Time_to_datetime.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import xarray as xr\n",
    "import glob"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "ds = xr.open_mfdataset(\"/g/data/w35/ccc561/SURFACEMODEL/LIS_HIST_*\",decode_times=False,concat_dim=\"time\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<xarray.Dataset>\n",
       "Dimensions:          (RelSMC_profiles: 6, SmFrozFrac_profiles: 6, SmLiqFrac_profiles: 6, SoilMoist_profiles: 6, SoilTemp_profiles: 6, east_west: 229, north_south: 109, time: 816)\n",
       "Coordinates:\n",
       "  * time             (time) float64 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 ...\n",
       "Dimensions without coordinates: RelSMC_profiles, SmFrozFrac_profiles, SmLiqFrac_profiles, SoilMoist_profiles, SoilTemp_profiles, east_west, north_south\n",
       "Data variables:\n",
       "    lat              (time, north_south, east_west) float32 dask.array<shape=(816, 109, 229), chunksize=(1, 109, 229)>\n",
       "    lon              (time, north_south, east_west) float32 dask.array<shape=(816, 109, 229), chunksize=(1, 109, 229)>\n",
       "    Swnet_tavg       (time, north_south, east_west) float32 dask.array<shape=(816, 109, 229), chunksize=(1, 109, 229)>\n",
       "    Lwnet_tavg       (time, north_south, east_west) float32 dask.array<shape=(816, 109, 229), chunksize=(1, 109, 229)>\n",
       "    Qle_tavg         (time, north_south, east_west) float32 dask.array<shape=(816, 109, 229), chunksize=(1, 109, 229)>\n",
       "    Qh_tavg          (time, north_south, east_west) float32 dask.array<shape=(816, 109, 229), chunksize=(1, 109, 229)>\n",
       "    Qg_tavg          (time, north_south, east_west) float32 dask.array<shape=(816, 109, 229), chunksize=(1, 109, 229)>\n",
       "    Snowf_tavg       (time, north_south, east_west) float32 dask.array<shape=(816, 109, 229), chunksize=(1, 109, 229)>\n",
       "    Rainf_tavg       (time, north_south, east_west) float32 dask.array<shape=(816, 109, 229), chunksize=(1, 109, 229)>\n",
       "    Evap_tavg        (time, north_south, east_west) float32 dask.array<shape=(816, 109, 229), chunksize=(1, 109, 229)>\n",
       "    Qs_tavg          (time, north_south, east_west) float32 dask.array<shape=(816, 109, 229), chunksize=(1, 109, 229)>\n",
       "    Qsb_tavg         (time, north_south, east_west) float32 dask.array<shape=(816, 109, 229), chunksize=(1, 109, 229)>\n",
       "    AvgSurfT_tavg    (time, north_south, east_west) float32 dask.array<shape=(816, 109, 229), chunksize=(1, 109, 229)>\n",
       "    Albedo_inst      (time, north_south, east_west) float32 dask.array<shape=(816, 109, 229), chunksize=(1, 109, 229)>\n",
       "    SWE_inst         (time, north_south, east_west) float32 dask.array<shape=(816, 109, 229), chunksize=(1, 109, 229)>\n",
       "    SnowDepth_inst   (time, north_south, east_west) float32 dask.array<shape=(816, 109, 229), chunksize=(1, 109, 229)>\n",
       "    SoilMoist_inst   (time, SoilMoist_profiles, north_south, east_west) float32 dask.array<shape=(816, 6, 109, 229), chunksize=(1, 6, 109, 229)>\n",
       "    SoilTemp_inst    (time, SoilTemp_profiles, north_south, east_west) float32 dask.array<shape=(816, 6, 109, 229), chunksize=(1, 6, 109, 229)>\n",
       "    SmLiqFrac_inst   (time, SmLiqFrac_profiles, north_south, east_west) float32 dask.array<shape=(816, 6, 109, 229), chunksize=(1, 6, 109, 229)>\n",
       "    SmFrozFrac_inst  (time, SmFrozFrac_profiles, north_south, east_west) float32 dask.array<shape=(816, 6, 109, 229), chunksize=(1, 6, 109, 229)>\n",
       "    SoilWet_inst     (time, north_south, east_west) float32 dask.array<shape=(816, 109, 229), chunksize=(1, 109, 229)>\n",
       "    ECanop_tavg      (time, north_south, east_west) float32 dask.array<shape=(816, 109, 229), chunksize=(1, 109, 229)>\n",
       "    TVeg_tavg        (time, north_south, east_west) float32 dask.array<shape=(816, 109, 229), chunksize=(1, 109, 229)>\n",
       "    ESoil_tavg       (time, north_south, east_west) float32 dask.array<shape=(816, 109, 229), chunksize=(1, 109, 229)>\n",
       "    CanopInt_inst    (time, north_south, east_west) float32 dask.array<shape=(816, 109, 229), chunksize=(1, 109, 229)>\n",
       "    SnowCover_inst   (time, north_south, east_west) float32 dask.array<shape=(816, 109, 229), chunksize=(1, 109, 229)>\n",
       "    Wind_f_inst      (time, north_south, east_west) float32 dask.array<shape=(816, 109, 229), chunksize=(1, 109, 229)>\n",
       "    Rainf_f_inst     (time, north_south, east_west) float32 dask.array<shape=(816, 109, 229), chunksize=(1, 109, 229)>\n",
