From 45a406961a7cff12a56cb3ddd8c240f050cfe874 Mon Sep 17 00:00:00 2001
From: HaoYizhi <haoyizhi@agentlab.cn>
Date: Tue, 14 Mar 2023 12:53:49 +0800
Subject: [PATCH] affect customer / remove customer up product conditionally

---
 __pycache__/firm.cpython-38.pyc | Bin 4768 -> 4868 bytes
 firm.py                         |  29 +++++++++++++++-------------
 test.ipynb                      |  33 +++++++++++++++++++++-----------
 3 files changed, 38 insertions(+), 24 deletions(-)

diff --git a/__pycache__/firm.cpython-38.pyc b/__pycache__/firm.cpython-38.pyc
index 2264692c096138dbefd4c0e270093fa16cd4901c..d3d35081c09271a554135278ac34edfb47ea1b08 100644
GIT binary patch
delta 942
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diff --git a/firm.py b/firm.py
index 0670e2a..bbda2fa 100644
--- a/firm.py
+++ b/firm.py
@@ -1,4 +1,5 @@
 import agentpy as ap
+import math
 
 
 class FirmAgent(ap.Agent):
@@ -29,7 +30,8 @@ class FirmAgent(ap.Agent):
                 # remove edge
                 # print(n1, n2, key, product_code)
                 self.firm_network.graph.remove_edge(n1, n2, key)
-                # remove customer up product if does not have alternative
+
+                # remove customer up product if does not have alternative / con
                 customer = ap.AgentIter(self.model, n2).to_list()[0]
                 list_in_edges = list(
                     self.firm_network.graph.in_edges(n2,
@@ -40,7 +42,8 @@ class FirmAgent(ap.Agent):
                     if edge[-1] == remove_product.code
                 ]
                 # print(select_edges)
-                if len(select_edges) == 0:
+                p_remove = math.exp(-1 * len(select_edges))
+                if self.model.nprandom.choice([True, False], p=[p_remove, 1-p_remove]):
                     print(self.name, remove_product.code, 'affect', customer.name)
                     if remove_product not in \
                             customer.a_list_up_product_removed:
@@ -123,17 +126,17 @@ class FirmAgent(ap.Agent):
             # print(product.code, [firm.name for firm in list_firm])
 
     def accept_request(self, down_firm, product):
-        # if self.model.nprandom.choice([True, False], p=[0.1, 0.9]):
-        self.firm_network.graph.add_edges_from([
-            (self.firm_network.positions[self],
-            self.firm_network.positions[down_firm], {
-                'Product': product.code
-            })
-        ])
-        self.dct_prod_capacity[product] -= 1
-        self.dct_request_prod_from_firm[product].remove(down_firm)
-        down_firm.a_list_up_product_removed.remove(product)
-        print(f"{self.name} accept {product.code} request from {down_firm.name}")
+        if self.model.nprandom.choice([True, False], p=[0.1, 0.9]):
+            self.firm_network.graph.add_edges_from([
+                (self.firm_network.positions[self],
+                self.firm_network.positions[down_firm], {
+                    'Product': product.code
+                })
+            ])
+            self.dct_prod_capacity[product] -= 1
+            self.dct_request_prod_from_firm[product].remove(down_firm)
+            down_firm.a_list_up_product_removed.remove(product)
+            print(f"{self.name} accept {product.code} request from {down_firm.name}")
 
     def clean_before_trial(self):
         self.dct_request_prod_from_firm = {}
diff --git a/test.ipynb b/test.ipynb
index 825b4bc..908176b 100644
--- a/test.ipynb
+++ b/test.ipynb
@@ -2,24 +2,35 @@
  "cells": [
   {
    "cell_type": "code",
-   "execution_count": 11,
+   "execution_count": 9,
    "metadata": {},
    "outputs": [
     {
-     "data": {
-      "text/plain": [
-       "1"
-      ]
-     },
-     "execution_count": 11,
-     "metadata": {},
-     "output_type": "execute_result"
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "85\n",
+      "63\n",
+      "51\n",
+      "26\n",
+      "30\n",
+      "4\n",
+      "7\n",
+      "1\n",
+      "17\n",
+      "81\n"
+     ]
     }
    ],
    "source": [
     "import numpy as np\n",
     "\n",
-    "np.random.randint(0.5, 3.5)"
+    "np.random.randint(0.5, 3.5)\n",
+    "p_remove = 1\n",
+    "np.random.choice([True, False], p=[p_remove, 1-p_remove])\n",
+    "rng = np.random.default_rng(0)\n",
+    "for _ in range(10):\n",
+    "    print(rng.integers(0,100))"
    ]
   },
   {
@@ -46,7 +57,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.8.8"
+   "version": "3.9.13"
   },
   "orig_nbformat": 4,
   "vscode": {