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155 | import matplotlib.pyplot as plt
import numpy as np
from matplotlib.ticker import AutoMinorLocator
from matplotlib.colors import ListedColormap
from mpl_toolkits.axes_grid1 import make_axes_locatable
from mpl_toolkits.axes_grid1.inset_locator import inset_axes
# Set up the figure layout
fig = plt.figure(figsize=(12.8, 10))
# Top row: 3 squared images
positions_top = [
[0.079, 0.484, 0.234, 0.4], # Left image
[0.415, 0.484, 0.234, 0.4], # Center image
[0.755, 0.484, 0.234, 0.4] # Right image
]
# Define visualization parameters
xticks_labels = ['0', ' ', '40', ' ', '80', ' ', '120']
# Load the RGB values from the IDL file and create the color map
rgb_values = np.loadtxt('Color_Tables/idl_walsa_powercolor_1.txt')
rgb_values[0,:] = [255.0,255.0,255.0]
rgb_values[255,:] = [0.,0.,0.]
rgb_values = rgb_values / 255.0
idl_colormap = ListedColormap(rgb_values)
# Setting global parameters
plt.rcParams.update({
'font.family': 'sans-serif', # Use sans-serif fonts
'font.sans-serif': 'Arial', # Set Helvetica as the default sans-serif font
'font.size': 19, # Global font size
'axes.titlesize': 20, # Title font size
'axes.labelsize': 18, # Axis label font size
'xtick.labelsize': 17, # X-axis tick label font size
'ytick.labelsize': 17, # Y-axis tick label font size
'legend.fontsize': 15, # Legend font size
'figure.titlesize': 19, # Figure title font size
'axes.grid': False, # Turn on grid by default
'grid.alpha': 0.5, # Grid transparency
'grid.linestyle': '--', # Grid line style
'font.weight': 'medium', # Make all fonts bold
'axes.titleweight': 'medium', # Make title font bold
'axes.labelweight': 'medium' # Make axis labels bold
})
plt.rc('axes', linewidth=1.3)
plt.rc('lines', linewidth=1.7)
# Plot the three snapshots in the top row
for i in range(3):
if i == 0:
im = FFT_dominant_frequency*1000 # Convert to mHz
colorbar_label = 'FFT\nDominant Frequency (mHz)'
elif i == 1:
im = Morlet_dominant_frequency*1000 # Convert to mHz
colorbar_label = 'RGWS - Morlet\nDominant Frequency (mHz)'
else:
im = Paul_dominant_frequency*1000 # Convert to mHz
colorbar_label = 'RGWS - Paul\nDominant Frequency (mHz)'
ax = fig.add_axes(positions_top[i]) # Create each subplot in specified position
DF = ax.imshow(WaLSA_histo_opt(im), cmap=idl_colormap, aspect='equal', origin='lower', vmin=im.min(), vmax=im.max())
# Configure axis ticks and labels
ax.tick_params(axis='both', which='both', direction='out', top=True, right=True)
ax.set_xticks(np.arange(0, 130, 20))
ax.set_yticks(np.arange(0, 130, 20))
ax.tick_params(axis='both', which='major', length=8, width=1.4) # Major ticks
ax.tick_params(axis='x', which='major', pad=8) # Major ticks
ax.tick_params(axis='both', which='minor', length=4, width=1.4) # Minor ticks
ax.xaxis.set_minor_locator(AutoMinorLocator(4))
ax.yaxis.set_minor_locator(AutoMinorLocator(4))
ax.set_xlabel('(pixel)')
ax.set_ylabel('(pixel)', labelpad=12)
# Create an inset color bar axis above the plot
divider = make_axes_locatable(ax)
cax = inset_axes(ax, width="100%", height="7.5%", loc='upper center', borderpad=-2.1)
cbar = plt.colorbar(DF, cax=cax, orientation='horizontal')
# Move color bar label to the top of the bar
cbar.set_label(colorbar_label, labelpad=16, linespacing=2)
cbar.ax.tick_params(direction='out', top=True, labeltop=True, bottom=False, labelbottom=False)
