
"""simple docstring"""





import datetime
import platform
import subprocess
from typing import Optional, Tuple, Union

import numpy as np





def 							A_     (__a				,   __a				):

					'''simple docstring'''





					A_				 =						f'{sampling_rate}'
					A_				 =						"1"
					A_				 =						"f32le"
					A_				 =						[
					    "ffmpeg",
					    "-i",
					    "pipe:0",
					    "-ac",
					    ac,
					    "-ar",
					    ar,
					    "-f",
					    format_for_conversion,
					    "-hide_banner",
					    "-loglevel",
					    "quiet",
					    "pipe:1",
					]

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





def 							A_     (__a				,   __a				,   __a = "f32le"				,   ):

					'''simple docstring'''





					A_				 =						f'{sampling_rate}'
					A_				 =						"1"
					if format_for_conversion == "s16le":
										A_				 =						2
					elif format_for_conversion == "f32le":
										A_				 =						4
					else:
										raise ValueError(f'Unhandled format `{format_for_conversion}`. Please use `s16le` or `f32le`'				)

					A_				 =						platform.system()
					if system == "Linux":
										A_				 =						"alsa"
										A_				 =						"default"
					elif system == "Darwin":
										A_				 =						"avfoundation"
										A_				 =						":0"
					elif system == "Windows":
										A_				 =						"dshow"
										A_				 =						"default"

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





def 							A_     (__a				,   __a				,   __a = None				,   __a = None				,   __a = "f32le"				,   ):

					'''simple docstring'''





					if stream_chunk_s is not None:
										A_				 =						stream_chunk_s
					else:
										A_				 =						chunk_length_s

					A_				 =						ffmpeg_microphone(_lowercase				,   _lowercase				,   format_for_conversion=_lowercase				)
					if format_for_conversion == "s16le":
										A_				 =						np.intaa
										A_				 =						2
					elif format_for_conversion == "f32le":
										A_				 =						np.floataa
										A_				 =						4
					else:
										raise ValueError(f'Unhandled format `{format_for_conversion}`. Please use `s16le` or `f32le`'				)

					if stride_length_s is None:
										A_				 =						chunk_length_s / 6
					A_				 =						int(round(sampling_rate * chunk_length_s				)				) * size_of_sample
					if isinstance(_lowercase				,   (int, float)				):
										A_				 =						[stride_length_s, stride_length_s]

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





def 							A_     (__a				,   __a				,   __a				,   __a = False				):

					'''simple docstring'''





					A_				 =						b""
					A_ ,    A_				 =						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}'				)
					A_				 =						0
					for raw in iterator:
										acc += raw
										if stream and len(_lowercase				) < chunk_len:
															A_				 =						(_stride_left, 0)
															yield {"raw": acc[:chunk_len], "stride": stride, "partial": True}
										else:
															while len(_lowercase				) >= chunk_len:
																				# We are flushing the accumulator
																				A_				 =						(_stride_left, stride_right)
																				A_				 =						{"raw": acc[:chunk_len], "stride": stride}
																				if stream:
																									A_				 =						False
																				yield item
																				A_				 =						stride_left
																				A_				 =						acc[chunk_len - stride_left - stride_right :]
    # Last chunk
					if len(_lowercase				) > stride_left:
										A_				 =						{"raw": acc, "stride": (_stride_left, 0)}
										if stream:
															A_				 =						False
										yield item





def 							A_     (__a				,   __a				):

					'''simple docstring'''





					A_				 =						2**24  # 16Mo
					try:
										with subprocess.Popen(_lowercase				,   stdout=subprocess.PIPE				,   bufsize=_lowercase				) as ffmpeg_process:
															while True:
																				A_				 =						ffmpeg_process.stdout.read(_lowercase				)
																				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






"""simple docstring"""





def 							A_     (__a				):

					'''simple docstring'''





					A_				 =						current_set.copy()
					for row_index, row in enumerate(__a				):
										A_				 =						row[0]
										for column_index, column in enumerate(__a				):
															if magnitude == 0:
																				A_				 =						column
																				continue
															A_				 =						column / magnitude
    # Subtract to cancel term
					A_				 =						current_set[0]
					A_				 =						[first_row]
					A_				 =						current_set[1::]
					for row in current_set:
										A_				 =						[]
										# If first term is 0, it is already in form we want, so we preserve it
										if row[0] == 0:
															final_set.append(__a				)
															continue
										for column_index in range(len(__a				)				):
															temp_row.append(first_row[column_index] - row[column_index]				)
										final_set.append(__a				)
					# Create next recursion iteration set
					if len(final_set[0]				) != 3:
										A_				 =						final_set[0]
										A_				 =						[]
										A_				 =						[]
										for row in final_set[1::]:
															current_first_column.append(row[0]				)
															next_iteration.append(row[1::]				)
										A_				 =						simplify(__a				)
										for i in range(len(__a				)				):
															resultant[i].insert(0				,   current_first_column[i]				)
										resultant.insert(0				,   __a				)
										A_				 =						resultant
					return final_set
def 							A_     (__a				):

					'''simple docstring'''





					if len(__a				) == 0:
										raise IndexError("solve_simultaneous() requires n lists of length n+1"				)
					A_				 =						len(__a				) + 1
					if any(len(__a				) != _length for item in equations				):
										raise IndexError("solve_simultaneous() requires n lists of length n+1"				)
					for row in equations:
										if any(not isinstance(__a				,   (int, float)				) for column in row				):
															raise ValueError("solve_simultaneous() requires lists of integers"				)
					if len(__a				) == 1:
										return [equations[0][-1] / equations[0][0]]
					A_				 =						equations.copy()
					if any(0 in row for row in data_set				):
										A_				 =						data_set.copy()
										A_				 =						[]
										for row_index, row in enumerate(__a				):
															if 0 not in row:
																				A_				 =						data_set.pop(__a				)
																				break
										if not full_row:
															raise ValueError("solve_simultaneous() requires at least 1 full equation"				)
										data_set.insert(0				,   __a				)
					A_				 =						data_set.copy()
					A_				 =						simplify(__a				)
					A_				 =						simplified[::-1]
					A_				 =						[]
					for row in simplified:
										A_				 =						row[-1]
										if not solutions:
															if row[-2] == 0:
																				solutions.append(0				)
																				continue
															solutions.append(current_solution / row[-2]				)
															continue
										A_				 =						row.copy()[: len(__a				) - 1 :]
										while temp_row[0] == 0:
															temp_row.pop(0				)
										if len(__a				) == 0:
															solutions.append(0				)
															continue
										A_				 =						temp_row[1::]
										A_				 =						temp_row[::-1]
										for column_index, column in enumerate(__a				):
															current_solution -= column * solutions[column_index]
										solutions.append(__a				)
					A_				 =						[]
					for item in solutions:
										final.append(float(round(__a				,   5				)				)				)
					return final[::-1]


if __name__ == "__main__":
		import doctest

		doctest.testmod()
		UpperCamelCase_					:						List[Any]				= [
		    [2, 1, 1, 1, 1, 4],
		    [1, 2, 1, 1, 1, 5],
		    [1, 1, 2, 1, 1, 6],
		    [1, 1, 1, 2, 1, 7],
		    [1, 1, 1, 1, 2, 8],
		]
		print(solve_simultaneous(eq))
		print(solve_simultaneous([[4, 2]]))




