函数定义

75278350@qq.com

大神请帮忙看看，怎样设置才能让changes 正常输出？
import pandas as pd
import numpy as np
import matplotlib.pyplot as plt

# 已知信息
selling_price, variable_cost, fixed_cost, quantity = 10, 3, 70000, 30000

# 定义敏感度分析的百分比变动范围
percentage_changes = np.linspace(-20, 20, 100)

# 计算利润
def calculate_profit(price_change=0, cost_change=0, fixed_cost_change=0, quantity_change=0):
    changes = np.array([price_change, cost_change, fixed_cost_change, quantity_change])
    new_values = np.array([selling_price, variable_cost, fixed_cost, quantity]) * (1 + changes / 100)
    return (new_values[0] - new_values[1]) * new_values[3] - new_values[2]
print(changes)

75278350@qq.com

如何理解这段代码呢？

import numpy as np
import matplotlib.pyplot as plt

# 已知信息
selling_price, variable_cost, fixed_cost, quantity = 10, 3, 70000, 30000

# 定义敏感度分析的百分比变动范围
percentage_changes = np.linspace(-20, 20, 100)

# 计算利润
def calculate_profit(price_change=0, cost_change=0, fixed_cost_change=0, quantity_change=0):
    changes = np.array([price_change, cost_change, fixed_cost_change, quantity_change])
    new_values = np.array([selling_price, variable_cost, fixed_cost, quantity]) * (1 + changes / 100)
    return (new_values[0] - new_values[1]) * new_values[3] - new_values[2]

75278350@qq.com

这段代码能正常运动，并未向你说的有报错，请帮忙解释下每段代码的含义，谢谢
import numpy as np
import matplotlib.pyplot as plt

# 已知信息
selling_price, variable_cost, fixed_cost, quantity = 10, 3, 70000, 30000

# 定义敏感度分析的百分比变动范围
percentage_changes = np.linspace(-20, 20, 100)

# 计算利润
def calculate_profit(price_change=0, cost_change=0, fixed_cost_change=0, quantity_change=0):
    changes = np.array([price_change, cost_change, fixed_cost_change, quantity_change])
    new_values = np.array([selling_price, variable_cost, fixed_cost, quantity]) * (1 + changes / 100)
    return (new_values[0] - new_values[1]) * new_values[3] - new_values[2]

# 计算基础利润
base_profit = calculate_profit()

# 计算敏感系数
sensitivity_labels = ['单价', '单位变动成本', '固定成本', '销量']
sensitivity_results = [(calculate_profit(*[i == j for j in range(4)]) - base_profit) / base_profit * 100
                        for i in range(4)]
#显示中文
plt.rcParams["font.family"] = "sans-serif"
plt.rcParams["font.sans-serif"] = "SimHei"
plt.rcParams["axes.unicode_minus"] = False

# 绘制敏感度分析图
fig, ax = plt.subplots(figsize=(10, 6))

# 绘制直线并标注敏感系数数值
for i in range(4):
    slope = sensitivity_results[i]     # 敏感系数即为斜率
    line = slope * percentage_changes  # 因素不变时，利润不变，因此直线过原点，即截距为0
    ax.plot(percentage_changes, line, label=f'{sensitivity_labels[i]}敏感系数: {slope:.2f}')

# 设置图表标题和标签
ax.set_title('利润敏感性分析')
ax.set_xlabel('因素变动百分比')
ax.set_ylabel('利润变动百分比')

# 添加图例
ax.legend()
ax.grid(True)

# 显示图表
plt.show()

75278350@qq.com

FishC 发表于 2024-5-16 11:05
问题出在函数内部的变量定义和赋值上。在`calculate_profit`函数中，`changes`和`new_values`都是空数组， ...

按这条代码，显示错误

operands could not be broadcast together with shapes (4,) (100,)

如何改正？

75278350@qq.com

这条代码的结果是143000，是如何得来的呢？没有看到有0.1或者10%的比例参数呀？

import numpy as np
import matplotlib.pyplot as plt

# 已知信息
selling_price, variable_cost, fixed_cost, quantity = 10, 3, 70000, 30000

# 计算利润
def calculate_profit(price_change=0, cost_change=0, fixed_cost_change=0, quantity_change=0):
    changes = np.array([price_change, cost_change, fixed_cost_change, quantity_change])
    new_values = np.array([selling_price, variable_cost, fixed_cost, quantity]) * (1 + changes / 100)
    return (new_values[0] - new_values[1]) * new_values[3] - new_values[2]

# 计算基础利润
base_profit = calculate_profit()


# 计算敏感系数

sensitivity_results = [(calculate_profit(*[i == j for j in range(1)]) ) / 1 * 1
                        for i in range(1)]
sensitivity_results