Black of the tutorials

Author: klapo

tutorials/tutorial20/costs-tutorial_real-data.ipynb

@@ -230,7 +230,7 @@
     "        step_size_array=step_sizes,\n",
     "        global_svd_array=global_svd_array,\n",
     "        cluster_sweep=True,\n",
-    "        transform_method='absolute',\n",
+    "        transform_method=\"absolute\",\n",
     "    )\n",
     "\n",
     "    mrc.fit(data, np.atleast_2d(ts))"
@@ -803,47 +803,49 @@
    "source": [
     "da = mrc._da_omega\n",
     "x = da.values\n",
-    "x = x.reshape(len(da.window_length), len(da.window_time_means) * len(da.svd_rank))\n",
+    "x = x.reshape(\n",
+    "    len(da.window_length), len(da.window_time_means) * len(da.svd_rank)\n",
+    ")\n",
     "\n",
     "# Squared frequencies\n",
     "x_trans = np.abs(x.imag) ** 2 / (2 * np.pi)\n",
     "plt.figure(figsize=(5, 2.5))\n",
     "plt.hist(\n",
     "    x=x_trans.T,\n",
     "    bins=np.linspace(0, 0.005, 100),\n",
-    "    histtype='barstacked',\n",
+    "    histtype=\"barstacked\",\n",
     "    density=True,\n",
     "    label=range(mrc.n_decompositions),\n",
-    ");\n",
+    ")\n",
     "plt.gca().set_title(\"Global histogram; Interpolated decomposition levels\")\n",
     "plt.gca().set_xlabel(r\"$Im(\\omega)^2 (2 \\pi)^{-1}$ (s$^2$)\")\n",
-    "plt.legend(title='decomposition level')\n",
+    "plt.legend(title=\"decomposition level\")\n",
     "\n",
     "# Frequency\n",
     "plt.figure(figsize=(5, 2.5))\n",
     "x_trans = np.abs(x.imag) / (2 * np.pi)\n",
     "plt.hist(\n",
     "    x=x_trans.T,\n",
     "    bins=100,\n",
-    "    histtype='barstacked',\n",
+    "    histtype=\"barstacked\",\n",
     "    density=True,\n",
     "    label=range(mrc.n_decompositions),\n",
-    ");\n",
+    ")\n",
     "plt.gca().set_title(\"Global histogram; Interpolated decomposition levels\")\n",
     "plt.gca().set_xlabel(r\"$Im(|\\omega|) (2 \\pi)^{-1}$ (s$^{-1}$)\")\n",
-    "plt.legend(title='decomposition level')\n",
+    "plt.legend(title=\"decomposition level\")\n",
     "\n",
     "# Period\n",
     "plt.figure(figsize=(5, 2.5))\n",
     "x_trans = (2 * np.pi) / np.abs(x.imag)\n",
     "plt.hist(\n",
     "    x=x_trans.T,\n",
     "    bins=100,\n",
-    "    histtype='barstacked',\n",
+    "    histtype=\"barstacked\",\n",
     "    density=True,\n",
     "    label=range(mrc.n_decompositions),\n",
-    ");\n",
-    "plt.legend(title='decomposition level')\n",
+    ")\n",
+    "plt.legend(title=\"decomposition level\")\n",
     "plt.gca().set_title(\"Global histogram; Interpolated decomposition levels\")\n",
     "plt.gca().set_xlabel(r\"Period; $(2 \\pi) / Im(|\\omega|)$ (s)\")"
    ]
@@ -911,15 +913,15 @@
     "plt.hist(\n",
     "    x=x_trans.T,\n",
     "    bins=np.logspace(start=np.log10(20), stop=np.log10(1300), num=100),\n",
-    "    histtype='barstacked',\n",
+    "    histtype=\"barstacked\",\n",
     "    label=range(mrc.n_decompositions),\n",
     "    weights=weights.T,\n",
-    ");\n",
-    "plt.xscale('log')\n",
-    "plt.legend(title='decomposition level')\n",
+    ")\n",
+    "plt.xscale(\"log\")\n",
+    "plt.legend(title=\"decomposition level\")\n",
     "plt.gca().set_title(\"Global histogram; Interpolated decomposition levels\")\n",
     "plt.gca().set_xlabel(r\"Period; $(2 \\pi) / Im(|\\omega|)$ (s)\")\n",
-    "plt.gca().set_ylabel('Weighted Count (-)')"
+    "plt.gca().set_ylabel(\"Weighted Count (-)\")"
    ]
   },
   {
@@ -1054,7 +1056,7 @@
    },
    "outputs": [],
    "source": [
-    "x_trans = (2 * np.pi / 10**omega_array)\n",
+    "x_trans = 2 * np.pi / 10**omega_array\n",
     "unique_labels, label_counts = np.unique(omega_classes, return_counts=True)\n",
     "weights = label_counts.max() / label_counts\n",
     "x_trans_labels = [x_trans[omega_classes == label] for label in unique_labels]\n",
@@ -1067,7 +1069,7 @@
     "    w = weights[ind_array]\n",
     "    x_w = x_trans_labels[ind_list]\n",
     "    w_broadcast = np.broadcast_to(w, (x_w.shape))\n",
-    "    weights_labels.append(w_broadcast)\n"
+    "    weights_labels.append(w_broadcast)"
    ]
   },
   {
@@ -1099,21 +1101,21 @@
     "plt.hist(\n",
     "    x=x_trans_labels,\n",
     "    bins=np.logspace(start=np.log10(20), stop=np.log10(1300), num=100),\n",
-    "    histtype='barstacked',\n",
-    "    weights=weights_labels\n",
-    ");\n",
+    "    histtype=\"barstacked\",\n",
+    "    weights=weights_labels,\n",
+    ")\n",
     "\n",
     "ax = plt.gca()\n",
-    "ax.set_xscale('log')\n",
+    "ax.set_xscale(\"log\")\n",
     "ax.set_title(\n",
     "    \"Global histogram of frequencies; Interpolated decomposition levels\"\n",
     ")\n",
     "ax.set_xlabel(r\"Period; $(2 \\pi) / Im(|\\omega|)$ (s)\")\n",
-    "ax.set_ylabel('Density (-)')\n",
+    "ax.set_ylabel(\"Density (-)\")\n",
     "[\n",
     "    ax.axvline(2 * np.pi / (10**c), color=\"k\", ls=\"--\")\n",
     "    for nc, c in enumerate(cluster_centroids)\n",
-    "];\n",
+    "]\n",
     "\n",
     "ylim_bottom, ylim_top = ax.get_ylim()\n",
     "[\n",
@@ -1126,7 +1128,7 @@
     "        ha=\"right\",\n",
     "    )\n",
     "    for c in cluster_centroids\n",
-    "];\n"
+    "];"
    ]
   },
   {

tutorials/tutorial20/costs-tutorial_toy-data.ipynb

@@ -877,7 +877,7 @@
     "    step_size_array=step_sizes,\n",
     "    global_svd_array=global_svd_array,\n",
     "    n_components_array=n_components_array,\n",
-    "    transform_method=transform_method\n",
+    "    transform_method=transform_method,\n",
     ")\n",
     "\n",
     "mrc.fit(data, np.atleast_2d(time))"