gnnwr.utils module

class gnnwr.utils.DIAGNOSIS(weight, x_data, y_data, y_pred)

Bases: object

Diagnosis is the class to calculate the diagnoses of GNNWR/GTNNWR.

Parameters:

• weight – output of the neural network

• x_data – the independent variables

• y_data – the dependent variables

• y_pred – output of the GNNWR/GTNNWR

AIC()

Returns:

AIC

AICc()

Returns:

AICc

Adjust_R2()

Returns:

Adjust R2 of the result

F1_GNN()

Returns:

F1-test

R2()

Returns:

R2 of the result

RMSE()

Returns:

RMSE of the result

hat()

Returns:

hat matrix

class gnnwr.utils.OLS(dataset, xName: list, yName: list)

Bases: object

OLS is the class to calculate the OLR weights of data.Get the weight by object.params.

Parameters:

• dataset – Input data

• xName – the independent variables’ column

• yName – the dependent variable’s column

class gnnwr.utils.Visualize(data, lon_lat_columns=None, zoom=4)

Bases: object

display_dataset(name='all', y_column=None, colors=None, steps=20, vmin=None, vmax=None)

dot_map(data, lon_column, lat_column, y_column, zoom=4, colors=None, steps=20, vmin=None, vmax=None)

weights_heatmap(data_column, colors=None, steps=20, vmin=None, vmax=None)