



"""simple docstring"""
from __future__ import annotations



class    SCREAMING_SNAKE_CASE__						:

   def __init__(     self   ,  _SCREAMING_SNAKE_CASE		)						->   Union[str, Any]:





    '''simple docstring'''




    UpperCAmelCase			:      List[Any]			=			TypeError(
        """Matrices must be formed from a list of zero or more lists containing at """
        """least one and the same number of values, each of which must be of type """
        """int or float."""		)
    if len(_SCREAMING_SNAKE_CASE		) != 0:
     UpperCAmelCase			:      Any			=			len(rows[0]		)
     if cols == 0:
      raise error
     for row in rows:
      if len(_SCREAMING_SNAKE_CASE		) != cols:
       raise error
      for value in row:
       if not isinstance(_SCREAMING_SNAKE_CASE   ,  (int, float)		):
        raise error
     UpperCAmelCase			:      Optional[int]			=			rows
    else:
     UpperCAmelCase			:      Tuple			=			[]

   def 			SCREAMING_SNAKE_CASE  (     self		)						->   list[list[int]]:





    '''simple docstring'''




    return [[row[i] for row in self.rows] for i in range(len(self.rows[0]		)		)]

   @property
   def 			SCREAMING_SNAKE_CASE  (     self		)						->   int:





    '''simple docstring'''




    return len(self.rows		)

   @property
   def 			SCREAMING_SNAKE_CASE  (     self		)						->   int:





    '''simple docstring'''




    return len(self.rows[0]		)

   @property
   def 			SCREAMING_SNAKE_CASE  (     self		)						->   tuple[int, int]:





    '''simple docstring'''




    return (self.num_rows, self.num_columns)

   @property
   def 			SCREAMING_SNAKE_CASE  (     self		)						->   bool:





    '''simple docstring'''




    return self.order[0] == self.order[1]

   def 			SCREAMING_SNAKE_CASE  (     self		)						->   Matrix:





    '''simple docstring'''




    UpperCAmelCase			:      str			=			[
        [0 if column_num != row_num else 1 for column_num in range(self.num_rows		)]
        for row_num in range(self.num_rows		)
    ]
    return Matrix(_SCREAMING_SNAKE_CASE		)

   def 			SCREAMING_SNAKE_CASE  (     self		)						->   int:





    '''simple docstring'''




    if not self.is_square:
     return 0
    if self.order == (0, 0):
     return 1
    if self.order == (1, 1):
     return int(self.rows[0][0]		)
    if self.order == (2, 2):
     return int(
         (self.rows[0][0] * self.rows[1][1])
         - (self.rows[0][1] * self.rows[1][0])		)
    else:
     return sum(
         self.rows[0][column] * self.cofactors().rows[0][column]
         for column in range(self.num_columns		)		)

   def 			SCREAMING_SNAKE_CASE  (     self		)						->   bool:





    '''simple docstring'''




    return bool(self.determinant()		)

   def 			SCREAMING_SNAKE_CASE  (     self   ,  _SCREAMING_SNAKE_CASE   ,  _SCREAMING_SNAKE_CASE		)						->   int:





    '''simple docstring'''




    UpperCAmelCase			:      List[str]			=			[
        [
            self.rows[other_row][other_column]
            for other_column in range(self.num_columns		)
            if other_column != column
        ]
        for other_row in range(self.num_rows		)
        if other_row != row
    ]
    return Matrix(_SCREAMING_SNAKE_CASE		).determinant()

   def 			SCREAMING_SNAKE_CASE  (     self   ,  _SCREAMING_SNAKE_CASE   ,  _SCREAMING_SNAKE_CASE		)						->   int:





    '''simple docstring'''




    if (row + column) % 2 == 0:
     return self.get_minor(_SCREAMING_SNAKE_CASE   ,  _SCREAMING_SNAKE_CASE		)
    return -1 * self.get_minor(_SCREAMING_SNAKE_CASE   ,  _SCREAMING_SNAKE_CASE		)

   def 			SCREAMING_SNAKE_CASE  (     self		)						->   Matrix:





