o
    Td)                    @   s
  d Z 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mZ ddlmZmZmZ ddlmZ ddlmZmZ dd	lmZ dd
lmZ edZejZedZedZdd Ze  Z!dZ"e#ee"Z$e%ee&ee"ee!egZ'e(e'Z)dd Z*dd Z+dd Z,dd Z-dd Z.dd Z/dd Z0dd  Z1d!d" Z2d#d$ Z3d%d& Z4d'd( Z5eej6d)d* Z7eejj6d+d* Z7d,d- Z8eejd.d/ Z9eejjeejj:eejj;eejj<d0d1 Z=eejjeejj:eejj;eejj<d2d3 Z>eej?eej@d4d5 ZAeejjBeejjCd6d7 ZDeejjCd8d9 ZEeejjCd:d; ZFeejjBd<d= ZGeejjCd>d? ZHd@dA ZIdBdC ZJdDdE ZKeejLdFdG ZMdHdI ZNeejOdJdK ZPeejOdLdM ZQdNdO ZReejOdPdQ ZSeejTdRdS ZUeejjTdTdU ZVeejjTdVdW ZWeejjTdXdY ZXeejYdZd[ ZZeejjYd\d] Z[eejYd^d_ Z\eejjYd`da Z]eejYdbdc Z^eejjYddde Z_dfdg Z`eejjYdhdi Zaeejbdjdk Zceejbdldm Zdeejjbdndm Zdeejjbdodp Zeeejfdqdr Zgeejjheejjidsdr Zgeejjidtdr Zgdudv Zjeejjidwdx Zkeejjhdydz Zleejmd{d| Zneejjod}d| Znd~d Zpeejjodd Zqeejrdd Zseejjtdd Zueejjtdd Zueejjveejjtdd Zueejjvdd Zweejjxdd Zyeejjxdd Zzeejjxdd Z{eejjxdd Z|eej}dd Z~dd Zeejdd Zeejjdd Zeejjdd Zeejdd Zeejjdd Zeejjdd Zeejdd Zeejjdd Zdd Zeejjdd Zeejjdd Zeejjdd Zeejjdd Zeejjdd Zeejjdd Zeejjdd Zeejjdd Zeejjdd Zeejjdd Zeejjdd Zeejjdd Zeejjdd Zeejjdd Zeejjdd Zeejjdd ZeejjddÄ Zddń ZeejjddǄ ZeejjddɄ Zeejjdd˄ Zeejjdd̈́ Zddτ Zddф Zeejjddӄ Zeejjddӄ Zeejjddք Zeejjdd؄ Zeejjddڄ Zeejjdd܄ Zeejjddބ Zeejjddބ Zeejjdd Zeejjdd Zdd Zeejjdd Zeejjdd Zeejjdd Zeejjdd Zeejjdd Zeejjdd Zeejjdd Zeejjdd Zeejjdd Zdd Zeejădd Zeejjădd Zeejjƃdd Zeejjȃdd ZeejjɃd d ZeejjʃdddZeejj˃dddZeejj̃dd Zeejj̃dd	dZed
d Zeejj΃dd Zeejj΃dddZedd Zedd ZdS (  z6
Implement the random and np.random module functions.
    N)ir)is_nonelike)	intrinsicoverloadregister_jitable)Registryimpl_ret_untrackedimpl_ret_new_ref	signature)typescgutils)arrayobj)NumbaTypeError
randomimpl    @   c                 C   s   t t| S N)r   Constantint32_t)x r   k/home/ncw/WWW/www-new/content/articles/pi-bbp/venv/lib/python3.10/site-packages/numba/cpython/randomimpl.py	const_int      r   ip  c                 C   sT   |dv sJ d| }t td}t|j||}|jd |jd ||dS )z
    Get a pointer to the given thread-local random state
    (depending on *name*: "py" or "np").
    If the state isn't initialized, it is lazily initialized with
    system entropy.
    )pynpinternalznumba_get_%s_random_stater   readnonenounwind)	r   FunctionTypernd_state_ptr_tr   get_or_insert_functionmodule
attributesaddcall)contextbuildername	func_namefntyfnr   r   r   get_state_ptr4   s   r-   c                 C      t | |dS )z@
    Get a pointer to the thread-local Python random state.
    r   r-   r'   r(   r   r   r   get_py_state_ptrE      r1   c                 C   r.   )z?
    Get a pointer to the thread-local Numpy random state.
    r   r/   r0   r   r   r   get_np_state_ptrK   r2   r3   c                 C   r.   )zB
    Get a pointer to the thread-local internal random state.
    r   r/   r0   r   r   r   get_internal_state_ptrQ   r2   r4   c                 C   s   t | |ddS Nr   r   gep_inboundsr(   	state_ptrr   r   r   get_index_ptrX      r:   c                 C      t | |ddS Nr      r6   r8   r   r   r   get_array_ptr[   r;   r?   c                 C   r<   )Nr      r6   r8   r   r   r   get_has_gauss_ptr^   r;   rA   c                 C   r<   )Nr      r6   r8   r   r   r   get_gauss_ptra   r;   rC   c                 C   s8   t t  tf}t| jj|d}|jd 	d |S )z<
    Get the internal function to shuffle the MT taste.
    numba_rnd_shuffler   	nocapture)
r   r    VoidTyper!   r   r"   functionr#   argsadd_attribute)r(   r+   r,   r   r   r   get_rnd_shuffled   s   rJ   c           	   
   C   s6  t ||}||}|d|t}t|| t|}|||f |t	d| W d   n1 s5w   Y  ||}t
||}|t||d|}||t	d}||| ||||t	d}|||||t	dt	d}|||||t	dt	d	}||||t	d
}|S )zB
    Get the next int32 generated by the PRNG at *state_ptr*.
    >=r   Nr>         l   VX:    l     _    )r:   loadicmp_unsignedN_constr   if_unlikelyrJ   r&   storer   r?   r7   r%   xorlshrand_shl)	r'   r(   r9   idxptridxneed_reshuffler,   	array_ptryr   r   r   get_next_int32o   s,   



r^   c                 C   st   | t| ||td}| t| ||td}||t}||t}|||||t	tdt	tdS )zC
    Get the next double generated by the PRNG at *state_ptr*.
          g      Ag      @C)
rV   r^   r   uitofpdoublefdivfaddfmulr   r   )r'   r(   r9   abr   r   r   get_next_double   s   
rh   c                    sL  t |jd fdd}t t td} d|} |r\}}	| ||}
  	|
t| W d   n1 sEw   Y  |	> rW| 
|}t }
sg| 
|}  	|
t  	|tt td} || W d   n1 sw   Y  W d   n1 sw   Y   |S )z2
    Get the next integer with width *nbits*.
    r   c                    s     | }t }| jj|jjk r ||j}n| jj|jjkr+ ||j}rC t|jd} 	||} 
||S  	||S r5   )subr^   typewidthzexttruncnot_r   r   rV   rW   )nbitsshiftr]   maskr(   c32r'   is_numpyr9   r   r   get_shifted_int   s   z%get_next_int.<locals>.get_shifted_intr   <=N)r   r   rj   r   alloca_once_valueint64_trQ   if_elserT   rl   ri   r^   r%   rX   rP   )r'   r(   r9   ro   rt   ru   retis_32bifsmalliflargelowhightotalr   rr   r   get_next_int   s4   


r   c                 C      t | tjr
tdS d S Nr   
isinstancer   Integer
_seed_implseedr   r   r   	seed_impl      r   c                 C   r   Nr   r   r   r   r   r   r      r   c                    s   t fdd  fddS )Nc                    s    fdd}t tjtj|fS )Nc                    sR   |\}t t  ttf}t|jj|d}|	|t
| | |f | tjd S )Nnumba_rnd_init)r   r    rF   r!   r   r   r"   rG   r#   r&   r-   get_constantr   none)r'   r(   sigrH   
seed_valuer+   r,   
state_typer   r   codegen   s   z*_seed_impl.<locals>._impl.<locals>.codegen)r   r   voiduint32)typingcontextr   r   r   r   r   _impl   s   z_seed_impl.<locals>._implc                        | S r   r   r   r   r   r   <lambda>       z_seed_impl.<locals>.<lambda>r   r   r   )r   r   r   r      s   
r   c                         t dd   fddS )Nc                 S      dd }t tj|fS )Nc                 S      t | |d}t| ||S r   r-   rh   r'   r(   r   rH   r9   r   r   r   r         z+random_impl.<locals>._impl.<locals>.codegen)r   r   rb   r   r   r   r   r   r         zrandom_impl.<locals>._implc                           S r   r   r   r   r   r   r          zrandom_impl.<locals>.<lambda>r   r   r   r   r   random_impl   s   
r   c                      r   )Nc                 S   r   )Nc                 S   r   r   r   r   r   r   r   r      r   z,random_impl0.<locals>._impl.<locals>.codegen)r   r   float64r   r   r   r   r      r   zrandom_impl0.<locals>._implc                      r   r   r   r   r   r   r   r      r   zrandom_impl0.<locals>.<lambda>r   r   r   r   r   random_impl0   s   
r   c                 C   J   t | rdd S t| tjst| tjr!t| jtjr#dd }|S d S d S )Nc                 S   
   t j S r   r   randomsizer   r   r   r        
 zrandom_impl1.<locals>.<lambda>c                 S   s2   t | }|j}t|jD ]	}t j ||< q|S r   )r   emptyflatranger   r   r   outout_flatrZ   r   r   r   r     
   
zrandom_impl1.<locals>._implr   r   r   r   UniTupledtyper   r   r   r   r   random_impl1   s   r   c                    D   t | tjtjfrt |tjtjfr tdd   fddS d S d S )Nc                 S   *   t |}t |}ttj||td||fS r   _double_preprocessorr   r   r   _gauss_implr   locscaleloc_preprocessorscale_preprocessorr   r   r   r     
   
zgauss_impl.<locals>._implc                    
    | |S r   r   r   r   r   r   r   r     r   zgauss_impl.<locals>.<lambda>r   r   Floatr   r   r   r   r   r   
gauss_impl  s   
r   c                   C      dd S )Nc                   S      t jddS N              ?r   r   normalr   r   r   r   r          z np_gauss_impl0.<locals>.<lambda>r   r   r   r   r   np_gauss_impl0  s   r   c                 C      t | tjtjfrdd S d S )Nc                 S      t j| dS Nr   r   r   r   r   r   r   &  r   z np_gauss_impl1.<locals>.<lambda>r   r   r   r   r   r   r   r   np_gauss_impl1#     r   c                    r   )Nc                 S   r   r   r   r   r   r   r   r   -  r   znp_gauss_impl2.<locals>._implc                    r   r   r   r   r   r   r   r   3  r   z np_gauss_impl2.<locals>.<lambda>r   r   r   r   r   np_gauss_impl2)     
r   c                 C   r   )Nc                 S   
   t j S r   r   r   standard_normalr   r   r   r   r   9  r   z'standard_normal_impl1.<locals>.<lambda>c                 S   2   t | }|j}t|jD ]	}t j ||< q|S r   )r   r   r   r   r   r   r   r   r   r   r   r   =  r   z$standard_normal_impl1.<locals>._implr   r   r   r   r   standard_normal_impl16     r   c                 C      t | tjtjfrt |tjtjfrt|rdd S t | tjtjfrEt |tjtjfrGt |tjs?t |tjrIt |jtjrKdd }|S d S d S d S d S )Nc                 S      t j| |S r   r   r   r   r   r   r   r   r   K  r   z np_gauss_impl3.<locals>.<lambda>c                 S   6   t |}|j}t|jD ]}t j| |||< q|S r   )r   r   r   r   r   r   r   r   r   r   r   r   rZ   r   r   r   r   Q  
   
znp_gauss_impl3.<locals>._implr   r   r   r   r   r   r   r   r   r   r   r   r   r   np_gauss_impl3F  (   

r   c                        fdd}|S )Nc                     sj   	 d   d } d   d }| |  ||  }|dk r |dkr nqt dt | | }||  || fS )zG
        Compute a pair of numbers on the normal distribution.
        T       @r   r          )mathsqrtlog)x1x2r2f_randomr   r   compute_gauss_pair[  s   z,_gauss_pair_impl.<locals>.compute_gauss_pairr   )r   r   r   r   r   _gauss_pair_implZ  s   r   c                        fdd}|S )Nc                    s  |j }| |}tjtjjd }t| |}tj||dd}t||}	t||}
t	||
|
}||l\}}| ||
|	| |td|
 W d    n1 sYw   Y  |5 | |t|tt|dd}t||d\}}|||	 ||| |td|
 W d    n1 sw   Y  W d    n1 sw   Y  |\}}| ||||||
|S )N)r   r   resultr)   r   r@   r   r>   )return_typeget_data_typer   r   r-   r   alloca_oncerC   rA   is_truerP   ry   rT   r   compile_internalr   r   r   r   unpack_tuplerd   re   )r'   r(   r   rH   tylltyr   r9   rz   	gauss_ptrhas_gauss_ptr	has_gaussthen	otherwisepairfirstsecondmusigmar   r   stater   r   r   m  sH   


z_gauss_impl.<locals>._implr   )r  r   r   r   r   r  r   r   l  s   $r   c                    sj   t j  t| tjr| jr fddS  fddS t| tjr/| jdkr+ fddS dd S td|  )Nc                       |  | S r   )sitofpr(   vr  r   r   r         z&_double_preprocessor.<locals>.<lambda>c                    r  r   )ra   r  r  r   r   r     r  r   c                    r  r   )fpextr  r  r   r   r     r  c                 S      |S r   r   )_builderr  r   r   r   r         z(Cannot convert {} to floating point type)	r   r   
DoubleTyper   r   signedr   bitwidth	TypeError)valuer   r  r   r     s   

r   c                    s(   t | tjrtdd   fddS d S )Nc                 S   s   dd }t tj||fS )Nc           	      S   s   |\}| d|td}| d|td}t|||| d}| j|t|f W d    n1 s5w   Y  t| |d}t	| |||dS )NrK   A   ==r   z getrandbits() limited to 64 bitsr   F)
rQ   r   r   rS   or_	call_convreturn_user_excOverflowErrorr-   r   )	r'   r(   r   rH   ro   	too_large	too_smallmsgr9   r   r   r   r     s   
z0getrandbits_impl.<locals>._impl.<locals>.codegen)r   r   uint64)r   kr   r   r   r   r     s   zgetrandbits_impl.<locals>._implc                    r   r   r   r.  r   r   r   r     r   z"getrandbits_impl.<locals>.<lambda>)r   r   r   r   r/  r   r   r   getrandbits_impl  s
   
r0  c              	      s  t  td}td}	tj dd}
  |||
   d||!  	 	 
|
||	} || |
 W d    n1 sRw   Y    d||	!   	 
|
||	} || |
 W d    n1 sw   Y   
|
t  d| d}j t|f W d    n1 sw   Y  ttjjg}t jj|d	 }d
krԈ |	n}  ||tjgt ttjtj dd fdd}d
krU  d|	9\}}|  | W d    n	1 s)w   Y  | |  W d    n	1 s?w   Y  W d    n	1 sOw   Y  n|   	|  
|S )Nr   r>   nr   <>rv   zempty range for randrange()zllvm.ctlz.%sr   rc                     s~     d}   d} |   |  t dk} |} d|} || |  |  | d S )Nwhilez	while.endr   rK   )append_basic_blockbranchposition_at_endr   rm   icmp_signedcbranchrT   )bbwhilebbendr4  r*  r(   r'   r1  ro   rptrr  r9   r  r   r   get_num  s   




z _randrange_impl.<locals>.get_numr%  )r-   r   r   r   r  rT   ri   if_thenr9  r%   rP   sdivrS   r'  r(  
ValueErrorr    true_bitrj   r"   rG   r#   rm   r&   r   rk   ry   mul)r'   r(   startstopstepr  r   r  zeroonenptrwr,  r+   r,   nm1r?  is_one
is_not_oner   r=  r   _randrange_impl  sT   


rO  c                 C      t | tjr
dd S d S )Nc                 S   s   t d| dS r=   r   	randrangerF  r   r   r   r     r   z"randrange_impl_1.<locals>.<lambda>r   r   r   rS  r   r   r   randrange_impl_1   r   rU  c                 C   (   t | tjrt |tjrdd S d S d S )Nc                 S   s   t | |dS Nr>   rQ  rE  rF  r   r   r   r   	  r   z"randrange_impl_2.<locals>.<lambda>rT  rX  r   r   r   randrange_impl_2     rY  c                 C   s(   |j | kr|jrtjjS tjjS dd S )Nc                 S   r  r   r   )r  r  _tyr   r   r   r     r  z)_randrange_preprocessor.<locals>.<lambda>)r!  r   r   	IRBuildersextrl   )r!  r  r   r   r   _randrange_preprocessor  s
   
r^  c                    s   t | tjrRt |tjrTt |tjrVt| j|j|jt| j|j|j}tj|t|t	|| t	||t	||t
fdd  fddS d S d S d S )Nc                    s&   fdd}t  ||||fS )Nc              	      sD   |\}}}|| }|| }|| }t | |||| dS r   )rO  r'   r(   r   rH   rE  rF  rG  )	llvm_typer   start_preprocessorstep_preprocessorstop_preprocessorr   r   r   #  s   
z0randrange_impl_3.<locals>._impl.<locals>.codegenr
   )r   rE  rF  rG  r   )int_tyr`  r   ra  rb  rc  r   r   r   !  s   zrandrange_impl_3.<locals>._implc                    s    | ||S r   r   )rE  rF  rG  r   r   r   r   ,  r  z"randrange_impl_3.<locals>.<lambda>r   r   r   maxr   r!  from_bitwidthr   IntTyper^  r   )rE  rF  rG  r!  r   )r   rd  r`  r   ra  rb  rc  r   randrange_impl_3  s   





ri  c                 C   rV  )Nc                 S   s   t | |d dS rW  rQ  rX  r   r   r   r   2  s    z randint_impl_1.<locals>.<lambda>rT  rX  r   r   r   randint_impl_1/  rZ  rj  c                 C   rP  )Nc                 S   s   t jd| S r5   r   r   randintr   r   r   r   r   8  r   z#np_randint_impl_1.<locals>.<lambda>rT  rm  r   r   r   np_randint_impl_15  r   rn  c                    s   t | tjrBt |tjrDt| j|jt| j|j}tj|t|t	|| t	||t
fdd  fddS d S d S )Nc                    s"   fdd}t  |||fS )Nc              	      sB   |\}}|| }|| }t  d}t| |||| dS )Nr>   r   )r   r   rO  r_  )r`  r   ra  rc  r   r   r   H  s   z1np_randint_impl_2.<locals>._impl.<locals>.codegenr
   )r   r~   r   r   )rd  r`  r   ra  rc  r   r   r   F  s   z np_randint_impl_2.<locals>._implc                    r   r   r   r~   r   r   r   r   r   Q  r   z#np_randint_impl_2.<locals>.<lambda>re  )r~   r   r!  r   )r   rd  r`  r   ra  rc  r   np_randint_impl_2;  s   



rp  c                    s   t | tjrt |tjrt|rdd S t | tjrJt |tjrLt |tjs3t |tjrNt |jtjrPt| j|j}tt	d|   fdd}|S d S d S d S d S )Nc                 S   r   r   rk  r~   r   r   r   r   r   r   X  r   z#np_randint_impl_3.<locals>.<lambda>intc                    s:   t j| d}|j}t|jD ]}t j| |||< q|S N)r   )r   r   r   r   r   r   rl  r~   r   r   r   r   rZ   result_typer   r   r   `  s
   z np_randint_impl_3.<locals>._impl)
r   r   r   r   r   r   rf  r!  getattrr   )r~   r   r   r!  r   r   ru  r   np_randint_impl_3T  s$   

rx  c                   C   r   )Nc                   S   s   t ddS r   r   uniformr   r   r   r   r   k  r  zuniform_impl0.<locals>.<lambda>r   r   r   r   r   uniform_impl0i     r{  c                   C   r   )Nc                   S   r   r   r   r   rz  r   r   r   r   r   p  r   z"np_uniform_impl0.<locals>.<lambda>r   r   r   r   r   np_uniform_impl0n  r|  r~  c                 C   r   )Nc                 S   s   t | dS r   ry  r~   r   r   r   r   v  r  zuniform_impl1.<locals>.<lambda>r   r  r   r   r   uniform_impl1s  r   r  c                 C   r   )Nc                 S   r   r   r}  r  r   r   r   r   |  r   z"np_uniform_impl1.<locals>.<lambda>r   r  r   r   r   np_uniform_impl1y  r   r  c                    r   )Nc                 S   r   r   r   r   r   r   uniform_implr   r~   r   low_preprocessorhigh_preprocessorr   r   r   r     
   zuniform_impl2.<locals>._implc                    r   r   r   ro  r   r   r   r     r   zuniform_impl2.<locals>.<lambda>r   ro  r   r   r   uniform_impl2  r   r  c                    r   )Nc                 S   r   r   r  r  r   r   r   r     r  znp_uniform_impl2.<locals>._implc                    r   r   r   ro  r   r   r   r     r   z"np_uniform_impl2.<locals>.<lambda>r   ro  r   r   r   np_uniform_impl2  r   r  c                    r   )Nc           	         sT   t | |}|\}} ||}||}|||}t| ||}|||||S r   )r-   fsubrh   rd   re   )	r'   r(   r   rH   r9   rf   rg   rk   r4  a_preprocessorb_preprocessorr  r   r   impl  s   

zuniform_impl.<locals>.implr   )r  r  r  r  r   r  r   r    s   r  c                 C   r   )Nc                 S   r   r   r}  rq  r   r   r   r     r   z"np_uniform_impl3.<locals>.<lambda>c                 S   r   r   )r   r   r   r   r   r   rz  rt  r   r   r   r     r   znp_uniform_impl3.<locals>._implr   )r~   r   r   r   r   r   r   np_uniform_impl3  r   r  c                 C   s8   dd }t | tjtjfrt |tjtjfr|S d S d S )Nc                 S   s@   t   }d}||krd| }|| } }| ||  t||   S )N      ?r   r   r   r   )r~   r   ucr   r   r   r     s   
z triangular_impl_2.<locals>._implr   )r~   r   r   r   r   r   triangular_impl_2  s   r  c                 C   N   t | tjtjfr!t |tjtjfr#t |tjtjfr%dd }|S d S d S d S )Nc                 S   s`   || kr| S t   }||  ||   }||kr#d| }d| }|| } }| ||  t||   S r   r  )r~   r   moder  r  r   r   r   r     s   
 triangular_impl_3.<locals>._implr   )r~   r   r  r   r   r   r   triangular_impl_3     r  c                 C   r  )Nc                 S   sb   || kr| S t j }||  ||   }||kr$d| }d| }|| } }| ||  t||   S r   )r   r   r   r   )r~   r  r   r  r  r   r   r   r     s   

r  r   )r~   r  r   r   r   r   r   r    r  c                 C   J   t |rdd S t|tjst|tjr!t|jtjr#dd }|S d S d S )Nc                 S      t j| ||S r   )r   r   
triangular)r~   r   r  r   r   r   r   r     s   
 z!triangular_impl.<locals>.<lambda>c                 S   s8   t |}|j}t|jD ]}t j| ||||< q|S r   )r   r   r   r   r   r   r  )r~   r   r  r   r   r   rZ   r   r   r   r     s
   
ztriangular_impl.<locals>._implr   )r~   r   r  r   r   r   r   r   triangular_impl     r  c                 C   s6   t | tjtjfrt |tjtjfrttjS d S d S r   )r   r   r   r   _gammavariate_implr   alphabetar   r   r   gammavariate_impl  
   
r  c                 C   r   )Nc                 S   r   r   r   r   gammar  r   r   r   r   
  r   z#gammavariate_impl.<locals>.<lambda>r   r  r   r   r   r    s   c                 C   s8   t | tjtjfrt |tjtjfrttjjS d S d S r   )r   r   r   r   r  r   r   r  r   r   r   r    
   c                    r   )Nc                    s  dt d }| dks|dkrtd| dkrvt d|  d }| t d }| | }	   }d|  k r9d	k s;n q+d   }t |d|  | }| t | }	|| | }
|||  |	 }|| d|
  dksq|t |
kru|	| S q,| dkrt d    | S 	   }t j|  t j }|| }|dkr|d|   }	n
t || |   }	  }|dkr||	| d  kr	 |	| S n|t |	 kr	 |	| S q)
z1Gamma distribution.  Taken from CPython.
        r   g      @r   z*gammavariate: alpha and beta must be > 0.0r   g      @r>   gHz>gP?)r   r   rB  r   expe)r  r  SG_MAGICCONSTainvbbbcccu1u2r  r   zr4  r  rg   pr   r   r   r     sL   
"z!_gammavariate_impl.<locals>._implr   r   r   r   r   r   r    s   7r  c                 C   J   t |rdd S t|tjst|tjr!t|jtjr#dd }|S d S d S )Nc                 S   r   r   r  r  r  r   r   r   r   r   R  r   zgamma_impl.<locals>.<lambda>c                 S   r   r   )r   r   r   r   r   r   r  r  r  r   r   r   rZ   r   r   r   r   V  r   zgamma_impl.<locals>._implr   r  r  r   r   r   r   r   
gamma_implO  r   r  c                 C   J   t |rdd S t|tjst|tjr!t|jtjr#dd }|S d S d S )Nc                 S      t j| S r   r   r   standard_gammar  r   r   r   r   r   b  r  z%standard_gamma_impl.<locals>.<lambda>c                 S   4   t |}|j}t|jD ]
}t j| ||< q|S r   )r   r   r   r   r   r   r  r  r   r   r   rZ   r   r   r   r   f  
   
