Notebook

Pint HTML Repr Demo¶

Attempt to move away from a $\LaTeX$ -based HTML repr (which has non-negligible render times for small arrays and causes Jupyter to hang on large arrays) to an HTML table-based repr inspired by Sparse, Dask, and xarray.

This shows a brief demo of what it looks like for small and large arrays

In [1]:

import dask.array as da
import numpy as np
import sparse
import xarray as xr
from pint import UnitRegistry

Large Arrays¶

In [2]:

ureg = UnitRegistry()

a = np.random.random((100, 100, 100))
a[a < 0.8] = 0

s = sparse.COO(a)  # convert to sparse array
d = da.from_array(a, chunks=(100, 1, 1))
q = a * ureg("m/s^2")
dims = ('x', 'y', 'z')
coords = {dim: np.arange(100) for dim in dims}
x = xr.DataArray(a, dims=dims, coords=coords)

In [3]:

Out[3]:

Format	coo
Data Type	float64
Shape	(100, 100, 100)
nnz	200138
Density	0.200138
Read-only	True
Size	6.1M
Storage ratio	0.8

In [4]:

Out[4]:

	Array	Chunk
Bytes	8.00 MB	800 B
Shape	(100, 100, 100)	(100, 1, 1)
Count	10001 Tasks	10000 Chunks
Type	float64	numpy.ndarray

In [5]:

Out[5]:

Magnitude

[[[0.0 0.0 0.0 ... 0.0 0.8164393236725807 0.0]
  [0.0 0.0 0.0 ... 0.0 0.0 0.9349092365967944]
  [0.0 0.0 0.0 ... 0.9511450113477807 0.0 0.8460087056782979]
  ...
  [0.0 0.0 0.0 ... 0.0 0.0 0.0]
  [0.0 0.9218783842853427 0.0 ... 0.0 0.0 0.0]
  [0.0 0.0 0.0 ... 0.0 0.0 0.0]]

 [[0.8759674991873286 0.0 0.0 ... 0.0 0.0 0.0]
  [0.0 0.0 0.0 ... 0.0 0.0 0.903222550259058]
  [0.0 0.0 0.0 ... 0.0 0.0 0.0]
  ...
  [0.86093744360292 0.0 0.8745785300753577 ... 0.0 0.0 0.0]
  [0.0 0.0 0.0 ... 0.0 0.0 0.0]
  [0.0 0.0 0.0 ... 0.0 0.8717363634658939 0.0]]

 [[0.0 0.0 0.0 ... 0.0 0.0 0.0]
  [0.0 0.8540478752188138 0.0 ... 0.0 0.0 0.9582037308015893]
  [0.0 0.0 0.0 ... 0.0 0.0 0.0]
  ...
  [0.8825405459149325 0.0 0.0 ... 0.0 0.8096152630483208
   0.9844489696358703]
  [0.0 0.0 0.0 ... 0.9015926268637143 0.98774633146913 0.0]
  [0.9979411434467779 0.0 0.0 ... 0.8008498502453875 0.0 0.0]]

 ...

 [[0.0 0.0 0.9352828374657314 ... 0.9522848832961982 0.0
   0.942606844036613]
  [0.0 0.0 0.0 ... 0.0 0.0 0.0]
  [0.8050375515668748 0.8977510781059791 0.0 ... 0.0 0.0 0.0]
  ...
  [0.0 0.9145412503372291 0.0 ... 0.0 0.0 0.9500028141342387]
  [0.0 0.0 0.0 ... 0.0 0.8719263851006498 0.9264469075452001]
  [0.0 0.0 0.0 ... 0.0 0.0 0.0]]

 [[0.8363907815344204 0.8782513631143479 0.0 ... 0.0 0.0 0.0]
  [0.0 0.0 0.0 ... 0.0 0.0 0.8270660068963335]
  [0.0 0.0 0.0 ... 0.0 0.8705023321344338 0.0]
  ...
  [0.0 0.0 0.0 ... 0.0 0.0 0.0]
  [0.0 0.0 0.0 ... 0.0 0.9109703404248978 0.0]
  [0.0 0.0 0.0 ... 0.0 0.0 0.9924330052668219]]

