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

# # itk-jupyter-widgets
# 
# ## Interactive 3D and 2D Visualization in Jupyter
# 
# TriPython March 2018 Meeting
# 
# Matthew McCormick, PhD
# 
# Kitware, Inc
# 
# [<img src="https://thumbs.gfycat.com/ShyFelineBeetle-size_restricted.gif" width="320">](https://github.com/InsightSoftwareConsortium/itk-jupyter-widgets)
# 
# [<img src="https://pydata.org/carolinas2016/media/sponsor_files/tripython-banner_478mQLr.svg" width="200">](http://trizpug.org/)
# 
# [<img src="https://upload.wikimedia.org/wikipedia/commons/thumb/f/f9/CC-Zero-badge.svg/88px-CC-Zero-badge.svg.png">](https://creativecommons.org/share-your-work/public-domain/cc0/)

# In[1]:


from itkwidgets import view

import requests
import itk

import shutil
import os

# Download data
fileName = '005_32months_T2_RegT1_Reg2Atlas_ManualBrainMask_Stripped.nrrd'
if not os.path.exists(fileName):
    response = requests.get('https://data.kitware.com/api/v1/file/564a5b078d777f7522dbfaa6/download', stream=True)
    with open(fileName, 'wb') as fp:
        response.raw.decode_content = True
        shutil.copyfileobj(response.raw, fp)
        
# Download data
brainFileName = 'brainweb165a10f17.mha'
if not os.path.exists(brainFileName):
    response = requests.get('https://data.kitware.com/api/v1/file/588271308d777f4f3f3072e2/download', stream=True)
    with open(brainFileName, 'wb') as fp:
        response.raw.decode_content = True
        shutil.copyfileobj(response.raw, fp)


# In[2]:


from itkwidgets import view
import itk
image = itk.imread(fileName)
#view(image)


# ## Agenda
# 

# ### Where have we come from? Where are we going?

# ### What is the problem we are solving?

# ### What technical approaches are required for this problem?

# ### How do I use this tool?

# ### What are the next steps?

# ## Where have we come from?
# 
# ## Where are we going?

# *with interactive scientific computing in the SciPy ecosystem*

# ### IPython Shell
# 
# Original author: Fernando Pérez
# 
# <img src="Fernando_Perez.jpg" width="200">
# <small><a href="https://en.wikipedia.org/wiki/Fernando_P%C3%A9rez_(software_developer)">Image source</a></small>
# 
# Initial release: 2001

# ### IPython Shell
# 
# IPython 0.7.2 released June 6, 2006
# 
# <img src="IPython-shell.png" width="900">
# <small>[Image source](https://en.wikipedia.org/wiki/IPython)</small>

# - Interactive: **tab completion**
# - Accessible: Matlab $\rightarrow$ **Scientific Python**
# - Brings powerful programming tools together: **matplotlib** integration

# ### IPython Notebook
# 
# IPython 0.12.0 released December 18, 2011
# 
# <img src="ipython_notebook.png" width="500">
# <small>[Image source](http://pgbovine.net/ipython-notebook-first-impressions.htm)</small>

# - Interactive: creates *a tool for open, collaborative, reproducible scientific computing*
# - Accessible: Terminal $\rightarrow$ **Web browser**
# - Brings powerful programming tools together: Literate programming: Markdown + $\LaTeX$ **prose**, IPython shell **code** cells, and matplotlib **visualizations**

# ### Jupyter Notebook
# 
# Fernando announces Project Jupyter at SciPy 2014
# 
# <img src="jupyter_notebook.png" width="500">
# <small>[Image source](https://jupyter.org/)</small>

# - Interactive: Adds a file browser, browser-based terminal, and browser-based text editor
# - Accessible: Open standards for interative computing to enabled customized applications: Notebook Document Format, Interactive Computing Protocol, The Kernel
# - Brings powerful programming tools together: Expands support for programming language kernels **other than Python**

# ### JupyterLab
# 
# ["JupyterLab is Ready for Users"](https://blog.jupyter.org/jupyterlab-is-ready-for-users-5a6f039b8906) - February 20, 2018
# 
# <img src="jupyterlab.png" width="600">
# <small>[Image source](https://blog.jupyter.org/jupyterlab-is-ready-for-users-5a6f039b8906)</small>

# - Interactive: Browser-based **window management**, customized viewers for different file types
# - Accessible: Drag and drop cells, easy deploy with *Docker-based* JupyterHub
# - Brings powerful programming tools together: Made with **community-developed extensions** in mind

# ### The Future
# 
# <img src="birth_death_javascript.png" width="500">
# <small>[Image source](https://www.destroyallsoftware.com/talks/the-birth-and-death-of-javascript)</small>
# 
# "To start developing a JupyterLab extension, see the JupyterLab Extension Developer Guide and the **TypeScript** or **JavaScript** extension templates. JupyterLab itself is co-developed on top of **PhosphorJS**, a new **Javascript** library for **building extensible, high-performance, desktop-style web applications**. We use **modern JavaScript technologies** such as **TypeScript, React, Lerna, Yarn, and webpack**."

# - Interactive: **Browser-based application**
# - Accessible: **Zero-install**, works on **all platforms**
# - Brings powerful programming tools together: **JavaScript**, **WebGL**, **WebAssembly**

# ## What is the problem we are solving?
# 

# *Interactive visualization to support multi-dimensional spatial analysis*

# ### ipyleaflet
# 
# *A Jupyter / Leaflet bridge enabling interactive maps in the Jupyter notebook.*
# 
# <img src="ipyleaflet.png" width="900">
# 
# <small>[Image source](https://github.com/ellisonbg/ipyleaflet)</small>

# ### GeoNotebook
# 
# *GeoNotebook is an application that provides client/server environment with interactive visualization and analysis capabilities using Jupyter, GeoJS and other open source tools.*
# 
# <img src="geonotebook.gif" width="600">
# 
# <small>[Image source](https://github.com/OpenGeoscience/geonotebook)</small>

# ### ipyvolume
# 
# *3d plotting for Python in the Jupyter notebook based on IPython widgets using WebGL.*
# 
# <img src="ipyvolume.gif" width="300">
# 
# <small>[Image source](https://github.com/maartenbreddels/ipyvolume)</small>

# ### pythreejs
# 
# *A Python / ThreeJS bridge utilizing the Jupyter widget infrastructure.*
# 
# <img src="pythreejs.gif" width="500">
# 
# <small>[Image source](https://github.com/jovyan/pythreejs)</small>

# ### itk-jupyter-widgets
# 
# These widgets are designed to support spatial analysis with the [Insight Toolkit (ITK)](https://www.itk.org), but they also work with other spatial analysis tools in the scientific Python ecosystem.
# 
# These widgets are built on [itk.js](https://github.com/InsightSoftwareConsortium/itk-js) and [vtk.js](https://github.com/Kitware/vtk-js).
# 
# [<img src="https://thumbs.gfycat.com/ShyFelineBeetle-size_restricted.gif" width="320">](https://github.com/InsightSoftwareConsortium/itk-jupyter-widgets)

# - 2D or 3D images
# - Excellent volume rendering
# - Slicing
# - Data probe
# - Histogram and opacity transfer function editor

# In[2]:


from itkwidgets import view
import itk
PixelType = itk.ctype('float')
image = itk.imread(brainFileName, PixelType)
view(image)


# In[3]:


# Smooth the image
smoother = itk.CurvatureFlowImageFilter.New(image)
smoother.SetNumberOfIterations(6)
smoother.SetTimeStep(0.05)
smoother.Update()
view(smoother.GetOutput())


# In[4]:


confidence_connected = itk.ConfidenceConnectedImageFilter.New(smoother.GetOutput())
confidence_connected.SetMultiplier(2.5)
confidence_connected.SetNumberOfIterations(5)
confidence_connected.SetInitialNeighborhoodRadius(2)
confidence_connected.SetReplaceValue(255)

Dimension = image.GetImageDimension()
SeedType = itk.Index[Dimension]
seed1 = SeedType()
seed1[0] = 118
seed1[1] = 133
seed1[2] = 92
confidence_connected.AddSeed(seed1)

seed2 = SeedType()
seed2[0] = 63
seed2[1] = 135
seed2[2] = 94
confidence_connected.AddSeed(seed2)

seed3 = SeedType()
seed3[0] = 63
seed3[1] = 157
seed3[2] = 90
confidence_connected.AddSeed(seed3)

seed4 = SeedType()
seed4[0] = 111
seed4[1] = 150
seed4[2] = 90
confidence_connected.AddSeed(seed4)

seed5 = SeedType()
seed5[0] = 111
seed5[1] = 50
seed5[2] = 88
confidence_connected.AddSeed(seed5)


# In[5]:


confidence_connected.Update()
view(confidence_connected.GetOutput())


# ## What technical approaches are required for this problem?

# ### Multiple Languages
# 
# <img src="languages.png" width="600">

# ### Attention to Performance

# - Browser memory limitations? **No!**

# - Browser compute limitations? **If so, not for long!**

# - Data transfer times? **Yes!**

# ## How do I use this tool?

# ### Window / Level
# 
# <img src="window_level.gif">
# <small>[Image source](https://docs.oracle.com/cd/E19253-01/817-7519/6mmr6chkl/index.html)</small>

# ### Opacity Transfer Function
# 
# - Revelant to volume rendering
# - Scalar intensity opacity
# - Gradient-based opacity (shading)
# 

# ## What are the next steps?

# ### Impact: Addressing Heart Disease
# 
# American Heart Association, Precision Medicine Platform
# 
# <img src="aha.png" width="800">
# <small>[Image source](https://precision.heart.org/workspace)</small>

# ### Impact: Smart, Data-driven Financial Investments
# 
# - [Triangle Quant Investing Strategies Meet-up](https://www.meetup.com/Quant-Investing-strategies/)
# - Quantopia
# 

# ### Satellite Image Analysis
# 
# - [PlanetLabs](https://www.planet.com/) Notebooks
# 
# <img src="satellite.png" width="700">
# <small>[Image source](https://github.com/planetlabs/notebooks/blob/master/jupyter-notebooks/crop-classification/classify-cart-l8-ps.ipynb)</small>

# ### Enable People to Unlock the Power of Math, Science, and Computing
# 
# <img src="easier_for_people.png" width="800">
# 

# ### Next Up for itk-jupyter-widgets
# 
# - Support image types other than itk.Image, NumPy Array, e.g. OpenCV Mat, ImageJ2 images, vtkImageData, ...
# - Rendering meshes and point clouds
# - Compression and dynamic downsampling
# - Documentation
# - Embedding
# - JupyterLab Support
# 

# - Interactive
# - Accessible
# - Brings powerful ~~programming tools~~ people together
# 
# 
# [<img src="https://pydata.org/carolinas2016/media/sponsor_files/tripython-banner_478mQLr.svg" width="300">](http://trizpug.org/)
# 
# https://twitter.com/thewtex
# 
# Email: matt.mccormick@kitware.com
#