
import contextlib
from multiprocessing import Pool, RLock

from tqdm.auto import tqdm

from ..utils import experimental, logging


SCREAMING_SNAKE_CASE							:Tuple										=    logging.get_logger(__name__)





class 							UpperCAmelCase				:




			'''simple docstring'''





			snake_case_    =					None





@experimental
def 						UpperCAmelCase      (     a_		,       a_		,       a_		,       a_		,       a_		,       a_		,       a_						)		->     str:







				"""simple docstring"""



				if ParallelBackendConfig.backend_name is None:
								return _map_with_multiprocessing_pool(
								    a_		,       a_		,       a_		,       a_		,       a_		,       a_		,       a_						)

				return _map_with_joblib(a_		,       a_		,       a_		,       a_		,       a_		,       a_		,       a_						)


def 						UpperCAmelCase      (     a_		,       a_		,       a_		,       a_		,       a_		,       a_		,       a_						)		->     Optional[Any]:







				"""simple docstring"""



				__A             =			num_proc if num_proc <= len(a_						) else len(a_						)
				__A             =			[]  # We organize the splits ourselve (contiguous splits)
				for index in range(a_						):
								__A             =			len(a_						) // num_proc
								__A             =			len(a_						) % num_proc
								__A             =			div * index + min(a_		,       a_						)
								__A             =			start + div + (1 if index < mod else 0)
								split_kwds.append((function, iterable[start:end], types, index, disable_tqdm, desc)						)

				if len(a_						) != sum(len(i[1]						) for i in split_kwds						):
								raise ValueError(
								    F'''Error dividing inputs iterable among processes. '''
								    F'''Total number of objects {len(a_						)}, '''
								    F'''length: {sum(len(i[1]						) for i in split_kwds						)}'''						)

				logger.info(
				    F'''Spawning {num_proc} processes for {len(a_						)} objects in slices of {[len(i[1]						) for i in split_kwds]}'''						)
				__A      ,							__A             =			None, None
				if not disable_tqdm:
								__A      ,							__A             =			(RLock(),), tqdm.set_lock
				with Pool(a_		,       initargs=a_		,       initializer=a_						) as pool:
								__A             =			pool.map(a_		,       a_						)
				logger.info(F'''Finished {num_proc} processes'''						)
				__A             =			[obj for proc_res in mapped for obj in proc_res]
				logger.info(F'''Unpacked {len(a_						)} objects'''						)

				return mapped


def 						UpperCAmelCase      (     a_		,       a_		,       a_		,       a_		,       a_		,       a_		,       a_						)		->     List[str]:







				"""simple docstring"""



				import joblib

				with joblib.parallel_backend(ParallelBackendConfig.backend_name		,       n_jobs=a_						):
								return joblib.Parallel()(
								    joblib.delayed(a_						)((function, obj, types, None, True, None)						) for obj in iterable						)


@experimental
@contextlib.contextmanager
def 						UpperCAmelCase      (     a_						)		->     Optional[int]:







				"""simple docstring"""



				__A             =			backend_name

				if backend_name == "spark":
								from joblibspark import register_spark

								register_spark()

								# TODO: call create_cache_and_write_probe if "download" in steps
								# TODO: raise NotImplementedError when Dataset.map etc is called

				try:
								yield
				finally:
								__A             =			None


from math import log

from scipy.constants import Boltzmann, physical_constants

SCREAMING_SNAKE_CASE							:Dict										=    300  # TEMPERATURE (unit = K)


def 						UpperCAmelCase      (     a_		,       a_		,       a_		,       )		->     float:







				"""simple docstring"""



				if donor_conc <= 0:
								raise ValueError("Donor concentration should be positive"						)
				elif acceptor_conc <= 0:
								raise ValueError("Acceptor concentration should be positive"						)
				elif intrinsic_conc <= 0:
								raise ValueError("Intrinsic concentration should be positive"						)
				elif donor_conc <= intrinsic_conc:
								raise ValueError(
								    "Donor concentration should be greater than intrinsic concentration"						)
				elif acceptor_conc <= intrinsic_conc:
								raise ValueError(
								    "Acceptor concentration should be greater than intrinsic concentration"						)
				else:
								return (
								    Boltzmann
								    * T
								    * log((donor_conc * acceptor_conc) / intrinsic_conc**2						)
								    / physical_constants["electron volt"][0]
								)


if __name__ == "__main__":
					import doctest

					doctest.testmod()
