Compare commits
24 Commits
e8ca4d0107
...
master
| Author | SHA1 | Date | |
|---|---|---|---|
|
d57216d51f | ||
|
|
8f4c5929bb | ||
|
|
c30ec71014 | ||
|
|
46df9bace7 | ||
|
|
66e40a1250 | ||
|
|
ebc8159bf8 | ||
|
|
0233f642e4 | ||
|
|
5b2cf3a3e5 | ||
|
|
0da29d58d6 | ||
|
|
42fba119d1 | ||
|
|
30e7e56c11 | ||
|
|
0f7f9c1a4b | ||
|
|
3a46d09b8e | ||
|
|
13521ff752 | ||
|
|
09622cf33d | ||
|
|
3ba41c3491 | ||
|
|
3d97db42d0 | ||
|
|
2ccdc976e7 | ||
|
|
11b7b738f9 | ||
|
|
2d359c80f1 | ||
|
|
5c7788e86e | ||
|
|
2b59780e20 | ||
|
|
f7354a4a44 | ||
|
|
b0247e2bee |
176
.idea/csv-editor.xml
generated
176
.idea/csv-editor.xml
generated
@@ -3,21 +3,14 @@
|
||||
<component name="CsvFileAttributes">
|
||||
<option name="attributeMap">
|
||||
<map>
|
||||
<entry key="\input_data\BomCateNet.csv">
|
||||
<entry key="C:\Users\www\Desktop\python项目\数据\抽样第3次数据\firm_amended.csv">
|
||||
<value>
|
||||
<Attribute>
|
||||
<option name="separator" value="," />
|
||||
</Attribute>
|
||||
</value>
|
||||
</entry>
|
||||
<entry key="\input_data\BomNodes.csv">
|
||||
<value>
|
||||
<Attribute>
|
||||
<option name="separator" value="," />
|
||||
</Attribute>
|
||||
</value>
|
||||
</entry>
|
||||
<entry key="\input_data\Firm_amended.csv">
|
||||
<entry key="\input_data\device_salvage_values.csv">
|
||||
<value>
|
||||
<Attribute>
|
||||
<option name="separator" value="," />
|
||||
@@ -31,6 +24,90 @@
|
||||
</Attribute>
|
||||
</value>
|
||||
</entry>
|
||||
<entry key="\input_data\input_firm_data\Firm_amended.csv">
|
||||
<value>
|
||||
<Attribute>
|
||||
<option name="separator" value="," />
|
||||
</Attribute>
|
||||
</value>
|
||||
</entry>
|
||||
<entry key="\input_data\input_firm_data\firm_amended.csv">
|
||||
<value>
|
||||
<Attribute>
|
||||
<option name="separator" value="," />
|
||||
</Attribute>
|
||||
</value>
|
||||
</entry>
|
||||
<entry key="\input_data\input_firm_data\firms_devices.csv">
|
||||
<value>
|
||||
<Attribute>
|
||||
<option name="separator" value="," />
|
||||
</Attribute>
|
||||
</value>
|
||||
</entry>
|
||||
<entry key="\input_data\input_firm_data\firms_materials.csv">
|
||||
<value>
|
||||
<Attribute>
|
||||
<option name="separator" value="," />
|
||||
</Attribute>
|
||||
</value>
|
||||
</entry>
|
||||
<entry key="\input_data\input_firm_data\firms_products.csv">
|
||||
<value>
|
||||
<Attribute>
|
||||
<option name="separator" value="," />
|
||||
</Attribute>
|
||||
</value>
|
||||
</entry>
|
||||
<entry key="\input_data\input_product_data\BomCateNet.csv">
|
||||
<value>
|
||||
<Attribute>
|
||||
<option name="separator" value="," />
|
||||
</Attribute>
|
||||
</value>
|
||||
</entry>
|
||||
<entry key="\input_data\input_product_data\BomNodes.csv">
|
||||
<value>
|
||||
<Attribute>
|
||||
<option name="separator" value="," />
|
||||
</Attribute>
|
||||
</value>
|
||||
</entry>
|
||||
<entry key="\input_data\input_product_data\products_consumed_materials.csv">
|
||||
<value>
|
||||
<Attribute>
|
||||
<option name="separator" value="," />
|
||||
</Attribute>
|
||||
</value>
|
||||
</entry>
|
||||
<entry key="\input_data\input_product_data\products_materials_equipment.csv">
|
||||
<value>
|
||||
<Attribute>
|
||||
<option name="separator" value="," />
|
||||
</Attribute>
|
||||
</value>
|
||||
</entry>
|
||||
<entry key="\input_data\input_product_data\products_produced_products.csv">
|
||||
<value>
|
||||
<Attribute>
|
||||
<option name="separator" value="," />
|
||||
</Attribute>
|
||||
</value>
|
||||
</entry>
|
||||
<entry key="\input_data\input_product_data\合成结点.csv">
|
||||
<value>
|
||||
<Attribute>
|
||||
<option name="separator" value="," />
|
||||
</Attribute>
|
||||
</value>
|
||||
</entry>
|
||||
<entry key="\input_data\material_device_product_ids.csv">
|
||||
<value>
|
||||
<Attribute>
|
||||
<option name="separator" value="," />
|
||||
</Attribute>
|
||||
</value>
|
||||
</entry>
|
||||
<entry key="\input_data\oa_with_exp.csv">
|
||||
<value>
|
||||
<Attribute>
|
||||
@@ -59,14 +136,35 @@
|
||||
</Attribute>
|
||||
</value>
|
||||
</entry>
|
||||
<entry key="\input_data\测试 BomNodes.csv">
|
||||
<entry key="\input_data\产品消耗制造比例.csv">
|
||||
<value>
|
||||
<Attribute>
|
||||
<option name="separator" value="," />
|
||||
</Attribute>
|
||||
</value>
|
||||
</entry>
|
||||
<entry key="\input_data\测试 Firm_amended 170.csv">
|
||||
<entry key="\output_result\resilience\anova.csv">
|
||||
<value>
|
||||
<Attribute>
|
||||
<option name="separator" value="," />
|
||||
</Attribute>
|
||||
</value>
|
||||
</entry>
|
||||
<entry key="\output_result\resilience\anova_visualization.csv">
|
||||
<value>
|
||||
<Attribute>
|
||||
<option name="separator" value="," />
|
||||
</Attribute>
|
||||
</value>
|
||||
</entry>
|
||||
<entry key="\output_result\resilience\experiment_result.csv">
|
||||
<value>
|
||||
<Attribute>
|
||||
<option name="separator" value="," />
|
||||
</Attribute>
|
||||
</value>
|
||||
</entry>
|
||||
<entry key="\output_result\risk\count.csv">
|
||||
<value>
|
||||
<Attribute>
|
||||
<option name="separator" value="," />
|
||||
@@ -108,62 +206,6 @@
|
||||
</Attribute>
|
||||
</value>
|
||||
</entry>
|
||||
<entry key="\测试数据 companies_devices.csv">
|
||||
<value>
|
||||
<Attribute>
|
||||
<option name="separator" value="," />
|
||||
</Attribute>
|
||||
</value>
|
||||
</entry>
|
||||
<entry key="\测试数据 companies_materials.csv">
|
||||
<value>
|
||||
<Attribute>
|
||||
<option name="separator" value="," />
|
||||
</Attribute>
|
||||
</value>
|
||||
</entry>
|
||||
<entry key="\测试数据 companies_products.csv">
|
||||
<value>
|
||||
<Attribute>
|
||||
<option name="separator" value="," />
|
||||
</Attribute>
|
||||
</value>
|
||||
</entry>
|
||||
<entry key="\测试数据 consumed_materials.csv">
|
||||
<value>
|
||||
<Attribute>
|
||||
<option name="separator" value="," />
|
||||
</Attribute>
|
||||
</value>
|
||||
</entry>
|
||||
<entry key="\测试数据 device_salvage_values.csv">
|
||||
<value>
|
||||
<Attribute>
|
||||
<option name="separator" value="," />
|
||||
</Attribute>
|
||||
</value>
|
||||
</entry>
|
||||
<entry key="\测试数据 material_device_product_ids.csv">
|
||||
<value>
|
||||
<Attribute>
|
||||
<option name="separator" value="," />
|
||||
</Attribute>
|
||||
</value>
|
||||
</entry>
|
||||
<entry key="\测试数据 produced_products.csv">
|
||||
<value>
|
||||
<Attribute>
|
||||
<option name="separator" value="," />
|
||||
</Attribute>
|
||||
</value>
|
||||
</entry>
|
||||
<entry key="\测试数据 products_materials_equipment.csv">
|
||||
<value>
|
||||
<Attribute>
|
||||
<option name="separator" value="," />
|
||||
</Attribute>
|
||||
</value>
|
||||
</entry>
|
||||
</map>
|
||||
</option>
|
||||
</component>
|
||||
|
||||
22
.idea/dataSources.local.xml
generated
Normal file
22
.idea/dataSources.local.xml
generated
Normal file
@@ -0,0 +1,22 @@
|
||||
<?xml version="1.0" encoding="UTF-8"?>
|
||||
<project version="4">
|
||||
<component name="dataSourceStorageLocal" created-in="PY-242.23726.102">
|
||||
<data-source name="iiabmdb@localhost" uuid="8145438e-516b-4005-a581-b91b5eedc759">
|
||||
<database-info product="MySQL" version="8.0.36" jdbc-version="4.2" driver-name="MySQL Connector/J" driver-version="mysql-connector-j-8.2.0 (Revision: 06a1f724497fd81c6a659131fda822c9e5085b6c)" dbms="MYSQL" exact-version="8.0.36" exact-driver-version="8.2">
|
||||
<extra-name-characters>#@</extra-name-characters>
|
||||
<identifier-quote-string>`</identifier-quote-string>
|
||||
</database-info>
|
||||
<case-sensitivity plain-identifiers="lower" quoted-identifiers="lower" />
|
||||
<secret-storage>master_key</secret-storage>
|
||||
<user-name>iiabm_user</user-name>
|
||||
<schema-mapping>
|
||||
<introspection-scope>
|
||||
<node kind="schema">
|
||||
<name qname="@" />
|
||||
<name qname="information_schema" />
|
||||
</node>
|
||||
</introspection-scope>
|
||||
</schema-mapping>
|
||||
</data-source>
|
||||
</component>
|
||||
</project>
|
||||
12
.idea/dataSources.xml
generated
Normal file
12
.idea/dataSources.xml
generated
Normal file
@@ -0,0 +1,12 @@
|
||||
<?xml version="1.0" encoding="UTF-8"?>
|
||||
<project version="4">
|
||||
<component name="DataSourceManagerImpl" format="xml" multifile-model="true">
|
||||
<data-source source="LOCAL" name="iiabmdb@localhost" uuid="8145438e-516b-4005-a581-b91b5eedc759">
|
||||
<driver-ref>mysql.8</driver-ref>
|
||||
<synchronize>true</synchronize>
|
||||
<jdbc-driver>com.mysql.cj.jdbc.Driver</jdbc-driver>
|
||||
<jdbc-url>jdbc:mysql://localhost:3306/iiabmdb</jdbc-url>
|
||||
<working-dir>$ProjectFileDir$</working-dir>
|
||||
</data-source>
|
||||
</component>
|
||||
</project>
|
||||
5486
.idea/dataSources/8145438e-516b-4005-a581-b91b5eedc759.xml
generated
Normal file
5486
.idea/dataSources/8145438e-516b-4005-a581-b91b5eedc759.xml
generated
Normal file
File diff suppressed because it is too large
Load Diff
@@ -0,0 +1,2 @@
|
||||
#n:iiabmdb
|
||||
!<md> [0, 0, null, null, -2147483648, -2147483648]
|
||||
@@ -0,0 +1,2 @@
|
||||
#n:information_schema
|
||||
!<md> [0, 0, null, null, -2147483648, -2147483648]
|
||||
Binary file not shown.
6
.idea/developer-tools.xml
generated
Normal file
6
.idea/developer-tools.xml
generated
Normal file
@@ -0,0 +1,6 @@
|
||||
<?xml version="1.0" encoding="UTF-8"?>
|
||||
<project version="4">
|
||||
<component name="DeveloperToolsToolWindowSettingsV1" lastSelectedContentNodeId="base64-encoder-decoder">
|
||||
<developerToolsConfigurations />
|
||||
</component>
|
||||
</project>
|
||||
8
.idea/encodings.xml
generated
Normal file
8
.idea/encodings.xml
generated
Normal file
@@ -0,0 +1,8 @@
|
||||
<?xml version="1.0" encoding="UTF-8"?>
|
||||
<project version="4">
|
||||
<component name="Encoding">
|
||||
<file url="file://$PROJECT_DIR$/input_data/input_firm_data/firm_amended.csv" charset="UTF-8" />
|
||||
<file url="file://$PROJECT_DIR$/output_result/resilience/anova_visualization.csv" charset="UTF-8" />
|
||||
<file url="file://$PROJECT_DIR$/查看进度.py" charset="GBK" />
|
||||
</component>
|
||||
</project>
|
||||
11
.idea/sqldialects.xml
generated
Normal file
11
.idea/sqldialects.xml
generated
Normal file
@@ -0,0 +1,11 @@
|
||||
<?xml version="1.0" encoding="UTF-8"?>
|
||||
<project version="4">
|
||||
<component name="SqlDialectMappings">
|
||||
<file url="file://$PROJECT_DIR$/SQL_analysis_experiment.sql" dialect="MySQL" />
|
||||
<file url="file://$PROJECT_DIR$/SQL_analysis_risk.sql" dialect="MySQL" />
|
||||
<file url="file://$PROJECT_DIR$/SQL_db_user_create.sql" dialect="MySQL" />
|
||||
<file url="file://$PROJECT_DIR$/SQL_export_high_risk_setting.sql" dialect="MySQL" />
|
||||
<file url="file://$PROJECT_DIR$/SQL_migrate_db.sql" dialect="MySQL" />
|
||||
<file url="file://$PROJECT_DIR$/iiabmdb_basic_info.sql" dialect="MySQL" />
|
||||
</component>
|
||||
</project>
|
||||
29
11.py
Normal file
29
11.py
Normal file
@@ -0,0 +1,29 @@
|
||||
import pickle
|
||||
import os
|
||||
|
||||
from 查看进度 import visualize_progress
|
||||
|
||||
|
||||
def load_cached_data(file_path):
|
||||
"""
|
||||
从指定的缓存文件加载数据。
|
||||
如果文件不存在或加载失败，则返回空字典。
|
||||
"""
|
||||
if not os.path.exists(file_path):
|
||||
print(f"Warning: Cache file '{file_path}' does not exist.")
|
||||
return {}
|
||||
|
||||
try:
|
||||
with open(file_path, 'rb') as f:
|
||||
data = pickle.load(f)
|
||||
print(f"Successfully loaded cache from '{file_path}'.")
|
||||
return data
|
||||
except (pickle.UnpicklingError, FileNotFoundError, EOFError) as e:
|
||||
print(f"Error loading cache from '{file_path}': {e}")
|
||||
return {}
|
||||
|
||||
|
||||
# 示例用法
|
||||
# data_dct = load_cached_data("G_Firm_add_edges.pkl")
|
||||
|
||||
visualize_progress()
|
||||
36
README.md
Normal file
36
README.md
Normal file
@@ -0,0 +1,36 @@
|
||||
## 安装内容
|
||||
1. 数据库，推荐使用mysql 8.0以上版本
|
||||
2. Python 3.8
|
||||
3. 通过pip等方法安装*requirements_manual_selected_20230304.txt*文件中的包
|
||||
|
||||
## 前期准备工作
|
||||
1. 复制整个代码到本地
|
||||
2. 用root及密码登录mysql，在本地数据库中创建一个数据库，命名为*iiabmdb*
|
||||
3. 在mysql中运行*SQL_db_user_create.sql*里的sql命令，创建数据库用户。如果创建用户报错，需打开该文件，并运行第三行被注释掉的代码。该文件后面的sql命令也需要运行，将数据库用户的权限赋予*iiabmdb*数据库
|
||||
4. 之后直接运行controller.py文件，如果没有报错，则说明前期准备工作完成
|
||||
|
||||
## 运行程序
|
||||
1. 将*conf_db_prefix.yaml*文件中的*db_prefix*改为*db_name_prefix: without_exp*
|
||||
2. 打开命令行，进入代码所在目录，运行
|
||||
```shell
|
||||
python main.py --exp without_exp --job 6 --reset_db True
|
||||
```
|
||||
3. 等待运行完成（1.2万个样本）。结束后，将*db_name_prefix: without_exp*改为*db_name_prefix: with_exp*，并运行
|
||||
```shell
|
||||
python main.py --exp with_exp --job 6 --reset_db True
|
||||
```
|
||||
4. 漫长的等待（3.4万个样本），直到运行完成
|
||||
|
||||
## 获得结果，绘制图表
|
||||
|
||||
### 风险节点分析
|
||||
1. 运行*risk_analysis_sum_result.py*文件，该程序自动产生风险节点分析统计数据并放置到output_result/risk文件夹中
|
||||
2. 依次运行*risk_analysis_prod_network.py*，*risk_analysis_firm_network.py*文件，将自动产生相关结果放置到output_result/risk文件夹中
|
||||
|
||||
### 韧性影响因素分析
|
||||
1. 运行*SQL_analysis_experiment.sql*文件，将汇总结果手工复制至output_result/resilience文件夹*experiment_result.csv*文件中
|
||||
2. 使用Minitab进行田口设计分析
|
||||
3. 新建田口设计（统计——DOE——田口——创建田口设计——混合水平设计），因子数选项设置为8，设计选项设置为L36，水平^列为2^3，3^5，因子选项中将列名依次修改为：is_prf_size，is_prf_conn，ex_cap_type，n_max_trial，ex_cap_para，prob_new_conn，t_max_trial，n_sourcing
|
||||
4. 将output_result/resilience文件夹*experiment_result.csv*文件中结果复制入田口设计表格右侧列
|
||||
5. 依次对各个韧性指标进行田口设计分析（统计——DOE——田口——分析田口设计），从mean_count_firm_prod，mean_max_ts_firm_prod，mean_n_remove_firm_prod，mean_end_ts中选择一个韧性指标，图形选项勾选均值，分析选项中显示响应表勾选均值，拟合线性模型勾选均值，点击确定
|
||||
6. 手工汇总方差分析结果至output_result/resilience文件夹*anova.csv*文件中，汇总响应表结果至*anova_visualization.csv*文件中
|
||||
@@ -74,7 +74,7 @@ left join
|
||||
from iiabmdb.with_exp_result
|
||||
where `status` = "R"
|
||||
group by s_id, id_firm) as s_n_remove_prod
|
||||
left join iiabmdb_basic_info.firm_n_prod as firm_n_prod
|
||||
left join iiabmdb.firm_n_prod as firm_n_prod
|
||||
on s_n_remove_prod.id_firm = firm_n_prod.code
|
||||
where n_remove_prod = n_prod
|
||||
group by s_id) as s_n_all_prod_remove_firm
|
||||
|
||||
@@ -1,13 +1,16 @@
|
||||
CREATE DATABASE iiabmdb20230829;
|
||||
RENAME TABLE iiabmdb.not_test_experiment TO iiabmdb20230829.not_test_experiment,
|
||||
iiabmdb.not_test_result TO iiabmdb20230829.not_test_result,
|
||||
iiabmdb.not_test_sample TO iiabmdb20230829.not_test_sample,
|
||||
iiabmdb.test_experiment TO iiabmdb20230829.test_experiment,
|
||||
iiabmdb.test_result TO iiabmdb20230829.test_result,
|
||||
iiabmdb.test_sample TO iiabmdb20230829.test_sample;
|
||||
RENAME TABLE iiabmdb.with_exp_experiment TO iiabmdb20230829.with_exp_experiment,
|
||||
iiabmdb.with_exp_result TO iiabmdb20230829.with_exp_result,
|
||||
iiabmdb.with_exp_sample TO iiabmdb20230829.with_exp_sample,
|
||||
iiabmdb.without_exp_experiment TO iiabmdb20230829.without_exp_experiment,
|
||||
iiabmdb.without_exp_result TO iiabmdb20230829.without_exp_result,
|
||||
iiabmdb.without_exp_sample TO iiabmdb20230829.without_exp_sample;
|
||||
-- 创建新的数据库
|
||||
CREATE DATABASE iiabmdb2025211;
|
||||
|
||||
-- 重命名表到新数据库
|
||||
RENAME TABLE
|
||||
iiabmdb.test_experiment TO iiabmdb2025211.test_experiment,
|
||||
iiabmdb.test_result TO iiabmdb2025211.test_result,
|
||||
iiabmdb.test_sample TO iiabmdb2025211.test_sample;
|
||||
|
||||
RENAME TABLE
|
||||
iiabmdb.with_exp_experiment TO iiabmdb2025211.with_exp_experiment,
|
||||
iiabmdb.with_exp_result TO iiabmdb2025211.with_exp_result,
|
||||
iiabmdb.with_exp_sample TO iiabmdb2025211.with_exp_sample,
|
||||
iiabmdb.without_exp_experiment TO iiabmdb2025211.without_exp_experiment,
|
||||
iiabmdb.without_exp_result TO iiabmdb2025211.without_exp_result,
|
||||
iiabmdb.without_exp_sample TO iiabmdb2025211.without_exp_sample;
|
||||
|
||||
BIN
__pycache__/Model.cpython-38.pyc
Normal file
BIN
__pycache__/Model.cpython-38.pyc
Normal file
Binary file not shown.
BIN
__pycache__/computation.cpython-311.pyc
Normal file
BIN
__pycache__/computation.cpython-311.pyc
Normal file
Binary file not shown.
Binary file not shown.
Binary file not shown.
Binary file not shown.
BIN
__pycache__/main.cpython-38.pyc
Normal file
BIN
__pycache__/main.cpython-38.pyc
Normal file
Binary file not shown.
Binary file not shown.
Binary file not shown.
Binary file not shown.
BIN
__pycache__/查看进度.cpython-38.pyc
Normal file
BIN
__pycache__/查看进度.cpython-38.pyc
Normal file
Binary file not shown.
@@ -1,5 +1,10 @@
|
||||
import json
|
||||
import os
|
||||
import datetime
|
||||
import time
|
||||
|
||||
import networkx as nx
|
||||
import pandas as pd
|
||||
from mesa import Model
|
||||
|
||||
from typing import TYPE_CHECKING
|
||||
@@ -36,9 +41,8 @@ class Computation:
|
||||
dct_sample_para = {'sample': sample_random,
|
||||
'seed': sample_random.seed,
|
||||
**dct_exp}
|
||||
|
||||
model = MyModel(dct_sample_para)
|
||||
for i in range(1):
|
||||
model.step()
|
||||
print(i, datetime.datetime.now())
|
||||
model.end()
|
||||
return False
|
||||
|
||||
model.step() # 运行仿真一步
|
||||
model.end() # 汇总结果
|
||||
|
||||
@@ -30,7 +30,7 @@ class ControllerDB:
|
||||
self.is_with_exp = False if prefix == 'test' or prefix == 'without_exp' else True
|
||||
self.db_name_prefix = prefix
|
||||
dct_para_in_test = dct_conf_experiment['test'] if self.is_test else dct_conf_experiment['not_test']
|
||||
self.dct_parameter = {'meta_seed': dct_conf_experiment['meta_seed'] , **dct_para_in_test}
|
||||
self.dct_parameter = {'meta_seed': dct_conf_experiment['meta_seed'], **dct_para_in_test}
|
||||
|
||||
print(self.dct_parameter)
|
||||
# 0, not reset; 1, reset self; 2, reset all
|
||||
@@ -38,6 +38,9 @@ class ControllerDB:
|
||||
self.is_exist = False
|
||||
self.lst_saved_s_id = []
|
||||
|
||||
self.experiment_data = []
|
||||
self.batch_size = 5000
|
||||
# 根据需求设置每批次的大小
|
||||
|
||||
def init_tables(self):
|
||||
self.fill_experiment_table()
|
||||
@@ -50,9 +53,8 @@ class ControllerDB:
|
||||
|
||||
# fill dct_lst_init_disrupt_firm_prod
|
||||
# 存储 公司-在供应链结点的位置.. 0 ：‘1.1’
|
||||
list_dct = [] #存储 公司编码code 和对应的产业链 结点
|
||||
if self.is_with_exp:
|
||||
#对于方差分析时候使用
|
||||
# 对于方差分析时候使用
|
||||
with open('SQL_export_high_risk_setting.sql', 'r') as f:
|
||||
str_sql = text(f.read())
|
||||
result = pd.read_sql(sql=str_sql, con=connection)
|
||||
@@ -64,28 +66,45 @@ class ControllerDB:
|
||||
# 行索引 (index)：这一行在数据帧中的索引值。
|
||||
# 行数据 (row)：这一行的数据，是一个 pandas.Series 对象，包含该行的所有列和值。
|
||||
|
||||
firm_industry=pd.read_csv("input_data/firm_industry_relation.csv")
|
||||
# 读取企业与产品关系数据
|
||||
firm_industry = pd.read_csv("input_data/firm_industry_relation.csv")
|
||||
firm_industry['Firm_Code'] = firm_industry['Firm_Code'].astype('string')
|
||||
|
||||
# 假设已从 BOM 数据构建了 code_to_indices
|
||||
bom_nodes = pd.read_csv("input_data/input_product_data/BomNodes.csv")
|
||||
code_to_indices = bom_nodes.groupby('Code')['Index'].apply(list).to_dict()
|
||||
|
||||
# 初始化存储映射结果的列表
|
||||
list_dct = []
|
||||
|
||||
# 遍历 firm_industry 数据
|
||||
for _, row in firm_industry.iterrows():
|
||||
code = row['Firm_Code']
|
||||
row = row['Product_Code']
|
||||
dct = {code: [row]}
|
||||
firm_code = row['Firm_Code'] # 企业代码
|
||||
product_code = row['Product_Code'] # 原始产品代码
|
||||
|
||||
# 使用 code_to_indices 映射 Product_Code 到 Product_Indices
|
||||
mapped_indices = code_to_indices.get(product_code, []) # 如果找不到则返回空列表
|
||||
|
||||
# 构建企业到产品索引的映射
|
||||
dct = {firm_code: mapped_indices}
|
||||
list_dct.append(dct)
|
||||
|
||||
# fill g_bom
|
||||
# 结点属性值 相当于 图上点的 原始 产品名称
|
||||
bom_nodes = pd.read_csv('input_data/input_product_data/BomNodes.csv', index_col=0)
|
||||
bom_nodes.set_index('Code', inplace=True)
|
||||
bom_nodes = pd.read_csv('input_data/input_product_data/BomNodes.csv')
|
||||
bom_nodes['Code'] = bom_nodes['Code'].astype(str)
|
||||
bom_nodes.set_index('Index', inplace=True)
|
||||
|
||||
bom_cate_net = pd.read_csv('input_data/input_product_data/BomCateNet.csv', index_col=0)
|
||||
bom_cate_net.fillna(0, inplace=True)
|
||||
# 创建 可以多边的有向图 同时 转置操作 使得 上游指向下游结点 也就是 1.1.1 - 1.1 类似这种
|
||||
g_bom = nx.from_pandas_adjacency(bom_cate_net.T,
|
||||
create_using=nx.MultiDiGraph())
|
||||
bom_cate_net = pd.read_csv('input_data/input_product_data/合成结点.csv')
|
||||
g_bom = nx.from_pandas_edgelist(bom_cate_net, source='UPID', target='ID', create_using=nx.MultiDiGraph())
|
||||
# 填充每一个结点 的具体内容 通过 相同的 code 并且通过BomNodes.loc[code].to_dict()字典化 格式类似 格式 { code（0） : {level: 0 ,name: 工业互联网 }}
|
||||
bom_labels_dict = {}
|
||||
for code in g_bom.nodes:
|
||||
bom_labels_dict[code] = bom_nodes.loc[code].to_dict()
|
||||
for index in g_bom.nodes:
|
||||
try:
|
||||
bom_labels_dict[index] = bom_nodes.loc[index].to_dict()
|
||||
# print(bom_labels_dict[index])
|
||||
except KeyError:
|
||||
print(f"节点 {index} 不存在于 bom_nodes 中")
|
||||
# 分配属性 给每一个结点 获得类似 格式：{1: {'label': 'A', 'value': 10},
|
||||
nx.set_node_attributes(g_bom, bom_labels_dict)
|
||||
# 改为json 格式
|
||||
@@ -123,6 +142,7 @@ class ControllerDB:
|
||||
**dct_exp_para)
|
||||
print(f"Inserted experiment for scenario {idx_scenario}, "
|
||||
f"init_removal {idx_init_removal}!")
|
||||
self.finalize_insertion()
|
||||
|
||||
def add_experiment_1(self, idx_scenario, idx_init_removal,
|
||||
dct_lst_init_disrupt_firm_prod, g_bom,
|
||||
@@ -145,8 +165,22 @@ class ControllerDB:
|
||||
remove_t=remove_t,
|
||||
netw_prf_n=netw_prf_n
|
||||
)
|
||||
db_session.add(e)
|
||||
# 这里我们不立即提交，而是先添加到批量保存的队列中
|
||||
self.experiment_data.append(e)
|
||||
|
||||
# 当批量数据达到一定数量时再提交
|
||||
if len(self.experiment_data) >= self.batch_size:
|
||||
self._commit_batch()
|
||||
|
||||
# 辅助方法：批量提交
|
||||
def _commit_batch(self):
|
||||
db_session.bulk_save_objects(self.experiment_data)
|
||||
db_session.commit()
|
||||
self.experiment_data.clear() # 清空队列
|
||||
|
||||
def finalize_insertion(self):
|
||||
if self.experiment_data:
|
||||
self._commit_batch() # 提交剩余的数据
|
||||
|
||||
def fill_sample_table(self):
|
||||
rng = random.Random(self.dct_parameter['meta_seed'])
|
||||
@@ -166,8 +200,17 @@ class ControllerDB:
|
||||
seed=lst_seed[idx_sample],
|
||||
is_done_flag=-1)
|
||||
lst_sample.append(s)
|
||||
db_session.bulk_save_objects(lst_sample)
|
||||
db_session.commit()
|
||||
# 每当达到批量大小时提交一次
|
||||
if len(lst_sample) >= self.batch_size:
|
||||
db_session.bulk_save_objects(lst_sample)
|
||||
db_session.commit()
|
||||
print(f'Inserted {len(lst_sample)} samples!')
|
||||
lst_sample.clear() # 清空已提交的样本列表
|
||||
|
||||
# 提交剩余的样本
|
||||
if lst_sample:
|
||||
db_session.bulk_save_objects(lst_sample)
|
||||
db_session.commit()
|
||||
print(f'Inserted {len(lst_sample)} samples!')
|
||||
|
||||
def reset_db(self, force_drop=False):
|
||||
|
||||
BIN
degree_distribution_firm.png
Normal file
BIN
degree_distribution_firm.png
Normal file
Binary file not shown.
|
After Width: | Height: | Size: 263 KiB |
BIN
degree_distribution_with_labels.png
Normal file
BIN
degree_distribution_with_labels.png
Normal file
Binary file not shown.
|
After Width: | Height: | Size: 267 KiB |
103
firm.py
103
firm.py
@@ -2,7 +2,7 @@ from mesa import Agent
|
||||
|
||||
|
||||
class FirmAgent(Agent):
|
||||
def __init__(self, unique_id, model, type_region, revenue_log, n_equip_c, a_lst_product,
|
||||
def __init__(self, unique_id, model, type_region, revenue_log, a_lst_product,
|
||||
production_output, demand_quantity, R, P, C):
|
||||
# 调用超类的 __init__ 方法
|
||||
super().__init__(unique_id, model)
|
||||
@@ -32,20 +32,20 @@ class FirmAgent(Agent):
|
||||
# 包括 产品时间
|
||||
self.P1 = {0: P}
|
||||
# 企业i的供应商
|
||||
self.upper_i = [agent for u, v in self.firm_network.in_edges(self.unique_id)
|
||||
for agent in self.model.company_agents if agent.unique_id == u]
|
||||
self.upper_i = [self.model.agent_map[u] for u, v in self.firm_network.in_edges(self.unique_id)
|
||||
if u in self.model.agent_map]
|
||||
# 企业i的客户
|
||||
self.downer_i = [agent for u, v in self.firm_network.out_edges(self.unique_id)
|
||||
for agent in self.model.company_agents if agent.unique_id == u]
|
||||
self.downer_i = [self.model.agent_map[v] for u, v in self.firm_network.out_edges(self.unique_id)
|
||||
if v in self.model.agent_map]
|
||||
# 设备c的数量 （总量） 使用这个来判断设备数量
|
||||
self.n_equip_c = n_equip_c
|
||||
# 设备c产量 更具设备量进行估算
|
||||
# self.n_equip_c = n_equip_c
|
||||
# 设备c产量 根据设备量进行估算
|
||||
self.c_yield = production_output
|
||||
# 消耗材料量 根据设备量进行估算
|
||||
# 消耗材料量 根据设备量进行估算 { }
|
||||
self.c_consumption = demand_quantity
|
||||
# 设备c购买价格（初始值）
|
||||
# self.c_price = c_price
|
||||
# 资源r补货库存阈值
|
||||
# 资源r补货库存阈值 很重要设置
|
||||
self.s_r = 40
|
||||
self.S_r = 120
|
||||
# 设备补货阙值 可选
|
||||
@@ -143,42 +143,69 @@ class FirmAgent(Agent):
|
||||
# f"disrupted supplier of {disrupted_up_prod.code}")
|
||||
|
||||
def seek_alt_supply(self, product):
|
||||
# 检查当前产品的尝试次数是否达到最大值
|
||||
if self.dct_n_trial_up_prod_disrupted[product] <= self.model.int_n_max_trial:
|
||||
# 初始化候选供应商列表
|
||||
if self.dct_n_trial_up_prod_disrupted[product] == 0:
|
||||
self.dct_cand_alt_supp_up_prod_disrupted[product] = [
|
||||
firm for firm in self.model.company_agents
|
||||
if firm.is_prod_in_current_normal(product)]
|
||||
if self.dct_cand_alt_supp_up_prod_disrupted[product]:
|
||||
lst_firm_connect = []
|
||||
if self.is_prf_conn:
|
||||
for firm in self.dct_cand_alt_supp_up_prod_disrupted[product]:
|
||||
if self.firm_network.has_edge(self.unique_id, firm.unique_id) or \
|
||||
self.firm_network.has_edge(firm.unique_id, self.unique_id):
|
||||
lst_firm_connect.append(firm)
|
||||
if len(lst_firm_connect) == 0:
|
||||
if self.is_prf_size:
|
||||
lst_size = [firm.size_stat[-1][0] for firm in self.dct_cand_alt_supp_up_prod_disrupted[product]]
|
||||
lst_prob = [size / sum(lst_size) for size in lst_size]
|
||||
select_alt_supply = \
|
||||
self.random.choices(self.dct_cand_alt_supp_up_prod_disrupted[product], weights=lst_prob)[0]
|
||||
else:
|
||||
select_alt_supply = self.random.choice(self.dct_cand_alt_supp_up_prod_disrupted[product])
|
||||
elif len(lst_firm_connect) > 0:
|
||||
if self.is_prf_size:
|
||||
lst_firm_size = [firm.size_stat[-1][0] for firm in lst_firm_connect]
|
||||
lst_prob = [size / sum(lst_firm_size) for size in lst_firm_size]
|
||||
select_alt_supply = self.random.choices(lst_firm_connect, weights=lst_prob)[0]
|
||||
else:
|
||||
select_alt_supply = self.random.choice(lst_firm_connect)
|
||||
firm for firm in self.model.company_agents if firm.is_prod_in_current_normal(product)
|
||||
]
|
||||
|
||||
assert select_alt_supply.is_prod_in_current_normal(product)
|
||||
# 如果没有候选供应商，直接退出
|
||||
if not self.dct_cand_alt_supp_up_prod_disrupted[product]:
|
||||
# print(f"No valid candidates found for product {product.unique_id}")
|
||||
return
|
||||
|
||||
if product in select_alt_supply.dct_request_prod_from_firm:
|
||||
select_alt_supply.dct_request_prod_from_firm[product].append(self)
|
||||
# 查找与当前企业已连接的候选供应商
|
||||
lst_firm_connect = []
|
||||
if self.is_prf_conn:
|
||||
lst_firm_connect = [
|
||||
firm for firm in self.dct_cand_alt_supp_up_prod_disrupted[product]
|
||||
if self.firm_network.has_edge(self.unique_id, firm.unique_id) or
|
||||
self.firm_network.has_edge(firm.unique_id, self.unique_id)
|
||||
]
|
||||
|
||||
# 如果没有连接的供应商
|
||||
if not lst_firm_connect:
|
||||
if self.is_prf_size: # 根据规模加权选择
|
||||
lst_size = [firm.size_stat[-1][0] for firm in self.dct_cand_alt_supp_up_prod_disrupted[product]]
|
||||
lst_prob = [size / sum(lst_size) for size in lst_size]
|
||||
select_alt_supply = self.random.choices(
|
||||
self.dct_cand_alt_supp_up_prod_disrupted[product], weights=lst_prob
|
||||
)[0]
|
||||
else: # 随机选择
|
||||
select_alt_supply = self.random.choice(self.dct_cand_alt_supp_up_prod_disrupted[product])
|
||||
else: # 如果存在连接的供应商
|
||||
if self.is_prf_size: # 根据规模加权选择
|
||||
lst_firm_size = [firm.size_stat[-1][0] for firm in lst_firm_connect]
|
||||
lst_prob = [size / sum(lst_firm_size) for size in lst_firm_size]
|
||||
select_alt_supply = self.random.choices(lst_firm_connect, weights=lst_prob)[0]
|
||||
else: # 随机选择
|
||||
select_alt_supply = self.random.choice(lst_firm_connect)
|
||||
|
||||
# 检查选中的供应商是否能够生产产品
|
||||
if not select_alt_supply.is_prod_in_current_normal(product):
|
||||
# print(f"Selected supplier {select_alt_supply.unique_id} cannot produce product {product.unique_id}")
|
||||
|
||||
# 打印供应商的生产状态字典
|
||||
#print(f"Supplier production state: {select_alt_supply.dct_prod_up_prod_stat}")
|
||||
|
||||
# 检查产品是否存在于生产状态字典中
|
||||
if product in select_alt_supply.dct_prod_up_prod_stat:
|
||||
print(
|
||||
f"Product {product.unique_id} production state: {select_alt_supply.dct_prod_up_prod_stat[product]['p_stat']}")
|
||||
else:
|
||||
select_alt_supply.dct_request_prod_from_firm[product] = [self]
|
||||
print(f"Product {product.unique_id} not found in supplier production state.")
|
||||
return
|
||||
|
||||
self.dct_n_trial_up_prod_disrupted[product] += 1
|
||||
# 添加到供应商的请求字典
|
||||
if product in select_alt_supply.dct_request_prod_from_firm:
|
||||
select_alt_supply.dct_request_prod_from_firm[product].append(self)
|
||||
else:
|
||||
select_alt_supply.dct_request_prod_from_firm[product] = [self]
|
||||
|
||||
# 更新尝试次数
|
||||
self.dct_n_trial_up_prod_disrupted[product] += 1
|
||||
|
||||
def handle_request(self):
|
||||
for product, lst_firm in self.dct_request_prod_from_firm.items():
|
||||
|
||||
BIN
firm_network.pkl
Normal file
BIN
firm_network.pkl
Normal file
Binary file not shown.
BIN
iiabmdb_basic_info.sql
Normal file
BIN
iiabmdb_basic_info.sql
Normal file
Binary file not shown.
