


import numpy as np







class  snake_case_     :
					def __init__(   self     :Tuple    ,__snake_case     :List[str]=None    ,__snake_case     :Union[str, Any]=None    ,__snake_case     :List[Any]=None    ,__snake_case     :Optional[int]=None    ,__snake_case     :List[Any]=None   )      ->					Any:
												self.set_matricies(red=lowercase_    ,green=lowercase_    ,blue=lowercase_    ,red_edge=lowercase_    ,nir=lowercase_   )
					def 				lowerCamelCase__(   self     :List[Any]    ,__snake_case     :int=None    ,__snake_case     :Optional[int]=None    ,__snake_case     :Dict=None    ,__snake_case     :Any=None    ,__snake_case     :Any=None   )      ->					Tuple:
												if red is not None:
																			a__    =  red
												if green is not None:
																			a__    =  green
												if blue is not None:
																			a__    =  blue
												if red_edge is not None:
																			a__    =  red_edge
												if nir is not None:
																			a__    =  nir
												return True
					def 				lowerCamelCase__(   self     :Optional[int]    ,__snake_case     :str=""    ,__snake_case     :Union[str, Any]=None    ,__snake_case     :Optional[Any]=None    ,__snake_case     :Tuple=None    ,__snake_case     :Any=None    ,__snake_case     :Any=None   )      ->					Dict:
												self.set_matricies(red=lowercase_    ,green=lowercase_    ,blue=lowercase_    ,red_edge=lowercase_    ,nir=lowercase_   )
												a__    =  {
												    "ARVI2": self.arvaa,
												    "CCCI": self.ccci,
												    "CVI": self.cvi,
												    "GLI": self.gli,
												    "NDVI": self.ndvi,
												    "BNDVI": self.bndvi,
												    "redEdgeNDVI": self.red_edge_ndvi,
												    "GNDVI": self.gndvi,
												    "GBNDVI": self.gbndvi,
												    "GRNDVI": self.grndvi,
												    "RBNDVI": self.rbndvi,
												    "PNDVI": self.pndvi,
												    "ATSAVI": self.atsavi,
												    "BWDRVI": self.bwdrvi,
												    "CIgreen": self.ci_green,
												    "CIrededge": self.ci_rededge,
												    "CI": self.ci,
												    "CTVI": self.ctvi,
												    "GDVI": self.gdvi,
												    "EVI": self.evi,
												    "GEMI": self.gemi,
												    "GOSAVI": self.gosavi,
												    "GSAVI": self.gsavi,
												    "Hue": self.hue,
												    "IVI": self.ivi,
												    "IPVI": self.ipvi,
												    "I": self.i,
												    "RVI": self.rvi,
												    "MRVI": self.mrvi,
												    "MSAVI": self.m_savi,
												    "NormG": self.norm_g,
												    "NormNIR": self.norm_nir,
												    "NormR": self.norm_r,
												    "NGRDI": self.ngrdi,
												    "RI": self.ri,
												    "S": self.s,
												    "IF": self._if,
												    "DVI": self.dvi,
												    "TVI": self.tvi,
												    "NDRE": self.ndre,
												}

