{
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"Table of Contents
\n",
""
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{
"cell_type": "markdown",
"metadata": {},
"source": [
"# Creating Non Rectilinear Grids from Scratch\n",
"\n",
"Download the Notebook [here](Creating_Non_Rectiilinear_Grids_From_Scratch.ipynb)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"# Table of Contents\n",
"\n",
"- [Preparing the notebook](#prepare)\n",
"- [Curvilinear Grid](#curv)\n",
" - [Load in data](#load_curv)\n",
" - [Prepare 2D \"axes\"](#axes_curv)\n",
" - [Create Curvilinear Grid](#grid_curv)\n",
" - [Applying Grid To Data](#data_curv)\n",
" - [Regrid to T42 Gaussian Grid](#regrid_curv)\n",
" - [Display Results](#plot_curv)\n",
"- [Generic Grid](#gen)\n",
" - [Load in data](#load_gen)\n",
" - [Prepare \"axes\"](#axes_gen)\n",
" - [Create Generic Grid](#grid_gen)\n",
" - [Applying Grid To Data](#data_gen)\n",
" - [Display Results](#plot_gen)\n",
"\n",
"\n",
"[Back To Top](#top)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"# Preparing The Notebook"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"# Prepare the notebook elements\n",
"import requests\n",
"def download(fnm):\n",
" r = requests.get(\"https://uvcdat.llnl.gov/cdat/sample_data/%s\" % fnm,stream=True)\n",
" with open(fnm,\"wb\") as f:\n",
" for chunk in r.iter_content(chunk_size=1024):\n",
" if chunk: # filter local_filename keep-alive new chunks\n",
" f.write(chunk)\n",
" \n",
"download(\"sampleCurveGrid4.nc\")\n",
"download(\"sampleGenGrid3.nc\")"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"# Curvilinear Grids\n",
"\n",
"In this section we will create a curvilinear grid from raw data and regrid it to T42 Gaussian Grid\n",
"\n",
"[Back To Top](#top)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Load the data\n",
"\n",
"[Back To Top](#top)"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"import cdms2\n",
"\n",
"fnm = \"sampleCurveGrid4.nc\"\n",
"f = cdms2.open(fnm)\n",
"data = f(\"sample\").filled() # Get data and forget all about it (pure numpy)\n",
"lat = f(\"lat\").filled() # latitude coordinates\n",
"lon = f(\"lon\").filled() # longitude coords\n",
"blon = f(\"bounds_lon\").filled() # longitude vertices\n",
"blat = f(\"bounds_lat\").filled() #latitude vertices"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Creating latitude and longitude two dimensional \"axes\"\n",
"\n",
"Let's prepare the \"axes\" for our data (i.e 2D lat lon)\n",
"\n",
"[Back To Top](#top)"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"lat_axis = cdms2.coord.TransientAxis2D(lat)\n",
"lat_axis.setBounds(blat)\n",
"\n",
"lon_axis = cdms2.coord.TransientAxis2D(lon)\n",
"lon_axis.setBounds(blon)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Creating two dimensional curvilinear grid\n",
"\n",
"Let's prepare the \"axes\" for our data (i.e 2D lat lon)\n",
"\n",
"[Back To Top](#top)"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"# Now let's create the grid\n",
"grid = cdms2.hgrid.TransientCurveGrid(lat_axis,lon_axis)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Applying grid to raw data\n",
"\n",
"Let's apply the grid to our data\n",
"\n",
"[Back To Top](#top)"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"data = cdms2.MV2.array(data)\n",
"data.setAxisList(grid.getAxisList())\n",
"data.setGrid(grid)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Converting to another grid\n",
"\n",
"Let's regrid our data to a T42 grid\n",
"\n",
"[Back To Top](#top)"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"regrid_data = data.regrid(cdms2.createGaussianGrid(128),regridTool=\"esmf\",regridMethod=\"conserve\")"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Display results\n",
"\n",
"let's plot the raw data and the regrided data\n",
"\n",
"[Back To Top](#top)"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"# And llet's plot it to be sure it worked\n",
"import vcs\n",
"import EzTemplate\n",
"\n",
"M = EzTemplate.Multi(rows=1,columns=2)\n",
"\n",
"# Raw data\n",
"mesh = vcs.createmeshfill()\n",
"x=vcs.init(bg=True)\n",
"x.plot(data,mesh,M.get(row=0,column=0))\n",
"\n",
"# Regridded data\n",
"x.plot(regrid_data,M.get(row=0,column=1))"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"# Generic Grids\n",
"\n",
"In this section we will create a genric grid from raw data and regrid it to T42 Gaussian Grid\n",
"\n",
"[Back To Top](#top)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Load the data\n",
"\n",
"[Back To Top](#top)"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"import cdms2\n",
"\n",
"fnm = \"sampleGenGrid3.nc\"\n",
"f = cdms2.open(fnm)\n",
"data = f(\"sample\").filled() # Get data and forget all about it (pure numpy)\n",
"lat = f(\"lat\").filled() # latitude coordinates\n",
"lon = f(\"lon\").filled() # longitude coords\n",
"blon = f(\"bounds_lon\").filled() # longitude vertices\n",
"blat = f(\"bounds_lat\").filled() #latitude vertices"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Creating latitude and longitude \"axes\"\n",
"\n",
"Let's prepare the \"axes\" for our data (i.e 1D lat lon)\n",
"\n",
"[Back To Top](#top)"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"#Ncells = len(lat)\n",
"#iaxis = cdms2.coord.TransientVirtualAxis(\"cell\", Ncells)\n",
"lat_axis = cdms2.auxcoord.TransientAuxAxis1D(lat)\n",
"lat_axis.setBounds(blat)\n",
"\n",
"lon_axis = cdms2.auxcoord.TransientAuxAxis1D(lon)\n",
"lon_axis.setBounds(blon)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Creating Unidimensional Generic Grid\n",
"\n",
"Let's prepare the \"axes\" for our data (i.e 2D lat lon)\n",
"\n",
"[Back To Top](#top)"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"# Now let's create the grid\n",
"grid = cdms2.gengrid.TransientGenericGrid(lat_axis,lon_axis)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Applying grid to raw data\n",
"\n",
"Let's apply the grid to our data\n",
"\n",
"[Back To Top](#top)"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"data = cdms2.MV2.array(data)\n",
"data.setAxisList(grid.getAxisList())\n",
"data.setGrid(grid)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Display results\n",
"\n",
"let's plot the raw data and the regrided data\n",
"\n",
"[Back To Top](#top)"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"# And llet's plot it to be sure it worked\n",
"import vcs\n",
"\n",
"# Raw data\n",
"mesh = vcs.createmeshfill()\n",
"mesh.mesh = True\n",
"x=vcs.init(bg=True)\n",
"x.plot(data,mesh)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"[Back To Top](#top)"
]
}
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