class_docstr: Not sure if I can avoid the state machine here
class_docstr_tok: ["Not","sure","if","I","can","avoid","the","state","machine","here"]
code: def _infer_daily_rule(self):
      annual_rule = self._get_annual_rule()
      if annual_rule:
          nyears = self.ydiffs[0]
          month = MONTH_ALIASES[self.rep_stamp.month]
          alias = "{prefix}-{month}".format(
              prefix=annual_rule, month=month
          )
          return _maybe_add_count(alias, nyears)
  
      quarterly_rule = self._get_quarterly_rule()
      if quarterly_rule:
          nquarters = self.mdiffs[0] / 3
          mod_dict = {0: 12, 2: 11, 1: 10}
          month = MONTH_ALIASES[mod_dict[self.rep_stamp.month % 3]]
          alias = "{prefix}-{month}".format(
              prefix=quarterly_rule, month=month
          )
          return _maybe_add_count(alias, nquarters)
  
      monthly_rule = self._get_monthly_rule()
      if monthly_rule:
          return _maybe_add_count(monthly_rule, self.mdiffs[0])
  
      if self.is_unique:
          days = self.deltas[0] / _ONE_DAY
          if days % 7 == 0:
              # Weekly
              day = int_to_weekday[self.rep_stamp.weekday()]
              return _maybe_add_count(
                  "W-{day}".format(day=day), days / 7
              )
          else:
              return _maybe_add_count("D", days)
  
      if self._is_business_daily():
          return "B"
  
      wom_rule = self._get_wom_rule()
      if wom_rule:
          return wom_rule
  
imports: from datetime import timedelta
  import re
  import numpy
  from pytz import AmbiguousTimeError
  from pandas._libs.algos import unique_deltas
  from pandas._libs.tslibs import Timedelta, Timestamp
  from pandas._libs.tslibs.ccalendar import MONTH_ALIASES, int_to_weekday
  from pandas._libs.tslibs.conversion import tz_convert
  from pandas._libs.tslibs.fields import build_field_sarray
  import pandas._libs.tslibs.frequencies
  from pandas._libs.tslibs.offsets import _offset_to_period_map
  import pandas._libs.tslibs.resolution
  from pandas._libs.tslibs.resolution import Resolution
  from pandas._libs.tslibs.timezones import UTC
  import pandas.compat
  from pandas.compat import zip
  from pandas.util._decorators import cache_readonly
  from pandas.core.dtypes.common import is_datetime64_dtype, is_period_arraylike, is_timedelta64_dtype
  from pandas.core.dtypes.generic import ABCSeries
  from pandas.core.algorithms import unique
  from pandas.tseries.offsets import DateOffset, Day, Hour, Micro, Milli, Minute, Nano, Second, prefix_mapping
label_desc: Use image node_id 14 for calling the _FrequencyInferer obj's underlying member method code with example usage: obj._infer_daily_rule() and returns: _maybe_add_count, _maybe_add_count, _maybe_add_count, str, wom_rule, _maybe_add_count, _maybe_add_count