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Solve the following problem using Python, implementing the functions described below, one line at a time
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Description:
 def qderiv(array):
 # TAKE THE ABSOLUTE DERIVATIVE OF A NUMARRY OBJECT """Take the absolute derivate of an image in memory."""


    #Create 2 empty arrays in memory of the same dimensions as 'array'
    tmpArray = np.zeros(array.shape,dtype=np.float64)
    outArray = np.zeros(array.shape, dtype=np.float64)

    # Get the length of an array side
    (naxis1,naxis2) = array.shape
    #print "The input image size is (",naxis1,",",naxis2,")."

#Main derivate loop:
    #Shift images +/- 1 in Y.
    for y in range(-1,2,2):
        if y == -1:
            #shift input image 1 pixel right
            tmpArray[0:(naxis1-1),1:(naxis2-1)] = array[0:(naxis1-1),0:(naxis2-2)]
            #print "Y shift = 1"
        else:
            #shift input image 1 pixel left
            tmpArray[0:(naxis1-1),0:(naxis2-2)] = array[0:(naxis1-1),1:(naxis2-1)]
            #print "Y shift = -1"
        #print "call _absoluteSubtract()"
        (tmpArray,outArray) = _absoluteSubtract(array,tmpArray,outArray)

    #Shift images +/- 1 in X.
    for x in range(-1,2,2):
        if x == -1:
            #shift input image 1 pixel right
            tmpArray[1:(naxis1-1),0:(naxis2-1)] = array[0:(naxis1-2),0:(naxis2-1)]
            #print "X shift = 1"
        else:
            #shift input image 1 pixel left
            tmpArray[0:(naxis1-2),0:(naxis2-1)] = array[1:(naxis1-1),0:(naxis2-1)]
            #print "X shift = -1"
        #print "call _absoluteSubtract()"
        (tmpArray,outArray) = _absoluteSubtract(array,tmpArray,outArray)



    return outArray.astype(np.float32)