From a11f6b3d5be5c88f2d1410d021d957b607b94ab4 Mon Sep 17 00:00:00 2001
From: Felipe <fima@dtu.dk>
Date: Mon, 24 Feb 2025 15:18:42 +0100
Subject: [PATCH] moving code to new branch
---
qim3d/viz/__init__.py | 6 +-
qim3d/viz/_data_exploration.py | 262 ++++++++++++++++++++++-----------
2 files changed, 174 insertions(+), 94 deletions(-)
diff --git a/qim3d/viz/__init__.py b/qim3d/viz/__init__.py
index e7ba84a..f785319 100644
--- a/qim3d/viz/__init__.py
+++ b/qim3d/viz/__init__.py
@@ -4,13 +4,11 @@ from ._data_exploration import (
chunks,
fade_mask,
histogram,
+ line_profile,
slicer,
slicer_orthogonal,
slices_grid,
- chunks,
- histogram,
- line_profile,
- threshold
+ threshold,
)
from ._detection import circles
from ._k3d import mesh, volumetric
diff --git a/qim3d/viz/_data_exploration.py b/qim3d/viz/_data_exploration.py
index 855d730..84c0266 100644
--- a/qim3d/viz/_data_exploration.py
+++ b/qim3d/viz/_data_exploration.py
@@ -4,20 +4,17 @@ Provides a collection of visualization functions.
import math
import warnings
-
-from typing import List, Optional, Union, Tuple
+from typing import List, Optional, Tuple, Union
import dask.array as da
import ipywidgets as widgets
import matplotlib
import matplotlib.figure
import matplotlib.pyplot as plt
-import matplotlib
-from IPython.display import SVG, display, clear_output
-import matplotlib
import numpy as np
import seaborn as sns
import skimage.measure
+from IPython.display import clear_output, display
import qim3d
from qim3d.utils._logger import log
@@ -1009,13 +1006,23 @@ def histogram(
if return_fig:
return fig
+
class _LineProfile:
- def __init__(self, volume, slice_axis, slice_index, vertical_position, horizontal_position, angle, fraction_range):
+ def __init__(
+ self,
+ volume,
+ slice_axis,
+ slice_index,
+ vertical_position,
+ horizontal_position,
+ angle,
+ fraction_range,
+ ):
self.volume = volume
self.slice_axis = slice_axis
self.dims = np.array(volume.shape)
- self.pad = 1 # Padding on pivot point to avoid border issues
+ self.pad = 1 # Padding on pivot point to avoid border issues
self.cmap = [matplotlib.cm.plasma, matplotlib.cm.spring][1]
self.initialize_widgets()
@@ -1025,7 +1032,7 @@ class _LineProfile:
self.y_widget.value = vertical_position
self.angle_widget.value = angle
self.line_fraction_widget.value = [fraction_range[0], fraction_range[1]]
-
+
def update_slice_axis(self, slice_axis):
self.slice_axis = slice_axis
self.slice_index_widget.max = self.volume.shape[slice_axis] - 1
@@ -1039,35 +1046,44 @@ class _LineProfile:
def initialize_widgets(self):
layout = widgets.Layout(width='300px', height='auto')
- self.x_widget = widgets.IntSlider(min=self.pad, step=1, description="", layout=layout)
- self.y_widget = widgets.IntSlider(min=self.pad, step=1, description="", layout=layout)
- self.angle_widget = widgets.IntSlider(min=0, max=360, step=1, value=0, description="", layout=layout)
+ self.x_widget = widgets.IntSlider(
+ min=self.pad, step=1, description='', layout=layout
+ )
+ self.y_widget = widgets.IntSlider(
+ min=self.pad, step=1, description='', layout=layout
+ )
+ self.angle_widget = widgets.IntSlider(
+ min=0, max=360, step=1, value=0, description='', layout=layout
+ )
self.line_fraction_widget = widgets.FloatRangeSlider(
- min=0, max=1, step=0.01, value=[0, 1],
- description="", layout=layout
+ min=0, max=1, step=0.01, value=[0, 1], description='', layout=layout
)
- self.slice_axis_widget = widgets.Dropdown(options=[0,1,2], value=self.slice_axis, description='Slice axis')
+ self.slice_axis_widget = widgets.Dropdown(
+ options=[0, 1, 2], value=self.slice_axis, description='Slice axis'
+ )
self.slice_axis_widget.layout.width = '250px'
- self.slice_index_widget = widgets.IntSlider(min=0, step=1, description="Slice index", layout=layout)
+ self.slice_index_widget = widgets.IntSlider(
+ min=0, step=1, description='Slice index', layout=layout
+ )
self.slice_index_widget.layout.width = '400px'
-
+
def calculate_line_endpoints(self, x, y, angle):
"""
Line is parameterized as: [x + t*np.cos(angle), y + t*np.sin(angle)]
"""
if np.isclose(angle, 0):
return [0, y], [self.x_max, y]
- elif np.isclose(angle, np.pi/2):
+ elif np.isclose(angle, np.pi / 2):
return [x, 0], [x, self.y_max]
elif np.isclose(angle, np.pi):
return [self.x_max, y], [0, y]
- elif np.isclose(angle, 3*np.pi/2):
+ elif np.isclose(angle, 3 * np.pi / 2):
return [x, self.y_max], [x, 0]
- elif np.isclose(angle, 2*np.pi):
+ elif np.isclose(angle, 2 * np.pi):
return [0, y], [self.x_max, y]
-
+
t_left = -x / np.cos(angle)
t_bottom = -y / np.sin(angle)
t_right = (self.x_max - x) / np.cos(angle)
@@ -1075,23 +1091,26 @@ class _LineProfile:
t_values = np.array([t_left, t_top, t_right, t_bottom])
t_pos = np.min(t_values[t_values > 0])
t_neg = np.max(t_values[t_values < 0])
-
+
src = [x + t_neg * np.cos(angle), y + t_neg * np.sin(angle)]
dst = [x + t_pos * np.cos(angle), y + t_pos * np.sin(angle)]
return src, dst
-
+
def update(self, slice_axis, slice_index, x, y, angle_deg, fraction_range):
if slice_axis != self.slice_axis:
self.update_slice_axis(slice_axis)
x = self.x_widget.value
y = self.y_widget.value
slice_index = self.slice_index_widget.value
-
+
clear_output(wait=True)
-
+
image = np.take(self.volume, slice_index, slice_axis)
angle = np.radians(angle_deg)
- src, dst = [np.array(point, dtype='float32') for point in self.calculate_line_endpoints(x, y, angle)]
+ src, dst = (
+ np.array(point, dtype='float32')
+ for point in self.calculate_line_endpoints(x, y, angle)
+ )
# Rescale endpoints
line_vec = dst - src
@@ -1101,30 +1120,37 @@ class _LineProfile:
y_pline = skimage.measure.profile_line(image, src, dst)
fig, ax = plt.subplots(1, 2, figsize=(10, 5))
-
+
# Image with color-gradiented line
num_segments = 100
x_seg = np.linspace(src[0], dst[0], num_segments)
y_seg = np.linspace(src[1], dst[1], num_segments)
- segments = np.stack([np.column_stack([y_seg[:-2], x_seg[:-2]]),
- np.column_stack([y_seg[2:], x_seg[2:]])], axis=1)
- norm = plt.Normalize(vmin=0, vmax=num_segments-1)
+ segments = np.stack(
+ [
+ np.column_stack([y_seg[:-2], x_seg[:-2]]),
+ np.column_stack([y_seg[2:], x_seg[2:]]),
+ ],
+ axis=1,
+ )
+ norm = plt.Normalize(vmin=0, vmax=num_segments - 1)
colors = self.cmap(norm(np.arange(num_segments - 1)))
lc = matplotlib.collections.LineCollection(segments, colors=colors, linewidth=2)
- ax[0].imshow(image,cmap='gray')
+ ax[0].imshow(image, cmap='gray')
ax[0].add_collection(lc)
# pivot point
- ax[0].plot(y,x,marker='s', linestyle='', color='cyan', markersize=4)
+ ax[0].plot(y, x, marker='s', linestyle='', color='cyan', markersize=4)
ax[0].set_xlabel(f'axis {np.delete(np.arange(3), self.slice_axis)[1]}')
ax[0].set_ylabel(f'axis {np.delete(np.arange(3), self.slice_axis)[0]}')
-
+
# Profile intensity plot
norm = plt.Normalize(0, vmax=len(y_pline) - 1)
