diff --git a/demo/datacube.ipynb b/demo/datacube.ipynb index 6353077e..700c8d26 100644 --- a/demo/datacube.ipynb +++ b/demo/datacube.ipynb @@ -669,7 +669,7 @@ " add_offset: 0.0\n", " _FillValue: 1.7976931348623157e+308\n", " value_type: ordinal\n", - " value_labels: {1: 'SVHNIR', 2: 'SVLNIR', 3: 'AVHNIR', 4: 'AVLNIR', 5: '...
array([[[29., 29., 29., ..., 29., 29., 29.],\n", + " value_labels: {1: 'SVHNIR', 2: 'SVLNIR', 3: 'AVHNIR', 4: 'AVLNIR', 5: '...
array([[[29., 29., 29., ..., 29., 29., 29.],\n", " [29., 29., 29., ..., 29., 29., 29.],\n", " [29., 29., 29., ..., 5., 29., 29.],\n", " ...,\n", @@ -691,26 +691,26 @@ " ...,\n", " [ 3., 3., 3., ..., 3., 27., 27.],\n", " [ 3., 27., 3., ..., 27., 27., 27.],\n", - " [27., 3., 7., ..., 27., 27., 27.]]])
array([4530115., 4530125., 4530135., ..., 4535845., 4535855., 4535865.])
array([2696625., 2696615., 2696605., ..., 2691025., 2691015., 2691005.])
array(0)
array(['2019-12-15T10:17:33.408715000', '2020-09-05T10:17:43.167942000',\n", - " '2020-12-19T10:17:34.610661000'], dtype='datetime64[ns]')
array(0)
array([[1., 1., 1., ..., 1., 1., 1.],\n", + " [27., 3., 7., ..., 27., 27., 27.]]])
array([4530115., 4530125., 4530135., ..., 4535845., 4535855., 4535865.])
array([2696625., 2696615., 2696605., ..., 2691025., 2691015., 2691005.])
array(0)
array(['2019-12-15T10:17:33.408715000', '2020-09-05T10:17:43.167942000',\n", + " '2020-12-19T10:17:34.610661000'], dtype='datetime64[ns]')
array(0)
array([[1., 1., 1., ..., 1., 1., 1.],\n", " [1., 1., 1., ..., 1., 1., 1.],\n", " [1., 1., 1., ..., 1., 1., 1.],\n", " ...,\n", " [1., 1., 1., ..., 1., 1., 1.],\n", " [1., 1., 1., ..., 1., 1., 1.],\n", - " [1., 1., 1., ..., 1., 1., 1.]])
PandasIndex(Index([4530115.0, 4530125.0, 4530135.0, 4530145.0, 4530155.0, 4530165.0,\n", + " [1., 1., 1., ..., 1., 1., 1.]])
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PandasIndex(Index([2696625.0, 2696615.0, 2696605.0, 2696595.0, 2696585.0, 2696575.0,\n", + " dtype='float64', name='x', length=576))
PandasIndex(Index([2696625.0, 2696615.0, 2696605.0, 2696595.0, 2696585.0, 2696575.0,\n", " 2696565.0, 2696555.0, 2696545.0, 2696535.0,\n", " ...\n", " 2691095.0, 2691085.0, 2691075.0, 2691065.0, 2691055.0, 2691045.0,\n", " 2691035.0, 2691025.0, 2691015.0, 2691005.0],\n", - " dtype='float64', name='y', length=563))
PandasIndex(DatetimeIndex(['2019-12-15 10:17:33.408715', '2020-09-05 10:17:43.167942',\n", + " dtype='float64', name='y', length=563))
PandasIndex(DatetimeIndex(['2019-12-15 10:17:33.408715', '2020-09-05 10:17:43.167942',\n", " '2020-12-19 10:17:34.610661'],\n", - " dtype='datetime64[ns]', name='time', freq=None))
array([[[0., 0., 0., ..., 0., 0., 0.],\n", + " value_type: binary
array([[[0., 0., 0., ..., 0., 0., 0.],\n", " [0., 0., 0., ..., 0., 0., 0.],\n", " [0., 0., 0., ..., 0., 0., 0.],\n", " ...,\n", @@ -971,26 +971,26 @@ " ...,\n", " [0., 0., 0., ..., 0., 0., 0.],\n", " [0., 0., 0., ..., 0., 0., 0.],\n", - " [0., 0., 0., ..., 0., 0., 0.]]])
array([4530115., 4530125., 4530135., ..., 4535845., 4535855., 4535865.])
array([2696625., 2696615., 2696605., ..., 2691025., 2691015., 2691005.])
array(0)
array(['2019-12-15T10:17:33.408715000', '2020-09-05T10:17:43.167942000',\n", - " '2020-12-19T10:17:34.610661000'], dtype='datetime64[ns]')
array(0)
array([[1., 1., 1., ..., 1., 1., 1.],\n", + " [0., 0., 0., ..., 0., 0., 0.]]])
array([4530115., 4530125., 4530135., ..., 4535845., 4535855., 4535865.])
array([2696625., 2696615., 2696605., ..., 2691025., 2691015., 2691005.])
array(0)
array(['2019-12-15T10:17:33.408715000', '2020-09-05T10:17:43.167942000',\n", + " '2020-12-19T10:17:34.610661000'], dtype='datetime64[ns]')
array(0)
array([[1., 1., 1., ..., 1., 1., 1.],\n", " [1., 1., 1., ..., 1., 1., 1.],\n", " [1., 1., 1., ..., 1., 1., 1.],\n", " ...,\n", " [1., 1., 1., ..., 1., 1., 1.],\n", " [1., 1., 1., ..., 1., 1., 1.],\n", - " [1., 1., 1., ..., 1., 1., 1.]])
PandasIndex(Index([4530115.0, 4530125.0, 4530135.0, 4530145.0, 4530155.0, 4530165.0,\n", + " [1., 1., 1., ..., 1., 1., 1.]])
PandasIndex(Index([4530115.0, 4530125.0, 4530135.0, 4530145.0, 4530155.0, 4530165.0,\n", " 4530175.0, 4530185.0, 4530195.0, 4530205.0,\n", " ...\n", " 4535775.0, 4535785.0, 4535795.0, 4535805.0, 4535815.0, 4535825.0,\n", " 4535835.0, 4535845.0, 4535855.0, 4535865.0],\n", - " dtype='float64', name='x', length=576))
PandasIndex(Index([2696625.0, 2696615.0, 2696605.0, 2696595.0, 2696585.0, 2696575.0,\n", + " dtype='float64', name='x', length=576))
PandasIndex(Index([2696625.0, 2696615.0, 2696605.0, 2696595.0, 2696585.0, 2696575.0,\n", " 2696565.0, 2696555.0, 2696545.0, 2696535.0,\n", " ...\n", " 2691095.0, 2691085.0, 2691075.0, 2691065.0, 2691055.0, 2691045.0,\n", " 2691035.0, 2691025.0, 2691015.0, 2691005.0],\n", - " dtype='float64', name='y', length=563))
PandasIndex(DatetimeIndex(['2019-12-15 10:17:33.408715', '2020-09-05 10:17:43.167942',\n", + " dtype='float64', name='y', length=563))
PandasIndex(DatetimeIndex(['2019-12-15 10:17:33.408715', '2020-09-05 10:17:43.167942',\n", " '2020-12-19 10:17:34.610661'],\n", - " dtype='datetime64[ns]', name='time', freq=None))
array([[[1., 1., 1., 1.],\n", + " value_labels: {1: 'feature_1'}
array([[[1., 1., 1., 1.],\n", " [1., 1., 1., 1.],\n", " [1., 1., 1., 1.],\n", " [1., 1., 1., 1.]],\n", @@ -599,11 +599,11 @@ " [[1., 1., 1., 1.],\n", " [1., 1., 1., 1.],\n", " [1., 1., 1., 1.],\n", - " [1., 1., 1., 1.]]])
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array([2696250., 2694750., 2693250., 2691750.])
array([4530750., 4532250., 4533750., 4535250.])
array(0)
array([[1., 1., 1., 1.],\n", + " [1., 1., 1., 1.]]])
array(['2019-01-01T00:00:00.000000000', '2020-12-31T00:00:00.000000000'],\n", + " dtype='datetime64[ns]')
array([2696250., 2694750., 2693250., 2691750.])
array([4530750., 4532250., 4533750., 4535250.])
array(0)
array([[1., 1., 1., 1.],\n", " [1., 1., 1., 1.],\n", " [1., 1., 1., 1.],\n", - " [1., 1., 1., 1.]])
array(0)
PandasIndex(Index([2696250.0, 2694750.0, 2693250.0, 2691750.0], dtype='float64', name='y'))
PandasIndex(Index([4530750.0, 4532250.0, 4533750.0, 4535250.0], dtype='float64', name='x'))
PandasIndex(DatetimeIndex(['2019-01-01', '2020-12-31'], dtype='datetime64[ns]', name='time', freq=None))
array(0)
PandasIndex(Index([2696250.0, 2694750.0, 2693250.0, 2691750.0], dtype='float64', name='y'))
PandasIndex(Index([4530750.0, 4532250.0, 4533750.0, 4535250.0], dtype='float64', name='x'))
PandasIndex(DatetimeIndex(['2019-01-01', '2020-12-31'], dtype='datetime64[ns]', name='time', freq=None))
array([[[0., 0., 0., 0.],\n", + " value_type: binary
array([[[0., 0., 0., 0.],\n", " [0., 0., 0., 0.],\n", " [0., 0., 0., 0.],\n", " [0., 0., 0., 0.]],\n", @@ -1201,13 +1201,13 @@ " [[0., 1., 0., 1.],\n", " [1., 1., 0., 0.],\n", " [0., 0., 0., 0.],\n", - " [1., 0., 0., 1.]]])
array([4530750., 4532250., 4533750., 4535250.])
array([2696250., 2694750., 2693250., 2691750.])
array(0)
array(['2019-12-15T10:17:33.408715000', '2020-09-05T10:17:43.167942000',\n", - " '2020-12-19T10:17:34.610661000'], dtype='datetime64[ns]')
array(0)
array([[1., 1., 1., 1.],\n", + " [1., 0., 0., 1.]]])
array([4530750., 4532250., 4533750., 4535250.])
array([2696250., 2694750., 2693250., 2691750.])
array(0)
array(['2019-12-15T10:17:33.408715000', '2020-09-05T10:17:43.167942000',\n", + " '2020-12-19T10:17:34.610661000'], dtype='datetime64[ns]')
array(0)
array([[1., 1., 1., 1.],\n", " [1., 1., 1., 1.],\n", " [1., 1., 1., 1.],\n", - " [1., 1., 1., 1.]])
PandasIndex(Index([4530750.0, 4532250.0, 4533750.0, 4535250.0], dtype='float64', name='x'))
PandasIndex(Index([2696250.0, 2694750.0, 2693250.0, 2691750.0], dtype='float64', name='y'))
PandasIndex(DatetimeIndex(['2019-12-15 10:17:33.408715', '2020-09-05 10:17:43.167942',\n", + " [1., 1., 1., 1.]])
PandasIndex(Index([4530750.0, 4532250.0, 4533750.0, 4535250.0], dtype='float64', name='x'))
PandasIndex(Index([2696250.0, 2694750.0, 2693250.0, 2691750.0], dtype='float64', name='y'))
PandasIndex(DatetimeIndex(['2019-12-15 10:17:33.408715', '2020-09-05 10:17:43.167942',\n", " '2020-12-19 10:17:34.610661'],\n", - " dtype='datetime64[ns]', name='time', freq=None))
array([[[0., 0., 0., 0.],\n", + " value_type: binary
array([[[0., 0., 0., 0.],\n", " [0., 0., 0., 0.],\n", " [0., 0., 0., 0.],\n", " [0., 0., 0., 0.]],\n", @@ -2205,13 +2205,13 @@ " [[1., 0., 0., 0.],\n", " [0., 0., 0., 1.],\n", " [1., 0., 0., 0.],\n", - " [0., 0., 0., 0.]]])
array([4530750., 4532250., 4533750., 4535250.])
array([2696250., 2694750., 2693250., 2691750.])
array(0)
array(['2019-12-15T10:17:33.408715000', '2020-09-05T10:17:43.167942000',\n", - " '2020-12-19T10:17:34.610661000'], dtype='datetime64[ns]')
array(0)
array([[1., 1., 1., 1.],\n", + " [0., 0., 0., 0.]]])
array([4530750., 4532250., 4533750., 4535250.])
array([2696250., 2694750., 2693250., 2691750.])
array(0)
array(['2019-12-15T10:17:33.408715000', '2020-09-05T10:17:43.167942000',\n", + " '2020-12-19T10:17:34.610661000'], dtype='datetime64[ns]')
array(0)
array([[1., 1., 1., 1.],\n", " [1., 1., 1., 1.],\n", " [1., 1., 1., 1.],\n", - " [1., 1., 1., 1.]])
PandasIndex(Index([4530750.0, 4532250.0, 4533750.0, 4535250.0], dtype='float64', name='x'))
PandasIndex(Index([2696250.0, 2694750.0, 2693250.0, 2691750.0], dtype='float64', name='y'))
PandasIndex(DatetimeIndex(['2019-12-15 10:17:33.408715', '2020-09-05 10:17:43.167942',\n", + " [1., 1., 1., 1.]])
PandasIndex(Index([4530750.0, 4532250.0, 4533750.0, 4535250.0], dtype='float64', name='x'))
PandasIndex(Index([2696250.0, 2694750.0, 2693250.0, 2691750.0], dtype='float64', name='y'))
PandasIndex(DatetimeIndex(['2019-12-15 10:17:33.408715', '2020-09-05 10:17:43.167942',\n", " '2020-12-19 10:17:34.610661'],\n", - " dtype='datetime64[ns]', name='time', freq=None))
array([[1., 1., 1., ..., 0., 0., 0.],\n", + " value_type: discrete
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array([4530115., 4530125., 4530135., ..., 4535845., 4535855., 4535865.])
array([2696625., 2696615., 2696605., ..., 2691025., 2691015., 2691005.])
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array(0)
array([[1., 1., 1., ..., 1., 1., 1.],\n", + " [0., 0., 0., ..., 0., 0., 0.]])
array([4530115., 4530125., 4530135., ..., 4535845., 4535855., 4535865.])
array([2696625., 2696615., 2696605., ..., 2691025., 2691015., 2691005.])
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array(0)
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PandasIndex(Index([4530115.0, 4530125.0, 4530135.0, 4530145.0, 4530155.0, 4530165.0,\n", + " [1., 1., 1., ..., 1., 1., 1.]])
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array([ 0., 44804., 78607.])
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array(123411.)
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array(0)
array(123411.)
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array(0)
array([[1., 1., 1., ..., 0., 0., 0.],\n", + " value_type: discrete
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array([4530115., 4530125., 4530135., ..., 4535845., 4535855., 4535865.])
array([2696625., 2696615., 2696605., ..., 2691025., 2691015., 2691005.])
array(0)
array(0)
array([[1., 1., 1., ..., 1., 1., 1.],\n", + " [0., 0., 0., ..., 0., 0., 0.]])
array([4530115., 4530125., 4530135., ..., 4535845., 4535855., 4535865.])
array([2696625., 2696615., 2696605., ..., 2691025., 2691015., 2691005.])
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array(0)
array([[1., 1., 1., ..., 1., 1., 1.],\n", " [1., 1., 1., ..., 1., 1., 1.],\n", " [1., 1., 1., ..., 1., 1., 1.],\n", " ...,\n", " [1., 1., 1., ..., 1., 1., 1.],\n", " [1., 1., 1., ..., 1., 1., 1.],\n", - " [1., 1., 1., ..., 1., 1., 1.]])
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PandasIndex(Index([4530115.0, 4530125.0, 4530135.0, 4530145.0, 4530155.0, 4530165.0,\n", " 4530175.0, 4530185.0, 4530195.0, 4530205.0,\n", " ...\n", " 4535775.0, 4535785.0, 4535795.0, 4535805.0, 4535815.0, 4535825.0,\n", " 4535835.0, 4535845.0, 4535855.0, 4535865.0],\n", - " dtype='float64', name='x', length=576))
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PandasIndex(Index([2696625.0, 2696615.0, 2696605.0, 2696595.0, 2696585.0, 2696575.0,\n", " 2696565.0, 2696555.0, 2696545.0, 2696535.0,\n", " ...\n", " 2691095.0, 2691085.0, 2691075.0, 2691065.0, 2691055.0, 2691045.0,\n", " 2691035.0, 2691025.0, 2691015.0, 2691005.0],\n", - " dtype='float64', name='y', length=563))
array([[[0., 0., 0.],\n", + " value_type: binary
array([[[0., 0., 0.],\n", " [0., 0., 0.],\n", " [0., 0., 0.]],\n", "\n", @@ -613,12 +613,12 @@ "\n", " [[0., 0., 0.],\n", " [1., 0., 0.],\n", - " [1., 0., 0.]]])
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array([2695500., 2693700., 2691900.])
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array(0)
array([[1., 1., 1.],\n", " [1., 1., 1.],\n", - " [1., 1., 1.]])
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PandasIndex(DatetimeIndex(['2019-12-15 10:17:33.408715', '2020-09-05 10:17:43.167942',\n", + " [1., 1., 1.]])
PandasIndex(Index([4531500.0, 4533300.0, 4535100.0], dtype='float64', name='x'))
PandasIndex(Index([2695500.0, 2693700.0, 2691900.0], dtype='float64', name='y'))
PandasIndex(DatetimeIndex(['2019-12-15 10:17:33.408715', '2020-09-05 10:17:43.167942',\n", " '2020-12-19 10:17:34.610661'],\n", - " dtype='datetime64[ns]', name='time', freq=None))
array([[[1., 1., 1.],\n", + " value_type: binary
array([[[1., 1., 1.],\n", " [1., 1., 1.],\n", " [1., 1., 1.]],\n", "\n", @@ -1063,12 +1063,12 @@ "\n", " [[1., 1., 1.],\n", " [0., 1., 1.],\n", - " [0., 1., 1.]]])
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PandasIndex(Index([2695500.0, 2693700.0, 2691900.0], dtype='float64', name='y'))
PandasIndex(Index([4531500.0, 4533300.0, 4535100.0], dtype='float64', name='x'))
PandasIndex(Index([2695500.0, 2693700.0, 2691900.0], dtype='float64', name='y'))
PandasIndex(Index([4531500.0, 4533300.0, 4535100.0], dtype='float64', name='x'))
array([2019, 2020, 2020])
array(0)
array(['2019-12-15T10:17:33.408715000', '2020-09-05T10:17:43.167942000',\n", - " '2020-12-19T10:17:34.610661000'], dtype='datetime64[ns]')
array(0)
PandasIndex(DatetimeIndex(['2019-12-15 10:17:33.408715', '2020-09-05 10:17:43.167942',\n", + " value_type: discrete
array([2019, 2020, 2020])
array(0)
array(['2019-12-15T10:17:33.408715000', '2020-09-05T10:17:43.167942000',\n", + " '2020-12-19T10:17:34.610661000'], dtype='datetime64[ns]')
array(0)
PandasIndex(DatetimeIndex(['2019-12-15 10:17:33.408715', '2020-09-05 10:17:43.167942',\n", " '2020-12-19 10:17:34.610661'],\n", - " dtype='datetime64[ns]', name='time', freq=None))
array([[1., 1., 1.],\n", + " value_labels: {1: 'feature_1'}
array([[1., 1., 1.],\n", " [1., 1., 1.],\n", - " [1., 1., 1.]])
array([4531500., 4533300., 4535100.])
array([2695500., 2693700., 2691900.])
array(0)
array(0)
array([[1., 1., 1.],\n", + " [1., 1., 1.]])
array([4531500., 4533300., 4535100.])
array([2695500., 2693700., 2691900.])
array(0)
array(0)
array([[1., 1., 1.],\n", " [1., 1., 1.],\n", - " [1., 1., 1.]])
PandasIndex(Index([4531500.0, 4533300.0, 4535100.0], dtype='float64', name='x'))
PandasIndex(Index([2695500.0, 2693700.0, 2691900.0], dtype='float64', name='y'))
PandasIndex(Index([4531500.0, 4533300.0, 4535100.0], dtype='float64', name='x'))
PandasIndex(Index([2695500.0, 2693700.0, 2691900.0], dtype='float64', name='y'))
array([[[0., 0., 0.],\n", + " value_type: binary
array([[[0., 0., 0.],\n", " [0., 0., 0.],\n", " [0., 0., 0.]],\n", "\n", @@ -10199,12 +10199,12 @@ "\n", " [[0., 0., 0.],\n", " [1., 0., 0.],\n", - " [1., 0., 0.]]])
array([4531500., 4533300., 4535100.])
array([2695500., 2693700., 2691900.])
array(0)
array(['2019-12-15T10:17:33.408715000', '2020-09-05T10:17:43.167942000',\n", - " '2020-12-19T10:17:34.610661000'], dtype='datetime64[ns]')
array(0)
array([[1., 1., 1.],\n", + " [1., 0., 0.]]])
array([4531500., 4533300., 4535100.])
array([2695500., 2693700., 2691900.])
array(0)
array(['2019-12-15T10:17:33.408715000', '2020-09-05T10:17:43.167942000',\n", + " '2020-12-19T10:17:34.610661000'], dtype='datetime64[ns]')
array(0)
array([[1., 1., 1.],\n", " [1., 1., 1.],\n", - " [1., 1., 1.]])
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PandasIndex(Index([2695500.0, 2693700.0, 2691900.0], dtype='float64', name='y'))
PandasIndex(DatetimeIndex(['2019-12-15 10:17:33.408715', '2020-09-05 10:17:43.167942',\n", + " [1., 1., 1.]])
PandasIndex(Index([4531500.0, 4533300.0, 4535100.0], dtype='float64', name='x'))
PandasIndex(Index([2695500.0, 2693700.0, 2691900.0], dtype='float64', name='y'))
PandasIndex(DatetimeIndex(['2019-12-15 10:17:33.408715', '2020-09-05 10:17:43.167942',\n", " '2020-12-19 10:17:34.610661'],\n", - " dtype='datetime64[ns]', name='time', freq=None))
array([[[1., 0., 1.],\n", + " value_type: binary
array([[[1., 0., 1.],\n", " [1., 0., 1.],\n", " [1., 1., 1.]],\n", "\n", @@ -10649,12 +10649,12 @@ "\n", " [[1., 1., 1.],\n", " [1., 1., 1.],\n", - " [1., 1., 1.]]])
array([4531500., 4533300., 4535100.])
array([2695500., 2693700., 2691900.])
array(0)
array(['2019-12-15T10:17:33.408715000', '2020-09-05T10:17:43.167942000',\n", - " '2020-12-19T10:17:34.610661000'], dtype='datetime64[ns]')
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array([[1., 1., 1.],\n", + " [1., 1., 1.]]])
array([4531500., 4533300., 4535100.])
array([2695500., 2693700., 2691900.])
array(0)
array(['2019-12-15T10:17:33.408715000', '2020-09-05T10:17:43.167942000',\n", + " '2020-12-19T10:17:34.610661000'], dtype='datetime64[ns]')
array(0)
array([[1., 1., 1.],\n", " [1., 1., 1.],\n", - " [1., 1., 1.]])
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PandasIndex(Index([2695500.0, 2693700.0, 2691900.0], dtype='float64', name='y'))
PandasIndex(DatetimeIndex(['2019-12-15 10:17:33.408715', '2020-09-05 10:17:43.167942',\n", + " [1., 1., 1.]])
PandasIndex(Index([4531500.0, 4533300.0, 4535100.0], dtype='float64', name='x'))
PandasIndex(Index([2695500.0, 2693700.0, 2691900.0], dtype='float64', name='y'))
PandasIndex(DatetimeIndex(['2019-12-15 10:17:33.408715', '2020-09-05 10:17:43.167942',\n", " '2020-12-19 10:17:34.610661'],\n", - " dtype='datetime64[ns]', name='time', freq=None))
array([[[ 0., nan, 0.],\n", + " value_type: binary
array([[[ 0., nan, 0.],\n", " [ 0., nan, 0.],\n", " [ 0., 0., 0.]],\n", "\n", @@ -11099,12 +11099,12 @@ "\n", " [[ 0., 0., 0.],\n", " [ 1., 0., 0.],\n", - " [ 1., 0., 0.]]])
array([4531500., 4533300., 4535100.])
array([2695500., 2693700., 2691900.])
array(0)
array(['2019-12-15T10:17:33.408715000', '2020-09-05T10:17:43.167942000',\n", - " '2020-12-19T10:17:34.610661000'], dtype='datetime64[ns]')
array(0)
array([[1., 1., 1.],\n", + " [ 1., 0., 0.]]])
array([4531500., 4533300., 4535100.])
array([2695500., 2693700., 2691900.])
array(0)
array(['2019-12-15T10:17:33.408715000', '2020-09-05T10:17:43.167942000',\n", + " '2020-12-19T10:17:34.610661000'], dtype='datetime64[ns]')
array(0)
array([[1., 1., 1.],\n", " [1., 1., 1.],\n", - " [1., 1., 1.]])
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PandasIndex(Index([2695500.0, 2693700.0, 2691900.0], dtype='float64', name='y'))
PandasIndex(DatetimeIndex(['2019-12-15 10:17:33.408715', '2020-09-05 10:17:43.167942',\n", + " [1., 1., 1.]])
PandasIndex(Index([4531500.0, 4533300.0, 4535100.0], dtype='float64', name='x'))
PandasIndex(Index([2695500.0, 2693700.0, 2691900.0], dtype='float64', name='y'))
PandasIndex(DatetimeIndex(['2019-12-15 10:17:33.408715', '2020-09-05 10:17:43.167942',\n", " '2020-12-19 10:17:34.610661'],\n", - " dtype='datetime64[ns]', name='time', freq=None))
array([[2., 0., 1.],\n", + " value_type: discrete
array([[2., 0., 1.],\n", " [1., 0., 2.],\n", - " [1., 1., 2.]])
array([4531500., 4533300., 4535100.])
array([2695500., 2693700., 2691900.])
array(0)
array(0)
array([[1., 1., 1.],\n", + " [1., 1., 2.]])
array([4531500., 4533300., 4535100.])
array([2695500., 2693700., 2691900.])
array(0)
array(0)
array([[1., 1., 1.],\n", " [1., 1., 1.],\n", - " [1., 1., 1.]])
PandasIndex(Index([4531500.0, 4533300.0, 4535100.0], dtype='float64', name='x'))
PandasIndex(Index([2695500.0, 2693700.0, 2691900.0], dtype='float64', name='y'))
PandasIndex(Index([4531500.0, 4533300.0, 4535100.0], dtype='float64', name='x'))
PandasIndex(Index([2695500.0, 2693700.0, 2691900.0], dtype='float64', name='y'))
array([[ 2., nan, nan],\n", + " value_type: discrete
array([[ 2., nan, nan],\n", " [nan, nan, 2.],\n", - " [nan, nan, 2.]])
array([4531500., 4533300., 4535100.])
array([2695500., 2693700., 2691900.])
array(0)
array(0)
array([[1., 1., 1.],\n", + " [nan, nan, 2.]])
array([4531500., 4533300., 4535100.])
array([2695500., 2693700., 2691900.])
array(0)
array(0)
array([[1., 1., 1.],\n", " [1., 1., 1.],\n", - " [1., 1., 1.]])
PandasIndex(Index([4531500.0, 4533300.0, 4535100.0], dtype='float64', name='x'))
PandasIndex(Index([2695500.0, 2693700.0, 2691900.0], dtype='float64', name='y'))
PandasIndex(Index([4531500.0, 4533300.0, 4535100.0], dtype='float64', name='x'))
PandasIndex(Index([2695500.0, 2693700.0, 2691900.0], dtype='float64', name='y'))
array([[[nan, nan, nan],\n", + " value_type: binary
array([[[nan, nan, nan],\n", " [nan, nan, nan],\n", " [nan, nan, nan]],\n", "\n", @@ -12458,12 +12458,12 @@ "\n", " [[ 0., 0., 0.],\n", " [ 1., 0., 0.],\n", - " [ 1., 0., 0.]]])
array([4531500., 4533300., 4535100.])
array([2695500., 2693700., 2691900.])
array(0)
array(['2019-12-15T10:17:33.408715000', '2020-09-05T10:17:43.167942000',\n", - " '2020-12-19T10:17:34.610661000'], dtype='datetime64[ns]')
array(0)
array([[1., 1., 1.],\n", + " [ 1., 0., 0.]]])
array([4531500., 4533300., 4535100.])
array([2695500., 2693700., 2691900.])
array(0)
array(['2019-12-15T10:17:33.408715000', '2020-09-05T10:17:43.167942000',\n", + " '2020-12-19T10:17:34.610661000'], dtype='datetime64[ns]')
array(0)
array([[1., 1., 1.],\n", " [1., 1., 1.],\n", - " [1., 1., 1.]])
PandasIndex(Index([4531500.0, 4533300.0, 4535100.0], dtype='float64', name='x'))
PandasIndex(Index([2695500.0, 2693700.0, 2691900.0], dtype='float64', name='y'))
PandasIndex(DatetimeIndex(['2019-12-15 10:17:33.408715', '2020-09-05 10:17:43.167942',\n", + " [1., 1., 1.]])
PandasIndex(Index([4531500.0, 4533300.0, 4535100.0], dtype='float64', name='x'))
PandasIndex(Index([2695500.0, 2693700.0, 2691900.0], dtype='float64', name='y'))
PandasIndex(DatetimeIndex(['2019-12-15 10:17:33.408715', '2020-09-05 10:17:43.167942',\n", " '2020-12-19 10:17:34.610661'],\n", - " dtype='datetime64[ns]', name='time', freq=None))
array([[[nan, nan, nan],\n", + " value_type: binary
array([[[nan, nan, nan],\n", " [nan, nan, nan],\n", " [nan, nan, nan]],\n", "\n", @@ -12938,12 +12938,12 @@ "\n", " [[ 0., 0., 0.],\n", " [ 1., 0., 0.],\n", - " [ 1., 0., 0.]]])
array([4531500., 4533300., 4535100.])
array([2695500., 2693700., 2691900.])
array(0)
array(['2019-12-15T10:17:33.408715000', '2020-09-05T10:17:43.167942000',\n", - " '2020-12-19T10:17:34.610661000'], dtype='datetime64[ns]')
array(0)
array([[1., 1., 1.],\n", + " [ 1., 0., 0.]]])
array([4531500., 4533300., 4535100.])
array([2695500., 2693700., 2691900.])
array(0)
array(['2019-12-15T10:17:33.408715000', '2020-09-05T10:17:43.167942000',\n", + " '2020-12-19T10:17:34.610661000'], dtype='datetime64[ns]')
array(0)
array([[1., 1., 1.],\n", " [1., 1., 1.],\n", - " [1., 1., 1.]])
PandasIndex(Index([4531500.0, 4533300.0, 4535100.0], dtype='float64', name='x'))
PandasIndex(Index([2695500.0, 2693700.0, 2691900.0], dtype='float64', name='y'))
PandasIndex(DatetimeIndex(['2019-12-15 10:17:33.408715', '2020-09-05 10:17:43.167942',\n", + " [1., 1., 1.]])
PandasIndex(Index([4531500.0, 4533300.0, 4535100.0], dtype='float64', name='x'))
PandasIndex(Index([2695500.0, 2693700.0, 2691900.0], dtype='float64', name='y'))
PandasIndex(DatetimeIndex(['2019-12-15 10:17:33.408715', '2020-09-05 10:17:43.167942',\n", " '2020-12-19 10:17:34.610661'],\n", - " dtype='datetime64[ns]', name='time', freq=None))
array([[[0., 0., 0.],\n", + " value_type: binary
array([[[0., 0., 0.],\n", " [0., 0., 0.],\n", " [0., 0., 0.]],\n", "\n", @@ -13431,12 +13431,12 @@ "\n", " [[1., 0., 0.],\n", " [0., 0., 1.],\n", - " [0., 0., 1.]]])
array([4531500., 4533300., 4535100.])
array([2695500., 2693700., 2691900.])
array(0)
array(['2019-12-15T10:17:33.408715000', '2020-09-05T10:17:43.167942000',\n", - " '2020-12-19T10:17:34.610661000'], dtype='datetime64[ns]')
array(0)
array([[1., 1., 1.],\n", + " [0., 0., 1.]]])
array([4531500., 4533300., 4535100.])
array([2695500., 2693700., 2691900.])
array(0)
array(['2019-12-15T10:17:33.408715000', '2020-09-05T10:17:43.167942000',\n", + " '2020-12-19T10:17:34.610661000'], dtype='datetime64[ns]')
array(0)
array([[1., 1., 1.],\n", " [1., 1., 1.],\n", - " [1., 1., 1.]])
PandasIndex(Index([4531500.0, 4533300.0, 4535100.0], dtype='float64', name='x'))
PandasIndex(Index([2695500.0, 2693700.0, 2691900.0], dtype='float64', name='y'))
PandasIndex(DatetimeIndex(['2019-12-15 10:17:33.408715', '2020-09-05 10:17:43.167942',\n", + " [1., 1., 1.]])
PandasIndex(Index([4531500.0, 4533300.0, 4535100.0], dtype='float64', name='x'))
PandasIndex(Index([2695500.0, 2693700.0, 2691900.0], dtype='float64', name='y'))
PandasIndex(DatetimeIndex(['2019-12-15 10:17:33.408715', '2020-09-05 10:17:43.167942',\n", " '2020-12-19 10:17:34.610661'],\n", - " dtype='datetime64[ns]', name='time', freq=None))
array([[[nan, nan, nan],\n", + " value_type: binary
array([[[nan, nan, nan],\n", " [nan, nan, nan],\n", " [nan, nan, nan]],\n", "\n", @@ -13881,12 +13881,12 @@ "\n", " [[ 1., nan, nan],\n", " [nan, nan, 1.],\n", - " [nan, nan, 1.]]])
array([4531500., 4533300., 4535100.])
array([2695500., 2693700., 2691900.])
array(0)
array(['2019-12-15T10:17:33.408715000', '2020-09-05T10:17:43.167942000',\n", - " '2020-12-19T10:17:34.610661000'], dtype='datetime64[ns]')
array(0)
array([[1., 1., 1.],\n", + " [nan, nan, 1.]]])
array([4531500., 4533300., 4535100.])
array([2695500., 2693700., 2691900.])
array(0)
array(['2019-12-15T10:17:33.408715000', '2020-09-05T10:17:43.167942000',\n", + " '2020-12-19T10:17:34.610661000'], dtype='datetime64[ns]')
array(0)
array([[1., 1., 1.],\n", " [1., 1., 1.],\n", - " [1., 1., 1.]])
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PandasIndex(Index([2695500.0, 2693700.0, 2691900.0], dtype='float64', name='y'))
PandasIndex(DatetimeIndex(['2019-12-15 10:17:33.408715', '2020-09-05 10:17:43.167942',\n", + " [1., 1., 1.]])
PandasIndex(Index([4531500.0, 4533300.0, 4535100.0], dtype='float64', name='x'))
PandasIndex(Index([2695500.0, 2693700.0, 2691900.0], dtype='float64', name='y'))
PandasIndex(DatetimeIndex(['2019-12-15 10:17:33.408715', '2020-09-05 10:17:43.167942',\n", " '2020-12-19 10:17:34.610661'],\n", - " dtype='datetime64[ns]', name='time', freq=None))
array([[[0., 0., 0.],\n", + " value_type: binary
array([[[0., 0., 0.],\n", " [0., 0., 0.],\n", " [0., 0., 0.]],\n", "\n", @@ -14376,12 +14376,12 @@ "\n", " [[1., 0., 0.],\n", " [0., 0., 1.],\n", - " [0., 0., 1.]]])
array([4531500., 4533300., 4535100.])
array([2695500., 2693700., 2691900.])
array(0)
array(['2019-12-15T10:17:33.408715000', '2020-09-05T10:17:43.167942000',\n", - " '2020-12-19T10:17:34.610661000'], dtype='datetime64[ns]')
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array([4531500., 4533300., 4535100.])
array([2695500., 2693700., 2691900.])
array(0)
array(['2019-12-15T10:17:33.408715000', '2020-09-05T10:17:43.167942000',\n", + " '2020-12-19T10:17:34.610661000'], dtype='datetime64[ns]')
array(0)
array([[1., 1., 1.],\n", " [1., 1., 1.],\n", - " [1., 1., 1.]])
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PandasIndex(Index([2695500.0, 2693700.0, 2691900.0], dtype='float64', name='y'))
PandasIndex(DatetimeIndex(['2019-12-15 10:17:33.408715', '2020-09-05 10:17:43.167942',\n", + " [1., 1., 1.]])
PandasIndex(Index([4531500.0, 4533300.0, 4535100.0], dtype='float64', name='x'))
PandasIndex(Index([2695500.0, 2693700.0, 2691900.0], dtype='float64', name='y'))
PandasIndex(DatetimeIndex(['2019-12-15 10:17:33.408715', '2020-09-05 10:17:43.167942',\n", " '2020-12-19 10:17:34.610661'],\n", - " dtype='datetime64[ns]', name='time', freq=None))
array([[[-99., -99., -99.],\n", + " value_type: continuous
array([[[-99., -99., -99.],\n", " [-99., -99., -99.],\n", " [-99., -99., -99.]],\n", "\n", @@ -14826,12 +14826,12 @@ "\n", " [[-99., -99., -99.],\n", " [-99., -99., -99.],\n", - " [-99., -99., -99.]]])
array([4531500., 4533300., 4535100.])
array([2695500., 2693700., 2691900.])
array(0)
array(['2019-12-15T10:17:33.408715000', '2020-09-05T10:17:43.167942000',\n", - " '2020-12-19T10:17:34.610661000'], dtype='datetime64[ns]')
array(0)
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array([4531500., 4533300., 4535100.])
array([2695500., 2693700., 2691900.])
array(0)
array(['2019-12-15T10:17:33.408715000', '2020-09-05T10:17:43.167942000',\n", + " '2020-12-19T10:17:34.610661000'], dtype='datetime64[ns]')
array(0)
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PandasIndex(Index([2695500.0, 2693700.0, 2691900.0], dtype='float64', name='y'))
PandasIndex(DatetimeIndex(['2019-12-15 10:17:33.408715', '2020-09-05 10:17:43.167942',\n", + " [1., 1., 1.]])
PandasIndex(Index([4531500.0, 4533300.0, 4535100.0], dtype='float64', name='x'))
PandasIndex(Index([2695500.0, 2693700.0, 2691900.0], dtype='float64', name='y'))
PandasIndex(DatetimeIndex(['2019-12-15 10:17:33.408715', '2020-09-05 10:17:43.167942',\n", " '2020-12-19 10:17:34.610661'],\n", - " dtype='datetime64[ns]', name='time', freq=None))
array([[2., 0., 1.],\n", + " value_type: discrete
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array([4531500., 4533300., 4535100.])
array([2695500., 2693700., 2691900.])
array(0)
array(0)
array([[1., 1., 1.],\n", + " [1., 1., 2.]])
array([4531500., 4533300., 4535100.])
array([2695500., 2693700., 2691900.])
array(0)
array(0)
array([[1., 1., 1.],\n", " [1., 1., 1.],\n", - " [1., 1., 1.]])
