Added vmin and vmax arguments to viz functions

qim3d/viz/cc.py

@@ -12,6 +12,9 @@ def plot_cc(
     overlay=None,
     crop=False,
     show=True,
+    cmap:str = 'viridis',
+    vmin:float = None,
+    vmax:float = None,
     **kwargs,
 ) -> list[plt.Figure]:
     """
@@ -24,6 +27,9 @@ def plot_cc(
         overlay (optional): Overlay image. Defaults to None.
         crop (bool, optional): Whether to crop the image to the cc. Defaults to False.
         show (bool, optional): Whether to show the figure. Defaults to True.
+        cmap (str, optional): Specifies the color map for the image. Defaults to "viridis".
+        vmin (float, optional): Together with vmax define the data range the colormap covers. By default colormap covers the full range. Defaults to None.
+        vmax (float, optional): Together with vmin define the data range the colormap covers. By default colormap covers the full range. Defaults to None
         **kwargs: Additional keyword arguments to pass to `qim3d.viz.slices`.
 
     Returns:
@@ -66,11 +72,10 @@ def plot_cc(
                 overlay_crop = overlay[bb]
                 # use cc as mask for overlay_crop, where all values in cc set to 0 should be masked out, cc contains integers
                 overlay_crop = np.where(cc == 0, 0, overlay_crop)
-                fig = qim3d.viz.slices(overlay_crop, show=show, **kwargs)
             else:
                 cc = connected_components.get_cc(component, crop=False)
                 overlay_crop = np.where(cc == 0, 0, overlay)
-                fig = qim3d.viz.slices(overlay_crop, show=show, **kwargs)
+            fig = qim3d.viz.slices(overlay_crop, show=show, cmap = cmap, vmin = vmin, vmax = vmax, **kwargs)
         else:
             # assigns discrete color map to each connected component if not given
             if "cmap" not in kwargs:

qim3d/viz/explore.py

@@ -20,6 +20,8 @@ def slices(
     n_slices: int = 5,
     max_cols: int = 5,
     cmap: str = "viridis",
+    vmin:float = None,
+    vmax:float = None,
     img_height: int = 2,
     img_width: int = 2,
     show: bool = False,
@@ -41,6 +43,8 @@ def slices(
         n_slices (int, optional): Defines how many slices the user wants to be displayed. Defaults to 5.
         max_cols (int, optional): The maximum number of columns to be plotted. Defaults to 5.
         cmap (str, optional): Specifies the color map for the image. Defaults to "viridis".
+        vmin (float, optional): Together with vmax define the data range the colormap covers. By default colormap covers the full range. Defaults to None.
+        vmax (float, optional): Together with vmin define the data range the colormap covers. By default colormap covers the full range. Defaults to None
         img_height (int, optional): Height of the figure.
         img_width (int, optional): Width of the figure.
         show (bool, optional): If True, displays the plot (i.e. calls plt.show()). Defaults to False.
@@ -136,8 +140,13 @@ def slices(
             slice_idx = i * max_cols + j
             try:
                 slice_img = vol.take(slice_idxs[slice_idx], axis=axis)
+
+                # If vmin is higher than the highest value in the image ValueError is raised
+                # We don't want to override the values because next slices might be okay
+                new_vmin = None if (isinstance(vmin, (float, int)) and vmin > np.max(slice_img)) else vmin
+                new_vmax = None if (isinstance(vmax, (float, int)) and vmax < np.min(slice_img)) else vmax
                 ax.imshow(
-                    slice_img, cmap=cmap, interpolation=interpolation, **imshow_kwargs
+                    slice_img, cmap=cmap, interpolation=interpolation,vmin = new_vmin, vmax = new_vmax, **imshow_kwargs
                 )
 
                 if show_position:
@@ -200,6 +209,8 @@ def slicer(
     vol: np.ndarray,
     axis: int = 0,
     cmap: str = "viridis",
+    vmin:float = None,
+    vmax:float = None,
     img_height: int = 3,
     img_width: int = 3,
     show_position: bool = False,
@@ -213,6 +224,8 @@ def slicer(
         vol (np.ndarray): The 3D volume to be sliced.
         axis (int, optional): Specifies the axis, or dimension, along which to slice. Defaults to 0.
         cmap (str, optional): Specifies the color map for the image. Defaults to "viridis".
+        vmin (float, optional): Together with vmax define the data range the colormap covers. By default colormap covers the full range. Defaults to None.
+        vmax (float, optional): Together with vmin define the data range the colormap covers. By default colormap covers the full range. Defaults to None
         img_height (int, optional): Height of the figure. Defaults to 3.
         img_width (int, optional): Width of the figure. Defaults to 3.
         show_position (bool, optional): If True, displays the position of the slices. Defaults to False.
@@ -241,6 +254,8 @@ def slicer(
             vol,
             axis=axis,
             cmap=cmap,
+            vmin = vmin,
+            vmax = vmax,
             img_height=img_height,
             img_width=img_width,
             show_position=show_position,
@@ -268,6 +283,8 @@ def slicer(
 def orthogonal(
     vol: np.ndarray,
     cmap: str = "viridis",
+    vmin:float = None,
+    vmax:float = None,
     img_height: int = 3,
     img_width: int = 3,
     show_position: bool = False,
@@ -279,6 +296,8 @@ def orthogonal(
     Args:
         vol (np.ndarray): The 3D volume to be sliced.
         cmap (str, optional): Specifies the color map for the image. Defaults to "viridis".
+        vmin (float, optional): Together with vmax define the data range the colormap covers. By default colormap covers the full range. Defaults to None.
+        vmax (float, optional): Together with vmin define the data range the colormap covers. By default colormap covers the full range. Defaults to None
         img_height (int, optional): Height of the figure.
         img_width (int, optional): Width of the figure.
         show_position (bool, optional): If True, displays the position of the slices. Defaults to False.
@@ -301,34 +320,22 @@ def orthogonal(
         img_height = img_size
         img_width = img_size
 
-    z_slicer = slicer(
-        vol,
-        axis=0,
-        cmap=cmap,
-        img_height=img_height,
-        img_width=img_width,
-        show_position=show_position,
-        interpolation=interpolation,
-    )
-    y_slicer = slicer(
+    get_slicer_for_axis = lambda axis: slicer(
         vol,
-        axis=1,
-        cmap=cmap,
-        img_height=img_height,
-        img_width=img_width,
-        show_position=show_position,
-        interpolation=interpolation,
-    )
-    x_slicer = slicer(
-        vol,
-        axis=2,
+        axis = axis,
         cmap = cmap,
+        vmin = vmin,
+        vmax = vmax,
         img_height = img_height,
         img_width = img_width,
         show_position = show_position,
         interpolation = interpolation,
         )
 
+    z_slicer = get_slicer_for_axis(axis = 0)
+    y_slicer = get_slicer_for_axis(axis = 1)
+    x_slicer = get_slicer_for_axis(axis = 2)
+
     z_slicer.children[0].description = "Z"
     y_slicer.children[0].description = "Y"
     x_slicer.children[0].description = "X"
@@ -336,7 +343,7 @@ def orthogonal(
     return widgets.HBox([z_slicer, y_slicer, x_slicer])
 
 
-def interactive_fade_mask(vol: np.ndarray, axis: int = 0):
+def interactive_fade_mask(vol: np.ndarray, axis: int = 0,cmap:str = 'viridis', vmin:float = None, vmax:float = None):
     """Interactive widget for visualizing the effect of edge fading on a 3D volume.
 
     This can be used to select the best parameters before applying the mask.
@@ -344,6 +351,9 @@ def interactive_fade_mask(vol: np.ndarray, axis: int = 0):
     Args:
         vol (np.ndarray): The volume to apply edge fading to.
         axis (int, optional): The axis along which to apply the fading. Defaults to 0.
+        cmap (str, optional): Specifies the color map for the image. Defaults to "viridis".
+        vmin (float, optional): Together with vmax define the data range the colormap covers. By default colormap covers the full range. Defaults to None.
+        vmax (float, optional): Together with vmin define the data range the colormap covers. By default colormap covers the full range. Defaults to None
 
     Example:
         ```python
@@ -359,7 +369,13 @@ def interactive_fade_mask(vol: np.ndarray, axis: int = 0):
     def _slicer(position, decay_rate, ratio, geometry, invert):
         fig, axes = plt.subplots(1, 3, figsize=(9, 3))
 
-        axes[0].imshow(vol[position, :, :], cmap="viridis")
+        slice_img = vol[position, :, :]
+        # If vmin is higher than the highest value in the image ValueError is raised
+        # We don't want to override the values because next slices might be okay
+        new_vmin = None if (isinstance(vmin, (float, int)) and vmin > np.max(slice_img)) else vmin
+        new_vmax = None if (isinstance(vmax, (float, int)) and vmax < np.min(slice_img)) else vmax
+
+        axes[0].imshow(slice_img, cmap=cmap, vmin = new_vmin, vmax = new_vmax)
         axes[0].set_title("Original")
         axes[0].axis("off")
 
