul>61 {/invalid}{:else}0{/invalid}62 </li>63 </ul>64 {?summary_only}{:else}65 {?problems_only}66 <h2>Problematic Packages</h2>67 <ul>68 {#problem_packages}{>PACKAGE/}{/problem_packages}69 </ul>70 {:else}71 <h2>Packages</h2>72 <ul>73 {#packages}{>PACKAGE/}{/packages}74 </ul>75 {/problems_only}76 {/summary_only}77 <p>Generated by <code><a href="{envrpt_home_page}">{analyzer}</a></code> on {date_analyzed|date} at {date_analyzed|time}</p>78 </body>79</html>''', # noqa80 'PACKAGE': '''81<li id="{key}"><strong>{?home_page}<a href="{home_page}">{name}</a>{:else}{name}{/home_page}</strong>82<ul>83 {?description}<li>{description}</li>{/description}84 <li>Version: {version}</li>85 <li>License: {?license}{license}{:else}Unknown{/license}</li>86{?issues}87 <li>Issues:88 <ul>89 {#issues}90 <li>{@eq key=type value="OUTDATED"}Package is outdated; <strong>{latest_version}</strong> is available{/eq}{@eq key=type value="REQ_MISSING"}Dependency <strong>{key}</strong> is missing{/eq}{@eq key=type value="REQ_INVALID"}Dependency <strong>{?summary_only}{key}{:else}<a href="#{key}">{key}</a>{/summary_only}</strong> is invalid; require <strong>{requirement}</strong> but <strong>{installed}</strong> is installed{/eq}{@eq key=type value="VULNERABLE"}Package has a known vulnerability: {id}: {description}{/eq}</li>91 {/issues}92 </ul>93 </li>94{/issues}95{?dependencies}96 <li><span title="Other packages that are required by this package.">Dependencies:</span>97 <ul>98 {#dependencies}99 <li>{?installed}<a href="#{key}">{key}</a>{:else}{key}{/installed}{?spec} ({spec}){/spec}</li>100 {/dependencies}101 </ul>102 </li>103{/dependencies}104{?dependents}105 <li><span title="Other packages that depend on this package.">Dependents:</span>106 <ul>107 {#dependents}108 <li><a href="#{key}">{key}</a></li>109 {/dependents}110 </ul>111 </li>112{/dependents}113</ul>114''', # noqa115 }116def create(environment, options):117 rpt = HtmlReport().create(environment, options)...

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bgp_route_aggregation.py

Source:bgp_route_aggregation.py Github

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...36 if summary_only is not None:37 self.summary_only = summary_only38 self.prefix = prefix39 @property40 def summary_only(self):41 """Gets the summary_only of this BgpRouteAggregation. # noqa: E50142 Flag to send only summarized route # noqa: E50143 :return: The summary_only of this BgpRouteAggregation. # noqa: E50144 :rtype: bool45 """46 return self._summary_only47 @summary_only.setter48 def summary_only(self, summary_only):49 """Sets the summary_only of this BgpRouteAggregation.50 Flag to send only summarized route # noqa: E50151 :param summary_only: The summary_only of this BgpRouteAggregation. # noqa: E50152 :type: bool53 """54 self._summary_only = summary_only55 @property56 def prefix(self):57 """Gets the prefix of this BgpRouteAggregation. # noqa: E50158 cidr of the aggregate address # noqa: E50159 :return: The prefix of this BgpRouteAggregation. # noqa: E50160 :rtype: str61 """62 return self._prefix...

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