corrected notebook parallelization mistakes

Author: pavelkomarov

examples/4_performance_analysis.ipynb

@@ -133,7 +133,7 @@
     "\t\t\tfor method,mname in tqdm(methods):\n",
     "\t\t\t\t#best_params, best_rmse = optimize(method, x, dt, dxdt_truth=dxdt_truth, metric='rmse')\n",
     "\t\t\t\t#best_params, best_ec = optimize(method, x, dt, dxdt_truth=dxdt_truth, metric='error_correlation')\n",
-    "\t\t\t\tbest_params, best_score = optimize(method, x, dt, tvgamma=tvgamma,\n",
+    "\t\t\t\tbest_params, best_score = optimize(method, x, dt, tvgamma=tvgamma, parallel=False,\n",
     "\t\t\t\t\t\tsearch_space_updates=({'order':{2,3}} if (method in [tvrdiff, robustdiff] and sim != triangle) else {})) # because convex-based with order 1 tends to hack the cost function\n",
     "\t\t\t\tx_hat, dxdt_hat = method(x, dt, **best_params)\n",
     "\t\n",
@@ -194,7 +194,8 @@
     "\tjobs += [{'dt':0.01, 'cutoff_frequency':3, 'noise_type':'normal', 'noise_params':[0, 0.1],\n",
     "\t\t\t'noise_scale':1, 'outliers':False, 'random_seed':random_seed} for cutoff_frequency in cutoff_frequencies] # 5\n",
     "\n",
-    "with Pool as pool: pool.map(lambda kwargs: main_loop(**kwargs), jobs)"
+    "def run(kwargs): main_loop(**kwargs)\n",
+    "with Pool() as pool: pool.map(run, jobs)"
    ]
   },
   {