x_pline = np.arange(len(y_pline))
points = np.column_stack((x_pline, y_pline))[:, np.newaxis, :]
segments = np.concatenate([points[:-1], points[1:]], axis=1)
- lc = matplotlib.collections.LineCollection(segments, cmap=self.cmap, norm=norm, array=x_pline[:-1], linewidth=2)
+ lc = matplotlib.collections.LineCollection(
+ segments, cmap=self.cmap, norm=norm, array=x_pline[:-1], linewidth=2
+ )
ax[1].add_collection(lc)
ax[1].autoscale()
@@ -1132,48 +1158,65 @@ class _LineProfile:
ax[1].grid(True)
plt.tight_layout()
plt.show()
-
+
def build_interactive(self):
# Group widgets into two columns
- title_style = "text-align:center; font-size:16px; font-weight:bold; margin-bottom:5px;"
- title_column1 = widgets.HTML(f"<div style='{title_style}'>Line parameterization</div>")
- title_column2 = widgets.HTML(f"<div style='{title_style}'>Slice selection</div>")
+ title_style = (
+ 'text-align:center; font-size:16px; font-weight:bold; margin-bottom:5px;'
+ )
+ title_column1 = widgets.HTML(
+ f"<div style='{title_style}'>Line parameterization</div>"
+ )
+ title_column2 = widgets.HTML(
+ f"<div style='{title_style}'>Slice selection</div>"
+ )
# Make label widgets instead of descriptions which have different lengths.
label_layout = widgets.Layout(width='120px')
- label_x = widgets.Label("Vertical position", layout=label_layout)
- label_y = widgets.Label("Horizontal position", layout=label_layout)
- label_angle = widgets.Label("Angle (°)", layout=label_layout)
- label_fraction = widgets.Label("Fraction range", layout=label_layout)
+ label_x = widgets.Label('Vertical position', layout=label_layout)
+ label_y = widgets.Label('Horizontal position', layout=label_layout)
+ label_angle = widgets.Label('Angle (°)', layout=label_layout)
+ label_fraction = widgets.Label('Fraction range', layout=label_layout)
row_x = widgets.HBox([label_x, self.x_widget])
row_y = widgets.HBox([label_y, self.y_widget])
row_angle = widgets.HBox([label_angle, self.angle_widget])
row_fraction = widgets.HBox([label_fraction, self.line_fraction_widget])
- controls_column1 = widgets.VBox([title_column1, row_x, row_y, row_angle, row_fraction])
- controls_column2 = widgets.VBox([title_column2, self.slice_axis_widget, self.slice_index_widget])
+ controls_column1 = widgets.VBox(
+ [title_column1, row_x, row_y, row_angle, row_fraction]
+ )
+ controls_column2 = widgets.VBox(
+ [title_column2, self.slice_axis_widget, self.slice_index_widget]
+ )
controls = widgets.HBox([controls_column1, controls_column2])
interactive_plot = widgets.interactive_output(
- self.update,
- {'slice_axis': self.slice_axis_widget, 'slice_index': self.slice_index_widget,
- 'x': self.x_widget, 'y': self.y_widget, 'angle_deg': self.angle_widget,
- 'fraction_range': self.line_fraction_widget}
+ self.update,
+ {
+ 'slice_axis': self.slice_axis_widget,
+ 'slice_index': self.slice_index_widget,
+ 'x': self.x_widget,
+ 'y': self.y_widget,
+ 'angle_deg': self.angle_widget,
+ 'fraction_range': self.line_fraction_widget,
+ },
)
return widgets.VBox([controls, interactive_plot])
+
def line_profile(
- volume: np.ndarray,
- slice_axis: int=0,
- slice_index: int | str='middle',
- vertical_position: int | str='middle',
- horizontal_position: int | str='middle',
- angle: int=0,
- fraction_range: Tuple[float,float]=(0.00, 1.00)
- ) -> widgets.interactive:
- """Returns an interactive widget for visualizing the intensity profiles of lines on slices.
