Add unit tests for incentives and alt rates #557
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- Both are tested for a fuel switching measure that shifts from natural gas furnaces. The focus of the testing is CA single family homes. - A slight adjustment to the 'apply_incentives' function was made to improve its robustness to cases where a user provides an incentive for a segment that doesn't already have incentives defined in the AEO baseline data.
jtlangevin
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Dec 8, 2025
jmythms
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Tested locally, works as intended, looks good to me:
- test_incentives() tests stacking incentives using the 'apply_incentives' in 'fill_mkts' function of ecm_prep.py. Verified test fails by changing numbers in the
hv.incentiveslist. - test_alt_rates() tests fill_mkts function ability to override standard prices using alternative electricity rates. Verfied tests failing by changing the low volume price to 0.07 in the
hv.low_volume_ratefor existing ASHP.
| self.ok_map_frefr_mkts_out[idx]) | ||
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| def test_incentives(self): | ||
| """Test 'apply_incentives' in 'fill_mkts' function given user-defined incentive inputs.""" |
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I see other docstrings in the MarketUpdatesTest class (eg. test_mseg_ok_full_tp) follow a "description, notes, raises" pattern. Could be good to maintain that pattern for these tests as well.
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| # Initialize dummy measure with state-level inputs to draw from | ||
| base_state_meas = self.ok_tpmeas_partchk_state_in[0] | ||
| # Pull handyvars from first sample measure and set year range | ||
| hv = copy.deepcopy(base_state_meas.handyvars) | ||
| # Set user-defined incentives information; test stacked federal and non-federal incentives | ||
| hv.incentives = [[ | ||
| "CA", "single family home", "existing", "heating", "ASHP", | ||
| "electricity", "natural gas", "no", "replace", "federal", False, | ||
| 0, "warm climates: 2.6; cold climates: 2.8", "COP", 30, 2000, | ||
| "$/unit", 2010, 2050, 1], | ||
| [ | ||
| "CA", "single family home", "existing", "heating", "ASHP", | ||
| "electricity", "natural gas", "no", "replace", "non-federal", False, | ||
| 0, 2.6, "COP", 50, float('nan'), "$/unit", 2010, 2050, 1] | ||
| ] | ||
| years = [str(y) for y in hv.aeo_years] | ||
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| # Seed BY-YEAR carbon price | ||
| carb_prices = hv.ccosts | ||
| carb_prices.update({y: 1 for y in years}) | ||
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| # Seed BY-YEAR electricity price & carbon intensities | ||
| el_prices = hv.ecosts.setdefault( | ||
| "residential", {}).setdefault("electricity", {}) | ||
| el_prices.update({y: 60.0 for y in years}) | ||
| ng_prices = hv.ecosts["residential"].setdefault("natural gas", {}) | ||
| ng_prices.update({y: 11.0 for y in years}) | ||
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| el_carb = hv.carb_int.setdefault( | ||
| "residential", {}).setdefault("electricity", {}) | ||
| el_carb.update({y: 5.0e-08 for y in years}) | ||
| ng_carb = hv.carb_int["residential"].setdefault("natural gas", {}) | ||
| ng_carb.update({y: 5.0e-08 for y in years}) | ||
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| hv.ss_conv.setdefault("electricity", {}) | ||
| hv.ss_conv.setdefault("natural gas", {}) | ||
| for y in years: | ||
| hv.ss_conv["electricity"][y] = 1.0 | ||
| hv.ss_conv["natural gas"][y] = 1.0 | ||
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| # Options: split fuel reporting + pick Max adoption potential | ||
| opts = copy.deepcopy(self.opts_state) | ||
| opts.adopt_scn_usr = ["Max adoption potential"] |
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Again, common elements in multiple tests can be grouped to form a test class method. Not required as an emergency fix, but it is recommended, especially if more tests will be added with similar scaffolding. We currently cannot view ecm_prep_test on GitHub because of how big the file is.
| # If there is no switching element of the measure, assign the measure's | ||
| # incentives modifications to that of the baseline mseg | ||
| if not cost_incentives_meas: | ||
| if not mskeys_swtch: |
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Good to make variable names more "Scout-specific", for ease of understanding.
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test_incentivesandtest_alt_ratesto existingMarketUpdatesTestclass withinecm_prep_testmodule. These methods test the user-defined incentives and alternate utilty rate structure capabilities, respectively, which are further described in previously closed pull request Handle alternate rate structures and enhance incentives #532.ecm_prep_testa very slight adjustment to theapply_incentivesfunction inecm_prepwas made to improve its robustness to cases where a user provides an incentive for a segment that doesn't already have incentives defined in the AEO baseline data.Addresses issue #544.