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PandasIndex(Index([2695500.0, 2693700.0, 2691900.0], dtype='float64', name='y'))
PandasIndex(Index([4531500.0, 4533300.0, 4535100.0], dtype='float64', name='x'))
PandasIndex(Index([2695500.0, 2693700.0, 2691900.0], dtype='float64', name='y'))
array([[2., 0., 0.],\n", + " value_type: discrete
array([[2., 0., 0.],\n", " [0., 0., 2.],\n", - " [0., 0., 2.]])
array([4531500., 4533300., 4535100.])
array([2695500., 2693700., 2691900.])
array(0)
array(0)
array([[1., 1., 1.],\n", + " [0., 0., 2.]])
array([4531500., 4533300., 4535100.])
array([2695500., 2693700., 2691900.])
array(0)
array(0)
array([[1., 1., 1.],\n", " [1., 1., 1.],\n", - " [1., 1., 1.]])
PandasIndex(Index([4531500.0, 4533300.0, 4535100.0], dtype='float64', name='x'))
PandasIndex(Index([2695500.0, 2693700.0, 2691900.0], dtype='float64', name='y'))
PandasIndex(Index([4531500.0, 4533300.0, 4535100.0], dtype='float64', name='x'))
PandasIndex(Index([2695500.0, 2693700.0, 2691900.0], dtype='float64', name='y'))
array([[[0., 0., 0.],\n", + " value_type: binary
array([[[0., 0., 0.],\n", " [0., 0., 0.],\n", " [0., 0., 0.]],\n", "\n", @@ -16192,12 +16192,12 @@ "\n", " [[1., 0., 0.],\n", " [0., 0., 1.],\n", - " [0., 0., 1.]]])
array([4531500., 4533300., 4535100.])
array([2695500., 2693700., 2691900.])
array(0)
array(['2019-12-15T10:17:33.408715000', '2020-09-05T10:17:43.167942000',\n", - " '2020-12-19T10:17:34.610661000'], dtype='datetime64[ns]')
array(0)
array([[1., 1., 1.],\n", + " [0., 0., 1.]]])
array([4531500., 4533300., 4535100.])
array([2695500., 2693700., 2691900.])
array(0)
array(['2019-12-15T10:17:33.408715000', '2020-09-05T10:17:43.167942000',\n", + " '2020-12-19T10:17:34.610661000'], dtype='datetime64[ns]')
array(0)
array([[1., 1., 1.],\n", " [1., 1., 1.],\n", - " [1., 1., 1.]])
PandasIndex(Index([4531500.0, 4533300.0, 4535100.0], dtype='float64', name='x'))
PandasIndex(Index([2695500.0, 2693700.0, 2691900.0], dtype='float64', name='y'))
PandasIndex(DatetimeIndex(['2019-12-15 10:17:33.408715', '2020-09-05 10:17:43.167942',\n", + " [1., 1., 1.]])
PandasIndex(Index([4531500.0, 4533300.0, 4535100.0], dtype='float64', name='x'))
PandasIndex(Index([2695500.0, 2693700.0, 2691900.0], dtype='float64', name='y'))
PandasIndex(DatetimeIndex(['2019-12-15 10:17:33.408715', '2020-09-05 10:17:43.167942',\n", " '2020-12-19 10:17:34.610661'],\n", - " dtype='datetime64[ns]', name='time', freq=None))
array([[[12., 12., 12.],\n", + " value_labels: {1: 'January', 2: 'February', 3: 'March', 4: 'April', 5: ...
array([[[12., 12., 12.],\n", " [12., 12., 12.],\n", " [12., 12., 12.]],\n", "\n", @@ -16643,12 +16643,12 @@ "\n", " [[12., 12., 12.],\n", " [12., 12., 12.],\n", - " [12., 12., 12.]]])
array([4531500., 4533300., 4535100.])
array([2695500., 2693700., 2691900.])
array(0)
array(['2019-12-15T10:17:33.408715000', '2020-09-05T10:17:43.167942000',\n", - " '2020-12-19T10:17:34.610661000'], dtype='datetime64[ns]')
array(0)
array([[1., 1., 1.],\n", + " [12., 12., 12.]]])
array([4531500., 4533300., 4535100.])
array([2695500., 2693700., 2691900.])
array(0)
array(['2019-12-15T10:17:33.408715000', '2020-09-05T10:17:43.167942000',\n", + " '2020-12-19T10:17:34.610661000'], dtype='datetime64[ns]')
array(0)
array([[1., 1., 1.],\n", " [1., 1., 1.],\n", - " [1., 1., 1.]])
PandasIndex(Index([4531500.0, 4533300.0, 4535100.0], dtype='float64', name='x'))
PandasIndex(Index([2695500.0, 2693700.0, 2691900.0], dtype='float64', name='y'))
PandasIndex(DatetimeIndex(['2019-12-15 10:17:33.408715', '2020-09-05 10:17:43.167942',\n", + " [1., 1., 1.]])
PandasIndex(Index([4531500.0, 4533300.0, 4535100.0], dtype='float64', name='x'))
PandasIndex(Index([2695500.0, 2693700.0, 2691900.0], dtype='float64', name='y'))
PandasIndex(DatetimeIndex(['2019-12-15 10:17:33.408715', '2020-09-05 10:17:43.167942',\n", " '2020-12-19 10:17:34.610661'],\n", - " dtype='datetime64[ns]', name='time', freq=None))
array([[[12., 12., 12.],\n", + " value_labels: {1: 'January', 2: 'February', 3: 'March', 4: 'April', 5: ...
array([[[12., 12., 12.],\n", " [12., 12., 12.],\n", " [12., 12., 12.]],\n", "\n", @@ -17125,12 +17125,12 @@ "\n", " [[12., 12., 12.],\n", " [12., 12., 12.],\n", - " [12., 12., 12.]]])
array([4531500., 4533300., 4535100.])
array([2695500., 2693700., 2691900.])
array(0)
array(['2019-12-15T10:17:33.408715000', '2020-09-05T10:17:43.167942000',\n", - " '2020-12-19T10:17:34.610661000'], dtype='datetime64[ns]')
array(0)
array([[1., 1., 1.],\n", + " [12., 12., 12.]]])
array([4531500., 4533300., 4535100.])
array([2695500., 2693700., 2691900.])
array(0)
array(['2019-12-15T10:17:33.408715000', '2020-09-05T10:17:43.167942000',\n", + " '2020-12-19T10:17:34.610661000'], dtype='datetime64[ns]')
array(0)
array([[1., 1., 1.],\n", " [1., 1., 1.],\n", - " [1., 1., 1.]])
PandasIndex(Index([4531500.0, 4533300.0, 4535100.0], dtype='float64', name='x'))
PandasIndex(Index([2695500.0, 2693700.0, 2691900.0], dtype='float64', name='y'))
PandasIndex(DatetimeIndex(['2019-12-15 10:17:33.408715', '2020-09-05 10:17:43.167942',\n", + " [1., 1., 1.]])
PandasIndex(Index([4531500.0, 4533300.0, 4535100.0], dtype='float64', name='x'))
PandasIndex(Index([2695500.0, 2693700.0, 2691900.0], dtype='float64', name='y'))
PandasIndex(DatetimeIndex(['2019-12-15 10:17:33.408715', '2020-09-05 10:17:43.167942',\n", " '2020-12-19 10:17:34.610661'],\n", - " dtype='datetime64[ns]', name='time', freq=None))
array([[ 2., nan, 1.],\n", + " value_type: discrete
array([[ 2., nan, 1.],\n", " [ 1., nan, 2.],\n", - " [ 1., 1., 2.]])
array([4531500., 4533300., 4535100.])
array([2695500., 2693700., 2691900.])
array(0)
array(0)
array([[1., 1., 1.],\n", + " [ 1., 1., 2.]])
array([4531500., 4533300., 4535100.])
array([2695500., 2693700., 2691900.])
array(0)
array(0)
array([[1., 1., 1.],\n", " [1., 1., 1.],\n", - " [1., 1., 1.]])
PandasIndex(Index([4531500.0, 4533300.0, 4535100.0], dtype='float64', name='x'))
PandasIndex(Index([2695500.0, 2693700.0, 2691900.0], dtype='float64', name='y'))
PandasIndex(Index([4531500.0, 4533300.0, 4535100.0], dtype='float64', name='x'))
PandasIndex(Index([2695500.0, 2693700.0, 2691900.0], dtype='float64', name='y'))
array([[ 2., -999., 1.],\n", + " value_type: discrete
array([[ 2., -999., 1.],\n", " [ 1., -999., 2.],\n", - " [ 1., 1., 2.]])
array([4531500., 4533300., 4535100.])
array([2695500., 2693700., 2691900.])
array(0)
array(0)
array([[1., 1., 1.],\n", + " [ 1., 1., 2.]])
array([4531500., 4533300., 4535100.])
array([2695500., 2693700., 2691900.])
array(0)
array(0)
array([[1., 1., 1.],\n", " [1., 1., 1.],\n", - " [1., 1., 1.]])
PandasIndex(Index([4531500.0, 4533300.0, 4535100.0], dtype='float64', name='x'))
PandasIndex(Index([2695500.0, 2693700.0, 2691900.0], dtype='float64', name='y'))
PandasIndex(Index([4531500.0, 4533300.0, 4535100.0], dtype='float64', name='x'))
PandasIndex(Index([2695500.0, 2693700.0, 2691900.0], dtype='float64', name='y'))
array([[[0., 0., 0.],\n", + " value_type: binary
array([[[0., 0., 0.],\n", " [0., 0., 0.],\n", " [0., 0., 0.]],\n", "\n", @@ -18532,12 +18532,12 @@ "\n", " [[1., 0., 0.],\n", " [0., 0., 1.],\n", - " [0., 0., 1.]]])
array([4531500., 4533300., 4535100.])
array([2695500., 2693700., 2691900.])
array(0)
array(['2019-12-15T10:17:33.408715000', '2020-09-05T10:17:43.167942000',\n", - " '2020-12-19T10:17:34.610661000'], dtype='datetime64[ns]')
array(0)
array([[1., 1., 1.],\n", + " [0., 0., 1.]]])
array([4531500., 4533300., 4535100.])
array([2695500., 2693700., 2691900.])
array(0)
array(['2019-12-15T10:17:33.408715000', '2020-09-05T10:17:43.167942000',\n", + " '2020-12-19T10:17:34.610661000'], dtype='datetime64[ns]')
array(0)
array([[1., 1., 1.],\n", " [1., 1., 1.],\n", - " [1., 1., 1.]])
