Added explanations

Gradio_app.ipynb

@@ -17,14 +17,14 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 29,
+   "execution_count": 32,
    "metadata": {},
    "outputs": [
     {
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "Running on local URL:  http://127.0.0.1:7875\n",
+      "Running on local URL:  http://127.0.0.1:7878\n",
       "\n",
       "To create a public link, set `share=True` in `launch()`.\n"
      ]
@@ -32,7 +32,7 @@
     {
      "data": {
       "text/html": [
-       "<div><iframe src=\"http://127.0.0.1:7875/\" width=\"100%\" height=\"500\" allow=\"autoplay; camera; microphone; clipboard-read; clipboard-write;\" frameborder=\"0\" allowfullscreen></iframe></div>"
+       "<div><iframe src=\"http://127.0.0.1:7878/\" width=\"100%\" height=\"500\" allow=\"autoplay; camera; microphone; clipboard-read; clipboard-write;\" frameborder=\"0\" allowfullscreen></iframe></div>"
       ],
       "text/plain": [
        "<IPython.core.display.HTML object>"
@@ -45,9 +45,84 @@
      "data": {
       "text/plain": []
      },
-     "execution_count": 29,
+     "execution_count": 32,
      "metadata": {},
      "output_type": "execute_result"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Starting to download inventory\n",
+      "Finished downloading inventory\n",
+      "Processing CI.CCC...\n",
+      "Downloading waveform\n",
+      "Skipping CI_CCC_2019-07-04T17:33:40.494920Z\n",
+      "Processing CI.CLC...\n",
+      "Processing CI.JRC2...\n",
+      "Reading cached waveform\n",
+      "Added CI.JRC2 to the list of waveforms\n",
+      "Processing CI.LRL...\n",
+      "Reading cached waveform\n",
+      "Added CI.LRL to the list of waveforms\n",
+      "Processing CI.MPM...\n",
+      "Reading cached waveform\n",
+      "Processing CI.Q0072...\n",
+      "Reading cached waveform\n",
+      "Processing CI.SLA...\n",
+      "Reading cached waveform\n",
+      "Added CI.SLA to the list of waveforms\n",
+      "Processing CI.SRT...\n",
+      "Reading cached waveform\n",
+      "Added CI.SRT to the list of waveforms\n",
+      "Processing CI.TOW2...\n",
+      "Reading cached waveform\n",
+      "Added CI.TOW2 to the list of waveforms\n",
+      "Processing CI.WBM...\n",
+      "Downloading waveform\n",
+      "Skipping CI_WBM_2019-07-04T17:33:40.063616Z\n",
+      "Processing CI.WCS2...\n",
+      "Downloading waveform\n",
+      "Skipping CI_WCS2_2019-07-04T17:33:40.200958Z\n",
+      "Processing CI.WMF...\n",
+      "Reading cached waveform\n",
+      "Added CI.WMF to the list of waveforms\n",
+      "Processing CI.WNM...\n",
+      "Reading cached waveform\n",
+      "Processing CI.WRC2...\n",
+      "Downloading waveform\n",
+      "Skipping CI_WRC2_2019-07-04T17:33:38.698099Z\n",
+      "Processing CI.WRV2...\n",
+      "Reading cached waveform\n",
+      "Processing CI.WVP2...\n",
+      "Downloading waveform\n",
+      "Skipping CI_WVP2_2019-07-04T17:33:39.650402Z\n",
+      "Processing NP.1809...\n",
+      "Reading cached waveform\n",
+      "Processing NP.5419...\n",
+      "Reading cached waveform\n",
+      "Processing PB.B916...\n",
+      "Reading cached waveform\n",
+      "Processing PB.B917...\n",
+      "Reading cached waveform\n",
+      "Processing PB.B918...\n",
+      "Reading cached waveform\n",
+      "Processing PB.B921...\n",
+      "Reading cached waveform\n",
+      "Starting to run predictions\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "/var/folders/_g/3q5q8_dj0ydcpktxlwxb5vrh0000gq/T/ipykernel_27324/2440224661.py:224: FutureWarning: The input object of type 'Tensor' is an array-like implementing one of the corresponding protocols (`__array__`, `__array_interface__` or `__array_struct__`); but not a sequence (or 0-D). In the future, this object will be coerced as if it was first converted using `np.array(obj)`. To retain the old behaviour, you have to either modify the type 'Tensor', or assign to an empty array created with `np.empty(correct_shape, dtype=object)`.\n",
