In [86]:

    

from __future__ import division
import numpy as np
import matplotlib.pyplot as plt
import ctypes
import c2raytools as c2t


    

In [87]:

    

# the data we want to analyse, a 3D array of floats
uv = c2t.read_cbin('/home/gorgel/Documents/C2ray/dtbox_smth7.96.cbin')

# the size of the data we want to analyse, a 1D array of three integers (same as the -x -y -z options)
usizev = np.array([504,504,504])

# integer: number of bins to use (same as -b option)
numbins = int(2)

#float: lowest value of threshold (same as -l option)
low = float(1)

# float: highest values of threshold (same as -h option)
high = float(20) 

# vsumv - the output, a 3D array of floats. The size is (3,numbins+1,5)


    

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In [90]:

    

def mink(input_array, array_size, nr_bins, low, high):
    lib_file = '/home/gorgel/Dropbox/simon/plugg/masterarbete/minkowski_files/MINKOWSKI2_PY/testpython/Minkowski_python/minkowski_python.so'
    lib = ctypes.cdll.LoadLibrary(lib_file)
    func = lib.minkowski
    input_array = input_array.astype('double')
    output_array = np.zeros((3,nr_bins+1,5), dtype=np.double)
    output_array = func(ctypes.c_void_p(input_array.ctypes.data), ctypes.c_void_p(array_size.ctypes.data),\
         ctypes.c_int(nr_bins), ctypes.c_float(low) , ctypes.c_float(high) ,ctypes.c_void_p(output_array.ctypes.data))

    return output_array


    

In [91]:

    

A = mink(uv, usizev, numbins, high, low)


    

In [92]:

    

A


    

    
Out[92]:





2

In [83]:

    

low


    

    
Out[83]:





1.0

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