def test_if_pie_charts_of_costs_is_stored(self):
F1.create_plotly_piechart_fig(
title_of_plot="a_title",
names=["costs1", "costs2"],
values=[0.2, 0.8],
file_name="filename.png",
file_path=OUTPUT_PATH,
)
assert os.path.exists(os.path.join(OUTPUT_PATH, "filename.png")) is True
def test_fixed_width_text_smaller_than_limit_returns_text():
txt = "12345"
assert F1.fixed_width_text(txt, char_num=2) == "12\n34\n5"
def test_fixed_width_text_smaller_than_limit_returns_text():
txt = "12345"
assert txt == F1.fixed_width_text(txt, char_num=10)
def test_get_color_is_cyclic():
colors = [1, 2, 3]
assert F1.get_color(3, colors) == colors[0]
def evaluate_dict(dict_values, path_pdf_report=None, path_png_figs=None):
"""This is the main function of F0. It calls all functions that prepare the simulation output, ie. Storing all simulation output into excellent files, bar charts, and graphs.
Parameters
----------
dict_values :
dict Of all input and output parameters up to F0
path_pdf_report : (str)
if provided, generate a pdf report of the simulation to the given path
path_png_figs : (str)
if provided, generate png figures of the simulation's results to the given path
Returns
-------
type
NA
"""
logging.info(
"Summarizing simulation results to results_timeseries and results_scalars_assets."
)
parse_simulation_log(
path_log_file=os.path.join(
dict_values[SIMULATION_SETTINGS][PATH_OUTPUT_FOLDER], LOGFILE),
dict_values=dict_values,
)
# storing all flows to exel.
store_timeseries_all_busses_to_excel(dict_values)
# Write everything to file with multiple tabs
store_scalars_to_excel(dict_values)
store_as_json(
dict_values,
dict_values[SIMULATION_SETTINGS][PATH_OUTPUT_FOLDER],
JSON_WITH_RESULTS,
)
# generate png figures
if path_png_figs is not None:
# plot demand timeseries
F1_plots.plot_timeseries(dict_values,
data_type=DEMANDS,
file_path=path_png_figs)
# plot demand timeseries for the first 2 weeks only
F1_plots.plot_timeseries(dict_values,
data_type=DEMANDS,
max_days=14,
file_path=path_png_figs)
# plot supply timeseries
F1_plots.plot_timeseries(dict_values,
data_type=RESOURCES,
file_path=path_png_figs)
# plot supply timeseries for the first 2 weeks only
F1_plots.plot_timeseries(dict_values,
data_type=RESOURCES,
max_days=14,
file_path=path_png_figs)
# plot power flows in the energy system
F1_plots.plot_instant_power(dict_values, file_path=path_png_figs)
# plot optimal capacities if there are optimized assets
F1_plots.plot_optimized_capacities(dict_values,
file_path=path_png_figs)
# plot annuity, first-investment and om costs
F1_plots.plot_piecharts_of_costs(dict_values, file_path=path_png_figs)
# generate a pdf report
if path_pdf_report is not None:
app = autoreport.create_app(dict_values)
autoreport.print_pdf(app, path_pdf_report=path_pdf_report)
logging.info("Generating PDF report of the simulation: {}".format(
path_pdf_report))