Rename and improve plotting of co-simulation Notebook

Signed-off-by: pipeacosta <pipeacosta@gmail.com>

examples/Notebooks/cosim-villas-socket.ipynb → examples/Notebooks/cosimulation-attributes.ipynb

@@ -189,8 +189,8 @@
     "import subprocess\n",
     "import numpy as np\n",
     "\n",
-    "H_v = np.array([1e-4, 2e-4, 4e-4])\n",
-    "H_v_legends = ['1e-4', '2e-4', '4e-4']\n",
+    "H_v = np.array([1e-4, 2e-4, 4e-4, 0.001, 0.003, 0.01])\n",
+    "H_v_legends = ['1e-4', '2e-4', '4e-4', '1e-3', '3e-3', '1e-2']\n",
     "\n",
     "i=0\n",
     "for H in H_v:\n",
@@ -236,7 +236,6 @@
     "import villas.dataprocessing.plottools as pt\n",
     "import villas.dataprocessing.readtools as rt\n",
     "import villas.dataprocessing.timeseries as ts\n",
-    "%matplotlib widget\n",
     "\n",
     "results = rt.read_timeseries_dpsim('logs/EMTCosim.csv')\n",
     "\n",
@@ -365,18 +364,18 @@
     "    v_zoh = np.array([ts_1_zoh.values[::m], ts_2_zoh.values[::m]])\n",
     "    v_linear = np.array([ts_1_linear.values[::m], ts_2_linear.values[::m]])\n",
     "    \n",
-    "    gloal_error_zoh_t = np.mean(np.linalg.norm(v_a - v_zoh, axis=0))\n",
+    "    gloal_error_zoh_t = np.max(np.linalg.norm(v_a - v_zoh, axis=0))\n",
     "    \n",
     "    global_error_zoh.append(gloal_error_zoh_t)\n",
-    "    global_error_linear.append(np.mean(np.linalg.norm(v_a - v_linear, axis=0)))\n",
+    "    global_error_linear.append(np.max(np.linalg.norm(v_a - v_linear, axis=0)))\n",
     "    \n",
     "plt.figure()\n",
     "plt.plot(np.log10(H_v), np.log10(global_error_zoh), 'b', label='ZOH')\n",
     "plt.plot(np.log10(H_v), np.log10(global_error_zoh), 'bo')\n",
-    "plt.plot(np.log10(H_v), np.log10(np.multiply(H_v, 10**0.85)), 'k', label=r'$\\mathcal{O}(H)$')\n",
+    "plt.plot(np.log10(H_v), np.log10(np.multiply(H_v, 10*0.012)), 'k', label=r'$\\mathcal{O}(H)$')\n",
     "plt.plot(np.log10(H_v), np.log10(global_error_linear), 'r', label='Linear')\n",
     "plt.plot(np.log10(H_v), np.log10(global_error_linear), 'ro')\n",
-    "plt.plot(np.log10(H_v), np.log10(np.multiply(H_v**2, 10**2.9)), '--k', label=r'$\\mathcal{O}(H^2)$')\n",
+    "plt.plot(np.log10(H_v), np.log10(np.multiply(H_v**2, 10**1.5)), '--k', label=r'$\\mathcal{O}(H^2)$')\n",
     "plt.xlabel('')\n",
     "# TODO: Fix log scale\n",
     "# plt.xscale(\"log\")\n",

examples/Python/Attributes/emt-cosim-attributes_polynomial.py

@@ -228,9 +228,7 @@ def set_dpsim2(t_s, t_f, vs_cond, logger_prefix):
 
     # We have to assume the trajectory of y_2 extending its initial value, since we have no prior information
     # y_1_m_prev = np.tile(y_1_0, m)
-
-    # This one as computed in Matlab
-    y_1_m_prev = np.array([30.108, y_1_0])
+    y_1_m_prev = np.array([complex(0, 0), y_1_0])
 
     for i in range(0, N):
         y_1_prev = y_1_m_prev[-1]