def write_crs(self,
input_crs=None,
grid_mapping_name=DEFAULT_GRID_MAP,
inplace=False):
"""
Write the CRS to the dataset in a CF compliant manner.
Parameters
----------
input_crs: object
Anything accepted by `rasterio.crs.CRS.from_user_input`.
grid_mapping_name: str, optional
Name of the coordinate to store the CRS information in.
inplace: bool, optional
If True, it will write to the existing dataset. Default is False.
Returns
-------
xarray.Dataset or xarray.DataArray:
Modified dataset with CF compliant CRS information.
"""
if input_crs is not None:
data_obj = self.set_crs(input_crs, inplace=inplace)
else:
data_obj = self._get_obj(inplace=inplace)
# remove old grid maping coordinate if exists
try:
del data_obj.coords[grid_mapping_name]
except KeyError:
pass
if data_obj.rio.crs is None:
raise MissingCRS(
"CRS not found. Please set the CRS with 'set_crs()'.")
# add grid mapping coordinate
data_obj.coords[grid_mapping_name] = xarray.Variable((), 0)
crs_wkt = crs_to_wkt(data_obj.rio.crs)
grid_map_attrs = dict()
grid_map_attrs["spatial_ref"] = crs_wkt
# http://cfconventions.org/Data/cf-conventions/cf-conventions-1.7/cf-conventions.html#appendix-grid-mappings
# http://desktop.arcgis.com/en/arcmap/10.3/manage-data/netcdf/spatial-reference-for-netcdf-data.htm
grid_map_attrs["crs_wkt"] = crs_wkt
data_obj.coords[grid_mapping_name].rio.set_attrs(grid_map_attrs,
inplace=True)
# add grid mapping attribute to variables
if hasattr(data_obj, "data_vars"):
for var in data_obj.data_vars:
if (self.x_dim in data_obj[var].dims
and self.y_dim in data_obj[var].dims):
data_obj[var].rio.update_attrs(
dict(grid_mapping=grid_mapping_name), inplace=True)
data_obj.rio.update_attrs(dict(grid_mapping=grid_mapping_name),
inplace=True)
return data_obj
def write_crs(self, input_crs=None, grid_mapping_name=None, inplace=False):
"""
Write the CRS to the dataset in a CF compliant manner.
Parameters
----------
input_crs: object
Anything accepted by `rasterio.crs.CRS.from_user_input`.
grid_mapping_name: str, optional
Name of the grid_mapping coordinate to store the CRS information in.
Default is the grid_mapping name of the dataset.
inplace: bool, optional
If True, it will write to the existing dataset. Default is False.
Returns
-------
:obj:`xarray.Dataset` | :obj:`xarray.DataArray`:
Modified dataset with CF compliant CRS information.
"""
if input_crs is not None:
data_obj = self.set_crs(input_crs, inplace=inplace)
else:
data_obj = self._get_obj(inplace=inplace)
# get original transform
transform = self._cached_transform()
# remove old grid maping coordinate if exists
grid_mapping_name = (self.grid_mapping if grid_mapping_name is None
else grid_mapping_name)
try:
del data_obj.coords[grid_mapping_name]
except KeyError:
pass
if data_obj.rio.crs is None:
raise MissingCRS(
"CRS not found. Please set the CRS with 'rio.write_crs()'.")
# add grid mapping coordinate
data_obj.coords[grid_mapping_name] = xarray.Variable((), 0)
grid_map_attrs = pyproj.CRS.from_user_input(data_obj.rio.crs).to_cf()
# spatial_ref is for compatibility with GDAL
crs_wkt = crs_to_wkt(data_obj.rio.crs)
grid_map_attrs["spatial_ref"] = crs_wkt
grid_map_attrs["crs_wkt"] = crs_wkt
if transform is not None:
grid_map_attrs["GeoTransform"] = " ".join(
[str(item) for item in transform.to_gdal()])
data_obj.coords[grid_mapping_name].rio.set_attrs(grid_map_attrs,
inplace=True)
return data_obj.rio.write_grid_mapping(
grid_mapping_name=grid_mapping_name, inplace=True)
def clip(
self,
geometries,
crs=None,
all_touched=False,
drop=True,
invert=False,
from_disk=False,
):
"""
Crops a :obj:`xarray.DataArray` by geojson like geometry dicts.
Powered by `rasterio.features.geometry_mask`.
Examples:
>>> geometry = ''' {"type": "Polygon",
... "coordinates": [
... [[-94.07955380199459, 41.69085871273774],
... [-94.06082436942204, 41.69103313774798],
... [-94.06063203899649, 41.67932439500822],
... [-94.07935807746362, 41.679150041277325],
... [-94.07955380199459, 41.69085871273774]]]}'''
>>> cropping_geometries = [geojson.loads(geometry)]
>>> xds = xarray.open_rasterio('cool_raster.tif')
>>> cropped = xds.rio.clip(geometries=cropping_geometries, crs=4326)
.. versionadded:: 0.2 from_disk
Parameters
----------
geometries: list
A list of geojson geometry dicts or objects with __geom_interface__ with
if you have rasterio 1.2+.
crs: :obj:`rasterio.crs.CRS`, optional
The CRS of the input geometries. Default is to assume it is the same
as the dataset.
all_touched : bool, optional
If True, all pixels touched by geometries will be burned in. If
false, only pixels whose center is within the polygon or that
are selected by Bresenham's line algorithm will be burned in.
drop: bool, optional
If True, drop the data outside of the extent of the mask geoemtries
Otherwise, it will return the same raster with the data masked.
Default is True.
invert: boolean, optional
If False, pixels that do not overlap shapes will be set as nodata.
Otherwise, pixels that overlap the shapes will be set as nodata.
False by default.
from_disk: boolean, optional
If True, it will clip from disk using rasterio.mask.mask if possible.
This is beneficial when the size of the data is larger than memory.
Default is False.
Returns
-------
:obj:`xarray.DataArray`:
The clipped object.
"""
if self.crs is None:
raise MissingCRS(
"CRS not found. Please set the CRS with 'rio.write_crs()'."
f"{_get_data_var_message(self._obj)}")
crs = crs_from_user_input(crs) if crs is not None else self.crs
if self.crs != crs:
if LooseVersion(rasterio.__version__) >= LooseVersion("1.2"):
geometries = rasterio.warp.transform_geom(
crs, self.crs, geometries)
else:
geometries = [
rasterio.warp.transform_geom(crs, self.crs, geometry)
for geometry in geometries
]
cropped_ds = None
if from_disk:
cropped_ds = _clip_from_disk(
self._obj,
geometries=geometries,
all_touched=all_touched,
drop=drop,
invert=invert,
)
if cropped_ds is None:
cropped_ds = _clip_xarray(
self._obj,
geometries=geometries,
all_touched=all_touched,
drop=drop,
invert=invert,
)
if (cropped_ds.coords[self.x_dim].size < 1
or cropped_ds.coords[self.y_dim].size < 1):
raise NoDataInBounds(
f"No data found in bounds.{_get_data_var_message(self._obj)}")
# make sure correct attributes preserved & projection added
_add_attrs_proj(cropped_ds, self._obj)
return cropped_ds
def reproject(
self,
dst_crs,
resolution=None,
shape=None,
transform=None,
resampling=Resampling.nearest,
):
"""
Reproject :obj:`xarray.DataArray` objects
Powered by `rasterio.warp.reproject`
.. note:: Only 2D/3D arrays with dimensions 'x'/'y' are currently supported.
Requires either a grid mapping variable with 'spatial_ref' or
a 'crs' attribute to be set containing a valid CRS.
If using a WKT (e.g. from spatiareference.org), make sure it is an OGC WKT.
.. versionadded:: 0.0.27 shape
.. versionadded:: 0.0.28 transform
Parameters
----------
dst_crs: str
OGC WKT string or Proj.4 string.
resolution: float or tuple(float, float), optional
Size of a destination pixel in destination projection units
(e.g. degrees or metres).
shape: tuple(int, int), optional
Shape of the destination in pixels (dst_height, dst_width). Cannot be used
together with resolution.
transform: optional
The destination transform.
resampling: Resampling method, optional
See rasterio.warp.reproject for more details.
Returns
-------
:obj:`xarray.DataArray`:
The reprojected DataArray.
"""
if resolution is not None and (shape is not None
or transform is not None):
raise RioXarrayError(
"resolution cannot be used with shape or transform.")
if self.crs is None:
raise MissingCRS(
"CRS not found. Please set the CRS with 'rio.write_crs()'."
f"{_get_data_var_message(self._obj)}")
src_affine = self.transform(recalc=True)
if transform is None:
dst_affine, dst_width, dst_height = _make_dst_affine(
self._obj, self.crs, dst_crs, resolution, shape)
else:
dst_affine = transform
if shape is not None:
dst_height, dst_width = shape
else:
dst_height, dst_width = self.shape
extra_dim = self._check_dimensions()
if extra_dim:
dst_data = np.zeros(
(self._obj[extra_dim].size, dst_height, dst_width),
dtype=self._obj.dtype.type,
)
else:
dst_data = np.zeros((dst_height, dst_width),
dtype=self._obj.dtype.type)
dst_nodata = self._obj.dtype.type(
self.nodata if self.nodata is not None else -9999)
src_nodata = self._obj.dtype.type(
self.nodata if self.nodata is not None else dst_nodata)
rasterio.warp.reproject(
source=self._obj.values,
destination=dst_data,
src_transform=src_affine,
src_crs=self.crs,
src_nodata=src_nodata,
dst_transform=dst_affine,
dst_crs=dst_crs,
dst_nodata=dst_nodata,
resampling=resampling,
)
# add necessary attributes
new_attrs = _generate_attrs(self._obj, dst_nodata)
# make sure dimensions with coordinates renamed to x,y
dst_dims = []
for dim in self._obj.dims:
if dim == self.x_dim:
dst_dims.append("x")
elif dim == self.y_dim:
dst_dims.append("y")
else:
dst_dims.append(dim)
xda = xarray.DataArray(
name=self._obj.name,
data=dst_data,
coords=_make_coords(self._obj, dst_affine, dst_width, dst_height),
dims=tuple(dst_dims),
attrs=new_attrs,
)
xda.encoding = self._obj.encoding
xda.rio.write_transform(dst_affine, inplace=True)
xda.rio.write_crs(dst_crs, inplace=True)
xda.rio.write_coordinate_system(inplace=True)
return xda
def reproject(
self,
dst_crs,
resolution=None,
shape=None,
transform=None,
resampling=Resampling.nearest,
nodata=None,
**kwargs,
):
"""
Reproject :obj:`xarray.DataArray` objects
Powered by :func:`rasterio.warp.reproject`
.. note:: Only 2D/3D arrays with dimensions 'x'/'y' are currently supported.
Requires either a grid mapping variable with 'spatial_ref' or
a 'crs' attribute to be set containing a valid CRS.
If using a WKT (e.g. from spatiareference.org), make sure it is an OGC WKT.
.. versionadded:: 0.0.27 shape
.. versionadded:: 0.0.28 transform
.. versionadded:: 0.5.0 nodata, kwargs
Parameters
----------
dst_crs: str
OGC WKT string or Proj.4 string.
resolution: float or tuple(float, float), optional
Size of a destination pixel in destination projection units
(e.g. degrees or metres).
shape: tuple(int, int), optional
Shape of the destination in pixels (dst_height, dst_width). Cannot be used
together with resolution.
transform: Affine, optional
The destination transform.
resampling: rasterio.enums.Resampling, optional
See :func:`rasterio.warp.reproject` for more details.
nodata: float, optional
The nodata value used to initialize the destination;
it will remain in all areas not covered by the reprojected source.
Defaults to the nodata value of the source image if none provided
and exists or attempts to find an appropriate value by dtype.
**kwargs: dict
Additional keyword arguments to pass into :func:`rasterio.warp.reproject`.
To override:
- src_transform: `rio.write_transform`
- src_crs: `rio.write_crs`
- src_nodata: `rio.write_nodata`
Returns
-------
:obj:`xarray.DataArray`:
The reprojected DataArray.
"""
if resolution is not None and (shape is not None
or transform is not None):
raise RioXarrayError(
"resolution cannot be used with shape or transform.")
if self.crs is None:
raise MissingCRS(
"CRS not found. Please set the CRS with 'rio.write_crs()'."
f"{_get_data_var_message(self._obj)}")
gcps = self.get_gcps()
if gcps:
kwargs.setdefault("gcps", gcps)
src_affine = None if "gcps" in kwargs else self.transform(recalc=True)
if transform is None:
dst_affine, dst_width, dst_height = _make_dst_affine(
self._obj, self.crs, dst_crs, resolution, shape, **kwargs)
else:
dst_affine = transform
if shape is not None:
dst_height, dst_width = shape
else:
dst_height, dst_width = self.shape
dst_data = self._create_dst_data(dst_height, dst_width)
dst_nodata = self._get_dst_nodata(nodata)
rasterio.warp.reproject(
source=self._obj.values,
destination=dst_data,
src_transform=src_affine,
src_crs=self.crs,
src_nodata=self.nodata,
dst_transform=dst_affine,
dst_crs=dst_crs,
dst_nodata=dst_nodata,
resampling=resampling,
**kwargs,
)
# add necessary attributes
new_attrs = _generate_attrs(self._obj, dst_nodata)
# make sure dimensions with coordinates renamed to x,y
dst_dims = []
for dim in self._obj.dims:
if dim == self.x_dim:
dst_dims.append("x")
elif dim == self.y_dim:
dst_dims.append("y")
else:
dst_dims.append(dim)
xda = xarray.DataArray(
name=self._obj.name,
data=dst_data,
coords=_make_coords(self._obj, dst_affine, dst_width, dst_height),
dims=tuple(dst_dims),
attrs=new_attrs,
)
xda.encoding = self._obj.encoding
xda.rio.write_transform(dst_affine, inplace=True)
xda.rio.write_crs(dst_crs, inplace=True)
xda.rio.write_coordinate_system(inplace=True)
return xda