+ volume: np.ndarray,
+ slice_axis: int = 0,
+ slice_index: int | str = 'middle',
+ vertical_position: int | str = 'middle',
+ horizontal_position: int | str = 'middle',
+ angle: int = 0,
+ fraction_range: Tuple[float, float] = (0.00, 1.00),
+) -> widgets.interactive:
+ """
+ Returns an interactive widget for visualizing the intensity profiles of lines on slices.
Args:
volume (np.ndarray): The 3D volume of interest.
@@ -1181,13 +1224,13 @@ def line_profile(
slice_index (int or str, optional): Specifies the initial slice index along slice_axis.
vertical_position (int or str, optional): Specifies the initial vertical position of the line's pivot point.
horizontal_position (int or str, optional): Specifies the initial horizontal position of the line's pivot point.
- angle (int or float, optional): Specifies the initial angle (°) of the line around the pivot point. A float will be converted to an int. A value outside the range will be wrapped modulo.
+ angle (int or float, optional): Specifies the initial angle (°) of the line around the pivot point. A float will be converted to an int. A value outside the range will be wrapped modulo.
fraction_range (tuple or list, optional): Specifies the fraction of the line segment to use from border to border. Both the start and the end should be in the range [0.0, 1.0].
Returns:
widget (widgets.widget_box.VBox): The interactive widget.
-
+
Example:
```python
import qim3d
@@ -1198,57 +1241,82 @@ def line_profile(
"""
+
def parse_position(pos, pos_range, name):
if isinstance(pos, int):
if not pos_range[0] <= pos < pos_range[1]:
- raise ValueError(f'Value for {name} must be inside [{pos_range[0]}, {pos_range[1]}]')
+ raise ValueError(
+ f'Value for {name} must be inside [{pos_range[0]}, {pos_range[1]}]'
+ )
return pos
elif isinstance(pos, str):
pos = pos.lower()
- if pos == 'start': return pos_range[0]
- elif pos == 'middle': return pos_range[0] + (pos_range[1] - pos_range[0]) // 2
- elif pos == 'end': return pos_range[1]
+ if pos == 'start':
+ return pos_range[0]
+ elif pos == 'middle':
+ return pos_range[0] + (pos_range[1] - pos_range[0]) // 2
+ elif pos == 'end':
+ return pos_range[1]
else:
raise ValueError(
f"Invalid string '{pos}' for {name}. "
"Must be 'start', 'middle', or 'end'."
)
else:
- raise TypeError(f'Axis position must be of type int or str.')
-
+ raise TypeError('Axis position must be of type int or str.')
+
if not isinstance(volume, (np.ndarray, da.core.Array)):
- raise ValueError("Data type for volume not supported.")
+ raise ValueError('Data type for volume not supported.')
if volume.ndim != 3:
- raise ValueError("Volume must be 3D.")
-
+ raise ValueError('Volume must be 3D.')
+
dims = volume.shape
slice_index = parse_position(slice_index, (0, dims[slice_axis] - 1), 'slice_index')
# the omission of the ends for the pivot point is due to border issues.
- vertical_position = parse_position(vertical_position, (1, np.delete(dims, slice_axis)[0] - 2), 'vertical_position')
- horizontal_position = parse_position(horizontal_position, (1, np.delete(dims, slice_axis)[1] - 2), 'horizontal_position')
-
+ vertical_position = parse_position(
+ vertical_position, (1, np.delete(dims, slice_axis)[0] - 2), 'vertical_position'
+ )
+ horizontal_position = parse_position(
+ horizontal_position,
+ (1, np.delete(dims, slice_axis)[1] - 2),
+ 'horizontal_position',
+ )
+
if not isinstance(angle, int | float):
- raise ValueError("Invalid type for angle.")
