Merge branch 'Increase_coverage_and_fail_under' into 'master'

Increase coverage and fail under

See merge request !68

.coveragerc

 [run]
 omit = 
 	*/Colonel/*
-	topfarm/tests/*
\ No newline at end of file
+	topfarm/tests/*
+[report]
+fail_under = 80
\ No newline at end of file

topfarm/easy_drivers.py

@@ -51,7 +51,7 @@ except ModuleNotFoundError:
 
 
 class EasySimpleGADriver(MySimpleGADriver):
-    def __init__(self, max_gen=100, pop_size=25, Pm=None, Pc=.5, elitism=True, bits={}, debug_print=[], run_parallel=False):
+    def __init__(self, max_gen=100, pop_size=25, Pm=None, Pc=.5, elitism=True, bits={}, debug_print=[], run_parallel=False, random_state=None):
         """SimpleGA driver with optional arguments
 
         Parameters
@@ -75,3 +75,5 @@ class EasySimpleGADriver(MySimpleGADriver):
         """
         MySimpleGADriver.__init__(self, max_gen=max_gen, pop_size=pop_size, Pm=Pm, Pc=Pc, elitism=elitism,
                                   bits=bits, debug_print=debug_print, run_parallel=run_parallel)
+        if random_state is not None:
+            self._randomstate = random_state

topfarm/tests/test_topfarm_problems/test_TopFarmProblem.py

@@ -64,6 +64,12 @@ def test_update_state(turbineTypeOptimizationProblem, types, cost):
     c, state = tf.evaluate({'turbineType': types})
     npt.assert_equal(c, cost)
     npt.assert_array_equal(state['turbineType'], types)
+    # wrong shape
+    c, state = tf.evaluate({'turbineType': [types]})
+    npt.assert_equal(c, cost)
+    npt.assert_array_equal(state['turbineType'], types)
+    # missing key
+    c, state = tf.evaluate({'missing': types})
 
 
 def test_evaluate(turbineTypeOptimizationProblem):

topfarm/tests/test_topfarm_utils/test_drivers.py

@@ -3,7 +3,8 @@ import numpy as np
 import pytest
 from topfarm.cost_models.dummy import DummyCost
 from topfarm.plotting import NoPlot
-from topfarm.easy_drivers import EasyScipyOptimizeDriver, EasyPyOptSparseIPOPT
+from topfarm.easy_drivers import EasyScipyOptimizeDriver, EasyPyOptSparseIPOPT,\
+    EasySimpleGADriver
 from topfarm.tests import npt, uta
 
 
@@ -41,6 +42,7 @@ def topfarm_generator():
     (EasyScipyOptimizeDriver(tol=1e-3, disp=False), 1e-2),
     (EasyScipyOptimizeDriver(maxiter=14, disp=False), 1e-1),
     (EasyScipyOptimizeDriver(optimizer='COBYLA', tol=1e-3, disp=False), 1e-2),
+    (EasySimpleGADriver(max_gen=10, pop_size=100, bits={'turbineX': [12] * 3, 'turbineY':[12] * 3}, random_state=1), 1e-1),
     (EasyPyOptSparseIPOPT(), 1e-4),
 ][:])
 def test_optimizers(driver, tol, topfarm_generator):
@@ -48,14 +50,15 @@ def test_optimizers(driver, tol, topfarm_generator):
         pytest.xfail("Driver missing")
     tf = topfarm_generator(driver)
     tf.evaluate()
-    _, _, recorder = tf.optimize()
+    cost, state, recorder = tf.optimize()
     print(recorder.driver_cases.num_cases)
     tb_pos = tf.turbine_positions[:, :2]
-    tf.plot_comp.show()
-
     assert sum((tb_pos[2] - tb_pos[0])**2) > 2**2 - tol  # check min spacing
     assert tb_pos[1][0] < 6 + tol  # check within border
-    np.testing.assert_array_almost_equal(tb_pos, optimal, -int(np.log10(tol)))
+    if isinstance(driver, EasySimpleGADriver):
+        assert cost == recorder['cost'].min()
+    else:
+        np.testing.assert_array_almost_equal(tb_pos, optimal, -int(np.log10(tol)))
 
 
 @pytest.mark.parametrize('driver,tol,N', [