From 9448fb254a8061af72a47becf75a9a2de704a36c Mon Sep 17 00:00:00 2001 From: Deepak Cherian Date: Fri, 2 Aug 2024 21:32:49 -0600 Subject: [PATCH] fix --- public/posts/flox-smart/dataset-repr.html | 579 +++++++++++++++++++++- 1 file changed, 578 insertions(+), 1 deletion(-) diff --git a/public/posts/flox-smart/dataset-repr.html b/public/posts/flox-smart/dataset-repr.html index 26984fa4..dcfac4a9 100644 --- a/public/posts/flox-smart/dataset-repr.html +++ b/public/posts/flox-smart/dataset-repr.html @@ -1 +1,578 @@ -
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<xarray.DataArray 'zwattablrt' (time: 14608, y: 15360, x: 18432)> Size: 33TB\ndask.array<getitem, shape=(14608, 15360, 18432), dtype=float64, chunksize=(224, 350, 350), chunktype=numpy.ndarray>\nCoordinates: (3)\nAttributes: (4)
xarray.DataArray
\'zwattablrt\'
  • time: 14608
  • y: 15360
  • x: 18432
  • dask.array<chunksize=(25, 350, 350), meta=np.ndarray>
    \n \n \n \n \n
    \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n
    Array Chunk
    Bytes 30.09 TiB 209.35 MiB
    Shape (14608, 15360, 18432) (224, 350, 350)
    Dask graph 156244 chunks in 3 graph layers
    Data type float64 numpy.ndarray
    \n     		\n \n\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n\n \n \n\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n\n \n \n\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n\n \n \n\n \n 18432\n 15360\n 14608\n\n
    • time
      (time)
      datetime64[ns]
      2001-01-01 ... 2005-12-31T21:00:00
      long_name :
      valid output time
      standard_name :
      time
      valid_max :
      4862880
      valid_min :
      4777980
      array(['2001-01-01T00:00:00.000000000', '2001-01-01T03:00:00.000000000',\n       '2001-01-01T06:00:00.000000000', ..., '2005-12-31T15:00:00.000000000',\n       '2005-12-31T18:00:00.000000000', '2005-12-31T21:00:00.000000000'],\n      dtype='datetime64[ns]')
    • x
      (x)
      float64
      -2.304e+06 -2.304e+06 ... 2.304e+06
      _CoordinateAxisType :
      GeoX
      long_name :
      x coordinate of projection
      resolution :
      250.0
      standard_name :
      projection_x_coordinate
      units :
      m
      array([-2303875., -2303625., -2303375., ...,  2303375.,  2303625.,  2303875.])
    • y
      (y)
      float64
      -1.92e+06 -1.92e+06 ... 1.92e+06
      _CoordinateAxisType :
      GeoY
      long_name :
      y coordinate of projection
      resolution :
      250.0
      standard_name :
      projection_y_coordinate
      units :
      m
      array([-1919875., -1919625., -1919375., ...,  1919375.,  1919625.,  1919875.])
    • time
      PandasIndex
      PandasIndex(DatetimeIndex(['2001-01-01 00:00:00', '2001-01-01 03:00:00',\n               '2001-01-01 06:00:00', '2001-01-01 09:00:00',\n               '2001-01-01 12:00:00', '2001-01-01 15:00:00',\n               '2001-01-01 18:00:00', '2001-01-01 21:00:00',\n               '2001-01-02 00:00:00', '2001-01-02 03:00:00',\n               ...\n               '2005-12-30 18:00:00', '2005-12-30 21:00:00',\n               '2005-12-31 00:00:00', '2005-12-31 03:00:00',\n               '2005-12-31 06:00:00', '2005-12-31 09:00:00',\n               '2005-12-31 12:00:00', '2005-12-31 15:00:00',\n               '2005-12-31 18:00:00', '2005-12-31 21:00:00'],\n              dtype='datetime64[ns]', name='time', length=14608, freq=None))
    • x
      PandasIndex
      PandasIndex(Index([-2303875.0, -2303625.0, -2303375.0, -2303125.0, -2302875.0, -2302625.0,\n       -2302375.0, -2302125.0, -2301875.0, -2301625.0,\n       ...\n        2301625.0,  2301875.0,  2302125.0,  2302375.0,  2302625.0,  2302875.0,\n        2303125.0,  2303375.0,  2303625.0,  2303875.0],\n      dtype='float64', name='x', length=18432))
    • y
      PandasIndex
      PandasIndex(Index([-1919875.0, -1919625.0, -1919375.0, -1919125.0, -1918875.0, -1918625.0,\n       -1918375.0, -1918125.0, -1917875.0, -1917625.0,\n       ...\n        1917625.0,  1917875.0,  1918125.0,  1918375.0,  1918625.0,  1918875.0,\n        1919125.0,  1919375.0,  1919625.0,  1919875.0],\n      dtype='float64', name='y', length=15360))
  • esri_pe_string :
    PROJCS["Lambert_Conformal_Conic",GEOGCS["GCS_Sphere",DATUM["D_Sphere",SPHEROID["Sphere",6370000.0,0.0]],PRIMEM["Greenwich",0.0],UNIT["Degree",0.0174532925199433]],PROJECTION["Lambert_Conformal_Conic_2SP"],PARAMETER["false_easting",0.0],PARAMETER["false_northing",0.0],PARAMETER["central_meridian",-97.0],PARAMETER["standard_parallel_1",30.0],PARAMETER["standard_parallel_2",60.0],PARAMETER["latitude_of_origin",40.0],UNIT["Meter",1.0]];-35691800 -29075200 10000;-100000 10000;-100000 10000;0.001;0.001;0.001;IsHighPrecision
    grid_mapping :
    crs
    long_name :
    depth to saturation, rounded to highest saturated layer
    units :
    m
+
+ + + + + + + + + + + + + + +
<xarray.DataArray 'zwattablrt' (time: 14608, y: 15360, x: 18432)> Size: 33TB
+dask.array<getitem, shape=(14608, 15360, 18432), dtype=float64, chunksize=(224, 350, 350), chunktype=numpy.ndarray>
+Coordinates: (3)
+Attributes: (4)