In [3]:
plt.plot(x,y)
Out[3]:
[<matplotlib.lines.Line2D at 0x7fc2836cc880>]
%matplotlib notebook
import matplotlib.pyplot as plt
import math, time, datetime
import numpy as np
from collections import Counter
# These parameters are to be tuned if you want different logarithmic 'curve'...
x=np.linspace(1,120,120)
y=1.09**x
plt.plot(x,y)
[<matplotlib.lines.Line2D at 0x7fc2836cc880>]
# Points (in hours). Round them and deduplicate:
tbl=set(np.floor(y).tolist()); tbl
{1.0,
2.0,
3.0,
4.0,
5.0,
6.0,
7.0,
8.0,
9.0,
10.0,
11.0,
12.0,
13.0,
14.0,
15.0,
17.0,
18.0,
20.0,
22.0,
24.0,
26.0,
28.0,
31.0,
34.0,
37.0,
40.0,
44.0,
48.0,
52.0,
57.0,
62.0,
68.0,
74.0,
81.0,
88.0,
96.0,
104.0,
114.0,
124.0,
135.0,
148.0,
161.0,
176.0,
191.0,
209.0,
227.0,
248.0,
270.0,
295.0,
321.0,
350.0,
382.0,
416.0,
454.0,
495.0,
539.0,
588.0,
641.0,
698.0,
761.0,
830.0,
905.0,
986.0,
1075.0,
1172.0,
1277.0,
1392.0,
1517.0,
1654.0,
1803.0,
1965.0,
2142.0,
2335.0,
2545.0,
2774.0,
3024.0,
3296.0,
3593.0,
3916.0,
4269.0,
4653.0,
5072.0,
5529.0,
6026.0,
6569.0,
7160.0,
7804.0,
8507.0,
9272.0,
10107.0,
11016.0,
12008.0,
13089.0,
14267.0,
15551.0,
16950.0,
18476.0,
20139.0,
21951.0,
23927.0,
26081.0,
28428.0,
30987.0}
# How many snapshots are to be kept?
len(tbl)
103
now=math.floor(time.time())
SECONDS_IN_HOUR=60*60
# Generate date/time points. Only one snapshot to be kept between each adjacent 'points'.
points=sorted(list(map(lambda x: datetime.datetime.fromtimestamp(now-x*SECONDS_IN_HOUR), tbl))); points
[datetime.datetime(2018, 9, 18, 9, 56, 10), datetime.datetime(2019, 1, 2, 23, 56, 10), datetime.datetime(2019, 4, 10, 19, 56, 10), datetime.datetime(2019, 7, 9, 13, 56, 10), datetime.datetime(2019, 9, 29, 21, 56, 10), datetime.datetime(2019, 12, 14, 8, 56, 10), datetime.datetime(2020, 2, 21, 15, 56, 10), datetime.datetime(2020, 4, 25, 6, 56, 10), datetime.datetime(2020, 6, 22, 13, 56, 10), datetime.datetime(2020, 8, 15, 1, 56, 10), datetime.datetime(2020, 10, 3, 3, 56, 10), datetime.datetime(2020, 11, 17, 3, 56, 10), datetime.datetime(2020, 12, 28, 11, 56, 10), datetime.datetime(2021, 2, 4, 8, 56, 10), datetime.datetime(2021, 3, 11, 3, 56, 10), datetime.datetime(2021, 4, 12, 1, 56, 10), datetime.datetime(2021, 5, 11, 8, 56, 10), datetime.datetime(2021, 6, 7, 4, 56, 10), datetime.datetime(2021, 7, 1, 19, 56, 10), datetime.datetime(2021, 7, 24, 10, 56, 10), datetime.datetime(2021, 8, 14, 3, 56, 10), datetime.datetime(2021, 9, 2, 4, 56, 10), datetime.datetime(2021, 9, 19, 15, 56, 10), datetime.datetime(2021, 10, 5, 15, 56, 10), datetime.datetime(2021, 10, 20, 8, 56, 10), datetime.datetime(2021, 11, 2, 18, 56, 10), datetime.datetime(2021, 11, 15, 3, 56, 10), datetime.datetime(2021, 11, 26, 11, 56, 10), datetime.datetime(2021, 12, 6, 21, 56, 10), datetime.datetime(2021, 12, 16, 10, 56, 10), datetime.datetime(2021, 12, 25, 4, 56, 10), datetime.datetime(2022, 1, 2, 5, 56, 10), datetime.datetime(2022, 1, 9, 14, 56, 10), datetime.datetime(2022, 1, 16, 8, 56, 10), datetime.datetime(2022, 1, 22, 13, 56, 10), datetime.datetime(2022, 1, 28, 6, 56, 10), datetime.datetime(2022, 2, 2, 11, 56, 10), datetime.datetime(2022, 2, 7, 6, 56, 10), datetime.datetime(2022, 2, 11, 15, 56, 10), datetime.datetime(2022, 2, 15, 16, 56, 10), datetime.datetime(2022, 2, 19, 9, 56, 10), datetime.datetime(2022, 2, 22, 18, 56, 10), datetime.datetime(2022, 2, 25, 21, 56, 10), datetime.datetime(2022, 2, 28, 18, 56, 10), datetime.datetime(2022, 3, 3, 9, 56, 10), datetime.datetime(2022, 3, 5, 18, 56, 10), datetime.datetime(2022, 3, 7, 23, 56, 10), datetime.datetime(2022, 3, 10, 0, 56, 10), datetime.datetime(2022, 3, 11, 20, 56, 10), datetime.datetime(2022, 3, 13, 13, 56, 10), datetime.datetime(2022, 3, 15, 3, 56, 10), datetime.datetime(2022, 3, 16, 