# Prepare Python environment
import scipy.io as sio
from pathlib import Path
data_dir = Path("../../../data/05-B0/data")
import math
import json
import nibabel as nib
import numpy as np
from numpy.fft import ifftn, fftn, ifft, fftshift, ifftshift
import os
import plotly.express as px
import plotly.graph_objects as go
from plotly.subplots import make_subplots
from scipy.signal import butter, lfilter, freqz, filtfilt
from scipy.io import loadmat
import warnings
PI_UNICODE = "\U0001D70B"
CHI_UNICODE = "\U0001D712"
MICRO_UNICODE = "\u00B5"
GYRO_BAR_RATIO_H = 42.6e6 # [Hz/T]
# Load cylinder (Y 64)
susc = nib.load(data_dir / "field_simulations" / "cylinder" / "Chi.nii.gz").get_fdata()
fmap_hz_all = nib.load(data_dir / "field_simulations" / "cylinder" / "fmap_hz.nii.gz").get_fdata()
local_field_cyl = nib.load(data_dir / "field_simulations" / "cylinder" / "local_field.nii.gz").get_fdata()
fig = make_subplots(rows=1, cols=3, shared_xaxes=False, horizontal_spacing=0.13, vertical_spacing = 0.12, subplot_titles=(f"Susceptibility distribution ({CHI_UNICODE})", "Simulated B0 map", "Simulated B0 map<br>no background field"), specs=[[{"type": "Heatmap"}, {"type": "Heatmap"}, {"type": "Heatmap"}]])
fig.add_trace(go.Heatmap(z=susc, colorscale='gray', colorbar_x=1/3 - 0.09, colorbar=dict(title="ppm", titleside="top")), 1, 1)
fig.add_trace(go.Heatmap(z=fmap_hz_all, colorscale='gray', colorbar_x=2/3 - 0.045, colorbar=dict(title="Hz", titleside="top")), 1, 2)
fig.add_trace(go.Heatmap(z=local_field_cyl, colorscale='gray', colorbar_x=1-0.004, colorbar=dict(title="Hz", titleside="top")), 1, 3)
### Create buttons for drop down menu
labels = ["Cylinders", "Brain"]
buttons = []
for i, label in enumerate(labels):
if label == "Cylinders":
visibility = [True, True, True, False, False, False]
else:
visibility = [False, False, False, True, True, True]
button = dict(
label = label,
method = 'update',
args = [{'visible': visibility},
{'title': " "}])
buttons.append(button)
updatemenus = list([
dict(active=0,
x=0.58,
y=1.5,
buttons=buttons,
showactive=True,
)
])
fig.update_xaxes(showticklabels=False)
fig.update_yaxes(showticklabels=False)
fig.update_layout({"height": 350, "width": 750},
title_text=" ",
title_x=0.5,
updatemenus=updatemenus,
showlegend=False
)
fig.show()Loading...
# Prepare Python environment
import scipy.io as sio
from pathlib import Path
data_dir = Path("../../../data/05-B0/data")
import math
import json
import nibabel as nib
import numpy as np
from numpy.fft import ifftn, fftn, ifft, fftshift, ifftshift
import os
import plotly.express as px
import plotly.graph_objects as go
from plotly.subplots import make_subplots
from scipy.signal import butter, lfilter, freqz, filtfilt
from scipy.io import loadmat
import warnings
PI_UNICODE = "\U0001D70B"
CHI_UNICODE = "\U0001D712"
MICRO_UNICODE = "\u00B5"
GYRO_BAR_RATIO_H = 42.6e6 # [Hz/T]
# Load cylinder (Y 64)
susc = nib.load(data_dir / "field_simulations" / "cylinder" / "Chi.nii.gz").get_fdata()
fmap_hz_all = nib.load(data_dir / "field_simulations" / "cylinder" / "fmap_hz.nii.gz").get_fdata()
local_field_cyl = nib.load(data_dir / "field_simulations" / "cylinder" / "local_field.nii.gz").get_fdata()
# Load brain (Z 210)
susc_brain = nib.load(data_dir / "field_simulations" / "brain" / "chi_masked.nii.gz").get_fdata()
fmap_hz_brain_all = nib.load(data_dir / "field_simulations" / "brain" / "fmap_masked.nii.gz").get_fdata()
local_field_brain = nib.load(data_dir / "field_simulations" / "brain" / "local_field.nii.gz").get_fdata()
# Rotate brain
susc_brain = np.rot90(susc_brain, -1)
fmap_hz_brain_all = np.rot90(fmap_hz_brain_all, -1)
local_field_brain = np.rot90(local_field_brain, -1)
fig = make_subplots(rows=1, cols=3, shared_xaxes=False, horizontal_spacing=0.13, vertical_spacing = 0.12, subplot_titles=(f"Susceptibility distribution ({CHI_UNICODE})", "Simulated B0 map", "Simulated B0 map<br>no background field"), specs=[[{"type": "Heatmap"}, {"type": "Heatmap"}, {"type": "Heatmap"}]])
fig.add_trace(go.Heatmap(z=susc, colorscale='gray', colorbar_x=1/3 - 0.09, colorbar=dict(title="ppm", titleside="top")), 1, 1)
fig.add_trace(go.Heatmap(z=fmap_hz_all, colorscale='gray', colorbar_x=2/3 - 0.045, colorbar=dict(title="Hz", titleside="top")), 1, 2)
fig.add_trace(go.Heatmap(z=local_field_cyl, colorscale='gray', colorbar_x=1-0.004, colorbar=dict(title="Hz", titleside="top")), 1, 3)
fig.add_trace(go.Heatmap(z=np.rot90(susc_brain, k=-1), colorscale='gray', colorbar_x=1/3 - 0.09, zmin=-0.5, zmax=0.5, colorbar=dict(title="ppm", titleside="top"), visible=False), 1, 1)
fig.add_trace(go.Heatmap(z=np.rot90(fmap_hz_brain_all, k=-1), colorscale='gray', colorbar_x=2/3 - 0.045, zmin=1100, zmax=2300, colorbar=dict(title="Hz", titleside="top"), visible=False), 1, 2)
fig.add_trace(go.Heatmap(z=np.rot90(local_field_brain, k=-1), colorscale='gray', zmin=-4, zmax=4, colorbar_x=1-0.004, colorbar=dict(title="Hz", titleside="top"), visible=False), 1, 3)
fig.update_xaxes(showticklabels=False)
fig.update_yaxes(showticklabels=False)
fig.update_layout({"height": 350, "width": 700},
title_text=" ",
title_x=0.5,
showlegend=False
)
# Add annotation for "a" (Figure 5-a)
fig.add_annotation(
x=-0.07, # X position (0 is left, 1 is right)
y=-0.05, # Y position (0 is bottom, 1 is top)
xref="paper", # Use paper coordinates (relative to the entire figure)
yref="paper",
text="a", # Text to display
showarrow=False, # Don't show an arrow
font=dict(size=50, color="black"), # Font size and color
xanchor="left", # Anchor text to the left
yanchor="bottom" # Anchor text to the bottom
)
fig.show()Loading...
