diff --git a/_images/index_28_0.png b/_images/index_28_0.png deleted file mode 100644 index d3c9f75..0000000 Binary files a/_images/index_28_0.png and /dev/null differ diff --git a/_images/index_44_0.png b/_images/index_44_0.png deleted file mode 100644 index bd2d6fd..0000000 Binary files a/_images/index_44_0.png and /dev/null differ diff --git a/_images/index_50_0.png b/_images/index_48_0.png similarity index 100% rename from _images/index_50_0.png rename to _images/index_48_0.png diff --git a/index.html b/index.html index 85c0f6b..a67b841 100644 --- a/index.html +++ b/index.html @@ -490,7 +490,7 @@

5     |     Process anat/T2starw (GRE) +
# Make figure of CSF/SC signal ratio from T2starw scan
 
@@ -535,12 +535,12 @@ 
5     |     Process anat/T2starw (GRE)data_stats = []
 
 # Data storage for Plotly
-data_plotly = {}
+t2_data_plotly = {}
 
 # Iterate over each subject and create a subplot
 for i, subject in enumerate(subjects):
     ax = axes[i]
-    data_plotly[subject]={}
+    t2_data_plotly[subject]={}
     for shim_mode in shim_modes:
         # Initialize list to collect data for this shim method
         method_data = []
@@ -571,7 +571,7 @@ 
5     |     Process anat/T2starw (GRE)# If there's data for this shim method, plot it and compute stats
         if method_data:
-            data_plotly[subject][shim_mode]=method_data
+            t2_data_plotly[subject][shim_mode]=method_data
 
             # Plotting each file's data separately
             for resampled_data in method_data:
@@ -583,7 +583,7 @@ 
5     |     Process anat/T2starw (GRE)sd_data = np.std(data_sc_csf_ratio)
             data_stats.append([subject, shim_mode, mean_data, sd_data])
         else:
-            data_plotly[subject][shim_mode]=None
+            t2_data_plotly[subject][shim_mode]=None
 