 [[0.0 0.0 0.0 ... 0.0 0.0 0.0]
  [0.0 0.0 0.0 ... 0.0 0.0 0.0]
  [0.0 0.0 0.0 ... 0.9911733788248696 0.0 0.0]
  ...
  [0.9148729639725798 0.0 0.0 ... 0.0 0.0 0.0]
  [0.9731139708096902 0.0 0.0 ... 0.0 0.0 0.9067372289126425]
  [0.0 0.9277293558768427 0.0 ... 0.0 0.0 0.0]]]

Units

meter/second²

In [6]:

Out[6]:

<xarray.DataArray (x: 100, y: 100, z: 100)>
array([[[0.        , 0.        , 0.        , ..., 0.        ,
         0.81643932, 0.        ],
        [0.        , 0.        , 0.        , ..., 0.        ,
         0.        , 0.93490924],
        [0.        , 0.        , 0.        , ..., 0.95114501,
         0.        , 0.84600871],
        ...,
        [0.        , 0.        , 0.        , ..., 0.        ,
         0.        , 0.        ],
        [0.        , 0.92187838, 0.        , ..., 0.        ,
         0.        , 0.        ],
        [0.        , 0.        , 0.        , ..., 0.        ,
         0.        , 0.        ]],

       [[0.8759675 , 0.        , 0.        , ..., 0.        ,
         0.        , 0.        ],
        [0.        , 0.        , 0.        , ..., 0.        ,
         0.        , 0.90322255],
        [0.        , 0.        , 0.        , ..., 0.        ,
         0.        , 0.        ],
...
        [0.        , 0.        , 0.        , ..., 0.        ,
         0.        , 0.        ],
        [0.        , 0.        , 0.        , ..., 0.        ,
         0.91097034, 0.        ],
        [0.        , 0.        , 0.        , ..., 0.        ,
         0.        , 0.99243301]],

       [[0.        , 0.        , 0.        , ..., 0.        ,
         0.        , 0.        ],
        [0.        , 0.        , 0.        , ..., 0.        ,
         0.        , 0.        ],
        [0.        , 0.        , 0.        , ..., 0.99117338,
         0.        , 0.        ],
        ...,
        [0.91487296, 0.        , 0.        , ..., 0.        ,
         0.        , 0.        ],
        [0.97311397, 0.        , 0.        , ..., 0.        ,
         0.        , 0.90673723],
        [0.        , 0.92772936, 0.        , ..., 0.        ,
         0.        , 0.        ]]])
Coordinates:
  * x        (x) int64 0 1 2 3 4 5 6 7 8 9 10 ... 90 91 92 93 94 95 96 97 98 99
  * y        (y) int64 0 1 2 3 4 5 6 7 8 9 10 ... 90 91 92 93 94 95 96 97 98 99
  * z        (z) int64 0 1 2 3 4 5 6 7 8 9 10 ... 90 91 92 93 94 95 96 97 98 99

xarray.DataArray

x: 100
y: 100
z: 100

0.0 0.0 0.0 0.0 0.0 0.8178 0.0 ... 0.9366 0.0 0.8743 0.0 0.0 0.0 0.0

array([[[0.        , 0.        , 0.        , ..., 0.        ,
         0.81643932, 0.        ],
        [0.        , 0.        , 0.        , ..., 0.        ,
         0.        , 0.93490924],
        [0.        , 0.        , 0.        , ..., 0.95114501,
         0.        , 0.84600871],
        ...,
        [0.        , 0.        , 0.        , ..., 0.        ,
         0.        , 0.        ],
        [0.        , 0.92187838, 0.        , ..., 0.        ,
         0.        , 0.        ],
        [0.        , 0.        , 0.        , ..., 0.        ,
         0.        , 0.        ]],

