carbon do_redd and do_valuation are dependent on calc_sequestration. #BITBUCKET-3912.
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@ -39,7 +39,7 @@ ARGS_SPEC = {
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},
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"calc_sequestration": {
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"type": "boolean",
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"required": False,
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"required": "do_valuation | do_redd",
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"about": (
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"Check to enable sequestration analysis. This requires "
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"inputs of Land Use/Land Cover maps for both current and "
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@ -333,9 +333,7 @@ class CarbonValidationTests(unittest.TestCase):
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'workspace_dir',
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'lulc_cur_path',
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'carbon_pools_path',
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'lulc_cur_year',
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'lulc_fut_year',
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'lulc_fut_path',
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'calc_sequestration',
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'lulc_redd_path',
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])
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self.assertEqual(invalid_keys, expected_missing_keys)
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@ -351,30 +349,9 @@ class CarbonValidationTests(unittest.TestCase):
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'workspace_dir',
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'lulc_cur_path',
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'carbon_pools_path',
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'lulc_cur_year',
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'lulc_fut_year',
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'lulc_fut_path',
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'calc_sequestration',
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'price_per_metric_ton_of_c',
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'discount_rate',
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'rate_change',
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])
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self.assertEqual(invalid_keys, expected_missing_keys)
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"""
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1. Test that the model will run given the
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argument requirements stated in ARGS SPEC.
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Build an arg set that meets the spec requirements
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and then run the model and observe no errors.
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2. Test that argument requirements stated in ARGS SPEC
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are not too strict. Will the model run without
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meeting all those requirements? How would I test this?
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3. Test that validation API works as expected given the
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conditional logic in ARGS_SPEC required fields. Functionality
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of common expressions (such as a single arg key string)
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is adequately tested by test_validation.py.
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Custom logical expressions should have tests here.
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4.
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"""
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