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7 | 7 |
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8 | 8 | @pytest.mark.parametrize(
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9 | 9 | "activity_type, ventilation_active, air_exch, flow_rate_lsp", [
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10 |
| - ['Seated', [8, 12, 13, 17], [0.25, 2.45, 0.25], [2.604166667, 51.04166667, 2.604166667]], |
| 10 | + ['Seated', [8, 12, 13, 17], [0.25, 2.45, 0.25], [2.604166667, 25.520833335, 2.604166667]], |
11 | 11 | ['Standing', [8, 10, 11, 12, 17], [1.25, 3.25, 1.45, 0.25], [13.02083333333, 33.8541666667, 15.1041666667, 2.6041666667]],
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12 | 12 | ['Light activity', [8, 12, 17], [1.25, 0.25], [13.02083333333, 2.6041666667]],
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13 | 13 | ['Moderate activity', [8, 13, 15, 16, 17], [2.25, 0.25, 3.45, 0.25], [23.4375, 2.6041666667, 35.9375, 2.6041666667]],
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@@ -40,6 +40,7 @@ def test_fitting_algorithm(data_registry, activity_type, ventilation_active, air
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40 | 40 | # Generate CO2DataModel
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41 | 41 | data_model = models.CO2DataModel(
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42 | 42 | data_registry=data_registry,
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| 43 | + room_capacity=2, |
43 | 44 | room_volume=75,
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44 | 45 | occupancy=models.IntPiecewiseConstant(transition_times=tuple(
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45 | 46 | [8, 12, 13, 17]), values=tuple([2, 1, 2])),
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