Skip to content

Instantly share code, notes, and snippets.

@nicolasfauchereau
Last active August 29, 2015 14:16
Show Gist options
  • Save nicolasfauchereau/d795a02a71d37201b10b to your computer and use it in GitHub Desktop.
Save nicolasfauchereau/d795a02a71d37201b10b to your computer and use it in GitHub Desktop.
Display the source blob
Display the rendered blob
Raw
{
"cells": [
{
"metadata": {},
"cell_type": "markdown",
"source": "## Load and re-create the netcdf file of simulated winds according to the conventions for seawinds"
},
{
"metadata": {
"collapsed": false,
"trusted": true
},
"cell_type": "code",
"source": "!date",
"execution_count": 1,
"outputs": [
{
"output_type": "stream",
"name": "stdout",
"text": "Mon 2 Mar 2015 13:23:14 NZDT\r\n"
}
]
},
{
"metadata": {},
"cell_type": "markdown",
"source": "[Nicolas Fauchereau](mailto:Nicolas.Fauchereau@niwa.co.nz)\n<hr size=5>"
},
{
"metadata": {
"collapsed": false,
"trusted": true
},
"cell_type": "code",
"source": "import numpy as np\nimport pandas as pd",
"execution_count": 2,
"outputs": []
},
{
"metadata": {
"collapsed": false,
"trusted": true
},
"cell_type": "code",
"source": "import xray; print(xray.__version__)",
"execution_count": 1,
"outputs": [
{
"output_type": "stream",
"text": "0.4.0rc1\n",
"name": "stdout"
}
]
},
{
"metadata": {},
"cell_type": "markdown",
"source": "### Loads the (template) seawinds dataset"
},
{
"metadata": {
"collapsed": false,
"trusted": true
},
"cell_type": "code",
"source": "seawinds = xray.open_dataset('../data/seawinds/winds.nc')",
"execution_count": 4,
"outputs": []
},
{
"metadata": {
"collapsed": false,
"trusted": true
},
"cell_type": "code",
"source": "seawinds",
"execution_count": 5,
"outputs": [
{
"execution_count": 5,
"output_type": "execute_result",
"data": {
"text/plain": "<xray.Dataset>\nDimensions: (lat: 121, lon: 201, time: 31, zlev: 1)\nCoordinates:\n * time (time) datetime64[ns] 2000-01-01T09:00:00 2000-01-02T09:00:00 ...\n * zlev (zlev) float32 10.0\n * lat (lat) float32 -30.0 -29.75 -29.5 -29.25 -29.0 -28.75 -28.5 -28.25 -28.0 ...\n * lon (lon) float32 180.0 180.25 180.5 180.75 181.0 181.25 181.5 181.75 182.0 ...\nData variables:\n u (time, zlev, lat, lon) float64 -1.071 -1.208 -1.356 -1.516 -1.681 -1.839 ...\n v (time, zlev, lat, lon) float64 -5.99 -5.822 -5.653 -5.476 -5.249 -4.962 ...\n w (time, zlev, lat, lon) float64 6.15 6.017 5.893 5.772 5.613 5.407 5.163 ...\nAttributes:\n Conventions: CF-1.0\n title: NOAA/NCDC Blended daily 0.25-degree Sea Surface Winds\n source: Multiple satellite observations: DMSP SSMI F08, F10, F11, F13,F14 F15; TMI; QuikSCAT; AMSR-E; Direction from NCEP Reanalysis-2\n summary: Gridded and blended sea surface vector winds from multiple satellites with direction from NCEP Reanalysis-2; Global ocean coverage with a 0.25-degree resolution; The whole datasets covers from July 1987 to present, daily resolution in this dataset; 6-hourly and monthly are also available in other directories; See http://www.ncdc.noaa.gov/oa/rsad/blendedseawinds.html and links within for details. Include (u,v) means and scalar mean speed w for comparison\n Keywords: sea winds, ocean winds, sea surface winds, air-sea interaction, air-sea flux, wind-driven circulation, Ekman pumping, Ekman transport, ocean upwelling, wind stress, windstress\n references: links at http://www.ncdc.noaa.gov/oa/rsad/blendedseawinds.html\n History: Translated to CF-1.0 Conventions by Netcdf-Java CDM (NetcdfCFWriter)\nOriginal Dataset = oceanwindsdly; Translation Date = Wed Aug 27 21:43:16 EDT 2014\n institution: NOAA NESDIS National Climatic Data Center\n Contact: Huai-Min.Zhang AT noaa.gov or satorder AT noaa.gov; ph:1+828-271-4090\n Acknowledgment: The gridded data were generated from the multiple satellite observations of DOD, NOAA and NASA (and future others) and wind retrievals of the Remote Sensing Systems, Inc. (http://www.remss.com), using scientific methods such as objective analysis (OA). The OA is only truly objective when the needed statistics are completely known, which may not be always the case.\n Data_Calendar_Date: 2014-08-25"
},
"metadata": {}
}
]
},
{
"metadata": {},
"cell_type": "markdown",
"source": "### loads the simulated wind fields"
},
{
"metadata": {
"collapsed": false,
"trusted": true
},
"cell_type": "code",
"source": "simu = xray.open_dataset('/Users/nicolasf/data/simulated_wind_1997_1998.nc')",
"execution_count": 6,
"outputs": []
},
{
"metadata": {
"collapsed": false,
"trusted": true
},
"cell_type": "code",
"source": "simu",
"execution_count": 7,
"outputs": [
{
"execution_count": 7,
"output_type": "execute_result",
"data": {
"text/plain": "<xray.Dataset>\nDimensions: (latitudes: 161, longitudes: 281, time: 730)\nCoordinates:\n * latitudes (latitudes) float64 -30.0 -29.75 -29.5 -29.25 -29.0 -28.75 -28.5 -28.25 ...\n * longitudes (longitudes) float64 160.0 160.2 160.5 160.8 161.0 161.2 161.5 161.8 ...\n * time (time) datetime64[ns] 1997-01-01 1997-01-02 1997-01-03 1997-01-04 ...\nData variables:\n vwnd (time, latitudes, longitudes) float32 -4.29999 -4.76999 -5.23999 -5.7 ...\n uwnd (time, latitudes, longitudes) float32 5.05 4.78001 4.51001 4.24001 3.97 ..."
},
"metadata": {}
}
]
},
{
"metadata": {},
"cell_type": "markdown",
"source": "### get the U and V values and add a dummy `zlev` dimension"
},
{
"metadata": {
"collapsed": false,
"trusted": true
},
"cell_type": "code",
"source": "uwnd = simu['uwnd'].values",
"execution_count": 8,
"outputs": []
},
{
"metadata": {
"collapsed": false,
"trusted": true
},
"cell_type": "code",
"source": "vwnd = simu['vwnd'].values",
"execution_count": 9,
"outputs": []
},
{
"metadata": {
"collapsed": false,
"trusted": true
},
"cell_type": "code",
"source": "uwnd = uwnd[:,np.newaxis,:,:]",
"execution_count": 10,
"outputs": []
},
{
"metadata": {
"collapsed": false,
"trusted": true
},
"cell_type": "code",
"source": "vwnd = vwnd[:,np.newaxis,:,:]",
"execution_count": 11,
"outputs": []
},
{
"metadata": {},
"cell_type": "markdown",
"source": "### Get the other dimension variables"
},
{
"metadata": {
"collapsed": false,
"trusted": true
},
"cell_type": "code",
"source": "dates = simu['time'].values",
"execution_count": 12,
"outputs": []
},
{
"metadata": {
"collapsed": false,
"trusted": true
},
"cell_type": "code",
"source": "lat = simu['latitudes'].values\nlon = simu['longitudes'].values",
"execution_count": 13,
"outputs": []
},
{
"metadata": {},
"cell_type": "markdown",
"source": "### creates a dict containing dims and variables"
},
{
"metadata": {
"collapsed": false,
"trusted": true
},
"cell_type": "code",
"source": "d = {}\nd['time'] = ('time',dates)\nd['lat'] = ('lat',lat)\nd['lon'] = ('lon', lon)\nd['zlev'] = ('zlev', [10.])\nd['uwnd'] = (['time','zlev','lat','lon'], uwnd)\nd['vwnd'] = (['time','zlev','lat','lon'], vwnd)",
