Reputation: 801
I have a list of elements with certain values of type float. I want to iterate over the elements and count them if they are over a certain value, but also only count them if they appear over the treshold value a minimum_count of times. So for example, if a have following input:
list_of_values = [2.0, 2.0, 2.0, 2.0, 0, 0, 2.0, 2.0, 2.0, 0, 0]
treshold_value = 1.0
minimum_count = 4
the answer should be 4, since the treshold_value 1.0 is consecutively exceeded 4 times only at indexes 0-3. I now have the code below,
for value in list_of_values:
if value >= treshold_value:
counter += 1
if counter >= (minimum_count):
time_use += 1
if value < min_treshold_value:
counter = 0
print(time_use)
I know there should be some pythonic way to achieve this :)
Edit: The sum of all consecutive subsequence values over the threshold should be counted.
Upvotes: 3
Views: 665
Reputation: 87084
You could use itertools.groupby()
to help:
from itertools import groupby
def count_runs(list_of_values, threshold_value=1.0, minimum_count=4):
count = 0
for k, g in groupby(list_of_values, key=lambda x: x >= threshold_value):
if k:
g = list(g)
if len(g) >= minimum_count:
count += len(g)
return count
>>> count_runs([2.0, 2.0, 2.0, 0.0, 0, 0, 2.0, 2.0, 2.0, 0, 0])
0
>>> count_runs([2.0, 2.0, 2.0, 2.0, 0, 0, 2.0, 2.0, 2.0, 0, 0])
4
>>> count_runs([2.0, 2.0, 2.0, 2.0, 0, 0, 3.0, 2.0, 2.0, 2.0, 10.0, 0, 0])
9
This will provide the count of the number of values that are above the threshold in groups of minimum_count
or more. Note that it handles multiple groups that match the criteria.
For example the groupby()
for the last example will return the following:
>>> list_of_values = [2.0, 2.0, 2.0, 2.0, 0, 0, 3.0, 2.0, 2.0, 2.0, 10.0, 0, 0]
>>> for k, g in groupby(list_of_values, key=lambda x: x >= threshold_value):
... print(k, list(g))
...
True [2.0, 2.0, 2.0, 2.0]
False [0, 0]
True [3.0, 2.0, 2.0, 2.0, 10.0]
False [0, 0]
Any group of 1 or more values >= the threshold will appear in a group with key True
. Only those with a length >= the minimum count will be considered further, where its length will be tallied with other such groups.
This code can be written more succinctly, and far less readably, like this:
def count_runs(list_of_values, threshold_value=1.0, minimum_count=4):
return sum(count for count in (len(list(g)) for k, g in groupby(list_of_values, key=lambda x: x >= threshold_value) if k) if count >= minimum_count)
Upvotes: 1
Reputation: 54233
It looks like you don't care about the order. In this case, groupby
isn't correct because it only groups adjacent elements.
You could use a Counter and two list comprehensions to filter values:
list_of_values = [2.0, 2.0, 2.0, 2.0, 0, 0, 3.0, 2.0, 2.0, 2.0, 10.0, 0, 0]
threshold_value = 1.0
minimum_count = 4
from collections import Counter
counter = Counter([x for x in list_of_values if x > threshold_value])
print(counter)
# Counter({2.0: 7, 3.0: 1, 10.0: 1})
print([(x, count) for x, count in counter.items() if count > minimum_count])
# [(2.0, 7)]
Upvotes: 0
Reputation: 73460
The following use of groupby
with a conditional generator and max
with appropriate key function should work:
from itertools import groupby
len(max((list(g) for k, g in groupby(list_ov, key=lambda x: x > threshold) if k), key=len))
groupby
groups an iterable by consecutive identical values wrt to the key function. It produces pairs of the key value and according sub-iterable.
Upvotes: 2
Reputation: 1628
just iterate over the list and create a dictionary with key = the float number and value = the number of times you encounter this number. and only add to dict floats that are greater then threshold . something like this:
d = {}
for f in list_of_values :
if f > treshold:
if d.get(f,False):
d[f] +=1
else:
d[f] = 1
max = 0
for k,v in d.iteritems():
if v> max:
max = v
return max
Upvotes: 0