nwm_eval.create_plots

Module for creating plots to visualize the metrics calculated for NWM evaluation.

Functions:

• get_metric_long_name: Get long names for metrics based on the library used for calculating the metrics.

• filter_by_lead_metric: Filter the metric DataFrame by lead times and metrics based on the configuration.

• gather_all_metrics: Gather metrics from all datasets into a single DataFrame.

• add_tag_to_filename: Add a tag to the filename if it exists in the config.

• save_plot: Save the plot to a file with a name based on the metric, lead time, dataset, and other parameters.

• group_df_by_location: Group DataFrame by location and return a tuple of DataFrames (in_list, out_list).

• get_metric_dataframe: Get the metric DataFrame by gathering all metrics and then filtering by metric subset and lead times.

• create_spatial_map: Create spatial maps for each dataset, metric, and lead time.

• set_up_figure: Set up a matplotlib figure with dynamic sizing based on data.

• add_shared_legend: Add a shared legend to the figure.

• create_boxplot: Create boxplots for each metric in the configuration.

• create_histogram: Create histograms for each metric in the configuration.

Functions

add_shared_legend	Add a shared legend to the figure.
add_tag_to_filename	Add a tag to the filename if it exists in the config.
barchart_all_metrics	Create a bar chart comparing datasets for each metric.
barchart_by_metric	Create a bar chart comparing datasets for each metric and lead time.
create_all_plots	Create all plots based on the configuration.
create_barchart	Create a bar chart comparing datasets for each metric and lead time.
create_boxplot	Create boxplots for each metric in the configuration.
create_histogram	Create histograms for each metric in the configuration.
create_metric_table	Create a metric table based on the configuration.
create_spatial_map	Create spatial maps for each dataset, metric, and lead time.
create_time_series	Create a time series plot for each dataset in the configuration.
filter_by_lead_metric	Filter the metric DataFrame by lead times and metrics.
gather_all_metrics	Gather metrics from all datasets into a single DataFrame.
get_metric_dataframe	Get the metric DataFrame by gathering all metrics and then filtering by metric subset and lead times.
get_metric_groups	Get metric groups for the configuration.
get_metric_long_name	Get long names for metrics.
get_time_series	Get forecast or observed time series data (and unit) from forecast or observed data file.
group_df_by_location	Group DataFrame by location and return a tuple of DataFrames (in_list, out_list).
plot_time_series	Plot time series of observed and forecasted streamflow for a single location.
save_plot	Save the plot to a file.
set_up_figure	Set up a matplotlib figure with dynamic sizing based on data.