"execution_count": 14,
"outputs": []
},
{
"metadata": {},
"cell_type": "markdown",
"source": "### casts into a `xray.Dataset`"
},
{
"metadata": {
"collapsed": false,
"trusted": true
},
"cell_type": "code",
"source": "dset_lev = xray.Dataset(d)",
"execution_count": 15,
"outputs": []
},
{
"metadata": {
"collapsed": false,
"trusted": true
},
"cell_type": "code",
"source": "dset_lev",
"execution_count": 16,
"outputs": [
{
"execution_count": 16,
"output_type": "execute_result",
"data": {
"text/plain": "<xray.Dataset>\nDimensions: (lat: 161, lon: 281, time: 730, zlev: 1)\nCoordinates:\n * lon (lon) float64 160.0 160.2 160.5 160.8 161.0 161.2 161.5 161.8 162.0 162.2 ...\n * time (time) datetime64[ns] 1997-01-01 1997-01-02 1997-01-03 1997-01-04 ...\n * lat (lat) float64 -30.0 -29.75 -29.5 -29.25 -29.0 -28.75 -28.5 -28.25 -28.0 ...\n * zlev (zlev) float64 10.0\nData variables:\n uwnd (time, zlev, lat, lon) float32 5.05 4.78001 4.51001 4.24001 3.97 3.70001 ...\n vwnd (time, zlev, lat, lon) float32 -4.29999 -4.76999 -5.23999 -5.7 -6.17 ..."
},
"metadata": {}
}
]
},
{
"metadata": {},
"cell_type": "markdown",
"source": "### set the attributes (global and variables) to match the seawinds one"
},
{
"metadata": {
"collapsed": false,
"trusted": true
},
"cell_type": "code",
"source": "dset_lev.attrs = seawinds.attrs",
"execution_count": 17,
"outputs": []
},
{
"metadata": {
"collapsed": false,
"trusted": true
},
"cell_type": "code",
"source": "dset_lev.time.attrs = seawinds.time.attrs\ndset_lev.lat.attrs = seawinds.lat.attrs\ndset_lev.lon.attrs = seawinds.lon.attrs\ndset_lev.zlev.attrs = seawinds.zlev.attrs",
"execution_count": 19,
"outputs": []
},
{
"metadata": {},
"cell_type": "markdown",
"source": "### saves to netcdf on disk"
},
{
"metadata": {
"collapsed": false,
"trusted": true
},
"cell_type": "code",
"source": "dset_lev.to_netcdf('/Users/nicolasf/data/simulated_wind_1997_1998_NC3.nc', format='NETCDF3_CLASSIC')",
"execution_count": 23,
"outputs": []
},
{
"metadata": {
"collapsed": true,
"trusted": true
},
"cell_type": "code",
"source": "from matplotlib import pyplot as plt \n%matplotlib inline",
"execution_count": 28,
"outputs": []
},
{
"metadata": {
"collapsed": false,
"trusted": true
},
"cell_type": "code",
"source": "plt.imshow(dset_lev.sel(time='1997-1-4')['uwnd'].squeeze())",
"execution_count": 33,
"outputs": [
{
"execution_count": 33,
"output_type": "execute_result",
"data": {
"text/plain": "<matplotlib.image.AxesImage at 0x12b188910>"
},
"metadata": {}
},
{
"output_type": "display_data",
"data": {
"image/png": "iVBORw0KGgoAAAANSUhEUgAAAXIAAADgCAYAAAAe/e31AAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nYII=\n",
"text/plain": "<matplotlib.figure.Figure at 0x12afbd650>"
},
"metadata": {}
}
]
},
{
"metadata": {
"collapsed": false,
"trusted": true
},
"cell_type": "code",
"source": "",
"execution_count": null,
"outputs": []
}
],
"metadata": {
"kernelspec": {
"name": "python2",
"display_name": "Python 2",
"language": "python"
},
"language_info": {
"mimetype": "text/x-python",
"nbconvert_exporter": "python",
"name": "python",
"pygments_lexer": "ipython2",
"version": "2.7.9",
"file_extension": ".py",
"codemirror_mode": {
"version": 2,
"name": "ipython"
}
},
"gist_id": "d795a02a71d37201b10b"
},
"nbformat": 3,
"nbformat_minor": 0
}
Sign up for free to join this conversation on GitHub. Already have an account? Sign in to comment