#!/usr/bin/env python
# coding: utf-8

# # stackview on google colab
# Interactive image stack viewing in jupyter notebooks based on
# [ipycanvas](https://ipycanvas.readthedocs.io/) and
# [ipywidgets](https://ipywidgets.readthedocs.io/en/latest/).
# 
# In this notebook we demonstate its usage on google colab.
# 
# [Run this notebook in google colab](https://colab.research.google.com/github/haesleinhuepf/stackview/blob/master/docs/colab_demo.ipynb)
# 
# ## Installation
# After starting a new session on google colab, you need to install stackview first.
# 
# Also note: The make stackview work in google colab, you need to install ipycanvas==0.11 ([read why](https://github.com/martinRenou/ipycanvas/issues/170#issuecomment-1119200238)).

# In[1]:


get_ipython().system('pip install stackview==0.16.0 ipycanvas==0.11')


# If you ran this for the first time, you need to restart your session.
# 
# ## Usage
# First we test the installation by importing the libraries we're going to use

# In[2]:


import stackview
from imageio.v3 import imread
from skimage.filters import gaussian


# In[3]:


# Activate widgets in google colab
from google.colab import output
output.enable_custom_widget_manager()


# Starting point is a 3D image dataset provided as numpy array.

# In[4]:


image_stack = imread('https://github.com/clEsperanto/clesperanto_example_data/raw/main/Haase_MRT_tfl3d1.tif?raw=true')

image_stack.shape


# In[5]:


stackview.insight(image_stack)


# ## Slicing
# 
# We can explore the dataset interactively using `stackview.slice`.

# In[6]:


stackview.slice(image_stack, zoom_factor=2)


# In[7]:


foggy_brain = gaussian(image_stack, sigma=1)

stackview.curtain(image_stack, foggy_brain, zoom_factor=2)


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