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visualizer docs
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@aelefebv
aelefebv committed Oct 3, 2024
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120 changes: 120 additions & 0 deletions nellie_napari/nellie_visualizer.py
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class NellieVisualizer(QWidget):
"""
The NellieVisualizer class provides an interface for visualizing different stages of the Nellie pipeline, such as raw images,
preprocessed images, segmentation labels, mocap markers, and reassigned labels. It also enables track visualization for specific
labels and all frame labels using napari.
Attributes
----------
nellie : object
Reference to the Nellie instance managing the pipeline.
viewer : napari.viewer.Viewer
Reference to the napari viewer instance.
scale : tuple of floats
Scaling factors for visualizing the images, based on the resolution of the image dimensions.
im_memmap : ndarray
Memory-mapped array for the raw image.
raw_layer : ImageLayer
The napari image layer for displaying the raw image.
im_branch_label_reassigned_layer : LabelsLayer
The napari labels layer for displaying reassigned branch labels.
im_branch_label_reassigned : ndarray
Memory-mapped array for reassigned branch labels.
im_obj_label_reassigned_layer : LabelsLayer
The napari labels layer for displaying reassigned object labels.
im_obj_label_reassigned : ndarray
Memory-mapped array for reassigned object labels.
im_marker_layer : ImageLayer
The napari image layer for displaying mocap markers.
im_marker : ndarray
Memory-mapped array for mocap marker images.
im_skel_relabelled_layer : LabelsLayer
The napari labels layer for displaying skeleton relabeled images.
im_instance_label_layer : LabelsLayer
The napari labels layer for displaying instance labels.
frangi_layer : ImageLayer
The napari image layer for displaying preprocessed images (Frangi-filtered).
im_skel_relabelled : ndarray
Memory-mapped array for skeleton relabeled images.
im_instance_label : ndarray
Memory-mapped array for instance labels.
im_frangi : ndarray
Memory-mapped array for the preprocessed (Frangi-filtered) images.
initialized : bool
Flag indicating whether the visualizer has been initialized.
Methods
-------
set_ui()
Initializes and sets the layout and UI components for the NellieVisualizer.
post_init()
Initializes the visualizer by setting the scale and making the scale bar visible in napari.
check_3d()
Ensures that the napari viewer is in 3D mode if the dataset contains Z-dimension data.
set_scale()
Sets the scale for image display based on the image resolution in Z, Y, and X dimensions.
open_preprocess_image()
Opens and displays the preprocessed (Frangi-filtered) image in the napari viewer.
open_segment_image()
Opens and displays the segmentation labels (skeleton relabeled and instance labels) in the napari viewer.
on_track_selected()
Visualizes the tracks for the currently selected label in the napari viewer.
track_all()
Visualizes tracks for all labels across frames in the napari viewer.
open_mocap_image()
Opens and displays the mocap marker image in the napari viewer.
open_reassign_image()
Opens and displays the reassigned branch and object labels in the napari viewer.
open_raw()
Opens and displays the raw image in the napari viewer.
check_file_existence()
Checks for the existence of files related to different steps of the pipeline, enabling or disabling buttons accordingly.
"""
def __init__(self, napari_viewer: 'napari.viewer.Viewer', nellie, parent=None):
"""
Initializes the NellieVisualizer class, setting up buttons and layout for opening and visualizing images and tracks.
Parameters
----------
napari_viewer : napari.viewer.Viewer
Reference to the napari viewer instance.
nellie : object
Reference to the Nellie instance managing the pipeline.
parent : QWidget, optional
Optional parent widget (default is None).
"""
super().__init__(parent)
self.nellie = nellie
self.viewer = napari_viewer
Expand Down Expand Up @@ -77,6 +160,10 @@ def __init__(self, napari_viewer: 'napari.viewer.Viewer', nellie, parent=None):
self.initialized = False

def set_ui(self):
"""
Initializes and sets the layout and UI components for the NellieVisualizer. It groups the buttons for image
and track visualization into separate sections and arranges them within a vertical layout.
"""
main_layout = QVBoxLayout()

# visualization group
Expand All @@ -101,32 +188,47 @@ def set_ui(self):
self.setLayout(main_layout)

def post_init(self):
"""
Post-initialization method that sets the image scale based on the image resolution and makes the scale bar visible.
"""
self.set_scale()
self.viewer.scale_bar.visible = True
self.viewer.scale_bar.unit = 'um'
self.initialized = True

def check_3d(self):
"""
Ensures that the napari viewer is in 3D mode if the dataset contains Z-dimension data.
"""
if not self.nellie.im_info.no_z and self.viewer.dims.ndim != 3:
# ndimensions should be 3 for viewer
self.viewer.dims.ndim = 3
self.viewer.dims.ndisplay = 3

def set_scale(self):
"""
Sets the scale for image display based on the resolution of the Z, Y, and X dimensions of the image.
"""
dim_res = self.nellie.im_info.dim_res
if self.nellie.im_info.no_z:
self.scale = (dim_res['Y'], dim_res['X'])
else:
self.scale = (dim_res['Z'], dim_res['Y'], dim_res['X'])

def open_preprocess_image(self):
"""
Opens and displays the preprocessed (Frangi-filtered) image in the napari viewer.
"""
self.im_frangi = tifffile.memmap(self.nellie.im_info.pipeline_paths['im_preprocessed'])
self.check_3d()
self.frangi_layer = self.viewer.add_image(self.im_frangi, name='Pre-processed', colormap='turbo', scale=self.scale)
self.frangi_layer.interpolation = 'nearest'
self.viewer.layers.selection.active = self.frangi_layer

def open_segment_image(self):
"""
Opens and displays the segmentation labels (skeleton relabeled and instance labels) in the napari viewer.
"""
self.im_instance_label = tifffile.memmap(self.nellie.im_info.pipeline_paths['im_instance_label'])
self.im_skel_relabelled = tifffile.memmap(self.nellie.im_info.pipeline_paths['im_skel_relabelled'])

Expand All @@ -139,6 +241,9 @@ def open_segment_image(self):
self.viewer.layers.selection.active = self.im_instance_label_layer

def on_track_selected(self):
"""
Visualizes the tracks for the currently selected label in the napari viewer, based on the active image layer.
"""
# if flow_vector_array path does not point to an existing file, return
if not os.path.exists(self.nellie.im_info.pipeline_paths['flow_vector_array']):
return
Expand Down Expand Up @@ -201,6 +306,9 @@ def on_track_selected(self):
self.check_file_existence()

def track_all(self):
"""
Visualizes tracks for all labels across frames in the napari viewer, based on the active image layer.
"""
layer = self.viewer.layers.selection.active
if layer == self.im_instance_label_layer:
label_path = self.nellie.im_info.pipeline_paths['im_instance_label']
Expand Down Expand Up @@ -243,6 +351,9 @@ def track_all(self):
self.check_file_existence()

def open_mocap_image(self):
"""
Opens and displays the mocap marker image in the napari viewer.
"""
self.check_3d()

self.im_marker = tifffile.memmap(self.nellie.im_info.pipeline_paths['im_marker'])
Expand All @@ -252,6 +363,9 @@ def open_mocap_image(self):
self.viewer.layers.selection.active = self.im_marker_layer

def open_reassign_image(self):
"""
Opens and displays the reassigned branch and object labels in the napari viewer.
"""
self.check_3d()

self.im_branch_label_reassigned = tifffile.memmap(self.nellie.im_info.pipeline_paths['im_branch_label_reassigned'])
Expand All @@ -262,6 +376,9 @@ def open_reassign_image(self):
self.viewer.layers.selection.active = self.im_obj_label_reassigned_layer

def open_raw(self):
"""
Opens and displays the raw image in the napari viewer.
"""
self.check_3d()
self.im_memmap = tifffile.memmap(self.nellie.im_info.im_path)
self.raw_layer = self.viewer.add_image(self.im_memmap, name='raw', colormap='gray',
Expand All @@ -271,6 +388,9 @@ def open_raw(self):
self.viewer.layers.selection.active = self.raw_layer

def check_file_existence(self):
"""
Checks for the existence of files related to different steps of the pipeline, enabling or disabling buttons accordingly.
"""
# set all other buttons to disabled first
self.raw_button.setEnabled(False)
self.open_preprocess_button.setEnabled(False)
Expand Down

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