reV.qa_qc.qa_qc.QaQc

class QaQc(out_dir)[source]

Bases: object

reV QA/QC

Parameters:

out_dir (str) – Directory path to save summary data and plots too

Methods

create_scatter_plots([plot_type, cmap])

Create scatter plot for all compatible summary .csv files

exclusions_mask(excl_h5, out_dir[, ...])

Create inclusion mask from given layers dictionary, dump to disk and plot

h5(h5_file, out_dir[, dsets, group, ...])

Run QA/QC by computing summary stats from dsets in h5_file and plotting scatters plots of compatible summary stats

supply_curve(sc_table, out_dir[, columns, ...])

Plot supply curve

Attributes

out_dir

Output directory
property out_dir

Output directory

Returns:

str

create_scatter_plots(plot_type='plotly', cmap='viridis', **kwargs)[source]

Create scatter plot for all compatible summary .csv files

Parameters:

  • plot_type (str, optional) – plot_type of plot to create ‘plot’ or ‘plotly’, by default ‘plotly’

  • cmap (str, optional) – Colormap name, by default ‘viridis’

  • kwargs (dict) – Additional plotting kwargs

classmethod h5(h5_file, out_dir, dsets=None, group=None, process_size=None, max_workers=None, plot_type='plotly', cmap='viridis', **kwargs)[source]

Run QA/QC by computing summary stats from dsets in h5_file and plotting scatters plots of compatible summary stats

Parameters:

  • h5_file (str) – Path to .h5 file to run QA/QC on

  • out_dir (str) – Directory path to save summary tables and plots too

  • dsets (str | list, optional) – Datasets to summarize, by default None

  • group (str, optional) – Group within h5_file to summarize datasets for, by default None

  • process_size (int, optional) – Number of sites to process at a time, by default None

  • max_workers (int, optional) – Number of workers to use when summarizing 2D datasets, by default None

  • plot_type (str, optional) – plot_type of plot to create ‘plot’ or ‘plotly’, by default ‘plotly’

  • cmap (str, optional) – Colormap name, by default ‘viridis’

  • kwargs (dict) – Additional plotting kwargs

classmethod supply_curve(sc_table, out_dir, columns=None, lcoe='mean_lcoe', plot_type='plotly', cmap='viridis', sc_plot_kwargs=None, scatter_plot_kwargs=None)[source]

Plot supply curve

Parameters:

  • sc_table (str) – Path to .csv file containing supply curve table

  • out_dir (str) – Directory path to save summary tables and plots too

  • columns (str | list, optional) – Column(s) to summarize, if None summarize all numeric columns, by default None

  • lcoe (str, optional) – LCOE value to plot, by default ‘mean_lcoe’

  • plot_type (str, optional) – plot_type of plot to create ‘plot’ or ‘plotly’, by default ‘plotly’

  • cmap (str, optional) – Colormap name, by default ‘viridis’

  • sc_plot_kwargs (dict, optional) – Kwargs for supply curve plot, by default None

  • scatter_plot_kwargs (dict) – Kwargs for scatter plot, by default None

classmethod exclusions_mask(excl_h5, out_dir, layers_dict=None, min_area=None, kernel='queen', hsds=False, plot_type='plotly', cmap='viridis', plot_step=100, **kwargs)[source]

Create inclusion mask from given layers dictionary, dump to disk and plot

Parameters:

  • excl_h5 (str) – Path to exclusions .h5 file

  • layers_dict (dict | NoneType) – Dictionary of LayerMask arugments {layer: {kwarg: value}}

  • min_area (float | NoneType) – Minimum required contiguous area in sq-km

  • kernel (str) – Contiguous filter method to use on final exclusions

  • hsds (bool) – Boolean flag to use h5pyd to handle .h5 ‘files’ hosted on AWS behind HSDS

  • plot_type (str, optional) – plot_type of plot to create ‘plot’ or ‘plotly’, by default ‘plotly’

  • cmap (str, optional) – Colormap name, by default ‘viridis’

  • plot_step (int) – Step between points to plot

  • kwargs (dict) – Additional plotting kwargs