# RCAIDE/Library/Plots/Thermal_Management/plot_air_cooled_conditions.py
#
#
# Created: Sep 2024, S. Shekar
# ----------------------------------------------------------------------------------------------------------------------
# IMPORT
# ----------------------------------------------------------------------------------------------------------------------
# RCAIDE imports
from RCAIDE.Library.Plots import *
from RCAIDE.Library.Plots.Common import set_axes, plot_style
# Pacakge imports
import numpy as np
from matplotlib import pyplot as plt
import matplotlib.colors as colors
# ----------------------------------------------------------------------------------------------------------------------
# Plot Aircraft Noise Certification Data
# ----------------------------------------------------------------------------------------------------------------------
[docs]
def plot_noise_certification_contour( noise_data,
noise_level = None,
min_noise_level = 45,
max_noise_level = 105,
noise_scale_label = "Max. SPL [dbA]",
save_figure = False,
show_figure = True,
save_filename = "Certification_Noise",
colormap = 'jet',
file_type = ".png",
width = 12,
height = 6):
fig = plt.figure(save_filename)
fig.set_size_inches(width,height)
noise_levels = np.linspace(min_noise_level,max_noise_level,7)
noise_cmap = plt.get_cmap('turbo')
noise_new_cmap = truncate_colormap(noise_cmap,0.0, 1.0)
noise_level = noise_data.certification_SPL_dBA_max
X = noise_data.certification_microphone_locations[:,:,0]
Y = noise_data.certification_microphone_locations[:,:,1]
ap_noise_level = noise_data.approach_SPL_dBA_max
ap_X = noise_data.approach_microphone_locations[:,:,0]
ap_Y = noise_data.approach_microphone_locations[:,:,1]
ap_POS = noise_data.approach_trajectory
to_noise_level = noise_data.takeoff_SPL_dBA_max
to_X = noise_data.takeoff_microphone_locations[:,:,0]
to_Y = noise_data.takeoff_microphone_locations[:,:,1]
to_POS = noise_data.takeoff_trajectory
axis_0 = fig.add_subplot(2,2,1)
axis_0.set_xlabel('x [m]')
axis_0.set_ylabel('altitude [m]')
axis_1 = fig.add_subplot(2,2,3)
axis_1.set_xlabel('x [m]')
axis_1.set_ylabel('y [m]')
axis_2 = fig.add_subplot(2,2,2)
axis_2.set_xlabel('x [m]')
axis_2.set_ylabel('y [m]')
axis_3 = fig.add_subplot(2,2,4)
axis_3.set_xlabel('x [m]')
axis_3.set_ylabel('y [m]')
# plot aircraft position
axis_0.plot(ap_POS[:,0],-ap_POS[:,2], color = 'black', linestyle = '-' , marker = 'o', linewidth = 2, label= "Approach")
axis_0.plot(to_POS[:,0],-to_POS[:,2], color = 'blue', linestyle = '-' , marker = 's', linewidth = 2, label= "Takeoff")
axis_0.legend(loc='upper center')
# plot aircraft noise levels
CS_11 = axis_1.contourf(X,Y,noise_level ,noise_levels,cmap = noise_new_cmap,extend='both')
CS_12 = axis_1.contourf(X,-Y,noise_level ,noise_levels,cmap = noise_new_cmap,extend='both')
CS_21 = axis_2.contourf(ap_X,ap_Y,ap_noise_level ,noise_levels,cmap = noise_new_cmap,extend='both')
CS_22 = axis_2.contourf(ap_X,-ap_Y,ap_noise_level ,noise_levels,cmap = noise_new_cmap,extend='both')
CS_31 = axis_3.contourf(to_X,to_Y,to_noise_level ,noise_levels,cmap = noise_new_cmap,extend='both')
CS_32 = axis_3.contourf(to_X,-to_Y,to_noise_level ,noise_levels,cmap = noise_new_cmap,extend='both')
cbar = fig.colorbar(CS_11, ax=axis_1)
cbar.ax.set_ylabel(noise_scale_label, rotation = 90)
cbar = fig.colorbar(CS_11, ax=axis_2)
cbar.ax.set_ylabel(noise_scale_label, rotation = 90)
cbar = fig.colorbar(CS_11, ax=axis_3)
cbar.ax.set_ylabel(noise_scale_label, rotation = 90)
run_way_x_pts = np.linspace(0, 3000, 20)
run_way_y_pts = run_way_x_pts * 0
axis_1.plot(run_way_x_pts,run_way_y_pts, color = 'grey', linestyle = '-' , linewidth = 5 , alpha=0.5)
axis_2.plot(run_way_x_pts,run_way_y_pts, color = 'grey', linestyle = '-' , linewidth = 5 , alpha=0.5)
axis_3.plot(run_way_x_pts,run_way_y_pts, color = 'grey', linestyle = '-' , linewidth = 5 , alpha=0.5)
set_axes(axis_1)
set_axes(axis_2)
set_axes(axis_3)
axis_0.set_title('Flight Trajectory')
axis_1.set_title('Approach and Takeoff Noise')
axis_2.set_title('Approach Noise')
axis_3.set_title('Takeoff Noise')
fig.tight_layout()
if save_figure:
figure_title = save_filename
plt.savefig(figure_title + file_type )
# ------------------------------------------------------------------
# Truncate colormaps
# ------------------------------------------------------------------
[docs]
def truncate_colormap(cmap, minval=0.0, maxval=1.0, n=100):
new_cmap = colors.LinearSegmentedColormap.from_list(
'trunc({n},{a:.2f},{b:.2f})'.format(n=cmap.name, a=minval, b=maxval),
cmap(np.linspace(minval, maxval, n)))
return new_cmap