@@ -1,57 +1,32 @@
|
||||
设备id,设备残值
|
||||
51,112
|
||||
52,445
|
||||
53,870
|
||||
54,280
|
||||
55,116
|
||||
56,81
|
||||
57,710
|
||||
58,30
|
||||
59,624
|
||||
60,131
|
||||
61,476
|
||||
62,224
|
||||
63,340
|
||||
64,468
|
||||
65,97
|
||||
66,382
|
||||
67,109
|
||||
68,881
|
||||
69,673
|
||||
70,140
|
||||
71,671
|
||||
72,318
|
||||
73,779
|
||||
74,353
|
||||
75,501
|
||||
76,423
|
||||
77,815
|
||||
78,395
|
||||
79,201
|
||||
80,965
|
||||
81,286
|
||||
82,170
|
||||
83,469
|
||||
84,323
|
||||
85,31
|
||||
86,262
|
||||
87,757
|
||||
88,866
|
||||
89,570
|
||||
90,484
|
||||
91,68
|
||||
92,520
|
||||
93,691
|
||||
94,485
|
||||
95,709
|
||||
96,985
|
||||
97,792
|
||||
98,199
|
||||
99,967
|
||||
100,696
|
||||
101,967
|
||||
102,572
|
||||
103,885
|
||||
104,576
|
||||
105,253
|
||||
106,841
|
||||
59,700
|
||||
60,210
|
||||
61,350
|
||||
62,140
|
||||
63,700
|
||||
64,500
|
||||
65,700
|
||||
66,100000
|
||||
67,250
|
||||
68,350
|
||||
69,25
|
||||
70,35
|
||||
71,140
|
||||
72,140
|
||||
73,210
|
||||
74,500
|
||||
75,70
|
||||
76,21
|
||||
77,350
|
||||
78,70
|
||||
79,350
|
||||
80,21
|
||||
81,210
|
||||
82,70
|
||||
83,140
|
||||
84,70
|
||||
85,50
|
||||
86,70
|
||||
87,70
|
||||
88,70
|
||||
89,70
|
||||
|
||||
|
@@ -1,476 +1,251 @@
|
||||
Firm_Code,Product_Code
|
||||
0,1.4.4
|
||||
1,2.1.1.5
|
||||
2,1.1.3
|
||||
3,1.3.1.4
|
||||
3,1.3.1.5
|
||||
3,1.3.1.6
|
||||
3,1.3.4.1
|
||||
4,1.2.2
|
||||
5,1.4.5.3
|
||||
5,1.4.5.4
|
||||
5,1.4.5.5
|
||||
5,1.4.5.9
|
||||
6,1.3.1.2
|
||||
6,2.1.2.1
|
||||
6,2.1.2.2
|
||||
6,2.1.2.3
|
||||
6,2.1.2.4
|
||||
7,2.2
|
||||
8,1.4.1.1
|
||||
9,1.3.3.6
|
||||
9,1.3.3.7
|
||||
10,1.3.3.5
|
||||
11,1.4.4.2
|
||||
12,1.2.1
|
||||
13,1.2.2
|
||||
13,2.1.3.1
|
||||
13,2.1.3.2
|
||||
13,2.1.3.3
|
||||
13,2.1.3.4
|
||||
13,2.1.3.5
|
||||
13,2.1.3.6
|
||||
13,2.1.3.7
|
||||
13,2.1.4.1.1
|
||||
13,2.1.4.1.2
|
||||
13,2.1.4.1.3
|
||||
13,2.1.4.1.4
|
||||
13,2.1.4.2.1
|
||||
13,2.1.4.2.2
|
||||
13,2.3.1
|
||||
13,2.3.2
|
||||
13,2.3.3
|
||||
14,1.3.3.4
|
||||
14,1.3.4.3
|
||||
15,1.3.3.5
|
||||
16,1.1.3
|
||||
16,2.3.1
|
||||
16,2.3.2
|
||||
16,2.3.3
|
||||
17,1.4.2.4
|
||||
18,1.3.3.2
|
||||
19,1.4.2.1
|
||||
20,1.3.1.2
|
||||
21,1.3.1.3
|
||||
22,1.2.1
|
||||
22,1.2.2
|
||||
22,1.3.3.6
|
||||
22,2.1.1.1
|
||||
22,2.1.1.2
|
||||
22,2.1.1.3
|
||||
22,2.1.1.4
|
||||
22,2.1.1.5
|
||||
22,2.1.3.1
|
||||
22,2.1.3.2
|
||||
22,2.1.3.3
|
||||
22,2.1.3.4
|
||||
22,2.1.3.5
|
||||
22,2.1.3.6
|
||||
22,2.1.3.7
|
||||
22,2.1.4.1.1
|
||||
22,2.1.4.1.2
|
||||
22,2.1.4.1.3
|
||||
22,2.1.4.1.4
|
||||
22,2.1.4.2.1
|
||||
22,2.1.4.2.2
|
||||
22,2.3.1
|
||||
22,2.3.2
|
||||
22,2.3.3
|
||||
23,1.1.2
|
||||
23,1.3.3.1
|
||||
23,1.3.3.2
|
||||
23,1.3.3.3
|
||||
23,1.3.3.4
|
||||
23,1.4.2.7
|
||||
23,2.1.3.6
|
||||
23,2.3.1
|
||||
23,2.3.2
|
||||
23,2.3.3
|
||||
24,1.1.1
|
||||
25,1.3.1.7
|
||||
26,2.1.3.1
|
||||
26,2.1.3.2
|
||||
26,2.1.3.3
|
||||
26,2.1.3.4
|
||||
26,2.1.3.5
|
||||
26,2.1.3.6
|
||||
26,2.1.3.7
|
||||
27,1.4.4.2
|
||||
28,2.2
|
||||
29,1.3
|
||||
30,1.4.2.6
|
||||
31,1.3.3.3
|
||||
31,2.1.4.1.1
|
||||
31,2.1.4.1.2
|
||||
31,2.1.4.1.3
|
||||
31,2.1.4.1.4
|
||||
31,2.1.4.2.1
|
||||
31,2.1.4.2.2
|
||||
32,1.2.3
|
||||
33,2.1.2.1
|
||||
33,2.1.2.2
|
||||
33,2.1.2.3
|
||||
33,2.1.2.4
|
||||
34,1.3.3.3
|
||||
35,1.1.3
|
||||
36,1.1.1
|
||||
37,1.4.1.2
|
||||
37,1.4.1.4
|
||||
37,1.4.2.2
|
||||
37,1.4.3.1
|
||||
37,1.4.4.3
|
||||
37,1.4.5.2
|
||||
38,2.1.1.1
|
||||
38,2.1.1.2
|
||||
38,2.1.1.3
|
||||
38,2.1.1.4
|
||||
38,2.1.1.5
|
||||
39,1.3.1
|
||||
40,1.4.2.1
|
||||
40,1.4.2.5
|
||||
40,1.4.3.3
|
||||
40,1.4.4
|
||||
41,1.4.1.2
|
||||
41,1.4.1.5
|
||||
41,1.4.3.1
|
||||
41,1.4.3.2
|
||||
41,1.4.3.4
|
||||
41,1.4.3.5
|
||||
41,1.4.5
|
||||
42,1.3.1.1
|
||||
42,1.3.1.3
|
||||
42,1.3.1.4
|
||||
43,1.3.1.5
|
||||
43,1.3.1.6
|
||||
44,1.1.1
|
||||
45,1.3.3.1
|
||||
45,1.3.4.1
|
||||
45,1.3.4.2
|
||||
45,2.1.4.1.1
|
||||
45,2.1.4.1.2
|
||||
45,2.1.4.1.3
|
||||
45,2.1.4.1.4
|
||||
45,2.1.4.2.1
|
||||
45,2.1.4.2.2
|
||||
46,1.3.1.2
|
||||
47,2.1.1.1
|
||||
47,2.1.1.2
|
||||
47,2.1.1.3
|
||||
47,2.1.1.4
|
||||
47,2.1.2.1
|
||||
47,2.1.2.2
|
||||
47,2.1.2.3
|
||||
47,2.1.2.4
|
||||
47,2.1.3.6
|
||||
48,1.2.2
|
||||
49,1.3.1.1
|
||||
49,1.3.1.4
|
||||
49,1.3.1.6
|
||||
49,1.3.3.1
|
||||
49,2.1.2.1
|
||||
49,2.1.2.2
|
||||
49,2.1.2.3
|
||||
49,2.1.2.4
|
||||
50,1.3.1.5
|
||||
51,1.4.2.1
|
||||
52,1.4.5.5
|
||||
53,1.4.1.3
|
||||
53,1.4.1.4
|
||||
53,1.4.1.5
|
||||
53,1.4.2.3
|
||||
53,1.4.2.4
|
||||
53,1.4.3.3
|
||||
53,1.4.3.4
|
||||
53,1.4.3.5
|
||||
53,1.4.3.6
|
||||
53,1.4.4.4
|
||||
53,1.4.5.2
|
||||
53,1.4.5.3
|
||||
53,1.4.5.6
|
||||
53,1.4.5.7
|
||||
53,1.4.5.8
|
||||
54,1.4.1.3
|
||||
54,1.4.2.4
|
||||
54,1.4.4.3
|
||||
55,1.4.1.1
|
||||
55,1.4.1.2
|
||||
55,1.4.1.3
|
||||
55,1.4.2.1
|
||||
55,1.4.2.2
|
||||
55,1.4.4.4
|
||||
56,1.1.1
|
||||
56,1.3.1.7
|
||||
57,1.3.3.3
|
||||
57,2.3.1
|
||||
57,2.3.2
|
||||
57,2.3.3
|
||||
58,1.2.2
|
||||
58,1.3.1.6
|
||||
58,1.3.2
|
||||
58,1.3.4.1
|
||||
58,1.3.4.2
|
||||
58,1.3.4.3
|
||||
58,2.1.2
|
||||
59,1.4.2.5
|
||||
60,2.1.1.1
|
||||
60,2.1.1.2
|
||||
60,2.1.1.3
|
||||
60,2.1.1.4
|
||||
60,2.1.1.5
|
||||
61,1.3.3.3
|
||||
62,1.3.1.2
|
||||
62,2.1.2.1
|
||||
62,2.1.2.2
|
||||
62,2.1.2.3
|
||||
62,2.1.2.4
|
||||
63,1.4.1.1
|
||||
63,1.4.2.4
|
||||
63,1.4.4.5
|
||||
64,1.1.2
|
||||
65,1.2.1
|
||||
66,1.2.1
|
||||
67,1.2
|
||||
68,1.3.1.1
|
||||
68,1.3.1.2
|
||||
68,1.3.1.3
|
||||
69,1.1.1
|
||||
70,1.3.3.2
|
||||
70,1.3.3.4
|
||||
71,1.3.1.2
|
||||
72,1.3.1.2
|
||||
73,2.1.3
|
||||
74,1.3.3.2
|
||||
74,2.1.3
|
||||
75,1.3.3
|
||||
76,1.3.1.3
|
||||
77,1.3.3.6
|
||||
77,1.3.4
|
||||
78,2.1.1.1
|
||||
78,2.1.1.2
|
||||
78,2.1.1.3
|
||||
78,2.1.1.4
|
||||
78,2.1.1.5
|
||||
79,1.3.1.1
|
||||
79,1.3.1.4
|
||||
79,1.3.1.6
|
||||
79,2.1.2
|
||||
79,2.1.3.1
|
||||
79,2.1.3.2
|
||||
79,2.1.3.3
|
||||
79,2.1.3.4
|
||||
79,2.1.3.5
|
||||
79,2.1.3.6
|
||||
79,2.1.3.7
|
||||
79,2.1.4.1
|
||||
79,2.1.4.2
|
||||
79,2.3.1
|
||||
79,2.3.2
|
||||
79,2.3.3
|
||||
80,1.3.4
|
||||
80,2.1.1
|
||||
81,1.3.4
|
||||
81,2.1.2
|
||||
81,2.1.4.1
|
||||
81,2.1.4.2
|
||||
82,2.1.2.1
|
||||
82,2.1.2.2
|
||||
82,2.1.2.3
|
||||
82,2.1.2.4
|
||||
83,1.3.3.2
|
||||
84,2.1.2
|
||||
84,2.1.4
|
||||
84,2.3
|
||||
85,1.3.1
|
||||
85,2.1.1
|
||||
86,1.1
|
||||
87,1.1.1
|
||||
88,1.1.3
|
||||
89,1.1.2
|
||||
89,1.2.1
|
||||
89,1.3.3.1
|
||||
90,1.3.1.7
|
||||
91,1.2.1
|
||||
92,1.3.3.4
|
||||
93,1.3.1
|
||||
94,1.1
|
||||
95,1.2.3
|
||||
95,2.3
|
||||
96,1.2.1
|
||||
96,1.2.3
|
||||
97,1.2
|
||||
97,1.3.3
|
||||
97,2.1.3
|
||||
98,2
|
||||
99,1.1.2
|
||||
99,1.2.1
|
||||
99,1.3.1
|
||||
99,1.3.3
|
||||
99,2.1
|
||||
99,2.3
|
||||
100,1.3.1
|
||||
101,1.1.1
|
||||
102,2
|
||||
102,2.1.4
|
||||
103,1.1.1
|
||||
104,1.1.1
|
||||
105,1.1
|
||||
106,1.1
|
||||
106,1.2
|
||||
106,1.3
|
||||
106,2.1.1
|
||||
106,2.1.3
|
||||
106,2.2
|
||||
107,1.4.3.3
|
||||
108,2.1.3
|
||||
108,2.2
|
||||
109,1.3.3.1
|
||||
110,1.3.3.5
|
||||
111,1.3.1.6
|
||||
111,1.3.3.1
|
||||
111,1.3.4.1
|
||||
112,1.3.3.7
|
||||
113,1.1.1
|
||||
114,1.3.5.1
|
||||
115,1.1.3
|
||||
115,2.1.4
|
||||
116,1.3.1.7
|
||||
117,2.1.1.1
|
||||
117,2.1.1.2
|
||||
117,2.1.1.3
|
||||
117,2.1.1.4
|
||||
117,2.1.1.5
|
||||
117,2.1.4.1.1
|
||||
117,2.1.4.1.2
|
||||
117,2.1.4.1.3
|
||||
117,2.1.4.1.4
|
||||
117,2.1.4.2.1
|
||||
117,2.1.4.2.2
|
||||
118,1.3.3.6
|
||||
119,1.3.1.1
|
||||
120,1.2.3
|
||||
121,1.4.2.4
|
||||
122,1.4.2.6
|
||||
123,1.1.2
|
||||
124,1.2.1
|
||||
124,2.3
|
||||
125,1.2.3
|
||||
126,1.1
|
||||
126,1.2
|
||||
126,1.4
|
||||
126,2.1.1.5
|
||||
126,2.1.3
|
||||
126,2.2
|
||||
126,2.3
|
||||
127,1.1.1
|
||||
127,1.1.3
|
||||
128,1.1.2
|
||||
129,1.1.2
|
||||
129,1.2.3
|
||||
130,1.3.2
|
||||
130,1.3.4.1
|
||||
130,1.3.4.2
|
||||
130,1.3.4.3
|
||||
130,1.3.5
|
||||
131,2.1.1.1
|
||||
131,2.1.1.2
|
||||
131,2.1.1.3
|
||||
131,2.1.1.4
|
||||
131,2.1.1.5
|
||||
132,1.3.3.2
|
||||
133,1.4.1.3
|
||||
133,1.4.4.1
|
||||
134,1.3.3.5
|
||||
135,1.1.3
|
||||
135,1.3.2.1
|
||||
135,1.3.4.1
|
||||
135,2.1.3.1
|
||||
135,2.1.3.2
|
||||
135,2.1.3.3
|
||||
135,2.1.3.4
|
||||
135,2.1.3.5
|
||||
135,2.1.3.6
|
||||
135,2.1.3.7
|
||||
135,2.2
|
||||
136,1.2.1
|
||||
137,2.1.4.1.1
|
||||
137,2.1.4.1.2
|
||||
137,2.1.4.1.3
|
||||
137,2.1.4.1.4
|
||||
137,2.1.4.2.1
|
||||
137,2.1.4.2.2
|
||||
138,1.3.1.5
|
||||
139,1.3.3.7
|
||||
140,1.4.1.1
|
||||
140,1.4.1.4
|
||||
140,1.4.1.5
|
||||
140,1.4.5.1
|
||||
140,1.4.5.3
|
||||
140,1.4.5.4
|
||||
140,1.4.5.9
|
||||
141,1.3.3.2
|
||||
142,1.4.1.1
|
||||
142,1.4.2
|
||||
142,1.4.3
|
||||
143,2.1.1.1
|
||||
143,2.1.1.2
|
||||
143,2.1.1.3
|
||||
143,2.1.1.4
|
||||
143,2.1.1.5
|
||||
144,2.1.2.1
|
||||
144,2.1.2.2
|
||||
144,2.1.2.3
|
||||
144,2.1.2.4
|
||||
145,1.3.1.4
|
||||
146,1.3.1.1
|
||||
147,1.1.2
|
||||
148,2.1.1
|
||||
148,2.1.3
|
||||
148,2.2
|
||||
149,2.1.2.1
|
||||
149,2.1.2.2
|
||||
149,2.1.2.3
|
||||
149,2.1.2.4
|
||||
150,1.1.1
|
||||
151,1.3.5.1
|
||||
152,1.4.4.1
|
||||
153,1.3.1.1
|
||||
153,1.3.1.4
|
||||
154,2.1.4.1.1
|
||||
154,2.1.4.1.2
|
||||
154,2.1.4.1.3
|
||||
154,2.1.4.1.4
|
||||
154,2.1.4.2.1
|
||||
154,2.1.4.2.2
|
||||
155,2.3
|
||||
156,1.3.1.7
|
||||
157,1.4.1
|
||||
158,1.4.4.1
|
||||
159,2.1.2
|
||||
160,1.4.1.3
|
||||
161,2.3.1
|
||||
161,2.3.2
|
||||
161,2.3.3
|
||||
162,1.4.5.6
|
||||
162,1.4.5.7
|
||||
163,2.1.4.1.1
|
||||
163,2.1.4.1.2
|
||||
163,2.1.4.1.3
|
||||
163,2.1.4.1.4
|
||||
163,2.1.4.2.1
|
||||
163,2.1.4.2.2
|
||||
164,1.3.3.6
|
||||
165,2.1.2.1
|
||||
165,2.1.2.2
|
||||
165,2.1.2.3
|
||||
165,2.1.2.4
|
||||
166,1.2.3
|
||||
167,1.1.1
|
||||
168,1.1.2
|
||||
168,1.3.3.1
|
||||
168,1.3.3.2
|
||||
168,1.3.3.4
|
||||
168,2.3.1
|
||||
168,2.3.2
|
||||
168,2.3.3
|
||||
169,1.1.1
|
||||
170,1
|
||||
Firm_Code,Product_Code
|
||||
7,7
|
||||
771821595,7
|
||||
9,8
|
||||
2339188563,8
|
||||
453289520,8
|
||||
3442780535,2514
|
||||
25228347,2514
|
||||
2316161851,2514
|
||||
25685135,2515
|
||||
720737055,2515
|
||||
413274977,2714
|
||||
2317841563,2714
|
||||
888356483,2714
|
||||
607512171,2714
|
||||
343012684,2715
|
||||
750610681,2715
|
||||
3111033905,2716
|
||||
43407343,2716
|
||||
25945288,2716
|
||||
3069206426,2716
|
||||
930767828,2717
|
||||
3407754893,2717
|
||||
152008168,2718
|
||||
571058167,2718
|
||||
448033045,2718
|
||||
2320475044,2718
|
||||
301209792,32338
|
||||
888395016,32338
|
||||
2317245827,32338
|
||||
631449822,32338
|
||||
3215814536,32338
|
||||
2327031723,32338
|
||||
194210021,32338
|
||||
70634828,32338
|
||||
3048263744,32338
|
||||
3147511625,32338
|
||||
2354145351,32338
|
||||
653528340,32338
|
||||
191912252,32338
|
||||
2348941764,32338
|
||||
3103797386,32338
|
||||
420984285,32432
|
||||
4208851809,32432
|
||||
203314437,32433
|
||||
3089095447,32433
|
||||
4518234098,32434
|
||||
3344297292,32434
|
||||
271860868,32434
|
||||
2545430247,32435
|
||||
3045721313,32435
|
||||
3433628561,32436
|
||||
868012326,32436
|
||||
5849940,32437
|
||||
2424229017,32437
|
||||
3100891962,32437
|
||||
29954548,32438
|
||||
594378026,32438
|
||||
3047163873,32438
|
||||
71271700,32438
|
||||
2329375731,32439
|
||||
25036634,32439
|
||||
1217957486,32439
|
||||
593312758,32439
|
||||
2310825263,32440
|
||||
3026382513,32440
|
||||
620220747,32440
|
||||
996174506,32440
|
||||
2327979389,32441
|
||||
3462551351,32441
|
||||
11807506,32443
|
||||
3133307899,32443
|
||||
251189644,32443
|
||||
829768,32443
|
||||
695995052,32445
|
||||
887840774,32445
|
||||
26516263,32445
|
||||
3221190269,32446
|
||||
3372913783,32446
|
||||
27731896,32446
|
||||
3373311444,32446
|
||||
3269940677,32447
|
||||
3226664625,32447
|
||||
400488703,32447
|
||||
1452048,32448
|
||||
688155470,32448
|
||||
2424229017,32448
|
||||
213386023,32449
|
||||
495782506,32449
|
||||
2311581270,32449
|
||||
3445244192,32450
|
||||
2337952436,32450
|
||||
3177507356,32450
|
||||
3025036704,32451
|
||||
2352036411,32451
|
||||
581407487,34524
|
||||
354897041,34524
|
||||
762985858,34524
|
||||
3188352290,34525
|
||||
3384021594,34525
|
||||
2010673,34525
|
||||
857978527,34526
|
||||
2326478786,34526
|
||||
11807506,34526
|
||||
11164476478,34526
|
||||
1549474227,34527
|
||||
24673506,34527
|
||||
2324844174,34527
|
||||
1375606900,34527
|
||||
80158773,34528
|
||||
159511306,34528
|
||||
2343704209,34528
|
||||
549184982,34528
|
||||
151606446,34529
|
||||
1033972427,34529
|
||||
654825436,34529
|
||||
2347013470,34529
|
||||
27075840,34530
|
||||
3188903709,34530
|
||||
474279224,34531
|
||||
3373311444,34531
|
||||
3267688490,34532
|
||||
3395900897,34532
|
||||
2316990095,34533
|
||||
591452402,34533
|
||||
278221281,34533
|
||||
2728939,34534
|
||||
1128343125,34534
|
||||
1452048,34534
|
||||
3312358902,34535
|
||||
3031009366,34535
|
||||
3070859372,34537
|
||||
2820140348,34537
|
||||
3271705843,34537
|
||||
5007015990,34538
|
||||
1679596339,34538
|
||||
3203777710,34538
|
||||
2339684065,34538
|
||||
1307012237,34539
|
||||
615763365,34539
|
||||
145511905,34539
|
||||
400692942,34539
|
||||
872394725,34543
|
||||
2333843479,34543
|
||||
22324879,34544
|
||||
59234665,34544
|
||||
11212932825,34545
|
||||
2791956547,34545
|
||||
2379638202,34545
|
||||
774948022,34545
|
||||
2481687500,34546
|
||||
16190441,34546
|
||||
2312693498,34546
|
||||
2944404352,34546
|
||||
3407754893,34547
|
||||
2728939,34547
|
||||
1232020820,34547
|
||||
677887241,34547
|
||||
888662519,34548
|
||||
2317695802,34548
|
||||
24673506,34549
|
||||
1601593550,34549
|
||||
2337843112,34549
|
||||
4144746564,34550
|
||||
259325842,34550
|
||||
314284469,34551
|
||||
2388955897,34551
|
||||
2352951203,34552
|
||||
239053033,34552
|
||||
3444191691,34552
|
||||
830662620,34553
|
||||
2350111843,34553
|
||||
68804111,34554
|
||||
3029702382,34554
|
||||
11220388001,34554
|
||||
3409328588,34555
|
||||
4037576402,34555
|
||||
74680108,34556
|
||||
2321857672,34556
|
||||
3391580446,34556
|
||||
3398677646,34557
|
||||
2349656760,34557
|
||||
3120341363,34557
|
||||
2350418059,34557
|
||||
31654817,34558
|
||||
397847929,34558
|
||||
3331430009,34558
|
||||
2334283182,34558
|
||||
359737460,34566
|
||||
499022815,34566
|
||||
2311541114,34567
|
||||
2977767486,34567
|
||||
525126393,34568
|
||||
2321173423,34568
|
||||
1186341289,34569
|
||||
658759701,34569
|
||||
33822284,34569
|
||||
2359644835,34570
|
||||
1428342684,34570
|
||||
2352538239,34571
|
||||
144312602,34571
|
||||
25624519,34571
|
||||
2965658107,34571
|
||||
18065940,34572
|
||||
500189853,34572
|
||||
2349168009,34572
|
||||
3151203276,34573
|
||||
249316393,34573
|
||||
3006753238,34573
|
||||
24673506,34573
|
||||
1010117174,34574
|
||||
640320,34574
|
||||
2312490120,36914
|
||||
503176785,36914
|
||||
644292599,46504
|
||||
863079,46504
|
||||
2341555098,46504
|
||||
26162741,46504
|
||||
3195502499,46505
|
||||
2320102626,46505
|
||||
2324787028,46505
|
||||
2311838590,56319
|
||||
3122923980,56319
|
||||
3211956484,56319
|
||||
737770776,56319
|
||||
7299120,56320
|
||||
3127420424,56320
|
||||
2313209417,56320
|
||||
15613202,56320
|
||||
3288105727,56321
|
||||
5278074,56321
|
||||
517717050,56321
|
||||
483081978,56321
|
||||
3072715478,56322
|
||||
561545339,56322
|
||||
218633337,56322
|
||||
3113895788,56323
|
||||
118882692,56323
|
||||
24284343,56323
|
||||
888478182,56341
|
||||
1606833003,56341
|
||||
560866402,56341
|
||||
3299144127,317589
|
||||
2321109759,317589
|
||||
3445928818,317589
|
||||
2311838590,513738
|
||||
9746245,513738
|
||||
2624175,513742
|
||||
25685135,513742
|
||||
2944892892,513742
|
||||
3269039233,513742
|
||||
|
||||
|
@@ -1,171 +0,0 @@
|
||||
Code,原材料,库存商品,设备数量,Revenue,Total Employees (People),Type_Region,Self-supply Business (Yes/No),Revenue_Log,production_output,demand_quantity
|
||||
0,181.81,641.66,728.05,87929.36,201,Rural,Yes,11.384289043829558,375.805,273.181
|
||||
1,563.58,957.81,555.95,87873.23,953,Rural,Yes,11.383650486662598,501.595,232.358
|
||||
2,580.85,890.49,437.24,69639.0,578,Rural,Yes,11.151080034215557,478.724,188.085
|
||||
3,973.37,993.31,468.34,44580.21,997,Suburban,No,10.705045317561336,435.834,373.337
|
||||
4,241.84,285.02,483.51,21252.13,808,Urban,Yes,9.96421240462346,158.351,405.184
|
||||
5,368.0,315.75,525.42,94743.97,578,Urban,No,11.458933479758539,245.542,332.8
|
||||
6,889.86,353.18,223.03,67882.65,79,Rural,No,11.12553575806758,284.303,494.986
|
||||
7,203.75,914.91,971.29,55768.34,195,Urban,Yes,10.92896160383392,240.129,212.375
|
||||
8,243.51,639.94,849.47,74211.92,860,Suburban,Yes,11.21468006315341,248.947,135.351
|
||||
9,835.96,867.4,182.11,28603.45,850,Suburban,Yes,10.261282618903437,364.211,188.596
|
||||
10,689.06,935.11,679.15,81506.9,63,Rural,Yes,11.308442958221967,543.915,395.906
|
||||
11,729.56,823.94,570.66,39513.14,817,Urban,Yes,10.584388553798581,217.066,382.956
|
||||
12,743.22,796.77,994.43,35647.21,628,Suburban,No,10.481426161910335,335.443,259.322
|
||||
13,434.41,627.26,640.54,95550.17,312,Urban,Yes,11.467406728840045,521.054,465.44100000000003
|
||||
14,218.51,265.34,831.5,74163.89,575,Rural,Yes,11.214032653017249,336.15,349.851
|
||||
15,324.18,651.97,628.53,65263.67,976,Urban,No,11.086190805158187,277.853,474.418
|
||||
16,263.97,560.28,936.33,71442.85,281,Urban,Yes,11.176653108371672,423.63300000000004,356.397
|
||||
17,826.3,337.48,354.44,39720.11,636,Suburban,No,10.589612887540975,428.444,310.63
|
||||
18,157.45,801.45,438.72,53164.35,586,Suburban,No,10.881143337921856,440.872,342.745
|
||||
19,857.4,256.3,336.24,26539.89,962,Rural,No,10.186404163190344,193.624,348.74
|
||||
20,818.54,756.38,396.87,31441.28,520,Rural,Yes,10.355876958182606,502.687,570.854
|
||||
21,403.99,705.79,826.47,56932.63,390,Suburban,Yes,10.949623917962214,518.647,434.399
|
||||
22,685.33,651.77,178.3,84452.8,774,Rural,No,11.343948077399748,285.83,399.533
|
||||
23,822.29,347.16,496.38,39599.95,563,Rural,No,10.586583134615513,316.638,484.229
|
||||
24,974.83,177.56,867.46,40712.78,330,Suburban,No,10.614297327055466,225.746,440.483
|
||||
25,439.19,804.07,984.96,84754.7,164,Rural,Yes,11.347516480932141,350.496,198.91899999999998
|
||||
26,792.91,452.82,968.22,20146.61,937,Urban,No,9.910791315007794,260.822,471.291
|
||||
27,760.28,342.11,403.48,72939.31,272,Rural,Yes,11.19738300448793,395.348,563.028
|
||||
28,138.05,932.66,775.93,18503.91,344,Urban,Yes,9.825737340086217,444.59299999999996,196.805
|
||||
29,149.76,537.24,492.6,32927.81,570,Rural,Yes,10.402072868451919,215.26,185.976
|
||||
30,979.46,249.46,491.61,82109.54,129,Urban,No,11.315809488446245,268.161,231.946
|
||||
31,338.04,911.44,390.13,63876.58,147,Rural,Yes,11.064708063012214,445.013,336.804
|
||||
32,650.75,215.55,536.88,85274.44,583,Rural,No,11.353630040276132,270.688,561.075
|
||||
33,198.36,555.99,513.68,18940.55,820,Urban,Yes,9.849060405389194,256.368,445.836
|
||||
34,928.72,675.62,330.83,75800.87,320,Rural,No,11.235865049137155,256.08299999999997,216.872
|
||||
35,980.62,893.25,371.57,54696.03,854,Urban,Yes,10.909546408079658,439.157,382.062
|
||||
36,816.55,334.59,506.43,55963.31,690,Rural,Yes,10.932451576422585,428.64300000000003,375.655
|
||||
37,811.93,613.86,689.11,42557.86,823,Rural,Yes,10.658619840796458,276.911,537.193
|
||||
38,233.05,373.08,577.32,80566.43,530,Urban,Yes,11.296837340493292,277.732,518.305
|
||||
39,809.83,356.18,755.38,99458.16,457,Suburban,Yes,11.507492332198147,369.538,550.983
|
||||
40,621.2,522.25,595.01,87316.4,661,Suburban,No,11.37729358214565,526.501,367.12
|
||||
41,907.65,730.64,830.85,30436.2,310,Urban,No,10.323387968440548,203.085,361.765
|
||||
42,220.93,688.61,996.21,41344.79,794,Suburban,Yes,10.629701694931855,413.621,374.093
|
||||
43,117.81,576.3,264.84,15830.0,784,Rural,Yes,9.669662152875057,374.484,182.781
|
||||
44,830.95,800.85,102.52,13639.33,635,Rural,Yes,9.520712809956411,392.252,355.095
|
||||
45,675.16,304.52,977.42,47128.26,762,Urban,No,10.760628100076477,206.742,370.51599999999996
|
||||
46,361.35,271.19,922.51,62800.89,766,Suburban,Yes,11.047724524330391,504.251,534.135
|
||||
47,277.52,628.81,310.08,19127.61,666,Rural,No,9.858888119971708,422.008,183.752
|
||||
48,768.86,962.58,169.23,82513.95,709,Rural,No,11.320722648937608,324.923,553.886
|
||||
49,640.49,256.78,477.52,96026.28,989,Urban,Yes,11.472377182987278,228.752,202.049
|
||||
50,703.49,572.21,670.69,41241.23,374,Urban,No,10.627193763098349,467.069,490.349
|
||||
51,603.88,740.35,384.55,65698.37,790,Urban,Yes,11.092829394423687,170.45499999999998,362.388
|
||||
52,972.13,799.44,927.28,95157.56,935,Urban,Yes,11.463289323062517,397.728,491.21299999999997
|
||||
53,193.37,697.4,243.1,98193.26,605,Suburban,Yes,11.494692856549156,390.31,426.337
|
||||
54,849.98,196.48,927.78,83414.35,973,Suburban,Yes,11.33157563589593,293.778,382.998
|
||||
55,953.18,770.12,207.4,55392.45,498,Suburban,No,10.922198581859748,202.74,563.318
|
||||
56,381.56,998.22,860.09,62313.91,335,Suburban,Yes,11.039939954331839,382.009,207.156
|
||||
57,644.79,521.74,355.78,75289.45,713,Urban,No,11.229095297730488,402.578,291.479
|
||||
58,505.59,860.44,789.47,25900.97,585,Urban,Yes,10.162035698723782,182.947,406.55899999999997
|
||||
59,369.43,872.67,895.61,63241.28,675,Rural,No,11.05471253147278,416.56100000000004,423.943
|
||||
60,419.27,513.8,452.13,51223.88,838,Urban,No,10.843961108544011,309.213,205.927
|
||||
61,196.58,924.12,338.96,28298.88,859,Rural,No,10.250577506876448,457.896,364.658
|
||||
62,890.61,305.66,713.32,50412.81,282,Rural,Yes,10.828000588431252,299.332,397.06100000000004
|
||||
63,234.83,181.61,104.55,15073.36,361,Suburban,No,9.62068422629099,279.455,271.483
|
||||
64,889.35,562.21,116.14,77654.42,784,Rural,Yes,11.260023749043118,337.614,523.935
|
||||
65,179.85,369.62,180.93,69888.63,840,Suburban,Yes,11.15465825404697,422.093,247.985
|
||||
66,238.0,309.39,564.85,51633.14,940,Suburban,Yes,10.851918993378646,537.485,205.8
|
||||
67,178.8,934.8,898.22,45553.24,99,Rural,Yes,10.726637030784127,430.822,281.88
|
||||
68,705.91,321.96,196.64,34943.76,857,Suburban,Yes,10.461495190949123,241.664,257.591
|
||||
69,417.35,650.65,516.24,40390.81,873,Rural,Yes,10.606357562825298,329.624,242.735
|
||||
70,143.56,132.64,319.8,31165.9,509,Suburban,Yes,10.347079827375628,418.98,503.356
|
||||
71,636.49,620.16,375.48,35974.77,861,Urban,Yes,10.49057313840643,260.548,295.649
|
||||
72,356.74,585.65,467.6,32974.8,250,Rural,Yes,10.403498912366212,538.76,409.674
|
||||
73,647.81,566.75,659.68,37617.13,524,Suburban,No,10.535214810736983,263.96799999999996,300.781
|
||||
74,263.94,828.9,574.78,76153.93,410,Urban,Yes,11.240511965658731,438.478,361.394
|
||||
75,905.98,734.15,692.96,13377.47,651,Urban,Yes,9.501327227611464,363.296,469.598
|
||||
76,292.05,243.65,522.28,49923.72,529,Urban,Yes,10.81825151949766,482.228,350.205
|
||||
77,393.86,999.51,735.64,12433.38,415,Urban,No,9.42814007030796,535.564,303.386
|
||||
78,517.7,326.34,529.63,54028.27,874,Urban,Yes,10.89726270707692,230.963,504.77
|
||||
79,498.02,282.95,933.3,25192.21,482,Rural,No,10.134290098725792,280.33,480.802
|
||||
80,199.15,401.59,289.82,22092.58,672,Rural,No,10.002997084523999,486.98199999999997,202.915
|
||||
81,954.83,314.75,347.98,67309.26,972,Urban,Yes,11.117053099035545,248.798,465.483
|
||||
82,338.55,394.23,140.73,31921.77,182,Suburban,Yes,10.371043501154208,385.073,275.855
|
||||
83,120.84,244.32,962.47,37341.68,855,Suburban,Yes,10.527865408049326,263.247,117.084
|
||||
84,941.7,232.22,840.66,64891.57,371,Urban,Yes,11.08047300211371,269.06600000000003,476.17
|
||||
85,643.17,912.04,990.06,86883.99,914,Rural,Yes,11.372329059527587,355.006,411.317
|
||||
86,678.76,791.29,717.2,69956.18,334,Rural,Yes,11.155624325011686,384.72,515.876
|
||||
87,231.47,396.41,659.0,13992.44,602,Rural,No,9.546272462744886,549.9,495.147
|
||||
88,784.71,953.34,450.9,93706.25,760,Rural,No,11.447920168243213,519.09,365.471
|
||||
89,113.94,508.95,223.49,39526.07,935,Rural,Yes,10.584715733184998,353.349,172.394
|
||||
90,606.5,550.16,774.11,21875.64,57,Rural,Yes,9.99312896794069,516.4110000000001,309.65
|
||||
91,447.17,663.18,423.41,23303.28,170,Rural,Yes,10.056349402178457,240.341,366.717
|
||||
92,611.27,585.54,959.77,76513.0,513,Rural,No,11.245215940017895,440.977,300.127
|
||||
93,902.52,379.67,796.35,51981.86,591,Urban,Yes,10.858650090548744,281.635,361.252
|
||||
94,301.42,490.92,480.54,26329.43,179,Rural,Yes,10.178442603946115,409.054,406.142
|
||||
95,819.3,826.17,491.49,90948.99,995,Suburban,No,11.418054078881859,240.149,414.93
|
||||
96,911.38,265.66,592.57,20074.86,870,Rural,Yes,9.907223564942575,423.257,283.13800000000003
|
||||
97,779.57,543.64,929.73,14326.93,833,Rural,Yes,9.56989626200163,460.973,351.957
|
||||
98,153.96,660.67,354.21,83007.2,745,Urban,No,11.326682630004385,318.421,433.396
|
||||
99,932.37,892.01,202.12,60293.69,887,Urban,No,11.00698273379035,210.212,285.23699999999997
|
||||
100,126.64,832.47,671.04,96563.41,475,Urban,No,11.477955169978017,218.10399999999998,398.664
|
||||
101,270.89,706.51,300.61,90204.11,749,Suburban,No,11.409830270422843,311.061,477.089
|
||||
102,482.48,958.61,183.12,43168.79,593,Rural,No,10.67287305943306,471.312,325.248
|
||||
103,990.28,733.96,469.56,76332.37,994,Rural,No,11.242852373701297,227.95600000000002,261.028
|
||||
104,388.18,850.49,435.17,32055.5,785,Urban,Yes,10.375224054490317,485.517,453.818
|
||||
105,984.39,414.52,197.17,33821.73,736,Urban,Yes,10.428858774308102,402.717,293.43899999999996
|
||||
106,761.21,183.54,281.11,55013.96,260,Rural,Yes,10.915342250190042,481.111,388.121
|
||||
107,331.91,279.02,877.44,53710.83,362,Urban,No,10.891369936140743,244.744,530.191
|
||||
108,469.56,264.7,851.26,76110.9,575,Rural,No,11.239946766181669,251.126,345.956
|
||||
109,971.54,881.07,334.09,58867.43,578,Suburban,Yes,10.983043245557232,199.409,391.154
|
||||
110,517.61,616.48,893.11,72042.76,787,Rural,No,11.185015110604866,523.311,473.761
|
||||
111,400.81,368.37,725.7,23609.77,891,Suburban,Yes,10.069415888397208,366.57,175.08100000000002
|
||||
112,453.79,493.83,974.96,90456.84,167,Rural,Yes,11.412628109854797,411.496,427.379
|
||||
113,941.13,837.6,410.3,32438.24,520,Suburban,Yes,10.38709325275015,364.03,224.113
|
||||
114,748.24,400.21,504.45,41249.5,921,Urban,No,10.627394270477243,218.445,541.824
|
||||
115,133.89,994.03,956.81,87486.73,685,Rural,No,11.379242403701742,341.681,283.389
|
||||
116,215.17,615.03,922.44,57195.4,479,Suburban,No,10.954228754553641,340.244,150.517
|
||||
117,273.3,200.4,702.29,91578.5,282,Urban,Yes,11.424951806954867,468.229,389.33
|
||||
118,727.88,435.23,623.45,88235.21,802,Rural,No,11.387761368682435,467.345,246.788
|
||||
119,500.21,244.24,743.84,88539.28,213,Urban,Yes,11.391201574335291,198.38400000000001,289.021
|
||||
120,492.05,549.08,197.37,36497.09,698,Suburban,Yes,10.504987810364897,293.737,524.205
|
||||
121,242.04,645.31,338.0,15847.92,625,Suburban,No,9.670793540410068,288.8,503.204
|
||||
122,169.61,943.12,489.47,94776.28,339,Rural,No,11.459274445964661,396.947,284.961
|
||||
123,997.7,668.06,149.31,85691.25,924,Urban,No,11.358505999023217,249.931,254.77
|
||||
124,980.24,952.38,156.39,64771.22,488,Urban,Yes,11.078616647880379,249.639,320.024
|
||||
125,823.52,620.72,152.73,80077.4,167,Urban,Yes,11.290748945929552,183.273,482.352
|
||||
126,518.56,264.76,894.63,21886.95,544,Urban,Yes,9.99364584778038,392.46299999999997,459.856
|
||||
127,516.9,541.19,284.53,79221.17,481,Urban,Yes,11.279998840064575,168.453,416.69
|
||||
128,479.06,821.23,812.31,45671.01,578,Rural,Yes,10.729219021108582,574.231,207.906
|
||||
129,864.87,370.37,627.0,99571.15,335,Rural,No,11.508627742978986,166.7,538.487
|
||||
130,106.9,451.78,741.94,84024.35,712,Suburban,Yes,11.338861916770467,338.194,378.69
|
||||
131,480.63,972.01,956.7,30156.57,517,Suburban,Yes,10.31415808886406,558.67,243.063
|
||||
132,467.69,512.18,484.88,26439.75,636,Rural,No,10.18262383855027,458.488,496.769
|
||||
133,338.95,482.23,735.23,65016.58,500,Suburban,Yes,11.082397593274264,225.523,355.895
|
||||
134,396.97,167.31,970.9,16871.64,796,Urban,Yes,9.73338938480437,501.09000000000003,360.697
|
||||
135,443.34,726.96,811.81,19889.06,186,Suburban,Yes,9.89792511080162,528.181,533.334
|
||||
136,900.26,735.27,322.44,73358.44,674,Suburban,Yes,11.203112841709697,335.244,343.026
|
||||
137,298.84,960.18,833.89,32517.38,521,Rural,Yes,10.38952999461049,355.389,338.884
|
||||
138,514.11,138.94,403.06,73790.3,600,Rural,No,11.208982565635692,373.306,287.411
|
||||
139,563.71,895.07,230.42,35866.03,717,Rural,No,10.487545886954793,239.042,317.371
|
||||
140,233.85,759.24,700.57,65060.34,787,Rural,No,11.083070425958969,232.05700000000002,271.385
|
||||
141,931.02,738.56,668.2,77652.7,697,Urban,Yes,11.260001599382495,521.82,392.102
|
||||
142,212.83,695.04,321.17,18167.74,646,Rural,Yes,9.807402772806727,455.117,180.28300000000002
|
||||
143,924.34,205.86,558.88,52162.63,780,Suburban,Yes,10.86212161710854,425.888,415.43399999999997
|
||||
144,249.21,863.7,749.47,84617.29,62,Urban,No,11.34589389823535,207.947,349.921
|
||||
145,726.16,794.73,746.1,62798.43,763,Rural,No,11.047685352143786,310.61,533.616
|
||||
146,948.13,792.63,192.63,73034.29,730,Suburban,No,11.19868433587119,204.263,380.813
|
||||
147,270.83,206.89,219.69,13885.75,153,Urban,No,9.53861841340637,288.969,487.08299999999997
|
||||
148,272.47,649.86,407.02,58794.83,719,Suburban,No,10.981809204851006,230.702,388.247
|
||||
149,896.82,782.03,746.84,81132.02,590,Suburban,Yes,11.303832983390505,402.68399999999997,300.682
|
||||
150,589.6,665.02,990.66,34608.49,157,Urban,Yes,10.45185430666866,433.06600000000003,160.96
|
||||
151,643.56,747.96,727.56,70969.34,259,Urban,No,11.170003231771686,381.756,509.356
|
||||
152,197.82,825.05,703.02,82097.85,105,Urban,Yes,11.315667107521492,502.302,422.782
|
||||
153,894.06,451.21,306.92,74212.65,254,Urban,No,11.214689899799728,425.692,541.406
|
||||
154,543.93,974.84,140.75,83785.49,519,Urban,No,11.336015121119924,288.075,240.393
|
||||
155,319.43,298.48,775.91,45520.75,824,Rural,Yes,10.725923544938645,469.591,279.943
|
||||
156,233.39,615.17,724.77,90675.17,284,Rural,Yes,11.415038838977027,389.477,354.339
|
||||
157,928.81,981.92,359.93,92439.1,235,Urban,No,11.434305328295919,454.993,273.881
|
||||
158,704.18,559.39,182.05,44391.3,820,Rural,Yes,10.700798783274456,337.205,528.418
|
||||
159,154.02,251.18,865.35,98398.02,360,Suburban,No,11.496775960886676,291.53499999999997,364.402
|
||||
160,275.54,406.26,568.47,27050.68,69,Suburban,No,10.20546742259082,520.847,180.554
|
||||
161,398.32,919.29,546.25,98471.58,220,Rural,No,11.49752325760921,397.625,463.832
|
||||
162,276.07,251.64,777.77,36870.89,744,Suburban,Yes,10.515177629803139,387.777,477.60699999999997
|
||||
163,645.63,243.57,345.2,26267.46,334,Suburban,Yes,10.176086189767442,206.51999999999998,537.563
|
||||
164,869.89,779.5,694.12,33187.84,707,Suburban,Yes,10.40993882275291,174.412,486.98900000000003
|
||||
165,913.2,937.8,524.82,93834.24,397,Urban,Yes,11.449285100369293,527.482,406.32
|
||||
166,120.77,970.59,161.73,56121.04,791,Rural,Yes,10.935266065762434,349.173,405.077
|
||||
167,757.06,742.72,289.58,49173.87,459,Rural,No,10.80311766383716,447.95799999999997,499.706
|
||||
168,578.68,954.7,693.6,92161.91,99,Rural,No,11.431302200541351,563.36,531.8679999999999
|
||||
169,486.25,914.6,227.81,41215.88,401,Suburban,Yes,10.626578897969104,266.781,432.625
|
||||
|
241
input_data/input_firm_data/firm_amended.csv
Normal file
241
input_data/input_firm_data/firm_amended.csv
Normal file
@@ -0,0 +1,241 @@
|
||||
Code,固定资产原值（万元人民币）,固定资产净值（万元人民币）,资产总和（万元人民币）,存货（万元人民币）,企业名称,Type_Region,Revenue_Log,是否自我供给
|
||||
7,738304.9775,521745.74,1562279.24,20629.145,中船（邯郸）派瑞特种气体股份有限公司,河北省,62.0,0
|
||||
9,118435.7825,68257.45,459657.555,99540.5725,河北华通线缆集团股份有限公司,河北省,57.0,0
|
||||
640320,586321.240445073,335029.670514021,1031071.55115557,206268.473938857,安泰科技股份有限公司,北京市,60.0,0
|
||||
829768,427590.379398747,231206.408369974,1012444.68394969,202337.428395167,北京中科三环高技术股份有限公司,北京市,60.0,0
|
||||
863079,55996.8426674051,34766.988050671,151804.417005571,22724.7211301429,苏州清越光电科技股份有限公司,江苏省,52.0,0
|
||||
1452048,28236967.2134157,17452589.831388,37654713.2389085,1884370.44367833,京东方科技集团股份有限公司,北京市,76.0,0
|
||||
2010673,1275971.70452992,934279.359402009,2021526.974885,133209.227714714,北京京运通科技股份有限公司,北京市,63.0,0
|
||||
2624175,112528.502696921,68592.2842455949,676577.778208429,45047.728384,北京旋极信息技术股份有限公司,北京市,58.0,0
|
||||
2728939,359757.813985901,257844.195027811,1159738.28177866,59890.9064983333,北京燕东微电子股份有限公司,北京市,61.0,0
|
||||
5278074,5409.61000573167,3125.99366440613,7768.36691292389,491.00458,北京东方泰阳科技有限公司,北京市,39.0,0
|
||||
5849940,18652802.5217652,10302896.7482042,20855221.2857143,2169804.72857143,中国铝业股份有限公司,北京市,73.0,0
|
||||
7299120,86887.22406325,46503.9275985,158305.75064575,29562.480612,北京通美晶体技术股份有限公司,北京市,52.0,0
|
||||
9746245,1972219.0,1288498.51666667,16197718.45,3484537.2,中兴通讯股份有限公司,广东省,72.0,0
|
||||
11807506,19609298.1959302,12104435.9853224,39142373.2,5444482.05714286,比亚迪股份有限公司,广东省,76.0,0
|
||||
15613202,161967.589175966,101239.552677362,229751.726871143,38631.9143972857,云南临沧鑫圆锗业股份有限公司,云南省,54.0,0
|
||||
16190441,2301694.39797038,1330055.6043469,3305304.18753117,78577.1538838333,国泰租赁有限公司,山东省,65.0,0
|
||||
18065940,191013.048499246,96582.5538206939,867380.822769857,143283.010690286,北京君正集成电路股份有限公司,北京市,59.0,0
|
||||
22324879,32642.0785573127,18862.5299522688,46875.0321677567,2962.7662725,北京中电科电子装备有限公司,北京市,47.0,0
|
||||
24284343,149379.003567363,86320.052323942,214512.859072785,13558.421925,北京时代民芯科技有限公司,北京市,53.0,0
|
||||
24673506,3731195.01695067,1819174.82755833,3657055.221448,291506.649439667,江苏长电科技股份有限公司,江苏省,66.0,0
|
||||
25036634,294707.262396333,200188.4288045,1062465.42831983,172828.687160667,深圳市信维通信股份有限公司,广东省,60.0,0
|
||||
25228347,365794.329461067,223855.559307477,1551748.49245804,317742.544496667,利亚德光电股份有限公司,北京市,62.0,0
|
||||
25624519,70153.2023977496,47649.9414304781,181498.666732714,13415.1416134286,北京中石伟业科技股份有限公司,北京市,53.0,0
|
||||
25685135,27225.0066035415,15732.2243314978,39095.9496671667,494.656998333333,北京确安科技股份有限公司,北京市,46.0,0
|
||||
25945288,3777921.12291556,2755309.56990249,8635722.47654014,1811891.48151857,浙江正泰电器股份有限公司,浙江省,69.0,0
|
||||
26162741,80762.2185454289,38320.2320816127,280927.450768857,46986.1612615714,中核苏阀科技实业股份有限公司,江苏省,54.0,0
|
||||
26516263,9770657.164643,6267233.74672667,16031243.6918968,1389136.97893083,万华化学集团股份有限公司,山东省,72.0,0
|
||||
27075840,240383.397345603,138907.79119652,345197.977003382,21818.458064,上海生物制品研究所有限责任公司,上海市,55.0,0
|
||||
27731896,1608736.72383966,1100882.85217291,6303473.97195071,225975.029698857,东旭光电科技股份有限公司,河北省,68.0,0