PandasIndex(Index([4531500.0, 4533300.0, 4535100.0], dtype='float64', name='x'))
PandasIndex(Index([2695500.0, 2693700.0, 2691900.0], dtype='float64', name='y'))
PandasIndex(DatetimeIndex(['2019-12-15 10:17:33.408715', '2020-09-05 10:17:43.167942',\n", + " [1., 1., 1.]])
PandasIndex(Index([4531500.0, 4533300.0, 4535100.0], dtype='float64', name='x'))
PandasIndex(Index([2695500.0, 2693700.0, 2691900.0], dtype='float64', name='y'))
PandasIndex(DatetimeIndex(['2019-12-15 10:17:33.408715', '2020-09-05 10:17:43.167942',\n", " '2020-12-19 10:17:34.610661'],\n", - " dtype='datetime64[ns]', name='time', freq=None))
array([[2., 0., 1.],\n", + " value_type: discrete
array([[2., 0., 1.],\n", " [1., 0., 2.],\n", - " [1., 1., 2.]])
array([4531500., 4533300., 4535100.])
array([2695500., 2693700., 2691900.])
array(0)
array(0)
array([[1., 1., 1.],\n", + " [1., 1., 2.]])
array([4531500., 4533300., 4535100.])
array([2695500., 2693700., 2691900.])
array(0)
array(0)
array([[1., 1., 1.],\n", " [1., 1., 1.],\n", - " [1., 1., 1.]])
PandasIndex(Index([4531500.0, 4533300.0, 4535100.0], dtype='float64', name='x'))
PandasIndex(Index([2695500.0, 2693700.0, 2691900.0], dtype='float64', name='y'))
PandasIndex(Index([4531500.0, 4533300.0, 4535100.0], dtype='float64', name='x'))
PandasIndex(Index([2695500.0, 2693700.0, 2691900.0], dtype='float64', name='y'))
array([0., 7., 3.])
array(0)
array(['2019-12-15T10:17:33.408715000', '2020-09-05T10:17:43.167942000',\n", - " '2020-12-19T10:17:34.610661000'], dtype='datetime64[ns]')
array(0)
PandasIndex(DatetimeIndex(['2019-12-15 10:17:33.408715', '2020-09-05 10:17:43.167942',\n", + " value_type: discrete
array([0., 7., 3.])
array(0)
array(['2019-12-15T10:17:33.408715000', '2020-09-05T10:17:43.167942000',\n", + " '2020-12-19T10:17:34.610661000'], dtype='datetime64[ns]')
array(0)
PandasIndex(DatetimeIndex(['2019-12-15 10:17:33.408715', '2020-09-05 10:17:43.167942',\n", " '2020-12-19 10:17:34.610661'],\n", - " dtype='datetime64[ns]', name='time', freq=None))
array(10.)
array(0)
array(0)
array(10.)
array(0)
array(0)
array([[[0., 0., 0.],\n", + " value_type: binary
array([[[0., 0., 0.],\n", " [0., 0., 0.],\n", " [0., 0., 0.]],\n", "\n", @@ -20286,12 +20286,12 @@ "\n", " [[0., 0., 0.],\n", " [1., 0., 0.],\n", - " [1., 0., 0.]]])
array([4531500., 4533300., 4535100.])
array([2695500., 2693700., 2691900.])
array(0)
array(['2019-12-15T10:17:33.408715000', '2020-09-05T10:17:43.167942000',\n", - " '2020-12-19T10:17:34.610661000'], dtype='datetime64[ns]')
array(0)
array([[1., 1., 1.],\n", + " [1., 0., 0.]]])
array([4531500., 4533300., 4535100.])
array([2695500., 2693700., 2691900.])
array(0)
array(['2019-12-15T10:17:33.408715000', '2020-09-05T10:17:43.167942000',\n", + " '2020-12-19T10:17:34.610661000'], dtype='datetime64[ns]')
array(0)
array([[1., 1., 1.],\n", " [1., 1., 1.],\n", - " [1., 1., 1.]])
PandasIndex(Index([4531500.0, 4533300.0, 4535100.0], dtype='float64', name='x'))
PandasIndex(Index([2695500.0, 2693700.0, 2691900.0], dtype='float64', name='y'))
PandasIndex(DatetimeIndex(['2019-12-15 10:17:33.408715', '2020-09-05 10:17:43.167942',\n", + " [1., 1., 1.]])
PandasIndex(Index([4531500.0, 4533300.0, 4535100.0], dtype='float64', name='x'))
PandasIndex(Index([2695500.0, 2693700.0, 2691900.0], dtype='float64', name='y'))
PandasIndex(DatetimeIndex(['2019-12-15 10:17:33.408715', '2020-09-05 10:17:43.167942',\n", " '2020-12-19 10:17:34.610661'],\n", - " dtype='datetime64[ns]', name='time', freq=None))
array([[[nan, nan, nan],\n", + " value_type: binary
array([[[nan, nan, nan],\n", " [nan, nan, nan],\n", " [nan, nan, nan]],\n", "\n", @@ -20736,12 +20736,12 @@ "\n", " [[ 0., 1., 0.],\n", " [ 0., 1., 0.],\n", - " [ 0., 0., 0.]]])
array([4531500., 4533300., 4535100.])
array([2695500., 2693700., 2691900.])
array(0)
array(['2019-12-15T10:17:33.408715000', '2020-09-05T10:17:43.167942000',\n", - " '2020-12-19T10:17:34.610661000'], dtype='datetime64[ns]')
array(0)
array([[1., 1., 1.],\n", + " [ 0., 0., 0.]]])
array([4531500., 4533300., 4535100.])
array([2695500., 2693700., 2691900.])
array(0)
array(['2019-12-15T10:17:33.408715000', '2020-09-05T10:17:43.167942000',\n", + " '2020-12-19T10:17:34.610661000'], dtype='datetime64[ns]')
array(0)
array([[1., 1., 1.],\n", " [1., 1., 1.],\n", - " [1., 1., 1.]])
PandasIndex(Index([4531500.0, 4533300.0, 4535100.0], dtype='float64', name='x'))
PandasIndex(Index([2695500.0, 2693700.0, 2691900.0], dtype='float64', name='y'))
PandasIndex(DatetimeIndex(['2019-12-15 10:17:33.408715', '2020-09-05 10:17:43.167942',\n", + " [1., 1., 1.]])
PandasIndex(Index([4531500.0, 4533300.0, 4535100.0], dtype='float64', name='x'))
PandasIndex(Index([2695500.0, 2693700.0, 2691900.0], dtype='float64', name='y'))
PandasIndex(DatetimeIndex(['2019-12-15 10:17:33.408715', '2020-09-05 10:17:43.167942',\n", " '2020-12-19 10:17:34.610661'],\n", - " dtype='datetime64[ns]', name='time', freq=None))
array([[[0., 0., 0.],\n", + " value_type: binary
array([[[0., 0., 0.],\n", " [0., 0., 0.],\n", " [0., 0., 0.]],\n", "\n", @@ -21245,12 +21245,12 @@ "\n", " [[1., 0., 0.],\n", " [0., 0., 1.],\n", - " [0., 0., 1.]]])
array([4531500., 4533300., 4535100.])
array([2695500., 2693700., 2691900.])
array(0)
array(['2019-12-15T10:17:33.408715000', '2020-09-05T10:17:43.167942000',\n", - " '2020-12-19T10:17:34.610661000'], dtype='datetime64[ns]')
array(0)
array([[1., 1., 1.],\n", + " [0., 0., 1.]]])
array([4531500., 4533300., 4535100.])
array([2695500., 2693700., 2691900.])
array(0)
array(['2019-12-15T10:17:33.408715000', '2020-09-05T10:17:43.167942000',\n", + " '2020-12-19T10:17:34.610661000'], dtype='datetime64[ns]')
array(0)
array([[1., 1., 1.],\n", " [1., 1., 1.],\n", - " [1., 1., 1.]])
PandasIndex(Index([4531500.0, 4533300.0, 4535100.0], dtype='float64', name='x'))
PandasIndex(Index([2695500.0, 2693700.0, 2691900.0], dtype='float64', name='y'))
PandasIndex(DatetimeIndex(['2019-12-15 10:17:33.408715', '2020-09-05 10:17:43.167942',\n", + " [1., 1., 1.]])
PandasIndex(Index([4531500.0, 4533300.0, 4535100.0], dtype='float64', name='x'))
PandasIndex(Index([2695500.0, 2693700.0, 2691900.0], dtype='float64', name='y'))
PandasIndex(DatetimeIndex(['2019-12-15 10:17:33.408715', '2020-09-05 10:17:43.167942',\n", " '2020-12-19 10:17:34.610661'],\n", - " dtype='datetime64[ns]', name='time', freq=None))
array([[[1., 0., 1.],\n", + " value_type: binary
array([[[1., 0., 1.],\n", " [1., 0., 1.],\n", " [1., 1., 1.]],\n", "\n", @@ -21695,12 +21695,12 @@ "\n", " [[2., 0., 1.],\n", " [1., 0., 2.],\n", - " [1., 1., 2.]]])
array([4531500., 4533300., 4535100.])
array([2695500., 2693700., 2691900.])
array(0)
array(['2019-12-15T10:17:33.408715000', '2020-09-05T10:17:43.167942000',\n", - " '2020-12-19T10:17:34.610661000'], dtype='datetime64[ns]')
array(0)
array([[1., 1., 1.],\n", + " [1., 1., 2.]]])
array([4531500., 4533300., 4535100.])
array([2695500., 2693700., 2691900.])
array(0)
array(['2019-12-15T10:17:33.408715000', '2020-09-05T10:17:43.167942000',\n", + " '2020-12-19T10:17:34.610661000'], dtype='datetime64[ns]')
array(0)
array([[1., 1., 1.],\n", " [1., 1., 1.],\n", - " [1., 1., 1.]])
