# Prepare Python environment
import numpy as np
import scipy.io as sio
from pathlib import Path
from contextlib import contextmanager
import sys, os
from pathlib import Path
@contextmanager
def suppress_stdout():
with open(os.devnull, "w") as devnull:
old_stdout = sys.stdout
sys.stdout = devnull
try:
yield
finally:
sys.stdout = old_stdout
import os
from pathlib import Path
def find_myst_yml_directories(start_dir=None):
"""
Recursively search for directories containing myst.yml file.
Args:
start_dir (str or Path): Starting directory (defaults to current directory)
Returns:
list: List of full paths to directories containing myst.yml
"""
if start_dir is None:
start_dir = Path.cwd()
else:
start_dir = Path(start_dir)
myst_dirs = []
def _search_directory(current_dir):
# Check if myst.yml exists in current directory
myst_file = current_dir / "myst.yml"
if myst_file.exists():
myst_dirs.append(str(current_dir.resolve()))
# Don't search subdirectories if we found myst.yml here
return
# Recursively search all subdirectories
for item in current_dir.iterdir():
if item.is_dir():
try:
_search_directory(item)
except (PermissionError, OSError):
# Skip directories we can't access
continue
_search_directory(start_dir)
return myst_dirs
def find_myst_yml_directories_upwards(start_dir=None):
"""
Search for myst.yml in current directory, if not found go to parent and repeat.
Args:
start_dir (str or Path): Starting directory (defaults to current directory)
Returns:
str or None: Full path of directory containing myst.yml, or None if not found
"""
if start_dir is None:
current_dir = Path.cwd()
else:
current_dir = Path(start_dir)
# Keep going up until we reach the filesystem root
while current_dir != current_dir.parent: # Stop at root
myst_file = current_dir / "myst.yml"
if myst_file.exists():
return str(current_dir.resolve())
# Move to parent directory
current_dir = current_dir.parent
return None
with suppress_stdout():
repo_path = Path(find_myst_yml_directories_upwards())
print(repo_path)
data_req_path = repo_path / "binder" / "data_requirement.json"
data_path = repo_path / "data"
dataset_path = data_path / "qmrlab-mooc"
data_dir = dataset_path / "03-T2" / "03-T2"
data_file = "t2_noise_simulation.mat"
#Load either archived or generated plot variables
mat_contents = sio.loadmat(data_dir / data_file)
# Get the signals and parameters from Matlab
# Get matlab signals
signal_SNR10 = mat_contents['signal_SNR10'][0]
signal_SNR50 = mat_contents['signal_SNR50'][0]
signal_SNR90 = mat_contents['signal_SNR90'][0]
signal_SNR130 = mat_contents['signal_SNR130'][0]
# Get T2 constants from matlab simulation
T2_SNR10 = mat_contents['T2_SNR10'][0]
T2_SNR50 = mat_contents['T2_SNR50'][0]
T2_SNR90 = mat_contents['T2_SNR90'][0]
T2_SNR130 = mat_contents['T2_SNR130'][0]
# TE
params = mat_contents['params'][0]
TE_signals = params['TE'][0][0]
TE = params['TE'][0][0]
# Noisy data
SEdata_SNR10 = np.squeeze(mat_contents['SEdata_SNR10'])
SEdata_SNR50 = np.squeeze(mat_contents['SEdata_SNR50'])
SEdata_SNR90 = np.squeeze(mat_contents['SEdata_SNR90'])
SEdata_SNR130 = np.squeeze(mat_contents['SEdata_SNR130'])
TE_datapoints = np.squeeze(mat_contents['EchoTimes'])
TE_datapoints = np.squeeze(mat_contents['EchoTimes'])
## Plot
import matplotlib.pyplot as plt
import chart_studio.plotly as py
import plotly.graph_objs as go
import numpy as np
from plotly.offline import iplot
config={'showLink': False, 'displayModeBar': False}
# T2 signals with different SNRs
## SNR = 10
SNR10 = go.Scatter(
x = TE_signals,
y = signal_SNR10,
name = f'T<sub>2</sub> Fitting (T<sub>2</sub> = {T2_SNR10})',
text = f'T<sub>2</sub> = {T2_SNR10}',
hoverinfo = 'x+y+text',