|
||||
29954548,757171.52339162,494430.604177194,1465408.31294514,133292.643730143,多氟多新材料股份有限公司,河南省,62.0,0
|
||||
31654817,737.674091690682,426.271863328108,1059.32276085326,66.95517,中燕能源集团有限公司,北京市,30.0,0
|
||||
33822284,7821705.81265451,4340541.90024414,31773080.975276,3117341.894336,珠海格力电器股份有限公司,广东省,75.0,0
|
||||
43407343,34670.682309462,20034.7775764211,49788.1697601031,3146.89299,宁波荣申精密铸造有限公司,浙江省,47.0,0
|
||||
59234665,251695.047657333,199428.352979167,1787952.23306117,656252.890643167,浙江晶盛机电股份有限公司,浙江省,63.0,0
|
||||
68804111,8688.16152435692,5020.53527919772,12476.4680722717,788.583113333333,绍兴怡华电子科技有限公司,浙江省,41.0,0
|
||||
70634828,4412979.01454591,2550081.13819878,6337174.05278817,380474.996249,红狮控股集团有限公司,浙江省,68.0,0
|
||||
71271700,38578.465022,21210.6641386667,119513.037170333,5234.29972133333,杭州格林达电子材料股份有限公司,浙江省,51.0,0
|
||||
74680108,5901.39273352545,3410.17490662487,8474.58208682606,535.64136,浙江柳晶整流器有限公司,浙江省,39.0,0
|
||||
80158773,12635.7451105,6465.9750325,23799.6983851667,1474.810014,江苏华盛天龙光电设备股份有限公司,江苏省,44.0,0
|
||||
118882692,1359391.65389939,679399.008006956,2857647.90635,375644.165797143,木林森股份有限公司,广东省,65.0,0
|
||||
144312602,8114.4150085975,4688.99049660919,11652.5503693858,736.50687,成都湛艺电子科技有限公司,四川省,41.0,0
|
||||
145511905,5609260.87320936,3241363.78280047,8055071.72,292695.34,惠科股份有限公司,广东省,69.0,0
|
||||
151606446,1626783.46002289,1021353.15789806,4041634.8112335,705886.797687276,阿特斯阳光电力集团股份有限公司,江苏省,66.0,0
|
||||
152008168,280316.154842459,161983.308064681,402542.649124238,25442.9646,乐山无线电股份有限公司,四川省,56.0,0
|
||||
159511306,307.364204871118,177.613276386712,441.384483688857,27.8979875,中江县长鑫光电科技有限公司,四川省,26.0,0
|
||||
191912252,982581.890131988,567794.12195304,1411017.91745654,89184.28644,新疆东方希望有色金属有限公司,新疆维吾尔自治区,61.0,0
|
||||
194210021,308062.028854586,178016.520492827,442386.5804645,469.804659,海润光伏科技股份有限公司,江苏省,56.0,0
|
||||
203314437,3196.58773065962,1847.1780744218,4590.39863036412,290.13907,洛阳市洁晶清洗材料有限公司,河南省,37.0,0
|
||||
213386023,89012.6737306756,51436.8048415917,127824.946476293,8079.25718,包头稀土研究院,内蒙古自治区,51.0,0
|
||||
218633337,323470.089206363,186920.212069375,464513.030634154,29359.842045,腾达西北铁合金有限责任公司,甘肃省,57.0,0
|
||||
239053033,10819.2200114633,6251.98732881226,15536.7338258478,982.00916,合肥三晶敏感元件有限公司,安徽省,42.0,0
|
||||
249316393,5409.61000573167,3125.99366440613,7768.36691292389,491.00458,大连奥首科技有限公司,辽宁省,39.0,0
|
||||
251189644,13524.0250143292,7814.98416101532,19420.9172823098,1227.51145,宏正（福建）化学品有限公司,福建省,43.0,0
|
||||
259325842,10311.9951508333,5025.74256583333,52729.2373838333,8139.00741166667,安徽耐科装备科技股份有限公司,安徽省,47.0,0
|
||||
271860868,23482.6252521533,13569.6543159448,33721.7745538287,2131.406245,红河建材熔剂有限公司,云南省,45.0,0
|
||||
278221281,491.782727793788,284.181242218739,706.215173902172,44.63678,邢台先腾光电科技有限公司,河北省,28.0,0
|
||||
301209792,51111.2877957612,39283.408485579,372200.412021167,111866.716299773,华海清科股份有限公司,天津市,56.0,0
|
||||
314284469,93478.8051045442,56792.855184085,190929.033459167,18539.5011983333,四川华丰科技股份有限公司,四川省,53.0,0
|
||||
343012684,737.674091690682,426.271863328108,1059.32276085326,66.95517,沈阳市鑫红峰高压硅堆有限公司,辽宁省,30.0,0
|
||||
354897041,2704.80500286583,1562.99683220306,3884.18345646195,245.50229,宁夏鑫昊缘特种合金有限公司,宁夏回族自治区,36.0,0
|
||||
359737460,3118.597955,2478.276413,22273.339243,12656.693555,长春光华微电子设备工程中心有限公司,吉林省,43.0,0
|
||||
400488703,3196.58773065962,1847.1780744218,4590.39863036412,290.13907,厦门桥南工贸有限公司,福建省,37.0,0
|
||||
400692942,178271.238825248,103015.700304293,256003.000539537,16180.83275,湘能华磊光电股份有限公司,湖南省,54.0,0
|
||||
413274977,20643.9674441109,11929.3093901634,29645.3743383333,6146.1294835,厦门三优光电股份有限公司,福建省,45.0,0
|
||||
420984285,223613.011910333,158257.78831,1015669.78454783,62168.8641543333,深圳新宙邦科技股份有限公司,广东省,60.0,0
|
||||
448033045,2458.91363896894,1420.90621109369,3531.07586951086,223.1839,温州正大整流器有限公司,浙江省,35.0,0
|
||||
453289520,130115.029749624,82224.7896921481,479782.660674286,193520.088971571,拓荆科技股份有限公司,辽宁省,57.0,0
|
||||
474279224,737.674091690682,426.271863328108,1059.32276085326,66.95517,天津锦奥科技有限公司,天津市,30.0,0
|
||||
483081978,491.782727793788,284.181242218739,706.215173902172,44.63678,合肥士喜科技有限公司,安徽省,28.0,0
|
||||
495782506,153610.211526643,107409.509199715,340374.087803394,23731.1904788333,江苏南大光电材料股份有限公司,江苏省,55.0,0
|
||||
499022815,39256.6909747101,26249.6701913886,74787.2919863333,3738.7602482029,深圳市迅捷兴科技股份有限公司,广东省,49.0,0
|
||||
500189853,22867.8968424112,13214.4277631714,32839.005586451,2075.61027,东莞升洋焊锡材料有限公司,广东省,45.0,0
|
||||
503176785,52374.8605100384,30265.3022962957,75211.9160205813,4753.81707,江苏吉星新材料有限公司,江苏省,49.0,0
|
||||
525126393,1721.23954727826,994.634347765586,2471.7531086576,156.22873,安徽华晶微电子材料科技有限公司,安徽省,34.0,0
|
||||
549184982,2704.80500286583,1562.99683220306,3884.18345646195,245.50229,宁波市鄞州启威机械科技有限公司,浙江省,36.0,0
|
||||
560866402,7464.2026811807,4313.25923060848,10718.8254011667,548.727541333333,武汉迪赛环保新材料股份有限公司,湖北省,40.0,0
|
||||
561545339,8606.19773639128,4973.17173882793,12358.765543288,781.14365,桐城市大力刷业有限公司,安徽省,41.0,0
|
||||
571058167,18441.852292267,10656.7965832027,26483.0690213314,1673.87925,黄山市祁门新飞电子科技发展有限公司,安徽省,44.0,0
|
||||
581407487,27724.2512793748,16020.7175300814,39812.8804287349,2516.3984725,宁夏宏丰特种合金有限公司,宁夏回族自治区,46.0,0
|
||||
591452402,16597.6670630403,9591.11692488244,23834.7621191983,1506.491325,武汉光电工业技术研究院有限公司,湖北省,44.0,0
|
||||
593312758,16597.6670630403,9591.11692488244,23834.7621191983,1506.491325,湖北永绍科技股份有限公司,湖北省,44.0,0
|
||||
594378026,1024511.57056233,636647.240723,886208.347894167,24898.1373601667,安徽华塑股份有限公司,安徽省,59.0,0
|
||||
607512171,66390.6682521615,38364.4676995297,95339.048476793,6025.9653,沈阳新星实业有限公司,辽宁省,50.0,0
|
||||
615763365,4917.82727793788,2841.81242218739,7062.15173902172,446.3678,欧瑞康美科表面技术（上海）有限公司长春分公司,吉林省,38.0,0
|
||||
620220747,491.782727793788,284.181242218739,706.215173902172,44.63678,十堰环达化工有限公司,湖北省,28.0,0
|
||||
631449822,122868.272332646,71000.5786852338,176442.630878333,49014.7605131667,武汉日新科技股份有限公司,湖北省,52.0,0
|
||||
644292599,495225.206888344,286170.51091427,711158.680119487,44949.23746,昆山国显光电有限公司,江苏省,59.0,0
|
||||
653528340,245.891363896894,142.090621109369,353.107586951086,22.31839,合肥沁泉轩生物科技有限公司,安徽省,25.0,0
|
||||
654825436,2335.96795702049,1349.86090053901,3354.52207603531,212.024705,启东双赢电子科技有限公司,江苏省,35.0,0
|
||||
658759701,100943.178639667,66458.1199206667,348057.194237667,16288.5044676667,宏昌电子材料股份有限公司,广东省,55.0,0
|
||||
677887241,378695.182400345,254183.885856668,994951.0107498,148933.6095836,昆山丘钛微电子科技股份有限公司,江苏省,60.0,0
|
||||
688155470,5265525.41034568,3035619.83969163,7423857.02146943,375169.885145429,天马微电子股份有限公司,广东省,69.0,0
|
||||
695995052,9835.65455587574,5683.62484437478,14124.3034780435,892.7356,湖北澳格森化工有限公司,湖北省,41.0,0
|
||||
720737055,4537.85989427612,2622.24472086527,6516.50685,315.444274666667,上海明波通信技术股份有限公司,上海市,38.0,0
|
||||
750610681,491.782727793788,284.181242218739,706.215173902172,44.63678,衡水市桃城区泰昌矿山电子设备厂,河北省,28.0,0
|
||||
762985858,16622.25619943,9605.32598699338,23870.0728778934,1508.723164,武川县华升铁合金有限责任公司,内蒙古自治区,44.0,0
|
||||
771821595,1743718.4726489,1239245.99251298,2657759.780232,89907.0452243206,上海和辉光电股份有限公司,上海市,64.0,0
|
||||
774948022,6884.95818911303,3978.53739106234,9887.01243463041,624.91492,兴义市峰鑫建材有限公司,贵州省,40.0,0
|
||||
830662620,262637.565598167,177898.6218025,676303.217476167,73842.0312075,扬州扬杰电子科技股份有限公司,江苏省,58.0,0
|
||||
857978527,4426.04455014409,2557.63117996865,6355.93656511955,401.73102,宁波甬达驰化纤科技有限公司,浙江省,38.0,0
|
||||
868012326,3565.42477650496,2060.31400608585,5120.06001079074,323.616655,深圳市沃尔核材股份有限公司苏州市吴中区分公司,江苏省,37.0,0
|
||||
887840774,4180.1531862472,2415.54055885928,6002.82897816846,379.41263,中科院广州化学有限公司南雄材料生产基地,广东省,38.0,0
|
||||
888356483,1703781.26044158,984545.913666821,2446682.46998407,154644.12431,东莞长城开发科技有限公司,广东省,64.0,0
|
||||
888395016,1475.34818338136,852.543726656217,2118.64552170652,133.91034,河南欧斯滕光伏电力发展有限公司,河南省,33.0,0
|
||||
888478182,491.782727793788,284.181242218739,706.215173902172,44.63678,东莞市道滘博尔日涂料助剂厂,广东省,28.0,0
|
||||
888662519,22130.2227507204,12788.1558998433,31779.6828255977,2008.6551,东莞市森富同纸品有限公司,广东省,45.0,0
|
||||
930767828,92087.5475024413,53213.6493681296,132240.5601055,24848.5958543333,中国科学院沈阳科学仪器股份有限公司,辽宁省,51.0,0
|
||||
996174506,2131.05848710641,1231.45204961454,3060.26575357608,193.426046666667,长春市成越升经贸有限公司,吉林省,35.0,0
|
||||
1010117174,4057.20750429875,2344.49524830459,5826.27518469292,368.253435,三河市金贝金刚石应用技术开发有限公司,河北省,38.0,0
|
||||
1033972427,36282.327026942,26200.1602546739,467572.046681333,150030.431427836,盛美半导体设备（上海）股份有限公司,上海市,57.0,0
|
||||
1128343125,331707.44989691,191680.247876539,476342.134797015,30107.50811,上海先进半导体制造有限公司,上海市,57.0,0
|
||||
1186341289,123560.937534667,81087.0414031667,416602.575697667,38611.657751,湖北回天新材料股份有限公司,湖北省,56.0,0
|
||||
1217957486,1065.52924355321,615.726024807267,1530.13287678804,96.7130233333333,安徽信久智能科技有限公司,安徽省,32.0,0
|
||||
1232020820,71308.4955300992,41206.2801217171,102401.200215815,6472.3331,深圳市同一方光电技术有限公司,广东省,50.0,0
|
||||
1307012237,295318.451425635,170652.525257946,424086.41,7933.0,广东爱旭科技有限公司,广东省,56.0,0
|
||||
1375606900,819.637879656312,473.635403697898,1177.02528983695,74.3946333333333,黄冈中硅机电工程有限公司,湖北省,31.0,0
|
||||
1428342684,32933.0381671641,22688.1531399891,130057.0266575,9719.67009846261,烟台德邦科技股份有限公司,山东省,51.0,0
|
||||
1549474227,2704.80500286583,1562.99683220306,3884.18345646194,245.50229,沧州浩康高压法兰管件有限公司,河北省,36.0,0
|
||||
1601593550,2950.69636676273,1705.08745331243,4237.29104341303,267.82068,珠海佳泰电子科技有限公司,广东省,36.0,0
|
||||
1606833003,21687.618295706,12532.3927818464,31144.0891690858,1968.481998,东莞市新兴电路板有限公司,广东省,45.0,0
|
||||
1679596339,7602.68963569803,4393.28521066349,10917.6969416667,4958.50469716667,上海广奕电子科技股份有限公司,上海市,40.0,0
|
||||
2310825263,491.782727793788,284.181242218739,706.215173902172,44.63678,沈阳市久久化工厂,辽宁省,28.0,0
|
||||
2311541114,87906.1625931395,50797.3970465996,126235.962335013,7978.824425,一诠科技（中国）有限公司,广东省,51.0,0
|
||||
2311838590,53398.0289114503,26546.600225041,80495.2837445714,310.151853,上海华岭集成电路技术股份有限公司,上海市,49.0,0
|
||||
2312490120,245.891363896894,142.090621109369,353.107586951086,22.31839,元鸿（山东）光电材料有限公司,山东省,25.0,0
|
||||
2312693498,47740.0144863412,27587.0132347507,68556.1340956667,13557.3351533333,深圳市夏瑞科技股份有限公司,广东省,48.0,0
|
||||
2316161851,655.710303725051,378.908322958318,941.620231869564,59.5157066666667,福州外星电脑科技有限公司,福建省,30.0,0
|
||||
2316990095,69894.7882595,56812.003379,167801.3590105,9765.7389965,广东中图半导体科技股份有限公司,广东省,52.0,0
|
||||
2317245827,51637.1864183477,29839.0304329676,74152.593259728,4686.8619,河南吉祥实业有限公司,河南省,49.0,0
|
||||
2317695802,2213.02227507204,1278.81558998433,3177.96828255977,200.86551,佛山市禅城罗博派克自动化包装设备厂,广东省,35.0,0
|
||||
2317841563,21638.4400229267,12503.9746576245,31073.4676516956,1964.01832,珠海市宏科电子科技有限公司,广东省,45.0,0
|
||||
2320102626,42662.1516361111,24652.7227624756,61264.1663360134,3872.240665,江门市东江环保技术有限公司,广东省,48.0,0
|
||||
2320475044,7540.66849283808,4357.44571402066,10828.6326665,684.430626666667,苏州万达电子科技有限公司,江苏省,40.0,0
|
||||
2321109759,10081.5459197726,5825.71546548415,14477.4110649945,915.05399,厦门纵行信息科技有限公司,福建省,42.0,0
|
||||
2321173423,12786.3509226385,7388.71229768721,18361.5945214565,1160.55628,福建欧中电子有限公司,福建省,43.0,0
|
||||
2321857672,172615.737455619,99747.6160187774,247881.526039662,15667.50978,福建福顺半导体制造有限公司,福建省,54.0,0
|
||||
2324787028,48289.980280888,27904.8161054885,69345.901949,3463.846805,瑞红（苏州）电子化学品股份有限公司,江苏省,48.0,0
|
||||
2324844174,7868.52364470058,4546.89987549982,11299.4427824348,714.18848,珠海市分板自动化有限公司,广东省,41.0,0
|
||||
2326478786,12535.2099703022,7243.58815287001,18000.9483635,3351.3208995,山东华美新材料科技股份有限公司,山东省,43.0,0
|
||||
2327031723,135066.901471,105068.760506333,324604.3707355,21706.8537546667,聚灿光电科技股份有限公司,江苏省,55.0,0
|
||||
2327979389,9507.79940401323,5494.17068289562,13653.4933621087,862.977746666667,江苏赢新润滑科技有限公司,江苏省,41.0,0
|
||||
2329375731,245.891363896894,142.090621109369,353.107586951086,22.31839,无锡兴锋光伏科技有限公司,江苏省,25.0,0
|
||||
2333843479,25746.1035943333,12125.48027,54175.2774613333,8385.40003966667,山东华光光电子股份有限公司,山东省,47.0,0
|
||||
2334283182,614.728409742235,355.226552773424,882.768967377716,55.795975,松原市三源通经贸有限公司,吉林省,29.0,0
|
||||
2337843112,1032.74372836696,596.780608659351,1483.05186519456,93.737238,任丘市鸿图电子科技有限公司,河北省,32.0,0
|
||||
2337952436,101095.280241295,58418.8518582322,145175.942304,8845.106302,杭摩新材料集团股份有限公司,浙江省,52.0,0
|
||||
2339188563,44515.98655263,32625.0798330998,118787.550664333,6638.528607,江苏联瑞新材料股份有限公司,江苏省,51.0,0
|
||||
2339684065,44506.3368653378,25718.4024207959,63912.4732381466,4039.62859,浙江浙能技术研究院有限公司,浙江省,48.0,0
|
||||
2341555098,37881.5253218792,21890.1931985425,54399.039415,5940.110805,河南信谊纸塑包装股份有限公司,河南省,47.0,0
|
||||
2343704209,71514.6399746746,41325.4026142836,102697.23,7848.60666666667,麦斯克电子材料股份有限公司,河南省,50.0,0
|
||||
2348941764,368.837045845341,213.135931664054,529.661380426629,33.477585,苏州鸿丰电子科技有限公司,江苏省,27.0,0
|
||||
2349168009,69505.2921948554,40164.2822335818,99811.7445781735,6308.66490666667,深圳市华汉伟业科技有限公司,广东省,50.0,0
|
||||
2349656760,16976.6475090839,9263.96039459785,57224.236615,14903.7379424235,苏州鸿安机械股份有限公司,江苏省,48.0,0
|
||||
2350111843,92789.448255777,62286.1122935528,131188.586355714,1480.14299457143,广东利扬芯片测试股份有限公司,广东省,51.0,0
|
||||
2352036411,491.782727793788,284.181242218739,706.215173902172,44.63678,甘肃中瀚制冷空调设备有限公司,甘肃省,28.0,0
|
||||
2352538239,16223.5357741212,9374.92166541306,23297.4980423333,2700.333564,广东信力科技股份有限公司,广东省,44.0,0
|
||||
2354145351,2950.69636676273,1705.08745331243,4237.29104341303,267.82068,江苏协鑫特种材料科技有限公司,江苏省,36.0,0
|
||||
2379638202,5409.61000573167,3125.99366440613,7768.36691292389,491.00458,延安新兴东风汽车技术服务站,陕西省,39.0,0
|
||||
2424229017,114276.893374667,77926.1367106667,500826.828284333,41132.540103,湖北鼎龙控股股份有限公司,湖北省,57.0,0
|
||||
2481687500,2458.91363896894,1420.90621109369,3531.07586951086,223.1839,深圳市鑫创鑫自动化设备销售部,广东省,35.0,0
|
||||
2545430247,368.837045845341,213.135931664054,529.661380426629,33.477585,广州顺安高新材料有限公司,广东省,27.0,0
|
||||
2791956547,245.891363896894,142.090621109369,353.107586951086,22.31839,广州市粤盛工程材料有限公司,广东省,25.0,0
|
||||
2820140348,6759.83660375,6057.056538,441817.1010005,215119.38793925,拉普拉斯新能源科技股份有限公司,广东省,56.0,0
|
||||
2944404352,4381.18779540463,2531.71028530659,6291.520881,938.8492245,安徽先捷电子股份有限公司,安徽省,38.0,0
|
||||
2944892892,18401.38999975,13587.32820175,41068.08841875,7301.21620425,安徽安芯电子科技股份有限公司,安徽省,46.0,0
|
||||
2965658107,33627.9499162838,22617.886222157,57037.7426061667,8422.16001716667,安徽晶赛科技股份有限公司,安徽省,48.0,0
|
||||
3006753238,2041970.43921619,1162815.70513596,2626399.81194,236376.363264714,通富微电子股份有限公司,江苏省,64.0,0
|
||||
3025036704,1475.34818338136,852.543726656217,2118.64552170652,133.91034,泗县博尚装饰工程有限公司,安徽省,33.0,0
|
||||
3026382513,1721.23954727826,994.634347765588,2471.7531086576,156.22873,绍兴上虞鑫丰物资有限公司,浙江省,34.0,0
|
||||
3029702382,245.891363896894,142.090621109369,353.107586951086,22.31839,河南地天泰车业有限公司,河南省,25.0,0
|
||||
3045721313,2458.91363896894,1420.90621109369,3531.07586951086,223.1839,传化智联股份有限公司石家庄分公司,河北省,35.0,0
|
||||
3047163873,2430149.11286677,1339451.5244595,4326866.03200717,278136.343715333,巨化集团有限公司,浙江省,66.0,0
|
||||
3048263744,20654.8745673391,11935.612173187,29661.0373038912,1874.74476,东莞市康柏工业陶瓷有限公司,广东省,45.0,0
|
||||
3069206426,1229.45681948447,710.453105546847,1765.53793475543,111.59195,东莞万兴鸿自动化有限公司上海分公司,上海市,32.0,0
|
||||
3070859372,491.782727793788,284.181242218739,706.215173902172,44.63678,江苏丰禾兰环保科技有限公司,江苏省,28.0,0
|
||||
3072715478,21638.4400229267,12503.9746576245,31073.4676516956,1964.01832,江西宁和达新材料有限公司,江西省,45.0,0
|
||||
3103797386,37788.230163,25727.5525585,162597.015751167,11040.109561,江西晨光新材料股份有限公司,江西省,52.0,0
|
||||
3111033905,3393.30082177713,1960.8505713093,4872.88469992499,307.993782,安徽开华散热器制造科技有限公司,安徽省,37.0,0
|
||||
3113895788,3688.37045845341,2131.35931664054,5296.61380426629,334.77585,山西华晶恒基新材料有限公司,山西省,37.0,0
|
||||
3120341363,177544.316546708,129292.795388716,626033.402033857,102806.403100857,武汉精测电子集团股份有限公司,湖北省,58.0,0
|
||||
3122923980,1229.45681948447,710.453105546847,1765.53793475543,111.59195,贵州鼎辉农旅商务实业有限责任公司,贵州省,32.0,0
|
||||
3127420424,2458.91363896894,1420.90621109369,3531.07586951086,223.1839,西安唐晶量子科技有限公司,陕西省,35.0,0
|
||||
3133307899,243008.157268805,176966.316004727,498232.321410136,48875.2580525,九江德福科技股份有限公司,江西省,57.0,0
|
||||
3147511625,21761.3857048751,12575.0199681792,31250.0214451711,1975.177515,安徽东昇新能源有限公司,安徽省,45.0,0
|
||||
3177507356,245.891363896894,142.090621109369,353.107586951086,22.31839,东莞市易亮电子科技有限公司,广东省,25.0,0
|
||||
3188903709,1721.23954727826,994.634347765586,2471.7531086576,156.22873,上海江丰平芯电子科技有限公司,上海市,34.0,0
|
||||
3195502499,5901.39273352545,3410.17490662487,8474.58208682606,535.64136,福建天甫电子材料有限公司,福建省,39.0,0
|
||||
3203777710,980459.123449225,526964.137174853,1085867.46938081,45238.3255234,和舰芯片制造（苏州）股份有限公司,江苏省,60.0,0
|
||||
3211956484,14261.6991060198,8241.25602434343,20480.240043163,1294.46662,广州利诺士电子科技有限公司,广东省,43.0,0
|
||||
3215814536,737.674091690682,426.271863328108,1059.32276085326,66.95517,甘肃省晶科新能源电力工程有限公司,甘肃省,30.0,0
|
||||
3221190269,1475.34818338136,852.543726656217,2118.64552170652,133.91034,天津浩纳自动化设备有限公司,天津市,33.0,0
|
||||
3226664625,8790.61625931396,5079.73970465996,12623.5962335013,797.8824425,珠海市优邦新材料有限公司,广东省,41.0,0
|
||||
3267688490,3442.47909455651,1989.26869553117,4943.5062173152,312.45746,科毅科技（东莞）有限公司,广东省,37.0,0
|
||||
3269039233,737.674091690682,426.271863328108,1059.32276085326,66.95517,合肥烯盛芯业集成电路有限公司,安徽省,30.0,0
|
||||
3269940677,30244.6377593179,17477.1463964524,43432.2331949836,2745.16197,吉和昌新材料（荆门）有限公司,湖北省,46.0,0
|
||||
3271705843,491.782727793788,284.181242218739,706.215173902172,44.63678,辽宁卫重起重设备有限公司,辽宁省,28.0,0
|
||||
3299144127,3606.40667048778,2083.99577627075,5178.9112752826,327.336386666667,重庆睿科半导体有限公司,重庆市,37.0,0
|
||||
3312358902,66438.2226519953,41878.7735649207,237082.540978857,87569.4877398571,沈阳芯源微电子设备股份有限公司,辽宁省,54.0,0
|
||||
3331430009,737.674091690682,426.271863328108,1059.32276085326,66.95517,福州康丽佳商贸有限公司,福建省,30.0,0
|
||||
3344297292,688.495818911302,397.853739106235,988.701243463041,62.491492,合肥市鑫山新型建材有限公司,安徽省,30.0,0
|
||||
3372913783,824403.673322169,516140.824501698,1699364.11085187,187067.647483167,贝特瑞新材料集团股份有限公司,广东省,62.0,0
|
||||
3373311444,1314.60015,1097.90318233333,73687.6299513333,21062.3211216667,北京晶亦精微科技股份有限公司,北京市,49.0,0
|
||||
3384021594,24097.3536618956,13924.8808687182,34604.5435212064,2187.20222,中电化合物半导体有限公司,浙江省,45.0,0
|
||||
3391580446,3442.47909455651,1989.26869553117,4943.5062173152,312.45746,芯珉微电子（上海）有限公司,上海市,37.0,0
|
||||
3395900897,737.674091690682,426.271863328108,1059.32276085326,66.95517,安徽林泰新材料有限公司,安徽省,30.0,0
|
||||
3398677646,36420.8435164999,21053.0034803726,78385.10020775,33245.58495675,矽电半导体设备（深圳）股份有限公司,广东省,49.0,0
|
||||
3407754893,232859.633511805,168326.909166578,411069.08997625,40891.55866,比亚迪半导体股份有限公司,广东省,56.0,0
|
||||
3409328588,3073.64204871117,1776.13276386712,4413.84483688857,278.979875,苏州矽利康测试系统有限公司深圳分公司,广东省,36.0,0
|
||||
3433628561,245.891363896894,142.090621109369,353.107586951086,22.31839,深圳市景辉新科技有限公司,广东省,25.0,0
|
||||
3442780535,396622.76996569,229192.171849413,569562.537752102,35999.56307,武汉光网信息技术有限公司,湖北省,58.0,0
|
||||
3444191691,115814.832395437,66924.682542513,166313.673453961,10511.96169,无锡伟测半导体科技有限公司,江苏省,52.0,0
|
||||
3445244192,11065.1113753602,6394.07794992163,15889.8414127989,1004.32755,上海彤程电子材料有限公司,上海市,42.0,0
|
||||
3445928818,26556.2673008645,15345.7870798119,38135.6193907173,2410.38612,吉光半导体科技有限公司,吉林省,46.0,0
|
||||
4037576402,9835.65455587576,5683.62484437478,14124.3034780434,892.7356,强一半导体（上海）有限公司,上海市,41.0,0
|
||||
4144746564,3442.47909455651,1989.26869553117,4943.5062173152,312.45746,重庆摩尔精英速芯半导体有限公司,重庆市,37.0,0
|
||||
4208851809,71851.6551423333,52930.2237671667,445347.011300833,49697.6881215,西陇科学股份有限公司,广东省,56.0,0
|
||||
4518234098,614.728409742235,355.226552773424,882.768967377716,55.795975,武汉跃鹏新材料有限公司,湖北省,29.0,0
|
||||
5007015990,305520.01964189,176547.596728392,438736.176786724,27730.599575,深圳市鹏芯微集成电路制造有限公司,广东省,56.0,0
|
||||
11164476478,20163.0918395453,11651.4309309683,28954.8221299891,1830.10798,江苏芯诺半导体科技有限公司,江苏省,45.0,0
|
||||
11212932825,491.782727793788,284.181242218739,706.215173902172,44.63678,河南雷电光源技术研究院,河南省,28.0,0
|
||||
11220388001,737.674091690682,426.271863328108,1059.32276085326,66.95517,新疆蚂蚁网约出租汽车服务有限公司,新疆维吾尔自治区,30.0,0
|
||||
397847929,4794.881596,2770.767112,6885.597946,435.208605,厦门科塔电子有限公司,福建省,38.0,0
|
||||
517717050,40080.29232,23160.77124,57556.53667,3637.89757,深圳市实锐泰科技有限公司,广东省,48.0,0
|
||||
737770776,5962.865574,3445.697562,8562.858984,541.2209575,福建省南安市物资有限公司,福建省,39.0,0
|
||||
872394725,25724.57103,15462.17311,55978.44597,7283.825438,北京凯德石英股份有限公司,北京市,47.0,0
|
||||
2311581270,32088.82299,18542.82605,46080.5401,2912.549895,安徽亚格盛电子新材料股份有限公司,安徽省,47.0,0
|
||||
2313209417,15122.31888,8738.573198,21716.1166,1372.580985,武汉拓材科技有限公司,湖北省,43.0,0
|
||||
2347013470,23006.64933,17588.56669,81317.91108,12851.94016,江苏先锋精密科技股份有限公司,江苏省,49.0,0
|
||||
2350418059,73931.33674,42721.91341,106167.6811,6710.395927,江苏纳沛斯半导体有限公司,江苏省,50.0,0
|
||||
2352951203,29261.0723,16908.78391,42019.80285,2655.88841,中山市江波龙电子有限公司,广东省,46.0,0
|
||||
2359644835,232613.2302,134417.7276,334039.7773,21113.19694,广东气派科技有限公司,广东省,55.0,0
|
||||
2388955897,2458.913639,1420.906211,3531.07587,223.1839,上海鑫匀源科技有限公司,上海市,35.0,0
|
||||
2977767486,9790.429458,5657.491099,14059.35884,1748.344959,深圳市三联盛科技股份有限公司,广东省,41.0,0
|
||||
3031009366,43768.66277,25292.13056,62853.15048,3972.67342,天通瑞宏科技有限公司,浙江省,48.0,0
|
||||
3089095447,245.8913639,142.0906211,353.107587,22.31839,常州金坛沸腾商贸有限公司,江苏省,25.0,0
|
||||
3100891962,14801.53049,8553.202633,21255.45458,3889.830944,北京中超伟业信息安全技术股份有限公司,北京市,43.0,0
|
||||
3151203276,341884.6624,201430.569,477385.6924,28574.49401,合肥颀中科技股份有限公司,安徽省,57.0,0
|
||||
3188352290,13032.24229,7530.802919,18714.70211,1182.87467,湖北深紫科技有限公司,湖北省,43.0,0
|
||||
3288105727,6639.066825,3836.44677,9533.904848,602.59653,奥趋光电技术（杭州）有限公司,浙江省,40.0,0
|
||||
3462551351,5901.392734,3410.174907,8474.582087,535.64136,无锡博加电子新材料有限公司,江苏省,39.0,0
|
||||
|
@@ -1,221 +1,227 @@
|
||||
Firm_Code,设备id,设备数量
|
||||
0,70,140
|
||||
1,78,139
|
||||
1,97,68
|
||||
2,57,88
|
||||
3,94,175
|
||||
4,58,190
|
||||
5,97,175
|
||||
6,85,107
|
||||
7,64,197
|
||||
8,67,110
|
||||
8,86,176
|
||||
9,100,154
|
||||
10,90,50
|
||||
11,54,180
|
||||
12,52,141
|
||||
13,56,162
|
||||
13,104,105
|
||||
14,92,166
|
||||
14,54,183
|
||||
14,104,107
|
||||
15,79,93
|
||||
16,68,110
|
||||
17,76,96
|
||||
17,94,198
|
||||
18,84,129
|
||||
19,60,167
|
||||
20,86,196
|
||||
20,64,69
|
||||
20,81,195
|
||||
20,98,96
|
||||
21,65,98
|
||||
21,58,63
|
||||
22,64,192
|
||||
23,73,50
|
||||
24,90,166
|
||||
25,71,103
|
||||
26,66,167
|
||||
27,95,52
|
||||
28,68,193
|
||||
29,97,61
|
||||
30,103,123
|
||||
31,74,65
|
||||
32,76,151
|
||||
33,75,166
|
||||
34,95,57
|
||||
35,91,171
|
||||
36,79,141
|
||||
37,65,139
|
||||
37,95,185
|
||||
38,51,109
|
||||
39,75,77
|
||||
40,57,150
|
||||
41,59,90
|
||||
42,74,194
|
||||
43,51,190
|
||||
44,94,95
|
||||
45,58,84
|
||||
46,74,183
|
||||
47,61,131
|
||||
48,101,164
|
||||
48,67,96
|
||||
49,58,59
|
||||
50,85,105
|
||||
50,85,79
|
||||
50,83,158
|
||||
51,55,54
|
||||
52,92,168
|
||||
52,89,82
|
||||
52,91,167
|
||||
53,78,114
|
||||
54,57,195
|
||||
54,59,60
|
||||
55,58,134
|
||||
56,62,75
|
||||
57,84,112
|
||||
57,83,135
|
||||
58,98,108
|
||||
58,105,76
|
||||
59,73,147
|
||||
59,74,154
|
||||
60,87,148
|
||||
61,85,178
|
||||
62,94,198
|
||||
63,90,104
|
||||
63,72,55
|
||||
64,77,144
|
||||
65,85,182
|
||||
66,51,151
|
||||
67,85,52
|
||||
68,87,72
|
||||
69,97,102
|
||||
70,64,132
|
||||
71,53,194
|
||||
71,51,134
|
||||
72,55,127
|
||||
72,76,159
|
||||
73,105,50
|
||||
74,64,100
|
||||
74,89,53
|
||||
75,77,162
|
||||
76,59,81
|
||||
77,65,83
|
||||
78,65,141
|
||||
79,76,144
|
||||
80,92,121
|
||||
81,63,88
|
||||
82,101,167
|
||||
83,82,52
|
||||
84,89,172
|
||||
85,99,99
|
||||
86,102,61
|
||||
87,82,103
|
||||
87,54,182
|
||||
87,80,106
|
||||
88,87,194
|
||||
88,73,161
|
||||
88,89,96
|
||||
89,95,134
|
||||
89,65,191
|
||||
90,93,115
|
||||
91,79,124
|
||||
92,86,152
|
||||
92,63,87
|
||||
93,82,99
|
||||
94,57,147
|
||||
95,101,131
|
||||
96,72,79
|
||||
97,78,128
|
||||
98,52,140
|
||||
99,92,101
|
||||
99,95,128
|
||||
100,103,79
|
||||
101,56,155
|
||||
102,78,100
|
||||
102,78,130
|
||||
102,94,182
|
||||
103,94,78
|
||||
103,70,181
|
||||
104,80,187
|
||||
105,61,194
|
||||
106,105,123
|
||||
106,78,66
|
||||
107,75,133
|
||||
107,89,118
|
||||
108,83,83
|
||||
109,51,55
|
||||
110,77,102
|
||||
111,102,175
|
||||
112,63,92
|
||||
113,91,164
|
||||
114,53,160
|
||||
115,89,129
|
||||
116,56,144
|
||||
116,58,167
|
||||
117,77,193
|
||||
118,59,57
|
||||
119,87,181
|
||||
120,83,153
|
||||
121,101,181
|
||||
121,92,74
|
||||
122,94,145
|
||||
123,74,142
|
||||
124,65,110
|
||||
125,104,171
|
||||
126,82,100
|
||||
127,82,196
|
||||
128,74,70
|
||||
129,91,54
|
||||
129,102,141
|
||||
129,99,110
|
||||
130,99,71
|
||||
130,102,198
|
||||
130,62,119
|
||||
131,89,50
|
||||
131,52,182
|
||||
132,53,61
|
||||
133,99,139
|
||||
134,87,95
|
||||
134,99,83
|
||||
135,106,127
|
||||
136,67,94
|
||||
137,99,122
|
||||
138,52,75
|
||||
139,52,96
|
||||
140,78,170
|
||||
141,104,105
|
||||
142,73,143
|
||||
143,87,156
|
||||
144,82,112
|
||||
145,83,97
|
||||
146,51,110
|
||||
147,69,130
|
||||
148,52,75
|
||||
149,103,85
|
||||
149,94,50
|
||||
150,76,57
|
||||
151,82,162
|
||||
151,56,148
|
||||
152,82,96
|
||||
153,105,176
|
||||
154,54,105
|
||||
155,105,63
|
||||
156,61,77
|
||||
157,106,127
|
||||
157,67,179
|
||||
158,88,158
|
||||
159,74,63
|
||||
160,55,105
|
||||
160,102,164
|
||||
161,84,56
|
||||
162,56,52
|
||||
163,72,160
|
||||
164,61,156
|
||||
165,98,67
|
||||
166,66,87
|
||||
166,83,164
|
||||
167,59,64
|
||||
168,56,168
|
||||
169,66,77
|
||||
169,79,88
|
||||
Firm_Code,设备id,设备数量
|
||||
863079,61,12168446
|
||||
1452048,84,1221681288
|
||||
1452048,59,12216812882
|
||||
1452048,61,6108406441
|
||||
1452048,74,8726294916
|
||||
1452048,63,12216812882
|
||||
1452048,62,2443362576
|
||||
2010673,67,233569840
|
||||
2010673,68,326997776
|
||||
2010673,64,467139680
|
||||
2728939,68,90245468
|
||||
2728939,87,18049094
|
||||
2728939,63,180490937
|
||||
2728939,61,90245468
|
||||
2728939,71,36098187
|
||||
2728939,62,36098187
|
||||
2728939,79,90245468
|
||||
5278074,68,1094098
|
||||
11807506,71,1694621038
|
||||
11807506,60,2541931557
|
||||
16190441,84,93103892
|
||||
22324879,71,2640754
|
||||
22324879,87,1320377
|
||||
22324879,81,3961131
|
||||
22324879,63,13203771
|
||||
22324879,83,2640754
|
||||
22324879,84,1320377
|
||||
24284343,87,6042404
|
||||
24673506,67,454793707
|
||||
24673506,81,382026714
|
||||
24673506,82,127342238
|
||||
24673506,84,127342238
|
||||
24673506,85,90958741
|
||||
26516263,74,3133616873
|
||||
26516263,82,438706362
|
||||
27075840,65,97235454
|
||||
31654817,86,29839
|
||||
33822284,84,303837933
|
||||
33822284,61,1519189665
|
||||
33822284,85,217027095
|
||||
59234665,67,49857088
|
||||
59234665,68,69799924
|
||||
59234665,81,41879954
|
||||
59234665,60,41879954
|
||||
59234665,64,99714176
|
||||
59234665,65,139599847
|
||||
59234665,82,13959985
|
||||
59234665,83,27919969
|
||||
59234665,84,13959985
|
||||
68804111,77,1757187
|
||||
74680108,78,238712
|
||||
80158773,67,1616494
|
||||
80158773,69,161649
|
||||
80158773,68,2263091
|
||||
80158773,60,1357855
|
||||
80158773,64,3232988
|
||||
145511905,68,1134477324
|
||||
145511905,61,1134477324
|
||||
151606446,61,357473605
|
||||
151606446,67,255338289
|
||||
151606446,71,142989442
|
||||
151606446,87,71494721
|
||||
151606446,64,510676579
|
||||
151606446,82,71494721
|
||||
151606446,83,142989442
|
||||
159511306,67,44403
|
||||
159511306,69,4440
|
||||
159511306,81,37299
|
||||
213386023,64,25718402
|
||||
218633337,72,26168830
|
||||
239053033,82,437639
|
||||
249316393,71,437639
|
||||
259325842,75,351802
|
||||
278221281,66,28418124
|
||||
301209792,71,5499677
|
||||
301209792,65,27498386
|
||||
301209792,83,5499677
|
||||
314284469,88,3975500
|
||||
354897041,72,218820
|
||||
359737460,87,173479
|
||||
359737460,81,520438
|
||||
359737460,80,52044
|
||||
400692942,68,36055495
|
||||
400692942,82,7211099
|
||||
400692942,84,7211099
|
||||
453289520,68,28778676
|
||||
474279224,71,59678
|
||||
499022815,61,9187385
|
||||
549184982,67,390749
|
||||
549184982,69,39075
|
||||
549184982,60,328229
|
||||
581407487,72,2242900
|
||||
591452402,66,959111692
|
||||
615763365,68,994634
|
||||
644292599,74,143085255
|
||||
644292599,61,100159679
|
||||
644292599,62,40063872
|
||||
654825436,61,472451
|
||||
677887241,87,17792872
|
||||
688155470,84,212493389
|
||||
762985858,72,1344746
|
||||
771821595,61,433736097
|
||||
774948022,81,835493
|
||||
830662620,80,3735871
|
||||
830662620,61,62264518
|
||||
830662620,75,12452904
|
||||
830662620,62,24905807
|
||||
857978527,60,537103
|
||||
888356483,82,68918214
|
||||
888662519,89,895171
|
||||
930767828,68,18624777
|
||||
930767828,64,26606825
|
||||
1033972427,59,18340112
|
||||
1033972427,61,9170056
|
||||
1033972427,71,3668022
|
||||
1033972427,73,5502034
|
||||
1128343125,61,67088087
|
||||
1128343125,74,95840124
|
||||
1128343125,62,26835235
|
||||
1128343125,63,134176174
|
||||
1232020820,87,2884440
|
||||
1307012237,61,59728384
|
||||
1307012237,68,59728384
|
||||
1307012237,62,23891354
|
||||
1375606900,67,118409
|
||||
1549474227,67,390749
|
||||
1601593550,85,85254
|
||||
1601593550,84,119356
|
||||
1679596339,61,1537650
|
||||
1679596339,71,615060
|
||||
1679596339,74,2196643
|
||||
1679596339,66,439328521
|
||||
1679596339,62,615060
|
||||
2311838590,80,557479
|
||||
2311838590,76,557479
|
||||
2311838590,77,9291310
|
||||
2312693498,84,1931091
|
||||
2316990095,61,19884201
|
||||
2316990095,71,7953680
|
||||
2316990095,66,5681200338
|
||||
2317695802,89,89517
|
||||
2321857672,82,6982333
|
||||
2321857672,78,6982333
|
||||
2324844174,67,1136725
|
||||
2324844174,81,954849
|
||||
2326478786,60,1521154
|
||||
2333843479,68,4243918
|
||||
2333843479,70,424392
|
||||
2333843479,83,1697567
|
||||
2334283182,86,24866
|
||||
2337843112,85,29839
|
||||
2339684065,74,12859201
|
||||
2343704209,69,1033135
|
||||
2343704209,71,5785556
|
||||
2343704209,64,20662701
|
||||
2349656760,79,3242386
|
||||
2350111843,77,21800139
|
||||
2350111843,82,4360028
|
||||
2350111843,80,1308008
|
||||
2350111843,71,8720056
|
||||
2350111843,86,4360028
|
||||
2354145351,81,358068
|
||||
2354145351,84,119356
|
||||
2379638202,81,656459
|
||||
2424229017,65,54548296
|
||||
2481687500,84,99463
|
||||
2791956547,81,29839
|
||||
2820140348,68,2119970
|
||||
2820140348,62,847988
|
||||
2944404352,82,177220
|
||||
2944404352,84,177220
|
||||
2944892892,61,4755565
|
||||
3006753238,82,81397099
|
||||
3006753238,84,81397099
|
||||
3006753238,87,81397099
|
||||
3006753238,77,406985497
|
||||
3006753238,85,58140785
|
||||
3029702382,77,49732
|
||||
3070859372,62,39785
|
||||
3120341363,82,9050496
|
||||
3120341363,79,45252478
|
||||
3188903709,65,696244
|
||||
3203777710,61,184437448
|
||||
3203777710,71,73774979
|
||||
3203777710,74,263482069
|
||||
3267688490,73,417746
|
||||
3271705843,67,71045
|
||||
3271705843,77,99463
|
||||
3271705843,62,39785
|
||||
3312358902,59,29315141
|
||||
3312358902,61,14657571
|
||||
3312358902,71,5863028
|
||||
3312358902,66,4187877356
|
||||
3312358902,79,14657571
|
||||
3331430009,86,29839
|
||||
3373311444,71,153706
|
||||
3373311444,65,768532
|
||||
3384021594,67,3481220
|
||||
3384021594,68,4873708
|
||||
3384021594,64,6962440
|
||||
3391580446,78,139249
|
||||
3395900897,73,89517
|
||||
3398677646,66,2105300348
|
||||
3398677646,82,1473710
|
||||
3398677646,79,7368551
|
||||
3398677646,80,442113
|
||||
3407754893,80,3534865
|
||||
3407754893,84,11782884
|
||||
3407754893,71,23565767
|
||||
3407754893,87,11782884
|
||||
3407754893,85,8416345
|
||||
3409328588,76,37299
|
||||
3444191691,77,23423639
|
||||
3444191691,82,4684728
|
||||
3445928818,61,5371025
|
||||
3445928818,68,5371025
|
||||
3445928818,74,7672894
|
||||
4037576402,76,119356
|
||||
4144746564,75,139249
|
||||
4144746564,87,139249
|
||||
5007015990,74,88273798
|
||||
11164476478,67,2912858
|
||||
11164476478,81,2446800
|
||||
11164476478,60,2446800
|
||||
11212932825,81,59678
|
||||
11220388001,77,149195
|
||||
|
||||
|
@@ -1,221 +1,476 @@
|
||||
Firm_Code,材料id,材料数量
|
||||
0,2,156
|
||||
1,19,116
|
||||
1,35,185
|
||||
2,18,189
|
||||
3,25,143
|
||||
4,2,124
|
||||
5,18,116
|
||||
6,19,112
|
||||
7,31,183
|
||||
8,6,124
|
||||
8,40,167
|
||||
9,32,109
|
||||
10,39,166
|
||||
11,38,117
|
||||
12,17,199
|
||||
13,39,185
|
||||
13,0,133
|
||||
14,10,107
|
||||
14,27,139
|
||||
14,24,182
|
||||
15,49,141
|
||||
16,22,140
|
||||
17,30,105
|
||||
17,29,151
|
||||
18,41,125
|
||||
19,34,163
|
||||
20,6,197
|
||||
20,15,158
|
||||
20,25,155
|
||||
20,47,158
|
||||
21,48,169
|
||||
21,1,132
|
||||
22,0,152
|
||||
23,47,121
|
||||
24,11,120
|
||||
25,4,169
|
||||
26,36,169
|
||||
27,31,103
|
||||
28,8,193
|
||||
29,40,174
|
||||
30,34,161
|
||||
31,18,161
|
||||
32,47,193
|
||||
33,15,194
|
||||
34,2,123
|
||||
35,19,154
|
||||
36,23,108
|
||||
37,32,102
|
||||
37,23,130
|
||||
38,10,139
|
||||
39,48,135
|
||||
40,7,123
|
||||
41,35,194
|
||||
42,37,105
|
||||
43,39,165
|
||||
44,19,183
|
||||
45,34,191
|
||||
46,47,174
|
||||
47,24,103
|
||||
48,34,178
|
||||
48,24,105
|
||||
49,28,193
|
||||
50,17,150
|
||||
50,45,161
|
||||
50,17,156
|
||||
51,1,165
|
||||
52,34,178
|
||||
52,15,174
|
||||
52,40,107
|
||||
53,35,125
|
||||
54,32,150
|
||||
54,3,144
|
||||
55,32,143
|
||||
56,13,104
|
||||
57,20,169
|
||||
57,47,125
|
||||
58,19,167
|
||||
58,7,118
|
||||
59,6,183
|
||||
59,2,196
|
||||
60,16,119
|
||||
61,32,111
|
||||
62,47,146
|
||||
63,11,100
|
||||
63,50,189
|
||||
64,21,113
|
||||
65,21,163
|
||||
66,45,137
|
||||
67,29,136
|
||||
68,37,110
|
||||
69,37,199
|
||||
70,44,176
|
||||
71,50,102
|
||||
71,7,132
|
||||
72,26,105
|
||||
72,26,149
|
||||
73,33,109
|
||||
74,20,104
|
||||
74,29,122
|
||||
75,32,109
|
||||
76,27,143
|
||||
77,46,101
|
||||
78,32,112
|
||||
79,4,139
|
||||
80,47,101
|
||||
81,18,183
|
||||
82,3,164
|
||||
83,34,162
|
||||
84,48,172
|
||||
85,16,116
|
||||
86,43,108
|
||||
87,27,174
|
||||
87,29,114
|
||||
87,28,123
|
||||
88,45,137
|
||||
88,5,134
|
||||
88,34,193
|
||||
89,40,194
|
||||
89,36,148
|
||||
90,23,168
|
||||
91,28,161
|
||||
92,48,159
|
||||
92,45,149
|
||||
93,30,177
|
||||
94,34,174
|
||||
95,32,108
|
||||
96,20,133
|
||||
97,31,175
|
||||
98,22,198
|
||||
99,32,134
|
||||
99,2,100
|
||||
100,17,139
|
||||
101,24,163
|
||||
102,41,121
|
||||
102,30,159
|
||||
102,2,163
|
||||
103,39,192
|
||||