     # Set x-ticks and labels for the bottom subplot
     if i == n_rows - 1:  # Check if it's the last subplot
@@ -614,207 +614,6 @@ 
5     |     Process anat/T2starw (GRE)
-_images/index_28_0.png
-
-
-
-
-
# PYTHON CODE
-# Module imports
-
-# Base python
-import os
-from os import path
-from pathlib import Path
-
-# Graphical
-
-import plotly.graph_objs as go
-from IPython.display import display, HTML
-from plotly import __version__
-from plotly.offline import init_notebook_mode, iplot, plot
-config={
-    'showLink': False,
-    'displayModeBar': False,
-    'toImageButtonOptions': {
-                'format': 'png', # one of png, svg, jpeg, webp
-                'filename': 'custom_image',
-                'height': 2500,
-                'width': 500,
-                'scale': 2 # Multiply title/legend/axis/canvas sizes by this factor
-            }
-    }
-
-init_notebook_mode(connected=True)
-
-from plotly.subplots import make_subplots
-import plotly.graph_objects as go
-
-import seaborn as sns
-
-# Set the color palette
-pal=sns.color_palette("Set2")
-
-# Imports
-import warnings
-warnings.filterwarnings("ignore")
-
-## Setup for plots
-fig = make_subplots(rows=5, cols=1, vertical_spacing = 0.05,
-                    subplot_titles=(
-    'sub-01',
-    'sub-02',
-    'sub-03',
-    'sub-04',
-    'sub-05'))
-
-datasets={}
-data = []
-legend_bool = True
-for subject in subjects:
-    index = 0
-    datasets[subject]={}
-    for shim_mode in shim_modes:
-        datasets[subject][shim_mode]={}
-        data=go.Line(
-            x=x_grid,
-            y=data_plotly[subject][shim_mode][0],
-            name=shim_mode,
-            legendgroup=shim_mode,
-            line=dict(color='rgb'+str(pal[index])),
-            showlegend=legend_bool
-            )
-        
-        datasets[subject][shim_mode]=data
-        index += 1
-    legend_bool=False
-    
-
-index = 1
-# For z-ordering   
-for subject in subjects:
-    for shim_mode in shim_modes:
-        fig.add_trace(
-            datasets[subject][shim_mode],
-            row=index, col=1
-        )
-    index+=1
-
-
-index = 1
-for subject in subjects:
-    fig.update_xaxes(
-        type="linear",
-        autorange=True,
-        title='<b>Vertebral Levels</b>',
-        showgrid=True,
-        gridcolor='rgb(169,169,169)',
-        tickvals=label_positions,
-        ticktext=vertebral_levels,
-        title_font_family="Times New Roman",
-        title_font_size = 20,
-        linecolor='black',
-        linewidth=2,
-        row=index, col=1
-        )
-    fig.update_yaxes(
-        type="linear",
-        title={
-            'text':'<b>CSF/Cord T<sub>2</sub><sup>*</sup>w signal ratio</b>',
-            'standoff':0
-            },
-        showgrid=True,
-        gridcolor='rgb(169,169,169)',
-        title_font_family="Times New Roman",
-        title_font_size = 20,
-        linecolor='black',
-        linewidth=2,
-        row=index, col=1
-        )
-    index+=1
-
-fig.update_layout(height=2000, width=500)
-fig.update_layout(legend=dict(
-    yanchor="top",
-    y=1.0,
-    xanchor="left",
-    x=0.01),
-    legend_tracegroupgap=0,
-    
-)
-
-
-#iplot(fig, filename = 'figure4a', config = config)
-plot(fig, filename = 'figure1a.html', config = config)
-display(HTML('figure1a.html'))
-
-
-
-
-
-
/opt/hostedtoolcache/Python/3.8.18/x64/lib/python3.8/site-packages/plotly/graph_objs/_deprecations.py:378: DeprecationWarning:
-
-plotly.graph_objs.Line is deprecated.
-Please replace it with one of the following more specific types
-  - plotly.graph_objs.scatter.Line
-  - plotly.graph_objs.layout.shape.Line
-  - etc.
-
-
-
- - -
-
- -
-
-
-
-
label_positions
-
-
-
-
-
array([0.07088123, 0.21264368, 0.3467433 , 0.46934866, 0.59386973,
-       0.74137931, 0.91187739])
-
-
-
-
-
-
-
vertebral_levels
-
-
-
-
-
['C3', 'C4', 'C5', 'C6', 'C7', 'T1', 'T2']
-
-
-

Perform statistics

@@ -1002,7 +801,7 @@

6     |     Process fmap/TFL (flip angle maps)

Make figure of B1+ values along the spinal cord across shim methods

-
+
# Go back to root data folder
 os.chdir(os.path.join(path_data))
@@ -1045,12 +844,17 @@ 
6     |     Process fmap/TFL (flip angle maps)# Data storage for statistics
 data_stats = []
 
+# Data storage for Plotly
+b1_data_plotly = {}
+
 # Iterate over each subject and create a subplot
 for i, subject in enumerate(subjects):
+    
     ax = axes[i]
     
     os.chdir(os.path.join(path_data, subject, "fmap"))
-
+    b1_data_plotly[subject]={}
+    
     for shim_mode in shim_modes:
         # Initialize list to collect data for this shim method
         method_data = []
@@ -1075,12 +879,16 @@ 
6     |     Process fmap/TFL (flip angle maps)if method_data:
             # Plotting each file's data separately
             for resampled_data in method_data:
+                b1_data_plotly[subject][shim_mode]=resampled_data
                 ax.plot(x_grid, resampled_data, label=f"{shim_mode}", linewidth=line_width)
 
