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Description
From case2.m output dict:
dict_keys(['version', 'baseMVA', 'bus', 'gen', 'branch', 'gencost', 'order', 'et', 'success', 'iterations', 'getdoc'])
{'version': '2',
'baseMVA': 100.0,
'bus': array([[ 1.00000000e+00, 3.00000000e+00, 0.00000000e+00,
0.00000000e+00, 0.00000000e+00, 0.00000000e+00,
1.00000000e+00, 1.00000000e+00, 0.00000000e+00,
3.45000000e+02, 1.00000000e+00, 1.10000000e+00,
9.00000000e-01],
[ 2.00000000e+00, 1.00000000e+00, 2.50000000e+00,
1.00000000e+00, 0.00000000e+00, 0.00000000e+00,
1.00000000e+00, 9.99498967e-01, -7.16556448e-02,
3.45000000e+02, 1.00000000e+00, 1.10000000e+00,
9.00000000e-01]]),
'gen': array([[ 1. , 2.5 , 1.00362863, 300. ,
-300. , 1. , 100. , 1. ,
15. , 0. , 0. , 0. ,
0. , 0. , 0. , 0. ,
0. , 0. , 0. , 0. ,
0. ]]),
'branch': array([[ 1.00000000e+00, 2.00000000e+00, 0.00000000e+00,
5.00000000e-02, 0.00000000e+00, 2.50000000e+02,
2.50000000e+02, 2.50000000e+02, 0.00000000e+00,
0.00000000e+00, 1.00000000e+00, -3.60000000e+02,
3.60000000e+02, 2.50000000e+00, 1.00362863e+00,
-2.50000000e+00, -9.99999997e-01]]),
'gencost': array([[ 2., 1500., 0., 3., 0., 5., 0.]]),
'order': {'bus': {'e2i': <Compressed Sparse Column sparse array of dtype 'float64'
with 2 stored elements and shape (2, 1)>,
'i2e': array([[1.],
[2.]]),
'status': {'on': array([[1.],
[2.]]),
'off': array([], shape=(0, 1), dtype=float64)}},
'gen': {'e2i': 1.0, 'i2e': 1.0, 'status': {'on': 1.0, 'off': []}},
'branch': {'status': {'on': 1.0, 'off': []}},
'state': 'e',
'int': {'bus': array([[ 1.00000000e+00, 3.00000000e+00, 0.00000000e+00,
0.00000000e+00, 0.00000000e+00, 0.00000000e+00,
1.00000000e+00, 1.00000000e+00, 0.00000000e+00,
3.45000000e+02, 1.00000000e+00, 1.10000000e+00,
9.00000000e-01],
[ 2.00000000e+00, 1.00000000e+00, 2.50000000e+00,
1.00000000e+00, 0.00000000e+00, 0.00000000e+00,
1.00000000e+00, 9.99498967e-01, -7.16556448e-02,
3.45000000e+02, 1.00000000e+00, 1.10000000e+00,
9.00000000e-01]]),
'branch': array([[ 1.00000000e+00, 2.00000000e+00, 0.00000000e+00,
5.00000000e-02, 0.00000000e+00, 2.50000000e+02,
2.50000000e+02, 2.50000000e+02, 0.00000000e+00,
0.00000000e+00, 1.00000000e+00, -3.60000000e+02,
3.60000000e+02, 2.50000000e+00, 1.00362863e+00,
-2.50000000e+00, -9.99999997e-01]]),
'gen': array([[ 1. , 2.5 , 1.00362863, 300. ,
-300. , 1. , 100. , 1. ,
15. , 0. , 0. , 0. ,
0. , 0. , 0. , 0. ,
0. , 0. , 0. , 0. ,
0. ]])}},
'et': 0.05357098579406738,
'success': 1,
'iterations': 2.0,
'getdoc': {}}
The easier part is to include 'et', 'success', 'iterations'. As it serve as info, for export, place it on:
pd.DataFrame(
data={
"INFO": {
"version": getattr(self, "version", None),
"baseMVA": getattr(self, "baseMVA", None),
}
}
).to_csv(os.path.join(path, f"{prefix}info{suffix}.csv"))But the code need to be refactored to only add the keys when it is not None for 'et', 'success', 'iterations'.
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