first commit

.idea/.gitignore

@@ -0,0 +1,3 @@
+# Default ignored files
+/shelf/
+/workspace.xml

.idea/hire.iml

@@ -0,0 +1,10 @@
+<?xml version="1.0" encoding="UTF-8"?>
+<module type="PYTHON_MODULE" version="4">
+  <component name="NewModuleRootManager">
+    <content url="file://$MODULE_DIR$">
+      <excludeFolder url="file://$MODULE_DIR$/venv" />
+    </content>
+    <orderEntry type="inheritedJdk" />
+    <orderEntry type="sourceFolder" forTests="false" />
+  </component>
+</module>

.idea/inspectionProfiles/profiles_settings.xml

@@ -0,0 +1,6 @@
+<component name="InspectionProjectProfileManager">
+  <settings>
+    <option name="USE_PROJECT_PROFILE" value="false" />
+    <version value="1.0" />
+  </settings>
+</component>

.idea/misc.xml

@@ -0,0 +1,4 @@
+<?xml version="1.0" encoding="UTF-8"?>
+<project version="4">
+  <component name="ProjectRootManager" version="2" project-jdk-name="Python 3.8 (venv) (3)" project-jdk-type="Python SDK" />
+</project>

.idea/modules.xml

@@ -0,0 +1,8 @@
+<?xml version="1.0" encoding="UTF-8"?>
+<project version="4">
+  <component name="ProjectModuleManager">
+    <modules>
+      <module fileurl="file://$PROJECT_DIR$/.idea/hire.iml" filepath="$PROJECT_DIR$/.idea/hire.iml" />
+    </modules>
+  </component>
+</project>

env.py

@@ -0,0 +1,77 @@
+import agentpy as ap
+
+from random import uniform
+
+from worker import WorkerAgent
+from firm import FirmAgent
+
+
+class Env(ap.Model):
+
+    float_market_size: float
+    percent_rh: float
+    percent_search: float
+    n_worker: int
+    n_firm: int
+
+    a_lst_worker: ap.AgentList
+    a_lst_firm: ap.AgentList
+
+    def setup(self):
+        # 工作人员、企业数量、搜寻企业数量赋值
+        self.n_worker = self.p.n_worker
+        self.n_firm = self.p.n_firm
+        self.percent_search = self.p.percent_search
+        # 工人、企业列表
+        self.a_lst_worker = ap.AgentList(self)
+        self.a_lst_firm = ap.AgentList(self)
+
+        # 在工人列表中添加工人
+        for i in range(self.n_worker):
+            # 初始化  workeragent，并把alpha属性传过去
+            w = WorkerAgent(self, self.p.alpha)
+            self.a_lst_worker.append(w)
+
+        # 在企业列表中添加企业
+        for i in range(self.n_firm):
+            f = FirmAgent(self)
+            self.a_lst_firm.append(f)
+
+    def step(self):
+        self.a_lst_worker.select_firm()
+
+        if self.t == 100:
+            self.stop()
+        pass
+
+    def provide_lst_random_firms(self, the_worker: WorkerAgent):
+        '''选择企业数量 = 企业总数*百分比
+        选择企业的列表 = 随机选择的企业的个数
+        如果员工处于被雇佣的状态：
+           如果员工工作的企业在随机选定的企业列表中：
+             打开列表中的企业
+             移除该企业
+             返回值：移除后，再重新选择随机选择企业
+           否则：
+            返回值：选择企业列表
+        '''
+        n_select_firms = int(self.percent_search * self.n_firm)
+        a_lst_select_firms = self.a_lst_firm.random(n_select_firms)
+        if the_worker.s_is_hired:
+            if the_worker.working_firm in a_lst_select_firms:
+                lst_f = self.a_lst_firm.to_list()
+                lst_f.remove(the_worker.working_firm)
+                return ap.AgentList(self, lst_f).random(n_select_firms)
+        else:
+            return ap.AgentList(self, a_lst_select_firms)
+
+
+if __name__ == '__main__':
+    dict_para = {'n_worker': 100,
+                 'n_firm': 10,
+                 'percent_search': 0.2,
+                 'alpha': 0.5}
+    my_model = Env(dict_para)
+    my_model.run()
+
+