13, 56, 10), datetime.datetime(2022, 3, 17, 21, 56, 10), datetime.datetime(2022, 3, 19, 2, 56, 10), datetime.datetime(2022, 3, 20, 4, 56, 10), datetime.datetime(2022, 3, 21, 5, 56, 10), datetime.datetime(2022, 3, 22, 3, 56, 10), datetime.datetime(2022, 3, 23, 0, 56, 10), datetime.datetime(2022, 3, 23, 18, 56, 10), datetime.datetime(2022, 3, 24, 12, 56, 10), datetime.datetime(2022, 3, 25, 3, 56, 10), datetime.datetime(2022, 3, 25, 18, 56, 10), datetime.datetime(2022, 3, 26, 7, 56, 10), datetime.datetime(2022, 3, 26, 20, 56, 10), datetime.datetime(2022, 3, 27, 8, 56, 10), datetime.datetime(2022, 3, 27, 18, 56, 10), datetime.datetime(2022, 3, 28, 4, 56, 10), datetime.datetime(2022, 3, 28, 12, 56, 10), datetime.datetime(2022, 3, 28, 20, 56, 10), datetime.datetime(2022, 3, 29, 3, 56, 10), datetime.datetime(2022, 3, 29, 10, 56, 10), datetime.datetime(2022, 3, 29, 16, 56, 10), datetime.datetime(2022, 3, 29, 22, 56, 10), datetime.datetime(2022, 3, 30, 3, 56, 10), datetime.datetime(2022, 3, 30, 8, 56, 10), datetime.datetime(2022, 3, 30, 12, 56, 10), datetime.datetime(2022, 3, 30, 16, 56, 10), datetime.datetime(2022, 3, 30, 20, 56, 10), datetime.datetime(2022, 3, 30, 23, 56, 10), datetime.datetime(2022, 3, 31, 2, 56, 10), datetime.datetime(2022, 3, 31, 5, 56, 10), datetime.datetime(2022, 3, 31, 8, 56, 10), datetime.datetime(2022, 3, 31, 10, 56, 10), datetime.datetime(2022, 3, 31, 12, 56, 10), datetime.datetime(2022, 3, 31, 14, 56, 10), datetime.datetime(2022, 3, 31, 16, 56, 10), datetime.datetime(2022, 3, 31, 18, 56, 10), datetime.datetime(2022, 3, 31, 19, 56, 10), datetime.datetime(2022, 3, 31, 21, 56, 10), datetime.datetime(2022, 3, 31, 22, 56, 10), datetime.datetime(2022, 3, 31, 23, 56, 10), datetime.datetime(2022, 4, 1, 0, 56, 10), datetime.datetime(2022, 4, 1, 1, 56, 10), datetime.datetime(2022, 4, 1, 2, 56, 10), datetime.datetime(2022, 4, 1, 3, 56, 10), datetime.datetime(2022, 4, 1, 4, 56, 10), datetime.datetime(2022, 4, 1, 5, 56, 10), datetime.datetime(2022, 4, 1, 6, 56, 10), datetime.datetime(2022, 4, 1, 7, 56, 10), datetime.datetime(2022, 4, 1, 8, 56, 10), datetime.datetime(2022, 4, 1, 9, 56, 10), datetime.datetime(2022, 4, 1, 10, 56, 10), datetime.datetime(2022, 4, 1, 11, 56, 10)]
# Snapshots kept, per each year:
Counter(map(lambda x: x.year, points))
Counter({2018: 1, 2019: 5, 2020: 7, 2021: 18, 2022: 72})
# Snapshots kept, per each month:
Counter(map(lambda x: x.year*100 + x.month, points))
Counter({201809: 1,
201901: 1,
201904: 1,
201907: 1,
201909: 1,
201912: 1,
202002: 1,
202004: 1,
202006: 1,
202008: 1,
202010: 1,
202011: 1,
202012: 1,
202102: 1,
202103: 1,
202104: 1,
202105: 1,
202106: 1,
202107: 2,
202108: 1,
202109: 2,
202110: 2,
202111: 3,
202112: 3,
202201: 5,
202202: 8,
202203: 47,
202204: 12})
# Snapshots kept, per each day:
Counter(map(lambda x: x.year*10000 + x.month*100 +x.day, points))
Counter({20180918: 1,
20190102: 1,
20190410: 1,
20190709: 1,
20190929: 1,
20191214: 1,
20200221: 1,
20200425: 1,
20200622: 1,
20200815: 1,
20201003: 1,
20201117: 1,
20201228: 1,
20210204: 1,
20210311: 1,
20210412: 1,
20210511: 1,
20210607: 1,
20210701: 1,
20210724: 1,
20210814: 1,
20210902: 1,
20210919: 1,
20211005: 1,
20211020: 1,
20211102: 1,
20211115: 1,
20211126: 1,
20211206: 1,
20211216: 1,
20211225: 1,
20220102: 1,
20220109: 1,
20220116: 1,
20220122: 1,
20220128: 1,
20220202: 1,
20220207: 1,
20220211: 1,
20220215: 1,
20220219: 1,
20220222: 1,
20220225: 1,
20220228: 1,
20220303: 1,
20220305: 1,
20220307: 1,
20220310: 1,
20220311: 1,
20220313: 1,
20220315: 1,
20220316: 1,
20220317: 1,
20220319: 1,
20220320: 1,
20220321: 1,
20220322: 1,
20220323: 2,
20220324: 1,
20220325: 2,
20220326: 2,
20220327: 2,
20220328: 3,
20220329: 4,
20220330: 6,
20220331: 12,
20220401: 12})