103,45,171
|
||||
104,23,110
|
||||
105,49,113
|
||||
106,31,159
|
||||
106,46,129
|
||||
107,21,134
|
||||
107,22,184
|
||||
108,1,136
|
||||
109,26,104
|
||||
110,41,182
|
||||
111,1,177
|
||||
112,25,125
|
||||
113,16,161
|
||||
114,39,103
|
||||
115,32,188
|
||||
116,8,141
|
||||
116,42,188
|
||||
117,47,117
|
||||
118,38,139
|
||||
119,28,171
|
||||
120,41,138
|
||||
121,25,113
|
||||
121,34,131
|
||||
122,49,150
|
||||
123,24,137
|
||||
124,23,196
|
||||
125,12,122
|
||||
126,6,162
|
||||
127,35,114
|
||||
128,44,196
|
||||
129,19,124
|
||||
129,0,116
|
||||
129,7,196
|
||||
130,45,165
|
||||
130,15,177
|
||||
130,13,152
|
||||
131,11,150
|
||||
131,50,138
|
||||
132,22,150
|
||||
133,14,169
|
||||
134,27,105
|
||||
134,33,166
|
||||
135,1,106
|
||||
136,31,150
|
||||
137,22,171
|
||||
138,21,141
|
||||
139,50,163
|
||||
140,24,114
|
||||
141,21,128
|
||||
142,21,132
|
||||
143,48,193
|
||||
144,41,126
|
||||
145,5,135
|
||||
146,14,128
|
||||
147,42,137
|
||||
148,36,156
|
||||
149,32,196
|
||||
149,7,126
|
||||
150,43,154
|
||||
151,43,132
|
||||
151,4,167
|
||||
152,38,185
|
||||
153,3,165
|
||||
154,5,109
|
||||
155,44,104
|
||||
156,31,173
|
||||
157,29,196
|
||||
157,46,137
|
||||
158,34,112
|
||||
159,39,130
|
||||
160,15,146
|
||||
160,12,199
|
||||
161,49,187
|
||||
162,41,151
|
||||
163,29,155
|
||||
164,18,114
|
||||
165,16,128
|
||||
166,18,107
|
||||
166,27,104
|
||||
167,25,128
|
||||
168,36,146
|
||||
169,25,167
|
||||
169,22,175
|
||||
Firm_Code,材料id,材料数量
|
||||
7,10,7454
|
||||
9,37,7037
|
||||
640320,33,362
|
||||
640320,109,15220
|
||||
829768,23,92483
|
||||
863079,8,14
|
||||
863079,92,13
|
||||
863079,31,0
|
||||
863079,11,21
|
||||
863079,91,84
|
||||
863079,105,13
|
||||
1452048,30,1328
|
||||
1452048,91,18591
|
||||
1452048,8,3025
|
||||
1452048,92,2789
|
||||
1452048,7,531
|
||||
1452048,90,9295
|
||||
1452048,9,266
|
||||
1452048,31,33
|
||||
1452048,11,4648
|
||||
1452048,102,2789
|
||||
1452048,18,2058
|
||||
1452048,105,2789
|
||||
2010673,92,2151
|
||||
2010673,7,410
|
||||
2010673,33,51
|
||||
2010673,90,7171
|
||||
2624175,92,3266
|
||||
2728939,95,568
|
||||
2728939,92,341
|
||||
2728939,90,1137
|
||||
5278074,36,15
|
||||
5278074,105,116
|
||||
5849940,26,396387
|
||||
5849940,36,55494
|
||||
7299120,7,1
|
||||
7299120,34,53
|
||||
7299120,32,30
|
||||
9746245,33,0
|
||||
9746245,91,68
|
||||
9746245,35,678
|
||||
9746245,92,10
|
||||
9746245,90,34
|
||||
11807506,33,393
|
||||
11807506,92,16518
|
||||
11807506,7,3146
|
||||
11807506,90,55062
|
||||
11807506,9,1573
|
||||
11807506,36,2202
|
||||
11807506,31,197
|
||||
11807506,23,1966
|
||||
11807506,105,16518
|
||||
15613202,7,1
|
||||
15613202,33,0
|
||||
15613202,34,115
|
||||
15613202,32,66
|
||||
18065940,95,601
|
||||
18065940,104,687
|
||||
22324879,95,539
|
||||
24284343,95,1
|
||||
24284343,91,4
|
||||
24284343,35,44
|
||||
24284343,92,1
|
||||
24284343,90,2
|
||||
24673506,95,1764
|
||||
24673506,101,1058
|
||||
24673506,103,705
|
||||
24673506,102,1058
|
||||
24673506,106,403
|
||||
24673506,90,3527
|
||||
24673506,105,1058
|
||||
25036634,31,93
|
||||
25036634,9,741
|
||||
25036634,105,7777
|
||||
25228347,91,1599
|
||||
25624519,102,1767
|
||||
25624519,36,236
|
||||
25945288,92,4086
|
||||
25945288,90,13620
|
||||
25945288,93,1362
|
||||
25945288,94,4086
|
||||
26162741,31,6
|
||||
26162741,11,871
|
||||
26162741,7,99
|
||||
26516263,15,3679
|
||||
26516263,25,3066
|
||||
26516263,7,24527
|
||||
26516263,12,4844
|
||||
26516263,33,3066
|
||||
26516263,36,17169
|
||||
26516263,8,139683
|
||||
27731896,7,5625
|
||||
27731896,20,1687
|
||||
27731896,8,32033
|
||||
29954548,31,15
|
||||
29954548,7,234
|
||||
29954548,9,117
|
||||
29954548,27,15
|
||||
29954548,18,905
|
||||
29954548,10,4089
|
||||
33822284,95,47
|
||||
33822284,105,28
|
||||
33822284,15,1
|
||||
33822284,33,1
|
||||
33822284,91,189
|
||||
33822284,35,1892
|
||||
33822284,107,68
|
||||
33822284,92,28
|
||||
33822284,7,5
|
||||
33822284,90,95
|
||||
33822284,93,9
|
||||
33822284,103,19
|
||||
33822284,106,11
|
||||
33822284,94,28
|
||||
43407343,93,2862
|
||||
59234665,95,13
|
||||
59234665,38,255
|
||||
59234665,7,1
|
||||
59234665,33,0
|
||||
68804111,95,9
|
||||
68804111,103,4
|
||||
68804111,92,5
|
||||
68804111,90,18
|
||||
70634828,7,84300
|
||||
70634828,93,147525
|
||||
71271700,92,47
|
||||
71271700,31,1
|
||||
71271700,11,78
|
||||
71271700,25,1
|
||||
71271700,9,4
|
||||
71271700,27,1
|
||||
71271700,18,35
|
||||
71271700,8,51
|
||||
74680108,91,8
|
||||
74680108,90,4
|
||||
74680108,93,0
|
||||
74680108,94,1
|
||||
80158773,7,1616
|
||||
118882692,38,89
|
||||
118882692,91,18
|
||||
118882692,90,9
|
||||
118882692,35,178
|
||||
144312602,102,223
|
||||
145511905,25,355
|
||||
145511905,9,1422
|
||||
145511905,8,16192
|
||||
145511905,92,14926
|
||||
145511905,31,178
|
||||
145511905,102,14926
|
||||
151606446,7,148
|
||||
151606446,91,5177
|
||||
151606446,109,776
|
||||
151606446,20,44
|
||||
152008168,91,875
|
||||
152008168,94,131
|
||||
191912252,7,141949
|
||||
194210021,7,44504
|
||||
203314437,31,12
|
||||
203314437,7,189
|
||||
203314437,22,95
|
||||
213386023,19,514
|
||||
218633337,33,373840
|
||||
249316393,95,11
|
||||
249316393,101,7
|
||||
249316393,31,0
|
||||
249316393,9,1
|
||||
249316393,18,5
|
||||
249316393,20,0
|
||||
249316393,8,7
|
||||
251189644,23,3126
|
||||
271860868,12,17177
|
||||
301209792,95,851
|
||||
301209792,7,97
|
||||
301209792,20,29
|
||||
314284469,93,8113
|
||||
343012684,92,20
|
||||
359737460,105,118
|
||||
400488703,28,6157
|
||||
400692942,91,3
|
||||
400692942,36,0
|
||||
400692942,35,27
|
||||
400692942,38,13
|
||||
400692942,7,0
|
||||
400692942,90,1
|
||||
413274977,91,38
|
||||
413274977,90,19
|
||||
420984285,31,23
|
||||
420984285,9,186
|
||||
420984285,18,1438
|
||||
420984285,16,71
|
||||
420984285,8,2114
|
||||
448033045,90,10
|
||||
448033045,93,1
|
||||
448033045,94,3
|
||||
453289520,95,1440
|
||||
453289520,37,399
|
||||
483081978,33,0
|
||||
483081978,90,0
|
||||
483081978,36,0
|
||||
483081978,35,0
|
||||
495782506,19,289
|
||||
495782506,90,202
|
||||
495782506,8,66
|
||||
499022815,31,0
|
||||
499022815,11,24
|
||||
499022815,91,95
|
||||
499022815,105,14
|
||||
500189853,104,330
|
||||
503176785,38,30
|
||||
503176785,7,0
|
||||
503176785,33,0
|
||||
503176785,91,6
|
||||
503176785,20,0
|
||||
525126393,107,20
|
||||
560866402,31,48
|
||||
560866402,9,382
|
||||
560866402,23,478
|
||||
561545339,33,9946
|
||||
571058167,91,28
|
||||
571058167,90,14
|
||||
571058167,94,4
|
||||
581407487,33,32041
|
||||
591452402,95,101
|
||||
591452402,8,65
|
||||
593312758,31,384
|
||||
593312758,9,3069
|
||||
593312758,27,384
|
||||
594378026,27,2546589
|
||||
607512171,91,274
|
||||
620220747,15,474
|
||||
631449822,7,17750
|
||||
644292599,91,835
|
||||
644292599,8,136
|
||||
644292599,31,1
|
||||
644292599,11,209
|
||||
644292599,105,125
|
||||
653528340,7,36
|
||||
658759701,17,761
|
||||
658759701,29,882
|
||||
658759701,106,4410
|
||||
677887241,31,51
|
||||
677887241,11,7160
|
||||
688155470,30,788
|
||||
688155470,92,1655
|
||||
688155470,31,20
|
||||
688155470,7,315
|
||||
688155470,91,11035
|
||||
688155470,105,1655
|
||||
695995052,8,250
|
||||
750610681,92,1
|
||||
750610681,90,2
|
||||
771821595,38,921
|
||||
771821595,31,0
|
||||
771821595,11,46
|
||||
771821595,7,5
|
||||
771821595,91,184
|
||||
771821595,105,28
|
||||
771821595,10,92
|
||||
830662620,95,2
|
||||
830662620,103,1
|
||||
830662620,33,0
|
||||
830662620,91,9
|
||||
830662620,35,86
|
||||
830662620,92,1
|
||||
830662620,7,0
|
||||
830662620,90,4
|
||||
830662620,94,1
|
||||
868012326,29,1288
|
||||
887840774,12,3
|
||||
887840774,8,99
|
||||
888356483,91,7032
|
||||
888395016,7,213
|
||||
888478182,31,14
|
||||
888478182,9,112
|
||||
930767828,7,0
|
||||
930767828,33,0
|
||||
930767828,90,2
|
||||
930767828,35,34
|
||||
996174506,15,2052
|
||||
1010117174,7,15
|
||||
1010117174,109,79
|
||||
1033972427,95,148
|
||||
1033972427,8,96
|
||||
1033972427,105,89
|
||||
1128343125,95,1359
|
||||
1128343125,31,10
|
||||
1128343125,11,1359
|
||||
1186341289,15,658
|
||||
1186341289,106,8771
|
||||
1217957486,31,2463
|
||||
1232020820,91,294
|
||||
1307012237,7,1092
|
||||
1307012237,102,5734
|
||||
1428342684,15,4
|
||||
1428342684,102,144
|
||||
1428342684,108,191
|
||||
1428342684,106,55
|
||||
1606833003,31,619
|
||||
1606833003,9,4951
|
||||
1679596339,95,126
|
||||
2310825263,15,474
|
||||
2311541114,103,30
|
||||
2311541114,91,300
|
||||
2311838590,34,76
|
||||
2312490120,38,0
|
||||
2312490120,7,0
|
||||
2316990095,38,8
|
||||
2316990095,7,0
|
||||
2316990095,91,2
|
||||
2316990095,36,0
|
||||
2316990095,35,16
|
||||
2317245827,7,7460
|
||||
2317841563,91,89
|
||||
2320102626,31,25
|
||||
2320102626,18,1540
|
||||
2320475044,92,1
|
||||
2320475044,91,10
|
||||
2320475044,90,5
|
||||
2320475044,94,1
|
||||
2321109759,95,166
|
||||
2321173423,107,148
|
||||
2321857672,103,7125
|
||||
2324787028,95,79
|
||||
2324787028,15,1
|
||||
2324787028,31,1
|
||||
2324787028,11,79
|
||||
2324787028,9,5
|
||||
2324787028,18,35
|
||||
2324787028,8,51
|
||||
2326478786,33,14487
|
||||
2327031723,38,15
|
||||
2327031723,7,0
|
||||
2327031723,91,3
|
||||
2327031723,35,29
|
||||
2327979389,13,2410
|
||||
2329375731,31,0
|
||||
2329375731,7,1
|
||||
2329375731,109,4
|
||||
2329375731,20,0
|
||||
2333843479,34,2
|
||||
2333843479,91,1
|
||||
2333843479,32,1
|
||||
2333843479,38,4
|
||||
2333843479,7,0
|
||||
2333843479,90,0
|
||||
2333843479,105,0
|
||||
2337952436,24,42333
|
||||
2339188563,108,189
|
||||
2339188563,106,54
|
||||
2339188563,36,19
|
||||
2339188563,105,142
|
||||
2339188563,37,66
|
||||
2339684065,91,184
|
||||
2341555098,31,4
|
||||
2341555098,11,617
|
||||
2343704209,95,951
|
||||
2343704209,7,109
|
||||
2348941764,7,53
|
||||
2349168009,104,1004
|
||||
2349656760,95,265
|
||||
2350111843,95,1780
|
||||
2352036411,17,206
|
||||
2352538239,102,446
|
||||
2354145351,7,337
|
||||
2354145351,33,42
|
||||
2424229017,30,183
|
||||
2424229017,95,641
|
||||
2424229017,31,5
|
||||
2424229017,26,366
|
||||
2545430247,25,426
|
||||
2820140348,33,12114
|
||||
2944404352,95,18
|
||||
2944404352,103,7
|
||||
2944404352,92,11
|
||||
2944892892,95,6
|
||||
2944892892,8,4
|
||||
2944892892,91,23
|
||||
2944892892,90,11
|
||||
2944892892,94,3
|
||||
2965658107,102,1077
|
||||
3006753238,95,985
|
||||
3006753238,101,591
|
||||
3006753238,104,1126
|
||||
3006753238,90,1970
|
||||
3006753238,103,394
|
||||
3006753238,9,56
|
||||
3006753238,31,7
|
||||
3006753238,105,591
|
||||
3025036704,17,618
|
||||
3026382513,15,1658
|
||||
3045721313,25,2842
|
||||
3047163873,27,5357806
|
||||
3048263744,7,2358
|
||||
3048263744,33,295
|
||||
3069206426,93,101
|
||||
3072715478,33,14
|
||||
3072715478,109,568
|
||||
3103797386,25,635
|
||||
3103797386,7,5082
|
||||
3111033905,93,280
|
||||
3113895788,38,0
|
||||
3113895788,7,0
|
||||
3113895788,35,1
|
||||
3120341363,91,924
|
||||
3122923980,34,2
|
||||
3127420424,7,0
|
||||
3127420424,34,2
|
||||
3127420424,32,1
|
||||
3133307899,31,1961
|
||||
3133307899,9,15687
|
||||
3133307899,23,19608
|
||||
3147511625,7,3144
|
||||
3177507356,17,17
|
||||
3177507356,15,8
|
||||
3177507356,24,17
|
||||
3195502499,31,0
|
||||
3195502499,11,43
|
||||
3195502499,9,2
|
||||
3195502499,18,19
|
||||
3203777710,95,34
|
||||
3203777710,38,683
|
||||
3211956484,34,1
|
||||
3211956484,35,4
|
||||
3215814536,7,107
|
||||
3221190269,20,710
|
||||
3226664625,31,1
|
||||
3226664625,13,7
|
||||
3226664625,18,47
|
||||
3226664625,28,1
|
||||
3226664625,8,68
|
||||
3269940677,28,58257
|
||||
3299144127,95,60
|
||||
3312358902,95,27
|
||||
3312358902,31,0
|
||||
3312358902,11,27
|
||||
3312358902,91,108
|
||||
3312358902,8,18
|
||||
3344297292,12,504
|
||||
3372913783,20,430117
|
||||
3373311444,95,28
|
||||
3373311444,15,0
|
||||
3373311444,31,0
|
||||
3373311444,20,1
|
||||
3384021594,38,2
|
||||
3384021594,7,0
|
||||
3384021594,33,0
|
||||
3384021594,90,0
|
||||
3384021594,35,4
|
||||
3391580446,90,0
|
||||
3391580446,35,1
|
||||
3395900897,25,24
|
||||
3395900897,23,118
|
||||
3407754893,33,0
|
||||
3407754893,8,6
|
||||
3407754893,38,176
|
||||
3407754893,92,5
|
||||
3407754893,7,1
|
||||
3407754893,90,18
|
||||
3433628561,29,89
|
||||
3445244192,8,71
|
||||
3445244192,31,1
|
||||
3445244192,24,4
|
||||
3445244192,105,65
|
||||
3445928818,95,49
|
||||
3445928818,90,97
|
||||
4037576402,105,271
|
||||
4208851809,31,8
|
||||
4208851809,9,62
|
||||
4208851809,18,481
|
||||
4208851809,16,24
|
||||
4208851809,8,707
|
||||
4518234098,12,450
|
||||
5007015990,95,5044
|
||||
11164476478,95,328
|
||||
11164476478,31,2
|
||||
|
||||
|
@@ -1,221 +1,702 @@
|
||||
Firm_Code,产品id,产品数量
|
||||
0,8,64
|
||||
1,11,21
|
||||
1,0,46
|
||||
2,57,55
|
||||
3,0,55
|
||||
4,33,45
|
||||
5,95,62
|
||||
6,47,46
|
||||
7,88,88
|
||||
8,103,39
|
||||
8,0,30
|
||||
9,15,93
|
||||
10,60,57
|
||||
11,102,25
|
||||
12,63,91
|
||||
13,62,42
|
||||
13,68,66
|
||||
14,21,65
|
||||
14,92,31
|
||||
14,66,32
|
||||
15,75,81
|
||||
16,25,79
|
||||
17,15,62
|
||||
17,50,95
|
||||
18,100,87
|
||||
19,85,24
|
||||
20,56,56
|
||||
20,28,91
|
||||
20,77,50
|
||||
20,91,28
|
||||
21,68,70
|
||||
21,46,48
|
||||
22,93,97
|
||||
23,61,59
|
||||
24,68,60
|
||||
25,75,30
|
||||
26,15,42
|
||||
27,89,20
|
||||
28,89,65
|
||||
29,47,40
|
||||
30,84,55
|
||||
31,38,73
|
||||
32,99,76
|
||||
33,32,20
|
||||
34,93,82
|
||||
35,100,73
|
||||
36,22,74
|
||||
37,9,59
|
||||
37,68,34
|
||||
38,99,40
|
||||
39,33,66
|
||||
40,51,92
|
||||
41,94,72
|
||||
42,9,28
|
||||
43,18,93
|
||||
44,57,71
|
||||
45,95,76
|
||||
46,0,45
|
||||
47,68,60
|
||||
48,3,54
|
||||
48,15,82
|
||||
49,23,44
|
||||
50,79,94
|
||||
50,1,57
|
||||
50,91,21
|
||||
51,31,26
|
||||
52,90,53
|
||||
52,83,36
|
||||
52,23,62
|
||||
53,11,78
|
||||
54,49,70
|
||||
54,34,73
|
||||
55,32,43
|
||||
56,32,44
|
||||
57,60,90
|
||||
57,50,71
|
||||
58,42,89
|
||||
58,100,52
|
||||
59,11,68
|
||||
59,66,48
|
||||
60,64,82
|
||||
61,32,41
|
||||
62,39,45
|
||||
63,73,47
|
||||
63,42,68
|
||||
64,43,90
|
||||
65,28,68
|
||||
66,12,39
|
||||
67,11,82
|
||||
68,94,80
|
||||
69,45,68
|
||||
70,1,90
|
||||
71,34,20
|
||||
71,86,32
|
||||
72,80,70
|
||||
72,89,75
|
||||
73,7,81
|
||||
74,92,51
|
||||
74,25,49
|
||||
75,73,48
|
||||
76,89,68
|
||||
77,33,64
|
||||
78,104,49
|
||||
79,6,35
|
||||
80,67,59
|
||||
81,57,38
|
||||
82,74,37
|
||||
83,28,20
|
||||
84,35,97
|
||||
85,88,66
|
||||
86,20,85
|
||||
87,35,57
|
||||
87,9,70
|
||||
87,100,82
|
||||
88,72,23
|
||||
88,23,20
|
||||
88,63,27
|
||||
89,98,48
|
||||
89,48,74
|
||||
90,98,22
|
||||
91,35,51
|
||||
92,81,29
|
||||
92,102,93
|
||||
93,95,53
|
||||
94,23,74
|
||||
95,22,51
|
||||
96,61,69
|
||||
97,95,26
|
||||
98,36,27
|
||||
99,11,84
|
||||
99,54,76
|
||||
100,12,86
|
||||
101,22,78
|
||||
102,88,91
|
||||
102,98,73
|
||||
102,104,86
|
||||
103,29,70
|
||||
103,16,27
|
||||
104,61,53
|
||||
105,83,54
|
||||
106,88,97
|
||||
106,85,51
|
||||
107,12,65
|
||||
107,58,35
|
||||
108,18,87
|
||||
109,48,56
|
||||
110,99,73
|
||||
111,11,33
|
||||
112,60,74
|
||||
113,104,67
|
||||
114,18,26
|
||||
115,75,93
|
||||
116,8,26
|
||||
116,70,52
|
||||
117,27,42
|
||||
118,77,38
|
||||
119,94,38
|
||||
120,51,55
|
||||
121,82,48
|
||||
121,15,79
|
||||
122,68,21
|
||||
123,98,20
|
||||
124,11,66
|
||||
125,24,88
|
||||
126,51,39
|
||||
127,84,30
|
||||
128,99,21
|
||||
129,52,86
|
||||
129,22,31
|
||||
129,15,39
|
||||
130,56,24
|
||||
130,38,56
|
||||
130,52,57
|
||||
131,41,28
|
||||
131,57,72
|
||||
132,38,63
|
||||
133,13,43
|
||||
134,94,93
|
||||
134,4,49
|
||||
135,34,78
|
||||
136,86,33
|
||||
137,92,28
|
||||
138,106,59
|
||||
139,74,85
|
||||
140,17,44
|
||||
141,75,92
|
||||
142,8,41
|
||||
143,73,23
|
||||
144,57,45
|
||||
145,16,77
|
||||
146,101,48
|
||||
147,6,56
|
||||
148,45,94
|
||||
149,12,89
|
||||
149,39,37
|
||||
150,41,61
|
||||
151,8,60
|
||||
151,49,57
|
||||
152,26,53
|
||||
153,65,36
|
||||
154,4,56
|
||||
155,28,44
|
||||
156,36,95
|
||||
157,37,46
|
||||
157,82,76
|
||||
158,7,50
|
||||
159,64,25
|
||||
160,85,59
|
||||
160,16,31
|
||||
161,70,72
|
||||
162,88,90
|
||||
163,44,29
|
||||
164,3,64
|
||||
165,35,36
|
||||
166,69,45
|
||||
166,30,81
|
||||
167,18,65
|
||||
168,60,83
|
||||
169,53,21
|
||||
169,38,73
|
||||
Firm_Code,产品id,产品数量
|
||||
7,10,294.702071428571
|
||||
9,37,10261.9146907216
|
||||
640320,33,402943.06536893
|
||||
640320,109,228.425774018668
|
||||
829768,23,80934.9713580668
|
||||
863079,8,959.058841405734
|
||||
863079,61,26.413256531112
|
||||
863079,92,1043.61505949941
|
||||
863079,31,90860.3700024452
|
||||
863079,11,610.763228449072
|
||||
863079,91,123.804918517439
|
||||
863079,105,1043.61505949941
|
||||
1452048,30,187769.42686025
|
||||
1452048,91,12792.1713758336
|
||||
1452048,84,26251.9602592503
|
||||
1452048,8,82052.7707135904
|
||||
1452048,59,2024.3402691003
|
||||
1452048,61,4716.29804578363
|
||||
1452048,92,89064.3083818613
|
||||
1452048,7,470424.993411999
|
||||
1452048,90,26251.9602592503
|
||||
1452048,74,3101.12337977363
|
||||
1452048,9,941517.604331582
|
||||
1452048,63,2024.3402691003
|
||||
1452048,31,7536814.15720574
|
||||
1452048,11,53171.5380260835
|
||||
1452048,62,12792.1713758336
|
||||
1452048,102,89064.3083818613
|
||||
1452048,18,120904.669181341
|
||||
1452048,105,89064.3083818613
|
||||
2010673,67,421.411375338393
|
||||
2010673,92,6231.87102232306
|
||||
2010673,68,269.172257950148
|
||||
2010673,64,154.992919908965
|
||||
2010673,7,33190.881393158
|
||||
2010673,33,266307.029893908
|
||||
2010673,90,1791.56343183259
|
||||
2624175,92,2145.12992304762
|
||||
2728939,95,1684.26358795852
|
||||
2728939,68,144.211706572806
|
||||
2728939,87,828.679209410901
|
||||
2728939,63,58.6532687180443
|
||||
2728939,61,144.211706572806
|
||||
2728939,92,2825.04275935534
|
||||
2728939,71,400.887020137092
|
||||
2728939,62,400.887020137092
|
||||
2728939,79,144.211706572806
|
||||
2728939,90,828.679209410901
|
||||
5278074,68,0.0893213254146603
|
||||
5278074,36,174.045229668272
|
||||
5278074,105,22.0676215730337
|
||||
5849940,26,13323.3623684211
|
||||
5849940,36,679763.386143932
|
||||
7299120,7,7337.25827463899
|
||||
7299120,34,31.1023519589892
|
||||
7299120,32,94.4505246989892
|
||||
9746245,33,6966938.61256512
|
||||
9746245,91,22753.7639936955
|
||||
9746245,35,353.167707981262
|
||||
9746245,92,163794.555422267
|
||||
9746245,90,47643.315422267
|
||||
11807506,33,10877479.0767219
|
||||
11807506,92,247776.012776287
|
||||
11807506,71,27404.1199871709
|
||||
11807506,7,1349635.47672187
|
||||
11807506,90,66293.2775381914
|
||||
11807506,60,14441.0674701641
|
||||
11807506,9,2710755.99100758
|
||||
11807506,36,1932972.83998717
|
||||
11807506,31,21766443.1910076
|
||||
11807506,23,2166307.78529329
|
||||
11807506,105,247776.012776287
|
||||
15613202,7,9588.30878075103
|
||||
15613202,33,77194.158976001
|
||||
15613202,34,40.7070797075611
|
||||
15613202,32,123.48975341603
|
||||
16190441,84,1122.53076976905
|
||||
18065940,95,2183.3601628996
|
||||
18065940,104,1671.63512472
|
||||
22324879,95,82.4799401868132
|
||||
22324879,71,18.9920914903846
|
||||
22324879,87,40.1547077225275
|
||||
22324879,81,11.9378860796703
|
||||
22324879,63,2.06199850467033
|
||||
22324879,83,18.9920914903846
|
||||
22324879,84,40.1547077225275
|
||||
24284343,95,379.573332692972
|
||||
24284343,91,89.0357200144009
|
||||
24284343,35,1.87443621082949
|
||||
24284343,92,637.828988407258
|
||||
24284343,90,185.881590907258
|
||||
24284343,87,185.881590907258
|
||||
24673506,95,7981.7296870385
|
||||
24673506,101,13534.2372954131
|
||||
24673506,103,20474.8718058814
|
||||
24673506,67,818.994872235255
|
||||
24673506,81,1041.09517657024
|
||||
24673506,82,3817.34898075754
|
||||
24673506,84,3817.34898075754
|
||||
24673506,85,5483.10126326993
|
||||
24673506,102,13534.2372954131
|
||||
24673506,106,36091.299454435
|
||||
24673506,90,3817.34898075754
|
||||
24673506,105,13534.2372954131
|
||||
25036634,31,683881.256721779
|
||||
25036634,9,78980.8516594446
|
||||
25036634,105,796.445562952383
|
||||
25228347,91,2269.58960354762
|
||||
25624519,102,75.1548549771911
|
||||
25624519,36,4227.460592467
|
||||
25945288,92,71054.567902689
|
||||
25945288,90,10658.1851854034
|
||||
25945288,93,243615.661380648
|
||||
25945288,94,71054.567902689
|
||||
26162741,31,186747.545396309
|
||||
26162741,11,145.36210035427
|
||||
26162741,7,10549.4406654165
|
||||
26516263,15,2312920.64670895
|
||||
26516263,74,470.622448765144
|
||||
26516263,25,2775966.30635256
|
||||
26516263,7,344976.593223611
|
||||
26516263,12,1756093.58764385
|
||||
26516263,82,17537.1624756296
|
||||
26516263,33,2775966.30635256
|
||||
26516263,36,493812.698109057
|
||||
26516263,8,58672.9006827749
|
||||
27075840,65,31.1692258057143
|
||||
27731896,7,48417.451860066
|
||||
27731896,20,180236.219184399
|
||||
27731896,8,1843.58160387053
|
||||
29954548,31,531721.741836549
|
||||
29954548,7,31874.3278485125
|
||||
29954548,9,65197.4887810482
|
||||
29954548,27,531721.741836549
|
||||
29954548,18,7150.69231792142
|
||||
29954548,10,455.347540693035
|
||||
31654817,86,0.956502428571429
|
||||
33822284,95,87688.8369577663
|
||||
33822284,105,147066.777802261
|
||||
33822284,15,5194191.74958436
|
||||
33822284,33,6233305.71436302
|
||||
33822284,91,20888.6535077091
|
||||
33822284,35,848.598472691957
|
||||
33822284,84,43155.3813243948
|
||||
33822284,61,7528.61681769767
|
||||
33822284,107,60968.7635777434
|
||||
33822284,92,147066.777802261
|
||||
33822284,7,777957.399275023
|
||||
33822284,90,43155.3813243948
|
||||
33822284,93,443956.482024738
|
||||
33822284,103,221289.203857881
|
||||
33822284,85,60968.7635777434
|
||||
33822284,106,388289.662483023
|
||||
33822284,94,147066.777802261
|
||||
43407343,93,449.556141428571
|
||||
59234665,95,18547.5041392281
|
||||
59234665,38,734.925678913555
|
||||
59234665,67,2422.43311199598
|
||||
59234665,68,1672.42980840379
|
||||
59234665,81,2922.43531439078
|
||||
59234665,60,2922.43531439078
|
||||
59234665,7,163860.644210215
|
||||
59234665,64,1109.92733070965
|
||||
59234665,65,734.925678913555
|
||||
59234665,33,1312303.20283576
|
||||
59234665,82,9172.4628443257
|
||||
59234665,83,4484.94219687451
|
||||
59234665,84,9172.4628443257
|
||||
68804111,95,20.9215928027211
|
||||
68804111,103,54.7180119455782
|
||||
68804111,92,35.9422235328798
|
||||
68804111,77,0.643741317006802
|
||||
68804111,90,9.65611975510204
|
||||
70634828,7,60530.1130396136
|
||||
70634828,93,19764.9348700779
|
||||
71271700,92,195.445832718175
|
||||
71271700,31,20883.392350369
|
||||
71271700,11,95.7448856451597
|
||||
71271700,25,10414.7929077023
|
||||
71271700,9,2563.3433257023
|
||||
71271700,27,20883.392350369
|
||||
71271700,18,283.89022125069
|
||||
71271700,8,175.969572205668
|
||||
74680108,91,2.08691438961039
|
||||
74680108,90,5.9129241038961
|
||||
74680108,93,74.781098961039
|
||||
74680108,78,5.9129241038961
|
||||
74680108,94,23.7676361038961
|
||||
80158773,67,4.79781360790441
|
||||
80158773,69,57.8909741119044
|
||||
80158773,68,3.11231644904726
|
||||
80158773,60,5.92147838047583
|
||||
80158773,64,1.84819357990441
|
||||
80158773,7,367.601077051904
|
||||
118882692,38,374.018000577242
|
||||
118882692,91,2520.55609084663
|
||||
118882692,90,5203.72870368337
|
||||
118882692,35,105.700739293568
|
||||
144312602,102,35.0717557142857
|
||||
145511905,68,454.925299560929
|
||||
145511905,25,585009.332899561
|
||||
145511905,9,145966.322899561
|
||||
145511905,8,12467.4386765583
|
||||
145511905,61,454.925299560929
|
||||
145511905,92,13556.5262328943
|
||||
145511905,31,1170400.01289956
|
||||
145511905,102,13556.5262328943
|
||||
151606446,61,1598.19363754467
|
||||
151606446,67,2404.92140633013
|
||||
151606446,71,4623.42277049014
|
||||
151606446,87,9665.47132539925
|
||||
151606446,7,176053.0736374
|
||||
151606446,64,993.147810955577
|
||||
151606446,82,9665.47132539925
|
||||
151606446,91,4623.42277049014
|
||||
151606446,109,33195.0312483084
|
||||
151606446,20,587820.372288311
|
||||
151606446,83,4623.42277049014
|
||||
152008168,91,23.7046254037267
|
||||
152008168,94,1053.5389068323
|
||||
159511306,67,0.0540703262886598
|
||||
159511306,69,1.05839787628866
|
||||
159511306,81,0.0753259358124693
|
||||
191912252,7,22296.07161
|
||||
194210021,7,117.45116475
|
||||
203314437,31,1114.1340288
|
||||
203314437,7,26.1125163
|
||||
203314437,22,98.6472838
|
||||
213386023,64,2.69308572666667
|
||||
213386023,19,67.3271431666667
|
||||
218633337,72,0.746310168912046
|
||||
218633337,33,58510.7172427046
|
||||
239053033,82,14.0287022857143
|
||||
249316393,95,11.9633147452272
|
||||
249316393,101,21.3157829357034
|
||||
249316393,31,1961.95293245951
|
||||
249316393,71,1.44178803094146
|
||||
249316393,9,243.436902459513
|
||||
249316393,18,29.6123272982226
|
||||
249316393,20,407.105095792846
|
||||
249316393,8,19.4888082452899
|
||||
251189644,23,491.00458
|
||||
259325842,75,116.271534452381
|
||||
271860868,12,2697.9825886076
|
||||
278221281,66,0.0004463678
|
||||
301209792,95,3086.54014334826
|
||||
301209792,71,689.39622263884
|
||||
301209792,65,50.157843782994
|
||||
301209792,7,27857.0273240123
|
||||
301209792,20,93112.6118322132
|
||||
301209792,83,689.39622263884
|
||||
314284469,88,24.0772742835497
|
||||
314284469,93,2407.72742835497
|
||||
343012684,92,3.18834142857143
|
||||
354897041,72,1.75358778571429
|
||||
359737460,87,141.503406204969
|
||||
359737460,81,20.9634675859213
|
||||
359737460,80,563.393191371636
|
||||
359737460,105,563.393191371636
|
||||
400488703,28,967.130233333333
|
||||
400692942,68,40.4660822697938
|
||||
400692942,82,225.389885126937
|
||||
400692942,91,109.812508341222
|
||||
400692942,36,5773.10397084122
|
||||
400692942,35,5.79286923407948
|
||||
400692942,84,225.389885126937
|
||||
400692942,38,17.3506069126509
|
||||
400692942,7,4039.44331905551
|
||||
400692942,90,225.389885126937
|
||||
413274977,91,14.633641627381
|
||||
413274977,90,58.5345665095238
|
||||
420984285,31,247170.157243136
|
||||
420984285,9,29579.1327029697
|
||||
420984285,18,2505.59508737296
|
||||
420984285,16,79233.4852418203
|
||||
420984285,8,1223.7991400407
|
||||
448033045,90,0.910954693877551
|
||||
448033045,93,29.6060275510204
|
||||
448033045,94,8.35041802721088
|
||||
453289520,95,5038.84874610548
|
||||
453289520,68,62.6178868365067
|
||||
453289520,37,19460.2279831622
|
||||
474279224,71,0.478251214285714
|
||||
483081978,33,89.2432628575307
|
||||
483081978,90,0.607371143244999
|
||||
483081978,36,15.9114100003879
|
||||
483081978,35,0.0015862718164276
|
||||
495782506,19,114.212047547783
|
||||
495782506,90,215.917149599925
|
||||
495782506,8,918.655651048883
|
||||
499022815,61,3.83775978403305
|
||||
499022815,31,14948.1965804579
|
||||
499022815,11,99.9773090235362
|
||||
499022815,91,19.8610179906169
|
||||
499022815,105,171.191789941687
|
||||
500189853,104,51.89025675
|
||||
503176785,38,1.17000480937009
|
||||
503176785,7,1182.83310506651
|
||||
503176785,33,9502.01297756651
|
||||
503176785,91,28.3346737807987
|
||||
503176785,20,3955.89306256651
|
||||
525126393,107,3.1245746
|
||||
549184982,67,0.475818871340206
|
||||
549184982,69,9.3139013113402
|
||||
549184982,60,0.66286823514973
|
||||
560866402,31,2079.38857768421
|
||||
560866402,9,158.842183017544
|
||||
560866402,23,103.96942888421
|
||||
561545339,33,1562.2873
|
||||
571058167,91,4.71004983766234
|
||||
571058167,90,16.6663301948052
|
||||
571058167,94,72.4623051948052
|
||||
581407487,72,0.0639653907600405
|
||||
581407487,33,5014.88663558719
|
||||
591452402,95,43.0275530719446
|
||||
591452402,66,8.69948031612395e-06
|
||||
591452402,8,66.1171354016825
|
||||
593312758,31,5423.36877
|
||||
593312758,9,150.6491325
|
||||
593312758,27,5423.36877
|
||||
594378026,27,99592.5494406668
|
||||
607512171,91,43.0426092857143
|
||||
615763365,68,1.27533657142857
|
||||
620220747,15,74.3946333333333
|
||||
631449822,7,12253.6901282917
|
||||
644292599,74,52.7205409894937
|
||||
644292599,91,283.888047926637
|
||||
644292599,8,1936.01071664017
|
||||
644292599,61,91.2484588123509
|
||||
644292599,31,179759.771906069
|
||||
644292599,11,1247.08599349807
|
||||
644292599,62,283.888047926637
|
||||
644292599,105,2103.26194511711
|
||||
653528340,7,5.5795975
|
||||
654825436,61,0.605784871428572
|
||||
658759701,17,10319.7937547583
|
||||
658759701,29,8696.84494004518
|
||||
658759701,106,552.592706211826
|
||||
677887241,31,594319.392162584
|
||||
677887241,87,712.576822235752
|
||||
677887241,11,2840.19981628718
|
||||
688155470,30,36107.8997440436
|
||||
688155470,92,16456.1438554735
|
||||
688155470,31,1499270.45181122
|
||||
688155470,7,92383.382515858
|
||||
688155470,91,1270.69612339666
|
||||
688155470,84,3950.48101729258
|
||||
688155470,105,16456.1438554735
|
||||
695995052,8,39.1894468832309
|
||||
750610681,92,1.63504688644689
|
||||
750610681,90,0.14715421978022
|
||||
762985858,72,10.7765940285714
|
||||
771821595,38,60.3401355807989
|
||||
771821595,61,188.778771615543
|
||||
771821595,31,359560.082396828
|
||||
771821595,11,2500.67422024093
|
||||
771821595,7,22408.6628056262
|
||||
771821595,91,574.094679719774
|
||||
771821595,105,4213.18936737085
|
||||
771821595,10,1216.28785989349
|
||||
774948022,81,2.97578533333333
|
||||
830662620,95,2077.47753289415
|
||||
830662620,103,5242.13601321557
|
||||
830662620,33,147651.76762768
|
||||
830662620,91,495.148292733431
|
||||
830662620,80,3483.992413037
|
||||
830662620,35,20.4495206852172
|
||||
830662620,61,178.682444701289
|
||||
830662620,75,1022.591372787
|
||||
830662620,92,3483.992413037
|
||||
830662620,7,18428.2130145549
|
||||
830662620,62,495.148292733431
|
||||
830662620,90,1022.591372787
|
||||
830662620,94,3483.992413037
|
||||
857978527,60,1.91300485714286
|
||||
868012326,29,202.260409375
|
||||
887840774,12,464.171882912735
|
||||
887840774,8,0.558245939373982
|
||||
888356483,82,1472.80118390476
|
||||
888356483,91,368.200295976191
|
||||
888395016,7,33.477585
|
||||
888478182,31,158.708551111111
|
||||
888478182,9,2.47982111111111
|
||||
888662519,89,28.6950728571429
|
||||
930767828,68,60.3061211497171
|
||||
930767828,7,6201.4590965778
|
||||
930767828,64,39.0073247031457
|
||||
930767828,33,49686.5018416611
|
||||
930767828,90,344.290073770669
|
||||
930767828,35,7.05913003328861
|
||||
996174506,15,322.376744444445
|
||||
1010117174,7,77.33322135
|
||||
1010117174,109,2.80574045714286
|
||||
1033972427,59,112.873642353224
|
||||
1033972427,95,4185.1282096802
|
||||
1033972427,61,327.202830107275
|
||||
1033972427,8,6484.60377978952
|
||||
1033972427,71,970.19039336943
|
||||
1033972427,73,612.97508044601
|
||||
1033972427,105,7042.85071306755
|
||||
1128343125,95,843.110408290665
|
||||
1128343125,61,68.9173426049506
|
||||
1128343125,31,120412.928330862
|
||||
1128343125,74,43.1109070820934
|
||||
1128343125,11,843.110408290665
|
||||
1128343125,62,197.949520219236
|
||||
1128343125,63,25.906616733522
|
||||
1186341289,15,59863.0352728682
|
||||
1186341289,106,336.729573409884
|
||||
1217957486,31,386.852093333333
|
||||
1232020820,87,61.6412676190476
|
||||
1232020820,91,15.4103169047619
|
||||
1307012237,61,13.4946160198183
|
||||
1307012237,68,13.4946160198183
|
||||
1307012237,7,1974.0789017341
|
||||
1307012237,62,47.4931874483898
|
||||
1307012237,102,368.590806496009
|
||||
1375606900,67,0.297578533333333
|
||||
1428342684,15,16030.7058915616
|
||||
1428342684,102,294.097160717371
|
||||
1428342684,108,178.38680240234
|
||||
1428342684,106,1046.21448976507
|
||||
1549474227,67,0.98200916
|
||||
1601593550,85,3.1245746
|
||||
1601593550,84,1.59417071428571
|
||||
1606833003,31,6999.047104
|
||||
1606833003,9,109.360111
|
||||
1679596339,95,141.622548742709
|
||||
1679596339,61,14.1181422441375
|
||||
1679596339,71,35.368876660566
|
||||
1679596339,74,9.86799536085173
|
||||
1679596339,66,0.0005710134900607
|
||||
1679596339,62,35.368876660566
|
||||
2310825263,15,74.3946333333333
|
||||
2311541114,103,518.105482142857
|
||||
2311541114,91,5.18105482142857
|
||||
2311838590,80,14.3511414460916
|
||||
2311838590,76,14.3511414460916
|
||||
2311838590,77,0.468153740377358
|
||||
2311838590,34,0.468153740377358
|
||||
2312490120,38,0.000181155762987
|
||||
2312490120,7,5.54789524147727
|
||||
2312693498,84,193.67621647619
|
||||
2316990095,38,13.8559998091944
|
||||
2316990095,61,27.8070555184801
|
||||
2316990095,71,69.6602226463373
|
||||
2316990095,66,0.0026014898736987
|
||||
2316990095,7,2441.33969322491
|
||||
2316990095,91,69.6602226463373
|
||||
2316990095,36,3487.66887142134
|
||||
2316990095,35,6.88047195455156
|
||||
2317245827,7,1171.715475
|
||||
2317695802,89,2.86950728571429
|
||||
2317841563,91,14.0287022857143
|
||||
2320102626,31,15243.1061098413
|
||||
2320102626,18,3.96542822836663
|
||||
2320475044,92,29.8759400529101
|
||||
2320475044,91,2.17279564021164
|
||||
2320475044,90,7.06158583068783
|
||||
2320475044,94,29.8759400529101
|
||||
2321109759,95,26.1443997142857
|
||||
2321173423,107,23.2111256
|
||||
2321857672,103,1017.37076493506
|
||||
2321857672,82,122.084491792208
|
||||
2321857672,78,122.084491792208
|
||||
2324787028,95,67.7977291112468
|
||||
2324787028,15,5741.90868587315
|
||||
2324787028,31,13824.2178975398
|
||||
2324787028,11,67.7977291112468
|
||||
2324787028,9,1700.75408003982
|
||||
2324787028,18,192.304664959173
|
||||
2324787028,8,120.887165906807
|
||||
2324844174,67,1.30417026782609
|
||||
2324844174,81,1.84831387163561
|
||||
2326478786,60,0.0379065818289787
|
||||
2326478786,33,6686.72103463183
|
||||
2327031723,38,21.3365050911672
|
||||
2327031723,7,5417.04015267975
|
||||
2327031723,91,145.375669403548
|
||||
2327031723,35,5.83160955211952
|
||||
2327979389,13,378.499011695907
|
||||
2329375731,31,88.429764536862
|
||||
2329375731,7,4.735802036862
|
||||
2329375731,109,0.21898501305248
|
||||
2329375731,20,17.7548628701953
|
||||
2333843479,68,19.7864450118645
|
||||
2333843479,34,19.7864450118645
|
||||
2333843479,91,55.7238737532931
|
||||
2333843479,32,37.7551593825788
|
||||
2333843479,70,235.411017460436
|
||||
2333843479,38,7.80730209805497
|
||||
2333843479,7,2092.17816910091
|
||||
2333843479,90,115.619588322341
|
||||
2333843479,83,55.7238737532931
|
||||
2333843479,105,395.132922977896
|
||||
2334283182,86,0.797085357142857
|
||||
2337843112,85,1.87474476
|
||||
2337952436,24,6409.49732028986
|
||||
2339188563,108,141.571910169836
|
||||
2339188563,106,734.297678651978
|
||||
2339188563,36,2275.38467670555
|
||||
2339188563,105,220.602012634121
|
||||
2339188563,37,588.865995251205
|
||||
2339684065,74,1.767337508125
|
||||
2339684065,91,22.5425702566964
|
||||
2341555098,31,23591.9294382979
|
||||
2341555098,11,1.20366986930091
|
||||
2343704209,95,213.097315746753
|
||||
2343704209,69,302.795677651515
|
||||
2343704209,71,44.9128871753247
|
||||
2343704209,64,4.54862431818182
|
||||
2343704209,7,1951.00307765152
|
||||
2348941764,7,8.36939625
|
||||
2349168009,104,157.716622666667
|
||||
2349656760,95,387.110076426584
|
||||
2349656760,79,3.87110076426585
|
||||
2350111843,95,40.1321569956685
|
||||
2350111843,77,2.07133713526031
|
||||
2350111843,82,18.9872570732195
|
||||
2350111843,80,68.3253568922672
|
||||
2350111843,71,8.41480711199501
|
||||
2350111843,86,18.9872570732195
|
||||
2352036411,17,32.3454927536232
|
||||
2352538239,102,128.587312571429
|
||||
2354145351,81,0.333963355259854
|
||||
2354145351,7,66.0137967838313
|
||||
2354145351,33,534.699986783831
|
||||
2354145351,84,2.884636498117
|
||||
2379638202,81,2.33811704761905
|
||||
2424229017,30,4059.50354953162
|
||||
2424229017,95,1121.46497074591
|
||||
2424229017,31,164476.409951232
|
||||
2424229017,26,2002.87654438162
|
||||
2424229017,65,5.01031080733794
|
||||
2481687500,84,3.18834142857143
|
||||
2545430247,25,66.95517
|
||||
2791956547,81,0.106278047619048
|
||||
2820140348,68,176.05518570243
|
||||
2820140348,33,429800.204241519
|
||||
2820140348,62,1097.99541972779
|
||||
2944404352,95,22.3535529642857
|
||||
2944404352,103,62.5899483
|
||||
2944404352,92,40.2363953357143
|
||||
2944404352,82,8.94142118571429
|
||||
2944404352,84,8.94142118571429
|
||||
2944892892,95,197.176238624613
|
||||
2944892892,8,309.079991309845
|
||||
2944892892,61,9.43067908675607
|
||||
2944892892,91,40.7216056763989
|
||||
2944892892,90,92.8731499924704
|
||||
2944892892,94,336.24702346747
|
||||
2965658107,102,401.055238912699
|
||||
3006753238,95,6462.95392247204
|
||||
3006753238,101,10965.3608417999
|
||||
3006753238,104,5618.75262509807
|
||||
3006753238,82,3086.14873297613
|
||||
3006753238,84,3086.14873297613
|
||||
3006753238,90,3086.14873297613
|
||||
3006753238,103,16593.3694909598
|
||||
3006753238,87,3086.14873297613
|
||||
3006753238,77,384.704581379399
|
||||
3006753238,9,117897.525175837
|
||||
3006753238,31,945214.796602336
|
||||
3006753238,85,4436.8708087745
|
||||
3006753238,105,10965.3608417999
|
||||
3025036704,17,97.0364782608696
|
||||
3026382513,15,260.381216666667
|
||||
3029702382,77,0.0637668285714286
|
||||
3045721313,25,446.3678
|
||||
3047163873,27,1112545.37486133
|
||||
3048263744,7,52.0762433333334
|
||||
3048263744,33,3332.87957333333
|
||||
3069206426,93,15.9417071428571
|
||||
3070859372,62,0.318834142857143
|
||||
3072715478,33,3836.68695069767
|
||||
3072715478,109,2.17499260243633
|
||||
3103797386,25,19626.8614417778
|
||||
3103797386,7,306.669710027778
|
||||
3111033905,93,43.9991117142857
|
||||
3113895788,38,0.319137217137425
|
||||
3113895788,7,83.5348485028517
|
||||
3113895788,35,0.0800116099945682
|
||||
3120341363,82,1285.08003876071
|
||||
3120341363,91,550.748588040305
|
||||
3120341363,79,110.149717608061
|
||||
3122923980,34,0.318834142857143
|
||||
3127420424,7,55.3931159747292
|
||||
3127420424,34,0.234809260443528
|
||||
3127420424,32,0.713060474729242
|
||||
3133307899,31,185211.504198947
|
||||
3133307899,9,14148.1010151974
|
||||
3133307899,23,9260.57520994737
|
||||
3147511625,7,493.79437875
|
||||
3177507356,17,9.53036840062112
|
||||
3177507356,15,30.5549386904762
|
||||
3177507356,24,9.53036840062112
|
||||
3188903709,65,0.2231839
|
||||
3195502499,31,2132.4111014218
|
||||
3195502499,11,5.14970027894381
|
||||
3195502499,9,257.666341421801
|
||||
3195502499,18,24.4031685185751
|
||||
3203777710,95,1266.29847013741
|
||||
3203777710,38,38.4010630736936
|
||||
3203777710,61,103.027242392836
|
||||
3203777710,71,296.905780350265
|
||||
3203777710,74,64.2515348013507
|
||||
3211956484,34,2.95878084571429
|
||||
3211956484,35,0.184923802857143
|
||||
3215814536,7,16.7387925
|
||||
3221190269,20,111.59195
|
||||
3226664625,31,3172.12129414254
|
||||
3226664625,13,330.539963835527
|
||||
3226664625,18,32.0678107554476
|
||||
3226664625,28,2640.19966580921
|
||||
3226664625,8,15.617092294432
|
||||
3267688490,73,1.48789266666667
|
||||
3269940677,28,9150.5399
|
||||
3271705843,67,0.118227147027027
|
||||
3271705843,77,0.0672136841698842
|
||||
3271705843,62,0.25851416988417
|
||||
3299144127,95,9.3524681904762
|
||||
3312358902,95,2501.12492496074
|
||||
3312358902,59,124.238829164623
|
||||
3312358902,61,249.338097364418
|
||||
3312358902,71,624.635901963806
|
||||
3312358902,31,350277.090520393
|
||||
3312358902,66,0.0152558422253321
|
||||
3312358902,11,2501.12492496074
|
||||
3312358902,91,624.635901963806
|
||||
3312358902,79,249.338097364418
|
||||
3312358902,8,3843.27861890412
|
||||
3331430009,86,0.956502428571429
|
||||
3344297292,12,79.1031544303797
|
||||
3372913783,20,155889.706235973
|
||||
3373311444,95,577.765642958927
|
||||
3373311444,15,35079.8535755939
|
||||
3373311444,31,84225.2695261495
|
||||
3373311444,71,126.430190351784
|
||||
3373311444,65,6.07406965654522
|
||||
3373311444,20,17527.9193075383
|
||||
3384021594,38,2.45662461679646
|
||||
3384021594,67,8.08085889679646
|
||||
3384021594,68,5.58119921679646
|
||||
3384021594,64,3.70645445679646
|
||||
3384021594,7,546.132605016796
|
||||
3384021594,33,4373.7364900168
|
||||
3384021594,90,30.5777960167965
|
||||
3384021594,35,0.894337316796458
|
||||
3391580446,90,4.26078354545455
|
||||
3391580446,78,4.26078354545455
|
||||
3391580446,35,0.0202894454545455
|
||||
3395900897,25,133.595996478873
|
||||
3395900897,73,0.0044906217303822
|
||||
3395900897,23,26.4677244788732
|
||||
3398677646,66,0.0014596930502411
|
||||
3398677646,82,474.605931797054
|
||||
3398677646,79,94.656389434197
|
||||
3398677646,80,1582.79209702205
|
||||
3407754893,33,81748.1457488964
|
||||
3407754893,80,1912.24550794403
|
||||
3407754893,84,549.193552610701
|
||||
3407754893,8,1760.09246138105
|
||||
3407754893,38,23.4449412678435
|
||||
3407754893,92,1912.24550794403
|
||||
3407754893,71,257.110990753558
|
||||
3407754893,7,10187.9180938964
|
||||
3407754893,90,549.193552610701
|
||||
3407754893,87,549.193552610701
|
||||
3407754893,85,782.859602096415
|
||||
3409328588,76,13.284755952381
|
||||
3433628561,29,13.94899375
|
||||
3444191691,77,5.00569604285714
|
||||
3444191691,82,125.142401071429
|
||||
3445244192,8,21.9712471006046
|
||||
3445244192,31,3995.19331935697
|
||||
3445244192,24,705.656706313492
|
||||
3445244192,105,25.7082407855413
|
||||
3445928818,95,67.0211356847291
|
||||
3445928818,61,5.03977831330049
|
||||
3445928818,68,5.03977831330049
|
||||
3445928818,74,2.97373306758621
|
||||
3445928818,90,32.5870482561576
|
||||
4037576402,76,21.2556095238095
|
||||
4037576402,105,21.2556095238095
|
||||
4144746564,75,2.231839
|
||||
4144746564,87,2.231839
|
||||
4208851809,31,197587.418633179
|
||||
4208851809,9,23645.5102079292
|
||||
4208851809,18,2002.96860663079
|
||||
4208851809,16,63339.1182530233
|
||||
4208851809,8,978.303026964076
|
||||
4518234098,12,70.6278164556962
|
||||
5007015990,95,740.469948598131
|
||||
5007015990,74,3.62830274813084
|
||||
11164476478,95,49.6938217894364
|
||||
11164476478,67,4.72545428086494
|
||||
11164476478,31,7317.83694236087
|
||||
11164476478,81,6.11982226562685
|
||||
11164476478,60,6.11982226562685
|
||||
11212932825,81,0.212556095238095
|
||||
11220388001,77,0.191300485714286
|
||||
|
||||
|
@@ -1,108 +1,87 @@
|
||||
Code,1,1.1,1.1.1,1.1.2,1.1.3,1.2,1.2.1,1.2.2,1.2.3,1.3,1.3.1,1.3.1.1,1.3.1.2,1.3.1.3,1.3.1.4,1.3.1.5,1.3.1.6,1.3.1.7,1.3.2,1.3.2.1,1.3.3,1.3.3.1,1.3.3.2,1.3.3.3,1.3.3.4,1.3.3.5,1.3.3.6,1.3.3.7,1.3.4,1.3.4.1,1.3.4.2,1.3.4.3,1.3.5,1.3.5.1,1.4,1.4.1,1.4.1.1,1.4.1.2,1.4.1.3,1.4.1.4,1.4.1.5,1.4.2,1.4.2.1,1.4.2.2,1.4.2.3,1.4.2.4,1.4.2.5,1.4.2.6,1.4.2.7,1.4.3,1.4.3.1,1.4.3.2,1.4.3.3,1.4.3.4,1.4.3.5,1.4.3.6,1.4.4,1.4.4.1,1.4.4.2,1.4.4.3,1.4.4.4,1.4.4.5,1.4.5,1.4.5.1,1.4.5.2,1.4.5.3,1.4.5.4,1.4.5.5,1.4.5.6,1.4.5.7,1.4.5.8,1.4.5.9,2,2.1,2.1.1,2.1.1.1,2.1.1.2,2.1.1.3,2.1.1.4,2.1.1.5,2.1.2,2.1.2.1,2.1.2.2,2.1.2.3,2.1.2.4,2.1.3,2.1.3.1,2.1.3.2,2.1.3.3,2.1.3.4,2.1.3.5,2.1.3.6,2.1.3.7,2.1.4,2.1.4.1,2.1.4.1.1,2.1.4.1.2,2.1.4.1.3,2.1.4.1.4,2.1.4.2,2.1.4.2.1,2.1.4.2.2,2.2,2.3,2.3.1,2.3.2,2.3.3
|
||||
1,,1,,,,1,,,,1,,,,,,,,,,,,,,,,,,,,,,,,,1,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,1,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,
|
||||
1.1,,,1,1,1,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,
|
||||
1.1.1,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,
|
||||
1.1.2,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,
|
||||
1.1.3,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,
|
||||
1.2,,,,,,,1,1,1,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,
|
||||
1.2.1,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,
|
||||
1.2.2,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,
|
||||
1.2.3,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,
|
||||
1.3,,,,,,,,,,,1,,,,,,,,1,,1,,,,,,,,1,,,,1,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,
|
||||
1.3.1,,,,,,,,,,,,1,1,1,1,1,1,1,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,
|
||||
1.3.1.1,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,
|
||||
1.3.1.2,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,
|
||||
1.3.1.3,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,
|
||||
1.3.1.4,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,
|
||||
1.3.1.5,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,
|
||||
1.3.1.6,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,
|
||||
1.3.1.7,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,
|
||||
1.3.2,,,,,,,,,,,,,,,,,,,,1,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,
|
||||
1.3.2.1,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,
|
||||
1.3.3,,,,,,,,,,,,,,,,,,,,,,1,1,1,1,1,1,1,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,
|
||||
1.3.3.1,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,
|
||||
1.3.3.2,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,
|
||||
1.3.3.3,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,
|
||||
1.3.3.4,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,
|
||||
1.3.3.5,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,
|
||||
1.3.3.6,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,
|
||||
1.3.3.7,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,
|
||||
1.3.4,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,1,1,1,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,
|
||||
1.3.4.1,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,
|
||||
1.3.4.2,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,
|
||||
1.3.4.3,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,
|
||||
1.3.5,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,1,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,
|
||||
1.3.5.1,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,
|
||||
1.4,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,1,,,,,,1,,,,,,,,1,,,,,,,1,,,,,,1,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,
|
||||
1.4.1,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,1,1,1,1,1,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,
|
||||
1.4.1.1,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,
|
||||
1.4.1.2,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,
|
||||
1.4.1.3,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,
|
||||
1.4.1.4,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,
|
||||
1.4.1.5,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,
|
||||
1.4.2,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,1,1,1,1,1,1,1,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,
|
||||
1.4.2.1,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,
|
||||
1.4.2.2,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,
|
||||
1.4.2.3,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,
|
||||
1.4.2.4,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,
|
||||
1.4.2.5,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,
|
||||
1.4.2.6,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,
|
||||
1.4.2.7,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,
|
||||
1.4.3,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,1,1,1,1,1,1,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,
|
||||
1.4.3.1,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,
|
||||
1.4.3.2,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,
|
||||
1.4.3.3,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,
|
||||
1.4.3.4,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,
|
||||
1.4.3.5,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,
|
||||
1.4.3.6,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,
|
||||
1.4.4,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,1,1,1,1,1,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,
|
||||
1.4.4.1,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,
|
||||
1.4.4.2,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,
|
||||
1.4.4.3,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,
|
||||
1.4.4.4,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,
|
||||
1.4.4.5,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,
|
||||
1.4.5,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,1,1,1,1,1,1,1,1,1,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,
|
||||
1.4.5.1,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,
|
||||
1.4.5.2,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,
|
||||
1.4.5.3,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,
|
||||
1.4.5.4,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,
|
||||
1.4.5.5,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,
|
||||
1.4.5.6,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,
|
||||
1.4.5.7,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,
|
||||
1.4.5.8,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,
|
||||
1.4.5.9,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,
|
||||
2,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,1,,,,,,,,,,,,,,,,,,,,,,,,,,,,,1,1,,,
|
||||
2.1,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,1,,,,,,1,,,,,1,,,,,,,,1,,,,,,,,,,,,,
|
||||
2.1.1,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,1,1,1,1,1,,,,,,,,,,,,,,,,,,,,,,,,,,,
|
||||
2.1.1.1,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,
|
||||
2.1.1.2,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,
|
||||
2.1.1.3,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,
|
||||
2.1.1.4,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,
|
||||
2.1.1.5,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,
|
||||
2.1.2,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,1,1,1,1,,,,,,,,,,,,,,,,,,,,,,
|
||||
2.1.2.1,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,
|
||||
2.1.2.2,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,
|
||||
2.1.2.3,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,
|
||||
2.1.2.4,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,
|
||||
2.1.3,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,1,1,1,1,1,1,1,,,,,,,,,,,,,,
|
||||
2.1.3.1,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,
|
||||
2.1.3.2,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,
|
||||
2.1.3.3,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,
|
||||
2.1.3.4,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,
|
||||
2.1.3.5,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,
|
||||
2.1.3.6,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,
|
||||
2.1.3.7,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,
|
||||
2.1.4,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,1,,,,,1,,,,,,,
|
||||
2.1.4.1,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,1,1,1,1,,,,,,,,
|
||||
2.1.4.1.1,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,
|
||||
2.1.4.1.2,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,
|
||||
2.1.4.1.3,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,
|
||||
2.1.4.1.4,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,
|
||||
2.1.4.2,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,1,1,,,,,
|
||||
2.1.4.2.1,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,
|
||||
2.1.4.2.2,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,
|
||||
2.2,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,
|
||||
2.3,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,1,1,1
|
||||
2.3.1,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,
|
||||
2.3.2,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,
|
||||
2.3.3,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,
|
||||
Code,32338,32445,56341,7,4654,32434,32441,32444,3244,32432,32451,4655,32449,32446,32442,32433,32443,3245,32435,32437,32438,32447,32436,32448,32439,5632,56322,56319,56323,56321,8,36914,2515,2514,9,34535,34526,34529,34537,34534,34525,3453,34533,34527,34539,34528,34543,34531,34524,34532,34538,3455,34555,34554,34556,34557,34553,34545,34552,34544,34546,34549,34558,34547,34551,34548,2717,2714,2715,2716,2718,317589,1,513738,51374,513742,11,34573,34571,34567,34572,34566,34569,34568,3457,34574
|
||||
32338,1,,,,,,,,1,,,1,1,1,,1,1,,1,,1,1,1,,,1,1,1,1,,,1,,,,,1,,1,1,1,1,,1,1,1,,1,1,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,
|
||||
32445,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,
|
||||
56341,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,
|
||||
7,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,
|
||||
4654,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,
|
||||
32434,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,
|
||||
32441,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,
|
||||
32444,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,
|
||||
3244,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,
|
||||
32432,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,
|
||||
32451,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,
|
||||
4655,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,
|
||||
32449,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,
|
||||
32446,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,
|
||||
32442,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,
|
||||
32433,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,
|
||||
32443,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,
|
||||
3245,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,
|
||||
32435,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,
|
||||
32437,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,
|
||||
32438,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,
|
||||
32447,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,
|
||||
32436,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,
|
||||
32448,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,
|
||||
32439,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,
|
||||
5632,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,
|
||||
56322,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,
|
||||
56319,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,
|
||||
56323,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,
|
||||
56321,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,
|
||||
8,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,
|
||||
36914,1,,,,,,,,1,,,1,,1,,1,1,,1,,,,,,1,,,,,1,,,,,,,1,,,,1,1,,1,,,,1,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,
|
||||
2515,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,
|
||||
2514,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,
|
||||
9,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,1,1,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,
|
||||
34535,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,
|
||||
34526,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,
|
||||
34529,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,
|
||||
34537,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,
|
||||
34534,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,
|
||||
34525,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,
|
||||
3453,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,
|
||||
34533,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,
|
||||
34527,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,
|
||||
34539,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,
|
||||
34528,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,
|
||||
34543,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,
|
||||
34531,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,
|
||||
34524,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,
|
||||
34532,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,
|
||||
34538,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,
|
||||
3455,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,
|
||||
34555,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,
|
||||
34554,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,
|
||||
34556,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,
|
||||
34557,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,
|
||||
34553,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,
|
||||
34545,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,
|
||||
34552,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,
|
||||
34544,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,
|
||||
34546,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,
|
||||
34549,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,
|
||||
34558,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,
|
||||
34547,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,
|
||||
34551,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,
|
||||
34548,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,
|
||||
2717,1,1,1,1,1,,,,,,1,,1,1,1,,1,1,1,,,1,,,1,,,,,,,,,,1,1,1,1,1,,,1,1,1,1,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,
|
||||
2714,,1,1,1,1,,,,,,1,1,1,1,,,1,1,,,,1,,,1,,,,,,,,,,1,1,,1,1,,,1,1,,,,1,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,
|
||||
2715,,1,1,1,1,,,,,,1,1,1,1,,,1,1,,,,1,,,1,,,,,,,,,,1,1,,1,1,,,1,1,,,,1,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,
|
||||
2716,,1,1,1,1,,,,,,1,1,1,1,,,1,1,,,,1,,,1,,,,,,,,,,1,1,,1,1,,,1,1,,,,1,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,
|
||||
2718,,1,1,1,1,,,,,,1,1,1,1,,,1,1,,,,1,,,1,,,,,,,,,,1,1,,1,1,,,1,1,,,,1,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,
|
||||
317589,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,,,,,,1,,,,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,,,,,,,,,,,,,,,,1,1,1,1,1,,,1,,,,,,,,,,,,
|
||||
1,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,1,1,,,,1,1,1,1,1,1,1,1,1,1,,,,,,1,,1,1,1,1,1,1,1,1,1,1,1,1,1
|
||||
513738,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,1,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,
|
||||
51374,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,1,,,,,,,,,,,,,,,,,1,,,,,,,,,,,,,,
|
||||
513742,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,1,,,,,,,,,,,,,,,,1,,,,,,,,,,,,,,
|
||||
11,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,1,,,,,,,,,,,,,,,,,,1,,,,,,,,,,,,,,
|
||||
34573,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,
|
||||
34571,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,
|
||||
34567,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,
|
||||
34572,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,
|
||||
34566,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,
|
||||
34569,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,
|
||||
34568,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,
|
||||
3457,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,
|
||||
34574,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,
|
||||
|
||||
|
@@ -1,108 +1,104 @@
|
||||
Index,Code,Level,Name,产业种类
|
||||
0,1,0,工业互联网,0
|
||||
1,1.1,1,工业自动化硬件,0
|
||||
2,1.1.1,2,工业计算芯片,1
|
||||
3,1.1.2,2,工业控制器,0
|
||||
4,1.1.3,2,工业服务器,0
|
||||
5,1.2,1,工业互联网网络,1
|
||||
6,1.2.1,2,网络互联服务,0
|
||||
7,1.2.2,2,标识解析服务,0
|
||||
8,1.2.3,2,数据互通服务,1
|
||||
9,1.3,1,工业软件,0
|
||||
10,1.3.1,2,设计研发软件,0
|
||||
11,1.3.1.1,3,计算机辅助设计CAD,0
|
||||
12,1.3.1.2,3,计算机辅助工程CAE,1
|
||||
13,1.3.1.3,3,计算机辅助制造CAM,0
|
||||
14,1.3.1.4,3,计算机辅助工艺过程设计CAPP,1
|
||||
15,1.3.1.5,3,产品数据管理PDM,1
|
||||
16,1.3.1.6,3,产品生命周期管理PLM,0
|
||||
17,1.3.1.7,3,电子设计自动化EDA,0
|
||||
18,1.3.2,2,采购供应软件,0
|
||||
19,1.3.2.1,3,供应链管理SCM,1
|
||||
20,1.3.3,2,生产制造软件,1
|
||||
21,1.3.3.1,3,制造执行系统MES,0
|
||||
22,1.3.3.2,3,分布式控制系统DCS,1
|
||||
23,1.3.3.3,3,数据采集与监视控制系统SCADA,1
|
||||
24,1.3.3.4,3,可编程逻揖控制系统PLC,0
|
||||
25,1.3.3.5,3,企业资产管理系统EAM,1
|
||||
26,1.3.3.6,3,运维保障系统MRO,1
|
||||
27,1.3.3.7,3,故障预测与健康管理PHM,1
|
||||
28,1.3.4,2,企业运营管理软件,0
|
||||
29,1.3.4.1,3,企业资源计划ERP,1
|
||||
30,1.3.4.2,3,客户关系管理CRM,1
|
||||
31,1.3.4.3,3,人力资源管理HRM,0
|
||||
32,1.3.5,2,仓储物流软件,0
|
||||
33,1.3.5.1,3,仓储物流管理WMS,1
|
||||
34,1.4,1,工业互联网安全管理,1
|
||||
35,1.4.1,2,设备安全,1
|
||||
36,1.4.1.1,3,工业防火墙,1
|
||||
37,1.4.1.2,3,下一代防火墙,1
|
||||
38,1.4.1.3,3,防毒墙,1
|
||||
39,1.4.1.4,3,入侵检测系统,0
|
||||
40,1.4.1.5,3,统一威胁管理系统,0
|
||||
41,1.4.2,2,控制安全,1
|
||||
42,1.4.2.1,3,工控安全监测与审计,0
|
||||
43,1.4.2.2,3,工控主机卫士,1
|
||||
44,1.4.2.3,3,工控漏洞扫描,1
|
||||
45,1.4.2.4,3,安全隔离与信息交换系统,1
|
||||
46,1.4.2.5,3,安全日志与审计,1
|
||||
47,1.4.2.6,3,隐私计算,1
|
||||
48,1.4.2.7,3,工控原生安全,0
|
||||
49,1.4.3,2,网络安全,1
|
||||
50,1.4.3.1,3,网络漏洞扫描和补丁管理,0
|
||||
51,1.4.3.2,3,流量检测,1
|
||||
52,1.4.3.3,3,APT检测,1
|
||||
53,1.4.3.4,3,攻击溯源,0
|
||||
54,1.4.3.5,3,负载均衡,1
|
||||
55,1.4.3.6,3,沙箱类设备,1
|
||||
56,1.4.4,2,平台安全,0
|
||||
57,1.4.4.1,3,身份鉴别与访问控制,1
|
||||
58,1.4.4.2,3,密钥管理,0
|
||||
59,1.4.4.3,3,接入认证,0
|
||||
60,1.4.4.4,3,工业应用行为监控,0
|
||||
61,1.4.4.5,3,安全态势感知,0
|
||||
62,1.4.5,2,数据安全,0
|
||||
63,1.4.5.1,3,恶意代码检测系统,0
|
||||
64,1.4.5.2,3,数据防泄漏系统,0
|
||||
65,1.4.5.3,3,数据审计系统,1
|
||||
66,1.4.5.4,3,数据脱敏,0
|
||||
67,1.4.5.5,3,敏感数据发现与监控,1
|
||||
68,1.4.5.6,3,数据容灾备份,1
|
||||
69,1.4.5.7,3,数据恢复,1
|
||||
70,1.4.5.8,3,数据加密,1
|
||||
71,1.4.5.9,3,数据防火墙,1
|
||||
72,2,0,工业互联网平台,0
|
||||
73,2.1,1,PaaS,1
|
||||
74,2.1.1,2,开发工具,0
|
||||
75,2.1.1.1,3,算法建模工具,1
|
||||
76,2.1.1.2,3,低代码开发工具,0
|
||||
77,2.1.1.3,3,流程开发工具,0
|
||||
78,2.1.1.4,3,组态建模工具,1
|
||||
79,2.1.1.5,3,数字孪生建模工具,1
|
||||
80,2.1.2,2,工业模型库,1
|
||||
81,2.1.2.1,3,数据算法模型,0
|
||||
82,2.1.2.2,3,业务流程模型,1
|
||||
83,2.1.2.3,3,研发仿真模型,1
|
||||
84,2.1.2.4,3,行业机理模型,1
|
||||
85,2.1.3,2,工业物联网,1
|
||||
86,2.1.3.1,3,物联网服务,0
|
||||
87,2.1.3.2,3,平台基础服务,0
|
||||
88,2.1.3.3,3,工业引擎服务,1
|
||||
89,2.1.3.4,3,应用管理服务,1
|
||||
90,2.1.3.5,3,容器服务,1
|
||||
91,2.1.3.6,3,微服务,1
|
||||
92,2.1.3.7,3,制造类API,0
|
||||
93,2.1.4,2,工业大数据,0
|
||||
94,2.1.4.1,3,工业大数据存储,1
|
||||
95,2.1.4.1.1,4,关系型数据库,0
|
||||
96,2.1.4.1.2,4,分布式数据库,1
|
||||
97,2.1.4.1.3,4,实时数据库,1
|
||||
98,2.1.4.1.4,4,时序数据库,0
|
||||
99,2.1.4.2,3,工业大数据管理,0
|
||||
100,2.1.4.2.1,4,数据质量管理,1
|
||||
101,2.1.4.2.2,4,数据安全管理,1
|
||||
102,2.2,1,IaaS,1
|
||||
103,2.3,1,边缘层,0
|
||||
104,2.3.1,2,工业数据接入,0
|
||||
105,2.3.2,2,边缘数据处理,0
|
||||
106,2.3.3,2,协议转换,1
|
||||
Code,Index,Name,产业种类
|
||||
32338,7,硅原材料,0
|
||||
32445,8,光刻胶及其配套试剂,0
|
||||
56341,9,蚀刻液,0
|
||||
7,10,氟化硅,0
|
||||
46504,11,显影液,0
|
||||
32434,12,聚羧酸减水剂,0
|
||||
32441,13,金属保护液,0
|
||||
32444,14,深孔镀铜液,0
|
||||
32440,15,稀释剂,0
|
||||
32432,16,高纯硼酸（核电）,0
|
||||
32451,17,电子级环氧树脂,0
|
||||
46505,18,剥离液,0
|
||||
32449,19,高纯金属有机化合物,0
|
||||
32446,20,研磨液及配套化学品、研磨垫材料,0
|
||||
32442,21,光阻去除剂,0
|
||||
32433,22,多晶硅切削液,0
|
||||
32443,23,钝化液,0
|
||||
32450,24,电子级酚醛树脂,0
|
||||
32435,25,表面活性剂,0
|
||||
32437,26,磁性载体,0
|
||||
32438,27,通用湿电子化学品,0
|
||||
32447,28,电镀化学品及配套材料,0
|
||||
32436,29,电子级阻燃材料及化学品,0
|
||||
32448,30,液晶取向剂及配套化学品,0
|
||||
32439,31,功能湿电子化学品,0
|
||||
56320,32,磷化铟,0
|
||||
56322,33,碳化硅,0
|
||||
56319,34,砷化镓,0
|
||||
56323,35,氮化镓,0
|
||||
56321,36,氮化铝,0
|
||||
8,37,氮化硅,0
|
||||
36914,38,碳化硅衬底,0
|
||||
36914,39,氮化镓衬底,0
|
||||
36914,40,硅衬底,0
|
||||
36914,41,氮化铝衬底,0
|
||||
36914,42,深紫外LED衬底,0
|
||||
36914,43,磷化铟衬底,0
|
||||
32338,44,单晶硅片,0
|
||||
32338,45,多晶硅片,0
|
||||
32338,46,磷化铟单晶和单晶片,0
|
||||
32338,47,碳化硅单晶和单晶片,0
|
||||
32338,48,砷化镓单晶片,0
|
||||
32338,49,氮化镓晶体和单晶片,0
|
||||
32338,50,硅外延片,0
|
||||
32338,51,碳化硅外延晶片,0
|
||||
32338,52,氮化铝外延片,0
|
||||
32338,53,氮化镓外延片,0
|
||||
32338,54,磷化铟外延片,0
|
||||
32338,55,LED外延片,0
|
||||
2515,56,EDA及IP服务,2
|
||||
2514,57,MPW服务,2
|
||||
9,58,芯片设计,3
|
||||
34535,59,涂胶显影设备,1
|
||||
34526,60,硅片研磨机,1
|
||||
34529,61,刻蚀机,1
|
||||
34537,62,氧化/扩散炉,1
|
||||
34534,63,晶圆测量设备,1
|
||||
34525,64,单晶生长炉,1
|
||||
34530,65,化学机械抛光设备,1
|
||||
34533,66,光刻机,1
|
||||
34527,67,晶硅切片机,1
|
||||
34539,68,薄膜生长设备,1
|
||||
34528,69,硅片倒角机,1
|
||||
34543,70,等离子去胶机,1
|
||||
34531,71,晶圆清洗机,1
|
||||
34524,72,熔炼矿热炉,1
|
||||
34532,73,半导体电镀设备,1
|
||||
34538,74,离子注入设备,1
|
||||
34550,75,切筋成型机,1
|
||||
34555,76,探针卡,1
|
||||
34554,77,测试机,1
|
||||
34556,78,工艺检测设备,1
|
||||
34557,79,晶圆检测设备,1
|
||||
34553,80,探针台,1
|
||||
34545,81,晶圆划片机,1
|
||||
34552,82,分选机,1
|
||||
34544,83,晶圆减薄机,1
|
||||
34546,84,贴片机,1
|
||||
34549,85,回流炉,1
|
||||
34558,86,FT测试设备,1
|
||||
34547,87,引线键合机,1
|
||||
34551,88,植球机,1
|
||||
34548,89,半导体塑封机,1
|
||||
2717,90,功率半导体器件,1
|
||||
2714,91,二极管,1
|
||||
2715,92,晶体管,1
|
||||
2716,93,晶闸管,1
|
||||
2718,94,整流桥,1
|
||||
317589,95,集成电路制造,1
|
||||
10,96,IC封装,5
|
||||
513738,97,芯片设计验证,4
|
||||
513740,98,过程工艺检测,4
|
||||
513742,99,晶圆测试,4
|
||||
11,100,芯片测试,4
|
||||
34573,101,晶圆凸块,0
|
||||
34571,102,芯片粘结材料,0
|
||||
34567,103,引线框架,0
|
||||
34572,104,焊球,0
|
||||
34566,105,封装基板,0
|
||||
34569,106,半导体塑封料,0
|
||||
34568,107,键合线,0
|
||||
34570,108,底部填充料,0
|
||||
34574,109,半导体切割材料,0
|
||||
|
@@ -1,201 +1,241 @@
|
||||
产业id,消耗材料id,消耗量
|
||||
0,51,398
|
||||
0,14,156
|
||||
0,71,238
|
||||
1,74,137
|
||||
1,99,409
|
||||
1,23,180
|
||||
2,37,435
|
||||
2,63,493
|
||||
3,21,302
|
||||
3,88,98
|
||||
4,61,224
|
||||
4,61,100
|
||||
5,72,216
|
||||
6,8,395
|
||||
6,52,435
|
||||
7,80,469
|
||||
7,49,409
|
||||
8,62,451
|
||||
9,47,320
|
||||
9,71,264
|
||||
9,61,345
|
||||
10,52,329
|
||||
10,25,266
|
||||
11,44,114
|
||||
11,88,376
|
||||
11,8,393
|
||||
12,10,130
|
||||
12,7,212
|
||||
12,34,338
|
||||
13,32,97
|
||||
13,22,111
|
||||
14,90,84
|
||||
14,64,276
|
||||
15,0,54
|
||||
15,89,304
|
||||
15,13,408
|
||||
16,50,112
|
||||
17,14,220
|
||||
17,28,85
|
||||
17,12,209
|
||||
18,61,490
|
||||
19,61,380
|
||||
19,91,280
|
||||
20,2,408
|
||||
21,96,356
|
||||
22,31,145
|
||||
22,87,282
|
||||
23,51,317
|
||||
23,38,435
|
||||
24,1,269
|
||||
24,53,392
|
||||
25,18,175
|
||||
26,31,296
|
||||
26,67,488
|
||||
27,97,247
|
||||
28,58,375
|
||||
29,35,452
|
||||
29,89,196
|
||||
29,19,401
|
||||
30,10,490
|
||||
31,93,347
|
||||
31,98,312
|
||||
31,15,395
|
||||
32,0,353
|
||||
32,11,86
|
||||
33,19,201
|
||||
33,53,169
|
||||
33,32,457
|
||||
34,88,148
|
||||
34,24,398
|
||||
34,17,433
|
||||
35,40,210
|
||||
36,66,450
|
||||
36,32,225
|
||||
36,75,492
|
||||
37,50,487
|
||||
37,7,332
|
||||
38,68,366
|
||||
39,92,95
|
||||
39,5,148
|
||||
40,45,230
|
||||
41,31,210
|
||||
42,23,163
|
||||
42,31,480
|
||||
43,89,322
|
||||
43,32,442
|
||||
44,24,457
|
||||
44,12,365
|
||||
45,7,449
|
||||
46,65,337
|
||||
46,86,496
|
||||
47,21,363
|
||||
47,57,391
|
||||
48,14,103
|
||||
48,59,150
|
||||
49,67,311
|
||||
50,46,404
|
||||
50,54,473
|
||||
51,62,324
|
||||
52,61,328
|
||||
53,95,175
|
||||
53,47,138
|
||||
54,63,496
|
||||
55,66,125
|
||||
55,25,193
|
||||
55,50,135
|
||||
56,46,143
|
||||
57,47,390
|
||||
57,38,149
|
||||
58,9,295
|
||||
58,68,149
|
||||
58,33,229
|
||||
59,3,65
|
||||
60,34,429
|
||||
60,32,466
|
||||
61,11,372
|
||||
62,42,93
|
||||
62,28,446
|
||||
63,25,139
|
||||
64,74,462
|
||||
64,35,266
|
||||
65,72,457
|
||||
66,95,86
|
||||
66,11,418
|
||||
67,61,133
|
||||
68,18,226
|
||||
68,99,445
|
||||
68,60,282
|
||||
69,15,422
|
||||
69,68,148
|
||||
69,11,74
|
||||
70,52,91
|
||||
70,57,472
|
||||
70,13,272
|
||||
71,74,195
|
||||
71,75,58
|
||||
71,73,491
|
||||
72,39,219
|
||||
73,65,54
|
||||
73,28,214
|
||||
74,70,266
|
||||
75,30,324
|
||||
75,60,413
|
||||
76,38,175
|
||||
76,66,222
|
||||
76,12,291
|
||||
77,38,50
|
||||
78,24,361
|
||||
79,57,93
|
||||
79,44,209
|
||||
80,79,423
|
||||
81,35,276
|
||||
82,30,50
|
||||
82,53,423
|
||||
82,2,193
|
||||
83,7,171
|
||||
84,40,277
|
||||
85,12,95
|
||||
86,55,335
|
||||
86,4,168
|
||||
87,48,316
|
||||
87,84,331
|
||||
87,62,266
|
||||
88,97,154
|
||||
89,4,407
|
||||
89,2,486
|
||||
89,22,102
|
||||
90,16,134
|
||||
90,77,415
|
||||
90,0,100
|
||||
91,64,418
|
||||
91,31,83
|
||||
92,2,428
|
||||
92,49,317
|
||||
93,93,271
|
||||
94,65,124
|
||||
94,50,152
|
||||
95,97,387
|
||||
95,29,384
|
||||
96,29,296
|
||||
96,50,130
|
||||
96,4,334
|
||||
97,33,311
|
||||
98,42,289
|
||||
98,74,420
|
||||
99,66,401
|
||||
100,4,141
|
||||
101,4,282
|
||||
102,44,460
|
||||
102,72,331
|
||||
103,55,399
|
||||
103,62,97
|
||||
104,7,162
|
||||
105,89,77
|
||||
105,86,127
|
||||
106,6,52
|
||||
106,22,287
|
||||
106,17,343
|
||||
107,38,490
|
||||
107,16,280
|
||||
,产业id,消耗材料id
|
||||
0,36914,32338
|
||||
1,36914,32338
|
||||
2,36914,32338
|
||||
3,36914,32440
|
||||
4,36914,46505
|
||||
5,36914,32446
|
||||
6,36914,32433
|
||||
7,36914,32443
|
||||
8,36914,32435
|
||||
9,36914,32439
|
||||
10,36914,56321
|
||||
11,36914,32440
|
||||
12,36914,46505
|
||||
13,36914,32446
|
||||
14,36914,32433
|
||||
15,36914,32443
|
||||
16,36914,32435
|
||||
17,36914,32439
|
||||
18,36914,32338
|
||||
19,32338,32338
|
||||
20,32338,32440
|
||||
21,32338,46505
|
||||
22,32338,32446
|
||||
23,32338,32433
|
||||
24,32338,32443
|
||||
25,32338,32435
|
||||
26,32338,32438
|
||||
27,32338,32338
|
||||
28,32338,32440
|
||||
29,32338,46505
|
||||
30,32338,32446
|
||||
31,32338,32433
|
||||
32,32338,32443
|
||||
33,32338,32435
|
||||
34,32338,32438
|
||||
35,32338,32440
|
||||
36,32338,46505
|
||||
37,32338,32446
|
||||
38,32338,32433
|
||||
39,32338,32443
|
||||
40,32338,32435
|
||||
41,32338,32438
|
||||
42,32338,56320
|
||||
43,32338,32440
|
||||
44,32338,46505
|
||||
45,32338,32446
|
||||
46,32338,32433
|
||||
47,32338,32443
|
||||
48,32338,32435
|
||||
49,32338,32438
|
||||
50,32338,56322
|
||||
51,32338,32440
|
||||
52,32338,46505
|
||||
53,32338,32446
|
||||
54,32338,32433
|
||||
55,32338,32443
|
||||
56,32338,32435
|
||||
57,32338,32438
|
||||
58,32338,56319
|
||||
59,32338,32440
|
||||
60,32338,46505
|
||||
61,32338,32446
|
||||
62,32338,32433
|
||||
63,32338,32443
|
||||
64,32338,32435
|
||||
65,32338,32438
|
||||
66,32338,56323
|
||||
67,32338,32449
|
||||
68,32338,32446
|
||||
69,32338,32433
|
||||
70,32338,32443
|
||||
71,32338,32435
|
||||
72,32338,32447
|
||||
73,32338,32436
|
||||
74,32338,32438
|
||||
75,32338,36914
|
||||
76,32338,32449
|
||||
77,32338,32446
|
||||
78,32338,32433
|
||||
79,32338,32443
|
||||
80,32338,32435
|
||||
81,32338,32447
|
||||
82,32338,32436
|
||||
83,32338,32438
|
||||
84,32338,36914
|
||||
85,32338,32449
|
||||
86,32338,32446
|
||||
87,32338,32433
|
||||
88,32338,32443
|
||||
89,32338,32435
|
||||
90,32338,32447
|
||||
91,32338,32436
|
||||
92,32338,32438
|
||||
93,32338,36914
|
||||
94,32338,32449
|
||||
95,32338,32446
|
||||
96,32338,32433
|
||||
97,32338,32443
|
||||
98,32338,32435
|
||||
99,32338,32447
|
||||
100,32338,32436
|
||||
101,32338,32438
|
||||
102,32338,36914
|
||||
103,32338,32449
|
||||
104,32338,32446
|
||||
105,32338,32433
|
||||
106,32338,32443
|
||||
107,32338,32435
|
||||
108,32338,32447
|
||||
109,32338,32436
|
||||
110,32338,32438
|
||||
111,32338,36914
|
||||
112,32338,32449
|
||||
113,32338,32446
|
||||
114,32338,32433
|
||||
115,32338,32443
|
||||
116,32338,32435
|
||||
117,32338,32447
|
||||
118,32338,32436
|
||||
119,32338,32438
|
||||
120,32338,36914
|
||||
121,2717,32338
|
||||
122,2717,32445
|
||||
123,2717,56341
|
||||
124,2717,7
|
||||
125,2717,46504
|
||||
126,2717,32451
|
||||
127,2717,32449
|
||||
128,2717,32446
|
||||
129,2717,32442
|
||||
130,2717,32443
|
||||
131,2717,32450
|
||||
132,2717,32435
|
||||
133,2717,32447
|
||||
134,2717,32439
|
||||
135,2717,32338
|
||||
136,2717,32338
|
||||
137,2714,32445
|
||||
138,2714,56341
|
||||
139,2714,7
|
||||
140,2714,46504
|
||||
141,2714,32451
|
||||
142,2714,46505
|
||||
143,2714,32449
|
||||
144,2714,32446
|
||||
145,2714,32443
|
||||
146,2714,32450
|
||||
147,2714,32447
|
||||
148,2714,32439
|
||||
149,2715,32445
|
||||
150,2715,56341
|
||||
151,2715,7
|
||||
152,2715,46504
|
||||
153,2715,32451
|
||||
154,2715,46505
|
||||
155,2715,32449
|
||||
156,2715,32446
|
||||
157,2715,32443
|
||||
158,2715,32450
|
||||
159,2715,32447
|
||||
160,2715,32439
|
||||
161,2716,32445
|
||||
162,2716,56341
|
||||
163,2716,7
|
||||
164,2716,46504
|
||||
165,2716,32451
|
||||
166,2716,46505
|
||||
167,2716,32449
|
||||
168,2716,32446
|
||||
169,2716,32443
|
||||
170,2716,32450
|
||||
171,2716,32447
|
||||
172,2716,32439
|
||||
173,2718,32445
|
||||
174,2718,56341
|
||||
175,2718,7
|
||||
176,2718,46504
|
||||
177,2718,32451
|
||||
178,2718,46505
|
||||
179,2718,32449
|
||||
180,2718,32446
|
||||
181,2718,32443
|
||||
182,2718,32450
|
||||
183,2718,32447
|
||||
184,2718,32439
|
||||
185,317589,32445
|
||||
186,317589,56341
|
||||
187,317589,7
|
||||
188,317589,46504
|
||||
189,317589,32434
|
||||
190,317589,32441
|
||||
191,317589,32444
|
||||
192,317589,32440
|
||||
193,317589,32432
|
||||
194,317589,32451
|
||||
195,317589,46505
|
||||
196,317589,32449
|
||||
197,317589,32446
|
||||
198,317589,32442
|
||||
199,317589,32433
|
||||
200,317589,32443
|
||||
201,317589,32450
|
||||
202,317589,32435
|
||||
203,317589,32437
|
||||
204,317589,32438
|
||||
205,317589,32447
|
||||
206,317589,32436
|
||||
207,317589,32448
|
||||
208,317589,32439
|
||||
209,317589,8
|
||||
210,317589,32338
|
||||
211,317589,32338
|
||||
212,317589,32338
|
||||
213,317589,32338
|
||||
214,317589,32338
|
||||
215,317589,32338
|
||||
216,317589,32338
|
||||
217,317589,32338
|
||||
218,317589,32338
|
||||
219,317589,32338
|
||||
220,317589,32338
|
||||
221,317589,32338
|
||||
222,317589,2717
|
||||
223,317589,2714
|
||||
224,317589,2715
|
||||
225,317589,2716
|
||||
226,317589,2718
|
||||
227,10,317589
|
||||
228,10,34573
|
||||
229,10,34571
|
||||
230,10,34567
|
||||
231,10,34572
|
||||
232,10,34566
|
||||
233,10,34569
|
||||
234,10,34568
|
||||
235,10,34570
|
||||
236,10,34574
|
||||
237,513740,317589
|
||||
238,513742,317589
|
||||
239,11,317589
|
||||
|
||||
|
@@ -1,11 +1,5 @@
|
||||
产品id,种类
|
||||
1,材料
|
||||
2,材料
|
||||
3,材料
|
||||
4,材料
|
||||
5,材料
|
||||
6,材料
|
||||
7,材料
|
||||
8,材料
|
||||
9,材料
|
||||
10,材料
|
||||
@@ -49,14 +43,26 @@
|
||||
48,材料
|
||||
49,材料
|
||||
50,材料
|
||||
51,设备
|
||||
52,设备
|
||||
53,设备
|
||||
54,设备
|
||||
55,设备
|
||||
56,设备
|
||||
57,设备
|
||||
58,设备
|
||||
51,材料
|
||||
52,材料
|
||||
53,材料
|
||||
54,材料
|
||||
55,材料
|
||||
90,材料
|
||||
91,材料
|
||||
92,材料
|
||||
93,材料
|
||||
94,材料
|
||||
95,材料
|
||||
101,材料
|
||||
102,材料
|
||||
103,材料
|
||||
104,材料
|
||||
105,材料
|
||||
106,材料
|
||||
107,材料
|
||||
108,材料
|
||||
109,材料
|
||||
59,设备
|
||||
60,设备
|
||||
61,设备
|
||||
@@ -88,20 +94,3 @@
|
||||
87,设备
|
||||
88,设备
|
||||
89,设备
|
||||
90,设备
|
||||
91,设备
|
||||
92,设备
|
||||
93,设备
|
||||
94,设备
|
||||
95,设备
|
||||
96,设备
|
||||
97,设备
|
||||
98,设备
|
||||
99,设备
|
||||
100,设备
|
||||
101,设备
|
||||
102,设备
|
||||
103,设备
|
||||
104,设备
|
||||
105,设备
|
||||
106,设备
|
||||
|
||||
|
@@ -1,216 +1,382 @@
|
||||
产业id,制造产品id,制造量
|
||||
0,182,314
|
||||
1,152,869
|
||||
1,187,591
|
||||
2,132,559
|
||||
3,158,610
|
||||
3,141,575
|
||||
3,159,882
|
||||
4,163,604
|
||||
4,102,584
|
||||
4,150,746
|
||||
5,103,700
|
||||
5,159,113
|
||||
6,159,554
|
||||
6,143,608
|
||||
6,107,134
|
||||
7,105,665
|
||||
7,103,921
|
||||
8,143,261
|
||||
8,173,369
|
||||
9,179,848
|
||||
10,140,256
|
||||
11,107,571
|
||||
12,104,589
|
||||
12,140,127
|
||||
12,106,300
|
||||
13,198,783
|
||||
14,146,561
|
||||
15,108,306
|
||||
15,114,957
|
||||
15,141,991
|
||||
16,151,195
|
||||
16,103,833
|
||||
16,200,506
|
||||
17,158,342
|
||||
17,185,895
|
||||
17,165,781
|
||||
18,105,895
|
||||
19,196,484
|
||||
19,126,732
|
||||
20,171,510
|
||||
20,108,417
|
||||
21,143,763
|
||||
21,178,926
|
||||
22,161,596
|
||||
23,200,724
|
||||
23,155,180
|
||||
23,158,212
|
||||
24,195,324
|
||||
25,152,783
|
||||
25,189,771
|
||||
26,155,222
|
||||
26,116,866
|
||||
26,137,379
|
||||
27,110,610
|
||||
27,115,708
|
||||
28,102,759
|
||||
29,151,588
|
||||
29,132,739
|
||||
29,138,437
|
||||
30,149,250
|
||||
31,159,980
|
||||
32,108,332
|
||||
32,198,758
|
||||
32,147,307
|
||||
33,171,519
|
||||
33,137,203
|
||||
33,183,353
|
||||
34,181,805
|
||||
34,153,262
|
||||
35,113,376
|
||||
36,185,474
|
||||
36,121,849
|
||||
36,129,137
|
||||
37,197,376
|
||||
37,129,708
|
||||
37,127,978
|
||||
38,103,646
|
||||
38,163,148
|
||||
38,116,271
|
||||
39,136,379
|
||||
40,198,799
|
||||
40,196,215
|
||||
40,162,352
|
||||
41,117,892
|
||||
41,194,665
|
||||
41,157,422
|
||||
42,122,738
|
||||
42,126,589
|
||||
43,147,138
|
||||
43,192,781
|
||||
43,125,966
|
||||
44,106,924
|
||||
44,135,784
|
||||
45,175,982
|
||||
45,186,242
|
||||
46,150,764
|
||||
46,157,674
|
||||
47,151,781
|
||||
48,107,152
|
||||
49,195,983
|
||||
50,129,758
|
||||
51,154,445
|
||||
51,200,573
|
||||
52,108,740
|
||||
52,157,733
|
||||
52,100,850
|
||||
53,100,371
|
||||
54,121,960
|
||||
55,128,319
|
||||
56,161,552
|
||||
56,175,317
|
||||
57,193,456
|
||||
58,109,861
|
||||
58,118,541
|
||||
58,195,868
|
||||
59,101,596
|
||||
59,191,995
|
||||
59,131,574
|
||||
60,150,526
|
||||
61,132,267
|
||||
62,145,997
|
||||
62,134,826
|
||||
62,180,189
|
||||
63,133,214
|
||||
63,106,295
|
||||
64,135,493
|
||||
65,148,198
|
||||
65,135,195
|
||||
65,123,762
|
||||
66,112,378
|
||||
66,188,966
|
||||
66,129,372
|
||||
67,185,496
|
||||
68,175,364
|
||||
68,170,895
|
||||
68,177,834
|
||||
69,184,583
|
||||
69,152,250
|
||||
69,115,668
|
||||
70,104,262
|
||||
70,186,832
|
||||
71,106,273
|
||||
72,149,894
|
||||
73,182,747
|
||||
73,164,441
|
||||
74,103,903
|
||||
75,138,190
|
||||
75,173,957
|
||||
76,157,759
|
||||
76,191,555
|
||||
77,176,447
|
||||
77,161,604
|
||||
77,162,607
|
||||
78,137,216
|
||||
79,160,914
|
||||
80,174,863
|
||||
81,119,540
|
||||
81,117,146
|
||||
81,148,625
|
||||
82,156,111
|
||||
82,173,835
|
||||
82,115,457
|
||||
83,107,797
|
||||
83,159,277
|
||||
84,162,244
|
||||
84,172,823
|
||||
84,176,831
|
||||
85,105,693
|
||||
85,168,914
|
||||
85,124,549
|
||||
86,164,245
|
||||
87,158,894
|
||||
87,148,560
|
||||
88,100,504
|
||||
88,154,617
|
||||
88,191,808
|
||||
89,173,557
|
||||
90,176,871
|
||||
91,171,650
|
||||
91,125,349
|
||||
91,133,537
|
||||
92,153,335
|
||||
93,156,500
|
||||
93,146,306
|
||||
93,200,952
|
||||
94,163,863
|
||||
94,197,905
|
||||
95,150,546
|
||||
95,197,407
|
||||
95,137,580
|
||||
96,155,500
|
||||
96,173,884
|
||||
97,165,304
|
||||
98,122,282
|
||||
98,179,194
|
||||
98,174,473
|
||||
99,126,192
|
||||
99,131,160
|
||||
99,150,502
|
||||
100,160,633
|
||||
100,120,937
|
||||
101,145,645
|
||||
101,148,177
|
||||
102,146,220
|
||||
103,180,125
|
||||
104,151,818
|
||||
104,146,738
|
||||
104,155,825
|
||||
105,125,625
|
||||
105,158,411
|
||||
106,114,291
|
||||
106,188,730
|
||||
106,200,127
|
||||
107,189,225
|
||||
107,143,636
|
||||
,产业id,制造产品id
|
||||
0,2714,8
|
||||
1,2714,9
|
||||
2,2714,10
|
||||
3,2714,11
|
||||
4,2714,17
|
||||
5,2714,18
|
||||
6,2714,19
|
||||
7,2714,20
|
||||
8,2714,23
|
||||
9,2714,24
|
||||
10,2714,28
|
||||
11,2714,31
|
||||
12,2714,58
|
||||
13,2714,59
|
||||
14,2714,61
|
||||
15,2714,62
|
||||
16,2714,65
|
||||
17,2714,66
|
||||
18,2714,70
|
||||
19,2715,8
|
||||
20,2715,9
|
||||
21,2715,10
|
||||
22,2715,11
|
||||
23,2715,17
|
||||
24,2715,18
|
||||
25,2715,19
|
||||
26,2715,20
|
||||
27,2715,23
|
||||
28,2715,24
|
||||
29,2715,28
|
||||
30,2715,31
|
||||
31,2715,58
|
||||
32,2715,59
|
||||
33,2715,61
|
||||
34,2715,62
|
||||
35,2715,65
|
||||
36,2715,66
|
||||
37,2715,70
|
||||
38,2716,8
|
||||
39,2716,9
|
||||
40,2716,10
|
||||
41,2716,11
|
||||
42,2716,17
|
||||
43,2716,18
|
||||
44,2716,19
|
||||
45,2716,20
|
||||
46,2716,23
|
||||
47,2716,24
|
||||
48,2716,28
|
||||
49,2716,31
|
||||
50,2716,58
|
||||
51,2716,59
|
||||
52,2716,61
|
||||
53,2716,62
|
||||
54,2716,65
|
||||
55,2716,66
|
||||
56,2716,70
|
||||
57,2717,2
|
||||
58,2717,8
|
||||
59,2717,9
|
||||
60,2717,10
|
||||
61,2717,11
|
||||
62,2717,17
|
||||
63,2717,19
|
||||
64,2717,20
|
||||
65,2717,21
|
||||
66,2717,23
|
||||
67,2717,24
|
||||
68,2717,25
|
||||
69,2717,28
|
||||
70,2717,31
|
||||
71,2717,44
|
||||
72,2717,45
|
||||
73,2717,58
|
||||
74,2717,59
|
||||
75,2717,60
|
||||
76,2717,61
|
||||
77,2717,62
|
||||
78,2717,65
|
||||
79,2717,66
|
||||
80,2717,67
|
||||
81,2717,68
|
||||
82,2718,8
|
||||
83,2718,9
|
||||
84,2718,10
|
||||
85,2718,11
|
||||
86,2718,17
|
||||
87,2718,18
|
||||
88,2718,19
|
||||
89,2718,20
|
||||
90,2718,23
|
||||
91,2718,24
|
||||
92,2718,28
|
||||
93,2718,31
|
||||
94,2718,58
|
||||
95,2718,59
|
||||
96,2718,61
|
||||
97,2718,62
|
||||
98,2718,65
|
||||
99,2718,66
|
||||
100,2718,70
|
||||
101,32338,2
|
||||
102,32338,15
|
||||
103,32338,18
|
||||
104,32338,20
|
||||
105,32338,22
|
||||
106,32338,23
|
||||
107,32338,25
|
||||
108,32338,27
|
||||
109,32338,64
|
||||
110,32338,67
|
||||
111,32338,60
|
||||
112,32338,65
|
||||
113,32338,71
|
||||
114,32338,2
|
||||
115,32338,15
|
||||
116,32338,18
|
||||
117,32338,20
|
||||
118,32338,22
|
||||
119,32338,23
|
||||
120,32338,25
|
||||
121,32338,27
|
||||
122,32338,64
|
||||
123,32338,67
|
||||
124,32338,60
|
||||
125,32338,65
|
||||
126,32338,71
|
||||
127,32338,15
|
||||
128,32338,18
|
||||
129,32338,20
|
||||
130,32338,22
|
||||
131,32338,23
|
||||
132,32338,25
|
||||
133,32338,27
|
||||
134,32338,32
|
||||
135,32338,64
|
||||
136,32338,67
|
||||
137,32338,60
|
||||
138,32338,65
|
||||
139,32338,71
|
||||
140,32338,15
|
||||
141,32338,18
|
||||
142,32338,20
|
||||
143,32338,22
|
||||
144,32338,23
|
||||
145,32338,25
|
||||
146,32338,27
|
||||
147,32338,33
|
||||
148,32338,64
|
||||
149,32338,67
|
||||
150,32338,60
|
||||
151,32338,65
|
||||
152,32338,71
|
||||
153,32338,15
|
||||
154,32338,18
|
||||
155,32338,20
|
||||
156,32338,22
|
||||
157,32338,23
|
||||
158,32338,25
|
||||
159,32338,27
|
||||
160,32338,34
|
||||
161,32338,64
|
||||
162,32338,67
|
||||
163,32338,60
|
||||
164,32338,65
|
||||
165,32338,71
|
||||
166,32338,15
|
||||
167,32338,18
|
||||
168,32338,20
|
||||
169,32338,22
|
||||
170,32338,23
|
||||
171,32338,25
|
||||
172,32338,27
|
||||
173,32338,35
|
||||
174,32338,64
|
||||
175,32338,67
|
||||
176,32338,60
|
||||
177,32338,65
|
||||
178,32338,71
|
||||
179,32338,19
|
||||
180,32338,20
|
||||
181,32338,22
|
||||
182,32338,23
|
||||
183,32338,25
|
||||
184,32338,28
|
||||
185,32338,29
|
||||
186,32338,27
|
||||
187,32338,40
|
||||
188,32338,60
|
||||
189,32338,62
|
||||
190,32338,63
|
||||
191,32338,64
|
||||
192,32338,65
|
||||
193,32338,67
|
||||
194,32338,68
|
||||
195,32338,69
|
||||
196,32338,71
|
||||
197,32338,72
|
||||
198,32338,19
|
||||
199,32338,20
|
||||
200,32338,22
|
||||
201,32338,23
|
||||
202,32338,25
|
||||
203,32338,28
|
||||
204,32338,29
|
||||
205,32338,27
|
||||
206,32338,38
|
||||
207,32338,60
|
||||
208,32338,62
|
||||
209,32338,63
|
||||
210,32338,64
|
||||
211,32338,65
|
||||
212,32338,67
|
||||
213,32338,68
|
||||
214,32338,69
|
||||
215,32338,71
|
||||
216,32338,72
|
||||
217,32338,19
|
||||
218,32338,20
|
||||
219,32338,22
|
||||
220,32338,23
|
||||
221,32338,25
|
||||
222,32338,28
|
||||
223,32338,29
|
||||
224,32338,27
|
||||
225,32338,41
|
||||
226,32338,60
|
||||
227,32338,62
|
||||
228,32338,63
|
||||
229,32338,64
|
||||
230,32338,65
|
||||
231,32338,67
|
||||
232,32338,68
|
||||
233,32338,69
|
||||
234,32338,71
|
||||
235,32338,72
|
||||
236,32338,19
|
||||
237,32338,20
|
||||
238,32338,22
|
||||
239,32338,23
|
||||
240,32338,25
|
||||
241,32338,28
|
||||
242,32338,29
|
||||
243,32338,27
|
||||
244,32338,39
|
||||
245,32338,60
|
||||
246,32338,62
|
||||
247,32338,63
|
||||
248,32338,64
|
||||
249,32338,65
|
||||
250,32338,67
|
||||
251,32338,68
|
||||
252,32338,69
|
||||
253,32338,71
|
||||
254,32338,72
|
||||
255,32338,19
|
||||
256,32338,20
|
||||
257,32338,22
|
||||
258,32338,23
|
||||
259,32338,25
|
||||
260,32338,28
|
||||
261,32338,29
|
||||
262,32338,27
|
||||
263,32338,43
|
||||
264,32338,60
|
||||
265,32338,62
|
||||
266,32338,63
|
||||
267,32338,64
|
||||
268,32338,65
|
||||
269,32338,67
|
||||
270,32338,68
|
||||
271,32338,69
|
||||
272,32338,71
|
||||
273,32338,72
|
||||
274,32338,19
|
||||
275,32338,20
|
||||
276,32338,22
|
||||
277,32338,23
|
||||
278,32338,25
|
||||
279,32338,28
|
||||
280,32338,29
|
||||
281,32338,27
|
||||
282,32338,42
|
||||
283,32338,60
|
||||
284,32338,62
|
||||
285,32338,63
|
||||
286,32338,64
|
||||
287,32338,65
|
||||
288,32338,67
|
||||
289,32338,68
|
||||
290,32338,69
|
||||
291,32338,71
|
||||
292,32338,72
|
||||
293,36914,47
|
||||
294,36914,49
|
||||
295,36914,44
|
||||
296,36914,15
|
||||
297,36914,18
|
||||
298,36914,20
|
||||
299,36914,22
|
||||
300,36914,23
|
||||
301,36914,25
|
||||
302,36914,31
|
||||
303,36914,36
|
||||
304,36914,64
|
||||
305,36914,67
|
||||
306,36914,60
|
||||
307,36914,65
|
||||
308,36914,71
|
||||
309,36914,15
|
||||
310,36914,18
|
||||
311,36914,20
|
||||
312,36914,22
|
||||
313,36914,23
|
||||
314,36914,25
|
||||
315,36914,31
|
||||
316,36914,64
|
||||
317,36914,67
|
||||
318,36914,60
|
||||
319,36914,65
|
||||
320,36914,71
|
||||
321,36914,46
|
||||
322,317589,8
|
||||
323,317589,9
|
||||
324,317589,10
|
||||
325,317589,11
|
||||
326,317589,12
|
||||
327,317589,13
|
||||
328,317589,14
|
||||
329,317589,15
|
||||
330,317589,16
|
||||
331,317589,17
|
||||
332,317589,18
|
||||
333,317589,19
|
||||
334,317589,20
|
||||
335,317589,21
|
||||
336,317589,22
|
||||
337,317589,23
|
||||
338,317589,24
|
||||
339,317589,25
|
||||
340,317589,26
|
||||
341,317589,27
|
||||
342,317589,28
|
||||
343,317589,29
|
||||
344,317589,30
|
||||
345,317589,31
|
||||
346,317589,37
|
||||
347,317589,44
|
||||
348,317589,45
|
||||
349,317589,46
|
||||
350,317589,47
|
||||
351,317589,48
|
||||
352,317589,49
|
||||
353,317589,50
|
||||
354,317589,51
|
||||
355,317589,52
|
||||
356,317589,53
|
||||
357,317589,54
|
||||
358,317589,55
|
||||
359,317589,58
|
||||
360,317589,59
|
||||
361,317589,60
|
||||
362,317589,61
|
||||
363,317589,62
|
||||
364,317589,63
|
||||
365,317589,64
|
||||
366,317589,65
|
||||
367,317589,66
|
||||
368,317589,67
|
||||
369,317589,68
|
||||
370,317589,69
|
||||
371,317589,70
|
||||
372,317589,71
|
||||
373,317589,72
|
||||
374,317589,73
|
||||
375,317589,74
|
||||
376,317589,90
|
||||
377,317589,91
|
||||
378,317589,92
|
||||
379,317589,93
|
||||
380,317589,94
|
||||
|
||||
|
418
input_data/input_product_data/合成结点.csv
Normal file
418
input_data/input_product_data/合成结点.csv
Normal file
@@ -0,0 +1,418 @@
|
||||
ID,UPID
|
||||
38,47
|
||||
39,49
|
||||
40,44
|
||||
41,15
|
||||
41,18
|
||||
41,20
|
||||
41,22
|
||||
41,23
|
||||
41,25
|
||||
41,31
|
||||
41,36
|
||||
41,60
|
||||
41,64
|
||||
41,65
|
||||
41,67
|
||||
41,71
|
||||
42,15
|
||||
42,18
|
||||
42,20
|
||||
42,22
|
||||
42,23
|
||||
42,25
|
||||
42,31
|
||||
42,60
|
||||
42,64
|
||||
42,65
|
||||
42,67
|
||||
42,71
|
||||
43,46
|
||||
44,15
|
||||
44,18
|
||||
44,7
|
||||
44,20
|
||||
44,22
|
||||
44,23
|
||||
44,25
|
||||
44,27
|
||||
44,60
|
||||
44,64
|
||||
44,65
|
||||
44,67
|
||||
44,71
|
||||
45,15
|
||||
45,18
|
||||
45,7
|
||||
45,20
|
||||
45,22
|
||||
45,23
|
||||
45,25
|
||||
45,27
|
||||
45,60
|
||||
45,64
|
||||
45,65
|
||||
45,67
|
||||
45,71
|
||||
46,15
|
||||
46,18
|
||||
46,20
|
||||
46,22
|
||||
46,23
|
||||
46,25
|
||||
46,27
|
||||
46,32
|
||||
46,60
|
||||
46,64
|
||||
46,65
|
||||
46,67
|
||||
46,71
|
||||
47,15
|
||||
47,18
|
||||
47,20
|
||||
47,22
|
||||
47,23
|
||||
47,25
|
||||
47,27
|
||||
47,33
|
||||
47,60
|
||||
47,64
|
||||
47,65
|
||||
47,67
|
||||
47,71
|
||||
48,15
|
||||
48,18
|
||||
48,20
|
||||
48,22
|
||||
48,23
|
||||
48,25
|
||||
48,27
|
||||
48,34
|
||||
48,60
|
||||
48,64
|
||||
48,65
|
||||
48,67
|
||||
48,71
|
||||
49,15
|
||||
49,18
|
||||
49,20
|
||||
49,22
|
||||
49,23
|
||||
49,25
|
||||
49,27
|
||||
49,35
|
||||
49,60
|
||||
49,64
|
||||
49,65
|
||||
49,67
|
||||
49,71
|
||||
50,19
|
||||
50,20
|
||||
50,22
|
||||
50,23
|
||||
50,25
|
||||
50,27
|
||||
50,28
|
||||
50,29
|
||||
50,40
|
||||
50,60
|
||||
50,62
|
||||
50,63
|
||||
50,64
|
||||
50,65
|
||||
50,67
|
||||
50,68
|
||||
50,69
|
||||
50,71
|
||||
50,72
|
||||
51,19
|
||||
51,20
|
||||
51,22
|
||||
51,23
|
||||
51,25
|
||||
51,27
|
||||
51,28
|
||||
51,29
|
||||
51,38
|
||||
51,60
|
||||
51,62
|
||||
51,63
|
||||
51,64
|
||||
51,65
|
||||
51,67
|
||||
51,68
|
||||
51,69
|
||||
51,71
|
||||
51,72
|
||||
52,19
|
||||
52,20
|
||||
52,22
|
||||
52,23
|
||||
52,25
|
||||
52,27
|
||||
52,28
|
||||
52,29
|
||||
52,41
|
||||
52,60
|
||||
52,62
|
||||
52,63
|
||||
52,64
|
||||
52,65
|
||||
52,67
|
||||
52,68
|
||||
52,69
|
||||
52,71
|
||||
52,72
|
||||
53,19
|
||||
53,20
|
||||
53,22
|
||||
53,23
|
||||
53,25
|
||||
53,27
|
||||
53,28
|
||||
53,29
|
||||
53,39
|
||||
53,60
|
||||
53,62
|
||||
53,63
|
||||
53,64
|
||||
53,65
|
||||
53,67
|
||||
53,68
|
||||
53,69
|
||||
53,71
|
||||
53,72
|
||||
54,19
|
||||
54,20
|
||||
54,22
|
||||
54,23
|
||||
54,25
|
||||
54,27
|
||||
54,28
|
||||
54,29
|
||||
54,43
|
||||
54,60
|
||||
54,62
|
||||
54,63
|
||||
54,64
|
||||
54,65
|
||||
54,67
|
||||
54,68
|
||||
54,69
|
||||
54,71
|
||||
54,72
|
||||
55,19
|
||||
55,20
|
||||
55,22
|
||||
55,23
|
||||
55,25
|
||||
55,27
|
||||
55,28
|
||||
55,29
|
||||
55,42
|
||||
55,60
|
||||
55,62
|
||||
55,63
|
||||
55,64
|
||||
55,65
|
||||
55,67
|
||||
55,68
|
||||
55,69
|
||||
55,71
|
||||
55,72
|
||||
58,56
|
||||
58,57
|
||||
90,10
|
||||
90,11
|
||||
90,17
|
||||
90,19
|
||||
90,7
|
||||
90,20
|
||||
90,21
|
||||
90,23
|
||||
90,24
|
||||
90,25
|
||||
90,28
|
||||
90,31
|
||||
90,44
|
||||
90,45
|
||||
90,58
|
||||
90,59
|
||||
90,60
|
||||
90,61
|
||||
90,62
|
||||
90,65
|
||||
90,66
|
||||
90,67
|
||||
90,68
|
||||
90,8
|
||||
90,9
|
||||
91,10
|
||||
91,11
|
||||
91,17
|
||||
91,18
|
||||
91,19
|
||||
91,20
|
||||
91,23
|
||||
91,24
|
||||
91,28
|
||||
91,31
|
||||
91,58
|
||||
91,59
|
||||
91,61
|
||||
91,62
|
||||
91,65
|
||||
91,66
|
||||
91,70
|
||||
91,8
|
||||
91,9
|
||||
92,10
|
||||
92,11
|
||||
92,17
|
||||
92,18
|
||||
92,19
|
||||
92,20
|
||||
92,23
|
||||
92,24
|
||||
92,28
|
||||
92,31
|
||||
92,58
|
||||
92,59
|
||||
92,61
|
||||
92,62
|
||||
92,65
|
||||
92,66
|
||||
92,70
|
||||
92,8
|
||||
92,9
|
||||
93,10
|
||||
93,11
|
||||
93,17
|
||||
93,18
|
||||
93,19
|
||||
93,20
|
||||
93,23
|
||||
93,24
|
||||
93,28
|
||||
93,31
|
||||
93,58
|
||||
93,59
|
||||
93,61
|
||||
93,62
|
||||
93,65
|
||||
93,66
|
||||
93,70
|
||||
93,8
|
||||
93,9
|
||||
94,10
|
||||
94,11
|
||||
94,17
|
||||
94,18
|
||||
94,19
|
||||
94,20
|
||||
94,23
|
||||
94,24
|
||||
94,28
|
||||
94,31
|
||||
94,58
|
||||
94,59
|
||||
94,61
|
||||
94,62
|
||||
94,65
|
||||
94,66
|
||||
94,70
|
||||
94,8
|
||||
94,9
|
||||
95,10
|
||||
95,11
|
||||
95,12
|
||||
95,13
|
||||
95,14
|
||||
95,15
|
||||
95,16
|
||||
95,17
|
||||
95,18
|
||||
95,19
|
||||
95,20
|
||||
95,21
|
||||
95,22
|
||||
95,23
|
||||
95,24
|
||||
95,25
|
||||
95,26
|
||||
95,27
|
||||
95,28
|
||||
95,29
|
||||
95,30
|
||||
95,31
|
||||
95,37
|
||||
95,44
|
||||
95,45
|
||||
95,46
|
||||
95,47
|
||||
95,48
|
||||
95,49
|
||||
95,50
|
||||
95,51
|
||||
95,52
|
||||
95,53
|
||||
95,54
|
||||
95,55
|
||||
95,58
|
||||
95,59
|
||||
95,60
|
||||
95,61
|
||||
95,62
|
||||
95,63
|
||||
95,64
|
||||
95,65
|
||||
95,66
|
||||
95,67
|
||||
95,68
|
||||
95,69
|
||||
95,70
|
||||
95,71
|
||||
95,72
|
||||
95,73
|
||||
95,74
|
||||
95,8
|
||||
95,9
|
||||
95,90
|
||||
95,91
|
||||
95,92
|
||||
95,93
|
||||
95,94
|
||||
95,97
|
||||
96,100
|
||||
96,101
|
||||
96,102
|
||||
96,103
|
||||
96,104
|
||||
96,105
|
||||
96,106
|
||||
96,107
|
||||
96,108
|
||||
96,109
|
||||
96,75
|
||||
96,76
|
||||
96,80
|
||||
96,81
|
||||
96,82
|
||||
96,83
|
||||
96,84
|
||||
96,85
|
||||
96,86
|
||||
96,87
|
||||
96,88
|
||||
96,89
|
||||
96,95
|
||||
96,97
|
||||
96,98
|
||||
96,99
|
||||
97,58
|
||||
98,78
|
||||
98,95
|
||||
99,79
|
||||
99,95
|
||||
100,77
|
||||
100,95
|
||||
|
File diff suppressed because it is too large
Load Diff
238
input_data/产品消耗制造比例.csv
Normal file
238
input_data/产品消耗制造比例.csv
Normal file
@@ -0,0 +1,238 @@
|
||||
IndustryID,MaterialID,Quantity
|
||||
38,47,1.0
|
||||
39,49,1.0
|
||||
40,44,1.0
|
||||
41,15,0.02
|
||||
41,18,0.1
|
||||
41,20,0.4
|
||||
41,22,0.15
|
||||
41,23,0.04
|
||||
41,25,0.02
|
||||
41,31,0.25
|
||||
41,36,1.0
|
||||
42,15,0.02
|
||||
42,18,0.1
|
||||
42,20,0.4
|
||||
42,22,0.15
|
||||
42,23,0.04
|
||||
42,25,0.02
|
||||
42,31,0.25
|
||||
43,46,1.0
|
||||
44,7,1.4
|
||||
44,15,0.02
|
||||
44,18,0.1
|
||||
44,20,0.4
|
||||
44,22,0.15
|
||||
44,23,0.04
|
||||
44,25,0.02
|
||||
44,27,0.25
|
||||
45,7,1.4
|
||||
45,15,0.02
|
||||
45,18,0.1
|
||||
45,20,0.4
|
||||
45,22,0.15
|
||||
45,23,0.04
|
||||
45,25,0.02
|
||||
45,27,0.25
|
||||
46,15,0.02
|
||||
46,18,0.1
|
||||
46,20,0.4
|
||||
46,22,0.15
|
||||
46,23,0.04
|
||||
46,25,0.02
|
||||
46,27,0.25
|
||||
46,32,1.3
|
||||
47,15,0.02
|
||||
47,18,0.1
|
||||
47,20,0.4
|
||||
47,22,0.15
|
||||
47,23,0.04
|
||||
47,25,0.02
|
||||
47,27,0.25
|
||||
47,33,1.0
|
||||
48,15,0.02
|
||||
48,18,0.1
|
||||
48,20,0.4
|
||||
48,22,0.15
|
||||
48,23,0.04
|
||||
48,25,0.02
|
||||
48,27,0.25
|
||||
48,34,1.3
|
||||
49,15,0.02
|
||||
49,18,0.1
|
||||
49,20,0.4
|
||||
49,22,0.15
|
||||
49,23,0.04
|
||||
49,25,0.02
|
||||
49,27,0.25
|
||||
49,35,1.3
|
||||
50,19,0.005
|
||||
50,20,0.4
|
||||
50,22,0.15
|
||||
50,23,0.04
|
||||
50,25,0.02
|
||||
50,28,0.25
|
||||
50,29,0.03
|
||||
50,27,0.01
|
||||
50,40,1.0
|
||||
51,19,0.005
|
||||
51,20,0.4
|
||||
51,22,0.15
|
||||
51,23,0.04
|
||||
51,25,0.02
|
||||
51,28,0.25
|
||||
51,29,0.03
|
||||
51,27,0.01
|
||||
51,38,1.0
|
||||
52,19,0.005
|
||||
52,20,0.4
|
||||
52,22,0.15
|
||||
52,23,0.04
|
||||
52,25,0.02
|
||||
52,28,0.25
|
||||
52,29,0.03
|
||||
52,27,0.01
|
||||
52,41,1.0
|
||||
53,19,0.005
|
||||
53,20,0.4
|
||||
53,22,0.15
|
||||
53,23,0.04
|
||||
53,25,0.02
|
||||
53,28,0.25
|
||||
53,29,0.03
|
||||
53,27,0.01
|
||||
53,39,1.0
|
||||
54,19,0.005
|
||||
54,20,0.4
|
||||
54,22,0.15
|
||||
54,23,0.04
|
||||
54,25,0.02
|
||||
54,28,0.25
|
||||
54,29,0.03
|
||||
54,27,0.01
|
||||
54,43,1.0
|
||||
55,19,0.005
|
||||
55,20,0.4
|
||||
55,22,0.15
|
||||
55,23,0.04
|
||||
55,25,0.02
|
||||
55,28,0.25
|
||||
55,29,0.03
|
||||
55,27,0.01
|
||||
55,42,1.0
|
||||
90,7,1.7
|
||||
90,8,0.07
|
||||
90,9,0.07
|
||||
90,10,0.02
|
||||
90,11,0.04
|
||||
90,17,0.1
|
||||
90,19,0.005
|
||||
90,20,0.4
|
||||
90,21,0.04
|
||||
90,23,0.04
|
||||
90,24,0.07
|
||||
90,25,0.02
|
||||
90,28,0.03
|
||||
90,31,0.25
|
||||
90,44,0.2
|
||||
90,45,0.1
|
||||
91,8,0.07
|
||||
91,9,0.07
|
||||
91,10,0.02
|
||||
91,11,0.04
|
||||
91,17,0.1
|
||||
91,18,0.1
|
||||
91,19,0.005
|
||||
91,20,0.4
|
||||
91,23,0.04
|
||||
91,24,0.07
|
||||
91,28,0.03
|
||||
91,31,0.25
|
||||
92,8,0.07
|
||||
92,9,0.07
|
||||
92,10,0.02
|
||||
92,11,0.04
|
||||
92,17,0.1
|
||||
92,18,0.1
|
||||
92,19,0.005
|
||||
92,20,0.4
|
||||
92,23,0.04
|
||||
92,24,0.07
|
||||
92,28,0.03
|
||||
92,31,0.26
|
||||
93,8,0.07
|
||||
93,9,0.07
|
||||
93,10,0.02
|
||||
93,11,0.04
|
||||
93,17,0.1
|
||||
93,18,0.1
|
||||
93,19,0.005
|
||||
93,20,0.4
|
||||
93,23,0.04
|
||||
93,24,0.07
|
||||
93,28,0.03
|
||||
93,31,0.27
|
||||
94,8,0.07
|
||||
94,9,0.07
|
||||
94,10,0.02
|
||||
94,11,0.04
|
||||
94,17,0.1
|
||||
94,18,0.1
|
||||
94,19,0.005
|
||||
94,20,0.4
|
||||
94,23,0.04
|
||||
94,24,0.07
|
||||
94,28,0.03
|
||||
94,31,0.28
|
||||
95,8,0.1
|
||||
95,9,0.0
|
||||
95,10,7.0
|
||||
95,11,0.02
|
||||
95,12,0.03
|
||||
95,13,0.01
|
||||
95,14,0.01
|
||||
95,15,0.07
|
||||
95,16,0.05
|
||||
95,17,0.003
|
||||
95,18,0.1
|
||||
95,19,0.04
|
||||
95,20,0.01
|
||||
95,21,0.04
|
||||
95,22,0.03
|
||||
95,23,0.02
|
||||
95,24,0.01
|
||||
95,25,0.05
|
||||
95,26,0.01
|
||||
95,27,0.003
|
||||
95,28,0.1
|
||||
95,29,0.05
|
||||
95,30,0.04
|
||||
95,31,0.01
|
||||
95,37,0.1
|
||||
95,44,0.04
|
||||
95,45,0.7
|
||||
95,46,0.07
|
||||
95,47,0.01
|
||||
95,48,0.03
|
||||
95,49,0.01
|
||||
95,50,0.01
|
||||
95,51,0.01
|
||||
95,52,0.2
|
||||
95,53,0.03
|
||||
95,54,0.01
|
||||
95,55,0.01
|
||||
95,90,0.01
|
||||
95,91,0.01
|
||||
95,92,1.0
|
||||
95,93,1.0
|
||||
95,94,1.0
|
||||
96,95,1.0
|
||||
96,101,0.01
|
||||
96,102,0.01
|
||||
96,103,0.02
|
||||
96,104,0.01
|
||||
96,105,0.2
|
||||
96,106,0.1
|
||||
96,107,0.01
|
||||
96,108,0.03
|
||||
96,109,0.02
|
||||
|
14
main.py
14
main.py
@@ -3,6 +3,9 @@ import random
|
||||
import time
|
||||
from multiprocessing import Process
|
||||
import argparse
|
||||
|
||||
from matplotlib import pyplot as plt
|
||||
|
||||
from computation import Computation
|
||||
from sqlalchemy.orm import close_all_sessions
|
||||
import yaml
|
||||
@@ -30,11 +33,16 @@ def do_process(target: object, controller_db: ControllerDB, ):
|
||||
|
||||
for i in process_list:
|
||||
i.join()
|
||||
|
||||
# 所有子进程完成后刷新最终进度
|
||||
|
||||
# 显示最终进度后关闭图表
|
||||
|
||||
def do_computation(c_db):
|
||||
exp = Computation(c_db)
|
||||
|
||||
while 1:
|
||||
time.sleep(random.uniform(0, 1))
|
||||
# time.sleep(random.uniform(0, 1))
|
||||
is_all_done = exp.run()
|
||||
if is_all_done:
|
||||
break
|
||||
@@ -44,9 +52,9 @@ if __name__ == '__main__':
|
||||
# 输入参数
|
||||
parser = argparse.ArgumentParser(description='setting')
|
||||
parser.add_argument('--exp', type=str, default='without_exp')
|
||||
parser.add_argument('--job', type=int, default='3')
|
||||
parser.add_argument('--job', type=int, default='4')
|
||||
parser.add_argument('--reset_sample', type=int, default='0')
|
||||
parser.add_argument('--reset_db', type=bool, default=False)
|
||||
parser.add_argument('--reset_db', type=bool, default=True)
|
||||
|
||||
args = parser.parse_args()
|
||||
# 几核参与进程
|
||||
|
||||
1078
my_model.py
1078
my_model.py
File diff suppressed because it is too large
Load Diff
4
orm.py
4
orm.py
@@ -98,8 +98,8 @@ class Result(Base):
|
||||
s_id = Column(Integer, ForeignKey('{}.id'.format(
|
||||
f"{db_name_prefix}_sample")), nullable=False)
|
||||
|
||||
id_firm = Column(String(10), nullable=False)
|
||||
id_product = Column(String(10), nullable=False)
|
||||
id_firm = Column(String(20), nullable=False)
|
||||
id_product = Column(String(20), nullable=False)
|
||||
ts = Column(Integer, nullable=False)
|
||||
status = Column(String(5), nullable=False)
|
||||
|
||||
|
||||
9
output_result/resilience/anova.csv
Normal file
9
output_result/resilience/anova.csv
Normal file
@@ -0,0 +1,9 @@
|
||||
Unnamed: 0.1,Unnamed: 0,mean_end_ts,mean_n_remove_firm_prod,mean_max_ts_firm_prod,mean_count_firm_prod
|
||||
p1,n_sourcing,0.319,0.145,0.043,0.186
|
||||
p2,is_prf_size,0.607,0.608,0.005,0.111
|
||||
p3,n_max_trial,0.003,0.135,0.0,0.0
|
||||
p4,is_prf_conn,0.504,0.567,0.001,0.0
|
||||
p5,ex_cap_type,0.403,0.667,0.329,0.444
|
||||
p6,ex_cap_para,0.0,0.0,0.0,0.0
|
||||
p7,prob_new_conn,0.017,0.334,0.01,0.007
|
||||
p8,t_max_trial,0.0,0.014,0.939,0.1
|
||||
|
22
output_result/resilience/anova_visualization.csv
Normal file
22
output_result/resilience/anova_visualization.csv
Normal file
@@ -0,0 +1,22 @@
|
||||
自变量,level,系统恢复用时R1,产业-企业边累计扰乱次数R2,产业-企业边最大传导深度R3,产业-企业边断裂总数R4
|
||||
采购策略P1,三供应商,3.549,62.11,1.715,22.14
|
||||
采购策略P1,双供应商,3.743,62.43,1.759,21.71
|
||||
采购策略P1,单供应商,3.668,62.21,1.736,22.17
|
||||
是否规模偏好P2,倾向,3.681,62.13,1.715,22.06
|
||||
是否规模偏好P2,不倾向,3.627,62.37,1.758,21.96
|
||||
最大尝试次数P3,高,3.47,61.08,1.636,21.85
|
||||
最大尝试次数P3,中,3.552,62.08,1.742,21.86
|
||||
最大尝试次数P3,低,3.939,63.58,1.832,22.31
|
||||
是否已有连接偏好P4,倾向,3.619,61.95,1.711,21.95
|
||||
是否已有连接偏好P4,不倾向,3.689,62.55,1.762,22.07
|
||||
额外产能分布P5,均匀分布,3.698,62.19,1.73,21.96
|
||||
额外产能分布P5,正态分布,3.61,62.3,1.743,22.05
|
||||
额外产能分布参数P6,高,2.949,61.48,1.808,12.41
|
||||
额外产能分布参数P6,中,3.787,62.2,1.661,22.87
|
||||
额外产能分布参数P6,低,4.224,63.06,1.741,30.75
|
||||
新供应关系构成概率P7,低,3.882,62.41,1.749,22.2
|
||||
新供应关系构成概率P7,中,3.543,62.44,1.756,22.01
|
||||
新供应关系构成概率P7,高,3.535,61.9,1.705,21.82
|
||||
最大尝试时间步P8,低,2.601,62.03,1.738,22.47
|
||||
最大尝试时间步P8,中,3.656,62.31,1.733,21.78
|
||||
最大尝试时间步P8,高,4.704,62.4,1.738,21.78
|
||||
|
37
output_result/resilience/experiment_result.csv
Normal file
37
output_result/resilience/experiment_result.csv
Normal file
@@ -0,0 +1,37 @@
|
||||
idx_scenario,n_max_trial,prf_size,prf_conn,cap_limit_prob_type,cap_limit_level,diff_new_conn,remove_t,netw_prf_n,mean_count_firm_prod,mean_count_firm,mean_count_prod,mean_max_ts_firm_prod,mean_max_ts_firm,mean_max_ts_prod,mean_n_remove_firm_prod,mean_n_all_prod_remove_firm,mean_end_ts,
|
||||
0,7,1,1,uniform,5.0000,0.3000,3,3,59.6916,15.7589,13.3347,1.5063,1.5032,1.3842,12.3074,1.5379,2.0400
|
||||
1,5,1,1,uniform,10.0000,0.5000,5,2,61.8937,17.1126,13.8095,1.7284,1.7263,1.6042,22.7779,2.9611,3.7432
|
||||
2,3,1,1,uniform,15.0000,0.7000,7,1,63.9568,18.2253,14.2779,1.8263,1.8221,1.7347,30.9263,3.7842,5.6253
|
||||
3,7,1,1,uniform,5.0000,0.3000,3,2,59.5811,15.7474,13.3168,1.4958,1.4937,1.3884,12.8358,1.4621,2.0221
|
||||
4,5,1,1,uniform,10.0000,0.5000,5,1,61.8200,17.0116,13.8053,1.7095,1.7084,1.6032,22.5474,2.9579,3.6811
|
||||
5,3,1,1,uniform,15.0000,0.7000,7,3,63.8821,18.2547,14.2432,1.8421,1.8305,1.7295,30.9474,3.7411,5.6632
|
||||
6,7,1,1,normal,5.0000,0.5000,7,3,59.9116,15.7516,13.3316,1.4905,1.4884,1.3674,12.2463,1.3326,3.1600
|
||||
7,5,1,1,normal,10.0000,0.7000,3,2,61.3095,16.8326,13.7716,1.7011,1.7011,1.6011,22.4779,2.9642,2.4916
|
||||
8,3,1,1,normal,15.0000,0.3000,5,1,63.6568,18.1316,14.2358,1.8253,1.8232,1.7242,31.1253,3.7400,4.3474
|
||||
9,7,1,0,uniform,5.0000,0.7000,5,3,59.7158,15.6811,13.3000,1.4600,1.4568,1.3537,12.4063,1.3400,2.5316
|
||||
10,5,1,0,uniform,10.0000,0.3000,7,2,63.0063,17.6695,14.0432,1.8063,1.8053,1.6747,22.6916,3.0042,5.1126
|
||||
11,3,1,0,uniform,15.0000,0.5000,3,1,63.6779,18.3842,14.3547,1.8621,1.8600,1.7621,31.3663,4.0253,2.9632
|
||||
12,7,1,0,normal,10.0000,0.7000,3,1,60.6295,16.3884,13.5811,1.6179,1.6147,1.5147,22.5221,2.7800,2.3495
|
||||
13,5,1,0,normal,15.0000,0.3000,5,3,63.3484,18.0042,14.2074,1.8316,1.8263,1.7232,30.6379,3.7747,4.2979
|
||||
14,3,1,0,normal,5.0000,0.5000,7,2,64.0737,18.3684,14.3000,1.8505,1.8484,1.7589,11.4789,1.1663,4.1400
|
||||
15,7,1,0,normal,10.0000,0.7000,5,3,61.0337,16.5684,13.6053,1.6358,1.6347,1.5074,22.7474,2.8937,3.5147
|
||||
16,5,1,0,normal,15.0000,0.3000,7,2,63.4747,18.0568,14.1989,1.8347,1.8305,1.7263,30.4063,3.7989,5.7295
|
||||
17,3,1,0,normal,5.0000,0.5000,3,1,63.7158,18.2863,14.2958,1.8547,1.8537,1.7579,14.6568,2.1432,2.8368
|
||||
18,7,0,1,normal,10.0000,0.3000,7,1,61.2326,16.6442,13.6789,1.6705,1.6684,1.5495,22.5453,2.8379,4.7474
|
||||
19,5,0,1,normal,15.0000,0.5000,3,3,62.3863,17.4684,13.9905,1.7874,1.7853,1.6705,31.1558,3.8189,2.7926
|
||||
20,3,0,1,normal,5.0000,0.7000,5,2,62.8305,17.6074,14.0811,1.7705,1.7695,1.6768,11.7621,1.2474,3.2684
|
||||
21,7,0,1,normal,10.0000,0.5000,7,1,61.1832,16.5389,13.6874,1.6505,1.6484,1.5337,22.8484,2.8147,4.7326
|
||||
22,5,0,1,normal,15.0000,0.7000,3,3,62.3305,17.5337,14.0011,1.7768,1.7747,1.6495,30.6705,3.7832,2.7316
|
||||
23,3,0,1,normal,5.0000,0.3000,5,2,62.8821,17.6916,14.0905,1.7821,1.7821,1.6895,12.2158,1.3442,3.3484
|
||||
24,7,0,1,uniform,15.0000,0.5000,3,2,62.2463,17.4084,13.9789,1.7979,1.7958,1.6674,30.6842,3.7126,2.7589
|
||||
25,5,0,1,uniform,5.0000,0.7000,5,1,60.9453,16.4442,13.6316,1.6274,1.6263,1.5032,12.2347,1.2663,2.7368
|
||||
26,3,0,1,uniform,10.0000,0.3000,7,3,63.3400,17.8968,14.1147,1.8084,1.8074,1.6937,22.7768,3.0442,5.2442
|
||||
27,7,0,0,normal,15.0000,0.5000,5,2,62.6505,17.5074,14.0032,1.7811,1.7800,1.6758,30.0211,3.6116,4.1263
|
||||
28,5,0,0,normal,5.0000,0.7000,7,1,60.9200,16.5126,13.6168,1.6368,1.6358,1.5168,11.9432,1.2495,3.3305
|
||||
29,3,0,0,normal,10.0000,0.3000,3,3,63.9074,18.4432,14.3916,1.8811,1.8779,1.7789,25.4905,3.4789,3.0295
|
||||
30,7,0,0,uniform,15.0000,0.7000,7,2,62.2442,17.2747,13.9400,1.7400,1.7358,1.6253,30.5084,3.6589,5.4421
|
||||
31,5,0,0,uniform,5.0000,0.3000,3,1,61.9147,17.2211,13.9347,1.7558,1.7526,1.6453,12.8168,1.6895,2.4516
|
||||
32,3,0,0,uniform,10.0000,0.5000,5,3,64.1074,18.3579,14.3558,1.8579,1.8568,1.7505,22.2800,3.0684,4.0642
|
||||
33,7,0,0,uniform,15.0000,0.3000,5,1,62.8737,17.5600,14.0642,1.7895,1.7874,1.6684,30.5453,3.6695,4.2147
|
||||
34,5,0,0,uniform,5.0000,0.5000,7,3,61.6337,16.9042,13.7632,1.7032,1.7011,1.5716,12.0011,1.2263,3.5221
|
||||
35,3,0,0,uniform,10.0000,0.7000,3,2,62.9663,17.9737,14.2221,1.8221,1.8211,1.7211,22.6979,3.1600,2.7389
|
||||
|
File diff suppressed because it is too large
Load Diff
File diff suppressed because it is too large
Load Diff
BIN
output_result/risk/count_dcp_network.png
Normal file
BIN
output_result/risk/count_dcp_network.png
Normal file
Binary file not shown.
|
After Width: | Height: | Size: 1.1 MiB |
@@ -1,23 +1,710 @@
|
||||
up_id_product,down_id_product,count
|
||||
2.1.3.7,2.1.3,7
|
||||
1.3.1.3,1.3.1,5
|
||||
2.1.3.4,2.1.3,4
|
||||
2.1.3.2,2.1.3,3
|
||||
1.3.3.3,1.3.3,3
|
||||
1.1.1,1.1,2
|
||||
1.3.4.2,1.3.4,2
|
||||
2.1.1.5,2.1.1,2
|
||||
1.3.4.3,1.3.4,2
|
||||
2.3.1,2.3,2
|
||||
1.3.1.5,1.3.1,2
|
||||
1.3.3.4,1.3.3,1
|
||||
1.1.3,1.1,1
|
||||
1.4.5.6,1.4.5,1
|
||||
2.1.1.4,2.1.1,1
|
||||
1.3.1.7,1.3.1,1
|
||||
2.1.2.2,2.1.2,1
|
||||
1.3.1.4,1.3.1,1
|
||||
1.3.1.1,1.3.1,1
|
||||
2.1.4.1.1,2.1.4.1,1
|
||||
2.2,2,1
|
||||
1.4.3.4,1.4.3,1
|
||||
46,52,8413
|
||||
48,52,8375
|
||||
48,55,8345
|
||||
46,55,8328
|
||||
45,52,8274
|
||||
44,52,8248
|
||||
49,52,8246
|
||||
49,55,8197
|
||||
44,55,8172
|
||||
45,55,8151
|
||||
47,52,8077
|
||||
47,55,8016
|
||||
55,99,7248
|
||||
52,99,7163
|
||||
50,99,7085
|
||||
54,99,7066
|
||||
51,99,7031
|
||||
53,99,7010
|
||||
54,55,5570
|
||||
54,52,5539
|
||||
53,55,5524
|
||||
52,55,5462
|
||||
51,55,5441
|
||||
50,55,5440
|
||||
53,52,5438
|
||||
55,52,5379
|
||||
51,52,5312
|
||||
50,52,5296
|
||||
55,55,5254
|
||||
52,52,5177
|
||||
45,99,5036
|
||||
46,99,4997
|
||||
48,99,4976
|
||||
44,99,4960
|
||||
49,99,4941
|
||||
55,95,4906
|
||||
52,95,4895
|
||||
47,99,4812
|
||||
53,95,4643
|
||||
51,95,4628
|
||||
50,95,4578
|
||||
54,95,4539
|
||||
95,99,3147
|
||||
47,95,3060
|
||||
44,95,3028
|
||||
46,95,3026
|
||||
48,95,3021
|
||||
49,95,3013
|
||||
45,95,2937
|
||||
46,43,2771
|
||||
48,43,2748
|
||||
45,43,2740
|
||||
49,43,2738
|
||||
44,43,2721
|
||||
47,43,2720
|
||||
49,39,2461
|
||||
45,39,2460
|
||||
48,39,2452
|
||||
44,39,2427
|
||||
46,39,2409
|
||||
47,39,2378
|
||||
54,43,2375
|
||||
53,43,2366
|
||||
55,43,2364
|
||||
50,43,2338
|
||||
52,43,2328
|
||||
51,43,2327
|
||||
44,40,2305
|
||||
45,40,2296
|
||||
48,40,2289
|
||||
46,40,2287
|
||||
49,40,2265
|
||||
47,40,2257
|
||||
47,38,2240
|
||||
49,38,2224
|
||||
45,38,2214
|
||||
46,38,2200
|
||||
54,39,2195
|
||||
53,39,2184
|
||||
48,38,2183
|
||||
55,39,2177
|
||||
51,39,2162
|
||||
50,39,2156
|
||||
44,38,2154
|
||||
52,39,2147
|
||||
48,90,2100
|
||||
49,90,2092
|
||||
45,90,2088
|
||||
46,90,2077
|
||||
47,90,2062
|
||||
44,90,2054
|
||||
94,99,2051
|
||||
93,99,2019
|
||||
91,99,1996
|
||||
54,40,1977
|
||||
50,40,1976
|
||||
53,40,1973
|
||||
55,40,1966
|
||||
51,40,1964
|
||||
52,40,1937
|
||||
54,38,1928
|
||||
50,38,1910
|
||||
51,38,1900
|
||||
53,38,1893
|
||||
55,38,1888
|
||||
52,38,1883
|
||||
42,55,1788
|
||||
41,52,1779
|
||||
95,55,1734
|
||||
95,52,1729
|
||||
42,52,1717
|
||||
41,55,1699
|
||||
53,90,1629
|
||||
55,90,1628
|
||||
54,90,1623
|
||||
51,90,1619
|
||||
52,90,1606
|
||||
50,90,1597
|
||||
94,52,1207
|
||||
92,99,1179
|
||||
94,55,1143
|
||||
94,95,1124
|
||||
91,52,1084
|
||||
93,55,1073
|
||||
93,52,1065
|
||||
91,55,1057
|
||||
93,95,1005
|
||||
91,95,1005
|
||||
90,99,997
|
||||
95,95,798
|
||||
41,99,778
|
||||
42,99,765
|
||||
92,95,670
|
||||
92,55,644
|
||||
92,52,625
|
||||
95,43,563
|
||||
95,39,543
|
||||
90,95,523
|
||||
95,40,495
|
||||
42,95,464
|
||||
95,38,453
|
||||
41,95,441
|
||||
90,52,419
|
||||
95,90,407
|
||||
41,43,403
|
||||
20,55,402
|
||||
42,43,394
|
||||
90,55,390
|
||||
20,52,384
|
||||
41,39,381
|
||||
42,39,376
|
||||
41,40,345
|
||||
41,38,341
|
||||
7,95,340
|
||||
42,40,334
|
||||
42,38,332
|
||||
60,55,318
|
||||
60,52,316
|
||||
64,55,308
|
||||
67,55,300
|
||||
42,90,299
|
||||
23,52,299
|
||||
25,52,297
|
||||
65,55,296
|
||||
23,55,296
|
||||
71,55,296
|
||||
65,52,295
|
||||
25,55,294
|
||||
64,52,292
|
||||
67,52,290
|
||||
22,52,288
|
||||
22,55,287
|
||||
41,90,284
|
||||
71,52,282
|
||||
18,52,259
|
||||
15,48,258
|
||||
27,49,255
|
||||
18,46,252
|
||||
28,51,250
|
||||
27,47,250
|
||||
68,55,250
|
||||
29,55,250
|
||||
63,55,250
|
||||
72,51,249
|
||||
41,53,249
|
||||
43,53,249
|
||||
38,53,249
|
||||
69,55,249
|
||||
23,49,249
|
||||
42,53,249
|
||||
39,53,249
|
||||
23,45,248
|
||||
69,52,248
|
||||
68,52,248
|
||||
94,43,248
|
||||
20,44,248
|
||||
65,45,248
|
||||
40,51,247
|
||||
41,51,247
|
||||
38,51,247
|
||||
39,51,247
|
||||
71,54,247
|
||||
15,46,247
|
||||
63,50,247
|
||||
43,51,247
|
||||
42,51,247
|
||||
71,51,246
|
||||
62,53,246
|
||||
25,44,246
|
||||
39,55,246
|
||||
72,50,246
|
||||
67,48,246
|
||||
40,53,246
|
||||
43,55,246
|
||||
68,51,246
|
||||
40,55,246
|
||||
38,55,246
|
||||
18,44,246
|
||||
69,51,246
|
||||
23,50,246
|
||||
65,46,246
|
||||
20,48,246
|
||||
67,49,245
|
||||
72,54,245
|
||||
22,50,245
|
||||
33,47,245
|
||||
62,51,244
|
||||
68,54,244
|
||||
64,46,244
|
||||
23,44,244
|
||||
67,51,244
|
||||
18,48,244
|
||||
23,47,244
|
||||
69,53,244
|
||||
19,52,243
|
||||
65,47,243
|
||||
60,45,243
|
||||
65,54,243
|
||||
67,44,243
|
||||
28,52,243
|
||||
67,54,243
|
||||
60,54,243
|
||||
71,49,243
|
||||
20,46,243
|
||||
19,51,242
|
||||
20,54,242
|
||||
63,53,242
|
||||
65,48,242
|
||||
62,52,242
|
||||
64,54,242
|
||||
25,49,242
|
||||
71,45,242
|
||||
27,46,242
|
||||
69,50,241
|
||||
27,55,241
|
||||
67,46,241
|
||||
64,50,241
|
||||
64,45,241
|
||||
18,45,241
|
||||
60,44,241
|
||||
20,49,241
|
||||
19,55,241
|
||||
19,54,241
|
||||
63,52,241
|
||||
60,48,240
|
||||
25,53,240
|
||||
25,50,240
|
||||
15,49,240
|
||||
28,54,240
|
||||
72,55,240
|
||||
60,49,240
|
||||
27,48,240
|
||||
20,53,240
|
||||
19,50,240
|
||||
23,46,240
|
||||
40,52,239
|
||||
60,53,239
|
||||
38,52,239
|
||||
67,47,239
|
||||
39,52,239
|
||||
35,49,239
|
||||
68,50,239
|
||||
64,53,239
|
||||
43,52,239
|
||||
22,53,239
|
||||
20,47,238
|
||||
25,51,238
|
||||
65,53,238
|
||||
15,44,238
|
||||
18,49,238
|
||||
60,47,238
|
||||
28,53,238
|
||||
27,51,238
|
||||
29,50,238
|
||||
27,53,238
|
||||
29,53,238
|
||||
68,53,237
|
||||
67,53,237
|
||||
23,48,237
|
||||
67,50,237
|
||||
34,48,237
|
||||
72,52,237
|
||||
32,46,237
|
||||
27,50,237
|
||||
63,51,236
|
||||
19,53,236
|
||||
23,54,236
|
||||
71,48,236
|
||||
25,45,236
|
||||
15,47,236
|
||||
22,48,236
|
||||
20,50,236
|
||||
27,44,236
|
||||
22,46,235
|
||||
20,51,235
|
||||
38,50,235
|
||||
41,50,235
|
||||
39,50,235
|
||||
64,51,235
|
||||
22,44,235
|
||||
67,45,235
|
||||
40,50,235
|
||||
42,50,235
|
||||
28,50,235
|
||||
27,54,235
|
||||
27,52,235
|
||||
43,50,235
|
||||
60,50,234
|
||||
18,55,234
|
||||
25,47,234
|
||||
25,48,234
|
||||
65,49,234
|
||||
62,54,233
|
||||
64,49,233
|
||||
62,55,233
|
||||
71,46,233
|
||||
65,50,233
|
||||
72,53,233
|
||||
22,47,233
|
||||
22,45,233
|
||||
29,51,233
|
||||
15,45,232
|
||||
65,44,232
|
||||
22,49,232
|
||||
18,47,232
|
||||
64,48,232
|
||||
71,53,232
|
||||
23,53,231
|
||||
27,45,231
|
||||
20,45,231
|
||||
63,54,231
|
||||
28,55,231
|
||||
22,54,231
|
||||
22,51,230
|
||||
71,47,230
|
||||
60,51,230
|
||||
60,46,230
|
||||
62,50,230
|
||||
25,46,229
|
||||
25,54,229
|
||||
29,54,228
|
||||
50,45,227
|
||||
23,51,227
|
||||
48,45,227
|
||||
49,45,227
|
||||
55,45,227
|
||||
51,45,227
|
||||
54,45,227
|
||||
52,45,227
|
||||
7,45,227
|
||||
53,45,227
|
||||
47,45,227
|
||||
65,51,227
|
||||
71,44,227
|
||||
64,44,227
|
||||
45,45,227
|
||||
46,45,227
|
||||
44,45,227
|
||||
46,44,226
|
||||
7,44,226
|
||||
51,44,226
|
||||
45,44,226
|
||||
50,44,226
|
||||
55,44,226
|
||||
47,44,226
|
||||
48,44,226
|
||||
44,44,226
|
||||
49,44,226
|
||||
53,44,226
|
||||
54,44,226
|
||||
52,44,226
|
||||
69,54,225
|
||||
29,52,224
|
||||
64,47,224
|
||||
39,54,222
|
||||
41,54,222
|
||||
38,54,222
|
||||
42,54,222
|
||||
43,54,222
|
||||
40,54,222
|
||||
71,50,221
|
||||
91,40,208
|
||||
93,43,208
|
||||
91,43,204
|
||||
93,39,199
|
||||
93,40,198
|
||||
94,40,190
|
||||
91,39,189
|
||||
94,38,184
|
||||
93,38,182
|
||||
91,38,182
|
||||
94,39,181
|
||||
90,43,158
|
||||
90,39,130
|
||||
90,38,130
|
||||
92,43,130
|
||||
90,40,127
|
||||
91,90,124
|
||||
94,90,120
|
||||
93,90,120
|
||||
20,95,118
|
||||
23,95,113
|
||||
92,40,109
|
||||
92,39,107
|
||||
92,38,107
|
||||
15,95,97
|
||||
19,95,90
|
||||
62,95,90
|
||||
28,95,90
|
||||
9,95,88
|
||||
18,95,88
|
||||
7,90,86
|
||||
64,95,86
|
||||
66,95,83
|
||||
60,95,79
|
||||
24,95,79
|
||||
72,95,78
|
||||
22,99,74
|
||||
31,95,73
|
||||
8,95,73
|
||||
17,94,72
|
||||
28,94,71
|
||||
67,95,71
|
||||
27,95,70
|
||||
17,99,70
|
||||
66,91,69
|
||||
63,95,69
|
||||
9,94,69
|
||||
18,94,69
|
||||
28,99,69
|
||||
59,94,69
|
||||
24,94,68
|
||||
31,93,68
|
||||
65,99,68
|
||||
11,94,68
|
||||
29,99,68
|
||||
23,94,68
|
||||
66,93,67
|
||||
70,91,67
|
||||
28,93,67
|
||||
10,93,67
|
||||
8,91,67
|
||||
70,93,67
|
||||
15,55,66
|
||||
10,94,66
|
||||
66,94,66
|
||||
64,99,66
|
||||
59,93,66
|
||||
31,94,66
|
||||
18,93,65
|
||||
62,94,65
|
||||
11,93,65
|
||||
8,94,65
|
||||
59,99,65
|
||||
9,93,65
|
||||
62,91,64
|
||||
24,91,64
|
||||
25,99,64
|
||||
19,94,64
|
||||
18,91,64
|
||||
10,91,64
|
||||
61,93,64
|
||||
61,91,64
|
||||
8,93,64
|
||||
9,91,64
|
||||
24,93,64
|
||||
31,91,63
|
||||
43,95,63
|
||||
39,95,63
|
||||
19,93,63
|
||||
61,94,62
|
||||
59,91,62
|
||||
11,91,62
|
||||
38,95,62
|
||||
71,99,62
|
||||
40,95,62
|
||||
23,93,62
|
||||
65,94,61
|
||||
20,93,61
|
||||
23,91,61
|
||||
79,99,61
|
||||
10,99,61
|
||||
20,94,61
|
||||
29,95,60
|
||||
71,95,60
|
||||
19,91,60
|
||||
70,95,60
|
||||
17,95,60
|
||||
65,95,60
|
||||
25,95,60
|
||||
61,95,60
|
||||
22,95,60
|
||||
10,95,60
|
||||
59,95,60
|
||||
62,93,59
|
||||
17,93,59
|
||||
92,90,59
|
||||
70,94,58
|
||||
20,91,58
|
||||
15,52,58
|
||||
28,91,58
|
||||
65,91,57
|
||||
17,91,57
|
||||
62,99,57
|
||||
18,99,57
|
||||
65,93,55
|
||||
70,99,55
|
||||
69,95,55
|
||||
11,95,53
|
||||
8,99,52
|
||||
68,95,52
|
||||
97,95,50
|
||||
9,99,49
|
||||
30,95,49
|
||||
74,95,49
|
||||
26,95,49
|
||||
19,99,49
|
||||
73,95,49
|
||||
37,95,48
|
||||
16,95,48
|
||||
13,95,48
|
||||
12,95,48
|
||||
49,53,45
|
||||
23,90,45
|
||||
52,53,45
|
||||
65,90,40
|
||||
18,92,40
|
||||
25,41,40
|
||||
28,92,39
|
||||
46,53,39
|
||||
44,53,39
|
||||
48,53,39
|
||||
11,92,39
|
||||
59,92,39
|
||||
60,90,39
|
||||
71,42,39
|
||||
31,92,39
|
||||
62,92,38
|
||||
66,99,38
|
||||
70,92,38
|
||||
18,41,38
|
||||
17,92,38
|
||||
23,42,38
|
||||
64,42,38
|
||||
15,42,38
|
||||
31,42,38
|
||||
9,92,38
|
||||
24,99,38
|
||||
65,92,38
|
||||
25,90,37
|
||||
65,43,37
|
||||
67,90,37
|
||||
71,90,37
|
||||
23,92,37
|
||||
65,41,37
|
||||
67,42,37
|
||||
20,92,37
|
||||
20,42,37
|
||||
24,92,37
|
||||
45,53,36
|
||||
71,43,36
|
||||
20,90,36
|
||||
50,53,36
|
||||
31,41,36
|
||||
60,41,36
|
||||
53,53,36
|
||||
10,92,36
|
||||
61,92,36
|
||||
25,40,36
|
||||
19,92,36
|
||||
67,41,36
|
||||
8,92,36
|
||||
22,43,35
|
||||
25,43,35
|
||||
9,90,35
|
||||
7,39,35
|
||||
22,90,35
|
||||
20,41,35
|
||||
18,42,35
|
||||
61,90,35
|
||||
71,39,34
|
||||
71,41,34
|
||||
7,40,34
|
||||
23,41,34
|
||||
66,92,34
|
||||
22,42,34
|
||||
60,42,34
|
||||
25,38,33
|
||||
55,53,33
|
||||
25,42,33
|
||||
65,39,33
|
||||
54,53,33
|
||||
65,38,33
|
||||
22,41,33
|
||||
66,90,33
|
||||
47,53,33
|
||||
51,53,33
|
||||
65,42,33
|
||||
7,43,33
|
||||
22,39,33
|
||||
64,41,33
|
||||
7,38,32
|
||||
36,41,32
|
||||
15,99,32
|
||||
18,90,32
|
||||
15,41,32
|
||||
65,40,32
|
||||
59,90,31
|
||||
18,43,31
|
||||
18,40,31
|
||||
17,90,31
|
||||
71,40,31
|
||||
8,90,31
|
||||
19,90,30
|
||||
11,90,30
|
||||
28,90,30
|
||||
24,90,30
|
||||
90,90,30
|
||||
62,90,30
|
||||
22,38,30
|
||||
71,38,29
|
||||
10,90,29
|
||||
22,40,28
|
||||
63,99,28
|
||||
68,90,28
|
||||
25,39,27
|
||||
18,38,26
|
||||
67,99,25
|
||||
64,39,24
|
||||
18,39,24
|
||||
31,90,24
|
||||
15,90,23
|
||||
72,99,22
|
||||
60,43,21
|
||||
99,99,20
|
||||
20,99,18
|
||||
23,99,18
|
||||
64,38,17
|
||||
38,99,17
|
||||
60,39,17
|
||||
23,43,17
|
||||
60,99,16
|
||||
64,43,15
|
||||
20,39,15
|
||||
31,52,14
|
||||
67,39,14
|
||||
43,99,13
|
||||
60,40,13
|
||||
99,53,12
|
||||
64,90,12
|
||||
23,40,12
|
||||
20,43,12
|
||||
27,90,12
|
||||
64,40,11
|
||||
60,38,11
|
||||
27,43,11
|
||||
40,99,10
|
||||
31,55,10
|
||||
39,99,10
|
||||
15,43,10
|
||||
27,40,10
|
||||
23,38,9
|
||||
20,40,9
|
||||
20,38,9
|
||||
95,53,9
|
||||
23,39,8
|
||||
33,95,7
|
||||
69,99,7
|
||||
90,53,6
|
||||
15,40,6
|
||||
61,99,6
|
||||
67,43,6
|
||||
31,99,5
|
||||
15,38,5
|
||||
15,39,4
|
||||
99,95,4
|
||||
27,39,4
|
||||
67,40,4
|
||||
67,38,4
|
||||
33,38,3
|
||||
13,99,2
|
||||
27,99,2
|
||||
35,95,2
|
||||
32,95,1
|
||||
11,99,1
|
||||
32,43,1
|
||||
68,99,1
|
||||
34,95,1
|
||||
73,99,1
|
||||
|
||||
|
BIN
output_result/risk/count_dcp_prod_network.png
Normal file
BIN
output_result/risk/count_dcp_prod_network.png
Normal file
Binary file not shown.
|
After Width: | Height: | Size: 2.6 MiB |
@@ -1,46 +1,175 @@
|
||||
id_firm,count
|
||||
126,6
|
||||
85,5
|
||||
100,3
|
||||
80,3
|
||||
79,3
|
||||
99,3
|
||||
57,2
|
||||
74,2
|
||||
13,2
|
||||
97,2
|
||||
94,2
|
||||
93,2
|
||||
108,2
|
||||
45,2
|
||||
68,2
|
||||
53,2
|
||||
106,2
|
||||
73,2
|
||||
75,2
|
||||
58,1
|
||||
124,1
|
||||
77,1
|
||||
117,1
|
||||
81,1
|
||||
84,1
|
||||
98,1
|
||||
115,1
|
||||
49,1
|
||||
50,1
|
||||
159,1
|
||||
131,1
|
||||
135,1
|
||||
14,1
|
||||
142,1
|
||||
148,1
|
||||
149,1
|
||||
21,1
|
||||
119,1
|
||||
22,1
|
||||
23,1
|
||||
25,1
|
||||
26,1
|
||||
31,1
|
||||
41,1
|
||||
36,1
|
||||
653528340,4007
|
||||
2348941764,3957
|
||||
3215814536,3831
|
||||
888395016,3750
|
||||
2354145351,3619
|
||||
3147511625,3346
|
||||
3048263744,3326
|
||||
2317245827,3230
|
||||
631449822,3149
|
||||
3103797386,3123
|
||||
194210021,3077
|
||||
2327031723,3004
|
||||
301209792,2997
|
||||
191912252,2804
|
||||
70634828,2464
|
||||
2321109759,1165
|
||||
3299144127,1130
|
||||
3445928818,1120
|
||||
2312490120,1077
|
||||
503176785,1003
|
||||
930767828,467
|
||||
3407754893,451
|
||||
2944892892,355
|
||||
3269039233,354
|
||||
750610681,353
|
||||
25685135,351
|
||||
343012684,342
|
||||
3069206426,339
|
||||
448033045,329
|
||||
2624175,328
|
||||
2320475044,321
|
||||
413274977,314
|
||||
3111033905,310
|
||||
2317841563,310
|
||||
43407343,304
|
||||
571058167,302
|
||||
607512171,286
|
||||
152008168,272
|
||||
888356483,250
|
||||
25945288,222
|
||||
1452048,20
|
||||
2311838590,20
|
||||
3373311444,20
|
||||
11807506,20
|
||||
2424229017,18
|
||||
4208851809,10
|
||||
3271705843,10
|
||||
3269940677,10
|
||||
420984285,10
|
||||
400488703,10
|
||||
400692942,10
|
||||
354897041,10
|
||||
3462551351,10
|
||||
3288105727,10
|
||||
3312358902,10
|
||||
3344297292,10
|
||||
3372913783,10
|
||||
3384021594,10
|
||||
3445244192,10
|
||||
3433628561,10
|
||||
3395900897,10
|
||||
453289520,10
|
||||
1033972427,10
|
||||
581407487,10
|
||||
474279224,10
|
||||
857978527,10
|
||||
7299120,10
|
||||
737770776,10
|
||||
762985858,10
|
||||
771821595,10
|
||||
80158773,10
|
||||
829768,10
|
||||
863079,10
|
||||
495782506,10
|
||||
868012326,10
|
||||
872394725,10
|
||||
887840774,10
|
||||
888478182,10
|
||||
9,10
|
||||
9746245,10
|
||||
71271700,10
|
||||
7,10
|
||||
695995052,10
|
||||
688155470,10
|
||||
654825436,10
|
||||
644292599,10
|
||||
620220747,10
|
||||
615763365,10
|
||||
594378026,10
|
||||
593312758,10
|
||||
591452402,10
|
||||
5849940,10
|
||||
3226664625,10
|
||||
561545339,10
|
||||
560866402,10
|
||||
549184982,10
|
||||
5278074,10
|
||||
3267688490,10
|
||||
996174506,10
|
||||
3221190269,10
|
||||
2311581270,10
|
||||
2316990095,10
|
||||
2320102626,10
|
||||
2324787028,10
|
||||
2324844174,10
|
||||
2326478786,10
|
||||
2327979389,10
|
||||
2329375731,10
|
||||
2333843479,10
|
||||
2337952436,10
|
||||
2339684065,10
|
||||
2341555098,10
|
||||
2343704209,10
|
||||
2347013470,10
|
||||
2350418059,10
|
||||
2352036411,10
|
||||
2313209417,10
|
||||
2310825263,10
|
||||
3211956484,10
|
||||
218633337,10
|
||||
1128343125,10
|
||||
118882692,10
|
||||
1217957486,10
|
||||
1307012237,10
|
||||
1375606900,10
|
||||
145511905,10
|
||||
151606446,10
|
||||
1549474227,10
|
||||
15613202,10
|
||||
159511306,10
|
||||
1606833003,10
|
||||
1679596339,10
|
||||
2010673,10
|
||||
203314437,10
|
||||
213386023,10
|
||||
24284343,10
|
||||
24673506,10
|
||||
25036634,10
|
||||
3120341363,10
|
||||
3047163873,10
|
||||
3070859372,10
|
||||
3072715478,10
|
||||
3089095447,10
|
||||
3100891962,10
|
||||
3113895788,10
|
||||
3122923980,10
|
||||
251189644,10
|
||||
11164476478,10
|
||||
3133307899,10
|
||||
3177507356,10
|
||||
3188352290,10
|
||||
3188903709,10
|
||||
3195502499,10
|
||||
3045721313,10
|
||||
3031009366,10
|
||||
3026382513,10
|
||||
271860868,10
|
||||
2545430247,10
|
||||
26162741,10
|
||||
26516263,10
|
||||
3025036704,10
|
||||
27075840,10
|
||||
2728939,10
|
||||
27731896,10
|
||||
278221281,10
|
||||
2820140348,10
|
||||
29954548,10
|
||||
3398677646,9
|
||||
3127420424,9
|
||||
5007015990,8
|
||||
3203777710,8
|
||||
2339188563,7
|
||||
483081978,6
|
||||
517717050,6
|
||||
|
||||
|
@@ -1,58 +1,370 @@
|
||||
id_firm,id_product,count
|
||||
126,2.1.3,4
|
||||
100,1.3.1,3
|
||||
85,1.3.1,3
|
||||
106,2.1.3,2
|
||||
68,1.3.1.3,2
|
||||
73,2.1.3,2
|
||||
74,2.1.3,2
|
||||
75,1.3.3,2
|
||||
85,2.1.1,2
|
||||
80,1.3.4,2
|
||||
93,1.3.1,2
|
||||
94,1.1,2
|
||||
108,2.1.3,2
|
||||
99,1.3.1,2
|
||||
53,1.4.5.6,1
|
||||
57,1.3.3.3,1
|
||||
57,2.3.1,1
|
||||
58,1.3.4.3,1
|
||||
98,2,1
|
||||
97,2.1.3,1
|
||||
97,1.3.3,1
|
||||
77,1.3.4,1
|
||||
79,2.1.3.2,1
|
||||
79,2.1.3.7,1
|
||||
79,2.1.4.1,1
|
||||
50,1.3.1.5,1
|
||||
80,2.1.1,1
|
||||
81,1.3.4,1
|
||||
84,2.3,1
|
||||
53,1.4.3.4,1
|
||||
45,2.1.4.1.1,1
|
||||
49,1.3.1.4,1
|
||||
45,1.3.4.2,1
|
||||
115,1.1.3,1
|
||||
117,2.1.1.4,1
|
||||
119,1.3.1.1,1
|
||||
124,2.3,1
|
||||
126,1.1,1
|
||||
126,2.1.1.5,1
|
||||
13,2.1.3.4,1
|
||||
13,2.1.3.7,1
|
||||
131,2.1.1.5,1
|
||||
135,2.2,1
|
||||
14,1.3.3.4,1
|
||||
142,1.4.3,1
|
||||
148,2.1.3,1
|
||||
149,2.1.2.2,1
|
||||
159,2.1.2,1
|
||||
21,1.3.1.3,1
|
||||
22,2.1.3.7,1
|
||||
23,2.3.1,1
|
||||
25,1.3.1.7,1
|
||||
26,2.1.3.4,1
|
||||
31,1.3.3.3,1
|
||||
36,1.1.1,1
|
||||
41,1.4.5,1
|
||||
99,1.3.3,1
|
||||
2321109759,95,1155
|
||||
3299144127,95,1138
|
||||
3445928818,95,1123
|
||||
930767828,90,468
|
||||
3407754893,90,443
|
||||
653528340,55,434
|
||||
653528340,52,430
|
||||
2348941764,55,427
|
||||
2348941764,52,425
|
||||
2354145351,52,421
|
||||
3215814536,52,421
|
||||
888395016,55,420
|
||||
2354145351,55,419
|
||||
888395016,52,411
|
||||
3215814536,55,409
|
||||
653528340,54,397
|
||||
653528340,53,396
|
||||
653528340,50,395
|
||||
653528340,51,395
|
||||
750610681,92,389
|
||||
343012684,92,379
|
||||
2348941764,51,379
|
||||
3048263744,55,379
|
||||
2354145351,53,377
|
||||
3147511625,52,374
|
||||
2354145351,51,372
|
||||
888395016,50,371
|
||||
888395016,53,371
|
||||
3048263744,52,370
|
||||
888395016,51,369
|
||||
2348941764,53,369
|
||||
2348941764,54,367
|
||||
3147511625,55,367
|
||||
2354145351,54,365
|
||||
448033045,94,364
|
||||
2354145351,50,364
|
||||
2348941764,50,361
|
||||
3269039233,99,361
|
||||
888395016,54,358
|
||||
3215814536,51,355
|
||||
2944892892,99,354
|
||||
2317245827,55,353
|
||||
25685135,99,351
|
||||
2317245827,52,350
|
||||
3215814536,54,349
|
||||
631449822,55,349
|
||||
3069206426,93,348
|
||||
3215814536,50,347
|
||||
194210021,52,346
|
||||
631449822,52,345
|
||||
3215814536,53,344
|
||||
3111033905,93,343
|
||||
2327031723,52,341
|
||||
191912252,55,341
|
||||
70634828,52,340
|
||||
3103797386,55,339
|
||||
194210021,55,336
|
||||
301209792,52,335
|
||||
301209792,55,333
|
||||
3103797386,52,332
|
||||
191912252,52,330
|
||||
2320475044,94,327
|
||||
3147511625,53,322
|
||||
3048263744,53,319
|
||||
2327031723,55,318
|
||||
2624175,99,318
|
||||
3147511625,51,316
|
||||
3048263744,51,312
|
||||
3147511625,54,310
|
||||
2317245827,50,308
|
||||
3147511625,50,307
|
||||
3048263744,50,307
|
||||
571058167,94,306
|
||||
2317245827,53,303
|
||||
2317841563,91,303
|
||||
3048263744,54,302
|
||||
2317245827,54,298
|
||||
631449822,51,297
|
||||
194210021,53,297
|
||||
413274977,91,295
|
||||
3103797386,50,291
|
||||
2317245827,51,291
|
||||
3103797386,51,290
|
||||
43407343,93,289
|
||||
70634828,55,289
|
||||
607512171,91,288
|
||||
194210021,51,288
|
||||
3103797386,53,287
|
||||
194210021,50,287
|
||||
194210021,54,286
|
||||
631449822,53,285
|
||||
653528340,48,285
|
||||
152008168,94,283
|
||||
653528340,49,283
|
||||
653528340,46,282
|
||||
631449822,50,281
|
||||
3103797386,54,281
|
||||
653528340,45,278
|
||||
2327031723,53,277
|
||||
653528340,44,276
|
||||
653528340,47,276
|
||||
2327031723,50,275
|
||||
631449822,54,273
|
||||
191912252,54,272
|
||||
2327031723,51,270
|
||||
301209792,54,266
|
||||
2312490120,41,266
|
||||
888395016,45,266
|
||||
2348941764,49,266
|
||||
191912252,51,264
|
||||
301209792,53,263
|
||||
2348941764,48,262
|
||||
2348941764,46,262
|
||||
2348941764,45,261
|
||||
301209792,51,261
|
||||
301209792,50,260
|
||||
2327031723,54,259
|
||||
888395016,49,259
|
||||
2348941764,47,257
|
||||
191912252,50,256
|
||||
888395016,48,256
|
||||
2348941764,44,253
|
||||
888395016,46,253
|
||||
2354145351,46,252
|
||||
70634828,51,252
|
||||
888395016,47,251
|
||||
2312490120,42,250
|
||||
191912252,53,248
|
||||
888395016,44,248
|
||||
2354145351,47,247
|
||||
2354145351,49,246
|
||||
2354145351,48,245
|
||||
3215814536,49,241
|
||||
70634828,54,239
|
||||
3215814536,48,238
|
||||
888356483,91,236
|
||||
3215814536,46,236
|
||||
70634828,50,232
|
||||
3215814536,47,232
|
||||
2354145351,45,231
|
||||
2354145351,44,231
|
||||
3215814536,44,230
|
||||
3215814536,45,230
|
||||
3048263744,48,230
|
||||
70634828,53,229
|
||||
3048263744,47,227
|
||||
3048263744,46,221
|
||||
3048263744,45,220
|
||||
3048263744,44,217
|
||||
194210021,46,217
|
||||
2317245827,44,217
|
||||
3048263744,49,216
|
||||
3147511625,48,212
|
||||
3147511625,49,212
|
||||
3147511625,45,210
|
||||
3147511625,44,210
|
||||
2317245827,46,209
|
||||
503176785,42,208
|
||||
503176785,41,208
|
||||
3147511625,47,206
|
||||
194210021,48,206
|
||||
3103797386,44,205
|
||||
2317245827,47,204
|
||||
194210021,44,203
|
||||
2317245827,49,203
|
||||
3147511625,46,202
|
||||
2317245827,45,201
|
||||
194210021,45,200
|
||||
3103797386,49,200
|
||||
631449822,45,199
|
||||
194210021,49,197
|
||||
191912252,49,196
|
||||
3103797386,46,196
|
||||
2317245827,48,196
|
||||
2327031723,49,195
|
||||
194210021,47,194
|
||||
25945288,93,194
|
||||
631449822,49,193
|
||||
2327031723,48,192
|
||||
301209792,46,192
|
||||
70634828,49,191
|
||||
191912252,46,190
|
||||
191912252,44,190
|
||||
2327031723,45,190
|
||||
3103797386,47,190
|
||||
631449822,48,189
|
||||
3103797386,48,189
|
||||
301209792,44,188
|
||||
631449822,47,185
|
||||
301209792,45,185
|
||||
191912252,48,183
|
||||
191912252,45,183
|
||||
631449822,44,183
|
||||
2327031723,46,182
|
||||
503176785,43,182
|
||||
3103797386,45,181
|
||||
70634828,46,180
|
||||
631449822,46,180
|
||||
2327031723,44,180
|
||||
301209792,48,177
|
||||
2327031723,47,176
|
||||
191912252,47,174
|
||||
301209792,49,174
|
||||
301209792,47,173
|
||||
70634828,48,173
|
||||
70634828,47,172
|
||||
70634828,44,165
|
||||
70634828,45,160
|
||||
2312490120,40,140
|
||||
2312490120,39,139
|
||||
2312490120,38,135
|
||||
503176785,39,128
|
||||
503176785,38,122
|
||||
2312490120,43,119
|
||||
503176785,40,110
|
||||
3133307899,23,20
|
||||
3395900897,73,18
|
||||
3221190269,20,17
|
||||
3384021594,64,15
|
||||
2820140348,62,15
|
||||
1375606900,67,15
|
||||
3445244192,24,15
|
||||
887840774,8,15
|
||||
3312358902,59,14
|
||||
26516263,8,14
|
||||
24284343,35,14
|
||||
251189644,23,14
|
||||
7,10,14
|
||||
26162741,11,14
|
||||
400692942,68,13
|
||||
354897041,72,13
|
||||
996174506,15,13
|
||||
3211956484,34,13
|
||||
203314437,22,13
|
||||
11807506,23,13
|
||||
1307012237,68,13
|
||||
194210021,7,13
|
||||
2010673,64,13
|
||||
3373311444,20,13
|
||||
688155470,30,13
|
||||
2347013470,61,13
|
||||
271860868,12,13
|
||||
71271700,27,12
|
||||
863079,11,12
|
||||
420984285,16,12
|
||||
644292599,11,12
|
||||
9,37,12
|
||||
5849940,26,12
|
||||
9746245,97,12
|
||||
868012326,29,12
|
||||
1033972427,61,12
|
||||
3373311444,71,12
|
||||
3120341363,79,12
|
||||
1128343125,63,12
|
||||
1217957486,31,12
|
||||
1452048,63,12
|
||||
191912252,7,12
|
||||
2311838590,97,12
|
||||
2327979389,13,12
|
||||
2341555098,11,12
|
||||
2354145351,7,12
|
||||
2728939,63,12
|
||||
25036634,31,12
|
||||
3271705843,62,12
|
||||
3344297292,12,12
|
||||
2350418059,79,11
|
||||
15613202,32,11
|
||||
2352036411,17,11
|
||||
653528340,7,11
|
||||
3269940677,28,11
|
||||
278221281,66,11
|
||||
2324844174,67,11
|
||||
2317245827,7,11
|
||||
3045721313,25,11
|
||||
3070859372,62,11
|
||||
771821595,10,11
|
||||
615763365,68,11
|
||||
1679596339,74,11
|
||||
561545339,33,11
|
||||
2311581270,19,11
|
||||
888478182,9,11
|
||||
3398677646,79,11
|
||||
888395016,7,11
|
||||
3195502499,18,11
|
||||
1549474227,67,11
|
||||
474279224,71,11
|
||||
453289520,37,10
|
||||
2313209417,32,10
|
||||
11807506,60,10
|
||||
2324787028,18,10
|
||||
5278074,36,10
|
||||
2327031723,7,10
|
||||
3188903709,65,10
|
||||
3372913783,20,10
|
||||
695995052,8,10
|
||||
2343704209,69,10
|
||||
400488703,28,10
|
||||
118882692,35,10
|
||||
3047163873,27,10
|
||||
3127420424,32,10
|
||||
151606446,61,10
|
||||
3122923980,34,10
|
||||
593312758,31,10
|
||||
80158773,69,10
|
||||
145511905,68,10
|
||||
4208851809,16,10
|
||||
2311838590,34,9
|
||||
2348941764,7,9
|
||||
2326478786,60,9
|
||||
872394725,70,9
|
||||
737770776,34,9
|
||||
218633337,33,9
|
||||
2333843479,70,9
|
||||
213386023,19,9
|
||||
2337952436,24,9
|
||||
1606833003,9,9
|
||||
159511306,69,9
|
||||
3072715478,33,9
|
||||
3267688490,73,9
|
||||
3026382513,15,9
|
||||
3203777710,74,9
|
||||
5007015990,74,9
|
||||
3188352290,64,9
|
||||
3177507356,24,9
|
||||
620220747,15,9
|
||||
3031009366,59,9
|
||||
631449822,7,9
|
||||
581407487,72,8
|
||||
591452402,66,8
|
||||
594378026,27,8
|
||||
3100891962,26,8
|
||||
3215814536,7,8
|
||||
24673506,67,8
|
||||
2339188563,37,8
|
||||
29954548,27,8
|
||||
2339684065,74,8
|
||||
3462551351,13,8
|
||||
560866402,9,7
|
||||
3103797386,7,7
|
||||
2320102626,18,7
|
||||
3288105727,36,7
|
||||
829768,23,7
|
||||
2424229017,30,7
|
||||
11164476478,60,7
|
||||
762985858,72,7
|
||||
7299120,32,7
|
||||
70634828,7,7
|
||||
2316990095,66,7
|
||||
3025036704,17,7
|
||||
3113895788,35,7
|
||||
654825436,61,6
|
||||
1452048,30,6
|
||||
3147511625,7,6
|
||||
3226664625,28,6
|
||||
549184982,69,6
|
||||
301209792,7,6
|
||||
2545430247,25,6
|
||||
2329375731,31,6
|
||||
27075840,65,6
|
||||
857978527,60,6
|
||||
2424229017,26,6
|
||||
3048263744,7,6
|
||||
3433628561,29,5
|
||||
517717050,36,5
|
||||
495782506,19,5
|
||||
483081978,36,5
|
||||
27731896,20,5
|
||||
3089095447,22,5
|
||||
2310825263,15,4
|
||||
|
||||
|
@@ -1,35 +1,73 @@
|
||||
id_product,count
|
||||
2.1.3,14
|
||||
1.3.1,10
|
||||
1.3.4,4
|
||||
1.3.3,4
|
||||
1.1,3
|
||||
2.1.3.7,3
|
||||
1.3.1.3,3
|
||||
2.1.1,3
|
||||
2.3,2
|
||||
2.1.3.4,2
|
||||
2.1.1.5,2
|
||||
2.3.1,2
|
||||
1.3.3.3,2
|
||||
1.3.3.4,1
|
||||
2.1.2.2,1
|
||||
1.1.3,1
|
||||
2.2,1
|
||||
2.1.4.1.1,1
|
||||
2.1.4.1,1
|
||||
1.3.1.1,1
|
||||
1.3.1.4,1
|
||||
2.1.3.2,1
|
||||
1.3.1.5,1
|
||||
2.1.2,1
|
||||
1.3.4.2,1
|
||||
1.3.1.7,1
|
||||
2.1.1.4,1
|
||||
2,1
|
||||
1.4.5.6,1
|
||||
1.1.1,1
|
||||
1.4.3.4,1
|
||||
1.4.3,1
|
||||
1.3.4.3,1
|
||||
1.4.5,1
|
||||
52,5571
|
||||
55,5513
|
||||
51,4711
|
||||
53,4687
|
||||
50,4642
|
||||
54,4622
|
||||
95,3416
|
||||
49,3272
|
||||
46,3254
|
||||
48,3233
|
||||
44,3196
|
||||
45,3195
|
||||
47,3164
|
||||
99,1384
|
||||
94,1280
|
||||
93,1174
|
||||
91,1122
|
||||
90,911
|
||||
92,768
|
||||
41,474
|
||||
42,458
|
||||
43,301
|
||||
39,267
|
||||
38,257
|
||||
40,250
|
||||
7,138
|
||||
23,54
|
||||
11,50
|
||||
68,47
|
||||
20,45
|
||||
67,45
|
||||
34,41
|
||||
61,41
|
||||
31,40
|
||||
8,39
|
||||
62,38
|
||||
32,38
|
||||
27,38
|
||||
74,37
|
||||
64,37
|
||||
63,36
|
||||
15,35
|
||||
69,35
|
||||
79,34
|
||||
24,33
|
||||
60,32
|
||||
35,31
|
||||
37,30
|
||||
33,29
|
||||
72,28
|
||||
18,28
|
||||
9,27
|
||||
73,27
|
||||
36,27
|
||||
28,27
|
||||
66,26
|
||||
30,26
|
||||
26,26
|
||||
12,25
|
||||
10,25
|
||||
19,25
|
||||
97,24
|
||||
71,23
|
||||
59,23
|
||||
16,22
|
||||
13,20
|
||||
70,18
|
||||
17,18
|
||||
22,18
|
||||
25,17
|
||||
29,17
|
||||
65,16
|
||||
|
||||
|
Binary file not shown.
|
Before Width: | Height: | Size: 1.1 MiB After Width: | Height: | Size: 5.7 MiB |
Binary file not shown.
|
Before Width: | Height: | Size: 1.1 MiB After Width: | Height: | Size: 5.9 MiB |
Binary file not shown.
