Affine Transformation

In [1]:

import xarray as xr
import numpy as np
from xcube_resampling.affine import affine_transform_dataset
from xcube_resampling.gridmapping import GridMapping

import xarray as xr import numpy as np from xcube_resampling.affine import affine_transform_dataset from xcube_resampling.gridmapping import GridMapping

In [2]:

def imshow(var):
    var.plot.imshow(vmin=0, vmax=4)

def imshow(var): var.plot.imshow(vmin=0, vmax=4)

In [3]:

res = 0.1
source_ds = xr.Dataset(
    data_vars=dict(
        refl=xr.DataArray(
            np.array(
                [
                    [0, 1, 0, 2, 0, 3, 0, 4],
                    [2, 0, 3, 0, 4, 0, 1, 0],
                    [0, 4, 0, 1, 0, 2, 0, 3],
                    [1, 0, 2, 0, 3, 0, 4, 0],
                    [0, 3, 0, 4, 0, 1, 0, 2],
                    [4, 0, 1, 0, 2, 0, 3, 0],
                ],
                dtype=np.float64,
            ),
            dims=("lat", "lon"),
        )
    ),
    coords=dict(
        lon=xr.DataArray(50.0 + res * np.arange(0, 8) + 0.5 * res, dims="lon"),
        lat=xr.DataArray(10.6 - res * np.arange(0, 6) - 0.5 * res, dims="lat"),
    ),
)
source_ds

res = 0.1 source_ds = xr.Dataset( data_vars=dict( refl=xr.DataArray( np.array( [ [0, 1, 0, 2, 0, 3, 0, 4], [2, 0, 3, 0, 4, 0, 1, 0], [0, 4, 0, 1, 0, 2, 0, 3], [1, 0, 2, 0, 3, 0, 4, 0], [0, 3, 0, 4, 0, 1, 0, 2], [4, 0, 1, 0, 2, 0, 3, 0], ], dtype=np.float64, ), dims=("lat", "lon"), ) ), coords=dict( lon=xr.DataArray(50.0 + res * np.arange(0, 8) + 0.5 * res, dims="lon"), lat=xr.DataArray(10.6 - res * np.arange(0, 6) - 0.5 * res, dims="lat"), ), ) source_ds

Out[3]:

<xarray.Dataset> Size: 496B
Dimensions:  (lon: 8, lat: 6)
Coordinates:
  * lon      (lon) float64 64B 50.05 50.15 50.25 50.35 50.45 50.55 50.65 50.75
  * lat      (lat) float64 48B 10.55 10.45 10.35 10.25 10.15 10.05
Data variables:
    refl     (lat, lon) float64 384B 0.0 1.0 0.0 2.0 0.0 ... 0.0 2.0 0.0 3.0 0.0

xarray.Dataset

• Dimensions:
  • lon: 8
  • lat: 6
• Coordinates: (2)
  • lon
    (lon)
    float64
    50.05 50.15 50.25 ... 50.65 50.75

    array([50.05, 50.15, 50.25, 50.35, 50.45, 50.55, 50.65, 50.75])

  • lat
    (lat)
    float64
    10.55 10.45 10.35 10.25 10.15 10.05

    array([10.55, 10.45, 10.35, 10.25, 10.15, 10.05])

• Data variables: (1)
  • refl
    (lat, lon)
    float64
    0.0 1.0 0.0 2.0 ... 2.0 0.0 3.0 0.0

    array([[0., 1., 0., 2., 0., 3., 0., 4.],
           [2., 0., 3., 0., 4., 0., 1., 0.],
           [0., 4., 0., 1., 0., 2., 0., 3.],
           [1., 0., 2., 0., 3., 0., 4., 0.],
           [0., 3., 0., 4., 0., 1., 0., 2.],
           [4., 0., 1., 0., 2., 0., 3., 0.]])

• Indexes: (2)
  • lon
    PandasIndex

    PandasIndex(Index([             50.05,              50.15,              50.25,
           50.349999999999994, 50.449999999999996,              50.55,
                        50.65,              50.75],
          dtype='float64', name='lon'))

  • lat
    PandasIndex

    PandasIndex(Index([10.549999999999999,              10.45,              10.35,
           10.249999999999998, 10.149999999999999, 10.049999999999999],
          dtype='float64', name='lat'))

• Attributes: (0)

In [4]:

imshow(source_ds.refl)

imshow(source_ds.refl)

In [5]:

source_gm = GridMapping.from_dataset(source_ds)
source_gm.xy_bbox, source_gm.xy_res

source_gm = GridMapping.from_dataset(source_ds) source_gm.xy_bbox, source_gm.xy_res

Out[5]:

((50, 10, 50.8, 10.6), (0.1, 0.1))

In [6]:

target_gm = GridMapping.regular((3, 3), (50, 10), 0.1, source_gm.crs)
# target_gm.ij_to_xy_transform, target_gm.xy_to_ij_transform
target_ds = affine_transform_dataset(source_ds, target_gm, interp_methods=1)
imshow(target_ds.refl)

target_gm = GridMapping.regular((3, 3), (50, 10), 0.1, source_gm.crs) # target_gm.ij_to_xy_transform, target_gm.xy_to_ij_transform target_ds = affine_transform_dataset(source_ds, target_gm, interp_methods=1) imshow(target_ds.refl)

In [7]:

target_gm = GridMapping.regular((3, 3), (50.05, 10.05), 0.1, source_gm.crs)
# target_gm.ij_to_xy_transform, target_gm.xy_to_ij_transform
target_ds = affine_transform_dataset(source_ds, target_gm, interp_methods="bilinear")
imshow(target_ds.refl)

target_gm = GridMapping.regular((3, 3), (50.05, 10.05), 0.1, source_gm.crs) # target_gm.ij_to_xy_transform, target_gm.xy_to_ij_transform target_ds = affine_transform_dataset(source_ds, target_gm, interp_methods="bilinear") imshow(target_ds.refl)

In [8]:

target_gm = GridMapping.regular((8, 6), (50.05, 10.05), 0.1, source_gm.crs)
# target_gm.ij_to_xy_transform, target_gm.xy_to_ij_transform
target_ds = affine_transform_dataset(source_ds, target_gm, interp_methods=dict(refl= 1))
imshow(target_ds.refl)

target_gm = GridMapping.regular((8, 6), (50.05, 10.05), 0.1, source_gm.crs) # target_gm.ij_to_xy_transform, target_gm.xy_to_ij_transform target_ds = affine_transform_dataset(source_ds, target_gm, interp_methods=dict(refl= 1)) imshow(target_ds.refl)

In [9]:

target_gm = GridMapping.regular((8, 6), (50.2, 10.1), 0.1, source_gm.crs)
# target_gm.ij_to_xy_transform, target_gm.xy_to_ij_transform
target_ds = affine_transform_dataset(source_ds, target_gm, interp_methods=dict(refl="bilinear"))
imshow(target_ds.refl)

target_gm = GridMapping.regular((8, 6), (50.2, 10.1), 0.1, source_gm.crs) # target_gm.ij_to_xy_transform, target_gm.xy_to_ij_transform target_ds = affine_transform_dataset(source_ds, target_gm, interp_methods=dict(refl="bilinear")) imshow(target_ds.refl)

In [10]:

target_gm = GridMapping.regular((8, 6), (49.8, 9.9), 0.1, source_gm.crs)
# target_gm.ij_to_xy_transform, target_gm.xy_to_ij_transform
target_ds = affine_transform_dataset(source_ds, target_gm, interp_methods=1)
imshow(target_ds.refl)

target_gm = GridMapping.regular((8, 6), (49.8, 9.9), 0.1, source_gm.crs) # target_gm.ij_to_xy_transform, target_gm.xy_to_ij_transform target_ds = affine_transform_dataset(source_ds, target_gm, interp_methods=1) imshow(target_ds.refl)

In [11]:

target_gm = GridMapping.regular((8, 6), (50, 10), 0.2, source_gm.crs)
# target_gm.ij_to_xy_transform, target_gm.xy_to_ij_transform
target_ds = affine_transform_dataset(source_ds, target_gm, interp_methods=1)
imshow(target_ds.refl)

target_gm = GridMapping.regular((8, 6), (50, 10), 0.2, source_gm.crs) # target_gm.ij_to_xy_transform, target_gm.xy_to_ij_transform target_ds = affine_transform_dataset(source_ds, target_gm, interp_methods=1) imshow(target_ds.refl)

In [12]:

target_gm = GridMapping.regular((8, 6), (49.8, 9.8), 0.2, source_gm.crs)
# target_gm.ij_to_xy_transform, target_gm.xy_to_ij_transform
target_ds = affine_transform_dataset(source_ds, target_gm, interp_methods=1)
imshow(target_ds.refl)

target_gm = GridMapping.regular((8, 6), (49.8, 9.8), 0.2, source_gm.crs) # target_gm.ij_to_xy_transform, target_gm.xy_to_ij_transform target_ds = affine_transform_dataset(source_ds, target_gm, interp_methods=1) imshow(target_ds.refl)

In [13]:

target_gm = GridMapping.regular((16, 12), (50, 10), 0.05, source_gm.crs)
# target_gm.ij_to_xy_transform, target_gm.xy_to_ij_transform
target_ds = affine_transform_dataset(source_ds, target_gm, interp_methods=1)
imshow(target_ds.refl)

target_gm = GridMapping.regular((16, 12), (50, 10), 0.05, source_gm.crs) # target_gm.ij_to_xy_transform, target_gm.xy_to_ij_transform target_ds = affine_transform_dataset(source_ds, target_gm, interp_methods=1) imshow(target_ds.refl)