cbar.ax.xaxis.set_label_position('top')
# Adjust tick marks for the color bar
cbar.ax.tick_params(axis='x', which='major', length=7, width=1.2, direction='out', top=True, labeltop=True, bottom=False)
cbar.ax.tick_params(axis='x', which='minor', length=4, width=1.2, direction='out', top=True, bottom=False)
# Set colorbar ticks and labels
cbar.ax.xaxis.set_major_formatter(plt.FuncFormatter(lambda x, _: f'{int(x)}'))
# Set minor ticks
cbar.ax.xaxis.set_minor_locator(AutoMinorLocator(10))
# Define the range of the color bar and set major ticks at intervals of 100
tick_min = np.floor(DF.get_clim()[0])
tick_max = np.ceil(DF.get_clim()[1])
major_ticks = np.arange(np.ceil(tick_min / 100) * 100, tick_max + 1, 100)
cbar.set_ticks(major_ticks)
cbar.ax.xaxis.set_major_formatter(plt.FuncFormatter(lambda x, _: f'{int(x)}'))
# Bottom row: 1D signal plot filling the entire row
ax1d = fig.add_axes([0.08, 0.08, 0.906, 0.291]) # [left, bottom, width, height]
ax1d.plot(FFT_frequencies*1000, FFT_averaged_power_normalized, color='DodgerBlue', label='FFT')
ax1d.plot(Morlet_frequencies*1000, Morlet_averaged_power_normalized, color='Red', label='RGWS (Morlet)')
ax1d.plot(Paul_frequencies*1000, Paul_averaged_power_normalized, color='Black', label='RGWS (Paul)')
ax1d.set_title('Mean Power Spectra', pad=21)
ax1d.set_xlabel('Frequency (mHz)', labelpad=5)
ax1d.set_ylabel('Normalised Power', labelpad=12)
ax1d.set_xlim([20, 640])
ax1d.set_ylim(0, 115)
# Set tick marks outside for all four axes
ax1d.tick_params(axis='both', which='both', direction='out', top=True, right=True)
# Custom tick intervals
xtick_positions = range(50, 650, 50) # Major tick marks every 50
xlabel_positions = range(100, 700, 100) # Labels every 100
ax1d.set_xticks(xtick_positions)
labels = [str(pos) if pos in xlabel_positions else '' for pos in xtick_positions]
ax1d.set_xticklabels(labels)
ax1d.set_yticks(np.arange(0, 115, 20))
# Custom tick sizes and thickness
ax1d.tick_params(axis='both', which='major', length=10, width=1.4, pad=5) # Major ticks
ax1d.tick_params(axis='x', which='major', pad=8) # Major ticks
ax1d.tick_params(axis='both', which='minor', length=6, width=1.4) # Minor ticks
# Set minor ticks
ax1d.xaxis.set_minor_locator(AutoMinorLocator(5))
ax1d.yaxis.set_minor_locator(AutoMinorLocator(4))
# Add custom labels manually to the plot .... to align the labels to the right
handles, labels = ax1d.get_legend_handles_labels()
# Define the vertical offset for each legend item
offset = 0.17
for i, (handle, label) in enumerate(zip(handles, labels)):
# Add the colored line
ax1d.plot(
[0.935, 0.98], # x coordinates (start and end of the line)
[0.85 - offset * i, 0.85 - offset * i], # y coordinates (constant to make it horizontal)
transform=ax1d.transAxes,
color=handle.get_color(), # Use the color from the original handle
linestyle=handle.get_linestyle(), # Use the linestyle from the original handle
linewidth=handle.get_linewidth(), # Use the linewidth from the original handle
)
# Add the label text
ax1d.text(
0.925, 0.85 - offset * i,
label,
transform=ax1d.transAxes,
ha='right', va='center', fontsize=17,
)
#--------------------------------------------------------------------------
# Save the figure as a single PDF
pdf_path = 'Figures/Fig4_dominant_frequency_mean_power_spectra.pdf'
WaLSA_save_pdf(fig, pdf_path, color_mode='CMYK')
plt.show()
|