line=dict(color='#1f77b4', dash='solid'),
visible = True
)
datapoints_SNR10 = go.Scatter(
x = TE_datapoints,
y = SEdata_SNR10,
name = 'Data points with SNR = 10',
hoverinfo = 'x+y',
mode='markers',
marker=dict(color='red'),
visible=True
)
## SNR = 50
SNR50 = go.Scatter(
x = TE,
y = signal_SNR50,
name = f'T<sub>2</sub> Fitting (T<sub>2</sub> = {T2_SNR50})',
text = f'T<sub>2</sub> = {T2_SNR50}',
hoverinfo = 'x+y+text',
line=dict(color='#1f77b4'),
visible = False
)
datapoints_SNR50 = go.Scatter(
x = TE_datapoints,
y = SEdata_SNR50,
name = 'Data points with SNR = 50',
hoverinfo = 'x+y',
mode='markers',
marker=dict(color='red'),
visible=False
)
## SNR = 90
SNR90 = go.Scatter(
x = TE_signals,
y = signal_SNR90,
name = f'T<sub>2</sub> Fitting (T<sub>2</sub> = {T2_SNR90})',
text = f'T<sub>2</sub> = {T2_SNR90}',
hoverinfo = 'x+y+text',
line=dict(color='#1f77b4'),
visible = False
)
datapoints_SNR90 = go.Scatter(
x = TE_datapoints,
y = SEdata_SNR90,
name = 'Data points with SNR = 90',
hoverinfo = 'x+y',
mode='markers',
marker=dict(color='red'),
visible=False
)
## SNR = 130
SNR130 = go.Scatter(
x = TE_signals,
y = signal_SNR130,
name = f'T<sub>2</sub> Fitting (T<sub>2</sub> = {T2_SNR130})',
text = f'T<sub>2</sub> = {T2_SNR130}',
hoverinfo = 'x+y+text',
line=dict(color='#1f77b4'),
visible = False
)
datapoints_SNR130 = go.Scatter(
x = TE_datapoints,
y = SEdata_SNR130,
name = 'Data points with SNR = 130',
hoverinfo = 'x+y',
mode='markers',
marker=dict(color='red'),
visible=False
)
data = [SNR10, SNR50, SNR90, SNR130, datapoints_SNR10, datapoints_SNR50, datapoints_SNR90, datapoints_SNR130]
layout = go.Layout(
width=600,
height=470,
margin=go.layout.Margin(
l=100,
r=50,
b=130,
t=20,
),
annotations=[
dict(
x=0.2,
y=0.96,
showarrow=False,
text='<b>True value : T<sub>2</sub> = 109 ms </b>',
font=dict(
family='Times New Roman',
size=14,
color = 'black',
),
xref='paper',
yref='paper'
),
dict(
x=0.5004254919715793,
y=-0.175,
showarrow=False,
text='Echo Time – TE (ms)',
font=dict(
family='Times New Roman',
size=22
),
xref='paper',
yref='paper'
),
dict(
x=-0.15,
y=0.50,
showarrow=False,
text='Transverse Magnetization (M<sub>xy</sub>)',
font=dict(
family='Times New Roman',
size=22
),
textangle=-90,
xref='paper',
yref='paper'
),
dict(
x=0.15,
y=-0.35,
showarrow=False,
text='SNR:',
font=dict(
family='Times New Roman',
size=22
),
xref='paper',
yref='paper'
),
],
xaxis=dict(
range=[0,300],
showgrid=False,
linecolor='black',
linewidth=2
),
yaxis=dict(
showgrid=False,
linecolor='black',
linewidth=2,
range=[0, 1]
),
legend=dict(
x=0.55,
y=0.97,
traceorder='normal',
font=dict(
family='Times New Roman',
size=12,
color='#000'
),
bordercolor='#000000',
borderwidth=2
),
updatemenus=[
dict(
buttons=list([
# Display T2 decay curve and data points with SNR = 10
dict(
args=[{'visible': [True, False, False, False, True, False, False, False]}],
label='10',
method='update'
),
# Display T2 decay curve and data points with SNR = 50
dict(
args=[{'visible': [False, True, False, False, False, True, False, False]}],
label='50',
method='update'
),
# Display T2 decay curve and data points with SNR = 90
dict(
args=[{'visible': [False, False, True, False, False, False, True, False]}],
label='90',
method='update'
),
# Display T2 decay curve and data points with SNR = 130
dict(
args=[{'visible': [False, False, False, True, False, False, False, True]}],
label='130',
method='update'
),
]),
direction='up',
pad={'r': 10, 't': 10},
showactive=True,
x=0.28,
xanchor='left',
y=-0.22,
yanchor='top',
font=dict(
family='Times New Roman',
size=12,
color='#000'
)
),
]
)
fig = dict(data=data, layout=layout)
iplot(fig, filename = 'ir_fig_2.html', config = config)Loading...