def high_pass_median(numpy_arr, medscale):
"""Remove everything below 1/2 of the median
value."""
# remove noise
median = numpy.median(numpy_arr)
def hp(x, m):
return 0 if x < m else x
return numpy.vectorize(hp)(numpy_arr, median * medscale)
def get_average_line_height(top_bottoms):
"""Tricksy - get height of median line?
"""
lheights = [b - t for t, b in top_bottoms]
lhm = numpy.max(lheights)
def weight(val):
return 0 if val < (lhm / 2) else 1
weights = numpy.vectorize(weight)(lheights)
return numpy.average(numpy.array(lheights), weights=weights)
def high_pass_median(numpy_arr, medscale):
"""Remove everything below 1/2 of the median
value."""
# remove noise
median = numpy.median(numpy_arr)
def hp(x, m):
return 0 if x < m else x
return numpy.vectorize(hp)(numpy_arr, median * medscale)
def get_average_line_height(top_bottoms):
"""Tricksy - get height of median line?
"""
lheights = [b - t for t, b in top_bottoms]
lhm = numpy.max(lheights)
def weight(val):
return 0 if val < (lhm / 2) else 1
weights = numpy.vectorize(weight)(lheights)
return numpy.average(numpy.array(lheights), weights=weights)