z"standard_gamma_impl.<locals>._implr   r  r   r   r   r   r   standard_gamma_impl_  r   r  c                 C   s6   t | tjtjfrt |tjtjfrttjS d S d S r   )r   r   r   r   _betavariate_implr   gammavariater  r   r   r   betavariate_implo  r  r  c                 C   8   t | tjtjfrt |tjtjfrttjjS d S d S r   )r   r   r   r   r  r   r   r  r  r   r   r   r  v  r  c                    r   )Nc                    s(    | d}|dkrdS || |d  S )z0Beta distribution.  Taken from CPython.
        r   r   r   )r  r  r]   r  r   r   r   ~  s   
z _betavariate_impl.<locals>._implr   )r  r   r   r  r   r  }  s   
r  c                 C   r  )Nc                 S   r   r   )r   r   r  r  r   r   r   r     r   zbeta_impl.<locals>.<lambda>c                 S   r   r   )r   r   r   r   r   r   r  r  r   r   r   r     r   zbeta_impl.<locals>._implr   r  r   r   r   	beta_impl  r   r  c                 C      t | tjrdd }|S d S )Nc                 S   s   t dt   |  S )z;Exponential distribution.  Taken from CPython.
            r   )r   r   r   )lambdr   r   r   r     s   zexpovariate_impl.<locals>._implr   r   r   )r  r   r   r   r   expovariate_impl  s   
r  c                 C   "   t | tjtjfrdd }|S d S )Nc                 S   s   t dtj   |  S r   r   r   r   r   )r   r   r   r   r     s   exponential_impl.<locals>._implr   )r   r   r   r   r   exponential_impl  s   r  c                 C   r  )Nc                 S   r  r   )r   r   exponential)r   r   r   r   r   r     r  z"exponential_impl.<locals>.<lambda>c                 S   r  r   )r   r   r   r   r   r   r  )r   r   r   r   rZ   r   r   r   r     r  r  r   )r   r   r   r   r   r   r    r   c                  C      dd } | S )Nc                   S   s   t dtj   S r   r  r   r   r   r   r     s   r  r   r   r   r   r   r    s   c                 C   r   )Nc                 S   r   r   )r   r   standard_exponentialr   r   r   r   r     r   z+standard_exponential_impl.<locals>.<lambda>c                 S   r   r   )r   r   r   r   r   r   r  r   r   r   r   r     r   z(standard_exponential_impl.<locals>._implr   r   r   r   r   standard_exponential_impl  s   
r  c                   C   r   )Nc                   S   r   r   r   r   	lognormalr   r   r   r   r     r   z$np_lognormal_impl0.<locals>.<lambda>r   r   r   r   r   np_lognormal_impl0  r|  r  c                 C   r   )Nc                 S   r   r   r  r  r   r   r   r     r   z%np_log_normal_impl1.<locals>.<lambda>r   r  r   r   r   np_log_normal_impl1  r   r  c                 C   r  r   )r   r   r   r   _lognormvariate_implr   r   r   r  r  r   r   r   np_log_normal_impl2  r  r  c                 C   r  )Nc                 S   r   r   r  )r  r  r   r   r   r   r     r   z lognormal_impl.<locals>.<lambda>c                 S   r   r   )r   r   r   r   r   r   r  )r  r  r   r   r   rZ   r   r   r   r     r   zlognormal_impl.<locals>._implr   )r  r  r   r   r   r   r   lognormal_impl  r   r  c                 C   s*   t | tjrt |tjrttjS d S d S r   )r   r   r   r  r   gaussr  r   r   r   lognormvariate_impl     
r  c                    s    fddS )Nc                    s   t  | |S r   )r   r  r  _gaussr   r   r     s    z&_lognormvariate_impl.<locals>.<lambda>r   r  r   r  r   r    r   r  c                 C   r  )Nc                 S   s   dt    }d|d|    S )z)Pareto distribution.  Taken from CPython.r   )r   r  r  r   r   r   r     s   z!paretovariate_impl.<locals>._implr  r  r   r   r   r   paretovariate_impl  s   r  c                 C   r  )Nc                 S   s"   dt j  }d|d|    d S )Nr   r>   r   r  r   r   r   r        pareto_impl.<locals>._implr  r  r   r   r   pareto_impl  s   r  c                 C   r  )Nc                 S   r  r   )r   r   paretor  r   r   r   r   "  r  zpareto_impl.<locals>.<lambda>c                 S   r  r   )r   r   r   r   r   r   r  r  r   r   r   r   &  r  r  r   r  r   r   r   r    r   c                 C   8   t | tjtjfrt |tjtjfrdd }|S d S d S )Nc                 S   s$   dt    }| t| d|   S )z*Weibull distribution.  Taken from CPython.r   )r   r   r   )r  r  r  r   r   r   r   3  s   z"weibullvariate_impl.<locals>._implr   )r  r  r   r   r   r   weibullvariate_impl/  s   r  c                 C   r  )Nc                 S   s"   dt j  }t| d|   S r   r   r   r   r   )r  r  r   r   r   r   ?  r  zweibull_impl.<locals>._implr   )r  r   r   r   r   weibull_impl<  s   r  c                 C   r  )Nc                 S   r  r   )r   r   weibull)r  r   r   r   r   r   J  r  zweibull_impl2.<locals>.<lambda>c                 S   r  r   )r   r   r   r   r   r   r  )r  r   r   r   rZ   r   r   r   r   N  r  zweibull_impl2.<locals>._implr   )r  r   r   r   r   r   weibull_impl2G  r   r  c                 C   s*   t | tjrt |tjrttjS d S d S r   )r   r   r   _vonmisesvariate_implr   r  kappar   r   r   vonmisesvariate_implW  r  r  c                 C   s,   t | tjrt |tjrttjjS d S d S r   )r   r   r   r  r   r   r  r   r   r   r  ]  s   c                    r   )Nc                    s   |dkrdt j    S d| }|t d||   }	   }t t j| }|||  }  }|d||  k sC|d| t | krDnqd| }|| d||   }	  }
|
dkrh| t |	 dt j  }|S | t |	 dt j  }|S )zCircular data distribution.  Taken from CPython.
        Note the algorithm in Python 2.6 and Numpy is different:
        http://bugs.python.org/issue17141
        gư>r   r  r   )r   pir   cosr  acos)r  r  sr4  r  r  dr  qr   u3thetar   r   r   r   d  s(   &	z$_vonmisesvariate_impl.<locals>._implr   r  r   r   r   r  c  s   (r  c                 C   r  )Nc                 S   r   r   )r   r   vonmises)r  r  r   r   r   r   r     r   zvonmises_impl.<locals>.<lambda>c                 S   r   r   )r   r   r   r   r   r   r  )r  r  r   r   r   rZ   r   r   r   r     r   zvonmises_impl.<locals>._implr   )r  r  r   r   r   r   r   vonmises_impl  r   r  c                 C   2   t | tjrt |tjtjfrdd }|S d S d S )Nc                 S   s\  | dk rt dd|  krdkst d t d|dkr dS |dkr&| S |dk}|r0d| }d| }d}||  }|dkrT|d	K }| d	L } ||  }| dksPJ |dks>| | }t| |d
t|| d   }d}|dkrd}	tj }
|}|	|kr|
|kr||r| |	 n|	7 }|d8 }n|
|8 }
|	d7 }	| |	 d | | |	|  }|	|ks{|dksn|S )z
            Binomial distribution.  Numpy's variant of the BINV algorithm
            is used.
            (Numpy uses BTPE for n*p >= 30, though)
            r   zbinomial(): n <= 0r   r   zbinomial(): p outside of [0, 1]r  r>   gx0 r@         $@)rB  minr   r   r   r   )r1  r  flippedr  nitersqnnp_prodboundr   XUpxr   r   r   r     sP    
binomial_impl.<locals>._implr   r   r   r   r1  r  r   r   r   r   binomial_impl  s   1r  c                 C   r  )Nc                 S   r   r   )r   r   binomial)r1  r  r   r   r   r   r     r   zbinomial_impl.<locals>.<lambda>c                 S   s<   t j|t jd}|j}t|jD ]}t j| |||< q|S rs  )r   r   intpr   r   r   r   r  )r1  r  r   r   r   rZ   r   r   r   r     s
   r	  r   )r1  r  r   r   r   r   r   r    r   c                 C   r  )Nc                 S   s   dt j| d  S Nr   r  )dfr   r   r   r        zchisquare_impl.<locals>._implr   r  r   r   r   r   chisquare_impl  s   r  c                 C   r  )Nc                 S   r  r   r   r   	chisquarer  r   r   r   r   r     r  z!chisquare_impl2.<locals>.<lambda>c                 S   r  r   )r   r   r   r   r   r   r  r  r   r   r   rZ   r   r   r   r     r  zchisquare_impl2.<locals>._implr   r  r   r   r   r   r   chisquare_impl2  r   r  c                 C   r  )Nc                 S   s    t j| | t j||   S r   r  )numdenomr   r   r   r     s   f_impl.<locals>._implr   )r  r  r   r   r   r   f_impl      r  c                 C   sn   t | tjtjfrt |tjtjfrt|rdd S t |tjs-t |tjr3t |jtjr5dd }|S d S d S )Nc                 S   r   r   )r   r   r   )r  r  r   r   r   r   r     r   zf_impl.<locals>.<lambda>c                 S   r   r   )r   r   r   r   r   r   r   )r  r  r   r   r   rZ   r   r   r   r     r   r  r   )r  r  r   r   r   r   r   r    s   c                 C   r  )Nc                 S   s   | dks| dkrt dd|  }| dkr7td}|  }}tj }||kr5||9 }||7 }|d7 }||ks%|S ttdtj  t| S )Nr   r   z geometric(): p outside of (0, 1]gUUUUUU?r>   )rB  rr  r   r   r   ceilr   )r  r  r  sumprodr  r   r   r   r      s    
geometric_impl.<locals>._implr   )r  r   r   r   r   geometric_impl  s   r#  c                 C   r  )Nc                 S   r  r   )r   r   	geometricr  r   r   r   r   8  r  z geometric_impl.<locals>.<lambda>c                 S   :   t j|t jd}|j}t|jD ]
}t j| ||< q|S rs  )r   r   int64r   r   r   r   r$  r  r   r   r   r   <  
   r"  r   r  r   r   r   r#  5  r   c                 C   r  )Nc                 S   s(   dt j  }| |tt|   S r   r  r   r   r  r   r   r   r   I  s   zgumbel_impl.<locals>._implr   )r   r   r   r   r   r   gumbel_implE  r  r)  c                 C   r  )Nc                 S   r   r   )r   r   gumbelr   r   r   r   r   S  r   zgumbel_impl3.<locals>.<lambda>c                 S   r   r   )r   r   r   r   r   r   r*  r   r   r   r   r   W  r   zgumbel_impl3.<locals>._implr   r   r   r   r   gumbel_impl3P  r   r+  c                 C   r  )Nc                 S   s   t |t |  t | }tt|| }|}t |}|dkr=|dkr=|ttj |||   8 }|d8 }|dkr=|dks!t || }| |krMt || S |S )z'Numpy's algorithm for hypergeometric().r   r   r>   )rr  floatr   r   floorr   r   )ngoodnbadnsamplesd1d2YKZr   r   r   r   e  s    "hypergeometric_impl.<locals>._implr   )r.  r/  r0  r   r   r   r   hypergeometric_impl`  s   r7  c                 C   r  )Nc                 S   r  r   )r   r   hypergeometric)r.  r/  r0  r   r   r   r   r   {  r;   z%hypergeometric_impl.<locals>.<lambda>c                 S   s>   t j|t jd}|j}t|jD ]}t j| ||||< q|S rs  )r   r   r  r   r   r   r   r8  )r.  r/  r0  r   r   r   rZ   r   r   r   r     s
   r6  r   )r.  r/  r0  r   r   r   r   r   r7  x  r  c                   C   r   )Nc                   S   r   r   r   r   laplacer   r   r   r   r     r   zlaplace_impl0.<locals>.<lambda>r   r   r   r   r   laplace_impl0  r|  r;  c                 C   r   )Nc                 S   r   r   r9  r   r   r   r   r     r   zlaplace_impl1.<locals>.<lambda>r   r   r   r   r   laplace_impl1  r   r<  c                 C   0   t | tjtjfrt |tjtjfrtS d S d S r   )r   r   r   r   laplace_implr   r   r   r   laplace_impl2  
   r?  c                 C   r  )Nc                 S   r   r   r9  r   r   r   r   r     r   zlaplace_impl3.<locals>.<lambda>c                 S   r   r   )r   r   r   r   r   r   r:  r   r   r   r   r     r   zlaplace_impl3.<locals>._implr   r   r   r   r   laplace_impl3  r   rA  c                 C   sB   t j }|dk r| |t||   S | |td| |   S )Nr  r   r  r(  r   r   r   r>    s   
r>  c                   C   r   )Nc                   S   r   r   r   r   logisticr   r   r   r   r     r   z logistic_impl0.<locals>.<lambda>r   r   r   r   r   logistic_impl0  r|  rD  c                 C   r   )Nc                 S   r   r   rB  r   r   r   r   r     r   z logistic_impl1.<locals>.<lambda>r   r   r   r   r   logistic_impl1  r   rE  c                 C   r=  r   )r   r   r   r   logistic_implr   r   r   r   logistic_impl2  r@  rG  c                 C   r  )Nc                 S   r   r   rB  r   r   r   r   r     r   z logistic_impl3.<locals>.<lambda>c                 S   r   r   )r   r   r   r   r   r   rC  r   r   r   r   r     r   zlogistic_impl3.<locals>._implr   r   r   r   r   logistic_impl3  r   rH  c                 C   s$   t j }| |t|d|    S r   r  r(  r   r   r   rF    s   
rF  c                 C   s   | dks| dkrt dtd|  }	 tj }|| krdS tj }dt||  }||| krBtdt|t|  S ||krHdS dS )z"Numpy's algorithm for logseries().r   r   z logseries(): p outside of (0, 1]r>   r@   )rB  r   r   r   r   r  r&  )r  r4  Vr  r  r   r   r   _logseries_impl  s   

