# RCAIDE/Library/Plots/Emissions/plot_emission_species_masses
#
#
# Created: Jul 2024, M. Clarke
# ----------------------------------------------------------------------------------------------------------------------
# IMPORT
# ----------------------------------------------------------------------------------------------------------------------
from RCAIDE.Framework.Core import Units
from RCAIDE.Library.Plots.Common import set_axes, plot_style
import matplotlib.pyplot as plt
import numpy as np
# ----------------------------------------------------------------------------------------------------------------------
# PLOTS
# ----------------------------------------------------------------------------------------------------------------------
[docs]
def plot_emission_species_masses(results,
save_figure = False,
show_legend = True,
save_filename = "Emission_Species_Masses" ,
file_type = ".png",
width = 8, height = 5):
"""
Generate a stacked area plot showing cumulative emissions mass by species over the mission.
Parameters
----------
results : Data
Mission results data structure containing:
results.segments[i].conditions.emissions.mass with fields:
- CO2 : array, carbon dioxide mass [kg]
- NOx : array, nitrogen oxide mass [kg]
- H2O : array, water vapor mass [kg]
- CO : array, carbon monoxide mass [kg]
save_figure : bool, optional
Save figure to file if True, default False
show_legend : bool, optional
Display species legend if True, default True
save_filename : str, optional
Name for saved figure file, default "Emission_Species_Masses"
file_type : str, optional
File extension for saved figure, default ".png"
width : float, optional
Figure width in inches, default 8
height : float, optional
Figure height in inches, default 5
Returns
-------
fig : matplotlib.figure.Figure
Figure showing stacked cumulative species emissions mass over time
"""
ps = plot_style()
parameters = {'axes.labelsize': ps.axis_font_size,
'xtick.labelsize': ps.axis_font_size,
'ytick.labelsize': ps.axis_font_size,
'axes.titlesize': ps.title_font_size}
plt.rcParams.update(parameters)
fig = plt.figure(save_filename)
fig.set_size_inches(width, height)
species_colors = {
'CO2': '#d62728',
'CO' : '#ff7f0e',
'NOx': '#2ca02c',
'H2O': '#1f77b4',
}
species_labels = {
'CO2': r'$CO_2$',
'CO' : r'$CO$',
'NOx': r'$NO_x$',
'H2O': r'$H_2O$',
}
time_all = []
mass = {k: [] for k in ['CO2', 'CO', 'NOx', 'H2O']}
running = {k: 0.0 for k in ['CO2', 'CO', 'NOx', 'H2O']}
for seg in results.segments:
t = seg.conditions.frames.inertial.time[:, 0] / Units.min
time_all.append(t)
for k, attr in [('CO2', 'CO2'), ('CO', 'CO'), ('NOx', 'NOx'), ('H2O', 'H2O')]:
seg_vals = getattr(seg.conditions.emissions.mass, attr)[:, 0] / 1E3
mass[k].append(seg_vals + running[k])
running[k] += seg_vals[-1]
time_all = np.concatenate(time_all)
for k in mass:
mass[k] = np.concatenate(mass[k])
axis_1 = plt.subplot(1, 1, 1)
bottom = np.zeros_like(time_all)
for species in ['CO2', 'CO', 'NOx', 'H2O']:
axis_1.fill_between(time_all, bottom, bottom + mass[species],
label=species_labels[species],
color=species_colors[species], alpha=0.85)
bottom += mass[species]
axis_1.set_ylabel(r'Species Mass (Metric Tons)')
axis_1.set_xlabel(r'Time (mins)')
set_axes(axis_1)
if show_legend:
leg = fig.legend(bbox_to_anchor=(0.5, 0.95), loc='upper center', ncol=4)
leg.set_title('Emission Species', prop={'size': ps.legend_font_size, 'weight': 'heavy'})
fig.tight_layout()
fig.suptitle('Emission Species Masses')
fig.subplots_adjust(top=0.8)
if save_figure:
plt.savefig(save_filename + file_type)
return fig