    '''simple docstring'''




    return Matrix(
        [
            [self.get_minor(_SCREAMING_SNAKE_CASE   ,  _SCREAMING_SNAKE_CASE		) for column in range(self.num_columns		)]
            for row in range(self.num_rows		)
        ]		)

   def 			SCREAMING_SNAKE_CASE  (     self		)						->   Matrix:





    '''simple docstring'''




    return Matrix(
        [
            [
                self.minors().rows[row][column]
                if (row + column) % 2 == 0
                else self.minors().rows[row][column] * -1
                for column in range(self.minors().num_columns		)
            ]
            for row in range(self.minors().num_rows		)
        ]		)

   def 			SCREAMING_SNAKE_CASE  (     self		)						->   Matrix:





    '''simple docstring'''




    UpperCAmelCase			:      Tuple			=			[
        [self.cofactors().rows[column][row] for column in range(self.num_columns		)]
        for row in range(self.num_rows		)
    ]
    return Matrix(_SCREAMING_SNAKE_CASE		)

   def 			SCREAMING_SNAKE_CASE  (     self		)						->   Matrix:





    '''simple docstring'''




    UpperCAmelCase			:      Any			=			self.determinant()
    if not determinant:
     raise TypeError("""Only matrices with a non-zero determinant have an inverse"""		)
    return self.adjugate() * (1 / determinant)

   def __repr__(     self		)						->   str:





    '''simple docstring'''




    return str(self.rows		)

   def __str__(     self		)						->   str:





    '''simple docstring'''




    if self.num_rows == 0:
     return "[]"
    if self.num_rows == 1:
     return "[[" + ". ".join(str(self.rows[0]		)		) + "]]"
    return (
        "["
        + "\n ".join(
            [
                """[""" + """. """.join([str(_SCREAMING_SNAKE_CASE		) for value in row]		) + """.]"""
                for row in self.rows
            ]		)
        + "]"
    )

   def 			SCREAMING_SNAKE_CASE  (     self   ,  _SCREAMING_SNAKE_CASE   ,  _SCREAMING_SNAKE_CASE = None		)						->   None:





    '''simple docstring'''




    UpperCAmelCase			:      int			=			TypeError("""Row must be a list containing all ints and/or floats"""		)
    if not isinstance(_SCREAMING_SNAKE_CASE   ,  _SCREAMING_SNAKE_CASE		):
     raise type_error
    for value in row:
     if not isinstance(_SCREAMING_SNAKE_CASE   ,  (int, float)		):
      raise type_error
    if len(_SCREAMING_SNAKE_CASE		) != self.num_columns:
     raise ValueError(
         """Row must be equal in length to the other rows in the matrix"""		)
    if position is None:
     self.rows.append(_SCREAMING_SNAKE_CASE		)
    else:
     UpperCAmelCase			:      List[str]			=			self.rows[0:position] + [row] + self.rows[position:]

   def 			SCREAMING_SNAKE_CASE  (     self   ,  _SCREAMING_SNAKE_CASE   ,  _SCREAMING_SNAKE_CASE = None		)						->   None:





    '''simple docstring'''




    UpperCAmelCase			:      Tuple			=			TypeError(
        """Column must be a list containing all ints and/or floats"""		)
    if not isinstance(_SCREAMING_SNAKE_CASE   ,  _SCREAMING_SNAKE_CASE		):
     raise type_error
    for value in column:
     if not isinstance(_SCREAMING_SNAKE_CASE   ,  (int, float)		):
      raise type_error
    if len(_SCREAMING_SNAKE_CASE		) != self.num_rows:
     raise ValueError(
         """Column must be equal in length to the other columns in the matrix"""		)
    if position is None:
     UpperCAmelCase			:      Dict			=			[self.rows[i] + [column[i]] for i in range(self.num_rows		)]
    else:
     UpperCAmelCase			:      List[Any]			=			[
         self.rows[i][0:position] + [column[i]] + self.rows[i][position:]
         for i in range(self.num_rows		)
     ]

   def __eq__(     self   ,  _SCREAMING_SNAKE_CASE		)						->   bool:





    '''simple docstring'''




    if not isinstance(_SCREAMING_SNAKE_CASE   ,  _SCREAMING_SNAKE_CASE		):
     return NotImplemented
    return self.rows == other.rows

   def __ne__(     self   ,  _SCREAMING_SNAKE_CASE		)						->   bool:





    '''simple docstring'''




    return not self == other

   def __neg__(     self		)						->   Matrix:





    '''simple docstring'''




    return self * -1

   def __add__(     self   ,  _SCREAMING_SNAKE_CASE		)						->   Matrix:





    '''simple docstring'''




    if self.order != other.order:
     raise ValueError("""Addition requires matrices of the same order"""		)
    return Matrix(
        [
            [self.rows[i][j] + other.rows[i][j] for j in range(self.num_columns		)]
            for i in range(self.num_rows		)
        ]		)

   def __sub__(     self   ,  _SCREAMING_SNAKE_CASE		)						->   Matrix:





    '''simple docstring'''




    if self.order != other.order:
     raise ValueError("""Subtraction requires matrices of the same order"""		)
    return Matrix(
        [
            [self.rows[i][j] - other.rows[i][j] for j in range(self.num_columns		)]
            for i in range(self.num_rows		)
        ]		)

   def __mul__(     self   ,  _SCREAMING_SNAKE_CASE		)						->   Matrix:





    '''simple docstring'''




    if isinstance(_SCREAMING_SNAKE_CASE   ,  (int, float)		):
     return Matrix(
         [[int(element * other		) for element in row] for row in self.rows]		)
    elif isinstance(_SCREAMING_SNAKE_CASE   ,  _SCREAMING_SNAKE_CASE		):
     if self.num_columns != other.num_rows:
      raise ValueError(
          """The number of columns in the first matrix must """
          """be equal to the number of rows in the second"""		)
     return Matrix(
         [
             [Matrix.dot_product(_SCREAMING_SNAKE_CASE   ,  _SCREAMING_SNAKE_CASE		) for column in other.columns()]
             for row in self.rows
         ]		)
    else:
     raise TypeError(
         """A Matrix can only be multiplied by an int, float, or another matrix"""		)

   def __pow__(     self   ,  _SCREAMING_SNAKE_CASE		)						->   Matrix:





    '''simple docstring'''




    if not isinstance(_SCREAMING_SNAKE_CASE   ,  _SCREAMING_SNAKE_CASE		):
     raise TypeError("""A Matrix can only be raised to the power of an int"""		)
    if not self.is_square:
     raise ValueError("""Only square matrices can be raised to a power"""		)
    if other == 0:
     return self.identity()
    if other < 0:
     if self.is_invertable():
      return self.inverse() ** (-other)
     raise ValueError(
         """Only invertable matrices can be raised to a negative power"""		)
    UpperCAmelCase			:      Optional[Any]			=			self
    for _ in range(other - 1		):
     result *= self
    return result




   @classmethod
   def 			SCREAMING_SNAKE_CASE  (     cls   ,  _SCREAMING_SNAKE_CASE   ,  _SCREAMING_SNAKE_CASE		)						->   int:





    '''simple docstring'''




    return sum(row[i] * column[i] for i in range(len(_SCREAMING_SNAKE_CASE		)		)		)


if __name__ == "__main__":
      import doctest

      doctest.testmod()










"""simple docstring"""
import datetime
import platform
import subprocess
from typing import Optional, Tuple, Union

import numpy as np

def    _snake_case		(		UpperCamelCase		:	bytes    ,	UpperCamelCase		:	int		):
 UpperCAmelCase			:      Tuple			=			F"{sampling_rate}"
 UpperCAmelCase			:      Optional[int]			=			"""1"""
 UpperCAmelCase			:      Dict			=			"""f32le"""
 UpperCAmelCase			:      Optional[int]			=			[
     """ffmpeg""",
     """-i""",
     """pipe:0""",
     """-ac""",
     ac,
     """-ar""",
     ar,
     """-f""",
     format_for_conversion,
     """-hide_banner""",
     """-loglevel""",
     """quiet""",
     """pipe:1""",
 ]

 try:
  with subprocess.Popen(UpperCamelCase    ,	stdin=subprocess.PIPE    ,	stdout=subprocess.PIPE		) as ffmpeg_process:
   UpperCAmelCase			:      str			=			ffmpeg_process.communicate(UpperCamelCase		)
 except FileNotFoundError as error:
  raise ValueError("""ffmpeg was not found but is required to load audio files from filename"""		) from error
 UpperCAmelCase			:      Tuple			=			output_stream[0]
 UpperCAmelCase			:      Union[str, Any]			=			np.frombuffer(UpperCamelCase    ,	np.floataa		)
 if audio.shape[0] == 0:
  raise ValueError("""Malformed soundfile"""		)
 return audio

def    _snake_case		(		UpperCamelCase		:	int    ,	UpperCamelCase		:	float    ,	UpperCamelCase		:	str = "f32le"    ,	):
 UpperCAmelCase			:      Tuple			=			F"{sampling_rate}"
 UpperCAmelCase			:      List[str]			=			"""1"""
 if format_for_conversion == "s16le":
  UpperCAmelCase			:      int			=			2
 elif format_for_conversion == "f32le":
  UpperCAmelCase			:      int			=			4
 else:
  raise ValueError(F"Unhandled format `{format_for_conversion}`. Please use `s16le` or `f32le`"		)

 UpperCAmelCase			:      Optional[Any]			=			platform.system()
 if system == "Linux":
  UpperCAmelCase			:      Tuple			=			"""alsa"""
  UpperCAmelCase			:      Any			=			"""default"""
 elif system == "Darwin":
  UpperCAmelCase			:      Any			=			"""avfoundation"""
  UpperCAmelCase			:      int			=			""":0"""
 elif system == "Windows":
  UpperCAmelCase			:      Optional[int]			=			"""dshow"""
  UpperCAmelCase			:      str			=			"""default"""

 UpperCAmelCase			:      Dict			=			[
     """ffmpeg""",
     """-f""",
     format_,
     """-i""",
     input_,
     """-ac""",
     ac,
     """-ar""",
     ar,
     """-f""",
     format_for_conversion,
     """-fflags""",
     """nobuffer""",
     """-hide_banner""",
     """-loglevel""",
     """quiet""",
     """pipe:1""",
 ]
 UpperCAmelCase			:      str			=			int(round(sampling_rate * chunk_length_s		)		) * size_of_sample
 UpperCAmelCase			:      Union[str, Any]			=			_ffmpeg_stream(UpperCamelCase    ,	UpperCamelCase		)
 for item in iterator:
  yield item

def    _snake_case		(		UpperCamelCase		:	int    ,	UpperCamelCase		:	float    ,	UpperCamelCase		:	Optional[int] = None    ,	UpperCamelCase		:	Optional[Union[Tuple[float, float], float]] = None    ,	UpperCamelCase		:	str = "f32le"    ,	):
 if stream_chunk_s is not None:
  UpperCAmelCase			:      List[Any]			=			stream_chunk_s
 else:
  UpperCAmelCase			:      List[Any]			=			chunk_length_s

 UpperCAmelCase			:      Union[str, Any]			=			ffmpeg_microphone(UpperCamelCase    ,	UpperCamelCase    ,	format_for_conversion=UpperCamelCase		)
 if format_for_conversion == "s16le":
  UpperCAmelCase			:      Dict			=			np.intaa
  UpperCAmelCase			:      Optional[Any]			=			2
 elif format_for_conversion == "f32le":
  UpperCAmelCase			:      Any			=			np.floataa
  UpperCAmelCase			:      Dict			=			4
 else:
  raise ValueError(F"Unhandled format `{format_for_conversion}`. Please use `s16le` or `f32le`"		)

 if stride_length_s is None:
  UpperCAmelCase			:      Tuple			=			chunk_length_s / 6
 UpperCAmelCase			:      Optional[Any]			=			int(round(sampling_rate * chunk_length_s		)		) * size_of_sample
 if isinstance(UpperCamelCase    ,	(int, float)		):
  UpperCAmelCase			:      str			=			[stride_length_s, stride_length_s]

 UpperCAmelCase			:      List[Any]			=			int(round(sampling_rate * stride_length_s[0]		)		) * size_of_sample
 UpperCAmelCase			:      Optional[int]			=			int(round(sampling_rate * stride_length_s[1]		)		) * size_of_sample
 UpperCAmelCase			:      List[Any]			=			datetime.datetime.now()
 UpperCAmelCase			:      Tuple			=			datetime.timedelta(seconds=UpperCamelCase		)
 for item in chunk_bytes_iter(UpperCamelCase    ,	UpperCamelCase    ,	stride=(stride_left, stride_right)    ,	stream=UpperCamelCase		):
  # Put everything back in numpy scale
  UpperCAmelCase			:      Dict			=			np.frombuffer(item["""raw"""]    ,	dtype=UpperCamelCase		)
  UpperCAmelCase			:      List[str]			=			(
      item["""stride"""][0] // size_of_sample,
      item["""stride"""][1] // size_of_sample,
  )
  UpperCAmelCase			:      Optional[Any]			=			sampling_rate
  audio_time += delta
  if datetime.datetime.now() > audio_time + 10 * delta:
   # We're late !! SKIP
   continue
  yield item

def    _snake_case		(		UpperCamelCase		:	Dict    ,	UpperCamelCase		:	int    ,	UpperCamelCase		:	Tuple[int, int]    ,	UpperCamelCase		:	bool = False		):
 UpperCAmelCase			:      Any			=			B""""""
 UpperCAmelCase			,	UpperCAmelCase			:      List[Any]			=			stride
 if stride_left + stride_right >= chunk_len:
  raise ValueError(
      F"Stride needs to be strictly smaller than chunk_len: ({stride_left}, {stride_right}) vs {chunk_len}"		)
 UpperCAmelCase			:      int			=			0
 for raw in iterator:
  acc += raw
  if stream and len(UpperCamelCase		) < chunk_len:
   UpperCAmelCase			:      Optional[Any]			=			(_stride_left, 0)
   yield {"raw": acc[:chunk_len], "stride": stride, "partial": True}
  else:
   while len(UpperCamelCase		) >= chunk_len:
    # We are flushing the accumulator
    UpperCAmelCase			:      List[str]			=			(_stride_left, stride_right)
    UpperCAmelCase			:      List[str]			=			{"""raw""": acc[:chunk_len], """stride""": stride}
    if stream:
     UpperCAmelCase			:      List[str]			=			False
    yield item
    UpperCAmelCase			:      Optional[Any]			=			stride_left
    UpperCAmelCase			:      Union[str, Any]			=			acc[chunk_len - stride_left - stride_right :]
    # Last chunk
 if len(UpperCamelCase		) > stride_left:
  UpperCAmelCase			:      Union[str, Any]			=			{"""raw""": acc, """stride""": (_stride_left, 0)}
  if stream:
   UpperCAmelCase			:      str			=			False
  yield item

def    _snake_case		(		UpperCamelCase		:	int    ,	UpperCamelCase		:	int		):
 UpperCAmelCase			:      List[Any]			=			2**24  # 16Mo
 try:
  with subprocess.Popen(UpperCamelCase    ,	stdout=subprocess.PIPE    ,	bufsize=UpperCamelCase		) as ffmpeg_process:
   while True:
    UpperCAmelCase			:      Optional[Any]			=			ffmpeg_process.stdout.read(UpperCamelCase		)
    if raw == b"":
     break
    yield raw
 except FileNotFoundError as error:
  raise ValueError("""ffmpeg was not found but is required to stream audio files from filename"""		) from error
