reorder tutorial plots

Author: radka-j

docs/tutorials/emulation/01_quickstart.ipynb

@@ -123,7 +123,7 @@
    "outputs": [],
    "source": [
     "# Run AutoEmulate with default settings\n",
-    "ae = AutoEmulate(x, y, log_level=\"error\")"
+    "ae = AutoEmulate(x, y, models=[\"GPRBF\"], model_params={}, log_level=\"error\")"
    ]
   },
   {
@@ -235,14 +235,14 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "ae.plot(best, output_names=projectile.output_names, input_names=projectile.param_names)"
+    "ae.plot_preds(best, output_names=projectile.output_names)"
    ]
   },
   {
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "We can also subset the data included in the plots by providing input and output ranges."
+    "We can also visualise the predictions against each input feature."
    ]
   },
   {
@@ -251,14 +251,14 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "ae.plot(best, input_ranges={0: (0, 4), 1: (200, 500)}, output_ranges={0: (0, 10)})\n"
+    "ae.plot(best, output_names=projectile.output_names, input_names=projectile.param_names)"
    ]
   },
   {
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "Alternatively we can plot the predicted vs. true values for all outputs (not by feature)."
+    "We can subset the data included in the feature plots by providing input and output ranges."
    ]
   },
   {
@@ -267,7 +267,7 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "ae.plot_preds(best, output_names=projectile.output_names)"
+    "ae.plot(best, input_ranges={0: (0, 4), 1: (200, 500)}, output_ranges={0: (0, 10)})\n"
    ]
   },
   {
@@ -285,7 +285,7 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "ae.plot_surface(best.model, projectile.parameters_range, quantile=0.5)\n"
+    "ae.plot_surface(best.model, projectile.parameters_range, quantile=0.5)"
    ]
   },
   {