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New metrics to return Transaction table with quantity in units of kg/GWe #161

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New metrics to return Transaction table with quantity in units of kg/GWe #161

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4d7a738
Create TransactionQuantityPerGWe metrics and tests for transaction_qu…
louishartono Feb 19, 2020
0095610
Removed inventory_quantity_per_gwe in metrics.py and test_metrics.py
louishartono Feb 19, 2020
74722c1
Change Time to TimeCreated on test_transaction_quantity_per_gwe
louishartono Feb 26, 2020
a9dfe4b
Clarify the purpose of the metric
louishartono Mar 4, 2020
96ecee8
Merge branch 'master' into transaction_metrics
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bam241 Jul 27, 2020
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36 changes: 36 additions & 0 deletions cymetric/metrics.py
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Original file line number Diff line number Diff line change
Expand Up @@ -467,6 +467,7 @@ def timelist(info):

del _tldeps, _tlschema


# Quantity per GigaWattElectric in Inventory [kg/GWe]
_invdeps = ['ExplicitInventory','TimeSeriesPower']

Expand Down Expand Up @@ -504,4 +505,39 @@ def inventory_quantity_per_gwe(expinv,power):
inv.Quantity = inv.Quantity/inv.Value
inv=inv.drop(['Value'],axis=1)
return inv
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# Quantity per GigaWattElectric in TransactionQuantity [kg/GWe]
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_tranactsdeps = ['TransactionQuantity','TimeSeriesPower']

_tranactsschema = [
('SimId', ts.UUID),
('TransactionId', ts.INT),
('ResourceId', ts.INT),
('ObjId', ts.INT),
('Time', ts.INT),
('SenderId', ts.INT),
('ReceiverId', ts.INT),
('Commodity', ts.STRING),
('Units', ts.STRING),
('Quantity', ts.DOUBLE)
]


@metric(name='TransactionQuantityPerGWe', depends=_tranactsdeps, schema=_tranactsschema)
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def transaction_quantity_per_gwe(tranacts, power):
"""Transaction Quantity per GWe metric returns the transaction quantity table
with quantity in units of kg/GWe, calculated by dividing the original quantity
by the electricity generated at the corresponding simulation and the specific
time in TimeSeriesPower metric.
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"""
power = power.groupby(['SimId','Time']).sum()
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df1 = power.reset_index()
tranacts_index = ['SimId', 'TransactionId', 'ResourceId', 'ObjId', 'Time',
'SenderId', 'ReceiverId', 'Commodity', 'Units', 'Quantity']
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tranacts['Time']= tranacts.TimeCreated
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tranacts['Units'] = tranacts['Units'] + "/MWe"
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tranacts=pd.merge(tranacts,df1, on=['SimId','Time'],how='left')
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tranacts.Quantity = tranacts.Quantity/tranacts.Value
return tranacts[tranacts_index]

78 changes: 70 additions & 8 deletions tests/test_metrics.py
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Expand Up @@ -366,36 +366,98 @@ def test_timelist():


def test_inventory_quantity_per_gwe():
#exp is the expected output metrics
# exp is the expected output metrics
exp = pd.DataFrame(np.array([
(UUID('f22f2281-2464-420a-8325-37320fd418f8'), 1, 0, 'core', 922350000, 1.0),
(UUID('f22f2281-2464-420a-8325-37320fd418f8'), 1, 0, 'usedfuel', 922350000, 2.0),
(UUID('f22f2281-2464-420a-8325-37320fd418f8'), 2, 1, 'core', 922350000, 2.0),
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], dtype=ensure_dt_bytes([
('SimId', 'O'), ('AgentId', '<i8'), ('Time', '<i8'),
('InventoryName', 'O'), ('NucId', '<i8'), ('Quantity', '<f8')]))
('SimId', 'O'),
('AgentId', '<i8'),
('Time', '<i8'),
('InventoryName', 'O'),
('NucId', '<i8'),
('Quantity', '<f8')]))
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)
#tsp is the TimeSeriesPower metrics
# tsp is the TimeSeriesPower metrics
tsp = pd.DataFrame(np.array([
(UUID('f22f2281-2464-420a-8325-37320fd418f8'), 1, 0, 100),
(UUID('f22f2281-2464-420a-8325-37320fd418f8'), 2, 0, 200),
(UUID('f22f2281-2464-420a-8325-37320fd418f8'), 1, 1, 100),
], dtype=ensure_dt_bytes([
('SimId', 'O'), ('AgentId', '<i8'), ('Time', '<i8'),
('SimId', 'O'),
('AgentId', '<i8'),
('Time', '<i8'),
('Value', '<f8')]))
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)
#inv is the ExplicitInventory metrics
# inv is the ExplicitInventory metrics
inv = pd.DataFrame(np.array([
(UUID('f22f2281-2464-420a-8325-37320fd418f8'), 1, 0, 'core', 922350000, 300),
(UUID('f22f2281-2464-420a-8325-37320fd418f8'), 1, 0, 'usedfuel', 922350000, 600),
(UUID('f22f2281-2464-420a-8325-37320fd418f8'), 2, 1, 'core', 922350000, 200),
], dtype=ensure_dt_bytes([
('SimId', 'O'), ('AgentId', '<i8'), ('Time', '<i8'),
('InventoryName', 'O'), ('NucId', '<i8'), ('Quantity', '<f8')]))
('SimId', 'O'),
('AgentId', '<i8'),
('Time', '<i8'),
('InventoryName', 'O'),
('NucId', '<i8'),
('Quantity', '<f8')]))
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)
obs = metrics.inventory_quantity_per_gwe.func(inv, tsp)
assert_frame_equal(exp, obs)
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def test_transaction_quantity_per_gwe():
# exp is the expected output metrics
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exp = pd.DataFrame(np.array([
(UUID('f22f2281-2464-420a-8325-37320fd418f8'),
1, 7, 3, 3, 10, 20, 'LWR Fuel', 'kg/MWe', 0.82),
(UUID('f22f2281-2464-420a-8325-37320fd418f8'),
2, 8, 4, 3, 20, 30, 'FR Fuel', 'kg/MWe', 0.61),
(UUID('f22f2281-2464-420a-8325-37320fd418f8'),
3, 9, 5, 12, 30, 40, 'Spent Fuel', 'kg/MWe', 0.09),
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], dtype=ensure_dt_bytes([
('SimId', 'O'),
('TransactionId', '<i8'),
('ResourceId', '<i8'),
('ObjId', '<i8'),
('Time', '<i8'),
('SenderId', '<i8'),
('ReceiverId', '<i8'),
('Commodity', 'O'),
('Units', 'O'),
('Quantity', '<f8')]))
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)
# tsp is the TimeSeriesPower metrics
tsp = pd.DataFrame(np.array([
(UUID('f22f2281-2464-420a-8325-37320fd418f8'), 1, 3, 225),
(UUID('f22f2281-2464-420a-8325-37320fd418f8'), 2, 3, 275),
(UUID('f22f2281-2464-420a-8325-37320fd418f8'), 1, 12, 100),
], dtype=ensure_dt_bytes([
('SimId', 'O'),
('AgentId', '<i8'),
('Time', '<i8'),
('Value', '<f8')]))
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)
# tranacts is the TransactionQuantity metrics
tranacts = pd.DataFrame(np.array([
(UUID('f22f2281-2464-420a-8325-37320fd418f8'), 1, 7, 3, 3, 10, 20, 'LWR Fuel', 'kg', 410),
(UUID('f22f2281-2464-420a-8325-37320fd418f8'), 2, 8, 4, 3, 20, 30, 'FR Fuel', 'kg', 305),
(UUID('f22f2281-2464-420a-8325-37320fd418f8'), 3, 9, 5, 12, 30, 40, 'Spent Fuel', 'kg', 9),
], dtype=ensure_dt_bytes([
('SimId', 'O'),
('TransactionId', '<i8'),
('ResourceId', '<i8'),
('ObjId', '<i8'),
('TimeCreated', '<i8'),
('SenderId', '<i8'),
('ReceiverId', '<i8'),
('Commodity', 'O'),
('Units', 'O'),
('Quantity', '<f8')]))
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)
obs = metrics.transaction_quantity_per_gwe.func(tranacts, tsp)
assert_frame_equal(exp, obs)

if __name__ == "__main__":
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nose.runmodule()
Expand Down