@@ -371,7 +387,7 @@ def interactive_fade_mask(vol: np.ndarray, axis: int = 0):
             axis=axis,
             invert=invert,
         )
-        axes[1].imshow(mask[position, :, :], cmap="viridis")
+        axes[1].imshow(mask[position, :, :], cmap=cmap)
         axes[1].set_title("Mask")
         axes[1].axis("off")
 
@@ -383,15 +399,20 @@ def interactive_fade_mask(vol: np.ndarray, axis: int = 0):
             axis=axis,
             invert=invert,
         )
-        axes[2].imshow(masked_vol[position, :, :], cmap="viridis")
+        # If vmin is higher than the highest value in the image ValueError is raised
+        # We don't want to override the values because next slices might be okay
+        slice_img = masked_vol[position, :, :]
+        new_vmin = None if (isinstance(vmin, (float, int)) and vmin > np.max(slice_img)) else vmin
+        new_vmax = None if (isinstance(vmax, (float, int)) and vmax < np.min(slice_img)) else vmax
+        axes[2].imshow(slice_img, cmap=cmap, vmin = new_vmin, vmax = new_vmax)
         axes[2].set_title("Masked")
         axes[2].axis("off")
 
         return fig
 
     shape_dropdown = widgets.Dropdown(
-        options=["sphere", "cilinder"],
-        value="sphere",  # default value
+        options=["spherical", "cylindrical"],
+        value="spherical",  # default value
         description="Geometry",
     )
 

qim3d/viz/k3d.py

@@ -14,13 +14,13 @@ from qim3d.utils.misc import downscale_img, scale_to_float16
 
 def vol(
     img,
-    vmin=None,
-    vmax=None,
     aspectmode="data",
     show=True,
     save=False,
     grid_visible=False,
     cmap=None,
+    vmin=None,
+    vmax=None,
     samples="auto",
     max_voxels=512**3,
     data_type="scaled_float16",
@@ -41,8 +41,12 @@ def vol(
             file will be saved. Defaults to False.
         grid_visible (bool, optional): If True, the grid is visible in the plot. Defaults to False.
         cmap (list, optional): The color map to be used for the volume rendering. Defaults to None.
+        vmin (float, optional): Together with vmax defines the data range the colormap covers. By default colormap covers the full range. Defaults to None.
+        vmax (float, optional): Together with vmin defines the data range the colormap covers. By default colormap covers the full range. Defaults to None
         samples (int, optional): The number of samples to be used for the volume rendering in k3d. Defaults to 512.
             Lower values will render faster but with lower quality.
+        max_voxels (int, optional): Defaults to 512^3.
+        data_type (str, optional): Default to 'scaled_float16'.
         **kwargs: Additional keyword arguments to be passed to the `k3d.plot` function.
 
     Returns:

qim3d/viz/structure_tensor.py

@@ -18,6 +18,9 @@ def vectors(
     volume: np.ndarray,
     vec: np.ndarray,
     axis: int = 0,
+    volume_cmap:str = 'grey',
+    vmin:float = None,
+    vmax:float = None,
     slice_idx: Optional[Union[int, float]] = None,
     grid_size: int = 10,
     interactive: bool = True,
@@ -31,6 +34,9 @@ def vectors(
         volume (np.ndarray): The 3D volume to be sliced.
         vec (np.ndarray): The eigenvectors of the structure tensor.
         axis (int, optional): The axis along which to visualize the orientation. Defaults to 0.
+        volume_cmap (str, optional): Defines colormap for display of the volume
+        vmin (float, optional): Together with vmax define the data range the colormap covers. By default colormap covers the full range. Defaults to None.
+        vmax (float, optional): Together with vmin define the data range the colormap covers. By default colormap covers the full range. Defaults to None
         slice_idx (int or float, optional): The initial slice to be visualized. The slice index
             can afterwards be changed. If value is an integer, it will be the index of the slice
             to be visualized. If value is a float between 0 and 1, it will be multiplied by the
@@ -169,7 +175,7 @@ def vectors(
             angles="xy",
         )
 
-        ax[0].imshow(data_slice, cmap=plt.cm.gray)
+        ax[0].imshow(data_slice, cmap = volume_cmap, vmin = vmin, vmax = vmax)
         ax[0].set_title(
             f"Orientation vectors (slice {slice_idx})"
             if not interactive