rasterize#

geobricks.rasterize(data, *,
                    src_crs = None,
                    base_template = None,
                    bounds = None,
                    x0 = None,
                    y0 = None,
                    mask = None,
                    export_extension = None,
                    main_var_list = None,
                    rasterize_mode = ['sum', 'dominant', 'and'],
                    **rio_kwargs)

Rasterize vector space-time data. rasterize() is a partial alias of the transform() function.

Parameters#

datastr, pathlib.Path, xarray.Dataset, xarray.DataArray or geopandas.GeoDataFrame

Data to transform. Supported file formats are .tif, .asc, .nc and vector formats supported by geopandas (.shp, .json, …).

src_crsint or str or rasterio.crs.CRS, optional, default None

Coordinate reference system of the source (data). When passed as an integer, src_crs refers to the EPSG code. When passed as a string, src_crs can be OGC WKT string or Proj.4 string.

base_templatestr, pathlib.Path, xarray.DataArray or geopandas.GeoDataFrame, optional, default None

Filepath, used as a template for spatial profile. Supported file formats are .tif, .nc and vector formats supported by geopandas (.shp, .json, …).

boundsiterable or None, optional, default None

Boundaries of the target domain as a tuple (x_min, y_min, x_max, y_max).

x0: number, optional, default None

Origin of the X-axis, used to align the reprojection grid.

y0: number, optional, default None

Origin of the Y-axis, used to align the reprojection grid.

maskstr, pathlib.Path, shapely.geometry, xarray.DataArray or geopandas.GeoDataFrame, optional, default None

Filepath of mask used to clip the data.

to_filebool or path (str or pathlib.Path), default False

If True and if data is a path (str or pathlib.Path), the resulting dataset will be exported to a file with the same pathname and the suffix ‘_geop4th’. If to_file is a path, the resulting dataset will be exported to this specified filepath.

export_extensionstr, default ‘.tif’

Extension to which the data will be converted and exported. Only used when the specified data is a filepath. It data is a variable and not a file, it will not be exported.

main_var_listiterable, default None

Data variables to rasterize. Only used if rasterize is True. If None, all variables in data are rasterized.

rasterize_modestr or list of str, or dict, default [‘sum’, ‘dominant’, ‘and’]

Defines the mode to rasterize data:

for numeric variables: 'mean' or 'sum' (default)

for categorical variables: 'percent' or 'dominant' (default)

'dominant' rises the most frequent level for each cell

'percent' creates a new variable per level, which stores

the percentage (from 0 to 100) of occurence of this level compared to all levels, for each cell.

for boolean variables: 'or' or 'and' (default)

The modes can be specified for each variable by passing rasterize_mode as a dict: {'<var1>': 'mean', '<var2>': 'percent', ...}. This argument specification makes it possible to force a numeric variable to be rasterized as a categorical variable. Unspecified variables will be rasterized with the default mode.

**rio_kwargskeyword args, optional, defaults are None

Argument passed to the xarray.Dataset.rio.reproject() function call.

Note: These arguments are prioritary over base_template attributes.

May contain:

dst_crs : str
resolution : float or tuple
shape : tuple (int, int)
transform : Affine
nodata : float or None
resampling :
- see help(rasterio.enums.Resampling)
- most common are: 5 (average), 13 (sum), 0 (nearest), 9 (min), 8 (max), 1 (bilinear), 2 (cubic)…
- the functionality 'std' (standard deviation) is also available
see help(xarray.Dataset.rio.reproject)

Returns#

Transformed dataxarray.Dataset or geopandas.GeoDataFrame.

The type of the resulting variable is accordingly to the type of input data and to the conversion operations (such as rasterize):

all vector data will be output as a geopandas.GeoDataFrame
all raster data and netCDF will be output as a xarray.Dataset

rasterize#

Parameters#

Returns#

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