cea.plots package

Submodules

cea.plots.graphs_demand module

graphs algorithm

cea.plots.graphs_demand.create_demand_graph_for_building(analysis_fields, area_df, color_palette, fields_date, locator, name, total_demand)

cea.plots.graphs_demand.demand_graph_fields(scenario_path)

Lists the available fields for the demand graphs - these are fields that are present in both the building demand results files as well as the totals file (albeit with different units).

cea.plots.graphs_demand.graphs_demand(locator, analysis_fields, gv)

algorithm to print graphs in PDF concerning the dynamics of each and all buildings

Parameters:

• locator (inputlocator.InputLocator) – an InputLocator set to the scenario to compute
• analysis_fields (list[string]) – list of fields (column names in Totals.csv) to analyse

Returns:

• Graphs of each building and total: .Pdf
• heat map file per variable of interest n.

cea.plots.graphs_demand.run_as_script(scenario_path=None, analysis_fields=['Ealf_kWh', 'Qhsf_kWh', 'Qwwf_kWh', 'Qcsf_kWh'])

cea.plots.graphs_optimization module

Note

documentation pending

cea.plots.graphs_solar_potential module

Solar graphs

cea.plots.graphs_solar_potential.calc_graph_I_sol(hourlydata_groups)

cea.plots.graphs_solar_potential.calc_graph_PV(results, results_perarea)

cea.plots.graphs_solar_potential.calc_graph_SC(result, Tin)

cea.plots.heatmaps module

cea.plots.scenario_plots module

scenario_plots.py

Create a list of plots for comparing multiple scenarios.

cea.plots.scenario_plots.create_page_demand(locators, pdf, scenario_names)

Create Page one: Demand :param locators: list of InputLocators, one for each scenario :param pdf: the PdfFile to write the page to :param scenario_names: list of scenario names :return: None

cea.plots.scenario_plots.create_page_lca_embodied(locators, pdf, scenario_names)

Create Page Two: LCA Embodied :param locators: list of InputLocators, one for each scenario :param pdf: the PdfFile to write the page to :param scenario_names: list of scenario names :return: None

cea.plots.scenario_plots.create_page_lca_operation(locators, pdf, scenario_names)

Create Page Three: LCA Operation :param locators: list of InputLocators, one for each scenario :param pdf: the PdfFile to write the page to :param scenario_names: list of scenario names :return: None

cea.plots.scenario_plots.plot_demand(ax, locators, scenario_names, column, title)

cea.plots.scenario_plots.plot_lca_embodied(ax, locators, scenario_names, column, title, unit)

cea.plots.scenario_plots.plot_lca_operation(ax, locators, scenario_names, column, title, unit)

cea.plots.scenario_plots.plot_scenarios(scenarios, output_file)

List each scenario in the folder scenario_root and plot demand and lca (operations, embodied) data.

Parameters:

• scenarios – A list of scenario folders.
• output_file – The filename (pdf) to save the results as.

Returns:

(None)

cea.plots.scenario_plots.run_as_script(scenario_folders=None, output_file=None)

cea.plots.sensitivity_demand_graphs module

Graphs for sensitivity_demand.py

cea.plots.sensitivity_demand_graphs.graph(locator, parameters, method, samples)

Parameters:

• locator – locator class
• parameters – list of output parameters to analyse
• method – ‘morris’ or ‘sobol’ methods
• samples – number of samples to calculate

Returns:

.pdf file per output_parameter stored in locator.get_sensitivity_plots_file()

cea.plots.sensitivity_demand_graphs.run_as_script()

cea.plots.timeseries_interactive_graph module

Module contents