From 574ce175b0ff52b6096a968fbb2713cd8307804b Mon Sep 17 00:00:00 2001 From: tomsail Date: Mon, 15 Jul 2024 07:33:37 +0200 Subject: [PATCH] add iceland --- Iceland.html | 11949 ++++++++++++++++++++++++++++++++++++++++++++++++ Iceland.ipynb | 702 +++ index.html | 1 + 3 files changed, 12652 insertions(+) create mode 100644 Iceland.html create mode 100644 Iceland.ipynb diff --git a/Iceland.html b/Iceland.html new file mode 100644 index 0000000..3bf4f98 --- /dev/null +++ b/Iceland.html @@ -0,0 +1,11949 @@ + + + + + +Iceland + + + + + + + + + + + + +
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+ + diff --git a/Iceland.ipynb b/Iceland.ipynb new file mode 100644 index 0000000..7b806a5 --- /dev/null +++ b/Iceland.ipynb @@ -0,0 +1,702 @@ +{ + "cells": [ + { + "cell_type": "code", + "execution_count": null, + "id": "82beda27-ce43-44ca-a7b4-d705469916fa", + "metadata": {}, + "outputs": [], + "source": [ + "import glob\n", + "import os\n", + "import io\n", + "import pymap3d\n", + "\n", + "import cartopy.feature as cf\n", + "import geopandas as gpd\n", + "import holoviews as hv\n", + "import hvplot.pandas\n", + "import hvplot.xarray\n", + "import numpy as np\n", + "import pandas as pd\n", + "import shapely\n", + "import thalassa\n", + "import xarray as xr\n", + "\n", + "import searvey\n", + "\n", + "import pyposeidon\n", + "import pyposeidon.meteo as pmeteo\n", + "import pyposeidon.dem as pdem\n", + "import pyposeidon.boundary as pbound\n", + "import pyposeidon.mesh as pmesh\n", + "import pyposeidon.model as pmodel\n", + "from pyposeidon.utils import cast\n", + "\n", + "import pyposeidon.utils.hplot as hplot\n", + "import pyposeidon.utils.pplot as pplot\n", + "\n", + "hv.extension(\"bokeh\")\n", + "\n", + "!mkdir -p data/iceland" + ] + }, + { + "cell_type": "markdown", + "id": "472bb041-4b91-471f-a09f-45eb2b4acd78", + "metadata": { + "execution": { + "iopub.execute_input": "2024-07-10T14:25:52.300893Z", + "iopub.status.busy": "2024-07-10T14:25:52.300644Z", + "iopub.status.idle": "2024-07-10T14:25:52.332912Z", + "shell.execute_reply": "2024-07-10T14:25:52.332032Z", + "shell.execute_reply.started": "2024-07-10T14:25:52.300869Z" + } + }, + "source": [ + "# Geometry" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "7b7d8fa2-d30c-449d-b000-f4bf316ca909", + "metadata": {}, + "outputs": [], + "source": [ + "lon_min = -28.0\n", + "lon_max = -11.1\n", + "lat_min = 62.0\n", + "lat_max = 68.0\n", + "\n", + "bbox = shapely.box(lon_min, lat_min, lon_max, lat_max)\n", + "geometry = dict(lon_min=lon_min, lon_max=lon_max, lat_min=lat_min, lat_max=lat_max)" + ] + }, + { + "cell_type": "markdown", + "id": "6a61f1c2-171a-48c3-9af0-b346cf561237", + "metadata": {}, + "source": [ + "# Coastlines" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "4709fe5f", + "metadata": {}, + "outputs": [], + "source": [ + "OSM_FOLDER = \"/home/tomsail/work/python/seareport_org/coastlines/raw/osm/land-polygons-complete-4326\"" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "46e368f3-cd56-4323-8197-30c3c3d26553", + "metadata": {}, + "outputs": [], + "source": [ + "coastlines = gpd.read_file(OSM_FOLDER + \"/land_polygons.shp\", bbox=bbox)\n", + "coastlines" + ] + }, + { + "cell_type": "markdown", + "id": "c0ce789c-a522-4a49-9d45-fd487d27c830", + "metadata": { + "execution": { + "iopub.execute_input": "2024-07-10T14:26:41.790292Z", + "iopub.status.busy": "2024-07-10T14:26:41.789720Z", + "iopub.status.idle": "2024-07-10T14:26:41.818903Z", + "shell.execute_reply": "2024-07-10T14:26:41.818384Z", + "shell.execute_reply.started": "2024-07-10T14:26:41.790214Z" + } + }, + "source": [ + "# Boundaries" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "b78eb9c5-22b6-4f05-9f45-6ffd684af9b6", + "metadata": {}, + "outputs": [], + "source": [ + "boundary = pbound.Boundary(geometry=geometry, coastlines=coastlines)\n", + "boundary.contours.head()\n", + "len(boundary.contours)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "79adcfc1-f974-4d37-9b0b-88e06e544943", + "metadata": {}, + "outputs": [], + "source": [ + "boundary.show()" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "f735e7ee-c001-40f0-aec8-632a1f0bbd6a", + "metadata": {}, + "outputs": [], + "source": [ + "# boundary.contours.hvplot(geo=True, tiles=True, frame_height=500)" + ] + }, + { + "cell_type": "markdown", + "id": "0a581850-d139-4f52-9dcb-b8b866c40905", + "metadata": {}, + "source": [ + "# DEM" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "d4c6e7a4-e435-443c-8412-65329d7a928f", + "metadata": {}, + "outputs": [], + "source": [ + "# url = \"https://coastwatch.pfeg.noaa.gov/erddap/griddap/srtm30plus\"\n", + "url = \"data/iceland.nc\"\n", + "dem = pdem.Dem(dem_source=url, **geometry)\n", + "dem.Dataset.load()" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "5fcdf1f5", + "metadata": {}, + "outputs": [], + "source": [ + "dem.Dataset.to_netcdf(\"./data/iceland/dem.nc\")" + ] + }, + { + "cell_type": "markdown", + "id": "c8e13b4f-5e85-459a-b86c-45a30a1f8aa2", + "metadata": {}, + "source": [ + "# Mesh" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "d9665b26-4b56-497f-9461-7adfa8898b12", + "metadata": {}, + "outputs": [], + "source": [ + "mesh = pmesh.set(\n", + " mesh_generator='oceanmesh',\n", + " bgmesh = \"om\",\n", + " dem_source=\"./data/iceland/dem.nc\",\n", + " type='tri2d',\n", + " geometry=geometry,\n", + " coastlines=coastlines,\n", + " grad = 0.15,\n", + " bathy_gradient= True,\n", + " resolution_min=0.02,\n", + " resolution_max=1.50,\n", + " alpha_wavelength= 100, # number of element to resolve WL\n", + " alpha_slope= 10, # number of element to resolve bathy gradient\n", + ")\n", + "mesh.Dataset.dims" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "5386162e", + "metadata": {}, + "outputs": [], + "source": [ + "mesh.Dataset.pplot.mesh()" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "cc9478be-2bfe-4060-9e8c-c91d1230a5ac", + "metadata": {}, + "outputs": [], + "source": [ + "mesh.to_file('./data/iceland/hgrid.gr3')\n", + "!head ./data/iceland/hgrid.gr3" + ] + }, + { + "cell_type": "markdown", + "id": "88223b90-0fa6-43d3-b739-61f30d9f4b0e", + "metadata": {}, + "source": [ + "### Fix bathy" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "7e91ddf8-72be-484f-ad20-ccc3bd007d7d", + "metadata": {}, + "outputs": [], + "source": [ + "#define in a dictionary the properties of the model..