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Merge pull request #14 from jukent/add-all
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@@ -16,6 +16,7 @@ dependencies: | |
- seaborn | ||
- bokeh | ||
- uxarray | ||
- datashader | ||
- geocat-datafiles | ||
- tropycal | ||
- pip | ||
|
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@@ -0,0 +1,238 @@ | ||
{ | ||
"cells": [ | ||
{ | ||
"cell_type": "markdown", | ||
"metadata": {}, | ||
"source": [ | ||
"# Animation" | ||
] | ||
}, | ||
{ | ||
"cell_type": "markdown", | ||
"metadata": { | ||
"collapsed": false, | ||
"jupyter": { | ||
"outputs_hidden": false | ||
} | ||
}, | ||
"source": [ | ||
"time stamp at 1:19" | ||
] | ||
}, | ||
{ | ||
"cell_type": "markdown", | ||
"metadata": {}, | ||
"source": [ | ||
"NCL_animate_1\n", | ||
"\n", | ||
"Please note:\n", | ||
" - Executing this script will not display a gif, but you have the option to uncomment a line at the bottom that will save a gif in the same directory as this script.\n", | ||
"\n", | ||
"[GeoCAT-examples](https://geocat-examples.readthedocs.io/en/latest/gallery/Animations/NCL_animate_1.html)\n" | ||
] | ||
}, | ||
{ | ||
"cell_type": "markdown", | ||
"metadata": {}, | ||
"source": [ | ||
"### Import packages:\n", | ||
"\n" | ||
] | ||
}, | ||
{ | ||
"cell_type": "code", | ||
"execution_count": null, | ||
"metadata": { | ||
"collapsed": false, | ||
"jupyter": { | ||
"outputs_hidden": false | ||
} | ||
}, | ||
"outputs": [], | ||
"source": [ | ||
"import cartopy.crs as ccrs\n", | ||
"import matplotlib.animation as animation\n", | ||
"import numpy as np\n", | ||
"import xarray as xr\n", | ||
"from matplotlib import pyplot as plt\n", | ||
"\n", | ||
"import geocat.datafiles as gdf\n", | ||
"import geocat.viz as gv" | ||
] | ||
}, | ||
{ | ||
"cell_type": "markdown", | ||
"metadata": {}, | ||
"source": [ | ||
"### Read in data:\n", | ||
"\n" | ||
] | ||
}, | ||
{ | ||
"cell_type": "code", | ||
"execution_count": null, | ||
"metadata": { | ||
"collapsed": false, | ||
"jupyter": { | ||
"outputs_hidden": false | ||
} | ||
}, | ||
"outputs": [], | ||
"source": [ | ||
"# Open a netCDF data file using xarray default engine and load the data into xarrays\n", | ||
"# Disable time decoding due to missing necessary metadata\n", | ||
"ds = xr.open_dataset(gdf.get(\"netcdf_files/meccatemp.cdf\"), decode_times=False)\n", | ||
"\n", | ||
"tas = ds.t\n", | ||
"tas" | ||
] | ||
}, | ||
{ | ||
"cell_type": "markdown", | ||
"metadata": {}, | ||
"source": [ | ||
"### Create animation:\n", | ||
"\n" | ||
] | ||
}, | ||
{ | ||
"cell_type": "code", | ||
"execution_count": null, | ||
"metadata": { | ||
"collapsed": false, | ||
"jupyter": { | ||
"outputs_hidden": false | ||
} | ||
}, | ||
"outputs": [], | ||
"source": [ | ||
"# Set up Axes with Cartopy Projection\n", | ||
"fig = plt.figure(figsize=(10, 8))\n", | ||
"ax = plt.axes(projection=ccrs.PlateCarree(central_longitude=150))\n", | ||
"ax.coastlines(linewidths=0.5)\n", | ||
"ax.set_extent([-180, 180, -90, 90], ccrs.PlateCarree())\n", | ||
"\n", | ||
"# Use geocat.viz.util convenience function to set axes limits & tick values\n", | ||
"gv.set_axes_limits_and_ticks(ax,\n", | ||
" xlim=(-180, 180),\n", | ||
" ylim=(-90, 90),\n", | ||
" xticks=np.linspace(-180, 180, 13),\n", | ||
" yticks=np.linspace(-90, 90, 7))\n", | ||
"\n", | ||
"# Use geocat.viz.util convenience function to add minor and major tick lines\n", | ||
"gv.add_major_minor_ticks(ax, labelsize=10)\n", | ||
"\n", | ||
"# Use geocat.viz.util convenience function to make latitude, longitude tick labels\n", | ||
"gv.add_lat_lon_ticklabels(ax)\n", | ||
"\n", | ||
"# create initial plot that establishes a colorbar\n", | ||
"tas[0, :, :].plot.contourf(ax=ax,\n", | ||
" transform=ccrs.PlateCarree(),\n", | ||
" vmin=195,\n", | ||
" vmax=328,\n", | ||
" levels=53,\n", | ||
" cmap=\"inferno\",\n", | ||
" cbar_kwargs={\n", | ||
" \"extendrect\": True,\n", | ||
" \"orientation\": \"horizontal\",\n", | ||
" \"ticks\": np.arange(195, 332, 9),\n", | ||
" \"label\": \"\",\n", | ||
" \"shrink\": 0.90\n", | ||
" })\n", | ||
"\n", | ||
"\n", | ||
"# animate function for matplotlib FuncAnimation\n", | ||
"def animate(i):\n", | ||
" tas[i, :, :].plot.contourf(\n", | ||
" ax=ax,\n", | ||
" transform=ccrs.PlateCarree(),\n", | ||
" vmin=195,\n", | ||
" vmax=328,\n", | ||
" levels=53,\n", | ||
" cmap=\"inferno\",\n", | ||
" add_colorbar=False,\n", | ||
" )\n", | ||
"\n", | ||
" gv.set_titles_and_labels(\n", | ||
" ax,\n", | ||
" maintitle=\"January Global Surface Temperature (K) - Day \" +\n", | ||
" str(tas.coords['time'].values[i])[:13],\n", | ||
" xlabel=\"\",\n", | ||
" ylabel=\"\")" | ||
] | ||
}, | ||
{ | ||
"cell_type": "markdown", | ||
"metadata": { | ||
"jupyter": { | ||
"outputs_hidden": false | ||
} | ||
}, | ||
"source": [ | ||
"### Run:" | ||
] | ||
}, | ||
{ | ||
"cell_type": "code", | ||
"execution_count": null, | ||
"metadata": { | ||
"collapsed": false, | ||
"jupyter": { | ||
"outputs_hidden": false | ||
} | ||
}, | ||
"outputs": [], | ||
"source": [ | ||
"# runs the animation initiated with the frame from init and progressed with the animate function\n", | ||
"anim = animation.FuncAnimation(fig, animate, frames=30, interval=200)" | ||
] | ||
}, | ||
{ | ||
"cell_type": "markdown", | ||
"metadata": { | ||
"jupyter": { | ||
"outputs_hidden": false | ||
} | ||
}, | ||
"source": [ | ||
"### Save:" | ||
] | ||
}, | ||
{ | ||
"cell_type": "code", | ||
"execution_count": null, | ||
"metadata": { | ||
"collapsed": false, | ||
"jupyter": { | ||
"outputs_hidden": false | ||
} | ||
}, | ||
"outputs": [], | ||
"source": [ | ||
"# Uncomment this line to save the created animation\n", | ||
"anim.save('images/animate_1.gif', writer='pillow', fps=5);" | ||
] | ||
} | ||
], | ||
"metadata": { | ||
"kernelspec": { | ||
"display_name": "Python 3 (ipykernel)", | ||
"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": "3.10.12" | ||
} | ||
}, | ||
"nbformat": 4, | ||
"nbformat_minor": 4 | ||
} |
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