             # Compute stats on the non-resampled data (to avoid interpolation errors)
             mean_data = np.mean(wa_data)
             sd_data = np.std(wa_data)
             data_stats.append([subject, shim_mode, mean_data, sd_data])
+        else:
+            b1_data_plotly[subject][shim_mode]=None
+
 
     # Set x-ticks and labels for the bottom subplot
     if i == n_rows - 1:  # Check if it's the last subplot
@@ -1111,9 +919,294 @@ 
6     |     Process fmap/TFL (flip angle maps)
+
+
+
+
# PYTHON CODE
+# Module imports
+
+# Base python
+import os
+from os import path
+from pathlib import Path
+
+# Graphical
+
+import plotly.graph_objs as go
+from IPython.display import display, HTML
+from plotly import __version__
+from plotly.offline import init_notebook_mode, iplot, plot
+config={
+    'showLink': False,
+    'displayModeBar': False,
+    'toImageButtonOptions': {
+                'format': 'png', # one of png, svg, jpeg, webp
+                'filename': 'custom_image',
+                'height': 2500,
+                'width': 500,
+                'scale': 2 # Multiply title/legend/axis/canvas sizes by this factor
+            }
+    }
+
+init_notebook_mode(connected=True)
+
+from plotly.subplots import make_subplots
+import plotly.graph_objects as go
+
+import seaborn as sns
+
+# Set the color palette
+pal=sns.color_palette()
+
+# Imports
+import warnings
+warnings.filterwarnings("ignore")
+
+## Setup for plots
+fig = make_subplots(rows=5, cols=2, vertical_spacing = 0.025,
+                    subplot_titles=(
+    '<b>sub-01</b>',
+    '<b>sub-01</b>',
+    '<b>sub-02</b>',
+    '<b>sub-02</b>',
+    '<b>sub-03</b>',
+    '<b>sub-03</b>',
+    '<b>sub-04</b>',
+    '<b>sub-04</b>',
+    '<b>sub-05</b>',
+    '<b>sub-05</b>',))
+
+t2_datasets={}
+b1_datasets={}
+
+t2_data = []
+b1_data = []
+
+legend_bool = True
+for subject in subjects:
+    index = 0
+    t2_datasets[subject]={}
+    b1_datasets[subject]={}
+
+    for shim_mode in shim_modes:
+        t2_datasets[subject][shim_mode]={}
+        b1_datasets[subject][shim_mode]={}
+
+        t2_data=go.Line(
+            x=x_grid,
+            y=t2_data_plotly[subject][shim_mode][0],
+            name=shim_mode,
+            legendgroup=shim_mode,
+            line=dict(color='rgb'+str(pal[index]), width=3),
+            showlegend=False
+            )
+
+        b1_data=go.Line(
+            x=x_grid,
+            y=b1_data_plotly[subject][shim_mode],
+            name=shim_mode,
+            legendgroup=shim_mode,
+            line=dict(color='rgb'+str(pal[index]), width=3),
+            showlegend=legend_bool
+            )        
+
+        
+        t2_datasets[subject][shim_mode]=t2_data
+        b1_datasets[subject][shim_mode]=b1_data
+
+        index += 1
+    legend_bool=False
+    
+
+index = 1
+# For z-ordering   
+for subject in subjects:
+    for shim_mode in shim_modes:
+        fig.add_trace(
+            t2_datasets[subject][shim_mode],
+            row=index, col=1
+        )
+        fig.add_trace(
+            b1_datasets[subject][shim_mode],
+            row=index, col=2
+        )
+    index+=1
+
+
+index = 1
+for subject in subjects:
+    if index == 5:
+        x_title = '<b>Vertebral Levels</b>'
+        showticklabels=True
+    else:
+        x_title = None
+        showticklabels=False
+
+    fig.update_xaxes(
+        type="linear",
+        autorange=True,
+        title=x_title,
+        showgrid=True,
+        gridcolor='rgb(169,169,169)',
+        tickvals=label_positions,
+        ticktext=vertebral_levels,
+        showticklabels=showticklabels,
+        title_font_family="Times New Roman",
+        title_font_size = 20,
+        linecolor='black',
+        linewidth=2,
+        tickfont=dict(
+            family='Times New Roman',
+            size=16,
+        ),
+        row=index, col=1
+        )
+    if index == 1:
+        fig.update_yaxes(
+            type="linear",
+            title={
+                'text':'<b>CSF/Cord T<sub>2</sub><sup>*</sup>w signal ratio</b>',
+                'standoff':0
+                },
+            range=[1.05, 1.4],
+            showgrid=True,
+            gridcolor='rgb(169,169,169)',
+            title_font_family="Times New Roman",
+            title_font_size = 20,
+            linecolor='black',
+            linewidth=2,
+            tickfont=dict(
+                family='Times New Roman',
+                size=16,
+            ),
+            row=index, col=1
+            )
+    else:
+        fig.update_yaxes(
+            type="linear",
+            title={
+                'text':'<b>CSF/Cord T<sub>2</sub><sup>*</sup>w signal ratio</b>',
+                'standoff':0
+                },
+            showgrid=True,
+            gridcolor='rgb(169,169,169)',
+            title_font_family="Times New Roman",
+            title_font_size = 20,
+            linecolor='black',
+            linewidth=2,
+            tickfont=dict(
+                family='Times New Roman',
+                size=16,
+            ),
+            row=index, col=1
+            )
+
+    fig.update_xaxes(
+        type="linear",
+        autorange=True,
+        title=x_title,
+        showgrid=True,
+        gridcolor='rgb(169,169,169)',
+        tickvals=label_positions,
+        ticktext=vertebral_levels,
+        showticklabels=showticklabels,
+        title_font_family="Times New Roman",
+        title_font_size = 20,
+        linecolor='black',
+        linewidth=2,
+        tickfont=dict(
+            family='Times New Roman',
+            size=16,
+        ),
+        row=index, col=2
+        )
+    fig.update_yaxes(
+        type="linear",
+        title={
+            'text':'<b>B<sub>1</sub><sup>+</sup> efficiency [nT/V]</b>',
+            'standoff':0
+            },
+        showgrid=True,
+        gridcolor='rgb(169,169,169)',
+        title_font_family="Times New Roman",
+        title_font_size = 20,
+        linecolor='black',
+        linewidth=2,
+        tickfont=dict(
+            family='Times New Roman',
+            size=16,
+        ),
+        row=index, col=2
+        )
+
+    index+=1
+
+fig.update_layout(height=1800, width=900)
+fig.update_layout(legend=dict(
+    yanchor="top",
+    y=0.999,
+    xanchor="left",
+    x=0.01,
+    font=dict(
+        family='Times New Roman',
+        size=12
+    ),
+    bordercolor="Black",
+    borderwidth=1.5
+    ),
+    legend_tracegroupgap=0,
+    paper_bgcolor='rgb(255, 255, 255)',
+    plot_bgcolor='rgb(255, 255, 255)',
+
+)
+
+fig.update_annotations(font_size=22)
+
+#iplot(fig, filename = 'figure4a', config = config)
+plot(fig, filename = 'figure1.html', config = config)
+display(HTML('figure1.html'))
+
+
+
-_images/index_44_0.png +
+
/opt/hostedtoolcache/Python/3.8.18/x64/lib/python3.8/site-packages/plotly/graph_objs/_deprecations.py:378: DeprecationWarning:
+
+plotly.graph_objs.Line is deprecated.
+Please replace it with one of the following more specific types
+  - plotly.graph_objs.scatter.Line
+  - plotly.graph_objs.layout.shape.Line
+  - etc.
+
+
+ + +
+
+ +

Perform statistics

@@ -1340,7 +1433,7 @@

6     |     Process fmap/TFL (flip angle maps)

-_images/index_50_0.png +_images/index_48_0.png