												try:
																			return funcs[index]()
												except KeyError:
																			print('Index not in the list!'   )
																			return False
					def 				lowerCamelCase__(   self     :List[str]   )      ->					Any:
												return -0.18 + (1.17 * ((self.nir - self.red) / (self.nir + self.red)))
					def 				lowerCamelCase__(   self     :Dict   )      ->					List[Any]:
												return ((self.nir - self.redEdge) / (self.nir + self.redEdge)) / (
												    (self.nir - self.red) / (self.nir + self.red)
												)
					def 				lowerCamelCase__(   self     :int   )      ->					Optional[int]:
												return self.nir * (self.red / (self.green**2))
					def 				lowerCamelCase__(   self     :Dict   )      ->					Union[str, Any]:
												return (2 * self.green - self.red - self.blue) / (
												    2 * self.green + self.red + self.blue
												)
					def 				lowerCamelCase__(   self     :int   )      ->					List[Any]:
												return (self.nir - self.red) / (self.nir + self.red)
					def 				lowerCamelCase__(   self     :Any   )      ->					List[str]:
												return (self.nir - self.blue) / (self.nir + self.blue)
					def 				lowerCamelCase__(   self     :List[Any]   )      ->					int:
												return (self.redEdge - self.red) / (self.redEdge + self.red)
					def 				lowerCamelCase__(   self     :Tuple   )      ->					Optional[int]:
												return (self.nir - self.green) / (self.nir + self.green)
					def 				lowerCamelCase__(   self     :Tuple   )      ->					Tuple:
												return (self.nir - (self.green + self.blue)) / (
												    self.nir + (self.green + self.blue)
												)
					def 				lowerCamelCase__(   self     :Union[str, Any]   )      ->					Dict:
												return (self.nir - (self.green + self.red)) / (
												    self.nir + (self.green + self.red)
												)
					def 				lowerCamelCase__(   self     :Dict   )      ->					Union[str, Any]:
												return (self.nir - (self.blue + self.red)) / (self.nir + (self.blue + self.red))
					def 				lowerCamelCase__(   self     :str   )      ->					Optional[int]:
												return (self.nir - (self.green + self.red + self.blue)) / (
												    self.nir + (self.green + self.red + self.blue)
												)
					def 				lowerCamelCase__(   self     :List[str]    ,__snake_case     :List[str]=0.08    ,__snake_case     :str=1.22    ,__snake_case     :str=0.03   )      ->					List[str]:
												return a * (
												    (self.nir - a * self.red - b)
												    / (a * self.nir + self.red - a * b + x * (1 + a**2))
												)
					def 				lowerCamelCase__(   self     :Union[str, Any]   )      ->					Optional[Any]:
												return (0.1 * self.nir - self.blue) / (0.1 * self.nir + self.blue)
					def 				lowerCamelCase__(   self     :str   )      ->					List[Any]:
												return (self.nir / self.green) - 1
					def 				lowerCamelCase__(   self     :List[Any]   )      ->					int:
												return (self.nir / self.redEdge) - 1
					def 				lowerCamelCase__(   self     :Optional[Any]   )      ->					List[Any]:
												return (self.red - self.blue) / self.red
					def 				lowerCamelCase__(   self     :Tuple   )      ->					List[str]:
												a__    =  self.ndvi()
												return ((ndvi + 0.5) / (abs(ndvi + 0.5   ))) * (abs(ndvi + 0.5   ) ** (1 / 2))
					def 				lowerCamelCase__(   self     :Any   )      ->					Optional[int]:
												return self.nir - self.green
					def 				lowerCamelCase__(   self     :Dict   )      ->					List[Any]:
												return 2.5 * (
												    (self.nir - self.red) / (self.nir + 6 * self.red - 7.5 * self.blue + 1)
												)
					def 				lowerCamelCase__(   self     :str   )      ->					str:
												a__    =  (2 * (self.nir**2 - self.red**2) + 1.5 * self.nir + 0.5 * self.red) / (
												    self.nir + self.red + 0.5
												)
												return n * (1 - 0.25 * n) - (self.red - 0.1_25) / (1 - self.red)
					def 				lowerCamelCase__(   self     :Any    ,__snake_case     :Optional[Any]=0.16   )      ->					Optional[Any]:
												return (self.nir - self.green) / (self.nir + self.green + y)
					def 				lowerCamelCase__(   self     :List[str]    ,__snake_case     :int=0.5   )      ->					List[Any]:
												return ((self.nir - self.green) / (self.nir + self.green + n)) * (1 + n)
					def 				lowerCamelCase__(   self     :int   )      ->					Optional[int]:
												return np.arctan(
												    ((2 * self.red - self.green - self.blue) / 30.5) * (self.green - self.blue)   )
					def 				lowerCamelCase__(   self     :List[Any]    ,__snake_case     :Dict=None    ,__snake_case     :Optional[Any]=None   )      ->					Any:
												return (self.nir - b) / (a * self.red)
					def 				lowerCamelCase__(   self     :Optional[int]   )      ->					int:
												return (self.nir / ((self.nir + self.red) / 2)) * (self.ndvi() + 1)
					def 				lowerCamelCase__(   self     :Any   )      ->					Optional[int]:
												return (self.red + self.green + self.blue) / 30.5
					def 				lowerCamelCase__(   self     :Optional[Any]   )      ->					Optional[Any]:
												return self.nir / self.red
					def 				lowerCamelCase__(   self     :List[str]   )      ->					str:
												return (self.rvi() - 1) / (self.rvi() + 1)
					def 				lowerCamelCase__(   self     :Optional[int]   )      ->					Tuple:
												return (
												    (2 * self.nir + 1)
												    - ((2 * self.nir + 1) ** 2 - 8 * (self.nir - self.red)) ** (1 / 2)
												) / 2
					def 				lowerCamelCase__(   self     :Dict   )      ->					Optional[int]:
												return self.green / (self.nir + self.red + self.green)
					def 				lowerCamelCase__(   self     :Optional[int]   )      ->					str:
												return self.nir / (self.nir + self.red + self.green)
					def 				lowerCamelCase__(   self     :str   )      ->					Optional[int]:
												return self.red / (self.nir + self.red + self.green)
					def 				lowerCamelCase__(   self     :Tuple   )      ->					int:
												return (self.green - self.red) / (self.green + self.red)
					def 				lowerCamelCase__(   self     :int   )      ->					Tuple:
												return (self.red - self.green) / (self.red + self.green)
					def 				lowerCamelCase__(   self     :Tuple   )      ->					Optional[Any]:
												a__    =  np.max([np.max(self.red   ), np.max(self.green   ), np.max(self.blue   )]   )
												a__    =  np.min([np.min(self.red   ), np.min(self.green   ), np.min(self.blue   )]   )
												return (max_value - min_value) / max_value
					def 				lowerCamelCase__(   self     :Union[str, Any]   )      ->					List[Any]:
												return (2 * self.red - self.green - self.blue) / (self.green - self.blue)
					def 				lowerCamelCase__(   self     :str   )      ->					str:
												return self.nir / self.red
					def 				lowerCamelCase__(   self     :Union[str, Any]   )      ->					Tuple:
												return (self.ndvi() + 0.5) ** (1 / 2)



