update visualize

bioMONAI/_modidx.py

@@ -112,6 +112,8 @@
                                      'bioMONAI.transforms._process_sz': ('transforms.html#_process_sz', 'bioMONAI/transforms.py')},
             'bioMONAI.visualize': { 'bioMONAI.visualize._fig_bounds': ('visualize.html#_fig_bounds', 'bioMONAI/visualize.py'),
                                     'bioMONAI.visualize.mosaic_image_3d': ('visualize.html#mosaic_image_3d', 'bioMONAI/visualize.py'),
+                                    'bioMONAI.visualize.plot_image': ('visualize.html#plot_image', 'bioMONAI/visualize.py'),
+                                    'bioMONAI.visualize.plot_volume': ('visualize.html#plot_volume', 'bioMONAI/visualize.py'),
                                     'bioMONAI.visualize.show_images_grid': ('visualize.html#show_images_grid', 'bioMONAI/visualize.py'),
                                     'bioMONAI.visualize.show_plane': ('visualize.html#show_plane', 'bioMONAI/visualize.py'),
                                     'bioMONAI.visualize.slice_explorer': ('visualize.html#slice_explorer', 'bioMONAI/visualize.py'),

bioMONAI/visualize.py

@@ -1,14 +1,15 @@
 # AUTOGENERATED! DO NOT EDIT! File to edit: ../nbs/09_visualize.ipynb.
 
 # %% auto 0
-__all__ = ['mosaic_image_3d', 'show_images_grid', 'show_plane', 'visualize_slices', 'slice_explorer']
+__all__ = ['plot_image', 'mosaic_image_3d', 'show_images_grid', 'show_plane', 'visualize_slices', 'slice_explorer', 'plot_volume']
 
 # %% ../nbs/09_visualize.ipynb 3
 import numpy as np
 import matplotlib.pyplot as plt
 from mpl_toolkits.mplot3d.art3d import Poly3DCollection
 import plotly.io as pio
 import plotly.express as px
+import plotly.graph_objects as go
 from skimage import util
 from skimage.data import cells3d
 import torchvision
@@ -19,12 +20,44 @@
 from .io import tiff2torch
 
 # %% ../nbs/09_visualize.ipynb 6
+def plot_image(values):
+    """
+    Plot a 2D image using Matplotlib. The function assumes that 'values' is a 2D array representing an image, typically in grayscale.
+    
+    Parameters:
+        values (numpy.ndarray): A 2D array of pixel values representing the image.
+    
+    Returns:
+        None
+    """
+    # Create a figure with Matplotlib
+    fig = plt.figure()
+
+    # Add an axis to the figure, which will be used for plotting the image
+    ax = fig.add_subplot(111)
+
+    # Display the image using imshow. The np.flipud function is applied to flip the array vertically, 
+    # which is necessary because Matplotlib's default orientation might differ from NumPy's or Plotly's.
+    ax.imshow(np.flipud(values), cmap='gray')
+
+    # Turn off axis numbers and ticks for a cleaner visual appearance of the image
+    ax.axis('off')
+
+    # Display the figure with all defined elements
+    plt.show()
+
+
+# Example usage:
+plot_image(data[35])
+
+
+# %% ../nbs/09_visualize.ipynb 8
 # Utility function for determining figure bounds
 def _fig_bounds(x):
     r = x//8
     return min(15, max(1,r))
 
-# %% ../nbs/09_visualize.ipynb 7
+# %% ../nbs/09_visualize.ipynb 9
 def mosaic_image_3d(t: (np.ndarray, torchTensor),
                   axis: int = 0,
                   figsize: tuple = (15,15),
@@ -78,7 +111,7 @@ def mosaic_image_3d(t: (np.ndarray, torchTensor),
     plt.imshow(grid[0,:,:], cmap=cmap, alpha=alpha)
     plt.axis('off')
 
