with_exp
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b4e9512439
commit
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@ -14,6 +14,7 @@
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"args": [
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"--exp", "without_exp",
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"--job", "24",
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"--reset_db", "True",
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]
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}
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]
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@ -0,0 +1,420 @@
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e_id,count,max_max_ts,dct_lst_init_remove_firm_prod
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@ -0,0 +1,17 @@
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select distinct s_id from iiabmdb.without_exp_result where ts > 0;
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select s_id, max(ts) as max_ts from iiabmdb.without_exp_result where ts > 0 group by s_id order by max_ts;
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select e_id, count(id) as count, max(max_ts) as max_max_ts from iiabmdb.without_exp_sample as a
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inner join (select s_id, max(ts) as max_ts from iiabmdb.without_exp_result where ts > 0 group by s_id) as b
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on a.id = b.s_id
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group by e_id
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order by count desc;
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select e_id, count, max_max_ts, dct_lst_init_remove_firm_prod from iiabmdb.without_exp_experiment as a
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inner join
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(select e_id, count(id) as count, max(max_ts) as max_max_ts from iiabmdb.without_exp_sample as a
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inner join (select s_id, max(ts) as max_ts from iiabmdb.without_exp_result where ts > 0 group by s_id) as b
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on a.id = b.s_id
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group by e_id) as b
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on a.id = b.e_id
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where count >= 9
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order by count desc;
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@ -0,0 +1,7 @@
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CREATE DATABASE iiabmdb_dissertation;
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RENAME TABLE iiabmdb.not_test_experiment TO iiabmdb_dissertation.not_test_experiment,
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iiabmdb.not_test_result TO iiabmdb_dissertation.not_test_result,
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iiabmdb.not_test_sample TO iiabmdb_dissertation.not_test_sample,
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iiabmdb.test_experiment TO iiabmdb_dissertation.test_experiment,
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iiabmdb.test_result TO iiabmdb_dissertation.test_result,
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iiabmdb.test_sample TO iiabmdb_dissertation.test_sample;
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select id, e_id, idx_sample, seed, ts_done from iiabmdb.without_exp_sample where is_done_flag != -1;
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select id, e_id, idx_sample, seed, ts_done from iiabmdb.without_exp_sample where is_done_flag != -1 order by ts_done;
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select count(id) from iiabmdb.without_exp_sample where is_done_flag != -1;
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select count(id) from iiabmdb.without_exp_sample;
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select count(id) from iiabmdb.without_exp_sample where is_done_flag != -1;
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@ -9,6 +9,7 @@ import pandas as pd
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import platform
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import networkx as nx
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import json
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import pickle
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class ControllerDB:
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@ -45,13 +46,31 @@ class ControllerDB:
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Firm.fillna(0, inplace=True)
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# fill dct_lst_init_remove_firm_prod
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list_dct = []
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for _, row in Firm.iterrows():
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code = row['Code']
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row = row['1':]
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for product_code in row.index[row == 1].to_list():
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dct = {code: [product_code]}
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list_dct.append(dct)
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# list_dct = []
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# for _, row in Firm.iterrows():
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# code = row['Code']
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# row = row['1':]
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# for product_code in row.index[row == 1].to_list():
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# dct = {code: [product_code]}
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# list_dct.append(dct)
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str_sql = "select e_id, count, max_max_ts, " \
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"dct_lst_init_remove_firm_prod from " \
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"iiabmdb.without_exp_experiment as a " \
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"inner join " \
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"(select e_id, count(id) as count, max(max_ts) as max_max_ts " \
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"from iiabmdb.without_exp_sample as a " \
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"inner join (select s_id, max(ts) as max_ts from " \
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"iiabmdb.without_exp_result where ts > 0 group by s_id) as b " \
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"on a.id = b.s_id " \
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"group by e_id) as b " \
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"on a.id = b.e_id " \
|
||||
"order by count desc;"
|
||||
result = pd.read_sql(sql=str_sql, con=engine)
|
||||
result['dct_lst_init_remove_firm_prod'] = \
|
||||
result['dct_lst_init_remove_firm_prod'].apply(
|
||||
lambda x: pickle.loads(x))
|
||||
list_dct = result.loc[result['count'] >= 9,
|
||||
'dct_lst_init_remove_firm_prod'].to_list()
|
||||
# list_dct = [{'140': ['1.4.5.1']}]
|
||||
# list_dct = [{'133': ['1.4.4.1']}]
|
||||
# list_dct = [{'2': ['1.1.3']}]
|
||||
|
|
@ -74,7 +93,7 @@ class ControllerDB:
|
|||
# insert exp
|
||||
df_xv = pd.read_csv("xv.csv", index_col=None)
|
||||
# read the OA table
|
||||
df_oa = pd.read_csv("oa.csv", index_col=None)
|
||||
df_oa = pd.read_csv("oa_with_exp.csv", index_col=None)
|
||||
for idx_scenario, row in df_oa.iterrows():
|
||||
dct_exp_para = {}
|
||||
for idx_col, para_level in enumerate(row):
|
||||
|
|
|
|||
|
|
@ -0,0 +1,30 @@
|
|||
X X X X X X X X X X X X X
|
||||
1 2 3 4 5 6 7 8 9 10 11 12 13
|
||||
-------------------------------------------
|
||||
1 1 1 1 1 1 1 1 1 1 1 1 1
|
||||
1 1 1 1 2 2 2 2 2 2 2 2 2
|
||||
1 1 1 1 3 3 3 3 3 3 3 3 3
|
||||
1 2 2 2 1 1 1 2 2 2 3 3 3
|
||||
1 2 2 2 2 2 2 3 3 3 1 1 1
|
||||
1 2 2 2 3 3 3 1 1 1 2 2 2
|
||||
1 3 3 3 1 1 1 3 3 3 2 2 2
|
||||
1 3 3 3 2 2 2 1 1 1 3 3 3
|
||||
1 3 3 3 3 3 3 2 2 2 1 1 1
|
||||
2 1 2 3 1 2 3 1 2 3 1 2 3
|
||||
2 1 2 3 2 3 1 2 3 1 2 3 1
|
||||
2 1 2 3 3 1 2 3 1 2 3 1 2
|
||||
2 2 3 1 1 2 3 2 3 1 3 1 2
|
||||
2 2 3 1 2 3 1 3 1 2 1 2 3
|
||||
2 2 3 1 3 1 2 1 2 3 2 3 1
|
||||
2 3 1 2 1 2 3 3 1 2 2 3 1
|
||||
2 3 1 2 2 3 1 1 2 3 3 1 2
|
||||
2 3 1 2 3 1 2 2 3 1 1 2 3
|
||||
3 1 3 2 1 3 2 1 3 2 1 3 2
|
||||
3 1 3 2 2 1 3 2 1 3 2 1 3
|
||||
3 1 3 2 3 2 1 3 2 1 3 2 1
|
||||
3 2 1 3 1 3 2 2 1 3 3 2 1
|
||||
3 2 1 3 2 1 3 3 2 1 1 3 2
|
||||
3 2 1 3 3 2 1 1 3 2 2 1 3
|
||||
3 3 2 1 1 3 2 3 2 1 2 1 3
|
||||
3 3 2 1 2 1 3 1 3 2 3 2 1
|
||||
3 3 2 1 3 2 1 2 1 3 1 3 2
|
||||
|
|
@ -0,0 +1,28 @@
|
|||
X1,X2,X3,X4,X5,X6,X7,X8,X9
|
||||
0,0,0,0,0,0,0,0,0
|
||||
0,0,0,0,1,1,1,1,1
|
||||
0,0,0,0,2,2,2,2,2
|
||||
0,1,1,1,0,0,0,1,1
|
||||
0,1,1,1,1,1,1,2,2
|
||||
0,1,1,1,2,2,2,0,0
|
||||
0,2,2,2,0,0,0,2,2
|
||||
0,2,2,2,1,1,1,0,0
|
||||
0,2,2,2,2,2,2,1,1
|
||||
1,0,1,2,0,1,2,0,1
|
||||
1,0,1,2,1,2,0,1,2
|
||||
1,0,1,2,2,0,1,2,0
|
||||
1,1,2,0,0,1,2,1,2
|
||||
1,1,2,0,1,2,0,2,0
|
||||
1,1,2,0,2,0,1,0,1
|
||||
1,2,0,1,0,1,2,2,0
|
||||
1,2,0,1,1,2,0,0,1
|
||||
1,2,0,1,2,0,1,1,2
|
||||
2,0,2,1,0,2,1,0,2
|
||||
2,0,2,1,1,0,2,1,0
|
||||
2,0,2,1,2,1,0,2,1
|
||||
2,1,0,2,0,2,1,1,0
|
||||
2,1,0,2,1,0,2,2,1
|
||||
2,1,0,2,2,1,0,0,2
|
||||
2,2,1,0,0,2,1,2,1
|
||||
2,2,1,0,1,0,2,0,2
|
||||
2,2,1,0,2,1,0,1,0
|
||||
|
32
test.ipynb
32
test.ipynb
|
|
@ -136,6 +136,38 @@
|
|||
"\n",
|
||||
"print(mp.cpu_count())"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": 18,
|
||||
"metadata": {},
|
||||
"outputs": [
|
||||
{
|
||||
"name": "stdout",
|
||||
"output_type": "stream",
|
||||
"text": [
|
||||
"71\n"
|
||||
]
|
||||
}
|
||||
],
|
||||
"source": [
|
||||
"from orm import engine\n",
|
||||
"import pandas as pd\n",
|
||||
"import pickle\n",
|
||||
"str_sql = \"select e_id, count, max_max_ts, dct_lst_init_remove_firm_prod from iiabmdb.without_exp_experiment as a \" \\\n",
|
||||
"\"inner join \" \\\n",
|
||||
"\"(select e_id, count(id) as count, max(max_ts) as max_max_ts from iiabmdb.without_exp_sample as a \" \\\n",
|
||||
"\"inner join (select s_id, max(ts) as max_ts from iiabmdb.without_exp_result where ts > 0 group by s_id) as b \" \\\n",
|
||||
"\"on a.id = b.s_id \" \\\n",
|
||||
"\"group by e_id) as b \" \\\n",
|
||||
"\"on a.id = b.e_id \" \\\n",
|
||||
"\"order by count desc;\"\n",
|
||||
"result = pd.read_sql(sql=str_sql, con=engine)\n",
|
||||
"result['dct_lst_init_remove_firm_prod'] = result['dct_lst_init_remove_firm_prod'].apply(lambda x: pickle.loads(x))\n",
|
||||
"# print(result)\n",
|
||||
"list_dct = result.loc[result['count']>=9, 'dct_lst_init_remove_firm_prod'].to_list()\n",
|
||||
"print(len(list_dct))"
|
||||
]
|
||||
}
|
||||
],
|
||||
"metadata": {
|
||||
|
|
|
|||
Loading…
Reference in New Issue