onstove.OnStove.create_layer#

OnStove.create_layer(variable: str, name: str | None = None, labels: dict[str, str] | None = None, cmap: dict[str, str] | None = None, metric: str = 'mean', nodata: float | int | None = None) → tuple[RasterLayer, dict[int, str], dict[int, str]][source]#

Creates a RasterLayer from a column of the main GeoDataFrame (gdf).

If the data is categorical, then a rasterized version of the data is created, using integers in asscending order for the diffenrent unique categories found. A codes and a cmap dictionaries will be returned containing the names and color equivalent of the numbered categories.

If the data is non-categorical, the source data will be rasterized into the RasterLayer using one of the available metrics.

Parameters:

variable: str

The column name from the gdf to use.

name: str, optional

The name to give to the RasterLayer.

labels: dictionary of str key-value pairs, optional

Dictionary with the keys-value pairs to use for the data categories. It is only used for categorical data.

Example of labels dictionary#

>>> labels = {'Biogas and Electricity': 'Electricity and Biogas',
...           'Collected Traditional Biomass': 'Biomass',
...           'Collected Improved Biomass': 'Biomass ICS (ND)',
...           'Traditional Charcoal': 'Charcoal',
...           'Biomass Forced Draft': 'Biomass ICS (FD)',
...           'Pellets Forced Draft': 'Pellets ICS (FD)'}

cmap: dictionary of str key-value pairs, optional

Dictionary with the colors to use for each data category. It is only used for categorical data.

Example of cmap dictionary#

>>> cmap = {'Biomass ICS (ND)': '#6F4070',
...         'LPG': '#66C5CC',
...         'Biomass': '#FFB6C1',
...         'Biomass ICS (FD)': '#af04b3',
...         'Pellets ICS (FD)': '#ef02f5',
...         'Charcoal': '#364135',
...         'Charcoal ICS': '#d4bdc5',
...         'Biogas': '#73AF48',
...         'Biogas and Biomass ICS (ND)': '#F6029E',
...         'Biogas and Biomass ICS (FD)': '#F6029E',
...         'Biogas and Pellets ICS (FD)': '#F6029E',
...         'Biogas and LPG': '#0F8554',
...         'Biogas and Biomass': '#266AA6',
...         'Biogas and Charcoal': '#3B05DF',
...         'Biogas and Charcoal ICS': '#3B59DF',
...         'Electricity': '#CC503E',
...         'Electricity and Biomass ICS (ND)': '#B497E7',
...         'Electricity and Biomass ICS (FD)': '#B497E7',
...         'Electricity and Pellets ICS (FD)': '#B497E7',
...         'Electricity and LPG': '#E17C05',
...         'Electricity and Biomass': '#FFC107',
...         'Electricity and Charcoal ICS': '#660000',
...         'Electricity and Biogas': '#f97b72',
...         'Electricity and Charcoal': '#FF0000'}

metric: str, default ‘mean’

Metric to use to aggregate data. It is only used for non-categorical data. Available metrics:

mean: average value between technologies used in the same cell.
total: the total value of the data accounting for all households in the cell.
per_100k: the values are calculated per 100 thousand population withing each cell.
per_household: average value per househol in each cell.

nodata: float or int

Defines nodata values to be ignored by the function.

Returns:

raster: RasterLayer: The :class:RasterLayer object.
codes: dictionary of int-str pairs: Contains the name equivalent to therasterized data (used if the data is categorical).
cmap: dictionary of int-str pairs: A modified cmap containing the color s equivalent to the rasterized data (used if the data is categorical).