-# %% ../nbs/09_visualize.ipynb 8
+# %% ../nbs/09_visualize.ipynb 10
 @delegates(plt.Axes.imshow, keep=True, but=['shape', 'imlim'])
 def show_images_grid(images, ax=None, ncols=10, figsize=None, title=None, spacing=0.02, max_slices=3, ctx=None, **kwargs):
     """
@@ -151,7 +184,7 @@ def show_images_grid(images, ax=None, ncols=10, figsize=None, title=None, spacin
 
     return ax
 
-# %% ../nbs/09_visualize.ipynb 12
+# %% ../nbs/09_visualize.ipynb 14
 def show_plane(ax, plane, cmap="gray", title=None, lines=None, linestyle='--', linecolor='white'):
     """
     Display a slice of the image tensor on a given axis with optional dashed lines.
@@ -175,7 +208,7 @@ def show_plane(ax, plane, cmap="gray", title=None, lines=None, linestyle='--', l
         ax.axvline(lines[1], color=linecolor, linestyle=linestyle)
 
 
-# %% ../nbs/09_visualize.ipynb 13
+# %% ../nbs/09_visualize.ipynb 15
 def visualize_slices(data, planes=None, showlines=True, **kwargs):
     """
     Visualize slices of a 3D image tensor along its planes, rows, and columns.
@@ -210,8 +243,8 @@ def visualize_slices(data, planes=None, showlines=True, **kwargs):
     plt.show()
 
 
-# %% ../nbs/09_visualize.ipynb 16
-def slice_explorer(data, width=500, height=500, **kwargs):
+# %% ../nbs/09_visualize.ipynb 18
+def slice_explorer(data, **kwargs):
     """
     Visualizes the provided data using Plotly's interactive imshow function with animation support.
     
@@ -221,19 +254,59 @@ def slice_explorer(data, width=500, height=500, **kwargs):
     Returns:
         None: Displays the plot directly.
     """
-    fig = px.imshow(data, animation_frame=0, binary_string=True)
-
+    if len(data.shape) == 4:
+        fig = px.imshow(data, animation_frame=0, binary_string=True, labels=dict(animation_frame="slice", facet_col='channel'), facet_col=1)
+    elif len(data.shape) == 3:
+        fig = px.imshow(data, animation_frame=0, binary_string=True, labels=dict(animation_frame="slice"))
+    else:
+        raise ValueError("Input must be a 3D or 4D array.")
+
     # Remove tick labels from axes
     fig.update_xaxes(showticklabels=False)
     fig.update_yaxes(showticklabels=False)
 
     # Set custom size for the plot
-    fig.update_layout(autosize=False, width=width, height=height, **kwargs)
-
-    # Drop animation buttons as they are not supported in this specific configuration
-    fig['layout'].pop('updatemenus')
-
+    fig.update_layout(**kwargs, title_x=0.5)
+
     # Display the plot using Plotly's show function
     pio.show(fig)
 
 
+
+# %% ../nbs/09_visualize.ipynb 21
+def plot_volume(values, opacity=0.1, min=0.1, max=0.8, surface_count=5, width=800, height=600):
+    """
+    Plot a 3D volume using Plotly. The function assumes that 'values' is a 3D array representing the volume data.
+    
+    Parameters:
+        values (numpy.ndarray): A 3D array of pixel values representing the volume.
+        opacity (float, optional): Opacity level for the surfaces in the volume plot. Defaults to 0.1.
+        min (float, optional): Minimum threshold multiplier for the visualization. Defaults to 0.1.
+        max (float, optional): Maximum threshold multiplier for the visualization. Defaults to 0.8.
+        surface_count (int, optional): Number of surfaces to display in the volume plot. Defaults to 5.
+        width (int, optional): Width of the plotted figure. Defaults to 800.
+        height (int, optional): Height of the plotted figure. Defaults to 600.
+    
+    Returns:
+        None
+    """
+    # Generate coordinates based on the shape of the values array
+    X, Y, Z = np.mgrid[0:values.shape[0], 0:values.shape[1], 0:values.shape[2]]
+
+    # Create a Plotly figure with volume data
+    fig = go.Figure(data=go.Volume(
+        x=X.flatten(),
+        y=Y.flatten(),
+        z=Z.flatten(),
+        value=values.flatten(),
+        isomin=np.min(values) * min, # Adjust the minimum threshold for visualization
+        isomax=np.max(values) * max, # Adjust the maximum threshold for visualization
+        opacity=opacity, # needs to be small to see through all surfaces
+        surface_count=surface_count, # needs to be a large number for good volume rendering
+    ))
+
+    # Update layout with specific width and height
+    fig.update_layout(width=width, height=height) # Adjust these values as needed
+
+    # Display the figure in a new window
+    fig.show()