+      "  waveforms = np.array(waveforms)[selection_indexes]\n",
+      "/var/folders/_g/3q5q8_dj0ydcpktxlwxb5vrh0000gq/T/ipykernel_27324/2440224661.py:224: VisibleDeprecationWarning: Creating an ndarray from ragged nested sequences (which is a list-or-tuple of lists-or-tuples-or ndarrays with different lengths or shapes) is deprecated. If you meant to do this, you must specify 'dtype=object' when creating the ndarray.\n",
+      "  waveforms = np.array(waveforms)[selection_indexes]\n",
+      "/var/folders/_g/3q5q8_dj0ydcpktxlwxb5vrh0000gq/T/ipykernel_27324/2440224661.py:231: UserWarning: To copy construct from a tensor, it is recommended to use sourceTensor.clone().detach() or sourceTensor.clone().detach().requires_grad_(True), rather than torch.tensor(sourceTensor).\n",
+      "  waveforms = [torch.tensor(waveform) for waveform in waveforms]\n"
+     ]
     }
    ],
    "source": [
@@ -446,11 +521,14 @@
     "        button.click(mark_phases, inputs=[inputs, upload], outputs=outputs)\n",
     "        \n",
     "    with gr.Tab(\"Select earthquake from catalogue\"):\n",
-    "        gr.Markdown(\"\"\"\n",
-    "        Select an earthquake from the global earthquake catalogue and the app will download the waveform from the FDSN client of your choice.\n",
-    "        Pick data for each waveform is reported in seconds from the start of the waveform.\n",
-    "        Velocities are derived from distance and travel time determined by PhaseHunter picks ($v = \\mathrm{distance}/\\mathrm{predicted_pick_time}$).\n",
-    "        Backround of velocity plot is colored by DEM.\n",
+    "\n",
+    "        gr.HTML(\"\"\"\n",
+    "        <div style=\"padding: 20px; border-radius: 10px; font-size: 16px;\">\n",
+    "        <p style=\"font-weight: bold; font-size: 24px; margin-bottom: 20px;\">Using PhaseHunter to Analyze Seismic Waveforms</p>\n",
+    "        <p>Select an earthquake from the global earthquake catalogue and the app will download the waveform from the FDSN client of your choice. The app will use a velocity model of your choice to select appropriate time windows for each station within a specified radius of the earthquake.</p>\n",
+    "        <p>The app will then analyze the waveforms and mark the detected phases on the waveform. Pick data for each waveform is reported in seconds from the start of the waveform.</p>\n",
+    "        <p>Velocities are derived from distance and travel time determined by PhaseHunter picks (<span style=\"font-style: italic;\">v = distance/predicted_pick_time</span>). The background of the velocity plot is colored by DEM.</p>\n",
+    "        </div>\n",
     "        \"\"\")\n",
     "        with gr.Row(): \n",
     "            client_inputs = gr.Dropdown(\n",

app.py

@@ -394,7 +394,9 @@ with gr.Blocks() as demo:
         
     with gr.Tab("Select earthquake from catalogue"):
         gr.Markdown("""
-        Select an earthquake from the global earthquake catalogue and the app will download the waveform from the FDSN client of your choice.
+        Select an earthquake from the global earthquake catalogue and the app will download the waveform from the FDSN client of your choice. 
+        The app will use a velocity model of your choice to select appropriate time windows for each station within specify radius of the earthquake.
+        The app will then analyze the waveforms and mark the detected phases on the waveform.
         Pick data for each waveform is reported in seconds from the start of the waveform.
         Velocities are derived from distance and travel time determined by PhaseHunter picks ($v = \mathrm{distance}/\mathrm{predicted_pick_time}$).
         Backround of velocity plot is colored by DEM.