我得到“數組必須都是相同的長度”。 有人可以幫我理解問題出在哪里以及如何解決嗎？

Question

我正在嘗試運行模擬並獲得利用率。

這是我的代碼。 plot 不幸地給出了錯誤，我不知道哪里出錯了。 有人可以解釋這意味着什么以及如何解決它嗎？

import gurobipy as gp
import numpy as np
import math
import seaborn as sn
import statistics as stat

roomPrice = 280
variablePrice = list(range(200, 350, 10))
dayAvailable = [1, 2, 3, 4, 5]
dayDemand = [[0], [1], [2], [3], [4], [0,1], [1,2], [2,3], [3,4], [0,1,2]]
customers = np.random.poisson(lam=250, size=1000)
customersDenied = []
utilization = []

def priceAccept(p): 
    value = 1/(1+math.exp(0.025*p-7.5))
    return value

for p in variablePrice: 
    bookings = 0 # to be able to calculate further, the bookings in this question cannot be a list and must be int
    for c in customers: # First we need to get customers booked or denied
        capacity = [50, 50, 50, 50, 50] # Allocate the max capacity per day
        customersHelped = 0 # Start the counting for customers that receive a booking
        deny = 0 # Start the counting for customer that are denied a booking
        probability = np.random.choice([0,1,2,3,4,5,6,7,8,9,], 
                                   size = c, 
                                   p = [0.15,0.05,0.1,
                                        0.05,0.1,0.2,
                                        0.1,0.1,0.05,0.1]) # The probability statistics for each (combination of) room
        for prob in probability: # We need to check whether max capacity has been reached
            capacityFull = 0 # variable for counting the bookings
            for i in dayDemand[prob]:
                if capacity[i] == 0:       # The next 3 lines indicate that capacity full and deny need to 
                    capacityFull += 1      # increase when capacity reaches 0. This is important for 
                    deny += 1              # the allocation of customers and the question later on.
            if capacityFull == 0: # If the room are empty
                priceAcceptCustomer = np.random.choice([1,0], size = 1, p=[priceAccept(roomPrice),1-priceAccept(roomPrice)])
                if priceAcceptCustomer == 1:
                    for d in dayDemand[prob]:
                        if capacity[d-1] > 0:
                            capacity[d-1] -= 1
                            customersHelped += 1
            bookings += customersHelped # bookings isnt appended but added to
        customersDenied.append(deny)
        utilization.append(bookings/1000/250*100)

plot = sn.lineplot(x = variablePrice,y = utilization)
plot.set(xlabel='Price per night', ylabel='Utilization [%]')

Answer 1

我沒有嘗試運行代碼，但這不是這一行的縮進錯誤嗎？

        utilization.append(bookings/1000/250*100)

我知道這應該只p in variablePrice發生一次，但您將它for c in customers 。

以下代碼適用於我：

import gurobipy as gp
import numpy as np
import math
import seaborn as sn
import statistics as stat
import tqdm

roomPrice = 280
variablePrice = list(range(200, 350, 10))
dayAvailable = [1, 2, 3, 4, 5]
dayDemand = [[0], [1], [2], [3], [4], [0,1], [1,2], [2,3], [3,4], [0,1,2]]
customers = np.random.poisson(lam=250, size=200)
customersDenied = []
utilization = []

def priceAccept(p): 
    value = 1/(1+math.exp(0.025*p-7.5))
    return value

p_pbar = tqdm.tqdm(variablePrice)
for p in p_pbar: 
    p_pbar.set_description(f"Processing p={p}")
    
    bookings = 0 # to be able to calculate further, the bookings in this question cannot be a list and must be int
    c_pbar = tqdm.tqdm(customers, leave=False)
    for c in c_pbar: # First we need to get customers booked or denied
        c_pbar.set_description(f"Processing c={c}")
        capacity = [50, 50, 50, 50, 50] # Allocate the max capacity per day
        customersHelped = 0 # Start the counting for customers that receive a booking
        deny = 0 # Start the counting for customer that are denied a booking
        probability = np.random.choice([0,1,2,3,4,5,6,7,8,9,], 
                                   size = c, 
                                   p = [0.15,0.05,0.1,
                                        0.05,0.1,0.2,
                                        0.1,0.1,0.05,0.1]) # The probability statistics for each (combination of) room
        for prob in probability: # We need to check whether max capacity has been reached
            capacityFull = 0 # variable for counting the bookings
            for i in dayDemand[prob]:
                if capacity[i] == 0:       # The next 3 lines indicate that capacity full and deny need to 
                    capacityFull += 1      # increase when capacity reaches 0. This is important for 
                    deny += 1              # the allocation of customers and the question later on.
            if capacityFull == 0: # If the room are empty
                priceAcceptCustomer = np.random.choice([1,0], size = 1, p=[priceAccept(roomPrice),1-priceAccept(roomPrice)])
                if priceAcceptCustomer == 1:
                    for d in dayDemand[prob]:
                        if capacity[d-1] > 0:
                            capacity[d-1] -= 1
                            customersHelped += 1
            bookings += customersHelped # bookings isnt appended but added to
        customersDenied.append(deny)
    utilization.append(bookings/1000/250*100)

plot = sn.lineplot(x = variablePrice,y = utilization)
plot.set(xlabel='Price per night', ylabel='Utilization [%]')

如您所見，我使用tqdm添加了一些進度條。 我推薦這個庫，它非常易於使用，並為您的腳本和工具帶來了不錯的優勢！