In [1]:

    

import pandas as pd
import skgstat as skg
import numpy as np


    

In [2]:

    

xy = pd.read_csv('radar_xy.csv', header=None)
xy.columns = ['x', 'y']
xy.head()

rad24 = pd.read_csv('./radar_sent/radar_snap_24h_2011_08_05-00_00.csv', header=None)
rad24 = rad24.iloc[0,5:1000]
rad24.index = np.arange(0,len(rad24),1)


    

In [3]:

    

wet = rad24>0


    

In [7]:

    

coords = np.array(xy)
coords = coords[0:995]


    

In [8]:

    

data = np.array(rad24)


    

In [6]:

    

len(wet)


    

    
Out[6]:





995

In [9]:

    

len(coords)


    

    
Out[9]:





995

In [10]:

    

from scipy.spatial.distance import pdist, squareform


    

In [11]:

    

distances = squareform(pdist(coords[wet]))


    

In [12]:

    

lags = np.arange(2, 100, 2)


    

In [13]:

    

lags


    

    
Out[13]:





array([ 2,  4,  6,  8, 10, 12, 14, 16, 18, 20, 22, 24, 26, 28, 30, 32, 34,
       36, 38, 40, 42, 44, 46, 48, 50, 52, 54, 56, 58, 60, 62, 64, 66, 68,
       70, 72, 74, 76, 78, 80, 82, 84, 86, 88, 90, 92, 94, 96, 98])

In [10]:

    

#bm = skg.binning.binify_even_width(coords[wet], w=2, maxlag=100)


    

In [15]:

    

len(coords[wet])


    

    
Out[15]:





19589

In [18]:

    

V = skg.Variogram(coordinates=coords[wet], values=data[wet], maxlag=100, N=5, is_directional=True)


    

In [19]:

    

print(V)


    

    




spherical Variogram
-------------------
Estimator:  matheron
Range:      20.02
Sill:       1.42
Nugget:     0.00







    




/home/kriete/.virtualenvs/cie5703/lib/python3.5/site-packages/scipy/optimize/minpack.py:779: OptimizeWarning: Covariance of the parameters could not be estimated
  category=OptimizeWarning)

In [20]:

    

V.hist


    

    
Out[20]:





array([ 16243.,      0.,      0.,      0.,      0.])

In [49]:

    

V.experimental()


    

    




---------------------------------------------------------------------------
KeyboardInterrupt                         Traceback (most recent call last)
<ipython-input-49-3dac1a2ffd8f> in <module>()
----> 1 V.experimental()

~/.virtualenvs/cie5703/lib/python3.5/site-packages/skgstat/Variogram.py in experimental(self)
    296         """
    297         # group the values to bins and apply the estimator
--> 298         _g = self.grouped_pairs
    299 
    300         # apply

~/.virtualenvs/cie5703/lib/python3.5/site-packages/skgstat/Variogram.py in grouped_pairs(self)
    313                                 maxlag=self.maxlag)
    314         else:
--> 315             return group_to_bin(self.values, self.bm, maxlag=self.maxlag)
    316 
    317 

~/.virtualenvs/cie5703/lib/python3.5/site-packages/skgstat/binning.py in group_to_bin(values, bm, X, azimuth_deg, tolerance, maxlag, **kwargs)
    212                     bin_grp[_bm[i, j]].extend(list(np.array(list(zip(values[i], values[j]))).flatten()))
    213                 else:
--> 214                     bin_grp[_bm[i, j]].extend([values[i], values[j]])
    215 
    216     # return

KeyboardInterrupt: 

In [ ]: