diff --git a/examples/PyMPDATA_examples/Olesik_et_al_2022/demo_make_plots.ipynb b/examples/PyMPDATA_examples/Olesik_et_al_2022/demo_make_plots.ipynb
index f021720f..87bb640b 100644
--- a/examples/PyMPDATA_examples/Olesik_et_al_2022/demo_make_plots.ipynb
+++ b/examples/PyMPDATA_examples/Olesik_et_al_2022/demo_make_plots.ipynb
@@ -18,7 +18,7 @@
},
{
"cell_type": "code",
- "execution_count": null,
+ "execution_count": 1,
"metadata": {},
"outputs": [],
"source": [
@@ -31,20 +31,12 @@
},
{
"cell_type": "code",
- "execution_count": null,
- "metadata": {},
- "outputs": [],
- "source": [
- "import os\n",
- "os.environ[\"NUMBA_DISABLE_JIT\"] = \"1\""
- ]
- },
- {
- "cell_type": "code",
- "execution_count": null,
+ "execution_count": 2,
"metadata": {},
"outputs": [],
"source": [
+ "import warnings\n",
+ "from numba.core.errors import NumbaExperimentalFeatureWarning\n",
"from matplotlib import pyplot\n",
"from open_atmos_jupyter_utils import show_plot\n",
"from PyMPDATA_examples.Olesik_et_al_2022.analysis import compute_figure_data, rel_disp, third_moment\n",
@@ -56,19 +48,21 @@
},
{
"cell_type": "code",
- "execution_count": null,
+ "execution_count": 3,
"metadata": {},
"outputs": [],
"source": [
"plot_steps = [0, 2, 5]\n",
"def compute_and_plot(psi_coord, grid_layout, n_bins, GC_max, variants, plots, filename):\n",
- " results, settings = compute_figure_data(\n",
- " psi_coord=psi_coord, \n",
- " grid_layouts=(grid_layout,),\n",
- " nr=n_bins,\n",
- " GC_max = GC_max,\n",
- " opt_set=tuple(default_opt_set[variant] for variant in variants)\n",
- " )\n",
+ " with warnings.catch_warnings():\n",
+ " warnings.simplefilter(\"ignore\", category=NumbaExperimentalFeatureWarning)\n",
+ " results, settings = compute_figure_data(\n",
+ " psi_coord=psi_coord, \n",
+ " grid_layouts=(grid_layout,),\n",
+ " nr=n_bins,\n",
+ " GC_max = GC_max,\n",
+ " opt_set=tuple(default_opt_set[variant] for variant in variants)\n",
+ " )\n",
" return_value = {}\n",
" for _, result in results.items():\n",
" out_steps = result['grid']['out_steps']\n",
@@ -127,7 +121,7 @@
},
{
"cell_type": "code",
- "execution_count": null,
+ "execution_count": 4,
"metadata": {},
"outputs": [],
"source": [
@@ -140,81 +134,28300 @@
},
{
"cell_type": "code",
- "execution_count": null,
+ "execution_count": 5,
"metadata": {},
- "outputs": [],
+ "outputs": [
+ {
+ "name": "stderr",
+ "output_type": "stream",
+ "text": [
+ "[Parallel(n_jobs=-2)]: Using backend ThreadingBackend with 11 concurrent workers.\n",
+ "[Parallel(n_jobs=-2)]: Done 1 tasks | elapsed: 14.3s\n"
+ ]
+ },
+ {
+ "data": {
+ "image/svg+xml": [
+ "\n",
+ "\n",
+ "\n"
+ ],
+ "text/plain": [
+ ""
+ ]
+ },
+ "metadata": {},
+ "output_type": "display_data"
+ },
+ {
+ "data": {
+ "application/vnd.jupyter.widget-view+json": {
+ "model_id": "85c6b6e7a4c548b29d42d0fd40a5aaac",
+ "version_major": 2,
+ "version_minor": 0
+ },
+ "text/plain": [
+ "HBox(children=(HTML(value=\"./fig_upwindb.pdf
\"), HTML(value…"
+ ]
+ },
+ "metadata": {},
+ "output_type": "display_data"
+ }
+ ],
"source": [
"compute_and_plot(**plot_setup_radius_linear, variants=('a',), plots=['n','m'], filename = 'fig_upwindb.pdf');"
]
},
{
"cell_type": "code",
- "execution_count": null,
+ "execution_count": 6,
"metadata": {},
- "outputs": [],
+ "outputs": [
+ {
+ "name": "stderr",
+ "output_type": "stream",
+ "text": [
+ "[Parallel(n_jobs=-2)]: Using backend ThreadingBackend with 11 concurrent workers.\n",
+ "[Parallel(n_jobs=-2)]: Done 1 tasks | elapsed: 0.1s\n"
+ ]
+ },
+ {
+ "data": {
+ "image/svg+xml": [
+ "\n",
+ "\n",
+ "\n"
+ ],
+ "text/plain": [
+ ""
+ ]
+ },
+ "metadata": {},
+ "output_type": "display_data"
+ },
+ {
+ "data": {
+ "application/vnd.jupyter.widget-view+json": {
+ "model_id": "e0c83cb875ea4cb7b381091f2f32bc13",
+ "version_major": 2,
+ "version_minor": 0
+ },
+ "text/plain": [
+ "HBox(children=(HTML(value=\"./fig_upwinda.pdf
\"), HTML(value…"
+ ]
+ },
+ "metadata": {},
+ "output_type": "display_data"
+ }
+ ],
"source": [
"table_data.append(compute_and_plot(**plot_setup_default, variants=('a',), plots=['n','m'], filename = 'fig_upwinda.pdf'))"
]
},
{
"cell_type": "code",
- "execution_count": null,
+ "execution_count": 7,
"metadata": {},
- "outputs": [],
+ "outputs": [
+ {
+ "name": "stderr",
+ "output_type": "stream",
+ "text": [
+ "[Parallel(n_jobs=-2)]: Using backend ThreadingBackend with 11 concurrent workers.\n",
+ "[Parallel(n_jobs=-2)]: Done 3 out of 3 | elapsed: 25.9s finished\n"
+ ]
+ },
+ {
+ "data": {
+ "image/svg+xml": [
+ "\n",
+ "\n",
+ "\n"
+ ],
+ "text/plain": [
+ ""
+ ]
+ },
+ "metadata": {},
+ "output_type": "display_data"
+ },
+ {
+ "data": {
+ "application/vnd.jupyter.widget-view+json": {
+ "model_id": "49539bc960dd4f8599029103ff57b909",
+ "version_major": 2,
+ "version_minor": 0
+ },
+ "text/plain": [
+ "HBox(children=(HTML(value=\"./fig_mpdatas.pdf
\"), HTML(value…"
+ ]
+ },
+ "metadata": {},
+ "output_type": "display_data"
+ }
+ ],
"source": [
"table_data.append(compute_and_plot(**plot_setup_default, variants=('a','b','g'), plots=['n'], filename = 'fig_mpdatas.pdf'))"
]
},
{
"cell_type": "code",
- "execution_count": null,
+ "execution_count": 8,
"metadata": {},
- "outputs": [],
+ "outputs": [
+ {
+ "name": "stderr",
+ "output_type": "stream",
+ "text": [
+ "[Parallel(n_jobs=-2)]: Using backend ThreadingBackend with 11 concurrent workers.\n",
+ "[Parallel(n_jobs=-2)]: Done 2 out of 2 | elapsed: 13.1s finished\n"
+ ]
+ },
+ {
+ "data": {
+ "image/svg+xml": [
+ "\n",
+ "\n",
+ "\n"
+ ],
+ "text/plain": [
+ ""
+ ]
+ },
+ "metadata": {},
+ "output_type": "display_data"
+ },
+ {
+ "data": {
+ "application/vnd.jupyter.widget-view+json": {
+ "model_id": "8ccca24931ec4b1899e1ee71b0e3c88b",
+ "version_major": 2,
+ "version_minor": 0
+ },
+ "text/plain": [
+ "HBox(children=(HTML(value=\"./fig_iga.pdf
\"), HTML(value=\"\n",
+ "\n",
+ "\n"
+ ],
+ "text/plain": [
+ ""
+ ]
+ },
+ "metadata": {},
+ "output_type": "display_data"
+ },
+ {
+ "data": {
+ "application/vnd.jupyter.widget-view+json": {
+ "model_id": "356604cb63764351bc38238afed9056f",
+ "version_major": 2,
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+ },
+ "text/plain": [
+ "HBox(children=(HTML(value=\"./fig_iga_fct.pdf
\"), HTML(value…"
+ ]
+ },
+ "metadata": {},
+ "output_type": "display_data"
+ }
+ ],
"source": [
"table_data.append(compute_and_plot(**plot_setup_default, variants=('c','d'), plots=['n'], filename = 'fig_iga_fct.pdf'))"
]
},
{
"cell_type": "code",
- "execution_count": null,
+ "execution_count": 10,
"metadata": {},
- "outputs": [],
+ "outputs": [
+ {
+ "name": "stderr",
+ "output_type": "stream",
+ "text": [
+ "[Parallel(n_jobs=-2)]: Using backend ThreadingBackend with 11 concurrent workers.\n",
+ "[Parallel(n_jobs=-2)]: Done 2 out of 2 | elapsed: 22.2s finished\n"
+ ]
+ },
+ {
+ "data": {
+ "image/svg+xml": [
+ "\n",
+ "\n",
+ "\n"
+ ],
+ "text/plain": [
+ ""
+ ]
+ },
+ "metadata": {},
+ "output_type": "display_data"
+ },
+ {
+ "data": {
+ "application/vnd.jupyter.widget-view+json": {
+ "model_id": "b6e3557d2a0849baa82d7e46d56b232f",
+ "version_major": 2,
+ "version_minor": 0
+ },
+ "text/plain": [
+ "HBox(children=(HTML(value=\"./fig_iga_fct_dpdc.pdf
\"), …"
+ ]
+ },
+ "metadata": {},
+ "output_type": "display_data"
+ }
+ ],
"source": [
"table_data.append(compute_and_plot(**plot_setup_default, variants=('d','e'), plots=['n'], filename = 'fig_iga_fct_dpdc.pdf'))"
]
},
{
"cell_type": "code",
- "execution_count": null,
+ "execution_count": 11,
"metadata": {},
- "outputs": [],
+ "outputs": [
+ {
+ "name": "stderr",
+ "output_type": "stream",
+ "text": [
+ "[Parallel(n_jobs=-2)]: Using backend ThreadingBackend with 11 concurrent workers.\n",
+ "[Parallel(n_jobs=-2)]: Done 2 out of 2 | elapsed: 13.7s finished\n"
+ ]
+ },
+ {
+ "data": {
+ "image/svg+xml": [
+ "\n",
+ "\n",
+ "\n"
+ ],
+ "text/plain": [
+ ""
+ ]
+ },
+ "metadata": {},
+ "output_type": "display_data"
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+ "data": {
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+ "version_major": 2,
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+ },
+ "text/plain": [
+ "HBox(children=(HTML(value=\"./fig_tot.pdf
\"), HTML(value=\"\n",
+ "\n",
+ "\n"
+ ],
+ "text/plain": [
+ ""
+ ]
+ },
+ "metadata": {},
+ "output_type": "display_data"
+ },
+ {
+ "data": {
+ "application/vnd.jupyter.widget-view+json": {
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+ "version_major": 2,
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+ },
+ "text/plain": [
+ "HBox(children=(HTML(value=\"./fig_multiopt.pdf
\"), HTML(val…"
+ ]
+ },
+ "metadata": {},
+ "output_type": "display_data"
+ }
+ ],
"source": [
"table_data.append(compute_and_plot(**plot_setup_default, variants=('f','h'), plots=['n'], filename = 'fig_multiopt.pdf'))"
]
},
{
"cell_type": "code",
- "execution_count": null,
+ "execution_count": 13,
"metadata": {},
- "outputs": [],
+ "outputs": [
+ {
+ "data": {
+ "image/svg+xml": [
+ "\n",
+ "\n",
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+ "text/plain": [
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+ "HBox(children=(HTML(value=\"./measures.pdf
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