from unittest import TestCase

from datasets import Sequence, Value
from datasets.arrow_dataset import Dataset
class    A_ (       a_ ):

  def 		_UpperCAmelCase   (		self :      str       ):
   return [
       {"col_1": 3, "col_2": "a"},
       {"col_1": 2, "col_2": "b"},
       {"col_1": 1, "col_2": "c"},
       {"col_1": 0, "col_2": "d"},
   ]

  def 		_UpperCAmelCase   (		self :      Union[str, Any]       ):
   __a       =  {"col_1": [3, 2, 1, 0], "col_2": ["a", "b", "c", "d"]}
   return Dataset.from_dict(__SCREAMING_SNAKE_CASE       )

  def 		_UpperCAmelCase   (		self :      Optional[int]       ):
   __a       =  self._create_example_records()
   __a       =  Dataset.from_list(__SCREAMING_SNAKE_CASE       )
   self.assertListEqual(dset.column_names     ,							["col_1", "col_2"]       )
   for i, r in enumerate(__SCREAMING_SNAKE_CASE       ):
    self.assertDictEqual(__SCREAMING_SNAKE_CASE     ,							example_records[i]       )

  def 		_UpperCAmelCase   (		self :      int       ):
   __a       =  self._create_example_records()
   __a       =  Dataset.from_list(__SCREAMING_SNAKE_CASE       )
   __a       =  Dataset.from_dict({k: [r[k] for r in example_records] for k in example_records[0]}       )
   self.assertEqual(dset.info     ,							dset_from_dict.info       )

  def 		_UpperCAmelCase   (		self :      Any       ):  # checks what happens with missing columns
   __a       =  [{"col_1": 1}, {"col_2": "x"}]
   __a       =  Dataset.from_list(__SCREAMING_SNAKE_CASE       )
   self.assertDictEqual(dset[0]     ,							{"col_1": 1}       )
   self.assertDictEqual(dset[1]     ,							{"col_1": None}       )  # NB: first record is used for columns

  def 		_UpperCAmelCase   (		self :      Optional[Any]       ):  # checks if the type can be inferred from the second record
   __a       =  [{"col_1": []}, {"col_1": [1, 2]}]
   __a       =  Dataset.from_list(__SCREAMING_SNAKE_CASE       )
   self.assertEqual(dset.info.features["col_1"]     ,							Sequence(Value("int64"       )       )       )

  def 		_UpperCAmelCase   (		self :      List[str]       ):
   __a       =  Dataset.from_list([]       )
   self.assertEqual(len(__SCREAMING_SNAKE_CASE       )     ,							0       )
   self.assertListEqual(dset.column_names     ,							[]       )



from __future__ import annotations
class    A_ :

  def __init__(		self :      Union[str, Any]     ,							__SCREAMING_SNAKE_CASE :      int       ):
   __a       =  order

   # a_{0} ... a_{k}
   __a       =  [1.0] + [0.0] * order
   # b_{0} ... b_{k}
   __a       =  [1.0] + [0.0] * order

   # x[n-1] ... x[n-k]
   __a       =  [0.0] * self.order
   # y[n-1] ... y[n-k]
   __a       =  [0.0] * self.order

  def 		_UpperCAmelCase   (		self :      Union[str, Any]     ,							__SCREAMING_SNAKE_CASE :      list[float]     ,							__SCREAMING_SNAKE_CASE :      list[float]       ):
   if len(__SCREAMING_SNAKE_CASE       ) < self.order:
    __a       =  [1.0, *a_coeffs]

   if len(__SCREAMING_SNAKE_CASE       ) != self.order + 1:
    __a       =  (
        f"""Expected a_coeffs to have {self.order + 1} elements """
        f"""for {self.order}-order filter, got {len(__SCREAMING_SNAKE_CASE       )}"""
    )
    raise ValueError(__SCREAMING_SNAKE_CASE       )

   if len(__SCREAMING_SNAKE_CASE       ) != self.order + 1:
    __a       =  (
        f"""Expected b_coeffs to have {self.order + 1} elements """
        f"""for {self.order}-order filter, got {len(__SCREAMING_SNAKE_CASE       )}"""
    )
    raise ValueError(__SCREAMING_SNAKE_CASE       )

   __a       =  a_coeffs
   __a       =  b_coeffs

  def 		_UpperCAmelCase   (		self :      Optional[Any]     ,							__SCREAMING_SNAKE_CASE :      float       ):
   __a       =  0.0

   # Start at index 1 and do index 0 at the end.
   for i in range(1     ,							self.order + 1       ):
    result += (
        self.b_coeffs[i] * self.input_history[i - 1]
        - self.a_coeffs[i] * self.output_history[i - 1]
    )

   __a       =  (result + self.b_coeffs[0] * sample) / self.a_coeffs[0]

   __a       =  self.input_history[:-1]
   __a       =  self.output_history[:-1]

   __a       =  sample
   __a       =  result

   return result


