update plotly layout to make readable on mobile

content/english/blog/efficient-compression-event-based-data-neuromorphic-applications/plotting.ipynb

@@ -2,7 +2,7 @@
  "cells": [
   {
    "cell_type": "code",
-   "execution_count": 5,
+   "execution_count": null,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -21,14 +21,31 @@
     "    }\n",
     ")\n",
     "\n",
+    "# Shorten the names of the encodings and frameworks to make the plotly legend readable on mobile\n",
+    "dataframe.loc[dataframe[\"Encoding\"] == \"numpy/brotli (Q=1)\", \"Encoding\"] = \"brotli (Q=1)\"\n",
+    "dataframe.loc[dataframe[\"Encoding\"] == \"numpy/brotli (Q=6)\", \"Encoding\"] = \"brotli (Q=6)\"\n",
+    "dataframe.loc[dataframe[\"Encoding\"] == \"numpy/brotli (Q=11)\", \"Encoding\"] = \"brotli (Q=11)\"\n",
+    "dataframe.loc[dataframe[\"Encoding\"] == \"numpy (pickle)\", \"Encoding\"] = \"pickle\"\n",
+    "dataframe.loc[dataframe[\"Encoding\"] == \"numpy (UNDR)\", \"Encoding\"] = \"UNDR\"\n",
+    "dataframe.loc[dataframe[\"Framework\"] == \"numpy/brotli\", \"Framework\"] = \"brotli\"\n",
+    "dataframe.loc[dataframe[\"Encoding\"] == \"eventstream\", \"Encoding\"] = \"es\"\n",
+    "\n",
     "# temporary hack because I forgot to add the number of events to the results, \n",
     "# should be fixed in current version though\n",
     "if len(results) < 17:\n",
     "    number_of_events = 1e7\n",
     "else:\n",
     "    number_of_events = results[-1]\n",
     "\n",
-    "title = f\"Reading the same {round(number_of_events / 1e6)} million events from different file formats.\"\n",
+    "title = f\"Reading the same {round(number_of_events / 1e6)} million events from different file formats.\"\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
     "\n",
     "figure = plotly.express.scatter(\n",
     "    dataframe,\n",
@@ -39,11 +56,22 @@
     "    template=\"plotly_dark\",\n",
     "    title=title,\n",
     ")\n",
+    "figure.update_layout(\n",
+    "    # legend=dict(orientation=\"v\", yanchor=\"top\", y=0, xanchor=\"right\", x=0.99, entrywidth=0.8, entrywidthmode=\"fraction\"),\n",
+    "    margin=dict(l=10, r=10, t=80, b=10),\n",
+    ")\n",
     "figure.update_traces(marker_size=13)\n",
     "figure.write_json(\"file_read_benchmark.json\")\n",
     "# figure.update_layout(height=600, width=900)\n",
-    "# figure.write_image(\"file_read_benchmark.png\")\n",
-    "\n",
+    "# figure.write_image(\"file_read_benchmark.png\")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
     "\n",
     "figure = plotly.express.scatter(\n",
     "    dataframe,\n",
@@ -74,6 +102,13 @@
     "# figure.update_layout(height=600, width=900)\n",
     "# figure.write_image(\"file_read_benchmark_log.png\", scale=2)\n"
    ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": []
   }
  ],
  "metadata": {

content/english/blog/spiking-neural-network-framework-benchmarking/plotting.ipynb

@@ -56,6 +56,8 @@
     "fig.update_layout(\n",
     "    title=f\"8k neurons, 1 Linear + 1 LIF layer, {n_steps} time steps, batch size {batch_size}\",\n",
     "    xaxis={'categoryorder':'total ascending'},\n",
+    "    legend=dict(orientation=\"h\", yanchor=\"bottom\", y=1.01, xanchor=\"right\", x=1),\n",
+    "    margin=dict(l=10, r=10, t=80, b=10),\n",
     ")\n",
     "# increase size of facet titles\n",
     "fig.update_annotations(font_size=14)\n",
@@ -95,6 +97,8 @@
     "fig.update_layout(\n",
     "    title=f\"4k neurons, 1 Linear + 1 LIF layer, {n_steps} time steps, batch size {batch_size}\",\n",
     "    xaxis={'categoryorder':'total ascending'},\n",
+    "    legend=dict(orientation=\"h\", yanchor=\"bottom\", y=1.01, xanchor=\"right\", x=1),\n",
+    "    margin=dict(l=10, r=10, t=80, b=10),\n",
     ")\n",
     "# increase size of facet titles\n",
     "fig.update_annotations(font_size=14)\n",
@@ -134,7 +138,8 @@
     "fig.update_layout(\n",
     "    title=f\"512 neurons, 1 Linear + 1 LIF layer, {n_steps} time steps, batch size {batch_size}\",\n",
     "    xaxis={'categoryorder':'total ascending'},\n",
-    "    yaxis_title=\"Time [s]\",\n",
+    "    legend=dict(orientation=\"h\", yanchor=\"bottom\", y=1.01, xanchor=\"right\", x=1),\n",
+    "    margin=dict(l=10, r=10, t=80, b=10),\n",
     ")\n",
     "# increase size of facet titles\n",
     "fig.update_annotations(font_size=14)\n",