def main(args=None):
"""
Parse the arguments, get the data in a df, and create the plot
:return: if requested, return the plot as JSON object
"""
if args is None:
args = sys.argv[1:]
parsed_args = parse_arguments(arguments=args)
conn = connect_to_database(db_path=parsed_args.database)
c = conn.cursor()
scenario_id, scenario = get_scenario_id_and_name(
scenario_id_arg=parsed_args.scenario_id,
scenario_name_arg=parsed_args.scenario,
c=c,
script="energy_plot")
tech_colors = get_tech_colors(c)
tech_plotting_order = get_tech_plotting_order(c)
energy_unit = get_unit(c, "energy")
plot_title = "{}Energy by Period - {} - Stage {}".format(
"{} - ".format(scenario) if parsed_args.scenario_name_in_title else "",
parsed_args.load_zone, parsed_args.stage)
plot_name = "EnergyPlot-{}-{}".format(parsed_args.load_zone,
parsed_args.stage)
df = get_plotting_data(conn=conn,
scenario_id=scenario_id,
load_zone=parsed_args.load_zone,
stage=parsed_args.stage)
source, x_col_reordered = process_stacked_plot_data(
df=df, y_col="energy_mwh", x_col=["period"], category_col="technology")
# Multi-level index in CDS will be joined into one column with "_" separator
x_col_cds = "_".join(x_col_reordered)
x_col_label = ", ".join([x.capitalize() for x in x_col_reordered])
plot = create_stacked_bar_plot(source=source,
x_col=x_col_cds,
x_label=x_col_label,
y_label="Energy ({})".format(energy_unit),
category_label="Technology",
category_colors=tech_colors,
category_order=tech_plotting_order,
title=plot_title,
ylimit=parsed_args.ylimit)
# Show plot in HTML browser file if requested
if parsed_args.show:
show_plot(plot=plot,
plot_name=plot_name,
plot_write_directory=parsed_args.plot_write_directory,
scenario=scenario)
# Return plot in json format if requested
if parsed_args.return_json:
return json_item(plot, plot_name)
def main(args=None):
"""
Parse the arguments, get the data in a df, and create the plot
:return: if requested, return the plot as JSON object
"""
if args is None:
args = sys.argv[1:]
parsed_args = parse_arguments(arguments=args)
conn = connect_to_database(db_path=parsed_args.database)
tech_colors = get_tech_colors(conn.cursor())
tech_plotting_order = get_tech_plotting_order(conn.cursor())
power_unit = get_unit(conn.cursor(), "power")
plot_title = "Total Capacity by Scenario - {} - Subproblem {} - Stage {}"\
.format(
parsed_args.load_zone,
parsed_args.subproblem,
parsed_args.stage
)
plot_name = "TotalCapacityPlot-{}-{}-{}"\
.format(
parsed_args.load_zone,
parsed_args.subproblem,
parsed_args.stage
)
df = get_plotting_data(conn=conn,
period=parsed_args.period,
load_zone=parsed_args.load_zone,
subproblem=parsed_args.subproblem,
stage=parsed_args.stage)
source, x_col_reordered = process_stacked_plot_data(
df=df,
y_col="capacity_mw",
x_col=["period", "scenario_id"],
category_col="technology")
# Multi-level index in CDS will be joined into one column with "_" separator
x_col_cds = "_".join(x_col_reordered)
x_col_label = ", ".join([x.capitalize() for x in x_col_reordered])
plot = create_stacked_bar_plot(
source=source,
x_col=x_col_cds,
x_label=x_col_label,
y_label="Total Capacity ({})".format(power_unit),
category_label="Technology",
category_colors=tech_colors,
category_order=tech_plotting_order,
title=plot_title,
ylimit=parsed_args.ylimit)
# Show plot in HTML browser file if requested
if parsed_args.show:
show_plot(plot=plot,
plot_name=plot_name,
plot_write_directory=parsed_args.plot_write_directory)
# Return plot in json format if requested
if parsed_args.return_json:
return json_item(plot, plot_name)
