code: 
  
  
  
  from typing import TYPE_CHECKING
  
  from ...utils import (
      OptionalDependencyNotAvailable,
      _LazyModule,
      is_sentencepiece_available,
      is_tf_available,
      is_tokenizers_available,
      is_torch_available,
  )
  
  
  __A       					=		{
      '''configuration_camembert''': ['''CAMEMBERT_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''CamembertConfig''', '''CamembertOnnxConfig'''],
  }
  
  try:
  						if not is_sentencepiece_available():
  												raise OptionalDependencyNotAvailable()
  except OptionalDependencyNotAvailable:
  						pass
  else:
  						__A       					=		['''CamembertTokenizer''']
  
  try:
  						if not is_tokenizers_available():
  												raise OptionalDependencyNotAvailable()
  except OptionalDependencyNotAvailable:
  						pass
  else:
  						__A       					=		['''CamembertTokenizerFast''']
  
  try:
  						if not is_torch_available():
  												raise OptionalDependencyNotAvailable()
  except OptionalDependencyNotAvailable:
  						pass
  else:
  						__A       					=		[
  						    '''CAMEMBERT_PRETRAINED_MODEL_ARCHIVE_LIST''',
  						    '''CamembertForCausalLM''',
  						    '''CamembertForMaskedLM''',
  						    '''CamembertForMultipleChoice''',
  						    '''CamembertForQuestionAnswering''',
  						    '''CamembertForSequenceClassification''',
  						    '''CamembertForTokenClassification''',
  						    '''CamembertModel''',
  						    '''CamembertPreTrainedModel''',
  						]
  
  try:
  						if not is_tf_available():
  												raise OptionalDependencyNotAvailable()
  except OptionalDependencyNotAvailable:
  						pass
  else:
  						__A       					=		[
  						    '''TF_CAMEMBERT_PRETRAINED_MODEL_ARCHIVE_LIST''',
  						    '''TFCamembertForCausalLM''',
  						    '''TFCamembertForMaskedLM''',
  						    '''TFCamembertForMultipleChoice''',
  						    '''TFCamembertForQuestionAnswering''',
  						    '''TFCamembertForSequenceClassification''',
  						    '''TFCamembertForTokenClassification''',
  						    '''TFCamembertModel''',
  						    '''TFCamembertPreTrainedModel''',
  						]
  
  
  if TYPE_CHECKING:
  						from .configuration_camembert import CAMEMBERT_PRETRAINED_CONFIG_ARCHIVE_MAP, CamembertConfig, CamembertOnnxConfig
  
  						try:
  												if not is_sentencepiece_available():
  																		raise OptionalDependencyNotAvailable()
  						except OptionalDependencyNotAvailable:
  												pass
  						else:
  												from .tokenization_camembert import CamembertTokenizer
  
  						try:
  												if not is_tokenizers_available():
  																		raise OptionalDependencyNotAvailable()
  						except OptionalDependencyNotAvailable:
  												pass
  						else:
  												from .tokenization_camembert_fast import CamembertTokenizerFast
  
  						try:
  												if not is_torch_available():
  																		raise OptionalDependencyNotAvailable()
  						except OptionalDependencyNotAvailable:
  												pass
  						else:
  												from .modeling_camembert import (
  												    CAMEMBERT_PRETRAINED_MODEL_ARCHIVE_LIST,
  												    CamembertForCausalLM,
  												    CamembertForMaskedLM,
  												    CamembertForMultipleChoice,
  												    CamembertForQuestionAnswering,
  												    CamembertForSequenceClassification,
  												    CamembertForTokenClassification,
  												    CamembertModel,
  												    CamembertPreTrainedModel,
  												)
  
  						try:
  												if not is_tf_available():
  																		raise OptionalDependencyNotAvailable()
  						except OptionalDependencyNotAvailable:
  												pass
  						else:
  												from .modeling_tf_camembert import (
  												    TF_CAMEMBERT_PRETRAINED_MODEL_ARCHIVE_LIST,
  												    TFCamembertForCausalLM,
  												    TFCamembertForMaskedLM,
  												    TFCamembertForMultipleChoice,
  												    TFCamembertForQuestionAnswering,
  												    TFCamembertForSequenceClassification,
  												    TFCamembertForTokenClassification,
  												    TFCamembertModel,
  												    TFCamembertPreTrainedModel,
  												)
  
  else:
  						import sys
  
  						__A       					=		_LazyModule(__name__, globals()['''__file__'''], _import_structure, module_spec=__spec__)
  
  
  
  
  
style_context: 
  
  
  
  from math import radians as angle_to_radians
  from math import sin
  
  # Acceleration Constant on Earth (unit m/s^2)
  __A       					=		9.8_0_6_6_5
  
  
  
  def  __a  (					lowerCAmelCase_     :      float    ,lowerCAmelCase_     :      float       )   ->				None:
  
  
  
  
  
  
  						'''simple docstring'''
  
  
  
  						if not isinstance(lowerCAmelCase_    ,(int, float)       ):
  												raise TypeError("""Invalid velocity. Should be a positive number."""       )
  
  						if not isinstance(lowerCAmelCase_    ,(int, float)       ):
  												raise TypeError("""Invalid angle. Range is 1-90 degrees."""       )
  
  						# Ensure valid angle
  						if angle > 90 or angle < 1:
  												raise ValueError("""Invalid angle. Range is 1-90 degrees."""       )
  
  						# Ensure valid velocity
  						if init_velocity < 0:
  												raise ValueError("""Invalid velocity. Should be a positive number."""       )
  
  
  
  def  __a  (					lowerCAmelCase_     :      float    ,lowerCAmelCase_     :      float       )   ->				float:
  
  
  
  
  
  
  						'''simple docstring'''
  
  
  
  						check_args(lowerCAmelCase_    ,lowerCAmelCase_       )
  						UpperCAmelCase_=     angle_to_radians(2 * angle       )
  						return round(init_velocity**2 * sin(lowerCAmelCase_       ) / g    ,2       )
  
  
  
  def  __a  (					lowerCAmelCase_     :      float    ,lowerCAmelCase_     :      float       )   ->				float:
  
  
  
  
  
  
  						'''simple docstring'''
  
  
  
  						check_args(lowerCAmelCase_    ,lowerCAmelCase_       )
  						UpperCAmelCase_=     angle_to_radians(lowerCAmelCase_       )
  						return round(init_velocity**2 * sin(lowerCAmelCase_       ) ** 2 / (2 * g)    ,2       )
  
  
  
  def  __a  (					lowerCAmelCase_     :      float    ,lowerCAmelCase_     :      float       )   ->				float:
  
  
  
  
  
  
  						'''simple docstring'''
  
  
  
  						check_args(lowerCAmelCase_    ,lowerCAmelCase_       )
  						UpperCAmelCase_=     angle_to_radians(lowerCAmelCase_       )
  						return round(2 * init_velocity * sin(lowerCAmelCase_       ) / g    ,2       )
  
  
  
  def  __a  (					)   ->				None:
  
  
  
  
  
  
  						'''simple docstring'''
  
  
  
  						UpperCAmelCase_,     UpperCAmelCase_=     25, 20
  						assert horizontal_distance(lowerCAmelCase_    ,lowerCAmelCase_       ) == 40.97
  						assert max_height(lowerCAmelCase_    ,lowerCAmelCase_       ) == 3.73
  						assert total_time(lowerCAmelCase_    ,lowerCAmelCase_       ) == 1.74
  
  
  if __name__ == "__main__":
  	from doctest import testmod
  
  	testmod()
  
  	# Get input from user
  	__A       					=		float(input('''Initial Velocity: ''').strip())
  
  	# Get input from user
  	__A       					=		float(input('''angle: ''').strip())
  
  	# Print results
  	print()
  	print('''Results: ''')
  	print(f'Horizontal Distance: {horizontal_distance(init_vel, angle)!s} [m]')
  	print(f'Maximum Height: {max_height(init_vel, angle)!s} [m]')
  	print(f'Total Time: {total_time(init_vel, angle)!s} [s]')
  
  
  
  
  