       "    Tair_f_inst      (time, north_south, east_west) float32 dask.array<shape=(816, 109, 229), chunksize=(1, 109, 229)>\n",
       "    Qair_f_inst      (time, north_south, east_west) float32 dask.array<shape=(816, 109, 229), chunksize=(1, 109, 229)>\n",
       "    Psurf_f_inst     (time, north_south, east_west) float32 dask.array<shape=(816, 109, 229), chunksize=(1, 109, 229)>\n",
       "    SWdown_f_inst    (time, north_south, east_west) float32 dask.array<shape=(816, 109, 229), chunksize=(1, 109, 229)>\n",
       "    LWdown_f_inst    (time, north_south, east_west) float32 dask.array<shape=(816, 109, 229), chunksize=(1, 109, 229)>\n",
       "    Landmask_inst    (time, north_south, east_west) float32 dask.array<shape=(816, 109, 229), chunksize=(1, 109, 229)>\n",
       "    Landcover_inst   (time, north_south, east_west) float32 dask.array<shape=(816, 109, 229), chunksize=(1, 109, 229)>\n",
       "    Soiltype_inst    (time, north_south, east_west) float32 dask.array<shape=(816, 109, 229), chunksize=(1, 109, 229)>\n",
       "    SandFrac_inst    (time, north_south, east_west) float32 dask.array<shape=(816, 109, 229), chunksize=(1, 109, 229)>\n",
       "    ClayFrac_inst    (time, north_south, east_west) float32 dask.array<shape=(816, 109, 229), chunksize=(1, 109, 229)>\n",
       "    SiltFrac_inst    (time, north_south, east_west) float32 dask.array<shape=(816, 109, 229), chunksize=(1, 109, 229)>\n",
       "    Elevation_inst   (time, north_south, east_west) float32 dask.array<shape=(816, 109, 229), chunksize=(1, 109, 229)>\n",
       "    LAI_inst         (time, north_south, east_west) float32 dask.array<shape=(816, 109, 229), chunksize=(1, 109, 229)>\n",
       "    RelSMC_inst      (time, RelSMC_profiles, north_south, east_west) float32 dask.array<shape=(816, 6, 109, 229), chunksize=(1, 6, 109, 229)>\n",
       "Attributes:\n",
       "    missing_value:           -9999.0\n",
       "    NUM_SOIL_LAYERS:         6\n",
       "    SOIL_LAYER_THICKNESSES:  [ 0.022       0.058       0.154       0.40900001...\n",
       "    title:                   LIS land surface model output\n",
       "    institution:             NASA GSFC\n",
       "    source:                  \n",
       "    history:                 created on date: 2018-06-13T14:18:26.063\n",
       "    references:              Kumar_etal_EMS_2006, Peters-Lidard_etal_ISSE_2007\n",
       "    conventions:             CF-1.6\n",
       "    comment:                 website: http://lis.gsfc.nasa.gov/\n",
       "    MAP_PROJECTION:          EQUIDISTANT CYLINDRICAL\n",
       "    SOUTH_WEST_CORNER_LAT:   25.875\n",
       "    SOUTH_WEST_CORNER_LON:   -124.875\n",
       "    DX:                      0.25\n",
       "    DY:                      0.25"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ds"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "a = [ i*30./(24.*60) for i in xrange(ds.time.size) ]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "outputs": [],
   "source": [
    "ds['time']= a"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array(0.020833333333333332)"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ds['time'][1].values"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "outputs": [],
   "source": [
    "import cftime\n",
    "import numpy as np\n",
    "ds['time']=np.array(cftime.num2date(ds['time'].values,'days since 2002-11-03 19:30:00'),dtype='datetime64[ns]')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "numpy.datetime64"
      ]
     },
     "execution_count": 24,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "tt = ds['time'].values\n",
    "type(tt[0])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [],
   "source": [
    "compress_values=dict(zlib=True, complevel=5)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/g/data3/hh5/public/apps/miniconda3/envs/analysis27-18.04/lib/python2.7/site-packages/xarray/coding/variables.py:135: RuntimeWarning: invalid value encountered in equal\n",
      "  condition |= data == fv\n",
      "/g/data3/hh5/public/apps/miniconda3/envs/analysis27-18.04/lib/python2.7/site-packages/xarray/coding/variables.py:183: RuntimeWarning: invalid value encountered in multiply\n",
      "  data *= scale_factor\n"
     ]
    }
   ],
   "source": [
    "ds.to_netcdf(\"test.nc\",encoding={var: compress_values for var in ds.data_vars},unlimited_dims=('time'))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
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