In [1]:

    

%matplotlib inline


    

In [2]:

    

import numpy as np
import matplotlib.pyplot as plt
import h5py
import ipywidgets
plt.rcParams["figure.figsize"] = (12,10)


    

In [3]:

    

scan_file = h5py.File("data-readonly/single_dicom.h5", "r")
scan = scan_file["/scan"].value


    

In [4]:

    

scan.shape


    

    
Out[4]:





(36, 512, 512)

In [5]:

    

image = scan[19,::,::]


    

In [6]:

    

image.shape


    

    
Out[6]:





(512, 512)

In [7]:

    

plt.imshow(image)


    

    
Out[7]:





<matplotlib.image.AxesImage at 0x7f707dade1d0>






    

In [8]:

    

plt.imshow(image, extent=[0.0, 1.0, 0., 0.5])


    

    
Out[8]:





<matplotlib.image.AxesImage at 0x7f707d8bb160>






    

In [9]:

    

image.max()


    

    
Out[9]:





1268.0

In [10]:

    

image2 = image.copy()
image2[:50, :50] = 1268


    

In [11]:

    

plt.imshow(image2, extent = [0, 1, 0., 0.5])


    

    
Out[11]:





<matplotlib.image.AxesImage at 0x7f707d7c9668>






    

In [12]:

    

scan.min(), scan.max()


    

    
Out[12]:





(0.0, 1747.0)

In [13]:

    

from matplotlib.colors import LogNorm, PowerNorm


    

In [14]:

    

def make_plot(position, gamma, cmap):
    image = scan[position, :, :]
    plt.imshow(image, cmap=cmap, norm=PowerNorm(gamma))
    plt.colorbar()
    plt.clim(1, 1747.0)


    

In [15]:

    

ipywidgets.interact(make_plot, position = (0, 35, 1), gamma = (0.0, 1.0, 0.01),
                   cmap = ["viridis", "magma", "plasma", "inferno", "jet",
                          "doom", "dusk", "arbre", "octarine"]
                   )


    

    






 
 










    
Out[15]:





<function __main__.make_plot>

In [16]:

    

arr = np.fromfile("data-readonly/michigan_lld/michigan_lld.flt", dtype="f4")
lmi = arr.reshape((4201, 5365), order="F").transpose()
lake = np.ma.MaskedArray(lmi, mask = (lmi == -9999))


    

In [17]:

    

plt.imshow(lake)


    

    
Out[17]:





<matplotlib.image.AxesImage at 0x7f707c5209b0>






    

In [18]:

    

lake.min()


    

    
Out[18]:





-275.89001

In [19]:

    

lake.max()


    

    
Out[19]:





351.94348

In [20]:

    

plt.imshow(lake, cmap="coolwarm")
plt.colorbar()
val = max(np.abs(lake.min()), lake.max())
plt.clim(-val, val)


    

In [ ]: