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Fix CSA_motor_efficiency UnboundLocalError for unsupported pole counts #98

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Merged
CalebBell merged 3 commits into from
Sep 15, 2026
+14 −0
Merged

Fix CSA_motor_efficiency UnboundLocalError for unsupported pole counts #98

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274c7f4
Fix CSA_motor_efficiency UnboundLocalError for unsupported pole counts
yuhuavit-hash Sep 9, 2026
1aa057b
Merge upstream/master
yuhuavit-hash Sep 15, 2026
302889b
Reword pole coverage note in CSA_motor_efficiency docstring
yuhuavit-hash Sep 15, 2026
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9 changes: 9 additions & 0 deletions fluids/pump.py
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Original file line number Diff line number Diff line change
Expand Up @@ -375,6 +375,10 @@ def CSA_motor_efficiency(P: float, closed: bool=False, poles: int=2, high_effici
Several low-efficiency standard high power values were added to allow for
easy programming; values are the last listed efficiency in the table.

The high-efficiency standard covers 2, 4, and 6 pole motors only; the
minimum efficiency standard additionally covers 8 pole motors. A
ValueError is raised for unsupported pole counts.

Examples
--------
>>> CSA_motor_efficiency(100*hp)
Expand All @@ -388,6 +392,11 @@ def CSA_motor_efficiency(P: float, closed: bool=False, poles: int=2, high_effici
375 kW). As modified 2015-12-17.
https://natural-resources.canada.ca/energy-efficiency/energy-efficiency-regulations/electric-motors-1-500-hp0746-375-kw
"""
if high_efficiency:
if poles not in (2, 4, 6):
raise ValueError("Only 2, 4, and 6 pole motors have high-efficiency standard values")
elif poles not in (2, 4, 6, 8):
raise ValueError("Only 2, 4, 6, and 8 pole motors have standard efficiency values")
P = P/hp
# This could be replaced by a dict and a jump list
if high_efficiency:
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5 changes: 5 additions & 0 deletions tests/test_pump.py
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Expand Up @@ -92,6 +92,11 @@ def test_CSA_motor_efficiency():
nema_min_Ps = [0.755, 0.825, 0.84, 0.855, 0.855, 0.875, 0.875, 0.885, 0.895, 0.902, 0.902, 0.91, 0.91, 0.917, 0.924, 0.93, 0.93, 0.936, 0.945, 0.945, 0.95, 0.95, 0.954, 0.954, 0.954, 0.954, 0.954, 0.954, 0.825, 0.84, 0.84, 0.875, 0.875, 0.875, 0.875, 0.895, 0.895, 0.91, 0.91, 0.924, 0.924, 0.93, 0.93, 0.936, 0.941, 0.945, 0.945, 0.95, 0.95, 0.95, 0.95, 0.954, 0.954, 0.954, 0.954, 0.958, 0.8, 0.855, 0.865, 0.875, 0.875, 0.875, 0.875, 0.895, 0.895, 0.902, 0.902, 0.917, 0.917, 0.93, 0.93, 0.936, 0.936, 0.941, 0.941, 0.95, 0.95, 0.95, 0.95, 0.95, 0.95, 0.95, 0.95, 0.95, 0.74, 0.77, 0.825, 0.84, 0.84, 0.855, 0.855, 0.855, 0.885, 0.885, 0.895, 0.895, 0.91, 0.91, 0.917, 0.917, 0.93, 0.93, 0.936, 0.936, 0.941, 0.941, 0.945, 0.945, 0.945, 0.945, 0.945, 0.945, 0.755, 0.825, 0.84, 0.84, 0.84, 0.855, 0.855, 0.875, 0.885, 0.895, 0.902, 0.91, 0.91, 0.917, 0.924, 0.93, 0.93, 0.93, 0.936, 0.936, 0.945, 0.945, 0.945, 0.95, 0.95, 0.954, 0.958, 0.958, 0.825, 0.84, 0.84, 0.865, 0.865, 0.875, 0.875, 0.885, 0.895, 0.91, 0.91, 0.917, 0.924, 0.93, 0.93, 0.936, 0.941, 0.941, 0.945, 0.95, 0.95, 0.95, 0.954, 0.954, 0.954, 0.954, 0.958, 0.958, 0.8, 0.84, 0.855, 0.865, 0.865, 0.875, 0.875, 0.885, 0.902, 0.902, 0.91, 0.917, 0.924, 0.93, 0.93, 0.936, 0.936, 0.941, 0.941, 0.945, 0.945, 0.945, 0.954, 0.954, 0.954, 0.954, 0.954, 0.954, 0.74, 0.755, 0.855, 0.865, 0.865, 0.875, 0.875, 0.885, 0.895, 0.895, 0.902, 0.902, 0.91, 0.91, 0.917, 0.924, 0.936, 0.936, 0.936, 0.936, 0.936, 0.936, 0.945, 0.945, 0.945, 0.945, 0.945, 0.945]
assert_close1d(nema_min_P_calcs, nema_min_Ps)

with pytest.raises(Exception):
CSA_motor_efficiency(100*hp, poles=8, high_efficiency=True)
with pytest.raises(Exception):
CSA_motor_efficiency(100*hp, poles=3)

def test_motor_efficiency_underloaded():
full_efficiencies = [motor_efficiency_underloaded(P*hp, .99) for P in (0.5, 2.5, 7, 12, 42, 90)]
assert_close1d(full_efficiencies, [1, 1, 1, 1, 1, 1])
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