       [[0.8759675 , 0.        , 0.        , ..., 0.        ,
         0.        , 0.        ],
        [0.        , 0.        , 0.        , ..., 0.        ,
         0.        , 0.90322255],
        [0.        , 0.        , 0.        , ..., 0.        ,
         0.        , 0.        ],
...
        [0.        , 0.        , 0.        , ..., 0.        ,
         0.        , 0.        ],
        [0.        , 0.        , 0.        , ..., 0.        ,
         0.91097034, 0.        ],
        [0.        , 0.        , 0.        , ..., 0.        ,
         0.        , 0.99243301]],

       [[0.        , 0.        , 0.        , ..., 0.        ,
         0.        , 0.        ],
        [0.        , 0.        , 0.        , ..., 0.        ,
         0.        , 0.        ],
        [0.        , 0.        , 0.        , ..., 0.99117338,
         0.        , 0.        ],
        ...,
        [0.91487296, 0.        , 0.        , ..., 0.        ,
         0.        , 0.        ],
        [0.97311397, 0.        , 0.        , ..., 0.        ,
         0.        , 0.90673723],
        [0.        , 0.92772936, 0.        , ..., 0.        ,
         0.        , 0.        ]]])

Coordinates: (3)

(x)

int64

0 1 2 3 4 5 6 ... 94 95 96 97 98 99

array([ 0,  1,  2,  3,  4,  5,  6,  7,  8,  9, 10, 11, 12, 13, 14, 15, 16, 17,
       18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35,
       36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53,
       54, 55, 56, 57, 58, 59, 60, 61, 62, 63, 64, 65, 66, 67, 68, 69, 70, 71,
       72, 73, 74, 75, 76, 77, 78, 79, 80, 81, 82, 83, 84, 85, 86, 87, 88, 89,
       90, 91, 92, 93, 94, 95, 96, 97, 98, 99])

(y)

int64

0 1 2 3 4 5 6 ... 94 95 96 97 98 99

array([ 0,  1,  2,  3,  4,  5,  6,  7,  8,  9, 10, 11, 12, 13, 14, 15, 16, 17,
       18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35,
       36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53,
       54, 55, 56, 57, 58, 59, 60, 61, 62, 63, 64, 65, 66, 67, 68, 69, 70, 71,
       72, 73, 74, 75, 76, 77, 78, 79, 80, 81, 82, 83, 84, 85, 86, 87, 88, 89,
       90, 91, 92, 93, 94, 95, 96, 97, 98, 99])

(z)

int64

0 1 2 3 4 5 6 ... 94 95 96 97 98 99

array([ 0,  1,  2,  3,  4,  5,  6,  7,  8,  9, 10, 11, 12, 13, 14, 15, 16, 17,
       18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35,
       36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53,
       54, 55, 56, 57, 58, 59, 60, 61, 62, 63, 64, 65, 66, 67, 68, 69, 70, 71,
       72, 73, 74, 75, 76, 77, 78, 79, 80, 81, 82, 83, 84, 85, 86, 87, 88, 89,
       90, 91, 92, 93, 94, 95, 96, 97, 98, 99])

Attributes: (0)

In [7]:

# Now combinations!
q_d = ureg.Quantity(d, 'm/s^2')
x_q = xr.DataArray(q, dims=dims, coords=coords)
x_q_d_s = xr.DataArray(
    ureg.Quantity(
        da.from_array(s),
        'm/s^2'
    ),
    dims=dims,
    coords=coords
)

In [8]:

q_d

Out[8]:

Magnitude

	Array	Chunk
Bytes	8.00 MB	800 B
Shape	(100, 100, 100)	(100, 1, 1)
Count	10001 Tasks	10000 Chunks
Type	float64	numpy.ndarray

Units

meter/second²

In [9]:

x_q

Out[9]:

<xarray.DataArray (x: 100, y: 100, z: 100)>
<Quantity([[[0.         0.         0.         ... 0.         0.81643932 0.        ]
  [0.         0.         0.         ... 0.         0.         0.93490924]
  [0.         0.         0.         ... 0.95114501 0.         0.84600871]
  ...
  [0.         0.         0.         ... 0.         0.         0.        ]
  [0.         0.92187838 0.         ... 0.         0.         0.        ]
  [0.         0.         0.         ... 0.         0.         0.        ]]

 [[0.8759675  0.         0.         ... 0.         0.         0.        ]
  [0.         0.         0.         ... 0.         0.         0.90322255]
  [0.         0.         0.         ... 0.         0.         0.        ]
  ...
  [0.86093744 0.         0.87457853 ... 0.         0.         0.        ]
  [0.         0.         0.         ... 0.         0.         0.        ]
  [0.         0.         0.         ... 0.         0.87173636 0.        ]]

 [[0.         0.         0.         ... 0.         0.         0.        ]
  [0.         0.85404788 0.         ... 0.         0.         0.95820373]
  [0.         0.         0.         ... 0.         0.         0.        ]
  ...
...
  ...
  [0.         0.91454125 0.         ... 0.         0.         0.95000281]
  [0.         0.         0.         ... 0.         0.87192639 0.92644691]
  [0.         0.         0.         ... 0.         0.         0.        ]]

 [[0.83639078 0.87825136 0.         ... 0.         0.         0.        ]
  [0.         0.         0.         ... 0.         0.         0.82706601]
  [0.         0.         0.         ... 0.         0.87050233 0.        ]
  ...
  [0.         0.         0.         ... 0.         0.         0.        ]
  [0.         0.         0.         ... 0.         0.91097034 0.        ]
  [0.         0.         0.         ... 0.         0.         0.99243301]]

 [[0.         0.         0.         ... 0.         0.         0.        ]
  [0.         0.         0.         ... 0.         0.         0.        ]
  [0.         0.         0.         ... 0.99117338 0.         0.        ]
  ...
  [0.91487296 0.         0.         ... 0.         0.         0.        ]
  [0.97311397 0.         0.         ... 0.         0.         0.90673723]
  [0.         0.92772936 0.         ... 0.         0.         0.        ]]], 'meter / second ** 2')>
Coordinates:
  * x        (x) int64 0 1 2 3 4 5 6 7 8 9 10 ... 90 91 92 93 94 95 96 97 98 99
  * y        (y) int64 0 1 2 3 4 5 6 7 8 9 10 ... 90 91 92 93 94 95 96 97 98 99
  * z        (z) int64 0 1 2 3 4 5 6 7 8 9 10 ... 90 91 92 93 94 95 96 97 98 99

xarray.DataArray

x: 100
y: 100
z: 100

<Quantity([[[0. 0. 0. ... 0. 0.8164...

Magnitude

[[[0.0 0.0 0.0 ... 0.0 0.8164393236725807 0.0]
  [0.0 0.0 0.0 ... 0.0 0.0 0.9349092365967944]
  [0.0 0.0 0.0 ... 0.9511450113477807 0.0 0.8460087056782979]
  ...
  [0.0 0.0 0.0 ... 0.0 0.0 0.0]
  [0.0 0.9218783842853427 0.0 ... 0.0 0.0 0.0]
  [0.0 0.0 0.0 ... 0.0 0.0 0.0]]

 [[0.8759674991873286 0.0 0.0 ... 0.0 0.0 0.0]
  [0.0 0.0 0.0 ... 0.0 0.0 0.903222550259058]
  [0.0 0.0 0.0 ... 0.0 0.0 0.0]
  ...
  [0.86093744360292 0.0 0.8745785300753577 ... 0.0 0.0 0.0]
  [0.0 0.0 0.0 ... 0.0 0.0 0.0]
  [0.0 0.0 0.0 ... 0.0 0.8717363634658939 0.0]]

 [[0.0 0.0 0.0 ... 0.0 0.0 0.0]
  [0.0 0.8540478752188138 0.0 ... 0.0 0.0 0.9582037308015893]
  [0.0 0.0 0.0 ... 0.0 0.0 0.0]
  ...
  [0.8825405459149325 0.0 0.0 ... 0.0 0.8096152630483208
   0.9844489696358703]
  [0.0 0.0 0.0 ... 0.9015926268637143 0.98774633146913 0.0]
  [0.9979411434467779 0.0 0.0 ... 0.8008498502453875 0.0 0.0]]

 ...

 [[0.0 0.0 0.9352828374657314 ... 0.9522848832961982 0.0
   0.942606844036613]
  [0.0 0.0 0.0 ... 0.0 0.0 0.0]
  [0.8050375515668748 0.8977510781059791 0.0 ... 0.0 0.0 0.0]
  ...
  [0.0 0.9145412503372291 0.0 ... 0.0 0.0 0.9500028141342387]
  [0.0 0.0 0.0 ... 0.0 0.8719263851006498 0.9264469075452001]
  [0.0 0.0 0.0 ... 0.0 0.0 0.0]]

 [[0.8363907815344204 0.8782513631143479 0.0 ... 0.0 0.0 0.0]
  [0.0 0.0 0.0 ... 0.0 0.0 0.8270660068963335]
  [0.0 0.0 0.0 ... 0.0 0.8705023321344338 0.0]
  ...
  [0.0 0.0 0.0 ... 0.0 0.0 0.0]
  [0.0 0.0 0.0 ... 0.0 0.9109703404248978 0.0]
  [0.0 0.0 0.0 ... 0.0 0.0 0.9924330052668219]]

 [[0.0 0.0 0.0 ... 0.0 0.0 0.0]
  [0.0 0.0 0.0 ... 0.0 0.0 0.0]
  [0.0 0.0 0.0 ... 0.9911733788248696 0.0 0.0]
  ...
  [0.9148729639725798 0.0 0.0 ... 0.0 0.0 0.0]
  [0.9731139708096902 0.0 0.0 ... 0.0 0.0 0.9067372289126425]
  [0.0 0.9277293558768427 0.0 ... 0.0 0.0 0.0]]]

Units

meter/second²

Coordinates: (3)

(x)

int64

0 1 2 3 4 5 6 ... 94 95 96 97 98 99

array([ 0,  1,  2,  3,  4,  5,  6,  7,  8,  9, 10, 11, 12, 13, 14, 15, 16, 17,
       18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35,
       36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53,
       54, 55, 56, 57, 58, 59, 60, 61, 62, 63, 64, 65, 66, 67, 68, 69, 70, 71,
       72, 73, 74, 75, 76, 77, 78, 79, 80, 81, 82, 83, 84, 85, 86, 87, 88, 89,
       90, 91, 92, 93, 94, 95, 96, 97, 98, 99])

(y)

int64

0 1 2 3 4 5 6 ... 94 95 96 97 98 99

array([ 0,  1,  2,  3,  4,  5,  6,  7,  8,  9, 10, 11, 12, 13, 14, 15, 16, 17,
       18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35,
       36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53,
       54, 55, 56, 57, 58, 59, 60, 61, 62, 63, 64, 65, 66, 67, 68, 69, 70, 71,
       72, 73, 74, 75, 76, 77, 78, 79, 80, 81, 82, 83, 84, 85, 86, 87, 88, 89,
       90, 91, 92, 93, 94, 95, 96, 97, 98, 99])

(z)

int64

0 1 2 3 4 5 6 ... 94 95 96 97 98 99

array([ 0,  1,  2,  3,  4,  5,  6,  7,  8,  9, 10, 11, 12, 13, 14, 15, 16, 17,
       18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35,
       36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53,
       54, 55, 56, 57, 58, 59, 60, 61, 62, 63, 64, 65, 66, 67, 68, 69, 70, 71,
       72, 73, 74, 75, 76, 77, 78, 79, 80, 81, 82, 83, 84, 85, 86, 87, 88, 89,
       90, 91, 92, 93, 94, 95, 96, 97, 98, 99])

Attributes: (0)

In [10]:

x_q_d_s

Out[10]:

<xarray.DataArray 'array-90ad3f4c8f39ebaece4f3bdfc729f1e6' (x: 100, y: 100, z: 100)>
<Quantity(dask.array<array, shape=(100, 100, 100), dtype=float64, chunksize=(100, 100, 100), chunktype=sparse.COO>, 'meter / second ** 2')>
Coordinates:
  * x        (x) int64 0 1 2 3 4 5 6 7 8 9 10 ... 90 91 92 93 94 95 96 97 98 99
  * y        (y) int64 0 1 2 3 4 5 6 7 8 9 10 ... 90 91 92 93 94 95 96 97 98 99
  * z        (z) int64 0 1 2 3 4 5 6 7 8 9 10 ... 90 91 92 93 94 95 96 97 98 99

xarray.DataArray

'array-90ad3f4c8f39ebaece4f3bdfc729f1e6'

x: 100
y: 100
z: 100

<Quantity(dask.array<array, shape=(100, 100, 100), dtype=float64, c...

Magnitude

	Array	Chunk
Shape	(100, 100, 100)	(100, 100, 100)
Count	2 Tasks	1 Chunks
Type	float64	sparse.COO

Units

meter/second²

Coordinates: (3)

(x)

int64

0 1 2 3 4 5 6 ... 94 95 96 97 98 99

array([ 0,  1,  2,  3,  4,  5,  6,  7,  8,  9, 10, 11, 12, 13, 14, 15, 16, 17,
       18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35,
       36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53,
       54, 55, 56, 57, 58, 59, 60, 61, 62, 63, 64, 65, 66, 67, 68, 69, 70, 71,
       72, 73, 74, 75, 76, 77, 78, 79, 80, 81, 82, 83, 84, 85, 86, 87, 88, 89,
       90, 91, 92, 93, 94, 95, 96, 97, 98, 99])

(y)

int64

0 1 2 3 4 5 6 ... 94 95 96 97 98 99

array([ 0,  1,  2,  3,  4,  5,  6,  7,  8,  9, 10, 11, 12, 13, 14, 15, 16, 17,
       18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35,
       36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53,
       54, 55, 56, 57, 58, 59, 60, 61, 62, 63, 64, 65, 66, 67, 68, 69, 70, 71,
       72, 73, 74, 75, 76, 77, 78, 79, 80, 81, 82, 83, 84, 85, 86, 87, 88, 89,
       90, 91, 92, 93, 94, 95, 96, 97, 98, 99])

(z)

int64

0 1 2 3 4 5 6 ... 94 95 96 97 98 99

array([ 0,  1,  2,  3,  4,  5,  6,  7,  8,  9, 10, 11, 12, 13, 14, 15, 16, 17,
       18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35,
       36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53,
       54, 55, 56, 57, 58, 59, 60, 61, 62, 63, 64, 65, 66, 67, 68, 69, 70, 71,
       72, 73, 74, 75, 76, 77, 78, 79, 80, 81, 82, 83, 84, 85, 86, 87, 88, 89,
       90, 91, 92, 93, 94, 95, 96, 97, 98, 99])

Attributes: (0)

Small Arrays¶

In [11]:

a = np.random.random((2, 2))
q = a * ureg.s
x_q = xr.DataArray(q, dims=('x', 'y'))

In [12]:

Out[12]:

Magnitude	[[0.5588875868917845 0.5514644183758584] [0.7819145279451066 0.696348353797128]]
Units	second

In [13]:

x_q

Out[13]:

<xarray.DataArray (x: 2, y: 2)>
<Quantity([[0.55888759 0.55146442]
 [0.78191453 0.69634835]], 'second')>
Dimensions without coordinates: x, y

xarray.DataArray

x: 2
y: 2

<Quantity([[0.55888759 0.55146442] [0.78191453 0.69634835]], 'seco...
Magnitude
[[0.5588875868917845 0.5514644183758584]
[0.7819145279451066 0.696348353797128]]
Units second
Coordinates: (0)
Attributes: (0)

Scalars¶

In [14]:

q[0, 0]

Out[14]:

0.5588875868917845 second

In [15]:

x_q[0, 0]

Out[15]:

<xarray.DataArray ()>
<Quantity(0.5588875868917845, 'second')>

In [ ]: