This notebook walks through some simple image display and maniputlation using the IPython notebook widgets with IPython 2.0 and Python 2.7



In [1]:

    
%matplotlib inline
from IPython.html import widgets
import matplotlib.pylab as plt
import numpy as np



In [2]:

    
x=np.random.rand(100) * np.ones((100,100))
y=np.random.rand(100) * np.ones((100,100))
plt.imshow(x)









    Out[2]:





<matplotlib.image.AxesImage at 0x107d687d0>



In [3]:

    
plt.imshow(y)









    Out[3]:





<matplotlib.image.AxesImage at 0x107d9fa90>



In [4]:

    
#some fits data to work with
from astropy.io import fits
space=fits.getdata('iabf01bzq_flt.fits')
z=space[0:x.shape[0],0:x.shape[1]]
plt.imshow(z,cmap=plt.cm.gray)









    Out[4]:





<matplotlib.image.AxesImage at 0x10868a950>



In [5]:

    
images=[x,y]

def on_click(blink_image):
    plt.imshow(images[blink_image],cmap=plt.cm.gray)

widgets.interact(on_click, blink_image = widgets.ToggleButtonWidget(min=0,max=2))









    Out[5]:





<function __main__.on_click>



In [6]:

    
#view images in a list with a slider
ims=[x,y,z]

def slide_image(images):
    num=len(ims)
    def view_image(i):
        plt.imshow(images[i],cmap=plt.cm.gray)
    widgets.interact(view_image,i=(0,num-1))
    
slide_image(ims)

I don't know why the slider wideget below is mostly ignoring the limits I gave it, it could be the versions I wrote this example with or I've missed something. I'll try this in the latest versions of widgets with python3 to see if it goes away



In [7]:

    
#now lets try scaling the image live
scaled = widgets.IntSliderWidget(description="Scale", value=1,min=1,max=15,step=1)

#simplistic, level of std scaling 
def scale_image(image):
    middle=np.median(image)
    std=np.std(image)
    def view_image(amount) :       
        _imin=middle-std*amount
        _imax=middle+std*amount
        plt.imshow(image,vmin=_imin, vmax=_imax,cmap=plt.cm.gray)
    widgets.interact(view_image,amount=(scaled.value))
    

scale_image(z)



In [7]: