docs: update formatting in 02_advanced

Aarhus-Psychiatry-Research · Dec 8, 2022 · 47065e9 · 47065e9
1 parent f2648f8
commit 47065e9
Showing 1 changed file with 33 additions and 19 deletions.
diff --git a/tutorials/02_advanced.ipynb b/tutorials/02_advanced.ipynb
@@ -332,7 +332,39 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 3,
+   "execution_count": 6,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "from timeseriesflattener.feature_spec_objects import PredictorGroupSpec\n",
+    "\n",
+    "# Import synth_predictor_binary to populate the data_loaders registry with the function\n",
+    "from timeseriesflattener.testing.load_synth_data import synth_predictor_binary\n",
+    "from pprint import pprint\n",
+    "from timeseriesflattener.resolve_multiple_functions import maximum\n",
+    "\n",
+    "pred_spec_batch = PredictorGroupSpec(\n",
+    "    values_loader=[\"synth_predictor_float\"],\n",
+    "    lookbehind_days=[365, 730],\n",
+    "    fallback=[np.nan],\n",
+    "    resolve_multiple_fn=[mean, maximum],\n",
+    ").create_combinations()\n"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "You'll note that:\n",
+    "1. All attributes are now required to be lists. This makes iteration easier when creating the combinations.\n",
+    "2. We require values_loaders to be strings that can be resolved in the registries. This string is used when creating the column names - otherwise we wouldn't know what to call the columns.\n",
+    "\n",
+    "Let's check that the results look good."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 7,
    "metadata": {},
    "outputs": [
     {
@@ -356,20 +388,6 @@
     }
    ],
    "source": [
-    "from timeseriesflattener.feature_spec_objects import PredictorGroupSpec\n",
-    "\n",
-    "# Import synth_predictor_binary to populate the data_loaders registry with the function\n",
-    "from timeseriesflattener.testing.load_synth_data import synth_predictor_binary\n",
-    "from pprint import pprint\n",
-    "from timeseriesflattener.resolve_multiple_functions import maximum\n",
-    "\n",
-    "pred_spec_batch = PredictorGroupSpec(\n",
-    "    values_loader=[\"synth_predictor_float\"],\n",
-    "    lookbehind_days=[365, 730],\n",
-    "    fallback=[np.nan],\n",
-    "    resolve_multiple_fn=[mean, maximum],\n",
-    ").create_combinations()\n",
-    "\n",
     "# Create a small summary to highlight the generated predictors\n",
     "pred_spec_batch_summary = [\n",
     "    {\n",
@@ -389,10 +407,6 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "You'll note that:\n",
-    "1. All attributes are now required to be lists. This makes iteration easier when creating the combinations.\n",
-    "2. We require values_loaders to be strings that can be resolved in the registries. This string is used when creating the column names - otherwise we wouldn't know what to call the columns.\n",
-    "\n",
     "Now we know how to create a bunch of feature specifications quickly! But with more features comes more computation. Let's look at caching next, so we can iterate on our datasets more quickly."
    ]
   },