Module combine

median() nominally computes the median pixels for a stack of
identically shaped images.

arrays     specifies a sequence of inputs arrays, which are nominally a
           stack of identically shaped images.

output     may be used to specify the output array.  If none is specified,
           either arrays[0] is copied or a new array of type 'outtype'
           is created.

outtype    specifies the type of the output array when no 'output' is
           specified.

nlow       specifies the number of pixels to be excluded from median
           on the low end of the pixel stack.

nhigh      specifies the number of pixels to be excluded from median
           on the high end of the pixel stack.

badmasks   specifies boolean arrays corresponding to 'arrays', where true
           indicates that a particular pixel is not to be included in the
           median calculation.

>>> a = num.arange(4)
>>> a = a.reshape((2,2))
>>> arrays = [a*16, a*4, a*2, a*8]
>>> median(arrays)
array([[ 0,  6],
       [12, 18]])
>>> median(arrays, nhigh=1)
array([[ 0,  4],
       [ 8, 12]])
>>> median(arrays, nlow=1)
array([[ 0,  8],
       [16, 24]])
>>> median(arrays, outtype=num.float32)
array([[  0.,   6.],
       [ 12.,  18.]], dtype=float32)
>>> bm = num.zeros((4,2,2), dtype=num.bool8)
>>> bm[2,...] = 1
>>> median(arrays, badmasks=bm)
array([[ 0,  8],
       [16, 24]])
>>> median(arrays, badmasks=threshhold(arrays, high=25))
array([[ 0,  6],
       [ 8, 12]])

average() nominally computes the average pixel value for a stack of
identically shaped images.

arrays     specifies a sequence of inputs arrays, which are nominally a
           stack of identically shaped images.

output     may be used to specify the output array.  If none is specified,
           either arrays[0] is copied or a new array of type 'outtype'
           is created.

outtype    specifies the type of the output array when no 'output' is
           specified.

nlow       specifies the number of pixels to be excluded from average
           on the low end of the pixel stack.

nhigh      specifies the number of pixels to be excluded from average
           on the high end of the pixel stack.

badmasks   specifies boolean arrays corresponding to 'arrays', where true
           indicates that a particular pixel is not to be included in the
           average calculation.

>>> a = num.arange(4)
>>> a = a.reshape((2,2))
>>> arrays = [a*16, a*4, a*2, a*8]
>>> average(arrays)
array([[ 0,  7],
       [15, 22]])
>>> average(arrays, nhigh=1)
array([[ 0,  4],
       [ 9, 14]])
>>> average(arrays, nlow=1)
array([[ 0,  9],
       [18, 28]])
>>> average(arrays, outtype=num.float32)
array([[  0. ,   7.5],
       [ 15. ,  22.5]], dtype=float32)
>>> bm = num.zeros((4,2,2), dtype=num.bool8)
>>> bm[2,...] = 1
>>> average(arrays, badmasks=bm)
array([[ 0,  9],
       [18, 28]])
>>> average(arrays, badmasks=threshhold(arrays, high=25))
array([[ 0,  7],
       [ 9, 14]])

minimum() nominally computes the minimum pixel value for a stack of
identically shaped images.

arrays     specifies a sequence of inputs arrays, which are nominally a
           stack of identically shaped images.

output     may be used to specify the output array.  If none is specified,
           either arrays[0] is copied or a new array of type 'outtype'
           is created.

outtype    specifies the type of the output array when no 'output' is
           specified.

nlow       specifies the number of pixels to be excluded from minimum
           on the low end of the pixel stack.

nhigh      specifies the number of pixels to be excluded from minimum
           on the high end of the pixel stack.

badmasks   specifies boolean arrays corresponding to 'arrays', where true
           indicates that a particular pixel is not to be included in the
           minimum calculation.

