save as csv

parse_exported.ipynb

@@ -33,7 +33,9 @@
     "import numpy as np\n",
     "\n",
     "\n",
-    "def to_scatter(key: str, dev_history: AwkwardArray, plot_key: Literal[\"value\", \"rssi\"] = \"value\") -> go.Scatter:\n",
+    "def to_scatter(\n",
+    "    key: str, dev_history: AwkwardArray, plot_key: Literal[\"value\", \"rssi\"] = \"value\"\n",
+    ") -> go.Scatter:\n",
     "    x = ak.to_numpy(dev_history[\"time\"])\n",
     "    if plot_key == \"rssi\":\n",
     "        y = ak.to_numpy(dev_history[\"rssi\"])\n",
@@ -43,6 +45,7 @@
     "        raise ValueError(f\"Unknown plot_key: {plot_key}\")\n",
     "    return go.Scatter(x=x, y=y, mode=\"lines+markers\", name=key)\n",
     "\n",
+    "\n",
     "scatters: list[go.Scatter] = []\n",
     "for k in data.fields:\n",
     "    val = data[k]\n",
@@ -59,6 +62,33 @@
    "source": [
     "display(fig)"
    ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import csv\n",
+    "def dump_as_csv(mac:str, device_record: AwkwardRecord, filename:str):\n",
+    "    time = ak.to_numpy(device_record[mac][\"time\"]) # type: ignore\n",
+    "    value = ak.to_numpy(device_record[mac][\"value\"]) # type: ignore\n",
+    "    rssi = ak.to_numpy(device_record[mac][\"rssi\"]) # type: ignore\n",
+    "    with open(filename, \"w\") as f:\n",
+    "        writer = csv.writer(f)\n",
+    "        writer.writerow([\"time\", \"value\", \"rssi\"])\n",
+    "        for t, v, r in zip(time, value, rssi):\n",
+    "            writer.writerow([t, v, r])"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "dump_as_csv(\"A09E1AE4E710\", data, \"A09E1AE4E710.csv\")"
+   ]
   }
  ],
  "metadata": {