Labeling alternating max/mins based on a user defined delta

Question

Given a set of values (points on a graph) find all the max/min points such that

• there is no max is followed by a max (i.e. the max and min points alternate)
• there is some minimum amount of change (C) between each max and min (.4 for this data set)
• the value of the minimums must be lower than the adjacent maximums

Here is what I have so far

import matplotlib.pyplot as plt
MAX = 1
MIN = -1
NEITHER = 0
def normalize(a):
 #this function is for graphing purposes
 min_ = min(a)
 max_ = max(a)
 d = max_ - min_
 a = [e - min_ for e in a]
 a = [e / d for e in a]
 return a
def compress(values, extrema):
 #identifies consecutive mins/maxs and takes the more extreme of the two
 prev_ext = None
 last_index = 0
 for i, ext in enumerate(extrema):
 if ext == NEITHER:
 continue
 if prev_ext is None:
 prev_ext = ext
 last_index = i
 continue
 cc = values[i]
 pc = values[last_index]
 if ext == prev_ext == MAX:
 if cc >= pc:
 extrema[last_index] = NEITHER
 else:
 extrema[i] = NEITHER
 if ext == prev_ext == MIN:
 if cc <= pc:
 extrema[last_index] = NEITHER
 else:
 extrema[i] = NEITHER
 if ext != NEITHER:
 last_index = i
 prev_ext = ext
 return extrema
def label(values, C=.4):
 #C is the amount that must change between two points for those points to
 #be considered extremes
 extrema = [NEITHER]
 prev = values[0]
 for curr in values[1:]:
 delta = abs(prev - curr)
 if curr > prev and delta > C:
 extrema.append(MAX)
 elif curr < prev and delta > C:
 extrema.append(MIN)
 else:
 extrema.append(NEITHER)
 prev = curr
 oldextrema = list(extrema)
 extrema = compress(values, extrema)
 while oldextrema != extrema:
 oldextrema = list(extrema)
 extrema = compress(values, extrema)
 #min_indicies = [i for i, e in enumerate(extrema) if e == MIN]
 #max_indicies = [i for i, e in enumerate(extrema) if e == MAX]
 return extrema
if __name__ == "__main__":
 values = [294.82, 294.85, 294.85, 294.83, 294.67, 294.77, 295.71,
 296.31, 296.07, 295.38, 295.83, 296.14, 296.2, 296.35,
 296.07, 296.35, 296.83, 296.9, 296.41, 296.49, 296.43,
 295.77, 295.75, 296.04, 296.12, 296.09, 296.16, 296.1,
 296.32, 296.24, 296.3, 296.5, 296.22, 296.16, 296.13,
 296.07, 296.09, 296.04, 296.29, 296.32, 296.31, 296.35,
 296.43, 296.6, 296.58, 296.4, 296.38, 296.6, 296.56,
 296.63, 296.72, 296.65, 296.69, 296.59, 296.56, 296.63,
 296.74, 296.75, 296.91, 296.81, 296.71, 296.78, 296.65,
 296.66, 296.71, 296.73, 296.89, 296.98, 297.19, 297.09,
 297.01, 296.95, 296.92, 297.0, 296.41, 296.39, 296.05,
 295.68, 295.11, 295.19, 295.3, 295.64, 295.53, 295.36,
 295.86, 295.75, 295.63, 295.65, 295.7, 295.61, 295.57,
 295.52, 295.54, 295.5, 295.44, 295.44, 295.82, 295.85,
 295.86, 296.09, 295.75, 295.41, 295.8, 296.2, 295.66,
 293.49, 293.4, 293.58, 294.37, 294.16, 295.13, 295.58,
 295.34, 295.35, 295.78, 295.87, 296.03, 296.32, 296.87,
 296.9, 296.87, 297.3, 296.98, 297.0, 296.87, 297.11,
 296.97, 297.1, 296.78, 296.72, 296.95, 297.04, 297.11,
 296.94, 296.88, 297.2, 297.04, 296.83, 297.08, 296.96,
 297.07, 296.85, 297.04, 296.93, 296.98, 296.92, 296.96,
 296.97, 296.89, 296.99, 296.94, 296.83, 296.75, 296.89,
 296.93, 296.92, 297.3, 297.12, 297.43]
 extrema = label(values)
 plt.plot(normalize(values))
 plt.plot(extrema)
 plt.show()

What I've written seems cumbersome and I'm fairly certain I'm not covering all the edge cases. I'm using numpy on this project but I couldn't find anything in numpy that would help me solve this (or more likely I found it but didn't comprehend). Is there a more concise way to write this? If there is anything I can do to clarify please don't hesitate to ask.

Answer 1

• The docstring is the common way of describing functions in Python.
• Especially in Math code, you should articulate a bit more the description of your functions.
• List comprehension can be joined together.
• Assigning max is not necessary as you use it only once.
• Some tests make development faster and code easier to read.
• You can return directly, without using an intermediate variable.
• Longer names are preferable: use delta instead of d:

Putting it all together:

def normalize(array):
 """
 Taking an array of numbers as input,
 numbers become from 0 to 1 while retaining their
 previous ratio.
 Especially useful for graphing purposes.
 >>> normalize(range(5))
 [0.0, 0.25, 0.5, 0.75, 1.0]
 >>> normalize([5,100,45])
 [0.0, 1.0, 0.42105263157894735]
 """
 min_ = min(array)
 delta = max(array) - min_
 return [(i - min_) / delta for i in array]