U
    9%e                   	   @   s   d dl Z d dlZd dlZd dlmZ d dlmZ d dlmZm	Z	 dgZ
dd Zdd	d
ddddgZdddddddddg	ZdddddddgZddd d!d"d#d$d%d&g	ZeegZeegZd,d'd(Zejjd)d* ZG d+d deZdS )-    N)constraints)Distribution)broadcast_alllazy_propertyVonMisesc                 C   s*   t |}| }|r&| | |  }q|S N)listpop)yZcoefresult r   \/var/www/html/Darija-Ai-API/env/lib/python3.8/site-packages/torch/distributions/von_mises.py
_eval_poly   s
    r   g      ?g$@g03@g,?N?g2t?gIx?gtHZr?g e3E?g-5?gՒ+Hub?gJNYgTPÂ?g'gZ?gUL+ߐg;^p?      ?gY?g(z?g*O?gZ9?g.h?gӰ٩=5?g.kg?VmgtZOZ?g<Q g'8`?gP⥝gqJ:N?g;PJ4qc                 C   s   |dks|dkst | d }|| }t|t| }|dkrF|  | }| }d|  }| d|    t|t|   }t| dk ||}|S )zX
    Returns ``log(I_order(x))`` for ``x > 0``,
    where `order` is either 0 or 1.
    r      g      @r   )AssertionErrorr   _COEF_SMALLabslog_COEF_LARGEtorchwhere)xorderr
   ZsmallZlarger   r   r   r   _log_modified_bessel_fnA   s    "r   c                 C   s   t j|jt j| jd}| st jd|j | j| jd}| \}}}t 	t
j| }	d||	  ||	  }
|||
  }|d|  | dk||  d | dkB }| rt ||d  |
  |}||B }q|t
j |  dt
j  t
j S )Ndtypedevice)   r      r   r   )r   Zzerosshapeboolr   allZrandr   Zunbindcosmathpir   anyr   signacos)locconcentrationZ
proposal_rr   doneuu1u2u3zfcacceptr   r   r   _rejection_sampleX   s    ,
r4   c                       s   e Zd ZdZejejdZejZdZ	d fdd	Z
dd Ze e fd	d
Z fddZedd Zedd Zedd Z  ZS )r   aW  
    A circular von Mises distribution.

    This implementation uses polar coordinates. The ``loc`` and ``value`` args
    can be any real number (to facilitate unconstrained optimization), but are
    interpreted as angles modulo 2 pi.

    Example::
        >>> # xdoctest: +IGNORE_WANT("non-deterinistic")
        >>> m = VonMises(torch.tensor([1.0]), torch.tensor([1.0]))
        >>> m.sample()  # von Mises distributed with loc=1 and concentration=1
        tensor([1.9777])

    :param torch.Tensor loc: an angle in radians.
    :param torch.Tensor concentration: concentration parameter
    )r)   r*   FNc                    s   t ||\| _| _| jj}t }ddd| jd     }|d|   d| j  }d|d  d|  | _t 	||| d S )Nr      r   )
r   r)   r*   r    r   Sizesqrt_proposal_rsuper__init__)selfr)   r*   validate_argsbatch_shapeZevent_shapetaurho	__class__r   r   r:   ~   s    zVonMises.__init__c                 C   sL   | j r| | | jt|| j  }|tdtj  t	| jdd }|S )Nr   r   r   )
_validate_argsZ_validate_sampler*   r   r#   r)   r$   r   r%   r   )r;   valuelog_probr   r   r   rE      s    
zVonMises.log_probc                 C   s6   |  |}tj|| jj| jjd}t| j| j| j|S )z
        The sampling algorithm for the von Mises distribution is based on the following paper:
        Best, D. J., and Nicholas I. Fisher.
        "Efficient simulation of the von Mises distribution." Applied Statistics (1979): 152-157.
        r   )	Z_extended_shaper   emptyr)   r   r   r4   r*   r8   )r;   Zsample_shaper    r   r   r   r   sample   s    
zVonMises.samplec                    s^   zt  |W S  tk
rX   | jd}| j|}| j|}t| |||d Y S X d S )NrC   )r<   )r9   expandNotImplementedError__dict__getr)   r*   type)r;   r=   r<   r)   r*   r@   r   r   rH      s    zVonMises.expandc                 C   s   | j S )z8
        The provided mean is the circular one.
        r)   r;   r   r   r   mean   s    zVonMises.meanc                 C   s   | j S r   rM   rN   r   r   r   mode   s    zVonMises.modec                 C   s$   dt | jddt | jdd   S )z<
        The provided variance is the circular one.
        r   rB   r   )r   r*   exprN   r   r   r   variance   s    zVonMises.variance)N)__name__
__module____qualname____doc__r   realZpositiveZarg_constraintsZsupportZhas_rsampler:   rE   r   Zno_gradr6   rG   rH   propertyrO   rP   r   rR   __classcell__r   r   r@   r   r   h   s   
	

)r   )r$   r   Z	torch.jitZtorch.distributionsr   Z torch.distributions.distributionr   Ztorch.distributions.utilsr   r   __all__r   Z_I0_COEF_SMALLZ_I0_COEF_LARGEZ_I1_COEF_SMALLZ_I1_COEF_LARGEr   r   r   ZjitZscript_if_tracingr4   r   r   r   r   r   <module>   sb   	



