energy_demand.plotting package¶
Submodules¶
energy_demand.plotting.basic_plot_functions module¶
Basic plotting functions
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energy_demand.plotting.basic_plot_functions.
cm2inch
(*tupl)[source]¶ Convert input cm to inches (width, hight)
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energy_demand.plotting.basic_plot_functions.
export_legend
(legend, filename='legend.png')[source]¶ Export legend as seperate file
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energy_demand.plotting.basic_plot_functions.
simple_smooth
(x_list, y_list, num=500, spider=False, interpol_kind='quadratic')[source]¶
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energy_demand.plotting.basic_plot_functions.
smooth_data
(x_list, y_list, num=500, spider=False, interpol_kind='quadratic')[source]¶ Smooth data
- x_listlist
List with x values
- y_listlist
List with y values
- numint
New number of interpolation points
- spiderbool
Criteria whether spider plot or not
- interpol_kindstr
Kind of interpolation, i.e. quadratic or cubic
needs at least 4 entries in lists
https://docs.scipy.org/doc/scipy/reference/tutorial/interpolate.html
The smoothing prevents negative values by setting them to zero
energy_demand.plotting.choropleth_mapping module¶
energy_demand.plotting.creage_gif module¶
Create dynamic gif file from results
VALID_EXTENSIONS = (‘png’, ‘jpg’)
http://www.idiotinside.com/2017/06/06/create-gif-animation-with-python/
energy_demand.plotting.fig3_weather_at_home_plot module¶
energy_demand.plotting.fig_3_plot_over_time module¶
energy_demand.plotting.fig_3_weather_map module¶
energy_demand.plotting.fig_cross_graphs module¶
energy_demand.plotting.fig_enduse_yh module¶
energy_demand.plotting.fig_fuels_enduses_week module¶
energy_demand.plotting.fig_fuels_enduses_y module¶
energy_demand.plotting.fig_fuels_peak_h module¶
energy_demand.plotting.fig_lf module¶
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energy_demand.plotting.fig_lf.
create_min_max_polygon_from_lines
(line_data)[source]¶ - Parameters
line_data (dict) –
- linedata containing info
{‘x_value’: [y_values]}
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energy_demand.plotting.fig_lf.
order_polygon
(upper_boundary, lower_boundary)[source]¶ Create correct sorting to draw filled polygon
- Parameters
upper_boundary –
lower_boundary –
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energy_demand.plotting.fig_lf.
plot_lf_y
(fueltype_int, fueltype_str, reg_load_factor_y, reg_nrs, path_plot_fig, plot_individ_lines=False, plot_max_min_polygon=True)[source]¶ Plot load factors per region for every year
energy_demand.plotting.fig_load_profile_dh_multiple module¶
energy_demand.plotting.fig_lp module¶
energy_demand.plotting.fig_one_fueltype_multiple_regions_peak_h module¶
energy_demand.plotting.fig_p2_annual_hours_sorted module¶
energy_demand.plotting.fig_p2_spatial_val module¶
energy_demand.plotting.fig_p2_spatial_weather_map module¶
energy_demand.plotting.fig_p2_temporal_validation module¶
energy_demand.plotting.fig_p2_total_demand_national_scenarios module¶
energy_demand.plotting.fig_p2_weather_val module¶
energy_demand.plotting.fig_spatial_distribution_of_peak module¶
energy_demand.plotting.fig_stacked_enduse module¶
Plot stacked enduses for each submodel
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energy_demand.plotting.fig_stacked_enduse.
run
(years_simulated, results_enduse_every_year, enduses, color_list, fig_name, plot_legend=True)[source]¶ Plots stacked energy demand
- Parameters
Note
Sum across all fueltypes
Not possible to plot single year
https://matplotlib.org/examples/pylab_examples/stackplot_demo.html
energy_demand.plotting.fig_stacked_enduse_sectors module¶
Plot stacked enduses per sector
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energy_demand.plotting.fig_stacked_enduse_sectors.
run
(lookups, years_simulated, results_enduse_every_year, rs_enduses, ss_enduses, is_enduses, fig_name)[source]¶ Plots summarised endues for the three sectors. Annual GWh are converted into GW.
- Parameters
data (dict) – Data container
results_objects –
enduses_data –
Note
Sum across all fueltypes
# INFO Cannot plot a single year?
energy_demand.plotting.fig_total_demand_peak module¶
energy_demand.plotting.fig_weather_variability_priod module¶
energy_demand.plotting.figs_p2 module¶
energy_demand.plotting.plotting_multiple_scenarios module¶
energy_demand.plotting.plotting_results module¶
energy_demand.plotting.plotting_styles module¶
Plotting styles
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energy_demand.plotting.plotting_styles.
font_info
(family='arial', color='black', weight='normal', size=8)[source]¶
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energy_demand.plotting.plotting_styles.
get_colorbrewer_color
(color_prop, color_palette, inverse=False)[source]¶ Get hex color from colorbrewer
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energy_demand.plotting.plotting_styles.
linestyles
()[source]¶ https://matplotlib.org/gallery/lines_bars_and_markers/linestyles.html