用于改变散景图像图中使用的切片的交互式滑块

Question

我有兴趣使用Bokeh将图像放入IPython笔记本中.特别是我经常与之交互的数据类型是具有3个或更多维度的多维NumPy数组.以三维数组为例.经常遇到的例子是RGB图像.这三个维度x,y以及color

我有兴趣使用Bokeh在IPython笔记本中绘制单个图像通道.我想提供一个交互式滑块,允许IPython笔记本的用户点击第三维的每个索引,在本例中为颜色.

我下面的代码(在IPython笔记本中运行时)成功显示了第一个颜色通道的图.但我无法弄清楚在我的电话中导致错误的原因interact.我ColumnDataSource是否在Bokeh图构造中正确定义并正确引用了？

# imports
import numpy as np
from scipy.misc import imread

from bokeh.plotting import figure, show
from bokeh.io import output_notebook
from bokeh.models import ColumnDataSource
from bokeh.palettes import Greys9

from IPython.html.widgets import interact

---

# enable Bokeh to plot to the notebook 
output_notebook()

# Make the Bokeh plot of the "first" layer of the 3D data
## This part works
TOOLS="pan, box_zoom, reset, save"

  # The image from https://windycitizensports.files.wordpress.com/2011/10/baboon.jpg?w=595
RGB_image = imread('/Users/curt/Downloads/BaboonRGB.jpg')

nx, ny, n_colors = RGB_image.shape

source = ColumnDataSource(data={'image': RGB_image[:, :, 0]})

p = figure(title="ColorChannel", 
           tools=TOOLS, 
           x_range=[0, nx], 
           y_range=[0, ny],
          )

p.image([source.data['image'][::-1, :]-1],
        x=0, 
        y=0, 
        dh=[ny], 
        dw=[nx], 
        palette=Greys9,
        source=source,
        )

show(p)

---

# try to add interactive slider
## This part does not work & gives a JavaScript error

def update(idx=0):
    global RGB_image
    source.data['image'] = RGB_image[:, :, idx]
    source.push_notebook()

interact(update, idx=(0, 2))

Javascript错误是:

Javascript error adding output!
TypeError: Failed to execute 'getImageData' on 'CanvasRenderingContext2D': The provided float value is non-finite.
See your browser Javascript console for more details.

我不确定这是怎么回事.我在定义之后立即尝试强制RGB_Image执行浮动,RGB_Image = RGB_Image.astype(float)但是我得到了同样的错误.

Answer 1

实质上,您的预定义图像与您尝试更新的图像之间的数据格式不一致.

有效的解决方法:

def update(idx=0):
    global RGB_image
    source.data['image'] = RGB_image[:, :, idx]
    p.image([source.data['image'][::-1, :]-1],
        x=0, 
        y=0, 
        dh=[ny], 
        dw=[nx], 
        palette=Greys9,
        source=source,
        )
    show(p)

interact(update, idx=(0, 2))

我会承认,一遍又一遍地定义图像并不是这样做的首选方法,但至少应该让你知道在哪里看.