From a8259fdc7d5736d215aa246b38567d9c2f9560a5 Mon Sep 17 00:00:00 2001
From: HaoYizhi <haoyizhi@agentlab.cn>
Date: Sat, 10 Jun 2023 19:02:43 +0800
Subject: [PATCH] damp prob removal first than sample

---
 __pycache__/firm.cpython-38.pyc  | Bin 6893 -> 6893 bytes
 __pycache__/model.cpython-38.pyc | Bin 11784 -> 11831 bytes
 model.py                         |   6 ++----
 3 files changed, 2 insertions(+), 4 deletions(-)

diff --git a/__pycache__/firm.cpython-38.pyc b/__pycache__/firm.cpython-38.pyc
index 3820ea3e24b7ef7d05e7711b2a5f4d44308c9604..c39ac4158dbbe2301a9250efcd21940b210e6987 100644
GIT binary patch
delta 371
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zjb`%!G5t1o^J+0NI!)fj=fE8d5(xkiE}I$o=Q1(6PJX~6GWj)^sbG;CNEq47pMo<4
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Dil0?L

delta 371
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D2a;8{

diff --git a/__pycache__/model.cpython-38.pyc b/__pycache__/model.cpython-38.pyc
index 1d55e5ef6df33f2a883e8d0b894c29ccd2719340..36beee74d4157b2b3a20977a940238ac064fb94e 100644
GIT binary patch
delta 2833
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diff --git a/model.py b/model.py
index 9c2952d..5facb84 100644
--- a/model.py
+++ b/model.py
@@ -1,7 +1,6 @@
 import agentpy as ap
 import pandas as pd
 import numpy as np
-# import random
 import networkx as nx
 from firm import FirmAgent
 from product import ProductAgent
@@ -14,7 +13,6 @@ class Model(ap.Model):
     def setup(self):
         self.sample = self.p.sample
         self.int_stop_times, self.int_stop_t = 0, None
-        # self.random = random.Random(self.p.seed)
         self.nprandom = np.random.default_rng(self.p.seed)
         self.int_n_iter = int(self.p.n_iter)
 
@@ -373,13 +371,13 @@ class Model(ap.Model):
                         std_size = (firm.revenue_log - min(lst_size) +
                                     1) / (max(lst_size) - min(lst_size) + 1)
                         prob_remove = 1 - std_size * (1 - lost_percent)
+                        # damp prod
+                        prob_remove = prob_remove ** self.flt_diff_remove
                         # sample prob
                         prob_remove = self.nprandom.uniform(
                             prob_remove - 0.1, prob_remove + 0.1)
                         prob_remove = 1 if prob_remove > 1 else prob_remove
                         prob_remove = 0 if prob_remove < 0 else prob_remove
-                        # damp prod
-                        prob_remove = prob_remove ** self.flt_diff_remove
                         if self.nprandom.choice([True, False],
                                                 p=[prob_remove,
                                                    1 - prob_remove]):