fix-notebookrun: update notebook TimeSeriesEDF content for testing

the-virtual-brain · Jul 31, 2024 · d6df191 · d6df191
1 parent ecffbbf
commit d6df191
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Showing 2 changed files with 15 additions and 73 deletions.
diff --git a/.github/workflows/notebooks.yml b/.github/workflows/notebooks.yml
@@ -25,6 +25,4 @@ jobs:
           python -m pip install nbformat nbconvert
 
       - name: Run notebooks
-        run: | 
-          cd notebooks
-          python ../dev/notebook_runner.py .
+        run: python ./dev/notebook_runner.py notebooks
diff --git a/notebooks/TimeSeriesEDF.ipynb b/notebooks/TimeSeriesEDF.ipynb
@@ -26,7 +26,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 1,
+   "execution_count": null,
    "id": "56d5c4b6-7804-46d6-931f-fcc5593977d1",
    "metadata": {},
    "outputs": [],
@@ -36,26 +36,13 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 2,
+   "execution_count": null,
    "id": "28420169-2274-4e0e-a73d-c1ab54e6da9c",
    "metadata": {
     "scrolled": true,
     "tags": []
    },
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "17-04-2024 05:02:37 - DEBUG - tvbwidgets - Package is not fully installed\n",
-      "17-04-2024 05:02:37 - DEBUG - tvbwidgets - Version read from the internal package.json file\n",
-      "17-04-2024 05:02:37 - INFO - tvbwidgets - Version: 2.0.0\n",
-      "Using matplotlib as 2D backend.\n",
-      "   INFO  Cannot import syncrypto library.\n",
-      "17-04-2024 05:02:49 - INFO - tvbwidgets.core.pse.parameters - ImportError: Dask dependency is not included, so this functionality won't be available\n"
-     ]
-    }
-   ],
+   "outputs": [],
    "source": [
     "import numpy as np\n",
     "from tvbwidgets.api import plot_timeseries\n",
@@ -72,45 +59,27 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 3,
+   "execution_count": null,
    "id": "94687d23-0222-4e9f-887e-e97169737304",
    "metadata": {
     "tags": []
    },
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "Extracting EDF parameters from C:\\Work\\TVB\\tvb-widgets\\tvbwidgets\\tests\\data\\test_file.edf...\n",
-      "EDF file detected\n",
-      "Setting channel info structure...\n",
-      "Creating raw.info structure...\n"
-     ]
-    }
-   ],
+   "outputs": [],
    "source": [
-    "edf_file_path = '../tvbwidgets/tests/data/test_file.edf' # replace path with your actual EDF file path\n",
+    "edf_file_path = 'tvbwidgets/tests/data/test_file.edf' # replace path with your actual EDF file path\n",
+    "                                                      # set this path file for notebooks tests\n",
+    "# you can use: '../tvbwidgets/tests/data/test_file.edf'\n",
     "data, freq, index = read_edf_file(edf_file_path)"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 4,
+   "execution_count": null,
    "id": "12da93b3-f96f-44cf-8555-52eee8aaecfd",
    "metadata": {
     "tags": []
    },
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "(92000, 32)\n",
-      "400.0\n"
-     ]
-    }
-   ],
+   "outputs": [],
    "source": [
     "print(data.shape)\n",
     "print(freq)"
@@ -126,7 +95,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 5,
+   "execution_count": null,
    "id": "cac83fe3-b4fe-486a-8955-70203dda1004",
    "metadata": {},
    "outputs": [],
@@ -136,35 +105,10 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 6,
+   "execution_count": null,
    "id": "20c3eae2-49dd-4d01-af9a-06a0dba15888",
    "metadata": {},
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "17-04-2024 05:02:49 - INFO - tvbwidgets.ui.ts.plotly_ts_widget - TimeSeries Widget with Plotly initialized\n",
-      "Creating RawArray with float64 data, n_channels=32, n_times=92000\n",
-      "    Range : 0 ... 91999 =      0.000 ...   229.998 secs\n",
-      "Ready.\n"
-     ]
-    },
-    {
-     "data": {
-      "application/vnd.jupyter.widget-view+json": {
-       "model_id": "28d8ffb85be94f28b59e85b521e4aeeb",
-       "version_major": 2,
-       "version_minor": 0
-      },
-      "text/plain": [
-       "TimeSeriesWidgetPlotly(children=(HBox(children=(Output(),)), VBox(children=(Dropdown(description='Colormap:', …"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    }
-   ],
+   "outputs": [],
    "source": [
     "tsw = plot_timeseries(data=data, sample_freq=freq, ch_idx=index, backend=backend)"
    ]
@@ -194,7 +138,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.9.18"
+   "version": "3.9.19"
   }
  },
  "nbformat": 4,