Composites

apply_xyt_weights(xyt_weights, standardized_indicators, begin, end, sos=None)

Applies pixel-level time weights over an xr.Dataset.

Parameters:

Name	Type	Description	Default
xyt_weights	DataArray	xr.DataArray of monthly weights to be applied	required
standardized_indicators	Dataset	xr.DataSet of indicators to be weighted, should already be shandardized into 0-100 range	required
begin	date	datetime.date,	required
end	date	datetime.date,	required
sos	DataArray	xr.DataArray of season start and end if using different season length aggregations by pixel	None

Returns:

Name	Type	Description
weighted_standardized_indicators	Dataset	xyt xr.DataSet

multiply_weights(da, weights)

Mutiplies Xarray by weights

percentile(da)

Computes percentile of each pixel of an Xarray

pixel_composite_index(indicators, begin, end, indicator_weights=None, sos=None)

Constructs a pixel-based composite index from indicators in an xr.DataSet. Is 'pixel-based' as the standardized values are based on the historical timeseries of the pixel Standardizes input indicators over time and applies variable importance weights

Parameters:

Name	Type	Description	Default
indicators	Dataset	xr.DataSet of N indicators to be combined	required
begin	date	datetime.date,	required
end	date	datetime.date,	required
indicator_weights	list | None	list of len N of importance weights for each indicator	None
sos	DataArray	xr.DataArray of season start and end if using different season length aggregations by pixel	None

Returns:

Name	Type	Description
standardized_indicators	Dataset	xyt xr.DataSet of indicators standardized to 0-100 range
monthly_composite_index	Dataset	xyt xr.DataSet of monthly index with variable weights applied