# Load brain (Z 210)
susc_brain = nib.load(data_dir / "field_simulations" / "brain" / "chi_masked.nii.gz").get_fdata()
fmap_hz_brain_all = nib.load(data_dir / "field_simulations" / "brain" / "fmap_masked.nii.gz").get_fdata()
local_field_brain = nib.load(data_dir / "field_simulations" / "brain" / "local_field.nii.gz").get_fdata()
# Rotate brain
susc_brain = np.rot90(susc_brain, -1)
fmap_hz_brain_all = np.rot90(fmap_hz_brain_all, -1)
local_field_brain = np.rot90(local_field_brain, -1)
fig_brain = make_subplots(rows=1, cols=3, shared_xaxes=False, horizontal_spacing=0.13, vertical_spacing = 0.12, subplot_titles=(f"Susceptibility distribution ({CHI_UNICODE})", "Simulated B0 map", "Simulated B0 map<br>no background field"), specs=[[{"type": "Heatmap"}, {"type": "Heatmap"}, {"type": "Heatmap"}]])
fig_brain.add_trace(go.Heatmap(z=np.rot90(susc_brain, k=-1), colorscale='gray', colorbar_x=1/3 - 0.09, zmin=-0.5, zmax=0.5, colorbar=dict(title="ppm", titleside="top")), 1, 1)
fig_brain.add_trace(go.Heatmap(z=np.rot90(fmap_hz_brain_all, k=-1), colorscale='gray', colorbar_x=2/3 - 0.045, zmin=1100, zmax=2300, colorbar=dict(title="Hz", titleside="top")), 1, 2)
fig_brain.add_trace(go.Heatmap(z=np.rot90(local_field_brain, k=-1), colorscale='gray', zmin=-4, zmax=4, colorbar_x=1-0.004, colorbar=dict(title="Hz", titleside="top")), 1, 3)
fig_brain.update_xaxes(showticklabels=False)
fig_brain.update_yaxes(showticklabels=False)
fig_brain.update_layout({"height": 350, "width": 700},
title_text=" ",
title_x=0.5,
showlegend=False
)
# Add annotation for "a" (Figure 5-a)
fig_brain.add_annotation(
x=-0.07, # X position (0 is left, 1 is right)
y=-0.05, # Y position (0 is bottom, 1 is top)
xref="paper", # Use paper coordinates (relative to the entire figure)
yref="paper",
text="b", # Text to display
showarrow=False, # Don't show an arrow
font=dict(size=50, color="black"), # Font size and color
xanchor="left", # Anchor text to the left
yanchor="bottom" # Anchor text to the bottom
)
fig_brain.show()Loading...
import copy
# Create a deep copy of fig_brain
fig_inverse = copy.deepcopy(fig_brain)
# Remove the annotation ("b") from the new fig object
fig_inverse.layout.annotations = [ann for ann in fig.layout.annotations if ann.text != "b"]
# Flip the traces (susc_brain and local_field_brain) using data from fig_brain
# Swap z, zmin, and zmax between the first and third traces
(fig_inverse.data[0].z, fig_inverse.data[1].z) = (fig_brain.data[1].z, fig_brain.data[0].z) # Swap z
(fig_inverse.data[0].zmin, fig_inverse.data[1].zmin) = (fig_brain.data[1].zmin, fig_brain.data[0].zmin) # Swap zmin
(fig_inverse.data[0].zmax, fig_inverse.data[1].zmax) = (fig_brain.data[1].zmax, fig_brain.data[0].zmax) # Swap zmax
# Swap the annotation titles by reusing the existing annotations
(fig_inverse.layout.annotations[0].text, fig_inverse.layout.annotations[1].text) = (
fig_brain.layout.annotations[1].text, fig_brain.layout.annotations[0].text
)
# Remove the third trace
fig_inverse.data = fig_inverse.data[0:2]
fig_inverse.layout.annotations = fig_inverse.layout.annotations[0:2]
fig_inverse.update_layout({"height": 350, "width": 700},
title_text=" ",
title_x=0.5,
showlegend=False
)
# Show the updated figure
fig_inverse.show()Loading...