# RCAIDE/Library/Plots/Geometry/plot_Layout_of_Passenger_Accommodations.py
#
# Created: Mar 2025, M. Clarke
# ----------------------------------------------------------------------------------------------------------------------
# IMPORT
# ----------------------------------------------------------------------------------------------------------------------
from RCAIDE.Library.Methods.Geometry.LOPA.compute_layout_of_passenger_accommodations import compute_layout_of_passenger_accommodations
import plotly.graph_objects as go
import numpy as np
import os
import sys
# ----------------------------------------------------------------------------------------------------------------------
# plot_Layout_of_Passenger_Accommodations
# ----------------------------------------------------------------------------------------------------------------------
[docs]
def plot_layout_of_passenger_accommodations(fuselage,
save_figure = False,
show_axes = False,
fontsize = 20,
save_filename = "Aircraft_LOPA",
show_figure = True):
'''Plot aircraft layout of passenger accommodations.'''
if type(fuselage.layout_of_passenger_accommodations) != np.ndarray:
compute_layout_of_passenger_accommodations(fuselage)
LOPA = fuselage.layout_of_passenger_accommodations.object_coordinates
fig = go.Figure()
fig.update_xaxes(range=[LOPA[:, 2].min() - 1, LOPA[:, 2].max() + 1], showgrid=True)
fig.update_yaxes(range=[LOPA[:, 3].min() - 1, LOPA[:, 3].max() + 1],
showgrid=True, scaleanchor="x", scaleratio=1)
# ------------------------------------------------------------------
# Cabin boundary
# ------------------------------------------------------------------
x_min_locs = np.where(LOPA[:, 2] == LOPA[:, 2].min())[0]
x_min = LOPA[x_min_locs[0], 2] - LOPA[x_min_locs[0], 5] / 2
x_min_y_max = (LOPA[x_min_locs, 3] + LOPA[x_min_locs, 6] / 2).max()
x_min_y_min = (LOPA[x_min_locs, 3] - LOPA[x_min_locs, 6] / 2).min()
y_max_locs = np.where(LOPA[:, 3] == LOPA[:, 3].max())[0]
y_max = LOPA[y_max_locs[0], 3] + LOPA[y_max_locs[0], 6] / 2
y_max_x_max = (LOPA[y_max_locs, 2] + LOPA[y_max_locs[0], 5] / 2).max()
y_max_x_min = (LOPA[y_max_locs, 2] - LOPA[y_max_locs[0], 5] / 2).min()
x_max_locs = np.where(LOPA[:, 2] == LOPA[:, 2].max())[0]
x_max = LOPA[x_max_locs[0], 2] + LOPA[x_max_locs[0], 5] / 2
x_max_y_max = (LOPA[x_max_locs, 3] + LOPA[x_max_locs, 6] / 2).max()
x_max_y_min = (LOPA[x_max_locs, 3] - LOPA[x_max_locs, 6] / 2).min()
y_min_locs = np.where(LOPA[:, 3] == LOPA[:, 3].min())[0]
y_min = LOPA[y_min_locs[0], 3] - LOPA[y_min_locs[0], 6] / 2
y_min_x_max = (LOPA[y_min_locs, 2] + LOPA[y_min_locs[0], 5] / 2).max()
y_min_x_min = (LOPA[y_min_locs, 2] - LOPA[y_min_locs[0], 5] / 2).min()
x_border = np.array([x_min, x_min, y_max_x_min, y_max_x_max,
x_max, x_max, y_min_x_max, y_min_x_min])
y_border = np.array([x_min_y_min, x_min_y_max, y_max, y_max,
x_max_y_max, x_max_y_min, y_min, y_min])
starboard = y_border >= 0
fig.add_trace(go.Scatter(x=x_border[starboard], y= y_border[starboard],
mode='lines', line_color='darkblue', fill=None, showlegend=False))
fig.add_trace(go.Scatter(x=x_border[starboard], y=-y_border[starboard],
mode='lines', line_color='darkblue', fill='tonexty', showlegend=False))
# ------------------------------------------------------------------
# Seat / galley rectangles — batched by visual category to minimise
# the number of Plotly objects (7 traces instead of one per seat).
#
# Each batch accumulates closed-polygon points with None separators
# so a single go.Scatter trace renders every rect of that category.
# ------------------------------------------------------------------
economy_seat_colors = ["steelblue", "deepskyblue", "skyblue"]
business_seat_colors = ["seagreen", "mediumseagreen", "lightseagreen"]
first_seat_colors = ["indianred", "lightcoral", "lightpink"]
lavatory_color = "sandybrown"
# key → [x_pts, y_pts, line_color, fill_color]
batches = {
('E', True): ([], [], economy_seat_colors[0], economy_seat_colors[1]),
('E', False): ([], [], economy_seat_colors[0], economy_seat_colors[2]),
('B', True): ([], [], business_seat_colors[0], business_seat_colors[1]),
('B', False): ([], [], business_seat_colors[0], business_seat_colors[2]),
('F', True): ([], [], first_seat_colors[0], first_seat_colors[1]),
('F', False): ([], [], first_seat_colors[0], first_seat_colors[2]),
'Lav': ([], [], lavatory_color, lavatory_color),
}
for row in LOPA:
xc, yc = row[2], row[3]
sl, sw = row[5], row[6]
F_c, B_c = row[7], row[8]
E_c, seat = row[9], row[10]
em_row = row[11]
gal_lav = row[12]
# Closed-polygon corners + None separator
x0, x1 = xc - sl / 2, xc + sl / 2
y0, y1 = yc - sw / 2, yc + sw / 2
xs = [x0, x1, x1, x0, x0, None]
ys = [y0, y0, y1, y1, y0, None]
if E_c == 1.0 and seat == 1.0:
key = ('E', em_row == 1.0)
elif B_c == 1 and seat == 1:
key = ('B', em_row == 1)
elif F_c == 1 and seat == 1:
key = ('F', em_row == 1)
elif gal_lav == 1:
key = 'Lav'
else:
continue
batches[key][0].extend(xs)
batches[key][1].extend(ys)
for xs, ys, line_color, fill_color in batches.values():
if not xs:
continue
fig.add_trace(go.Scatter(
x=xs, y=ys,
mode='lines',
line=dict(color=line_color, width=2),
fill='toself',
fillcolor=fill_color,
showlegend=False,
))
# ------------------------------------------------------------------
# Layout
# ------------------------------------------------------------------
common = dict(showlegend=False, font=dict(family="Times New Roman", size=fontsize, color="black"))
if show_axes:
fig.update_layout(**common,
xaxis_title='x', yaxis_title='y',
xaxis=dict(showline=True, linewidth=1, linecolor='black',
showticklabels=True, ticks="outside", tickcolor='black'),
yaxis=dict(showline=True, linewidth=1, linecolor='black',
showticklabels=True, ticks="outside", tickcolor='black'))
else:
fig.update_layout(**common,
plot_bgcolor="white", paper_bgcolor="white",
xaxis=dict(showline=False, linecolor='white', showticklabels=False, tickcolor='white'),
yaxis=dict(showline=False, linecolor='white', showticklabels=False, tickcolor='white'))
save_filename = os.path.join(sys.path[0], save_filename)
if save_figure:
fig.write_image(save_filename + ".png")
if show_figure:
fig.write_html(save_filename + '.html', auto_open=True)
del fig
