onstove.DataProcessor#

class onstove.DataProcessor(project_crs: pyproj.CRS | int | None = 3395, cell_size: tuple[float] = (1000, 1000), output_directory: str = '.')[source]#

Class containing the methods to process the GIS datasets required for the MCA and the OnStove models.

Parameters:

project_crs: pyproj.CRS or int, default 3395: The coordinate system of the project. The value can be anything accepted by geopandas.GeoDataFrame.to_crs, such as an authority string (eg “EPSG:4326”), a WKT string or an EPSG int. If defined all datasets added to the DataProcessor will be reprojected to this crs when calling the reproject_layers() method. If not defined then the crs of the base_layer will be used.
cell_size: tuple of float (width, height), default (1000, 1000): The desired cell size of the raster layers. It should be defined in the units of the used crs. If defined, it will be used to rescale all datasets when calling the align() method. If not defined, the cell_size of the base_layer will be used.
output_directory: str, default ‘output’: A folder path where to save the output datasets.

Attributes:

layers: dict[str, dict[str, ‘RasterLayer’]]: All layers added to the DataProcessor using the add_layer() method.
mask_layer: VectorLayer: Layer used to mask all datasets when calling the mask_layers() method. It is set with the add_mask_layer() method.
conn: psycopg2.connect: Connection to a PostgreSQL database, set with the set_postgres() method.
base_layer:: RasterLayer to use as template for all raster based data processes. For example, the align_layers() uses the grid cell of this raster to align all other rasters.

Methods

`add_layer`(path, layer_type[, category, ...])	Adds a new layer (type VectorLayer or RasterLayer) to the DataProcessor class
`add_mask_layer`(path[, category, name, ...])	Adds a vector layer to self.mask_layer.
`align_layers`([datasets, save_layers])	Ensures that the coordinate system and resolution of the raster is the same as the base layer
`get_distance_rasters`([datasets, save_layers])	Calls the .distance_raster method of all the layers entered.
`mask_layers`([datasets, crop, save_layers])	Uses the mask layer in `self.mask_layer` to mask layers to its boundaries.
`normalize_rasters`([datasets, buffer, ...])	Calls the .normalize method of all the layers entered.
`read_model`(path)	Reads a model from a pickle
`reproject_layers`([datasets, save_layers])	Reprojects all layers entered.
`save_datasets`([datasets])	Saves layers.
`set_postgres`(dbname, user, password)	Wrapper function to set a connection to a PostgreSQL database using the psycopg2.connect class.
`to_pickle`(name)	Saves the model as a pickle.