Visualization¶
plot_accuracy_map¶
Plot predicted accuracy as a spatial map.
Usage¶
from geoequity.visualization import plot_accuracy_map
fig, ax = plot_accuracy_map(
model,
ds,
mask=land_mask,
cmap='Spectral_r',
vmin=0, vmax=1
)
Parameters¶
| Name | Type | Default | Description |
|---|---|---|---|
| model | TwoStageModel | - | Fitted TwoStageModel |
| ds | xarray.Dataset | - | Dataset with lon/lat coordinates |
| mask | array | None | Boolean mask for valid regions |
| cmap | str | 'Spectral_r' | Matplotlib colormap |
| vmin | float | 0 | Colorbar minimum |
| vmax | float | 1 | Colorbar maximum |
plot_accuracy_comparison¶
Compare accuracy across multiple visualization modes.
Usage¶
from geoequity.visualization import plot_accuracy_comparison
fig, axes = plot_accuracy_comparison(
df,
model_name='MyModel',
modes=['observation', 'interpolation', 'spatial_model'],
accuracy_range=(0, 1),
lon_range=(-10, 35),
lat_range=(35, 70)
)
Parameters¶
| Name | Type | Default | Description |
|---|---|---|---|
| df | DataFrame | - | Data with model predictions |
| model_name | str | - | Model column prefix |
| modes | list | - | Visualization modes to compare |
| accuracy_range | tuple | (0, 1) | Colorbar range |
| lon_range | tuple | None | Longitude bounds |
| lat_range | tuple | None | Latitude bounds |