Merge branch 'multistart' into 'master'

- multistart with position shufling implemented

Closes #15 and mowflot#28

See merge request !42

topfarm/_topfarm.py

@@ -126,7 +126,7 @@ class TopFarm(object):
         t = time.time()
         self.problem.run_driver()
         print("Optimized in\t%.3fs" % (time.time() - t))
-        return np.array([self.problem['turbineX'], self.problem['turbineY']]).T
+        return self.get_cost(), np.array([self.problem['turbineX'], self.problem['turbineY']]).T
 
     def get_cost(self):
         return self.problem['cost'][0]

topfarm/cost_models/utils/aep_calculator.py

-'''
-Created on 19/04/2018
-
-@author: Mads
-'''
-import os
-
 import numpy as np
 from topfarm.cost_models.fused_wake_wrappers import FusedWakeGCLWakeModel
 from topfarm.cost_models.utils.wind_resource import WindResource

topfarm/multistart.py

+import os
+import numpy as np
+import multiprocessing
+
+
+def run(N, single_starter, processes=None):
+    """Run N single starts in parallel
+
+    Parameters
+    ----------
+    N : int
+        Number of single starts
+    single_starter : function
+        function for single start. Interface must be:
+        def f(id):
+            tf = Topfarm(...)
+            return tf.optimize
+    processes : int or None, optional
+        Number of processes passed to multiprocessing.Pool
+
+    Returns
+    -------
+    best : (cost, turbine_positions)
+        best result
+    results : [(cost1, turbine_positions1),...]
+        all results
+    """
+    pool = multiprocessing.Pool(processes)
+    results = pool.map(single_starter, range(N))
+    best = results[np.argmin([r[0] for r in results])]
+    return best, results
+
+
+def single_start_example(id, maxiter=5, plot_comp=None):
+    from topfarm._topfarm import TopFarm
+    from topfarm.cost_models.fused_wake_wrappers import FusedWakeNOJWakeModel
+    from topfarm.cost_models.utils.aep_calculator import AEPCalculator
+    from topfarm.cost_models.utils.wind_resource import WindResource
+    from topfarm.easy_drivers import EasyScipyOptimizeDriver
+    from topfarm.tests.test_files import tfp
+
+    D = 80.0
+    D2 = 2 * D
+    init_pos = np.array([(0, D2), (0, 0), (0, -D2)])
+    boundary = [(-D2, D2), (D2, D2), (D2, -D2), (-D2, -D2)]
+    minSpacing = 2.0
+    f, A, k = [1, 0, 0, 0], [10, 10, 10, 10], [2, 2, 2, 2]
+    wr = WindResource(f, A, k, ti=np.zeros_like(f) + .1)
+    wm = FusedWakeNOJWakeModel(tfp + "wind_farms/3tb.yml")
+    aep_calc = AEPCalculator(wr, wm)
+    driver = EasyScipyOptimizeDriver(maxiter=maxiter, disp=False)
+    tf = TopFarm(init_pos, aep_calc.get_TopFarm_cost_component(), minSpacing * D,
+                 boundary=boundary, plot_comp=plot_comp, driver=driver)
+    tf.shuffle_positions('abs')
+    return tf.optimize()
+
+
+def try_me():
+    if __name__ == '__main__':
+        print(run(4, single_start_example)[0], 2)
+        print(single_start_example(0, 10))
+
+
+try_me()