def visualize_and_save_independence(independence: 'xr.DataArray', cfg: dict,
ancestors: list):
"""Visualize independence."""
variable = independence.variable_group
labels = list(independence.model_ensemble.values)
figure, axes = plt.subplots(figsize=(15, 15),
subplot_kw={'aspect': 'equal'})
chart = sns.heatmap(
independence,
linewidths=1,
cmap="YlGn",
xticklabels=labels,
yticklabels=labels,
cbar_kws={'label': f'Euclidean distance ({independence.units})'},
ax=axes,
)
chart.set_title(f'Distance matrix for {variable}')
filename_plot = get_plot_filename(f'independence_{variable}', cfg)
figure.savefig(filename_plot, dpi=300, bbox_inches='tight')
plt.close(figure)
filename_data = get_diagnostic_filename(f'independence_{variable}',
cfg,
extension='nc')
independence.to_netcdf(filename_data)
caption = f'Euclidean distance matrix for variable {variable}'
log_provenance(caption, filename_plot, cfg, ancestors)
log_provenance(caption, filename_data, cfg, ancestors)
def visualize_and_save_weights(weights: 'xr.DataArray', cfg: dict,
ancestors: list):
"""Visualize weights."""
label = 'Weights'
filename_plot = get_plot_filename('weights', cfg)
barplot(weights, label, filename_plot)
filename_data = get_diagnostic_filename('weights', cfg, extension='nc')
weights.to_netcdf(filename_data)
caption = 'Weights'
log_provenance(caption, filename_plot, cfg, ancestors)
log_provenance(caption, filename_data, cfg, ancestors)
def visualize_and_save_performance(performance: 'xr.DataArray', cfg: dict,
ancestors: list):
"""Visualize performance."""
label = 'RMS error'
variable_group = performance.variable_group
filename_plot = get_plot_filename(f'performance_{variable_group}', cfg)
barplot(performance, label, filename_plot)
filename_data = get_diagnostic_filename(f'performance_{variable_group}',
cfg,
extension='nc')
performance.to_netcdf(filename_data)
caption = f'Performance metric {label} for variable group {variable_group}'
log_provenance(caption, filename_plot, cfg, ancestors)
log_provenance(caption, filename_data, cfg, ancestors)