firm.py

@@ -0,0 +1,105 @@
+from typing import Union, Any
+
+import agentpy as ap
+from random import uniform, randint
+
+class FirmAgent(ap.Agent):
+    c_incentive: float
+    s_IsRH: bool
+    s_a_senior_yield: float
+    s_a_junior_yield: float
+    s_a_yield: float
+    s_salary: float
+    s_revenue: float
+    s_profit: float
+    l_senior_workers: list
+    l_junior_workers: list
+    l_applied_workers: list
+
+    def setup(self):
+        self.c_incentive = uniform(0, 1)
+        self.s_profit = randint(10, 20)
+        self.l_applied_workers = []
+
+    def apply(self, the_worker):
+        self.l_applied_workers.append(the_worker)
+
+    def select_worker(self):
+        '''
+        企业找到最想招聘的员工
+        :return:
+        '''
+        n_a_firms = len(self.l_applied_workers)
+        # 对员工产出进行排队和比较
+        max_s_yield: float
+        max_s_yield, best_worker = 0, None
+        for i in self.l_applied_workers:
+            y = max_s_yield
+            if y > max_s_yield:
+                max_s_yield = y
+                best_worker = i
+        # print(f'{self}: my best firm is {best_firm} from {n_firms} firms with utility {max_utility}')
+        # return best_worker
+        # 当企业是想要利用产出最高的员工时，从申请的员工中选出产出最高的员工
+        '''if self.s_IsRH :
+            # 计算该名员工的工资水平： 原有工资水平* （1+incentive）
+            bw_salary = self.best_worker.salary()
+
+            # 将该名员工的产出与公司原有员工的产出进行对比，如果高于senior列表中的最后一名的产出，就进入senior_list, 否则进入junior_list
+                self.l_senior_workers.append(best_worker)
+            else:
+                self.l_junior_workers.append(best_worker)
+            # best_worker.apply(self)
+        else:
+            # 计算由于改名员工下一期的薪资总数（根据薪资函数更新）以及企业下一期的利润的差值，并选出最大值
+        '''
+
+    def S_a_Yield(self):
+        # 更新总产出
+        # s_total_senior_yield = self.s_a_senior_yield * len(self.l_senior_workers)
+        # s_total_junior_yield = self.s_a_junior_yield * len(self.l_senior_workers)
+        l_s_workers = self.l_senior_workers
+        l_j_workers = self.l_junior_workers
+        # s_a_yield = s_total_yield / len(self.l_senior_workers + self.l_junior_workers)
+        s_total_senior_yield, s_total_junior_yield = 0, 0
+        '''for i in range(len(self.l_senior_workers)):
+            # 加入工人主体的产出属性
+                s_total_senior_yield += '工人的yield'
+            for i in range (len(self.l_junior_workers)):
+                s_total_junior_yield += '工人的yield'
+        s_a_senior_yield = s_total_senior_yield / len(l_s_workers)
+        s_a_junior_yield = s_total_junior_yield / len(l_j_workers)   
+        s_a_yield = 0.8*s_a_senior_yield+0.2*s_a_junior_yield
+        return s_a_yield
+            '''
+        return
+
+    def LogitShare(self):
+        '''
+        self.logitshare = exp(S_a_Yield)/ np.sum(exp(S_a_Yield))
+        :return:
+        '''
+        return
+
+    def Sum_salary(self, l_senior_workers, l_junior_workers):
+        '''
+       计算某公司整体的薪金水平
+        '''
+        l_all_workers = l_senior_workers + l_junior_workers
+        for i in l_all_workers:
+            #self.sum_salary = np.sum()
+            return
+
+    def S_Profit(self):
+        # self.s_profit =self.LogitShare() * EnvironmentAgent.s_e_Irevenue - self.Sum_salary()
+        return
+
+    def step(self):
+        '''
+        更新三个集合：
+        首先，判断员工i在企业j第t时期的l_applied_workers列表里；
+        第二步，判断企业j 的s_IsRH是0或者是1；
+        如果是1，则将应聘员工中s_w_yield最大的员工从l_applied_workers列表转移到l_senior_workers或l_junior_workers列表；
+        否则（即如果是0），则计算每名员工如果进入企业，下一期企业利润的提升max的员工，
+        从l_applied_workers列表转移到l_senior_workers或l_junior_workers列表。
+        '''