					def 				lowerCamelCase__(   self     :Dict   )      ->					Optional[int]:
												return (self.nir - self.redEdge) / (self.nir + self.redEdge)









import math
from typing import List, Optional, Tuple, Union

import numpy as np
import torch

from ..configuration_utils import ConfigMixin, register_to_config
from .scheduling_utils import SchedulerMixin, SchedulerOutput







class  snake_case_     (lowerCamelCase_			,		lowerCamelCase_   ):
					UpperCAmelCase__      :					Optional[Any]					   =    1
					@register_to_config
					def __init__(   self     :Optional[int]    ,__snake_case     :int = 10_00    ,__snake_case     :Optional[Union[np.ndarray, List[float]]] = None   )      ->					int:
												# set `betas`, `alphas`, `timesteps`
												self.set_timesteps(__snake_case   )

												# standard deviation of the initial noise distribution
												a__    =  1.0

												# For now we only support F-PNDM, i.e. the runge-kutta method
												# For more information on the algorithm please take a look at the paper: https://arxiv.org/pdf/2202.09778.pdf
												# mainly at formula (9), (12), (13) and the Algorithm 2.
												a__    =  4

												# running values
												a__    =  []
					def 				lowerCamelCase__(   self     :Union[str, Any]    ,__snake_case     :int    ,__snake_case     :Union[str, torch.device] = None   )      ->					Union[str, Any]:
												a__    =  num_inference_steps
												a__    =  torch.linspace(1    ,0    ,num_inference_steps + 1   )[:-1]
												a__    =  torch.cat([steps, torch.tensor([0.0]   )]   )

												if self.config.trained_betas is not None:
																			a__    =  torch.tensor(self.config.trained_betas    ,dtype=torch.floataa   )
												else:
																			a__    =  torch.sin(steps * math.pi / 2   ) ** 2

												a__    =  (1.0 - self.betas**2) ** 0.5

												a__    =  (torch.atana(self.betas    ,self.alphas   ) / math.pi * 2)[:-1]
												a__    =  timesteps.to(__snake_case   )

												a__    =  []
					def 				lowerCamelCase__(   self     :Any    ,__snake_case     :torch.FloatTensor    ,__snake_case     :int    ,__snake_case     :torch.FloatTensor    ,__snake_case     :bool = True    ,)      ->					Union[SchedulerOutput, Tuple]:
												if self.num_inference_steps is None:
																			raise ValueError(
																			    'Number of inference steps is \'None\', you need to run \'set_timesteps\' after creating the scheduler'   )

												a__    =  (self.timesteps == timestep).nonzero().item()
												a__    =  timestep_index + 1

												a__    =  sample * self.betas[timestep_index] + model_output * self.alphas[timestep_index]
												self.ets.append(__snake_case   )

												if len(self.ets   ) == 1:
																			a__    =  self.ets[-1]
												elif len(self.ets   ) == 2:
																			a__    =  (3 * self.ets[-1] - self.ets[-2]) / 2
												elif len(self.ets   ) == 3:
																			a__    =  (23 * self.ets[-1] - 16 * self.ets[-2] + 5 * self.ets[-3]) / 12
												else:
																			a__    =  (1 / 24) * (55 * self.ets[-1] - 59 * self.ets[-2] + 37 * self.ets[-3] - 9 * self.ets[-4])

												a__    =  self._get_prev_sample(__snake_case    ,__snake_case    ,__snake_case    ,__snake_case   )

												if not return_dict:
																			return (prev_sample,)

												return SchedulerOutput(prev_sample=__snake_case   )
					def 				lowerCamelCase__(   self     :Union[str, Any]    ,__snake_case     :torch.FloatTensor    ,*__snake_case     :int    ,**__snake_case     :Optional[int]   )      ->					torch.FloatTensor:
												return sample
					def 				lowerCamelCase__(   self     :Optional[Any]    ,__snake_case     :List[Any]    ,__snake_case     :Optional[int]    ,__snake_case     :Dict    ,__snake_case     :Any   )      ->					Optional[Any]:
												a__    =  self.alphas[timestep_index]
												a__    =  self.betas[timestep_index]

												a__    =  self.alphas[prev_timestep_index]
												a__    =  self.betas[prev_timestep_index]

												a__    =  (sample - sigma * ets) / max(__snake_case    ,1E-8   )
												a__    =  next_alpha * pred + ets * next_sigma

												return prev_sample



					def __len__(   self     :Any   )      ->					Union[str, Any]:
												return self.config.num_train_timesteps




