debugging

PSD/complex_current_and_nodes.py

@@ -88,9 +88,9 @@ def numba_sp_complex_currents(data, indptr, indices, v, i):
 
 
 def define_network_rhs(node_list, Y):
-    assert len(node_list) == len(Y)
-    length = len(Y)
-    total_length = 2*length
+    assert len(node_list) == Y.shape[0]
+    length = Y.shape[0]
+    total_length = 2 * length
 
     def network_rhs(y, t):
         coupling_sp = sps.csr_matrix(Y)

PSD/microgrid_frequency_dynamics.py

@@ -20,6 +20,7 @@ def load_PYPSA(filename):
 def load_PyPSA_df(adm, par):
     from pandas import read_csv
     Y = np.load(adm)
+    Y = Y[()] # this is import to recover a csr_matrix
     df = read_csv(par, index_col=0)
     system_size = df.shape[0]
     node_list = [SwingEquationNode(3, infeed=df.p.iloc[i], H=0.1, damping=0.01, v_set=df.v_nom.iloc[i]) for i in range(system_size)]
@@ -80,20 +81,29 @@ def main(sim_dir=default_dir, create_test_data=True, run_test=True, flag_baobab=
         # Run Test PYPSD without BAOBAB
         times = np.linspace(0., 10., 100)
         from scipy.integrate import odeint
-        brp = bao.BatchRunParameters(number_of_batches=10, simulations_per_batch=10, system_dimension=100)
+
+        brp = bao.BatchRunParameters(number_of_batches=1, simulations_per_batch=1, system_dimension=Y.shape[0])
+
+        import time
+        print "start","{0.tm_year}-{0.tm_mon}.{0.tm_mday}.-{0.tm_hour}h{0.tm_min}m.timestamp".format(time.localtime(time.time()))
 
         generate_run_conditions = define_gen_rc(brp, rhs)
         rc = generate_run_conditions(0, 0)
+        print "generate_run_conditions", "{0.tm_year}-{0.tm_mon}.{0.tm_mday}.-{0.tm_hour}h{0.tm_min}m.timestamp".format(time.localtime(time.time()))
 
         #node_list[0].infeed += 0.1
         rhs = define_network_rhs(node_list, Y)
+        print "define_network_rhs", "{0.tm_year}-{0.tm_mon}.{0.tm_mday}.-{0.tm_hour}h{0.tm_min}m.timestamp".format(time.localtime(time.time()))
+
         states = odeint(rhs, rc[0], times)
+        print "integration", "{0.tm_year}-{0.tm_mon}.{0.tm_mday}.-{0.tm_hour}h{0.tm_min}m.timestamp".format(time.localtime(time.time()))
+
         import matplotlib.pyplot as plt
         from mpl_toolkits.mplot3d import Axes3D
 
         fig = plt.figure()
         ax = fig.gca(projection='3d')
-        for k in range(brp.system_dimension):
+        for k in range(3):
             ax.plot(states[:, k], states[:, brp.system_dimension+k], states[:, 2*brp.system_dimension+k])
         ax.set_xlabel(r"$\Re$ V")
         ax.set_ylabel(r"$\Im$ V")