|
Before Width: | Height: | Size: 3.1 MiB After Width: | Height: | Size: 13 MiB |
@@ -2,13 +2,14 @@ from mesa import Agent
|
||||
|
||||
|
||||
class ProductAgent(Agent):
|
||||
def __init__(self, unique_id, model, name, type2, j_comp_data_consumed, j_comp_data_produced):
|
||||
def __init__(self, unique_id, model, name, type2, production_ratio):
|
||||
# 调用超类的 __init__ 方法
|
||||
super().__init__(unique_id, model)
|
||||
|
||||
# 初始化代理属性
|
||||
self.name = name
|
||||
self.product_network = self.model.product_network
|
||||
self.production_ratio = production_ratio
|
||||
if type2 == 0:
|
||||
self.is_equip = True
|
||||
else:
|
||||
@@ -16,9 +17,6 @@ class ProductAgent(Agent):
|
||||
# depreciation ratio 折旧比值
|
||||
# self.depreciation ratio
|
||||
|
||||
self.j_comp_data_produced = j_comp_data_produced
|
||||
self.j_comp_data_consumed = j_comp_data_consumed
|
||||
|
||||
def a_successors(self):
|
||||
# 从 product_network 中找到当前代理的后继节点
|
||||
successors = list(self.model.product_network.successors(self.unique_id))
|
||||
|
||||
@@ -1,5 +1,5 @@
|
||||
agentpy==0.1.5
|
||||
matplotlib==3.3.4
|
||||
matplotlib==3.7.5
|
||||
matplotlib-inline==0.1.6
|
||||
networkx==2.5
|
||||
numpy==1.20.3
|
||||
|
||||
@@ -13,8 +13,7 @@ count_dcp = pd.read_csv("output_result/risk/count_dcp.csv",
|
||||
'up_id_firm': str,
|
||||
'down_id_firm': str
|
||||
})
|
||||
# print(count_dcp)
|
||||
count_dcp = count_dcp[count_dcp['count'] > 35]
|
||||
count_dcp = count_dcp[count_dcp['count'] > 130]
|
||||
|
||||
list_firm = count_dcp['up_id_firm'].tolist(
|
||||
) + count_dcp['down_id_firm'].tolist()
|
||||
@@ -24,7 +23,7 @@ list_firm = list(set(list_firm))
|
||||
Firm = pd.read_csv("input_data/input_firm_data/Firm_amended.csv")
|
||||
Firm['Code'] = Firm['Code'].astype('string')
|
||||
Firm.fillna(0, inplace=True)
|
||||
Firm_attr = Firm.loc[:, ["Code", "Type_Region", "Revenue_Log"]]
|
||||
Firm_attr = Firm.loc[:, ["Code", "企业名称", "Type_Region", "Revenue_Log"]]
|
||||
firm_industry_relation = pd.read_csv("input_data/firm_industry_relation.csv")
|
||||
firm_industry_relation['Firm_Code'] = firm_industry_relation['Firm_Code'].astype('string')
|
||||
firm_product = []
|
||||
@@ -43,7 +42,7 @@ nx.set_node_attributes(G_firm, firm_labels_dict)
|
||||
|
||||
count_max = count_dcp['count'].max()
|
||||
count_min = count_dcp['count'].min()
|
||||
k = 5 / (count_max - count_min)
|
||||
k = 15 / (count_max - count_min)
|
||||
for _, row in count_dcp.iterrows():
|
||||
# print(row)
|
||||
lst_add_edge = [(
|
||||
@@ -54,20 +53,43 @@ for _, row in count_dcp.iterrows():
|
||||
'down_id_product': row['down_id_product'],
|
||||
'edge_label': f"{row['up_id_product']} - {row['down_id_product']}",
|
||||
'edge_width': k * (row['count'] - count_min),
|
||||
'count': row['count']
|
||||
'count': (row['count'])*18
|
||||
})]
|
||||
G_firm.add_edges_from(lst_add_edge)
|
||||
|
||||
# dcp_networkx
|
||||
pos = nx.nx_agraph.graphviz_layout(G_firm, prog="dot", args="")
|
||||
node_label = nx.get_node_attributes(G_firm, 'Revenue_Log')
|
||||
pos = nx.nx_agraph.graphviz_layout(G_firm, prog="twopi", args="")
|
||||
node_label = nx.get_node_attributes(G_firm, '企业名称')
|
||||
# desensitize
|
||||
node_label = {key: f"{key} " for key, value in node_label.items()}
|
||||
node_label = {
|
||||
key: key
|
||||
for key in node_label.keys()
|
||||
'343012684': '59',
|
||||
'2944892892': '165',
|
||||
'3269039233': '194',
|
||||
'503176785': '73',
|
||||
'3111033905': '178',
|
||||
'3215814536': '190',
|
||||
'413274977': '64',
|
||||
'2317841563': '131',
|
||||
'2354145351': '157',
|
||||
'653528340': '88',
|
||||
'888395016': '104',
|
||||
'3069206426': '174',
|
||||
'3299144127': '197',
|
||||
'2624175': '8',
|
||||
'25685135': '24',
|
||||
'2348941764': '151',
|
||||
'750610681': '95',
|
||||
'2320475044': '133',
|
||||
'571058167': '78',
|
||||
'152008168': '44',
|
||||
'448033045': '66',
|
||||
'2321109759': '134',
|
||||
'3445928818': '213'
|
||||
}
|
||||
|
||||
node_size = list(nx.get_node_attributes(G_firm, 'Revenue_Log').values())
|
||||
node_size = list(map(lambda x: x**2, node_size))
|
||||
node_size = list(map(lambda x: x * 10, node_size))
|
||||
edge_label = nx.get_edge_attributes(G_firm, "edge_label")
|
||||
edge_label = {(n1, n2): label for (n1, n2, _), label in edge_label.items()}
|
||||
edge_width = nx.get_edge_attributes(G_firm, "edge_width")
|
||||
@@ -77,23 +99,30 @@ colors = [w for (n1, n2, _), w in colors.items()]
|
||||
vmin = min(colors)
|
||||
vmax = max(colors)
|
||||
cmap = plt.cm.Blues
|
||||
fig = plt.figure(figsize=(10, 8), dpi=300)
|
||||
fig = plt.figure(figsize=(10, 8), dpi=500)
|
||||
nx.draw(G_firm,
|
||||
pos,
|
||||
node_size=node_size,
|
||||
labels=node_label,
|
||||
font_size=8,
|
||||
width=3,
|
||||
width=2,
|
||||
edge_color=colors,
|
||||
edge_cmap=cmap,
|
||||
edge_vmin=vmin,
|
||||
edge_vmax=vmax)
|
||||
nx.draw_networkx_edge_labels(G_firm, pos, edge_label, font_size=6)
|
||||
# nx.draw_networkx_edge_labels(G_firm, pos, font_size=6)
|
||||
nx.draw_networkx_edge_labels(
|
||||
G_firm,
|
||||
pos,
|
||||
edge_labels=edge_label,
|
||||
font_size=5
|
||||
)
|
||||
|
||||
sm = plt.cm.ScalarMappable(cmap=cmap, norm=plt.Normalize(vmin=vmin, vmax=vmax))
|
||||
sm._A = []
|
||||
position = fig.add_axes([0.95, 0.05, 0.01, 0.3])
|
||||
cb = plt.colorbar(sm, fraction=0.01, cax=position)
|
||||
cb.ax.tick_params(labelsize=10)
|
||||
cb.ax.tick_params(labelsize=4)
|
||||
cb.outline.set_visible(False)
|
||||
plt.savefig("output_result\\risk\\count_dcp_network")
|
||||
plt.close()
|
||||
|
||||
@@ -11,53 +11,82 @@ print(count_prod)
|
||||
print(count_prod.describe())
|
||||
|
||||
# prod_networkx
|
||||
BomNodes = pd.read_csv('input_data/input_product_data/BomNodes.csv', index_col=0)
|
||||
BomNodes.set_index('Code', inplace=True)
|
||||
BomCateNet = pd.read_csv('input_data/input_product_data/BomCateNet.csv', index_col=0)
|
||||
BomCateNet.fillna(0, inplace=True)
|
||||
# BomNodes = pd.read_csv('input_data/input_product_data/BomNodes.csv', index_col=0)
|
||||
# BomNodes.set_index('Code', inplace=True)
|
||||
# BomCateNet = pd.read_csv('input_data/input_product_data/BomCateNet.csv', index_col=0)
|
||||
# BomCateNet.fillna(0, inplace=True)
|
||||
|
||||
G = nx.from_pandas_adjacency(BomCateNet.T, create_using=nx.MultiDiGraph())
|
||||
bom_nodes = pd.read_csv('input_data/input_product_data/BomNodes.csv')
|
||||
bom_nodes['Code'] = bom_nodes['Code'].astype(str)
|
||||
bom_nodes.set_index('Index', inplace=True)
|
||||
|
||||
bom_cate_net = pd.read_csv('input_data/input_product_data/合成结点.csv')
|
||||
g_bom = nx.from_pandas_edgelist(bom_cate_net, source='UPID', target='ID', create_using=nx.MultiDiGraph())
|
||||
|
||||
labels_dict = {}
|
||||
for code in G.nodes:
|
||||
node_attr = BomNodes.loc[code].to_dict()
|
||||
for code in g_bom.nodes:
|
||||
node_attr = bom_nodes.loc[code].to_dict()
|
||||
index_list = count_prod[count_prod['id_product'] == code].index.tolist()
|
||||
index = index_list[0] if len(index_list) == 1 else -1
|
||||
node_attr['count'] = count_prod['count'].get(index, 0)
|
||||
node_attr['node_size'] = count_prod['count'].get(index, 0)
|
||||
node_attr['node_size'] = (count_prod['count'].get(index, 0))/10
|
||||
node_attr['node_color'] = count_prod['count'].get(index, 0)
|
||||
labels_dict[code] = node_attr
|
||||
nx.set_node_attributes(G, labels_dict)
|
||||
nx.set_node_attributes(g_bom, labels_dict)
|
||||
# print(labels_dict)
|
||||
|
||||
pos = nx.nx_agraph.graphviz_layout(G, prog="twopi", args="")
|
||||
dict_node_name = nx.get_node_attributes(G, 'Name')
|
||||
pos = nx.nx_agraph.graphviz_layout(g_bom, prog="twopi", args="")
|
||||
dict_node_name = nx.get_node_attributes(g_bom, 'Name')
|
||||
node_labels = {}
|
||||
for node in nx.nodes(G):
|
||||
for node in nx.nodes(g_bom):
|
||||
node_labels[node] = f"{node} {str(dict_node_name[node])}"
|
||||
# node_labels[node] = f"{str(dict_node_name[node])}"
|
||||
colors = list(nx.get_node_attributes(G, 'node_color').values())
|
||||
colors = list(nx.get_node_attributes(g_bom, 'node_color').values())
|
||||
vmin = min(colors)
|
||||
vmax = max(colors)
|
||||
cmap = plt.cm.Blues
|
||||
# 创建绘图对象
|
||||
fig = plt.figure(figsize=(10, 10), dpi=300)
|
||||
nx.draw(G,
|
||||
pos,
|
||||
node_size=list(nx.get_node_attributes(G, 'node_size').values()),
|
||||
ax = fig.add_subplot(111)
|
||||
|
||||
# 绘制网络图（优化样式参数）
|
||||
nx.draw(g_bom, pos,
|
||||
node_size=list(nx.get_node_attributes(g_bom, 'node_size').values()),
|
||||
labels=node_labels,
|
||||
font_size=6,
|
||||
font_size=3,
|
||||
node_color=colors,
|
||||
cmap=cmap,
|
||||
vmin=vmin,
|
||||
vmax=vmax,
|
||||
edge_color='grey')
|
||||
edge_color='#808080', # 中性灰
|
||||
width=0.3,
|
||||
edgecolors='#404040',
|
||||
linewidths=0.2)
|
||||
|
||||
# 创建颜色条（修正实现方式）
|
||||
sm = plt.cm.ScalarMappable(cmap=cmap, norm=plt.Normalize(vmin=vmin, vmax=vmax))
|
||||
sm._A = []
|
||||
position = fig.add_axes([0.01, 0.05, 0.01, 0.3])
|
||||
cb = plt.colorbar(sm, fraction=0.01, cax=position)
|
||||
cb.ax.tick_params(labelsize=8)
|
||||
cb.outline.set_visible(False)
|
||||
plt.savefig("output_result\\risk\\count_prod_network")
|
||||
sm.set_array([])
|
||||
|
||||
# 设置颜色条位置和样式
|
||||
cax = fig.add_axes([0.88, 0.3, 0.015, 0.4]) # 右侧垂直对齐
|
||||
cb = plt.colorbar(sm, cax=cax)
|
||||
cb.ax.tick_params(labelsize=4, width=0.5, colors='#333333')
|
||||
cb.outline.set_linewidth(0.5)
|
||||
cb.set_label('Risk Level', fontsize=5, labelpad=2)
|
||||
|
||||
# 添加图元信息
|
||||
ax.set_title("Production Risk Network", fontsize=6, pad=8, color='#2F2F2F')
|
||||
plt.text(0.5, 0.02, 'Data: USTB Production System | Viz: DeepSeek-R1',
|
||||
ha='center', fontsize=3, color='#666666',
|
||||
transform=fig.transFigure)
|
||||
|
||||
# 调整边界和保存
|
||||
plt.subplots_adjust(left=0.05, right=0.85, top=0.95, bottom=0.1) # 适应颜色条
|
||||
plt.savefig(r"output_result/risk/count_prod_network.png", # 规范路径格式
|
||||
dpi=600,
|
||||
bbox_inches='tight',
|
||||
pad_inches=0.05,
|
||||
transparent=False)
|
||||
plt.close()
|
||||
|
||||
# dcp_prod
|
||||
@@ -74,7 +103,7 @@ count_dcp_prod.sort_values('count', inplace=True, ascending=False)
|
||||
count_dcp_prod.to_csv('output_result\\risk\\count_dcp_prod.csv',
|
||||
index=False,
|
||||
encoding='utf-8-sig')
|
||||
count_dcp_prod = count_dcp_prod[count_dcp_prod['count'] > 50]
|
||||
count_dcp_prod = count_dcp_prod[count_dcp_prod['count'] > 1000]
|
||||
# print(count_dcp_prod)
|
||||
|
||||
list_prod = count_dcp_prod['up_id_product'].tolist(
|
||||
@@ -83,8 +112,8 @@ list_prod = list(set(list_prod))
|
||||
|
||||
# init graph bom
|
||||
|
||||
BomNodes = pd.read_csv('input_data/input_product_data/BomNodes.csv', index_col=0)
|
||||
BomNodes.set_index('Code', inplace=True)
|
||||
BomNodes = pd.read_csv('input_data/input_product_data/BomNodes.csv')
|
||||
BomNodes.set_index('Index', inplace=True)
|
||||
|
||||
g_bom = nx.MultiDiGraph()
|
||||
g_bom.add_nodes_from(list_prod)
|
||||
@@ -95,7 +124,6 @@ for code in list_prod:
|
||||
bom_labels_dict[code] = dct_attr
|
||||
nx.set_node_attributes(g_bom, bom_labels_dict)
|
||||
|
||||
|
||||
count_max = count_dcp_prod['count'].max()
|
||||
count_min = count_dcp_prod['count'].min()
|
||||
k = 5 / (count_max - count_min)
|
||||
@@ -110,28 +138,55 @@ for _, row in count_dcp_prod.iterrows():
|
||||
g_bom.add_edges_from(lst_add_edge)
|
||||
|
||||
# dcp_networkx
|
||||
pos = nx.nx_agraph.graphviz_layout(g_bom, prog="dot", args="")
|
||||
pos = nx.nx_agraph.graphviz_layout(g_bom, prog="twopi", args="")
|
||||
node_labels = nx.get_node_attributes(g_bom, 'Name')
|
||||
# rename node 1
|
||||
# node_labels['1'] = '解决方案'
|
||||
|
||||
temp = {}
|
||||
for key, value in node_labels.items():
|
||||
temp[key] = key + " " + value
|
||||
temp[key] = str(key) + " " + value
|
||||
node_labels = temp
|
||||
node_labels ={
|
||||
38: 'SiC Substrate',
|
||||
39: 'GaN Substrate',
|
||||
40: 'Si Substrate',
|
||||
41: 'AlN Substrate',
|
||||
42: 'DUV LED Substrate',
|
||||
43: 'InP Substrate',
|
||||
44: 'Mono-Si Wafer',
|
||||
45: 'Poly-Si Wafer',
|
||||
46: 'InP Cryst./Wafer',
|
||||
47: 'SiC Cryst./Wafer',
|
||||
48: 'GaAs Wafer',
|
||||
49: 'GaN Cryst./Wafer',
|
||||
50: 'Si Epi Wafer',
|
||||
51: 'SiC Epi Wafer',
|
||||
52: 'AlN Epi',
|
||||
53: 'GaN Epi',
|
||||
54: 'InP Epi',
|
||||
55: 'LED Epi Wafer',
|
||||
90: 'Power Devices',
|
||||
91: 'Diode',
|
||||
92: 'Transistor',
|
||||
93: 'Thyristor',
|
||||
94: 'Rectifier',
|
||||
95: 'IC Fab',
|
||||
99: 'Wafer Test'
|
||||
}
|
||||
colors = nx.get_edge_attributes(g_bom, "count")
|
||||
colors = [w for (n1, n2, _), w in colors.items()]
|
||||
vmin = min(colors)
|
||||
vmax = max(colors)
|
||||
cmap = plt.cm.Blues
|
||||
|
||||
pos_new = {}
|
||||
for node, p in pos.items():
|
||||
pos_new[node] = (p[1], p[0])
|
||||
pos_new = {node: (p[1], p[0]) for node, p in pos.items()} # 字典推导式优化
|
||||
|
||||
fig = plt.figure(figsize=(6, 10), dpi=300)
|
||||
# plt.subplots_adjust(right=0.7)
|
||||
nx.draw(g_bom,
|
||||
pos_new,
|
||||
fig = plt.figure(figsize=(8, 8), dpi=300)
|
||||
plt.subplots_adjust(right=0.85) # 关键调整：右侧保留15%空白
|
||||
|
||||
# 使用Axes对象精准控制
|
||||
main_ax = fig.add_axes([0.1, 0.1, 0.75, 0.8]) # 主图占左75%宽，上下各留10%边距
|
||||
nx.draw(g_bom, pos_new,
|
||||
ax=main_ax,
|
||||
node_size=50,
|
||||
labels=node_labels,
|
||||
font_size=5,
|
||||
@@ -139,17 +194,30 @@ nx.draw(g_bom,
|
||||
edge_color=colors,
|
||||
edge_cmap=cmap,
|
||||
edge_vmin=vmin,
|
||||
edge_vmax=vmax)
|
||||
plt.axis('off')
|
||||
axis = plt.gca()
|
||||
axis.set_xlim([1.2*x for x in axis.get_xlim()])
|
||||
axis.set_ylim([1.2*y for y in axis.get_ylim()])
|
||||
edge_vmax=vmax,
|
||||
)
|
||||
main_ax.axis('off')
|
||||
|
||||
# 颜色条定位系统
|
||||
cbar_ax = fig.add_axes([0.86, 0.15, 0.015, 0.3]) # 右边缘86%位置，底部15%起，占30%高度
|
||||
sm = plt.cm.ScalarMappable(cmap=cmap, norm=plt.Normalize(vmin=vmin, vmax=vmax))
|
||||
sm._A = []
|
||||
position = fig.add_axes([0.75, 0.1, 0.01, 0.2])
|
||||
cb = plt.colorbar(sm, fraction=0.01, cax=position)
|
||||
cb.ax.tick_params(labelsize=8)
|
||||
cb.outline.set_visible(False)
|
||||
plt.savefig("output_result\\risk\\count_dcp_prod_network")
|
||||
sm._A = [] # 必需的空数组
|
||||
|
||||
# 微调颜色条样式
|
||||
cbar = fig.colorbar(sm, cax=cbar_ax, orientation='vertical')
|
||||
cbar.ax.tick_params(labelsize=4,
|
||||
width=0.3, # 刻度线粗细
|
||||
length=1.5, # 刻度线长度
|
||||
pad=0.8) # 标签与条间距
|
||||
cbar.outline.set_linewidth(0.5) # 边框线宽
|
||||
|
||||
# 输出前验证边界
|
||||
print(f"Colorbar position: {cbar_ax.get_position().bounds}") # 应输出(0.86,0.15,0.015,0.3)
|
||||
|
||||
# 专业级保存参数
|
||||
plt.savefig("output_result/risk/count_dcp_prod_network.png",
|
||||
dpi=900,
|
||||
bbox_inches='tight', # 自动裁剪白边
|
||||
pad_inches=0.05, # 保留0.05英寸边距
|
||||
metadata={'CreationDate': None}) # 避免时间戳污染元数据
|
||||
plt.close()
|
||||
|
||||
@@ -1,3 +1,5 @@
|
||||
import pickle
|
||||
|
||||
from sqlalchemy import text
|
||||
from orm import engine, connection
|
||||
import pandas as pd
|
||||
@@ -5,107 +7,450 @@ import networkx as nx
|
||||
import json
|
||||
import matplotlib.pyplot as plt
|
||||
|
||||
# prep data
|
||||
# Prepare data
|
||||
Firm = pd.read_csv("input_data/input_firm_data/Firm_amended.csv")
|
||||
Firm['Code'] = Firm['Code'].astype('string')
|
||||
Firm.fillna(0, inplace=True)
|
||||
BomNodes = pd.read_csv('input_data/input_product_data/BomNodes.csv', index_col=0)
|
||||
|
||||
# SQL query
|
||||
with open('SQL_analysis_risk.sql', 'r') as f:
|
||||
str_sql = text(f.read())
|
||||
|
||||
result = pd.read_sql(sql=str_sql,
|
||||
con=connection)
|
||||
result.to_csv('output_result\\risk\\count.csv',
|
||||
index=False,
|
||||
encoding='utf-8-sig')
|
||||
result = pd.read_sql(sql=str_sql, con=connection)
|
||||
result.to_csv('output_result/risk/count.csv', index=False, encoding='utf-8-sig')
|
||||
print(result)
|
||||
|
||||
# G bom
|
||||
# G_bom
|
||||
plt.rcParams['font.sans-serif'] = 'SimHei'
|
||||
|
||||
exp_id = 1
|
||||
G_bom_str = pd.read_sql(
|
||||
sql=text(f'select g_bom from iiabmdb.without_exp_experiment '
|
||||
f'where id = {exp_id};'),
|
||||
con=connection)['g_bom'].tolist()[0]
|
||||
G_bom_df = pd.read_sql(
|
||||
sql=text(f'select g_bom from iiabmdb.without_exp_experiment where id = {exp_id};'),
|
||||
con=connection
|
||||
)
|
||||
|
||||
if G_bom_df.empty:
|
||||
raise ValueError(f"No g_bom found for exp_id = {exp_id}")
|
||||
|
||||
G_bom_str = G_bom_df['g_bom'].tolist()[0]
|
||||
if G_bom_str is None:
|
||||
raise ValueError(f"g_bom data is None for exp_id = {exp_id}")
|
||||
|
||||
G_bom = nx.adjacency_graph(json.loads(G_bom_str))
|
||||
pos = nx.nx_agraph.graphviz_layout(G_bom, prog="twopi", args="")
|
||||
node_labels = nx.get_node_attributes(G_bom, 'Name')
|
||||
# rename node 1
|
||||
# node_labels['1'] = '工业互联网'
|
||||
# node_labels['1.1'] = '工业自动化硬件'
|
||||
# node_labels['1.4'] = '工业互联网安全管理'
|
||||
# node_labels['1.2.1'] = '网络互联服务'
|
||||
# node_labels['1.2.2'] = '标识解析服务'
|
||||
# node_labels['1.2.3'] = '数据互通服务'
|
||||
# node_labels['1.3.1'] = '设计研发软件'
|
||||
# node_labels['1.3.2'] = '采购供应软件'
|
||||
# node_labels['1.3.3'] = '生产制造软件'
|
||||
# node_labels['1.3.4'] = '企业运营软件'
|
||||
# node_labels['1.3.5'] = '仓储物流软件'
|
||||
plt.figure(figsize=(12, 12), dpi=300)
|
||||
nx.draw_networkx_nodes(G_bom, pos)
|
||||
nx.draw_networkx_edges(G_bom, pos)
|
||||
nx.draw_networkx_labels(G_bom, pos, labels=node_labels, font_size=6)
|
||||
# plt.show()
|
||||
plt.savefig(f"output_result\\risk\\g_bom_exp_id_{exp_id}.png")
|
||||
node_labels = {
|
||||
7: 'Si Raw Mtl.',
|
||||
8: 'Photoresist & Reagents',
|
||||
9: 'Etch Solution',
|
||||
10: 'SiF4',
|
||||
11: 'Developer',
|
||||
12: 'PCE Superplasticizer',
|
||||
13: 'Metal Protectant',
|
||||
14: 'Deep Hole Cu Plating',
|
||||
15: 'Thinner',
|
||||
16: 'HP Boric Acid (Nuc.)',
|
||||
17: 'E-Grade Epoxy',
|
||||
18: 'Stripper',
|
||||
19: 'HP-MOC',
|
||||
20: 'CMP Slurry & Consumables',
|
||||
21: 'PR Remover',
|
||||
22: 'Poly-Si Cutting Fluid',
|
||||
23: 'Passivation',
|
||||
24: 'E-Grade Phenolic',
|
||||
25: 'Surfactant',
|
||||
26: 'Mag. Carrier',
|
||||
27: 'Wet Chems.',
|
||||
28: 'Plating Chems.',
|
||||
29: 'E-FR Materials',
|
||||
30: 'LC Alignment Agent',
|
||||
31: 'Func. Wet Chems.',
|
||||
32: 'InP',
|
||||
33: 'SiC',
|
||||
34: 'GaAs',
|
||||
35: 'GaN',
|
||||
36: 'AlN',
|
||||
37: 'Si3N4',
|
||||
38: 'SiC Substrate',
|
||||
39: 'GaN Substrate',
|
||||
40: 'Si Wafer',
|
||||
41: 'AlN Substrate',
|
||||
42: 'DUV LED Substrate',
|
||||
43: 'InP Substrate',
|
||||
44: 'Mono-Si Wafer',
|
||||
45: 'Poly-Si Wafer',
|
||||
46: 'InP Cryst./Wafer',
|
||||
47: 'SiC Cryst./Wafer',
|
||||
48: 'GaAs Wafer',
|
||||
49: 'GaN Cryst./Wafer',
|
||||
50: 'Si Epi Wafer',
|
||||
51: 'SiC Epi Wafer',
|
||||
52: 'AlN Epi',
|
||||
53: 'GaN Epi',
|
||||
54: 'InP Epi',
|
||||
55: 'LED Epi',
|
||||
56: 'EDA/IP',
|
||||
57: 'MPW Service',
|
||||
58: 'IC Design',
|
||||
59: 'Track System',
|
||||
60: 'Wafer Grinder',
|
||||
61: 'Etcher',
|
||||
62: 'Ox/Diff Furnace',
|
||||
63: 'Wafer Metrology',
|
||||
64: 'Crystal Grower',
|
||||
65: 'CMP Tool',
|
||||
66: 'Stepper',
|
||||
67: 'Wafer Dicer',
|
||||
68: 'Deposition System',
|
||||
69: 'Edge Profiler',
|
||||
70: 'Descum Tool',
|
||||
71: 'Clean System',
|
||||
72: 'SAF',
|
||||
73: 'Plating Eqpt.',
|
||||
74: 'Implanter',
|
||||
75: 'Trim/Form',
|
||||
76: 'Probe Card',
|
||||
77: 'ATE',
|
||||
78: 'PCM Eqpt.',
|
||||
79: 'Inspection Sys.',
|
||||
80: 'Prober',
|
||||
81: 'Dicing Saw',
|
||||
82: 'Handler',
|
||||
83: 'Backgrinder',
|
||||
84: 'Die Bonder',
|
||||
85: 'Reflow Oven',
|
||||
86: 'FT Tester',
|
||||
87: 'Wire Bonder',
|
||||
88: 'BGA Mounter',
|
||||
89: 'Molding Press',
|
||||
90: 'Power Devices',
|
||||
91: 'Diode',
|
||||
92: 'Transistor',
|
||||
93: 'Thyristor',
|
||||
94: 'Rectifier',
|
||||
95: 'IC Fab',
|
||||
96: 'IC PKG',
|
||||
97: 'DV',
|
||||
98: 'IPM',
|
||||
99: 'CP Test',
|
||||
100: 'FT Test',
|
||||
101: 'Bumping',
|
||||
102: 'DA Materials',
|
||||
103: 'Leadframe',
|
||||
104: 'Solder Ball',
|
||||
105: 'Substrate',
|
||||
106: 'EMC',
|
||||
107: 'Bond Wire',
|
||||
108: 'Underfill',
|
||||
109: 'Dicing Tape'
|
||||
}
|
||||
plt.figure(figsize=(12, 12), dpi=500)
|
||||
plt.axis('off') # 关闭坐标轴边框
|
||||
|
||||
# 优化节点绘制参数
|
||||
nx.draw_networkx_nodes(
|
||||
G_bom, pos,
|
||||
node_size=100, # 优化节点尺寸
|
||||
linewidths=0.0 # 去除节点边框
|
||||
)
|
||||
# 优化边绘制参数
|
||||
nx.draw_networkx_edges(
|
||||
G_bom, pos,
|
||||
width=0.3, # 更细的边宽
|
||||
alpha=0.5 # 半透明边
|
||||
)
|
||||
# 优化标签参数
|
||||
nx.draw_networkx_labels(
|
||||
G_bom, pos,
|
||||
labels=node_labels,
|
||||
font_size=3, # 适当增大字号
|
||||
font_family='sans-serif', # 使用无衬线字体
|
||||
font_weight='bold', # 增强可读性
|
||||
)
|
||||
|
||||
# 专业级保存参数设置
|
||||
plt.savefig(
|
||||
f"output_result/risk/g_bom_exp_id_{exp_id}.png",
|
||||
bbox_inches='tight', # 去除图像白边
|
||||
pad_inches=0.1, # 适当内边距
|
||||
facecolor='white' # 保证背景纯白
|
||||
)
|
||||
plt.close()
|
||||
|
||||
# G firm
|
||||
# G_firm
|
||||
plt.rcParams['font.sans-serif'] = 'SimHei'
|
||||
|
||||
sample_id = 1
|
||||
# G_firm_df = pd.read_sql(
|
||||
# sql=text(f'select g_firm from iiabmdb.without_exp_sample where id = {sample_id};'),
|
||||
# con=connection
|
||||
# )
|
||||
#
|
||||
# if G_firm_df.empty:
|
||||
# raise ValueError(f"No g_firm found for sample_id = {sample_id}")
|
||||
#
|
||||
# G_firm_str = G_firm_df['g_firm'].tolist()[0]
|
||||
# if G_firm_str is None:
|
||||
# raise ValueError(f"g_firm data is None for sample_id = {sample_id}")
|
||||
#
|
||||
# G_firm = nx.adjacency_graph(json.loads(G_firm_str))
|
||||
|
||||
G_firm_str = pd.read_sql(
|
||||
sql=text(f'select g_firm from iiabmdb.without_exp_sample '
|
||||
f'where id = {exp_id};'),
|
||||
con=connection)['g_firm'].tolist()[0]
|
||||
with open("firm_network.pkl", 'rb') as f:
|
||||
G_firm = pickle.load(f)
|
||||
print(f"Successfully loaded cached data from firm_network.pkl")
|
||||
|
||||
G_firm = nx.adjacency_graph(json.loads(G_firm_str))
|
||||
# 1. 移除孤立节点
|
||||
isolated_nodes = list(nx.isolates(G_firm)) # 找出所有没有连接的孤立节点
|
||||
G_firm.remove_nodes_from(isolated_nodes) # 从图中移除这些节点
|
||||
|
||||
# 2. 重新布局和绘图
|
||||
pos = nx.nx_agraph.graphviz_layout(G_firm, prog="twopi", args="")
|
||||
# desensitize
|
||||
node_label = nx.get_node_attributes(G_firm, 'Revenue_Log')
|
||||
node_label = {key: key for key in nx.get_node_attributes(G_firm, 'Revenue_Log').keys()}
|
||||
node_label = {
|
||||
key: key
|
||||
for key in node_label.keys()
|
||||
"7": "1",
|
||||
"9": "2",
|
||||
"829768": "4",
|
||||
"863079": "5",
|
||||
"1452048": "6",
|
||||
"2010673": "7",
|
||||
"2624175": "8",
|
||||
"2728939": "9",
|
||||
"5278074": "10",
|
||||
"5849940": "11",
|
||||
"7299120": "12",
|
||||
"9746245": "13",
|
||||
"11807506": "14",
|
||||
"15613202": "15",
|
||||
"24284343": "19",
|
||||
"24673506": "20",
|
||||
"25036634": "21",
|
||||
"25685135": "24",
|
||||
"25945288": "25",
|
||||
"26162741": "26",
|
||||
"26516263": "27",
|
||||
"27075840": "28",
|
||||
"27731896": "29",
|
||||
"29954548": "30",
|
||||
"43407343": "33",
|
||||
"70634828": "36",
|
||||
"71271700": "37",
|
||||
"80158773": "39",
|
||||
"118882692": "40",
|
||||
"145511905": "42",
|
||||
"151606446": "43",
|
||||
"152008168": "44",
|
||||
"159511306": "45",
|
||||
"191912252": "46",
|
||||
"194210021": "47",
|
||||
"203314437": "48",
|
||||
"213386023": "49",
|
||||
"218633337": "50",
|
||||
"251189644": "53",
|
||||
"271860868": "55",
|
||||
"278221281": "56",
|
||||
"301209792": "57",
|
||||
"343012684": "59",
|
||||
"354897041": "60",
|
||||
"400488703": "62",
|
||||
"400692942": "63",
|
||||
"413274977": "64",
|
||||
"420984285": "65",
|
||||
"448033045": "66",
|
||||
"453289520": "67",
|
||||
"474279224": "68",
|
||||
"483081978": "69",
|
||||
"495782506": "70",
|
||||
"503176785": "73",
|
||||
"549184982": "75",
|
||||
"560866402": "76",
|
||||
"561545339": "77",
|
||||
"571058167": "78",
|
||||
"581407487": "79",
|
||||
"591452402": "80",
|
||||
"593312758": "81",
|
||||
"594378026": "82",
|
||||
"607512171": "83",
|
||||
"615763365": "84",
|
||||
"620220747": "85",
|
||||
"631449822": "86",
|
||||
"644292599": "87",
|
||||
"653528340": "88",
|
||||
"654825436": "89",
|
||||
"688155470": "92",
|
||||
"695995052": "93",
|
||||
"750610681": "95",
|
||||
"762985858": "96",
|
||||
"771821595": "97",
|
||||
"857978527": "100",
|
||||
"868012326": "101",
|
||||
"887840774": "102",
|
||||
"888356483": "103",
|
||||
"888395016": "104",
|
||||
"888478182": "105",
|
||||
"930767828": "107",
|
||||
"996174506": "108",
|
||||
"1033972427": "110",
|
||||
"1128343125": "111",
|
||||
"1217957486": "113",
|
||||
"1307012237": "115",
|
||||
"1375606900": "116",
|
||||
"1549474227": "118",
|
||||
"1606833003": "120",
|
||||
"1679596339": "121",
|
||||
"2310825263": "122",
|
||||
"2311838590": "124",
|
||||
"2312490120": "125",
|
||||
"2316990095": "128",
|
||||
"2317245827": "129",
|
||||
"2317841563": "131",
|
||||
"2320102626": "132",
|
||||
"2320475044": "133",
|
||||
"2321109759": "134",
|
||||
"2324787028": "137",
|
||||
"2324844174": "138",
|
||||
"2326478786": "139",
|
||||
"2327031723": "140",
|
||||
"2327979389": "141",
|
||||
"2329375731": "142",
|
||||
"2333843479": "143",
|
||||
"2337952436": "146",
|
||||
"2339188563": "147",
|
||||
"2339684065": "148",
|
||||
"2341555098": "149",
|
||||
"2343704209": "150",
|
||||
"2348941764": "151",
|
||||
"2352036411": "155",
|
||||
"2354145351": "157",
|
||||
"2424229017": "159",
|
||||
"2545430247": "161",
|
||||
"2820140348": "163",
|
||||
"2944892892": "165",
|
||||
"3025036704": "168",
|
||||
"3026382513": "169",
|
||||
"3045721313": "171",
|
||||
"3047163873": "172",
|
||||
"3048263744": "173",
|
||||
"3069206426": "174",
|
||||
"3070859372": "175",
|
||||
"3072715478": "176",
|
||||
"3103797386": "177",
|
||||
"3111033905": "178",
|
||||
"3113895788": "179",
|
||||
"3120341363": "180",
|
||||
"3122923980": "181",
|
||||
"3127420424": "182",
|
||||
"3133307899": "183",
|
||||
"3147511625": "184",
|
||||
"3177507356": "185",
|
||||
"3188903709": "186",
|
||||
"3195502499": "187",
|
||||
"3203777710": "188",
|
||||
"3211956484": "189",
|
||||
"3215814536": "190",
|
||||
"3221190269": "191",
|
||||
"3226664625": "192",
|
||||
"3267688490": "193",
|
||||
"3269039233": "194",
|
||||
"3269940677": "195",
|
||||
"3271705843": "196",
|
||||
"3299144127": "197",
|
||||
"3312358902": "198",
|
||||
"3344297292": "200",
|
||||
"3372913783": "201",
|
||||
"3373311444": "202",
|
||||
"3384021594": "203",
|
||||
"3395900897": "205",
|
||||
"3398677646": "206",
|
||||
"3407754893": "207",
|
||||
"3433628561": "209",
|
||||
"3445244192": "212",
|
||||
"3445928818": "213",
|
||||
"4208851809": "216",
|
||||
"5007015990": "218",
|
||||
"11164476478": "219",
|
||||
"517717050": "223",
|
||||
"737770776": "224",
|
||||
"872394725": "225",
|
||||
"2311581270": "226",
|
||||
"2313209417": "227",
|
||||
"2347013470": "228",
|
||||
"2350418059": "229",
|
||||
"3031009366": "234",
|
||||
"3089095447": "235",
|
||||
"3100891962": "236",
|
||||
"3188352290": "238",
|
||||
"3288105727": "239",
|
||||
"3462551351": "240"
|
||||
}
|
||||
node_size = list(nx.get_node_attributes(G_firm, 'Revenue_Log').values())
|
||||
node_size = list(map(lambda x: x**2, node_size))
|
||||
edge_label = nx.get_edge_attributes(G_firm, "Product")
|
||||
edge_label = {(n1, n2): label for (n1, n2, _), label in edge_label.items()}
|
||||
plt.figure(figsize=(12, 12), dpi=300)
|
||||
nx.draw(G_firm, pos, node_size=node_size, labels=node_label, font_size=6)
|
||||
nx.draw_networkx_edge_labels(G_firm, pos, edge_label, font_size=4)
|
||||
# plt.show()
|
||||
plt.savefig(f"output_result\\risk\\g_firm_sample_id_{exp_id}_de.png")
|
||||
|
||||
node_size = [value * 5 for value in nx.get_node_attributes(G_firm, 'Revenue_Log').values()]
|
||||
edge_label = {(n1, n2): label for (n1, n2, _), label in nx.get_edge_attributes(G_firm, "Product").items()}
|
||||
|
||||
plt.figure(figsize=(15, 15), dpi=500)
|
||||
plt.axis('off') # 完全关闭坐标轴系统
|
||||
|
||||
# 分层绘制网络组件
|
||||
nodes = nx.draw_networkx_nodes(
|
||||
G_firm, pos,
|
||||
node_size=node_size, # 保持原始尺寸设置
|
||||
)
|
||||
|
||||
edges = nx.draw_networkx_edges(
|
||||
G_firm, pos,
|
||||
width=0.3, # 保持原始线宽设置
|
||||
)
|
||||
|
||||
# 优化节点标签
|
||||
labels = nx.draw_networkx_labels(
|
||||
G_firm, pos,
|
||||
labels=node_label,
|
||||
font_size=6, # 保持原始字号
|
||||
)
|
||||
|
||||
# 增强边标签可读性
|
||||
edge_labels = nx.draw_networkx_edge_labels(
|
||||
G_firm, pos,
|
||||
edge_labels=edge_label,
|
||||
font_size=2,
|
||||
label_pos=0.5, # 标签沿边偏移量
|
||||
rotate=False, # 禁止自动旋转
|
||||
)
|
||||
|
||||
# 专业级输出配置
|
||||
plt.savefig(
|
||||
f"output_result/risk/g_firm_sample_id_{sample_id}_de.png",
|
||||
bbox_inches='tight',
|
||||
pad_inches=0.05, # 更紧凑的边距
|
||||
facecolor='white', # 强制白色背景
|
||||
metadata={
|
||||
'Title': f"Supply Chain Risk Map - Sample {sample_id}",
|
||||
'Author': 'USTB Risk Analytics',
|
||||
'Copyright': 'Confidential'
|
||||
}
|
||||
)
|
||||
plt.close()
|
||||
|
||||
# count firm product
|
||||
|
||||
# Count firm product
|
||||
count_firm_prod = result.value_counts(subset=['id_firm', 'id_product'])
|
||||
count_firm_prod.name = 'count'
|
||||
count_firm_prod = count_firm_prod.to_frame().reset_index()
|
||||
count_firm_prod.to_csv('output_result\\risk\\count_firm_prod.csv',
|
||||
index=False,
|
||||
encoding='utf-8-sig')
|
||||
count_firm_prod.to_csv('output_result/risk/count_firm_prod.csv', index=False, encoding='utf-8-sig')
|
||||
print(count_firm_prod)
|
||||
|
||||
# count firm
|
||||
# Count firm
|
||||
count_firm = count_firm_prod.groupby('id_firm')['count'].sum()
|
||||
count_firm = count_firm.to_frame().reset_index()
|
||||
count_firm.sort_values('count', inplace=True, ascending=False)
|
||||
count_firm.to_csv('output_result\\risk\\count_firm.csv',
|
||||
index=False,
|
||||
encoding='utf-8-sig')
|
||||
count_firm.to_csv('output_result/risk/count_firm.csv', index=False, encoding='utf-8-sig')
|
||||
print(count_firm)
|
||||
|
||||
# count product
|
||||
# Count product
|
||||
count_prod = count_firm_prod.groupby('id_product')['count'].sum()
|
||||
count_prod = count_prod.to_frame().reset_index()
|
||||
count_prod.sort_values('count', inplace=True, ascending=False)
|
||||
count_prod.to_csv('output_result\\risk\\count_prod.csv',
|
||||
index=False,
|
||||
encoding='utf-8-sig')
|
||||
count_prod.to_csv('output_result/risk/count_prod.csv', index=False, encoding='utf-8-sig')
|
||||
print(count_prod)
|
||||
|
||||
# DCP disruption causing probability
|
||||
@@ -114,26 +459,33 @@ print(result_disrupt_ts_above_0)
|
||||
result_dcp = pd.DataFrame(columns=[
|
||||
's_id', 'up_id_firm', 'up_id_product', 'down_id_firm', 'down_id_product'
|
||||
])
|
||||
|
||||
result_dcp_list = [] # 用列表收集数据，避免DataFrame逐行增长的问题
|
||||
for sid, group in result.groupby('s_id'):
|
||||
ts_start = max(group['ts'])
|
||||
while ts_start >= 1:
|
||||
ts_end = ts_start - 1
|
||||
while ts_end >= 0:
|
||||
up = group.loc[group['ts'] == ts_end, ['id_firm', 'id_product']]
|
||||
down = group.loc[group['ts'] == ts_start,
|
||||
['id_firm', 'id_product']]
|
||||
down = group.loc[group['ts'] == ts_start, ['id_firm', 'id_product']]
|
||||
for _, up_row in up.iterrows():
|
||||
for _, down_row in down.iterrows():
|
||||
row = [sid]
|
||||
row += up_row.tolist()
|
||||
row += down_row.tolist()
|
||||
result_dcp.loc[len(result_dcp.index)] = row
|
||||
result_dcp_list.append([sid] + up_row.tolist() + down_row.tolist())
|
||||
ts_end -= 1
|
||||
ts_start -= 1
|
||||
|
||||
# 转换为DataFrame
|
||||
result_dcp = pd.DataFrame(result_dcp_list, columns=[
|
||||
's_id', 'up_id_firm', 'up_id_product', 'down_id_firm', 'down_id_product'
|
||||
])
|
||||
|
||||
# 统计
|
||||
count_dcp = result_dcp.value_counts(
|
||||
subset=['up_id_firm', 'up_id_product', 'down_id_firm', 'down_id_product'])
|
||||
count_dcp.name = 'count'
|
||||
count_dcp = count_dcp.to_frame().reset_index()
|
||||
count_dcp.to_csv('output_result\\risk\\count_dcp.csv',
|
||||
index=False, encoding='utf-8-sig')
|
||||
subset=['up_id_firm', 'up_id_product', 'down_id_firm', 'down_id_product']
|
||||
).reset_index(name='count')
|
||||
|
||||
# 保存文件
|
||||
count_dcp.to_csv('output_result/risk/count_dcp.csv', index=False, encoding='utf-8-sig')
|
||||
|
||||
# 输出结果
|
||||
print(count_dcp)
|
||||
|
||||
50
企业描述性数据分析.py
Normal file
50
企业描述性数据分析.py
Normal file
@@ -0,0 +1,50 @@
|
||||
import pandas as pd
|
||||
|
||||
# 读取数据
|
||||
df = pd.read_csv('input_data/input_firm_data/firm_amended.csv') # 替换为你的 CSV 文件路径
|
||||
|
||||
# 要分析的列
|
||||
columns = [
|
||||
"固定资产原值（万元人民币）",
|
||||
"固定资产净值（万元人民币）",
|
||||
"资产总和（万元人民币）",
|
||||
"存货（万元人民币）"
|
||||
]
|
||||
|
||||
# 字段类型定义（可人工定义，也可自动判断）
|
||||
column_types = {
|
||||
"固定资产原值（万元人民币）": "连续型",
|
||||
"固定资产净值（万元人民币）": "连续型",
|
||||
"资产总和（万元人民币）": "连续型",
|
||||
"存货（万元人民币）": "连续型"
|
||||
}
|
||||
|
||||
# 统计分析
|
||||
summary = []
|
||||
|
||||
for col in columns:
|
||||
data = df[col].dropna()
|
||||
summary.append({
|
||||
"字段名": col,
|
||||
"类型": column_types[col],
|
||||
"计数（非空）": data.count(),
|
||||
"均值": data.mean(),
|
||||
"标准差": data.std(),
|
||||
"最小值": data.min(),
|
||||
"中位数": data.median(),
|
||||
"最大值": data.max()
|
||||
})
|
||||
|
||||
# 转为 DataFrame 展示
|
||||
summary_df = pd.DataFrame(summary)
|
||||
|
||||
# 设置列顺序
|
||||
summary_df = summary_df[["字段名", "类型", "计数（非空）", "均值", "标准差", "最小值", "中位数", "最大值"]]
|
||||
|
||||
# 打印结果
|
||||
print(summary_df)
|
||||
# 保存为 Excel 文件
|
||||
output_path = "企业规模数据描述性统计表.xlsx"
|
||||
summary_df.to_excel(output_path, index=False)
|
||||
|
||||
print(f"统计结果已保存为 Excel 文件：{output_path}")
|
||||
BIN
企业规模数据描述性统计表.xlsx
Normal file
BIN
企业规模数据描述性统计表.xlsx
Normal file
Binary file not shown.
60
可视化测试.py
60
可视化测试.py
@@ -1,60 +0,0 @@
|
||||
import matplotlib.pyplot as plt
|
||||
from mpl_toolkits.mplot3d import Axes3D
|
||||
import numpy as np
|
||||
from matplotlib import rcParams
|
||||
|
||||
# 设置中文字体和符号显示
|
||||
rcParams['font.sans-serif'] = ['SimHei'] # 或者使用 ['Microsoft YaHei']
|
||||
rcParams['axes.unicode_minus'] = False # 用来正常显示负号
|
||||
# 定义节点和边
|
||||
nodes = {
|
||||
0: '原材料供应商',
|
||||
1: '零部件制造商',
|
||||
2: '产品制造商',
|
||||
3: '分销商',
|
||||
4: '零售商'
|
||||
}
|
||||
|
||||
edges = [
|
||||
(0, 1), # 原材料供应商 -> 零部件制造商
|
||||
(1, 2), # 零部件制造商 -> 产品制造商
|
||||
(2, 3), # 产品制造商 -> 分销商
|
||||
(3, 4) # 分销商 -> 零售商
|
||||
]
|
||||
|
||||
# 定义节点的三维坐标 (x, y, z)
|
||||
positions = {
|
||||
0: (0, 0, 0), # 原材料供应商
|
||||
1: (1, 0, 1), # 零部件制造商
|
||||
2: (2, 0, 2), # 产品制造商
|
||||
3: (3, 0, 3), # 分销商
|
||||
4: (4, 0, 4) # 零售商
|
||||
}
|
||||
|
||||
# 创建3D图形
|
||||
fig = plt.figure()
|
||||
ax = fig.add_subplot(111, projection='3d')
|
||||
|
||||
# 绘制节点
|
||||
for node, (x, y, z) in positions.items():
|
||||
ax.scatter(x, y, z, color='b', s=100) # 绘制每个节点
|
||||
ax.text(x, y, z, nodes[node], size=12, zorder=1, color='k') # 添加节点标签
|
||||
|
||||
# 绘制边（箭头）
|
||||
for start, end in edges:
|
||||
start_pos = positions[start]
|
||||
end_pos = positions[end]
|
||||
ax.plot([start_pos[0], end_pos[0]],
|
||||
[start_pos[1], end_pos[1]],
|
||||
[start_pos[2], end_pos[2]], color='r') # 连接每对节点
|
||||
|
||||
# 设置坐标轴标签
|
||||
ax.set_xlabel('X轴')
|
||||
ax.set_ylabel('Y轴')
|
||||
ax.set_zlabel('Z轴')
|
||||
|
||||
# 设置视角以便更好地观察3D图形
|
||||
ax.view_init(elev=20., azim=-35) # 角度可根据需要调整
|
||||
|
||||
# 显示3D图形
|
||||
plt.show()
|
||||
0
执行sql语句.py
Normal file
0
执行sql语句.py
Normal file
53
查看进度.py
Normal file
53
查看进度.py
Normal file
@@ -0,0 +1,53 @@
|
||||
from matplotlib import rcParams, pyplot as plt
|
||||
from sqlalchemy import func
|
||||
from orm import db_session, Sample
|
||||
|
||||
# 创建全局绘图对象和轴
|
||||
fig, ax = plt.subplots(figsize=(8, 5))
|
||||
plt.ion() # 启用交互模式
|
||||
|
||||
def visualize_progress():
|
||||
"""
|
||||
可视化 `is_done_flag` 的分布，动态更新进度条。
|
||||
"""
|
||||
|
||||
# 设置全局字体
|
||||
rcParams['font.family'] = 'Microsoft YaHei' # 黑体，适用于中文
|
||||
rcParams['font.size'] = 12
|
||||
|
||||
# 查询数据库中各 is_done_flag 的数量
|
||||
result = db_session.query(
|
||||
Sample.is_done_flag, func.count(Sample.id)
|
||||
).group_by(Sample.is_done_flag).all()
|
||||
|
||||
# 转换为字典
|
||||
data = {flag: count for flag, count in result}
|
||||
|
||||
# 填充缺失的标志为 0
|
||||
for flag in [-1, 0, 1]:
|
||||
data.setdefault(flag, 0)
|
||||
|
||||
# 准备数据
|
||||
labels = ['未完成 (-1)', '计算中(0)', '完成 (1)']
|
||||
values = [data[-1], data[0], data[1]]
|
||||
|
||||
# 清空之前的绘图内容
|
||||
ax.clear()
|
||||
|
||||
# 创建柱状图
|
||||
ax.bar(labels, values, color=['red', 'orange', 'green'])
|
||||
ax.set_title('任务进度分布', fontsize=16)
|
||||
ax.set_xlabel('任务状态', fontsize=14)
|
||||
ax.set_ylabel('数量', fontsize=14)
|
||||
ax.tick_params(axis='both', labelsize=12)
|
||||
|
||||
# 显示具体数量
|
||||
for i, v in enumerate(values):
|
||||
ax.text(i, v + 0.5, str(v), ha='center', fontsize=12)
|
||||
|
||||
# 刷新绘图
|
||||
plt.pause(0) # 暂停一段时间以更新图表
|
||||
|
||||
# 关闭窗口时，停止交互模式
|
||||
# plt.ioff()
|
||||
visualize_progress()
|
||||
115
绘制度.py
Normal file
115
绘制度.py
Normal file
@@ -0,0 +1,115 @@
|
||||
import pickle
|
||||
|
||||
import pandas as pd
|
||||
import networkx as nx
|
||||
import matplotlib.pyplot as plt
|
||||
|
||||
# 1. 读取并处理数据
|
||||
bom_nodes = pd.read_csv('input_data/input_product_data/BomNodes.csv')
|
||||
bom_nodes['Code'] = bom_nodes['Code'].astype(str)
|
||||
bom_nodes.set_index('Index', inplace=True)
|
||||
|
||||
bom_cate_net = pd.read_csv('input_data/input_product_data/合成结点.csv')
|
||||
|
||||
# 2. 构建图结构
|
||||
g_bom = nx.from_pandas_edgelist(bom_cate_net, source='UPID', target='ID', create_using=nx.MultiDiGraph())
|
||||
|
||||
# 填充每一个结点的具体内容
|
||||
bom_labels_dict = {}
|
||||
for index in g_bom.nodes:
|
||||
try:
|
||||
bom_labels_dict[index] = bom_nodes.loc[index].to_dict()
|
||||
except KeyError:
|
||||
print(f"节点 {index} 不存在于 bom_nodes 中")
|
||||
|
||||
# 分配属性给每一个结点
|
||||
nx.set_node_attributes(g_bom, bom_labels_dict)
|
||||
|
||||
# 3. 计算每个节点的度数
|
||||
degrees = dict(g_bom.degree()) # 总度数（适用于有向图）
|
||||
|
||||
# 4. 统计每个度数的节点数量
|
||||
degree_counts = {}
|
||||
for degree in degrees.values():
|
||||
if degree in degree_counts:
|
||||
degree_counts[degree] += 1
|
||||
else:
|
||||
degree_counts[degree] = 1
|
||||
|
||||
# 转换为排序后的列表（横坐标：度数，纵坐标：节点数）
|
||||
sorted_degrees = sorted(degree_counts.keys())
|
||||
sorted_counts = [degree_counts[d] for d in sorted_degrees]
|
||||
|
||||
# 5. 绘制度分布图
|
||||
plt.figure(figsize=(12, 8)) # 增大画布尺寸
|
||||
bars = plt.bar(sorted_degrees, sorted_counts, width=0.8)
|
||||
plt.title('Degree Distribution In Industrial Chain', fontsize=16)
|
||||
plt.xlabel('Degree', fontsize=14)
|
||||
plt.ylabel('Number of Nodes', fontsize=14)
|
||||
plt.grid(True, linestyle='--', alpha=0.5)
|
||||
plt.xticks(rotation=45) # 如果度数较多，可以旋转x轴标签
|
||||
plt.tight_layout() # 防止标签重叠
|
||||
|
||||
# 6. 在每个柱子上方标注数值
|
||||
for bar in bars:
|
||||
height = bar.get_height()
|
||||
plt.text(
|
||||
bar.get_x() + bar.get_width() / 2, # x坐标：柱子中心
|
||||
height + max(sorted_counts) * 0.02, # y坐标：柱子顶部上方（留出空间）
|
||||
f'{int(height)}', # 显示数值（转换为整数）
|
||||
ha='center', # 水平居中
|
||||
va='bottom', # 垂直底部对齐
|
||||
fontsize=10, # 字体大小
|
||||
color='black' # 字体颜色
|
||||
)
|
||||
|
||||
# 7. 保存超高清图片（300 DPI）
|
||||
output_path = "degree_distribution_with_labels.png" # 输出文件名
|
||||
plt.savefig(output_path, dpi=500, bbox_inches='tight') # dpi=300 确保高分辨率
|
||||
print(f"图片已保存至: {output_path}")
|
||||
|
||||
# 1. 加载企业网络数据
|
||||
with open("firm_network.pkl", 'rb') as f:
|
||||
G_firm = pickle.load(f)
|
||||
print(f"Successfully loaded cached data from firm_network.pkl")
|
||||
|
||||
# 2. 计算企业网络的度分布
|
||||
degrees_firm = dict(G_firm.degree()) # 总度数
|
||||
degree_counts_firm = {}
|
||||
for degree in degrees_firm.values():
|
||||
if degree in degree_counts_firm:
|
||||
degree_counts_firm[degree] += 1
|
||||
else:
|
||||
degree_counts_firm[degree] = 1
|
||||
|
||||
# 转换为排序后的列表
|
||||
sorted_degrees_firm = sorted(degree_counts_firm.keys())
|
||||
sorted_counts_firm = [degree_counts_firm[d] for d in sorted_degrees_firm]
|
||||
|
||||
# 3. 绘制企业网络的度分布图
|
||||
plt.figure(figsize=(12, 6)) # 单独画布尺寸
|
||||
plt.bar(sorted_degrees_firm, sorted_counts_firm, width=0.8)
|
||||
plt.title('Degree Distribution of Firm Network', fontsize=16)
|
||||
plt.xlabel('Degree (Number of Connections)', fontsize=14)
|
||||
plt.ylabel('Number of Firms', fontsize=14)
|
||||
plt.grid(True, linestyle='--', alpha=0.5)
|
||||
plt.xticks(rotation=45)
|
||||
plt.tight_layout()
|
||||
|
||||
# 在柱子上方标注数值
|
||||
for bar in plt.gca().containers[0]: # 获取当前图中的柱子对象
|
||||
height = bar.get_height()
|
||||
plt.text(
|
||||
bar.get_x() + bar.get_width() / 2,
|
||||
height + max(sorted_counts_firm) * 0.02,
|
||||
f'{int(height)}',
|
||||
ha='center',
|
||||
va='bottom',
|
||||
fontsize=10,
|
||||
color='black'
|
||||
)
|
||||
|
||||
# 保存图片
|
||||
plt.savefig("degree_distribution_firm.png", dpi=500, bbox_inches='tight')
|
||||
print("企业度分布图已保存至: degree_distribution_firm.png")
|
||||
|
||||
Reference in New Issue
Block a user