rerun notebooks and clear numba warnings

open-atmos · Dec 10, 2024 · 178a828 · 178a828
1 parent 8d28db4
commit 178a828
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Showing 11 changed files with 1,632 additions and 326 deletions.
diff --git a/examples/PySDM_examples/Arabas_et_al_2015/paraview_hello_world.ipynb b/examples/PySDM_examples/Arabas_et_al_2015/paraview_hello_world.ipynb
@@ -264,20 +264,15 @@
   {
    "cell_type": "code",
    "id": "23e0cf61",
-   "metadata": {
-    "ExecuteTime": {
-     "end_time": "2024-12-08T22:48:58.129587Z",
-     "start_time": "2024-12-08T22:48:58.078686Z"
-    }
-   },
+   "metadata": {},
    "source": [
     "if platform.system() != 'Windows':\n",
     "    for file in glob.glob('output/anim_frame_*.pdf'):\n",
     "        subprocess.run(['ps2pdf', file, file+'_'], capture_output=True, check=True)\n",
     "        subprocess.run(['mv', file+'_', file], check=True)"
    ],
    "outputs": [],
-   "execution_count": 12
+   "execution_count": null
   },
   {
    "cell_type": "code",

diff --git a/examples/PySDM_examples/Arabas_et_al_2023/copula_hello.ipynb b/examples/PySDM_examples/Arabas_et_al_2023/copula_hello.ipynb
diff --git a/examples/PySDM_examples/Arabas_et_al_2023/fig_A2.ipynb b/examples/PySDM_examples/Arabas_et_al_2023/fig_A2.ipynb
@@ -17,7 +17,12 @@
    "id": "c6f48049ea08fe2e"
   },
   {
-   "metadata": {},
+   "metadata": {
+    "ExecuteTime": {
+     "end_time": "2024-12-10T19:07:17.683093Z",
+     "start_time": "2024-12-10T19:07:17.680958Z"
+    }
+   },
    "cell_type": "code",
    "source": [
     "import sys\n",
@@ -28,12 +33,17 @@
    ],
    "id": "dba473e974480091",
    "outputs": [],
-   "execution_count": null
+   "execution_count": 1
   },
   {
    "cell_type": "code",
    "id": "7ea1f100",
-   "metadata": {},
+   "metadata": {
+    "ExecuteTime": {
+     "end_time": "2024-12-10T19:07:18.553880Z",
+     "start_time": "2024-12-10T19:07:17.688797Z"
+    }
+   },
    "source": [
     "import os\n",
     "import itertools\n",
@@ -51,12 +61,17 @@
     "from open_atmos_jupyter_utils import show_plot"
    ],
    "outputs": [],
-   "execution_count": null
+   "execution_count": 2
   },
   {
    "cell_type": "code",
    "id": "a56c35fe",
-   "metadata": {},
+   "metadata": {
+    "ExecuteTime": {
+     "end_time": "2024-12-10T19:07:18.616824Z",
+     "start_time": "2024-12-10T19:07:18.613867Z"
+    }
+   },
    "source": [
     "CI = 'CI' in os.environ\n",
     "\n",
@@ -83,12 +98,19 @@
     "    return np.sqrt(np.mean(np.square(actual - expected)))"
    ],
    "outputs": [],
-   "execution_count": null
+   "execution_count": 3
   },
   {
    "cell_type": "code",
    "id": "6c3ba75d",
-   "metadata": {},
+   "metadata": {
+    "jupyter": {
+     "is_executing": true
+    },
+    "ExecuteTime": {
+     "start_time": "2024-12-10T19:07:18.628649Z"
+    }
+   },
    "source": [
     "cases = tuple({\"dt\": dt, \"N\": mlt, \"seed\": seed} for dt, mlt, seed in itertools.product(DTS, MLT, SEEDS))\n",
     "\n",
@@ -146,7 +168,23 @@
     "with open('output.pkl','wb') as file:\n",
     "    pickle.dump(output, file)"
    ],
-   "outputs": [],
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "5:262144:0 ...\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "/Users/agnieszkazaba/PycharmProjects/PySDM/PySDM/backends/thrust_rtc.py:74: UserWarning: CUDA is not available, using FakeThrustRTC!\n",
+      "  warnings.warn(\"CUDA is not available, using FakeThrustRTC!\")\n"
+     ]
+    }
+   ],
    "execution_count": null
   },
   {