\n", + "model_parameters = {\n", + " \"solver_name\": \"telemac\",\n", + " \"rpath\": \"./data/iceland/\",\n", + " \"dem_source\": \"./data/iceland/dem.nc\",\n", + " \"mesh_file\": \"./data/iceland/hgrid.gr3\",\n", + " \"update\": [\"dem\"], #set which component should be updated (meteo,dem,model)\n", + " \"start_date\": \"2018-10-01T00:00:00\",\n", + " \"time_frame\": \"1d\",\n", + " \"global\": False,\n", + "}\n", + "model_parameters" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "67ac2c07-bb87-4338-a155-de5a362fde9a", + "metadata": {}, + "outputs": [], + "source": [ + "model = pmodel.set(**model_parameters)\n", + "model.create()\n", + "model.mesh.to_file('./data/iceland/hgrid.gr3')\n", + "!head ./data/iceland/hgrid.gr3" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "113fe1f8-f5c0-44e1-a916-6b431c786145", + "metadata": {}, + "outputs": [], + "source": [ + "def parse_hgrid_nodes(path: os.PathLike[str] | str) -> pd.DataFrame:\n", + " with open(path, \"rb\") as fd:\n", + " _ = fd.readline()\n", + " _, no_points = map(int, fd.readline().strip().split(b\" \"))\n", + " content = io.BytesIO(b''.join(next(fd) for _ in range(no_points)))\n", + " nodes = pd.read_csv(\n", + " content,\n", + " engine=\"pyarrow\",\n", + " sep=\"\\t\",\n", + " header=None,\n", + " names=[\"lon\", \"lat\", \"depth\"],\n", + " index_col=0\n", + " )\n", + " nodes = nodes.reset_index(drop=True)\n", + " return nodes\n", + " \n", + "def parse_hgrid_elements3(path: os.PathLike[str] | str) -> pd.DataFrame:\n", + " with open(path, \"rb\") as fd:\n", + " _ = fd.readline()\n", + " no_elements, no_points = map(int, fd.readline().strip().split(b\" \"))\n", + " for _ in range(no_points):\n", + " next(fd) \n", + " content = io.BytesIO(b''.join(next(fd) for _ in range(no_elements)))\n", + " elements = pd.read_csv(\n", + " content,\n", + " engine=\"pyarrow\",\n", + " sep=\"\\t\",\n", + " header=None,\n", + " names=[\"no_nodes\", \"n1\", \"n2\", \"n3\"],\n", + " index_col=0\n", + " )\n", + " elements = elements.assign(\n", + " n1=elements.n1 - 1,\n", + " n2=elements.n2 - 1,\n", + " n3=elements.n3 - 1,\n", + " ).reset_index(drop=True)\n", + " return elements\n", + "\n", + "def get_skews_and_base_cfls(lons, lats, depths) -> np.ndarray:\n", + " # The shape of each one of the input arrays needs to be (3, )\n", + " #ell = pymap3d.Ellipsoid.from_name(\"wgs84\")\n", + " ell = pymap3d.Ellipsoid(6378206.4, 6378206.4, \"schism\", \"schism\")\n", + " local_x, local_y, _ = pymap3d.geodetic2enu(lats, lons, depths, lats[0], lons[0], depths[0], ell=ell)\n", + " areas = (local_x[1] * local_y[2] - local_x[2] * local_y[1]) * 0.5\n", + " rhos = np.sqrt(areas / np.pi)\n", + " max_sides = np.maximum(\n", + " np.sqrt(local_x[1] ** 2 + local_y[1] ** 2),\n", + " np.sqrt(local_x[2] ** 2 + local_y[2] ** 2),\n", + " np.sqrt((local_x[2] - local_x[1]) ** 2 + (local_y[2] - local_y[1]) ** 2),\n", + " )\n", + " skews = max_sides / rhos\n", + " base_cfls = np.sqrt(9.81 * np.maximum(0.1, depths.mean(axis=0))) / rhos / 2\n", + " return skews, base_cfls\n", + "\n", + "def get_skews_and_base_cfls_from_path(path: os.PathLike[str] | str) -> np.ndarray:\n", + " nodes = parse_hgrid_nodes(path)\n", + " elements = parse_hgrid_elements3(path)\n", + " tri = elements[[\"n1\", \"n2\", \"n3\"]].values\n", + " lons = nodes.lon.values[tri].T\n", + " lats = nodes.lat.values[tri].T\n", + " depths = nodes.depth.values[tri].T\n", + " skews, base_cfls = get_skews_and_base_cfls(lons=lons, lats=lats, depths=depths)\n", + " return skews, base_cfls\n", + " " + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "7e7a4f00-01da-4a80-9825-23abf9df1c99", + "metadata": {}, + "outputs": [], + "source": [ + "skews, base_cfls = get_skews_and_base_cfls_from_path(\"./data/iceland/hgrid.gr3\")\n", + "CFL_THRESHOLD = 0.4\n", + "print(f\"elements violating CFL threshold < {CFL_THRESHOLD}\")\n", + "print(\"time N %\")\n", + "for dt in (1, 50, 75, 100, 120, 150, 200, 300, 400, 600, 900, 1200, 1800, 3600):\n", + " violations = (base_cfls * dt < CFL_THRESHOLD).sum()\n", + " print(f\"{dt:>4d} {violations:>12d} {violations / len(base_cfls) * 100:>8.2f}%\")\n", + " " + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "d50c240d-24f4-4b30-82b7-6f6d7b100fd0", + "metadata": {}, + "outputs": [], + "source": [ + "pd.DataFrame({\"skew\": skews}).describe([0.25, 0.5, 0.75, 0.9, 0.95, 0.99, 0.995, 0.999])" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "eaae98ef", + "metadata": {}, + "outputs": [], + "source": [ + "def get_meta() -> gpd.GeoDataFrame:\n", + " meta_web = searvey.get_ioc_stations().drop(columns=[\"lon\", \"lat\"])\n", + " meta_api = (\n", + " pd.read_json(\n", + " \"http://www.ioc-sealevelmonitoring.org/service.php?query=stationlist&showall=all\"\n", + " )\n", + " .drop_duplicates()\n", + " .drop(columns=[\"lon\", \"lat\"])\n", + " .rename(columns={\"Code\": \"ioc_code\", \"Lon\": \"longitude\", \"Lat\": \"latitude\"})\n", + " )\n", + " merged = pd.merge(\n", + " meta_web,\n", + " meta_api[[\"ioc_code\", \"longitude\", \"latitude\"]].drop_duplicates(),\n", + " on=[\"ioc_code\"],\n", + " )\n", + " updated = merged.assign(\n", + " geometry=gpd.points_from_xy(merged.longitude, merged.latitude, crs=\"EPSG:4326\")\n", + " )\n", + " return updated\n", + "\n", + "ioc_ = get_meta()\n", + "ioc_[bbox.contains(ioc_.geometry)].to_csv('data/iceland/stations.csv')" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "fb76718f-7816-46f1-8f54-72ba32433239", + "metadata": {}, + "outputs": [], + "source": [ + "#define in a dictionary the properties of the model..\n", + "model_parameters = {\n", + " \"solver_name\": \"telemac\",\n", + " \"tag\": \"telemac2d\",\n", + " \"rpath\": \"./data/iceland/20181001\",\n", + " \"mesh_file\": \"./data/iceland/hgrid.gr3\",\n", + " \"update\": [\"all\"], #set which component should be updated (meteo,dem,model)\n", + " \"meteo_source\": glob.glob(\"data/uvp_*.grib\"),\n", + " \"meteo_merge\": \"last\", # combine meteo\n", + " \"meteo_combine_by\": \"nested\",\n", + " \"meteo_xr_kwargs\": {\"concat_dim\": \"step\"},\n", + " \"start_date\": \"2018-10-01T00:00:00\",\n", + " \"time_frame\": \"2d\",\n", + " \"obs\": \"data/iceland/stations.csv\",\n", + " \"monitor\": True,\n", + " \"parameters\": {\n", + " \"dt\": 100\n", + " }\n", + "}\n", + "model_parameters" + ] + }, + { + "cell_type": "markdown", + "id": "05b44459", + "metadata": {}, + "source": [ + "## run days 1&2" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "0ee58df7", + "metadata": {}, + "outputs": [], + "source": [ + "a = pmodel.set(**model_parameters)\n", + "a.create()\n", + "# IMPORTANT! Here, for a simple surge application, \n", + "# we will need close all boundaries, otherwise the \n", + "# model will run out of water\n", + "a.mesh.Dataset.type[:] = 'closed' # it will create a cli file with all boundaries closed (this can be done only once)\n", + "# we also need to drop some meteo variables, it is necesarry for zarr export\n", + "a.output(**{\"global\": False})\n", + "a.set_obs()\n", + "a.save() # saves the json model file\n", + "a.run() # runs the model" + ] + }, + { + "cell_type": "markdown", + "id": "c13a8dfb", + "metadata": {}, + "source": [ + "## run days 3&4 from hotstart" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "a64f3563", + "metadata": {}, + "outputs": [], + "source": [ + "# restart model\n", + "prev_ = pd.Timestamp('2018-10-01')\n", + "next_ = pd.Timestamp('2018-10-03')\n", + "end_ = pd.Timestamp('2018-10-05')\n", + "ppath = os.path.join('data/iceland', prev_.strftime(\"%Y%m%d\"))\n", + "npath = os.path.join('data/iceland', next_.strftime(\"%Y%m%d\"))\n", + "m = pyposeidon.model.read(os.path.join(ppath, \"telemac2d_model.json\"))\n", + "meteo = pmeteo.Meteo(glob.glob(\"data/uvp_*.grib\"),meteo_merge= \"last\", meteo_combine_by= \"nested\", meteo_xr_kwargs= {\"concat_dim\": \"step\"},)\n", + "rs = cast.set(\n", + " solver_name=\"telemac\",\n", + " model=m,\n", + " ppath=ppath, # old path\n", + " cpath=npath, # new path\n", + " meteo=meteo.Dataset.sel(time=slice(next_, end_)).compute(),\n", + " sdate=next_, # new start date\n", + " end_date=end_, # new end date\n", + " start=next_, # start\n", + " copy=True,\n", + ")\n", + "b = rs.run(execute=False)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "a6405f1b", + "metadata": {}, + "outputs": [], + "source": [ + "b.run()" + ] + }, + { + "cell_type": "markdown", + "id": "af15ee7b", + "metadata": {}, + "source": [ + "## run 4 days model - check" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "9624eb1a", + "metadata": {}, + "outputs": [], + "source": [ + "#define in a dictionary the properties of the model..\n", + "model_parameters = {\n", + " \"solver_name\": \"telemac\",\n", + " \"tag\": \"telemac2d\",\n", + " \"rpath\": \"./data/iceland/20181001-04\",\n", + " \"mesh_file\": \"./data/iceland/hgrid.gr3\",\n", + " \"update\": [\"all\"], #set which component should be updated (meteo,dem,model)\n", + " \"meteo_source\": glob.glob(\"data/uvp_*.grib\"),\n", + " \"meteo_merge\": \"last\", # combine meteo\n", + " \"meteo_combine_by\": \"nested\",\n", + " \"meteo_xr_kwargs\": {\"concat_dim\": \"step\"},\n", + " \"start_date\": \"2018-10-01T00:00:00\",\n", + " \"time_frame\": \"4d\",\n", + " \"global\": False,\n", + " \"obs\": \"data/iceland/stations.csv\",\n", + " \"monitor\": True,\n", + " \"parameters\": {\n", + " \"dt\": 100\n", + " }\n", + "}\n", + "model_parameters" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "9787559b", + "metadata": {}, + "outputs": [], + "source": [ + "c = pmodel.set(**model_parameters)\n", + "c.create()\n", + "# IMPORTANT! Here, for a simple surge application, \n", + "# we will need close all boundaries, otherwise the \n", + "# model will run out of water\n", + "c.mesh.Dataset.type[:] = 'closed' # it will create a cli file with all boundaries closed (this can be done only once)\n", + "# we also need to drop some meteo variables, it is necesarry for zarr export\n", + "c.meteo.Dataset = c.meteo.Dataset.compute()\n", + "c.output()\n", + "c.set_obs()\n", + "c.save() # saves the json model file\n", + "c.run() # runs the model" + ] + }, + { + "cell_type": "markdown", + "id": "5da57efc", + "metadata": {}, + "source": [ + "## compare results" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "bce6f374", + "metadata": {}, + "outputs": [], + "source": [ + "res_2days = xr.open_dataset(\"data/iceland/20181001-04/results_2D.slf\")\n", + "res_day1 = xr.open_dataset(\"data/iceland/20181001/results_2D.slf\")\n", + "res_day2 = xr.open_dataset(\"data/iceland/20181003/results_2D.slf\")" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "85bff31a", + "metadata": {}, + "outputs": [], + "source": [ + "node = 15000\n", + "p1 = res_day1.S.isel(node = node).hvplot(label = \"Day 1&2\")\n", + "p2 = res_day2.S.isel(node = node).hvplot(label = \"Day 3&4\")\n", + "p3 = res_2days.S.isel(node = node).hvplot(label = \"4 Days\", line_dash='dashed')\n", + "p1 * p2 * p3" + ] + }, + { + "cell_type": "markdown", + "id": "4692bce5", + "metadata": {}, + "source": [ + "## compare with observations" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "32e3a069", + "metadata": {}, + "outputs": [], + "source": [ + "res_2days = xr.open_dataset(\"data/iceland/20181001-04/results_1D.slf\")\n", + "res_day1 = xr.open_dataset(\"data/iceland/20181001/results_1D.slf\")\n", + "res_day2 = xr.open_dataset(\"data/iceland/20181003/results_1D.slf\")\n", + "res_day2" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "8eb42188", + "metadata": {}, + "outputs": [], + "source": [ + "stations = pd.read_csv(\"data/iceland/stations.csv\")\n", + "stations" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "c6e13834", + "metadata": {}, + "outputs": [], + "source": [ + "from searvey import ioc\n", + "data = ioc.get_ioc_station_data('reyk', endtime=\"2018-10-05\", period=30)\n", + "data.index = data['time']\n", + "data = data.drop(columns=['time'])\n", + "data" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "43b9e48a", + "metadata": {}, + "outputs": [], + "source": [ + "# detide \n", + "from analysea.tide import detide\n", + "surge = detide(data[\"prs\"],lat = 64.15)\n", + "surge" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "e487c500", + "metadata": {}, + "outputs": [], + "source": [ + "p1 = res_day1.S.isel(node = 0).hvplot(label = \"Day 1\")\n", + "p2 = res_day2.S.isel(node = 0).hvplot(label = \"Day 2\")\n", + "p3 = res_2days.S.isel(node = 0).hvplot(label = \"2 Days\", line_dash='dashed')\n", + "obs_ = surge.loc[\"2018-10-01\":\"2018-10-05\"].hvplot(label = \"Observations\", color = 'k', line_dash='dotted')\n", + "p1 * p2 * p3 * obs_" + ] + } + ], + "metadata": { + "kernelspec": { + "display_name": "pos_test", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.11.8" + } + }, + "nbformat": 4, + "nbformat_minor": 5 +} diff --git a/index.html b/index.html index 3d38329..2af5fc6 100644 --- a/index.html +++ b/index.html @@ -45,6 +45,7 @@