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Fixed last trend detection #18

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Fixed last trend detection #18

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3a9d716
fix: #12 fixed last trend detection.
jokaorgua Jan 17, 2022
024c995
fix: #11 fixed detecting the last trend in data and added 5 seconds t…
jokaorgua Jan 17, 2022
589461f
Merge remote-tracking branch 'origin/master'
jokaorgua Jan 17, 2022
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5 changes: 5 additions & 0 deletions tests/test_trendet.py
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Original file line number Diff line number Diff line change
@@ -1,5 +1,6 @@
# Copyright 2019-2020 Alvaro Bartolome
# See LICENSE for details.
import time

import pytest

Expand Down Expand Up @@ -94,6 +95,8 @@ def test_trendet():
trend_limit=param['trend_limit'],
labels=param['labels'],
identify=param['identify'])
# sleep for 5 seconds to avoid http code 429 error
time.sleep(5)

trendet.identify_all_trends(stock=param['stock'],
country=param['country'],
Expand Down Expand Up @@ -130,6 +133,8 @@ def test_trendet():
column=param['column'],
window_size=param['window_size'],
identify=param['identify'])
# sleep for 5 seconds to avoid http code 429 error
time.sleep(5)


if __name__ == '__main__':
Expand Down
20 changes: 12 additions & 8 deletions trendet/identification.py
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Original file line number Diff line number Diff line change
Expand Up @@ -361,11 +361,10 @@ def identify_all_trends(stock, country, from_date, to_date, window_size=5, ident

trends = list()

df_length = len(obj['element'])

for index, value in enumerate(obj['element'], 0):
if limit and limit > value:
values.append(value)
limit = mean(values)
elif limit and limit < value:
if limit and limit < value or index == df_length - 1:
if len(values) > window_size:
min_value = min(values)

Expand All @@ -384,6 +383,9 @@ def identify_all_trends(stock, country, from_date, to_date, window_size=5, ident

limit = None
values = list()
elif limit and limit > value:
values.append(value)
limit = mean(values)
else:
from_trend = index

Expand Down Expand Up @@ -547,11 +549,10 @@ def identify_df_trends(df, column, window_size=5, identify='both'):

trends = list()

df_length = len(obj['element'])

for index, value in enumerate(obj['element'], 0):
if limit and limit > value:
values.append(value)
limit = mean(values)
elif limit and limit < value:
if limit and limit < value or index == df_length -1:
if len(values) > window_size:
min_value = min(values)

Expand All @@ -570,6 +571,9 @@ def identify_df_trends(df, column, window_size=5, identify='both'):

limit = None
values = list()
elif limit and limit > value:
values.append(value)
limit = mean(values)
else:
from_trend = index

Expand Down