main.py

@@ -0,0 +1,16 @@
+# This is a sample Python script.
+
+# Press Shift+F10 to execute it or replace it with your code.
+# Press Double Shift to search everywhere for classes, files, tool windows, actions, and settings.
+
+
+def print_hi(name):
+    # Use a breakpoint in the code line below to debug your script.
+    print(f'Hi, {name}')  # Press Ctrl+F8 to toggle the breakpoint.
+
+
+# Press the green button in the gutter to run the script.
+if __name__ == '__main__':
+    print_hi('PyCharm')
+
+# See PyCharm help at https://www.jetbrains.com/help/pycharm/

worker.py

@@ -0,0 +1,77 @@
+import math
+
+import agentpy as ap
+from random import uniform, randint
+from firm import FirmAgent
+
+
+class WorkerAgent(ap.Agent):
+    select_firm: object
+    c_effort: float
+    s_is_hired: bool
+    c_work_months: int
+    s_work_duration: int
+    working_firm: FirmAgent
+    s_salary: float
+    s_yield: float
+    # s_w_applied: bool
+    c_alpha: float
+
+    def setup(self, alpha):
+        # super().__init__(unique_id, model)
+        # self.num_workers = 10000
+        self.c_effort = uniform(0, 1)
+        self.c_work_months = randint(0, 60)
+        self.s_is_hired = False
+        self.c_alpha = alpha
+        # return
+
+    # def A_Utility(self, c_w_weight=0.5):
+    #     a = np.exp(FirmAgent.c_f_incentive, c_w_weight)
+    #     b = np.exp(FirmAgent.s_f_profit/max(FirmAgent.s_f_profit), 1-c_w_weight)
+    #     self.select_firm = a * b
+
+    def select_firm(self):
+        '''
+        挑选出来的企业列表
+        数量：列表的长度
+        '''
+        lst_firms = self.model.provide_lst_random_firms(self)
+        n_firms = len(lst_firms)
+        # find the max incentive and profit among all firms
+        max_incentive, max_profit = 0, 0
+        for f in lst_firms:
+            if f.c_incentive > max_incentive:
+                max_incentive = f.c_incentive
+            if f.s_profit > max_profit:
+                max_profit = f.s_profit
+        # computer the utility for each firm
+        max_utility, best_firm = 0, None
+        for f in lst_firms:
+            u = math.pow(f.c_incentive / max_incentive, self.c_alpha) * math.pow(f.s_profit/max_profit, 1-self.c_alpha)
+            if u > max_utility:
+                max_utility = u
+                best_firm = f
+        # print(f'{self}: my best firm is {best_firm} from {n_firms} firms with utility {max_utility}')
+        # 选出能够给自己带来最好的效用的企业，并输出/返回
+        best_firm.apply(self)
+        return best_firm
+
+    def salary(self, the_firm: FirmAgent):
+        '''
+        如果员工首次受到雇佣，薪资 = 某公司初始薪资
+        如果员工更换了公司， 薪资 = 原薪资 * （1+c_incentive）
+        ? 换公司
+        :return:
+        '''
+        pass
+
+
+
+    def step(self):
+        if self.s_is_hired == 1:
+            self.s_work_duration +=1
+            self.s_yield = 2 / (1 + math.exp(-0.01 * self.s_work_duration * self.c_effort)) - 1
+        '''
+        是否更换公司成功的状态转换？
+        '''