def peak_merger(maxima, minima, pdf, merge_criteria):
''' Merge any maxima that are closer than the minimum spacing
Lists are modified in place. The lower maxima is merged into the higher
one. Any minima between merged maxima are deleted
'''
for first_index, (max1, max2) in enumerate(consecutive_pairs(maxima)):
y_max1 = pdf(max1)
y_max2 = pdf(max2)
low_index = ((y_max1 < y_max2) and first_index or first_index+1)
# Check if these peaks need to be merged
if merge_criteria(max1, max2, y_max1, y_max2):
print "Merging", max1, max2
# Remove the lower maximum. It's okay to modify this inside the
# loop, as if the merge criteria is met the loop is always exited.
del maxima[low_index]
# Remove all minima between the two points
minima[:] = [min for min in minima if min < max1 or min > max2]
# Recurse down with the cleaner list
peak_merger(maxima, minima, pdf, merge_criteria)
# When done merging, escape this loop
return None
# If no merged candidates found, exit
return None
def make_choices(maxima, minima, prob_func, stepsize=5, growth_min=5e-4):
''' Build windows from set of maxima and minima
The windows will grow in both directions about the maxima, until they reach
a minima or the total change in integraged window area is less than growth_min
in the last step
'''
windows = izip(maxima, consecutive_pairs(minima))
# Loop over the windows to build
for start, (min, max) in windows:
last_area = 0.0
total_area = 0.0
# Grow the window in steps until we reach the end
low=None; high=None
for win_low, win_high in grow_window(start, min, max):
last_area = total_area
total_area = prob_func(win_low, win_high)
low = win_low; high = win_high
#if (total_area - last_area) < growth_min:
if (last_area/total_area) > (1 - growth_min):
# Move to next window
break
yield (low, high, total_area)
