Summary Results

This page documents the classes and functions in the summary_results module of the HydroGenerate package.

flow_efficiency_power_plot(x)

Plot turbine efficiency and power as a function of turbine flow.

This function expects time-series outputs stored on x.dataframe_output. It deduplicates by turbine flow, sorts, and then creates a dual-axis plot: efficiency on the left axis and power on the right axis.

Parameters:

x (object) – HydroGenerate results object. Expected attributes include pandas_dataframe (bool) dataframe_output (pandas.DataFrame) with columns: 'turbine_flow_cfs', 'efficiency', 'power_kW'

Returns:

Matplotlib figure containing the dual-axis plot.

Return type:

matplotlib.figure.Figure

Notes

If x.pandas_dataframe is False, the function prints an informational message and returns None.

flow_efficiency_plot(x)

Plot turbine efficiency as a function of turbine flow.

Parameters:

x (object) – HydroGenerate results object. Expected attributes include pandas_dataframe (bool), dataframe_output (pandas.DataFrame) with columns: 'turbine_flow_cfs', 'efficiency', 'power_kW'

Returns:

Matplotlib figure containing the efficiency plot.

Return type:

matplotlib.figure.Figure

Notes

If x.pandas_dataframe is False, the function prints an informational message and returns None.

flow_duration_curve_plot(x)

Plot the flow duration curve (FDC).

The function reads x.flowduration_curve and plots flow versus percent exceedance. It also overlays the design-flow marker using x.design_flow and x.pctime_runfull when available.

Parameters:

x (object) – HydroGenerate results object expected to include flowduration_curve (pandas.DataFrame) with columns 'Percent_Exceedance' and 'Flow' (in m³/s), units (‘US’ or ‘SI’), design_flow (float), pctime_runfull (float)

Returns:

Matplotlib figure containing the flow duration curve.

Return type:

matplotlib.figure.Figure

Notes

If the required flowduration_curve attribute is missing, the function prints an informational message and returns None.

turbine_type_plot(x)

Plot turbine selection regions and mark site characteristics.

The plot uses polygon “regions of influence” in head-flow space for common turbine types (Pelton, Turgo, Francis, Crossflow, Kaplan) and marks the site’s (flow, head) point.

Parameters:

x (object) – HydroGenerate results object expected to include: net_head (float): head (m in SI; ft in US, then converted), design_flow (float or None): m³/s in SI; cfs in US, then converted, flow (float): used if design_flow is not available, units (‘US’ or ‘SI’)

Returns:

Matplotlib figure containing the turbine selection plot.

Return type:

matplotlib.figure.Figure

Notes

The turbine region polygons are defined in SI units. If x.units == 'US', head and flow are converted to SI before plotting.

monthly_figure_plot(df, var_fig)

Generate a monthly summary figure for a specified variable.

The function computes monthly mean and median, and plots the interquartile range (IQR) as a shaded band.

Parameters:

• df (pandas.DataFrame) – Time-indexed DataFrame (DatetimeIndex) containing the target column.

• var_fig (str) – Column name to plot. Common values in HydroGenerate outputs include: 'turbine_flow_cfs', 'energy_kWh', 'capacity_factor'

Returns:

Matplotlib figure containing the monthly plot.

Return type:

matplotlib.figure.Figure

Notes

Axis labels are set based on var_fig to match the original plotting behavior.

plant_capfactor_plot(x)

Plot monthly capacity factor statistics.

Parameters:

x (object) – HydroGenerate results object expected to include: pandas_dataframe (bool), dataframe_output (pandas.DataFrame) with column 'power_kW', rated_power (float): kW

Returns:

Matplotlib figure of monthly capacity factor summary.

Return type:

matplotlib.figure.Figure

Notes

If x.pandas_dataframe is False, the function prints an informational message and returns None.

plant_turbineflow_plot(x)

Plot monthly turbine flow statistics.

Parameters:

x (object) – HydroGenerate results object expected to include: pandas_dataframe (bool), dataframe_output (pandas.DataFrame) with column 'turbine_flow_cfs'

Returns:

Matplotlib figure of monthly turbine flow summary.

Return type:

matplotlib.figure.Figure

Notes

If x.pandas_dataframe is False, the function prints an informational message and returns None.

plant_elecgeneration_plot(x)

Plot monthly electricity generation statistics.

Parameters:

x (object) – HydroGenerate results object expected to include: pandas_dataframe (bool), dataframe_output (pandas.DataFrame) with column 'energy_kWh'

Returns:

Matplotlib figure of monthly electricity generation summary.

Return type:

matplotlib.figure.Figure

Notes

If x.pandas_dataframe is False, the function prints an informational message and returns None.