>>> a = num.arange(4)
>>> a = a.reshape((2,2))
>>> arrays = [a*16, a*4, a*2, a*8]
>>> minimum(arrays)
array([[0, 2],
       [4, 6]])
>>> minimum(arrays, nhigh=1)
array([[0, 2],
       [4, 6]])
>>> minimum(arrays, nlow=1)
array([[ 0,  4],
       [ 8, 12]])
>>> minimum(arrays, outtype=num.float32)
array([[ 0.,  2.],
       [ 4.,  6.]], dtype=float32)
>>> bm = num.zeros((4,2,2), dtype=num.bool8)
>>> bm[2,...] = 1
>>> minimum(arrays, badmasks=bm)
array([[ 0,  4],
       [ 8, 12]])
>>> minimum(arrays, badmasks=threshhold(arrays, low=10))
array([[ 0, 16],
       [16, 12]])

threshhold() computes a boolean array 'outputs' with corresponding elements for each element of arrays. The boolean value is true where each of the arrays values is < the low or >= the high threshholds.

>>> a=num.arange(100)
>>> a=a.reshape((10,10))
>>> (threshhold(a, 1, 50)).astype(num.int8)
array([[1, 0, 0, 0, 0, 0, 0, 0, 0, 0],
       [0, 0, 0, 0, 0, 0, 0, 0, 0, 0],
       [0, 0, 0, 0, 0, 0, 0, 0, 0, 0],
       [0, 0, 0, 0, 0, 0, 0, 0, 0, 0],
       [0, 0, 0, 0, 0, 0, 0, 0, 0, 0],
       [1, 1, 1, 1, 1, 1, 1, 1, 1, 1],
       [1, 1, 1, 1, 1, 1, 1, 1, 1, 1],
       [1, 1, 1, 1, 1, 1, 1, 1, 1, 1],
       [1, 1, 1, 1, 1, 1, 1, 1, 1, 1],
       [1, 1, 1, 1, 1, 1, 1, 1, 1, 1]], dtype=int8)
>>> (threshhold([ range(10)]*10, 3, 7)).astype(num.int8)
array([[1, 1, 1, 0, 0, 0, 0, 1, 1, 1],
       [1, 1, 1, 0, 0, 0, 0, 1, 1, 1],
       [1, 1, 1, 0, 0, 0, 0, 1, 1, 1],
       [1, 1, 1, 0, 0, 0, 0, 1, 1, 1],
       [1, 1, 1, 0, 0, 0, 0, 1, 1, 1],
       [1, 1, 1, 0, 0, 0, 0, 1, 1, 1],
       [1, 1, 1, 0, 0, 0, 0, 1, 1, 1],
       [1, 1, 1, 0, 0, 0, 0, 1, 1, 1],
       [1, 1, 1, 0, 0, 0, 0, 1, 1, 1],
       [1, 1, 1, 0, 0, 0, 0, 1, 1, 1]], dtype=int8)
>>> (threshhold(a, high=50)).astype(num.int8)
array([[0, 0, 0, 0, 0, 0, 0, 0, 0, 0],
       [0, 0, 0, 0, 0, 0, 0, 0, 0, 0],
       [0, 0, 0, 0, 0, 0, 0, 0, 0, 0],
       [0, 0, 0, 0, 0, 0, 0, 0, 0, 0],
       [0, 0, 0, 0, 0, 0, 0, 0, 0, 0],
       [1, 1, 1, 1, 1, 1, 1, 1, 1, 1],
       [1, 1, 1, 1, 1, 1, 1, 1, 1, 1],
       [1, 1, 1, 1, 1, 1, 1, 1, 1, 1],
       [1, 1, 1, 1, 1, 1, 1, 1, 1, 1],
       [1, 1, 1, 1, 1, 1, 1, 1, 1, 1]], dtype=int8)
>>> (threshhold(a, low=50)).astype(num.int8)
array([[1, 1, 1, 1, 1, 1, 1, 1, 1, 1],
       [1, 1, 1, 1, 1, 1, 1, 1, 1, 1],
       [1, 1, 1, 1, 1, 1, 1, 1, 1, 1],
       [1, 1, 1, 1, 1, 1, 1, 1, 1, 1],
       [1, 1, 1, 1, 1, 1, 1, 1, 1, 1],
       [0, 0, 0, 0, 0, 0, 0, 0, 0, 0],
       [0, 0, 0, 0, 0, 0, 0, 0, 0, 0],
       [0, 0, 0, 0, 0, 0, 0, 0, 0, 0],
       [0, 0, 0, 0, 0, 0, 0, 0, 0, 0],
       [0, 0, 0, 0, 0, 0, 0, 0, 0, 0]], dtype=int8)