PandasIndex(Index([4531500.0, 4533300.0, 4535100.0], dtype='float64', name='x'))
PandasIndex(Index([2695500.0, 2693700.0, 2691900.0], dtype='float64', name='y'))
PandasIndex(DatetimeIndex(['2019-12-15 10:17:33.408715', '2020-09-05 10:17:43.167942',\n", + " [1., 1., 1.]])
PandasIndex(Index([4531500.0, 4533300.0, 4535100.0], dtype='float64', name='x'))
PandasIndex(Index([2695500.0, 2693700.0, 2691900.0], dtype='float64', name='y'))
PandasIndex(DatetimeIndex(['2019-12-15 10:17:33.408715', '2020-09-05 10:17:43.167942',\n", " '2020-12-19 10:17:34.610661'],\n", - " dtype='datetime64[ns]', name='time', freq=None))
array([[[nan, nan, nan],\n", + " value_type: binary
array([[[nan, nan, nan],\n", " [nan, 0., nan],\n", " [nan, nan, nan]],\n", "\n", @@ -22145,12 +22145,12 @@ "\n", " [[nan, nan, nan],\n", " [nan, 3., nan],\n", - " [nan, nan, nan]]])
array([4531500., 4533300., 4535100.])
array([2695500., 2693700., 2691900.])
array(0)
array(['2019-12-15T10:17:33.408715000', '2020-09-05T10:17:43.167942000',\n", - " '2020-12-19T10:17:34.610661000'], dtype='datetime64[ns]')
array(0)
array([[1., 1., 1.],\n", + " [nan, nan, nan]]])
array([4531500., 4533300., 4535100.])
array([2695500., 2693700., 2691900.])
array(0)
array(['2019-12-15T10:17:33.408715000', '2020-09-05T10:17:43.167942000',\n", + " '2020-12-19T10:17:34.610661000'], dtype='datetime64[ns]')
array(0)
array([[1., 1., 1.],\n", " [1., 1., 1.],\n", - " [1., 1., 1.]])
PandasIndex(Index([4531500.0, 4533300.0, 4535100.0], dtype='float64', name='x'))
PandasIndex(Index([2695500.0, 2693700.0, 2691900.0], dtype='float64', name='y'))
PandasIndex(DatetimeIndex(['2019-12-15 10:17:33.408715', '2020-09-05 10:17:43.167942',\n", + " [1., 1., 1.]])
PandasIndex(Index([4531500.0, 4533300.0, 4535100.0], dtype='float64', name='x'))
PandasIndex(Index([2695500.0, 2693700.0, 2691900.0], dtype='float64', name='y'))
PandasIndex(DatetimeIndex(['2019-12-15 10:17:33.408715', '2020-09-05 10:17:43.167942',\n", " '2020-12-19 10:17:34.610661'],\n", - " dtype='datetime64[ns]', name='time', freq=None))
array([[[nan, nan, nan],\n", + " value_type: binary
array([[[nan, nan, nan],\n", " [nan, nan, nan],\n", " [nan, nan, nan]],\n", "\n", @@ -22648,12 +22648,12 @@ "\n", " [[nan, nan, nan],\n", " [ 1., nan, nan],\n", - " [ 1., nan, nan]]])
array([4531500., 4533300., 4535100.])
array([2695500., 2693700., 2691900.])
array(0)
array(['2019-12-15T10:17:33.408715000', '2020-09-05T10:17:43.167942000',\n", - " '2020-12-19T10:17:34.610661000'], dtype='datetime64[ns]')
array(0)
array([[1., 1., 1.],\n", + " [ 1., nan, nan]]])
array([4531500., 4533300., 4535100.])
array([2695500., 2693700., 2691900.])
array(0)
array(['2019-12-15T10:17:33.408715000', '2020-09-05T10:17:43.167942000',\n", + " '2020-12-19T10:17:34.610661000'], dtype='datetime64[ns]')
array(0)
array([[1., 1., 1.],\n", " [1., 1., 1.],\n", - " [1., 1., 1.]])
PandasIndex(Index([4531500.0, 4533300.0, 4535100.0], dtype='float64', name='x'))
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PandasIndex(DatetimeIndex(['2019-12-15 10:17:33.408715', '2020-12-19 10:17:34.610661'], dtype='datetime64[ns]', name='time', freq=None))
PandasIndex(Index([4531500.0, 4533300.0, 4535100.0], dtype='float64', name='x'))
PandasIndex(Index([2695500.0, 2693700.0, 2691900.0], dtype='float64', name='y'))
PandasIndex(DatetimeIndex(['2019-12-15 10:17:33.408715', '2020-12-19 10:17:34.610661'], dtype='datetime64[ns]', name='time', freq=None))
array([[0., 0., 0.],\n", + " value_type: binary
array([[0., 0., 0.],\n", " [0., 0., 0.],\n", - " [0., 0., 0.]])
array([4531500., 4533300., 4535100.])
array([2695500., 2693700., 2691900.])
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array('2019-12-15T10:17:33.408715000', dtype='datetime64[ns]')
array(0)
array([[1., 1., 1.],\n", + " [0., 0., 0.]])
array([4531500., 4533300., 4535100.])
array([2695500., 2693700., 2691900.])
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array('2019-12-15T10:17:33.408715000', dtype='datetime64[ns]')
array(0)
array([[1., 1., 1.],\n", " [1., 1., 1.],\n", - " [1., 1., 1.]])
PandasIndex(Index([4531500.0, 4533300.0, 4535100.0], dtype='float64', name='x'))
PandasIndex(Index([2695500.0, 2693700.0, 2691900.0], dtype='float64', name='y'))
PandasIndex(Index([4531500.0, 4533300.0, 4535100.0], dtype='float64', name='x'))
PandasIndex(Index([2695500.0, 2693700.0, 2691900.0], dtype='float64', name='y'))
array([[0., 1., 0.],\n", + " value_type: binary
array([[0., 1., 0.],\n", " [0., 1., 0.],\n", - " [0., 0., 0.]])
array([4531500., 4533300., 4535100.])
array([2695500., 2693700., 2691900.])
array(0)
array('2020-09-05T10:17:43.167942000', dtype='datetime64[ns]')
array(0)
array([[1., 1., 1.],\n", + " [0., 0., 0.]])
array([4531500., 4533300., 4535100.])
array([2695500., 2693700., 2691900.])
array(0)
array('2020-09-05T10:17:43.167942000', dtype='datetime64[ns]')
array(0)
array([[1., 1., 1.],\n", " [1., 1., 1.],\n", - " [1., 1., 1.]])
PandasIndex(Index([4531500.0, 4533300.0, 4535100.0], dtype='float64', name='x'))
PandasIndex(Index([2695500.0, 2693700.0, 2691900.0], dtype='float64', name='y'))
PandasIndex(Index([4531500.0, 4533300.0, 4535100.0], dtype='float64', name='x'))
PandasIndex(Index([2695500.0, 2693700.0, 2691900.0], dtype='float64', name='y'))
array([[0., 0., 0.],\n", + " value_type: binary
array([[0., 0., 0.],\n", " [1., 0., 0.],\n", - " [1., 0., 0.]])
array([4531500., 4533300., 4535100.])
array([2695500., 2693700., 2691900.])
array(0)
array('2020-12-19T10:17:34.610661000', dtype='datetime64[ns]')
array(0)
array([[1., 1., 1.],\n", + " [1., 0., 0.]])
array([4531500., 4533300., 4535100.])
array([2695500., 2693700., 2691900.])
array(0)
array('2020-12-19T10:17:34.610661000', dtype='datetime64[ns]')
array(0)
array([[1., 1., 1.],\n", " [1., 1., 1.],\n", - " [1., 1., 1.]])
PandasIndex(Index([4531500.0, 4533300.0, 4535100.0], dtype='float64', name='x'))
PandasIndex(Index([2695500.0, 2693700.0, 2691900.0], dtype='float64', name='y'))
PandasIndex(Index([4531500.0, 4533300.0, 4535100.0], dtype='float64', name='x'))
PandasIndex(Index([2695500.0, 2693700.0, 2691900.0], dtype='float64', name='y'))
array([[[[0., 0., 0.],\n", + " value_type: binary
array([[[[0., 0., 0.],\n", " [0., 0., 0.],\n", " [0., 0., 0.]],\n", "\n", @@ -31016,12 +31016,12 @@ "\n", " [[1., 0., 0.],\n", " [0., 0., 1.],\n", - " [0., 0., 1.]]]])
array([4531500., 4533300., 4535100.])
array([2695500., 2693700., 2691900.])
array(0)
array(['2019-12-15T10:17:33.408715000', '2020-09-05T10:17:43.167942000',\n", - " '2020-12-19T10:17:34.610661000'], dtype='datetime64[ns]')
array(0)
array([[1., 1., 1.],\n", + " [0., 0., 1.]]]])
array([4531500., 4533300., 4535100.])
array([2695500., 2693700., 2691900.])
array(0)
array(['2019-12-15T10:17:33.408715000', '2020-09-05T10:17:43.167942000',\n", + " '2020-12-19T10:17:34.610661000'], dtype='datetime64[ns]')
array(0)
array([[1., 1., 1.],\n", " [1., 1., 1.],\n", - " [1., 1., 1.]])
array(['water', 'snow', 'vegetation'], dtype=object)
PandasIndex(Index([4531500.0, 4533300.0, 4535100.0], dtype='float64', name='x'))
PandasIndex(Index([2695500.0, 2693700.0, 2691900.0], dtype='float64', name='y'))
PandasIndex(DatetimeIndex(['2019-12-15 10:17:33.408715', '2020-09-05 10:17:43.167942',\n", + " [1., 1., 1.]])
array(['water', 'snow', 'vegetation'], dtype=object)
PandasIndex(Index([4531500.0, 4533300.0, 4535100.0], dtype='float64', name='x'))
PandasIndex(Index([2695500.0, 2693700.0, 2691900.0], dtype='float64', name='y'))
PandasIndex(DatetimeIndex(['2019-12-15 10:17:33.408715', '2020-09-05 10:17:43.167942',\n", " '2020-12-19 10:17:34.610661'],\n", - " dtype='datetime64[ns]', name='time', freq=None))
PandasIndex(Index(['water', 'snow', 'vegetation'], dtype='object', name='concept'))
PandasIndex(Index(['water', 'snow', 'vegetation'], dtype='object', name='concept'))
array([[[0., 0., 0.],\n", + " value_type: binary
array([[[0., 0., 0.],\n", " [0., 0., 0.],\n", " [0., 0., 0.]],\n", "\n", @@ -31537,12 +31537,12 @@ "\n", " [[0., 0., 0.],\n", " [1., 0., 0.],\n", - " [1., 0., 0.]]])
array([4531500., 4533300., 4535100.])
array([2695500., 2693700., 2691900.])
array(0)
array(['2019-12-15T10:17:33.408715000', '2020-09-05T10:17:43.167942000',\n", - " '2020-12-19T10:17:34.610661000'], dtype='datetime64[ns]')
array(0)
array([[1., 1., 1.],\n", + " [1., 0., 0.]]])
array([4531500., 4533300., 4535100.])
array([2695500., 2693700., 2691900.])
array(0)
array(['2019-12-15T10:17:33.408715000', '2020-09-05T10:17:43.167942000',\n", + " '2020-12-19T10:17:34.610661000'], dtype='datetime64[ns]')
array(0)
array([[1., 1., 1.],\n", " [1., 1., 1.],\n", - " [1., 1., 1.]])
PandasIndex(Index([4531500.0, 4533300.0, 4535100.0], dtype='float64', name='x'))
PandasIndex(Index([2695500.0, 2693700.0, 2691900.0], dtype='float64', name='y'))
PandasIndex(DatetimeIndex(['2019-12-15 10:17:33.408715', '2020-09-05 10:17:43.167942',\n", + " [1., 1., 1.]])
PandasIndex(Index([4531500.0, 4533300.0, 4535100.0], dtype='float64', name='x'))
PandasIndex(Index([2695500.0, 2693700.0, 2691900.0], dtype='float64', name='y'))
PandasIndex(DatetimeIndex(['2019-12-15 10:17:33.408715', '2020-09-05 10:17:43.167942',\n", " '2020-12-19 10:17:34.610661'],\n", - " dtype='datetime64[ns]', name='time', freq=None))
array([[[ 2., nan, 2.],\n", + " value_labels: {1: 'water', 2: 'snow', 3: 'vegetation'}
array([[[ 2., nan, 2.],\n", " [ 2., nan, 2.],\n", " [ 2., 2., 2.]],\n", "\n", @@ -32037,12 +32037,12 @@ "\n", " [[ 3., nan, nan],\n", " [ 1., nan, 3.],\n", - " [ 1., nan, 3.]]])
array([4531500., 4533300., 4535100.])
array([2695500., 2693700., 2691900.])
array(0)
array(['2019-12-15T10:17:33.408715000', '2020-09-05T10:17:43.167942000',\n", - " '2020-12-19T10:17:34.610661000'], dtype='datetime64[ns]')
array(0)
array([[1., 1., 1.],\n", + " [ 1., nan, 3.]]])
array([4531500., 4533300., 4535100.])
array([2695500., 2693700., 2691900.])
array(0)
array(['2019-12-15T10:17:33.408715000', '2020-09-05T10:17:43.167942000',\n", + " '2020-12-19T10:17:34.610661000'], dtype='datetime64[ns]')
array(0)
array([[1., 1., 1.],\n", " [1., 1., 1.],\n", - " [1., 1., 1.]])
PandasIndex(Index([4531500.0, 4533300.0, 4535100.0], dtype='float64', name='x'))
PandasIndex(Index([2695500.0, 2693700.0, 2691900.0], dtype='float64', name='y'))
PandasIndex(DatetimeIndex(['2019-12-15 10:17:33.408715', '2020-09-05 10:17:43.167942',\n", + " [1., 1., 1.]])
PandasIndex(Index([4531500.0, 4533300.0, 4535100.0], dtype='float64', name='x'))
PandasIndex(Index([2695500.0, 2693700.0, 2691900.0], dtype='float64', name='y'))
PandasIndex(DatetimeIndex(['2019-12-15 10:17:33.408715', '2020-09-05 10:17:43.167942',\n", " '2020-12-19 10:17:34.610661'],\n", - " dtype='datetime64[ns]', name='time', freq=None))
array([[[1., 0., 1.],\n", + " value_type: binary
array([[[1., 0., 1.],\n", " [1., 0., 1.],\n", " [1., 1., 1.]],\n", "\n", @@ -32525,12 +32525,12 @@ "\n", " [[1., 0., 0.],\n", " [1., 0., 1.],\n", - " [1., 0., 1.]]])
array([4531500., 4533300., 4535100.])
array([2695500., 2693700., 2691900.])
array(0)
array(['2019-12-15T10:17:33.408715000', '2020-09-05T10:17:43.167942000',\n", - " '2020-12-19T10:17:34.610661000'], dtype='datetime64[ns]')
array(0)
array([[1., 1., 1.],\n", + " [1., 0., 1.]]])
array([4531500., 4533300., 4535100.])
array([2695500., 2693700., 2691900.])
array(0)
array(['2019-12-15T10:17:33.408715000', '2020-09-05T10:17:43.167942000',\n", + " '2020-12-19T10:17:34.610661000'], dtype='datetime64[ns]')
array(0)
array([[1., 1., 1.],\n", " [1., 1., 1.],\n", - " [1., 1., 1.]])
PandasIndex(Index([4531500.0, 4533300.0, 4535100.0], dtype='float64', name='x'))
PandasIndex(Index([2695500.0, 2693700.0, 2691900.0], dtype='float64', name='y'))
PandasIndex(DatetimeIndex(['2019-12-15 10:17:33.408715', '2020-09-05 10:17:43.167942',\n", + " [1., 1., 1.]])
PandasIndex(Index([4531500.0, 4533300.0, 4535100.0], dtype='float64', name='x'))
PandasIndex(Index([2695500.0, 2693700.0, 2691900.0], dtype='float64', name='y'))
PandasIndex(DatetimeIndex(['2019-12-15 10:17:33.408715', '2020-09-05 10:17:43.167942',\n", " '2020-12-19 10:17:34.610661'],\n", - " dtype='datetime64[ns]', name='time', freq=None))
array([0., 2.])
array(0)
array(0)
array([2019, 2020])
PandasIndex(Index([2019, 2020], dtype='int64', name='year'))
array([0., 2.])
array(0)
array(0)
array([2019, 2020])
PandasIndex(Index([2019, 2020], dtype='int64', name='year'))
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array(0)
array(['2019-12-15T10:17:33.408715000', '2020-09-05T10:17:43.167942000',\n", - " '2020-12-19T10:17:34.610661000'], dtype='datetime64[ns]')
array(0)
array(['Northern', 'Southern'], dtype=object)
PandasIndex(DatetimeIndex(['2019-12-15 10:17:33.408715', '2020-09-05 10:17:43.167942',\n", + " value_type: discrete
array([[ 0., 61., 18.],\n", + " [ 0., 102., 67.]])
array(0)
array(['2019-12-15T10:17:33.408715000', '2020-09-05T10:17:43.167942000',\n", + " '2020-12-19T10:17:34.610661000'], dtype='datetime64[ns]')
array(0)
array(['Northern', 'Southern'], dtype=object)
PandasIndex(DatetimeIndex(['2019-12-15 10:17:33.408715', '2020-09-05 10:17:43.167942',\n", " '2020-12-19 10:17:34.610661'],\n", - " dtype='datetime64[ns]', name='time', freq=None))
PandasIndex(Index(['Northern', 'Southern'], dtype='object', name='feat'))
PandasIndex(Index(['Northern', 'Southern'], dtype='object', name='feat'))
array([[[[0., 0., 0.],\n", + " value_type: binary
array([[[[0., 0., 0.],\n", " [0., 0., 0.],\n", " [0., 0., 0.]],\n", "\n", @@ -34184,12 +34184,12 @@ "\n", " [[1., 0., 0.],\n", " [0., 0., 1.],\n", - " [0., 0., 1.]]]])
array([4531500., 4533300., 4535100.])
array([2695500., 2693700., 2691900.])
array(0)
array(['2019-12-15T10:17:33.408715000', '2020-09-05T10:17:43.167942000',\n", - " '2020-12-19T10:17:34.610661000'], dtype='datetime64[ns]')
array(0)
array([[1., 1., 1.],\n", + " [0., 0., 1.]]]])
array([4531500., 4533300., 4535100.])
array([2695500., 2693700., 2691900.])
array(0)
array(['2019-12-15T10:17:33.408715000', '2020-09-05T10:17:43.167942000',\n", + " '2020-12-19T10:17:34.610661000'], dtype='datetime64[ns]')
array(0)
array([[1., 1., 1.],\n", " [1., 1., 1.],\n", - " [1., 1., 1.]])
array(['W', 'S', 'V'], dtype=object)
PandasIndex(Index([4531500.0, 4533300.0, 4535100.0], dtype='float64', name='x'))
PandasIndex(Index([2695500.0, 2693700.0, 2691900.0], dtype='float64', name='y'))
PandasIndex(DatetimeIndex(['2019-12-15 10:17:33.408715', '2020-09-05 10:17:43.167942',\n", + " [1., 1., 1.]])
array(['W', 'S', 'V'], dtype=object)
PandasIndex(Index([4531500.0, 4533300.0, 4535100.0], dtype='float64', name='x'))
PandasIndex(Index([2695500.0, 2693700.0, 2691900.0], dtype='float64', name='y'))
PandasIndex(DatetimeIndex(['2019-12-15 10:17:33.408715', '2020-09-05 10:17:43.167942',\n", " '2020-12-19 10:17:34.610661'],\n", - " dtype='datetime64[ns]', name='time', freq=None))
PandasIndex(Index(['W', 'S', 'V'], dtype='object', name='concept'))
PandasIndex(Index(['W', 'S', 'V'], dtype='object', name='concept'))