updates tolerances and changelog

CHANGELOG.md

@@ -6,6 +6,13 @@ The format is based on [Keep a Changelog](https://keepachangelog.com/en/1.0.0/),
 and this project adheres to [Semantic Versioning](https://semver.org/spec/v2.0.0.html).
 
 ## [Unreleased]
+## [0.2.1] - 2022-11-01
+### Fixed
+- Fixes a bug where storage constraints were not initialized in the `DispatchModel`.
+- Fixes the tolerances in the testing suite so that the tests pass. 
+Previously, a single test was failing due to (-1e-9 == 0 ± 1e-12). 
+This should pass, since 1e-9 is still close to zero.
+
 ## [0.2.0] - 2022-10-31
 ### Added
 - Adds the following Technology subclasses

docs/source/conf.py

@@ -22,7 +22,7 @@
 author = 'Samuel Dotson'
 
 # The full version, including alpha/beta/rc tags
-release = '0.2.0'
+release = '0.2.1'
 
 
 # -- General configuration ---------------------------------------------------

setup.py

@@ -7,7 +7,7 @@
 # Format expected by setup.py and doc/source/conf.py: string of form "X.Y.Z"
 _version_major = 0
 _version_minor = 2
-_version_micro = 0  # use '' for first of series, number for 1 and above
+_version_micro = 1  # use '' for first of series, number for 1 and above
 # _version_extra = 'dev'
 _version_extra = ''  # Uncomment this for full releases
 

tests/test_models.py

@@ -203,10 +203,10 @@ def test_dispatch_model_solve_case1(technology_set_1, net_demand):
         [t.variable_cost for t in technology_set_1]).min()
     expected_result = cheapest_tech * net_demand.sum()
 
-    assert model.objective == pytest.approx(expected_result, TOL)
+    assert model.objective == pytest.approx(expected_result, abs=TOL)
     assert model.results['Nuclear'].sum(
     ) == pytest.approx(net_demand.sum(), TOL)
-    assert model.results['NaturalGas'].sum() == pytest.approx(0.0, TOL)
+    assert model.results['NaturalGas'].sum() == pytest.approx(0.0, abs=TOL)
 
 
 def test_dispatch_model_solve_case2(technology_set_2, net_demand):
@@ -226,7 +226,7 @@ def test_dispatch_model_solve_case2(technology_set_2, net_demand):
     expected_natgas = net_demand - expected_nuclear
     expected_result = (expected_nuclear * nuclear.variable_cost
                        + expected_natgas * natgas.variable_cost).sum()
-    assert model.objective == pytest.approx(expected_result, TOL)
+    assert model.objective == pytest.approx(expected_result, abs=TOL)
 
 
 def test_dispatch_model_solve_case3(technology_set_3, net_demand):
@@ -244,9 +244,9 @@ def test_dispatch_model_solve_case3(technology_set_3, net_demand):
     min_power_delta = ((model.results.Nuclear.diff())
                        / nuclear.capacity.to_value()).min()
     assert max_power_delta == pytest.approx(
-        nuclear.ramp_up_rate.to_value(), TOL)
+        nuclear.ramp_up_rate.to_value(), abs=TOL)
     assert min_power_delta == pytest.approx(
-        -nuclear.ramp_down_rate.to_value(), TOL)
+        -nuclear.ramp_down_rate.to_value(), abs=TOL)
 
 
 def test_dispatch_model_solve_case4(technology_set_4, net_demand):
@@ -263,5 +263,5 @@ def test_dispatch_model_solve_case4(technology_set_4, net_demand):
                                'Battery_charge']].sum().sum()
     binary_charging = np.dot(model.results.Battery,
                              model.results.Battery_charge)
-    assert (total_gen - net_demand.sum()) == pytest.approx(0, TOL)
-    assert binary_charging == pytest.approx(0, TOL)
+    assert (total_gen - net_demand.sum()) == pytest.approx(0, abs=TOL)
+    assert binary_charging == pytest.approx(0, abs=TOL)