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Merge pull request #152 from haesleinhuepf/histogram
Add interactive histogram
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‎README.md‎

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@@ -74,7 +74,13 @@ stackview.display_range(image)
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![img.png](https://raw.githubusercontent.com/haesleinhuepf/stackview/main/docs/images/demo_display_range.gif)
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### Interactive histogram
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```
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stackview.histogram(image)
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```
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![img.png](https://raw.githubusercontent.com/haesleinhuepf/stackview/main/docs/images/histogram.gif)
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### Static insight views
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‎docs/histogram.ipynb‎

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{
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"cells": [
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{
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"cell_type": "markdown",
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"id": "94e6bb0c-c0ff-445a-abb4-f80e77f607e6",
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"metadata": {},
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"source": [
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"# Interactive histogram\n",
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"In this notebook we will create a histogram shown next to an image. By dragging the mouse in the image, one can create a new histogram of the intensities in the specified region."
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]
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},
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{
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"cell_type": "code",
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"execution_count": 1,
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"id": "f85a9c99-dd9b-4adf-8fde-1e74c942694b",
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"metadata": {},
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"outputs": [],
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"source": [
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"import numpy as np\n",
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"import stackview \n",
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"from skimage.io import imread\n",
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"\n",
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"image = imread(\"data/Haase_MRT_tfl3d1.tif\")"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 2,
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"id": "28034b4b-2393-4930-ad80-60b6c38b549d",
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"metadata": {},
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"outputs": [
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{
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"data": {
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"application/vnd.jupyter.widget-view+json": {
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"model_id": "8e4ef033adff4193a5bef60299f7b41a",
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"version_major": 2,
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"version_minor": 0
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},
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"text/plain": [
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"HBox(children=(VBox(children=(HBox(children=(VBox(children=(HBox(children=(VBox(children=(ImageWidget(height=2…"
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]
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},
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"execution_count": 2,
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"metadata": {},
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"output_type": "execute_result"
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}
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],
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"source": [
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"stackview.histogram(image, zoom_factor=1.5)"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"id": "661d2ad6-c80c-4357-84ba-4e530a8f62e5",
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"metadata": {},
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"outputs": [],
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"source": []
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"id": "fa383f8c-767f-4003-ab8e-b10bec4463b5",
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"metadata": {},
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"outputs": [],
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"source": []
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}
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],
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"metadata": {
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"kernelspec": {
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"display_name": "Python 3 (ipykernel)",
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"language": "python",
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"name": "python3"
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},
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"language_info": {
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"codemirror_mode": {
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"name": "ipython",
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"version": 3
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},
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"file_extension": ".py",
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"mimetype": "text/x-python",
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"name": "python",
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"nbconvert_exporter": "python",
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"pygments_lexer": "ipython3",
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"version": "3.11.11"
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}
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},
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"nbformat": 4,
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"nbformat_minor": 5
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}

‎docs/images/histogram.gif‎

2.87 MB
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‎setup.py‎

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setuptools.setup(
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name="stackview",
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version="0.14.3",
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version="0.15.0",
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author="Robert Haase",
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author_email="[email protected]",
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description="Interactive image stack viewing in jupyter notebooks",

‎stackview/__init__.py‎

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__version__ = "0.14.3"
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__version__ = "0.15.0"
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from ._static_view import jupyter_displayable_output, insight
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from ._utilities import merge_rgb
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from ._sliceplot import sliceplot
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from ._wordcloudplot import wordcloudplot
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from ._add_bounding_boxes import add_bounding_boxes
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from ._histogram import histogram
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‎stackview/_histogram.py‎

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import warnings
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def histogram(
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image,
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slice_number: int = None,
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alpha: float = 0.5,
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continuous_update: bool = True,
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slider_text: str = "[{}]",
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zoom_factor: float = 1.0,
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zoom_spline_order: int = 0,
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colormap:str = None,
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display_min:float = None,
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display_max:float = None
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):
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"""Shows an image with a slider to go through a stack plus a label with the current mouse position and intensity at that position.
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Parameters
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----------
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image : image
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Image shown
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labels: label image
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Labels which can be manually modified to draw annotations
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slice_number : int, optional
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Slice-position in the stack
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alpha : float, optional
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Alpha blending value for the labels on top of the image
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continuous_update : bool, optional
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Update the image while dragging the mouse on the slider, default: False
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zoom_factor: float, optional
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Allows showing the image larger (> 1) or smaller (<1)
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zoom_spline_order: int, optional
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Spline order used for interpolation (default=0, nearest-neighbor)
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colormap: str, optional
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Matplotlib colormap name or "pure_green", "pure_magenta", ...
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display_min: float, optional
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Lower bound of properly shown intensities
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display_max: float, optional
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Upper bound of properly shown intensities
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Returns
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-------
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An ipywidget with an image display, a slider and a label showing mouse position and intensity.
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"""
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from ._utilities import _no_resize
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from ._image_widget import _img_to_rgb
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import ipywidgets
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from ipyevents import Event
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from ._slice_viewer import _SliceViewer
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import numpy as np
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import matplotlib.pyplot as plt
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from ._grid import grid
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if 'cupy.ndarray' in str(type(image)):
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image = image.get()
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if slice_number is None:
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slice_number = int(image.shape[0] / 2)
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total_min = float(image.min())
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total_max = float(image.max())
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# Image view
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viewer = _SliceViewer(image,
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zoom_factor=zoom_factor,
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zoom_spline_order=zoom_spline_order,
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colormap=colormap,
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display_min=display_min,
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display_max=display_max,
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slider_text=slider_text)
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view = viewer.view
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# setup user interface for changing the slice
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slice_slider = viewer.slice_slider
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former_drawn_position = {'state':None,
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'start_x': 0,
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'start_y': 0,
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'end_x': image.shape[-1],
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'end_y': image.shape[-2],
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}
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def create_histogram_plot(image, x, y, width, height):
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#return np.random.normal(50, y, (100, 100))
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cropped_image = image[..., y:y+height, x:x+width]
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#histogram = np.histogram(cropped_image, bins=256, range=(0, 255))
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# plot histogram and store histogram as numpy RGB array
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plt.figure(figsize=(1.8, 1.4))
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# measure how long this takes
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plt.hist(cropped_image.flatten(), bins=32)
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plt.xlim(total_min, total_max)
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plt.yticks([])
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plt.xticks([total_min, int((total_min + total_max) / 2), total_max])
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plt.tight_layout()
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from io import BytesIO
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from PIL import Image
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with BytesIO() as file_obj:
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plt.savefig(file_obj, format='png')
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plt.close() # supress plot output
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file_obj.seek(0)
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# Open the image using PIL's Image.open() which accepts a file-like object
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histogram_image = Image.open(file_obj)
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# Convert the PIL image to a numpy array
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return np.array(histogram_image)[...,:3]
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histogram_image = create_histogram_plot(image, 0, 0, image.shape[-2], image.shape[-1])
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histogram_viewer = _SliceViewer(histogram_image)
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width = image.shape[-1]
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height = image.shape[-2]
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layout = layout=ipywidgets.Layout(display="flex", max_height="25px")
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slice_lbl = ipywidgets.Label(f"(..., 0:{height}, 0:{width}", layout=layout)
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dtype_lbl = ipywidgets.Label(str(image.dtype), layout=layout)
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min_intensity_lbl = ipywidgets.Label("", layout=layout)
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max_intensity_lbl = ipywidgets.Label("", layout=layout)
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layout = ipywidgets.Layout(display="flex", justify_content="flex-end", min_width="50px", max_height="25px")
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table = grid([
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[ipywidgets.Label("slice", layout=layout), slice_lbl],
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[ipywidgets.Label("dtype", layout=layout), dtype_lbl],
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[ipywidgets.Label("min", layout=layout), min_intensity_lbl],
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[ipywidgets.Label("max", layout=layout), max_intensity_lbl],
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])
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# event handler when the user changed the slider:
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def update_display(event=None):
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slice_image1 = viewer.get_view_slice()
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rgb_image1 = _img_to_rgb(slice_image1, colormap=colormap, display_min=display_min, display_max=display_max)
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from ._add_bounding_boxes import add_bounding_boxes
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bb = None
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if former_drawn_position['state'] is not None:
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bb = {
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'x': min(former_drawn_position['start_x'], former_drawn_position['end_x']),
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'y': min(former_drawn_position['start_y'], former_drawn_position['end_y']),
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'width': abs(former_drawn_position['start_x'] - former_drawn_position['end_x']),
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'height': abs(former_drawn_position['start_y'] - former_drawn_position['end_y'])
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}
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annotated_image = add_bounding_boxes(rgb_image1, [bb])
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slice_lbl.value = f"(..., {bb['y']}:{bb['y']+bb['height']}, {bb['x']}:{bb['x']+bb['width']})"
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else:
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annotated_image = rgb_image1
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if former_drawn_position['state'] == "mouse-up" and bb is not None:
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h_image = create_histogram_plot(slice_image1, bb['x'], bb['y'], bb['width'], bb['height'])
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histogram_viewer.view.data = h_image
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former_drawn_position['state'] = None
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min_intensity_lbl.value = str(np.min(slice_image1))
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max_intensity_lbl.value = str(np.max(slice_image1))
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view.data = annotated_image
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# user interface for histogram
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tool_box = ipywidgets.VBox([
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table,
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histogram_viewer.view
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])
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event_handler = Event(source=view, watched_events=['mousemove'])
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if slice_slider is not None:
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# connect user interface with event
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result = _no_resize(ipywidgets.HBox([
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ipywidgets.VBox([_no_resize(view), slice_slider]),
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tool_box
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]))
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else:
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result = _no_resize(ipywidgets.VBox([
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ipywidgets.HBox([_no_resize(view), tool_box]),
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]))
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# event handler for when something was drawn
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def update_display_while_drawing(event):
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# get position from event
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relative_position_x = event['relativeX'] / zoom_factor
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relative_position_y = event['relativeY'] / zoom_factor
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absolute_position_x = int(relative_position_x)
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absolute_position_y = int(relative_position_y)
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if event['buttons'] == 0:
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if former_drawn_position['state'] == 'mouse-down':
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# not clicked
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former_drawn_position['state'] = 'mouse-up'
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update_display()
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return
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# compare position and last known position. If equal, don't update / redraw
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if former_drawn_position["end_x"] == absolute_position_x and former_drawn_position["end_y"] == absolute_position_y:
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return
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if former_drawn_position['state'] is None:
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# mouse-down event
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former_drawn_position['state'] = 'mouse-down'
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former_drawn_position['start_x'] = absolute_position_x
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former_drawn_position['start_y'] = absolute_position_y
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former_drawn_position['end_x'] = absolute_position_x
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former_drawn_position['end_y'] = absolute_position_y
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x = min(former_drawn_position['start_x'], former_drawn_position['end_x'])
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y = min(former_drawn_position['start_y'], former_drawn_position['end_y'])
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w = abs(former_drawn_position['start_x'] - former_drawn_position['end_x'])
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h = abs(former_drawn_position['start_y'] - former_drawn_position['end_y'])
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update_display()
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# draw everything once
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update_display()
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# connect events
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event_handler.on_dom_event(update_display_while_drawing)
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def viewer_update(e=None):
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former_drawn_position['state'] = 'mouse-up'
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update_display()
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viewer.observe(viewer_update)
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result.update = update_display
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return result

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