In [12]:

    

# this is a notebook


    

In [13]:

    

# we can write code
print("hello world")


    

    




hello world

In [62]:

    

import numpy as np
import matplotlib.pyplot as plt


    

In [63]:

    

x = np.linspace(0,3, num=100)


    

In [64]:

    

y = x + np.random.normal(loc=0, scale=1, size=100)


    

In [65]:

    

plt.plot(x, y, 'k.')


    

    
Out[65]:





[<matplotlib.lines.Line2D at 0x7f40b7378c10>]






    

In [68]:

    

np.linspace


    

    
Out[68]:





<function numpy.core.function_base.linspace>

In [69]:

    

np.linspace?


    

In [70]:

    

np.linspace??


    

In [73]:

    

#np.linspa#tab


    

In [72]:

    

#np.linspace(#shift tab)


    

In [76]:

    

import pandas
import requests
import io


    

In [83]:

    

response = requests.get('http://publicwiki.deltares.nl/download/attachments/90415361/RondeHoep.csv')
response.text[:20]


    

    
Out[83]:





u'"","Date","Period","'

In [84]:

    

df = pandas.read_csv(io.StringIO(response.text))


    

In [87]:

    

df.head()


    

    
Out[87]:






  

    

      

      
Unnamed: 0
      
Date
      
Period
      
Month
      
Location
      
EC
      
IR
    
  
  

    

      
0
      
 1
      
 25/10/2010
      
 Autumn
      
 10
      
 RH1
      
  47.862614
      
 44.478155
    
    

      
1
      
 2
      
  14/2/2011
      
 Winter
      
  2
      
 RH1
      
  35.134578
      
 51.520307
    
    

      
2
      
 3
      
   4/4/2011
      
 Spring
      
  4
      
 RH1
      
  43.660839
      
 45.420540
    
    

      
3
      
 4
      
   2/5/2011
      
 Spring
      
  5
      
 RH1
      
  56.480512
      
 45.802499
    
    

      
4
      
 5
      
   7/6/2011
      
 Summer
      
  6
      
 RH1
      
 219.040737
      
 22.484707
    
  

5 rows × 7 columns

In [104]:

    

_ = df.groupby('Period').plot('EC', 'IR', style='.')
# http://publicwiki.deltares.nl/display/VWD/Home


    

In [107]:

    

!ls


    

    




calc.py		diskless.ipynb	   G0113773.JPG       gopro.ipynb      nearest.ipynb		    peopledetect.ipynb	README.md	   test.py
checkers.ipynb	esmf regrid.ipynb  gabor.ipynb	      idiomatic.ipynb  notebookdemo.ipynb	    __pycache__		seaice.ipynb	   widgets.ipynb
cropped.jpg	fluid.ipynb	   geos regrid.ipynb  LICENSE	       people_comfort_forces.ipynb  ravensburger.ipynb	soapexample.ipynb

In [111]:

    

files = !ls


    

In [112]:

    

[f for f in files if not f.endswith('.ipynb')]


    

    
Out[112]:





['calc.py',
 'cropped.jpg',
 'G0113773.JPG',
 'LICENSE',
 '__pycache__',
 'README.md',
 'test.py']

In [114]:

    

!less cropped.jpg


    

    




cropped.jpg JPEG 1448x1048 1448x1048+0+0 8-bit DirectClass 230KB 0.000u 0:00.000
(END)

In [125]:

    

import IPython.display


    

In [135]:

    

IPython.display.Image('cropped.jpg', width=300)


    

    
Out[135]:

In [130]:

    

img = plt.imread('cropped.jpg')
plt.imshow(img)


    

    
Out[130]:





<matplotlib.image.AxesImage at 0x7f40a7f390d0>






    

In [124]:

    

import skimage.filter


    

    




Could not import matplotlib -- skimage.viewer not available.






    




/home/fedor/.virtualenvs/main/local/lib/python2.7/site-packages/skimage/viewer/qt/__init__.py:18: UserWarning: Could not import PyQt4: ImageViewer not available!
  warnings.warn("Could not import PyQt4: ImageViewer not available!")

In [134]:

    

# detect areas that are lighter than their surroundings
plt.imshow(skimage.filter.gaussian_filter(img, 6) - skimage.filter.gaussian_filter(img, 5))


    

    
Out[134]:





<matplotlib.image.AxesImage at 0x7f40a7cfec90>






    

In [141]:

    

from IPython.html.widgets import interact

def plot(sigma):
    plt.imshow(skimage.filter.gaussian_filter(img, sigma) - skimage.filter.gaussian_filter(img, sigma-1))

interact(plot, sigma=(3,7))


    

In [ ]: