# RCAIDE/Library/Plots/Noise/plot_3D_noise_contour.py
#
#
# Created: Jul 2023, M. Clarke
# ----------------------------------------------------------------------------------------------------------------------
# IMPORT
# ----------------------------------------------------------------------------------------------------------------------
from RCAIDE.Framework.Core import Units
from RCAIDE.Library.Plots import *
# python imports
import numpy as np
import plotly.graph_objects as go
# ----------------------------------------------------------------------------------------------------------------------
# PLOTS
# ----------------------------------------------------------------------------------------------------------------------
[docs]
def plot_3D_noise_contour(noise_data,
noise_level = None,
min_noise_level = 35,
max_noise_level = 90,
noise_scale_label = None,
save_figure = False,
show_figure = True,
save_filename = "Noise_Contour",
use_lat_long_coordinates = True,
show_trajectory = False,
show_microphones = False,
colormap = 'jet',
file_type = ".png",
background_color = 'rgb(17,54,71)',
grid_color = 'gray',
width = 1400,
height = 800):
"""
Creates an interactive 3D visualization of noise contours with optional aircraft trajectory.
Parameters
----------
noise_data : NoiseData
RCAIDE noise data structure containing:
- microphone_locations[:,:,0:3]
3D array of microphone positions in (nmi, nmi, ft)
- aircraft_position[:,0:3]
Aircraft trajectory points in (nmi, nmi, ft)
noise_level : ndarray
2D array of noise levels at measurement points
min_noise_level : float, optional
Minimum noise level for contour scale (default: 35 dB)
max_noise_level : float, optional
Maximum noise level for contour scale (default: 90 dB)
noise_scale_label : str, optional
Label for noise metric (e.g., "dBA", "EPNL", etc.)
save_figure : bool, optional
Flag for saving the figure (default: False)
show_figure : bool, optional
Flag to display the figure (default: True)
save_filename : str, optional
Name of file for saved figure (default: "Noise_Contour")
use_lat_long_coordinates : bool, optional
Flag to use geographic coordinates (default: True)
show_trajectory : bool, optional
Flag to display aircraft trajectory (default: False)
show_microphones : bool, optional
Flag to display microphone locations (default: False)
colormap : str, optional
Colormap specification for noise contours (default: 'jet')
file_type : str, optional
File extension for saved figure (default: ".png")
background_color : str, optional
Color specification for plot background (default: 'rgb(17,54,71)')
grid_color : str, optional
Color specification for grid lines (default: 'gray')
width : int, optional
Figure width in pixels (default: 1400)
height : int, optional
Figure height in pixels (default: 800)
Returns
-------
fig_3d : plotly.graph_objects.Figure
Handle to the generated interactive 3D figure
Notes
-----
Creates visualization showing:
* 3D noise contour surface
* Optional aircraft trajectory
* Optional microphone locations
* Interactive viewing controls
* Customizable appearance
**Major Assumptions**
* Noise levels are in decibels
* Coordinates are in nautical miles and feet
* Measurement grid is regularly spaced
* Z-axis represents elevation
**Definitions**
'Noise Contour'
Surface of constant noise level
'Aircraft Trajectory'
Time history of aircraft position
'Microphone Location'
Measurement point coordinates
See Also
--------
RCAIDE.Library.Plots.Noise.plot_2D_noise_contour : 2D visualization of noise field
RCAIDE.Library.Plots.Noise.contour_surface_slice : Surface generation utility
"""
Aircraft_pos = noise_data.aircraft_position
X = noise_data.microphone_locations[:,:,0]/Units.nmi
Y = noise_data.microphone_locations[:,:,1]/Units.nmi
Z = noise_data.microphone_locations[:,:,2]/Units.feet
plot_data = []
# ---------------------------------------------------------------------------
# TRHEE DIMENSIONAL NOISE CONTOUR
# ---------------------------------------------------------------------------
# TERRAIN CONTOUR
ground_contour = contour_surface_slice(Y,X,Z,noise_level,color_scale=colormap)
plot_data.append(ground_contour)
# GROUND MICROPHONES
if show_microphones:
microphones = go.Scatter3d(x = Y.flatten(),
y = X.flatten(),
z = Z.flatten(),
mode = 'markers',
marker = dict(size=6,color='white',opacity=0.8),
line = dict(color='white',width=2))
plot_data.append(microphones)
# AIRCRAFT TRAJECTORY
if show_trajectory:
aircraft_trajectory = go.Scatter3d(x = Aircraft_pos[:,1]/Units.nmi,
y = Aircraft_pos[:,0]/Units.nmi,
z = Aircraft_pos[:,2]/Units.feet,
mode= 'markers',
marker=dict(size=6,
color='black',
opacity=0.8),
line=dict(color='black',width=2))
plot_data.append(aircraft_trajectory)
# Define Colorbar Bounds
min_alt = np.minimum(np.min(Z),0)
max_alt = np.maximum(np.max(Z), np.max(Aircraft_pos[:,2]/Units.feet))
fig_3d = go.Figure(data=plot_data)
if show_microphones or show_trajectory:
pass
else:
fig_3d.update_traces(colorbar_orientation = 'v',
colorbar_thickness = 50,
colorbar_nticks = 10,
colorbar_title_text = noise_scale_label,
colorbar_tickfont_size = 16,
colorbar_title_side = "right",
colorbar_ypad = 50,
colorbar_len = 0.75)
fig_3d.update_layout(
title_text = save_filename,
title_x = 0.5,
width = width,
height = height,
font_size = 12,
scene_aspectmode = "manual",
scene_aspectratio = dict(x=1, y=1, z=0.5),
scene_zaxis_range = [min_alt,max_alt*3],
scene = dict(xaxis_title='Latitude [nmi]',
yaxis_title='Longitude [nmi]',
zaxis_title='Elevation [ft]',
xaxis = dict(
backgroundcolor=background_color,
gridcolor="white",
showbackground=True,
zerolinecolor=grid_color,),
yaxis = dict(
backgroundcolor=background_color,
gridcolor=grid_color,
showbackground=True,
zerolinecolor="white"),
zaxis = dict(
backgroundcolor=background_color,
gridcolor=grid_color,
showbackground=True,
zerolinecolor="white",),),
scene_camera=dict(up = dict(x=0, y=0, z=1),
center= dict(x=-0.05, y=0, z=-0.20),
eye = dict(x=-1.0, y=-1.0, z=.4))
)
if show_figure:
fig_3d.show()
if save_figure:
fig_3d.write_image(save_filename, file_type)
return fig_3d
[docs]
def colorax(vmin, vmax):
return dict(cmin=vmin, cmax=vmax)
