read wind climate from lib file for gcl to be consistent with fuga

examples/irp_wind/optimization_3tb.py

@@ -7,50 +7,74 @@ from topfarm.cost_models.utils.aep_calculator import AEPCalculator
 from topfarm.cost_models.utils.wind_resource import WindResource
 from topfarm.plotting import PlotComp
 from topfarm.topfarm import TopFarm
-
+from topfarm.cost_models.fuga.lib_reader import read_lib
+import matplotlib.pyplot as plt
 
 D = 80.0
 D2 = 2 * D
 initial_position = np.array([(0, D2), (0, 0), (0, -D2)])
 boundary = [(-D2, D2), (D2, D2), (D2, -D2), (-D2, -D2)]
 minSpacing = 2.0
+fuga_path = os.path.abspath(os.path.dirname(py_fuga.__file__)) + '/Colonel/'
 
 
 def optimize_AEP_FusedWake_GCL():
     plot_comp = PlotComp()
-    f = [1, 0, 0, 0]
-    A = [9.176929, 9.782334, 9.531809, 9.909545]
-    k = [2.392578, 2.447266, 2.412109, 2.591797]
-
+    f, A, k = read_lib(fuga_path + 'LUT/Farms/Horns Rev 1\hornsrev_north_only_pm45.lib')
     wr = WindResource(f, A, k, ti=np.zeros_like(f) + .1)
-
     wm = FusedWakeGCLWakeModel(os.path.dirname(__file__) + "/3tb.yml")
     aep_calc = AEPCalculator(wr, wm)
-    aep_calc(np.array([[0, 0, 100], [160, 0, -160]]).T)
     init_pos = initial_position.copy()
-    init_pos[:, 0] += [-50, 0, 50]
-    print(aep_calc(np.array([[-160, 0, 160], [0, 0, 0]]).T))
+    init_pos[:, 0] += [-20, 0, 20]
     tf = TopFarm(init_pos, aep_calc.get_TopFarm_cost_component(), minSpacing * D, boundary=boundary, plot_comp=plot_comp)
+    tf.evaluate()
+    print(tf.get_cost())
     tf.optimize()
+    print(tf.get_cost())
+    save_plot('final_gcl.png', tf, False)
     plot_comp.show()
 
 
 def optimize_AEP_Fuga():
     plot_comp = PlotComp()
-    fuga_path = os.path.abspath(os.path.dirname(py_fuga.__file__)) + '/Colonel/'
+
     pyFuga = PyFuga(farm_name='Horns Rev 1',
                     turbine_model_path=fuga_path + 'LUT/', turbine_model_name='Vestas_V80_(2_MW_offshore)[h=67.00]',
                     tb_x=initial_position[:, 0], tb_y=initial_position[:, 1],
                     mast_position=(0, 0, 70), z0=0.0001, zi=400, zeta0=0,
-                    farms_dir=fuga_path + 'LUT/Farms/', wind_atlas_path='Horns Rev 1\hornsrev_north_only.lib')
+                    farms_dir=fuga_path + 'LUT/Farms/', wind_atlas_path='Horns Rev 1\hornsrev_north_only_pm45.lib', climate_interpolation=False)
 
     init_pos = initial_position.copy()
     init_pos[:, 0] += [-20, 0, 20]
     tf = TopFarm(init_pos, pyFuga.get_TopFarm_cost_component(), minSpacing * D, boundary=boundary, plot_comp=plot_comp)
+
+    save_plot('initial.png', tf, True)
+    tf.evaluate()
+    print(tf.get_cost())
     tf.optimize()
+    print(tf.get_cost())
+    save_plot('final_fuga.png', tf, False)
     plot_comp.show()
 
 
+def save_plot(filename, tf, initial=False):
+    import matplotlib.pyplot as plt
+    plt.figure(figsize=(3, 3))
+    plt.axis('equal')
+    plt.xlabel('Distance [m]')
+    plt.ylabel('Distance [m]')
+    if initial:
+        pos = tf.initial_positions
+    else:
+        pos = tf.turbine_positions
+    plt.plot(tf.boundary[:, 0], tf.boundary[:, 1], label='Boundary')
+    plt.plot(pos[:, 0], pos[:, 1], '2', ms=15, label='%s turbine positions' % ('Optimized', 'initial')[initial])
+    # plt.legend(loc=1)
+    plt.tight_layout()
+    plt.savefig(filename)
+    plt.show()
+
+
 if __name__ == '__main__':
     optimize_AEP_Fuga()
     optimize_AEP_FusedWake_GCL()