diff --git a/examples/PySDM_examples/Bartman_et_al_2021/demo.ipynb b/examples/PySDM_examples/Bartman_et_al_2021/demo.ipynb
@@ -18,7 +18,12 @@
   },
   {
    "cell_type": "code",
-   "metadata": {},
+   "metadata": {
+    "ExecuteTime": {
+     "end_time": "2024-12-10T19:08:53.936568Z",
+     "start_time": "2024-12-10T19:08:53.928270Z"
+    }
+   },
    "source": [
     "import sys\n",
     "if 'google.colab' in sys.modules:\n",
@@ -27,11 +32,16 @@
     "    pip_install_on_colab('PySDM-examples')"
    ],
    "outputs": [],
-   "execution_count": null
+   "execution_count": 1
   },
   {
    "cell_type": "code",
-   "metadata": {},
+   "metadata": {
+    "ExecuteTime": {
+     "end_time": "2024-12-10T19:08:56.943705Z",
+     "start_time": "2024-12-10T19:08:53.955929Z"
+    }
+   },
    "source": [
     "from PySDM_examples.Arabas_et_al_2015 import Settings, SpinUp\n",
     "from PySDM_examples.Szumowski_et_al_1998 import Simulation, Storage\n",
@@ -50,7 +60,7 @@
     "from matplotlib.gridspec import GridSpec"
    ],
    "outputs": [],
-   "execution_count": null
+   "execution_count": 2
   },
   {
    "cell_type": "code",
@@ -92,27 +102,72 @@
   },
   {
    "cell_type": "code",
-   "metadata": {},
+   "metadata": {
+    "ExecuteTime": {
+     "end_time": "2024-12-10T19:10:16.997824Z",
+     "start_time": "2024-12-10T19:09:05.454322Z"
+    }
+   },
    "source": [
     "simulation.run(ProgBarController())"
    ],
-   "outputs": [],
-   "execution_count": null
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "FloatProgress(value=0.0, max=1.0)"
+      ],
+      "application/vnd.jupyter.widget-view+json": {
+       "version_major": 2,
+       "version_minor": 0,
+       "model_id": "3c3c15bac3554992a2fd3561f7f01169"
+      }
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "execution_count": 4
   },
   {
    "cell_type": "code",
-   "metadata": {},
+   "metadata": {
+    "ExecuteTime": {
+     "end_time": "2024-12-10T19:10:17.100250Z",
+     "start_time": "2024-12-10T19:10:17.027190Z"
+    }
+   },
    "source": [
     "temp_file = TemporaryFile('.nc')\n",
     "exporter = NetCDFExporter(storage, settings, simulation, temp_file.absolute_path)\n",
     "exporter.run(ProgBarController())"
    ],
-   "outputs": [],
-   "execution_count": null
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "FloatProgress(value=0.0, max=1.0)"
+      ],
+      "application/vnd.jupyter.widget-view+json": {
+       "version_major": 2,
+       "version_minor": 0,
+       "model_id": "f6e74820c325436f89cb745ba26a8ac5"
+      }
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "execution_count": 5
   },
   {
    "cell_type": "code",
-   "metadata": {},
+   "metadata": {
+    "ExecuteTime": {
+     "end_time": "2024-12-10T19:10:17.308418Z",
+     "start_time": "2024-12-10T19:10:17.105187Z"
+    }
+   },
    "source": [
     "default_figsize = rcParams[\"figure.figsize\"]\n",
     "figsize = (1.75 * default_figsize[0], 3.1* default_figsize[1])\n",
@@ -176,7 +231,7 @@
     "pyplot.close(fig)"
    ],
    "outputs": [],
-   "execution_count": null
+   "execution_count": 6
   },
   {
    "cell_type": "code",
@@ -197,8 +252,8 @@
    "cell_type": "code",
    "metadata": {
     "ExecuteTime": {
-     "end_time": "2024-12-08T22:55:44.806466Z",
-     "start_time": "2024-12-08T22:55:41.828713Z"
+     "end_time": "2024-12-10T19:15:11.015148Z",
+     "start_time": "2024-12-10T19:15:10.681211Z"
     }
    },
    "source": [
@@ -211,19 +266,19 @@
     {
      "data": {
       "text/plain": [
-       "HTML(value=\"<a href='./tmpnde48zdo.svg' target='_blank'>./tmpnde48zdo.svg</a><br>\")"
+       "HTML(value=\"<a href='./tmp61kw9k3q.svg' target='_blank'>./tmp61kw9k3q.svg</a><br>\")"
       ],
       "application/vnd.jupyter.widget-view+json": {
        "version_major": 2,
        "version_minor": 0,
-       "model_id": "7391d5bb2d2f46758a7fbb7cbfd010a7"
+       "model_id": "7b2ea768988f432ebada3f9b5d50a865"
       }
      },
      "metadata": {},
      "output_type": "display_data"
     }
    ],
-   "execution_count": 8
+   "execution_count": 13
   },
   {
    "metadata": {},