+ raise ValueError('Invalid type for angle.')
angle = round(angle) % 360
- if not (0.0 <= fraction_range[0] <= 1.0 and 0.0 <= fraction_range[1] <= 1.0 and fraction_range[0] <= fraction_range[1]):
- raise ValueError("Invalid values for fraction_range.")
+ if not (
+ 0.0 <= fraction_range[0] <= 1.0
+ and 0.0 <= fraction_range[1] <= 1.0
+ and fraction_range[0] <= fraction_range[1]
+ ):
+ raise ValueError('Invalid values for fraction_range.')
- lp = _LineProfile(volume, slice_axis, slice_index, vertical_position, horizontal_position, angle, fraction_range)
+ lp = _LineProfile(
+ volume,
+ slice_axis,
+ slice_index,
+ vertical_position,
+ horizontal_position,
+ angle,
+ fraction_range,
+ )
return lp.build_interactive()
+
def threshold(
- volume: np.ndarray,
- cmap_image: str = 'viridis',
- vmin: float = None,
- vmax: float = None,
+ volume: np.ndarray,
+ cmap_image: str = 'viridis',
+ vmin: float = None,
+ vmax: float = None,
) -> widgets.VBox:
"""
- This function provides an interactive interface to explore thresholding on a
- 3D volume slice-by-slice. Users can either manually set the threshold value
- using a slider or select an automatic thresholding method from `skimage`.
+ This function provides an interactive interface to explore thresholding on a
+ 3D volume slice-by-slice. Users can either manually set the threshold value
+ using a slider or select an automatic thresholding method from `skimage`.
- The visualization includes the original image slice, a binary mask showing regions above the
+ The visualization includes the original image slice, a binary mask showing regions above the
threshold and an overlay combining the binary mask and the original image.
Args:
@@ -1257,16 +1325,16 @@ def threshold(
cmap_threshold (str, optional): Colormap for the binary image. Defaults to 'gray'.
vmin (float, optional): Minimum value for the colormap. Defaults to None.
vmax (float, optional): Maximum value for the colormap. Defaults to None.
-
+
Returns:
slicer_obj (widgets.VBox): The interactive widget for thresholding a 3D volume.
-
+
Interactivity:
- **Manual Thresholding**:
- Select 'Manual' from the dropdown menu to manually adjust the threshold
+ Select 'Manual' from the dropdown menu to manually adjust the threshold
using the slider.
- **Automatic Thresholding**:
- Choose a method from the dropdown menu to apply an automatic thresholding
+ Choose a method from the dropdown menu to apply an automatic thresholding
algorithm. Available methods include:
- Otsu
- Isodata
@@ -1276,7 +1344,7 @@ def threshold(
- Triangle
- Yen
- The threshold slider will display the computed value and will be disabled
+ The threshold slider will display the computed value and will be disabled
in this mode.
@@ -1290,6 +1358,7 @@ def threshold(
qim3d.viz.threshold(vol)
```
+
"""
# Centralized state dictionary to track current parameters
@@ -1348,10 +1417,14 @@ def threshold(
# Original image
new_vmin = (
- None if (isinstance(vmin, (float, int)) and vmin > np.max(slice_img)) else 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
+ None
+ if (isinstance(vmax, (float, int)) and vmax < np.min(slice_img))
+ else vmax
)
axes[0].imshow(slice_img, cmap=cmap_image, vmin=new_vmin, vmax=new_vmax)
axes[0].set_title('Original')
@@ -1405,7 +1478,16 @@ def threshold(
)
method_dropdown = widgets.Dropdown(
- options=['Manual', 'Otsu', 'Isodata', 'Li', 'Mean', 'Minimum', 'Triangle', 'Yen'],
+ options=[
+ 'Manual',
+ 'Otsu',
+ 'Isodata',
+ 'Li',
+ 'Mean',
+ 'Minimum',
+ 'Triangle',
+ 'Yen',
+ ],
value=state['method'],
description='Method',
)
--
GitLab