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https://github.com/wassname/pytorch-ts.git
synced 2026-07-10 09:56:26 +08:00
Dr. Kashif Rasul
52 lines
1.4 KiB
Python
52 lines
1.4 KiB
Python
import re
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from typing import Tuple
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from functools import lru_cache
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def get_granularity(freq_str: str) -> Tuple[int, str]:
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"""
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Splits a frequency string such as "7D" into the multiple 7 and the base
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granularity "D".
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Parameters
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----------
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freq_str
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Frequency string of the form [multiple][granularity] such as "12H", "5min", "1D" etc.
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"""
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freq_regex = r"\s*((\d+)?)\s*([^\d]\w*)"
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m = re.match(freq_regex, freq_str)
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assert m is not None, "Cannot parse frequency string: %s" % freq_str
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groups = m.groups()
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multiple = int(groups[1]) if groups[1] is not None else 1
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granularity = groups[2]
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return multiple, granularity
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@lru_cache()
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def get_seasonality(freq: str) -> int:
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"""
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Returns the default seasonality for a given freq str. E.g. for
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2H -> 12
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"""
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match = re.match(r"(\d*)(\w+)", freq)
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assert match, "Cannot match freq regex"
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mult, base_freq = match.groups()
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multiple = int(mult) if mult else 1
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seasonalities = {"H": 24, "D": 1, "W": 1, "M": 12, "B": 5}
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if base_freq in seasonalities:
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seasonality = seasonalities[base_freq]
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else:
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seasonality = 1
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if seasonality % multiple != 0:
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# logging.warning(
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# f"multiple {multiple} does not divide base "
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# f"seasonality {seasonality}."
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# f"Falling back to seasonality 1"
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# )
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return 1
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return seasonality // multiple
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