rJ  c                 C      t | tjtjfrtS d S r   )r   r   r   r   rJ  )r  r   r   r   logseries_impl     rL  c                 C   r  )Nc                 S   r  r   )r   r   	logseriesr  r   r   r   r     r  z logseries_impl.<locals>.<lambda>c                 S   r%  rs  )r   r   r&  r   r   r   r   rN  r  r   r   r   r     r'  zlogseries_impl.<locals>._implr   r  r   r   r   rL    r   c                 C   r  )Nc                 S   sJ   | dkrt d|dk s|dkrt dtj| d| | }tj|S )Nr   znegative_binomial(): n <= 0r   r   z(negative_binomial(): p outside of [0, 1])rB  r   r   r  poisson)r1  r  r3  r   r   r   r   	  s   z%negative_binomial_impl.<locals>._implr
  r  r   r   r   negative_binomial_impl  s   rP  c                   C   r   )Nc                   S      t jdS r   r   r   rO  r   r   r   r   r     r  zpoisson_impl0.<locals>.<lambda>r   r   r   r   r   poisson_impl0  r|  rS  c                    s.   t | tjtjfrtdd   fddS d S )Nc                    s$   t |  fdd}ttj||fS )Nc                    s0  t | |}tj|tdd}|d}|d}|\}||}|d|ttd}	|	|	, t
tttf}
t|jj|
d}||||f}||| || W d    n1 s^w   Y  || || tjjtj  fdd	}| ||||}||| || || ||S )
Nrz   r   bbcontr<  rK   r  numba_poisson_ptrsc                    sT   | dk rt d| dkrdS  |  }d}d}	  }||9 }||kr%|S |d7 }q)ag  Numpy's algorithm for poisson() on small *lam*.

                    This method is invoked only if the parameter lambda of the
                    distribution is small ( < 10 ). The algorithm used is
                    described in "Knuth, D. 1969. 'Seminumerical Algorithms.
                    The Art of Computer Programming' vol 2.
                    r   zpoisson(): lambda < 0r   r   r>   rB  )lamenlamr  r!  r  _expr   r   r   poisson_impl<  s   
zCpoisson_impl1.<locals>._impl.<locals>.codegen.<locals>.poisson_impl)r3   r   r  rx   r6  fcmp_orderedr   r   rb   r@  r    r!   r"   rG   r#   r&   rT   r7  r8  r   r   r   r  r  rP   )r'   r(   r   rH   r9   retptrrT  r<  rW  big_lamr+   r,   rz   r[  lam_preprocessorrY  r   r      s:   










z-poisson_impl1.<locals>._impl.<locals>.codegen)r   r   r   r&  )r   rW  r   r   r_  r   r     s   7zpoisson_impl1.<locals>._implc                    r   r   r   rW  r   r   r   r   X  r   zpoisson_impl1.<locals>.<lambda>r   ra  r   r   r   poisson_impl1  s
   
;rb  c                 C   sr   t | tjtjfrt|rdd S t | tjtjfr3t |tjs-t |tjr5t |jtjr7dd }|S d S d S d S )Nc                 S   r  r   rR  )rW  r   r   r   r   r   ^  r  zpoisson_impl2.<locals>.<lambda>c                 S   r%  rs  )r   r   r  r   r   r   r   rO  )rW  r   r   r   rZ   r   r   r   r   d  r'  zpoisson_impl2.<locals>._implr   )rW  r   r   r   r   r   poisson_impl2[  s   

rc  c                 C   r  )Nc                 S   s2   | dkrt dtdttj   d|  S )Nr   zpower(): a <= 0r>   r   )rB  r   powr  r   r   r  rf   r   r   r   r   p  s
   power_impl.<locals>._implr   rf   r   r   r   r   
power_implm     rh  c                 C   r  )Nc                 S   r  r   )r   r   powerrf   r   r   r   r   r   |  r  zpower_impl.<locals>.<lambda>c                 S   r  r   )r   r   r   r   r   r   rj  rf   r   r   r   rZ   r   r   r   r     r  rf  r   rf   r   r   r   r   r   rh  y  r   c                   C   r   )Nc                   S   rQ  r   r   r   rayleighr   r   r   r   r     r  z rayleigh_impl0.<locals>.<lambda>r   r   r   r   r   rayleigh_impl0  r|  rp  c                 C   rK  r   )r   r   r   r   rayleigh_implr  r   r   r   rayleigh_impl1  rM  rs  c              	   C   s2   | dkrt d| tdtdtj    S )Nr   zrayleigh(): mode <= 0r   r   )rB  r   r   r   r   r   rr  r   r   r   rq    s   "rq  c                 C   r  )Nc                 S   r  r   rn  )r  r   r   r   r   r     r  z rayleigh_impl2.<locals>.<lambda>c                 S   r  r   )r   r   r   r   r   r   ro  )r  r   r   r   rZ   r   r   r   r     r  zrayleigh_impl2.<locals>._implr   )r  r   r   r   r   r   rayleigh_impl2  r   rt  c                  C   r  )Nc                   S   s   t j t j  S r   r   r   r   r   r   r     r  zcauchy_impl.<locals>._implr   r   r   r   r   cauchy_impl  s   ru  c                 C   r   )Nc                 S   r   r   )r   r   standard_cauchyr   r   r   r   r     r   z&standard_cauchy_impl.<locals>.<lambda>c                 S   r   r   )r   r   r   r   r   r   rv  r   r   r   r   r     r   z#standard_cauchy_impl.<locals>._implr   r   r   r   r   standard_cauchy_impl  r   rw  c                 C   r  )Nc                 S   s:   t j }t j| d }t| d | t| }|S r  )r   r   r   r  r   r   )r  NGr  r   r   r   r     s   
zstandard_t_impl.<locals>._implr   r  r   r   r   standard_t_impl  ri  rz  c                 C   r  )Nc                 S   r  r   )r   r   
standard_tr  r   r   r   r     r  z"standard_t_impl2.<locals>.<lambda>c                 S   r  r   )r   r   r   r   r   r   r{  )r  r   r   r   rZ   r   r   r   r     r  zstandard_t_impl2.<locals>._implr   )r  r   r   r   r   r   standard_t_impl2  r   r|  c                 C   s,   t | tjrt |tjrdd }|S d S d S )Nc                 S   s   | dkrt d|dkrt d| d|  }tj }| | | }| ||td| | ||     }tj }|| | |  krC|S | |  | S )Nr   zwald(): mean <= 0zwald(): scale <= 0r      )rB  r   r   r   r   r   )meanr   mu_2lr3  r  r  r   r   r   r     s   
&
zwald_impl.<locals>._implr  )r~  r   r   r   r   r   	wald_impl  s   r  c                 C   r  )Nc                 S   r   r   )r   r   wald)r~  r   r   r   r   r   r     r   zwald_impl2.<locals>.<lambda>c                 S   r   r   )r   r   r   r   r   r   r  )r~  r   r   r   r   rZ   r   r   r   r     r   zwald_impl2.<locals>._implr   )r~  r   r   r   r   r   r   
wald_impl2  r   r  c                 C   r  )Nc                 S   s   | dkrt d| d }d| }	 dtj  }tj }tt|d|  }dd|  | }|dkrF|| |d  |d  || krF|S q)Nr   zzipf(): a <= 1r   r>   g      )rB  r   r   rr  r   r-  )rf   am1rg   r  rI  r  Tr   r   r   r     s   
(zipf_impl.<locals>._implr  rg  r   r   r   	zipf_impl  s   r  c                 C   r  )Nc                 S   r  r   )r   r   zipfrk  r   r   r   r     r  zzipf_impl.<locals>.<lambda>c                 S   r%  rs  )r   r   r  r   r   r   r   r  rl  r   r   r   r     r'  r  r   rm  r   r   r   r    r   c                    s^   t | tjs
td|dkrtjj n|dkrtj | jdkr' fdd}|S  fdd}|S )Nz1The argument to shuffle() should be a buffer typer   r   r>   c                    sT   | j d d }|dkr( |d }| | | | | |< | |< |d8 }|dksd S d S r=   )shapearrijrandr   r   r  0  s   zdo_shuffle_impl.<locals>.implc                    s`   | j d d }|dkr. |d }t| | t| | | |< | |< |d8 }|dksd S d S r=   )r  r   copyr  r  r   r   r  7  s   &)	r   r   Bufferr"  r   r   rl  rR  ndim)r  rngr  r   r  r   do_shuffle_impl%  s   

r  c                 C   
   t | dS r   r  r  r   r   r   shuffle_implA     
r  c                 C   r  r   r  r  r   r   r   r  F  r  c                 C   s8   t | tjrdd }|S t | tjrdd }|S d }|S )Nc                 S   s   t | }t j| |S r   )r   aranger   shuffle)r   r]   r   r   r   permutation_implN  s   
z*permutation_impl.<locals>.permutation_implc                 S   s   |   }tj| |S r   )r  r   r   r  )r   arr_copyr   r   r   r  S  s   )r   r   r   Array)r   r  r   r   r   r  K  s   r  c                  G   $   t | dkrdd }|S dd }|S )Nr   c                  W   r   r   r   r   r   r   r   	rand_implc     
zrand.<locals>.rand_implc                  W   s   t j| S r   r   r   r   r   r   r  h  r   len)r   r  r   r   r   r  _  
   r  c                  G   r  )Nr   c                  W   r   r   r   r   r   r   r   
randn_implr  r  zrandn.<locals>.randn_implc                  W   r  r   r   r   r   r   r   r  w  r   r  )r   r  r   r   r   randnn  r  r  Tc                    s   t | tjr#| jdksJ | j tdd tdd }tdd n#t | tjr?tj tdd td	d }td
d nt	d| f |d tj
fv rWdfdd	}|S d fdd	}|S )Nr>   c                 S   s   t | S r   r  re  r   r   r   get_source_size  r|  zchoice.<locals>.get_source_sizec                 S   s   |   S r   )r  re  r   r   r   copy_source  r|  zchoice.<locals>.copy_sourcec                 S   s   | | S r   r   rf   a_ir   r   r   getitem  r|  zchoice.<locals>.getitemc                 S   s   | S r   r   re  r   r   r   r       c                 S   s
   t | S r   )r   r  re  r   r   r   r    r  c                 S   r  r   r   r  r   r   r   r    r  z@np.random.choice() first argument should be int or array, got %sTc                    s     | }t jd|}| |S )zs
            choice() implementation returning a single sample
            (note *replace* is ignored)
            r   rk  )rf   r   replacer1  r  )r  r  r   r   choice_impl  s   
zchoice.<locals>.choice_implc           	         s   | }|r(t | }|j}tt|D ]}t jd|}| |||< q|S t | }|j|kr7tdt j	| }|j}tt|D ]}|| ||< qF|S )zO
            choice() implementation returning an array of samples
            r   z@Cannot take a larger sample than population when 'replace=False')
r   r   r   r   r  r   rl  r   rB  permutation)	rf   r   r  r1  r   flr  r  
permuted_ar   r  r  r   r   r    s    
NT)r   r   r  r  r   r   r   r   r  r"  r   )rf   r   r  r  r  r   r  r   choice  s2   



(r  c                    s   t j tdd t| tjstd| f t|tjtjfs&td|f |d tj	fv r7d
 fdd	}|S t|tjrGd
 fdd	}|S t|tj
rWd
 fdd	}|S td	|f )Nc                 S   s   |j }|j}t|}td||D ]=}d}| }td|d D ]#}	||	 }
tj||
|  }|||	 < ||8 }|dkr< n||
8 }q|dkrM|||| d < qd S )Nr   r   r>   )r   r   r  r   r   r   r  )r1  pvalsr   r  szplenr  p_sumn_experimentsr  p_jn_jr   r   r   multinomial_inner  s"   
z&multinomial.<locals>.multinomial_innerz7np.random.multinomial(): n should be an integer, got %szEnp.random.multinomial(): pvals should be an array or sequence, got %sc                    s    t t| }| || |S )z5
            multinomial(..., size=None)
            r   zerosr  r1  r  r   r   r   r  r   r   multinomial_impl  s   z%multinomial.<locals>.multinomial_implc                    s$   t |t|f }| || |S )z4
            multinomial(..., size=int)
            r  r  r  r   r   r    s   c                    s&   t |t|f  }| || |S )z6
            multinomial(..., size=tuple)
            r  r  r  r   r   r    s   zDnp.random.multinomial(): size should be int or tuple or None, got %sr   )r   r  r   r   r   r   r"  Sequencer  r   	BaseTuple)r1  r  r   r  r   r  r   multinomial  s.   
r  c                 C   r  )Nc                 S   s   t t| }t| | |S r   r   r   r  dirichlet_arr)r  r   r   r   r   dirichlet_impl+     
!dirichlet.<locals>.dirichlet_impl)r   r   r  r  )r  r  r   r   r   	dirichlet(  s   r  c                 C   s   t | tjtjfstd| f |d tjfv rddd}|S t |tjr+ddd}|S t |tjr?t |jtjr?ddd}|S td| )NzCnp.random.dirichlet(): alpha should be an array or sequence, got %sc                 S   s   t t| }t| | |S r   r  r  r   r   r   r   r   r  <  r  r  c                 S   s    t |t| f}t| | |S )z2
            dirichlet(..., size=int)
            r  r  r   r   r   r  C  s   
c                 S   s"   t |t| f }t| | |S )z4
            dirichlet(..., size=tuple)
            r  r  r   r   r   r  M  s   
zJnp.random.dirichlet(): size should be int or tuple of ints or None, got %sr   )	r   r   r  r  r   r   r   r   r   )r  r   r  r   r   r   r  2  s,   


c           
      C   s   t | D ]
}|dkrtdqt| }|j}|j}td||D ]5}d}t| D ]\}}	tj	|	d||| < ||||  
 7 }q't| D ]\}}	|||   |  < qEqd S )Nr   zdirichlet: alpha must be > 0.0r>   )iterrB  r  r   r   r   	enumerater   r   r  item)
r  r   a_vala_lenr   r   r  normr.  rK  r   r   r   r  ^  s    r  c                 C   r  )Nc                 S      t | | t| |S r   #validate_noncentral_chisquare_inputnoncentral_chisquare_singler  noncr   r   r   noncentral_chisquare_impl|     

7noncentral_chisquare.<locals>.noncentral_chisquare_implr   )r  r  r  r   r   r   noncentral_chisquarex  r  r  c                 C   s\   |d t jfv rddd}|S t|t js!t|t jr(t|jt jr(ddd}|S td| )Nc                 S   r  r   r  )r  r  r   r   r   r   r    r  r  c                 S   s<   t | | t|}|j}t|jD ]	}t| |||< q|S r   )r  r   r   r   r   r   r  )r  r  r   r   r   rZ   r   r   r   r    s   

zUnp.random.noncentral_chisquare(): size should be int or tuple of ints or None, got %sr   )r   r   r   r   r   r   r   )r  r  r   r  r   r   r   r    s   

c                 C   sl   t |rt jS d| k r$t j| d }t j t | }|||  S t j|d }t j| d|  S )Nr>   r   r@   )r   isnannanr   r  r   r   rO  )r  r  chi2r1  r  r   r   r   r    s   
r  c                 C   s$   | dkrt d|dk rt dd S )Nr   zdf <= 0znonc < 0rV  r  r   r   r   r    s
   r  r  r   )__doc__r   r   numpyr   llvmliter   numba.core.cgutilsr   numba.core.extendingr   r   r   numba.core.imputilsr   r   r	   numba.core.typingr   
numba.corer   r   numba.npr   numba.core.errorsr   registrylowerrh  r   rx   r   r  rb   rx  r   rR   LiteralStructType	ArrayTypernd_state_tPointerTyper!   r-   r1   r3   r4   r:   r?   rA   rC   rJ   r^   rh   r   r   r   r   r   random_samplesampleranfr   r   r  normalvariater   r   r   r   r   r   r   r   r   r   r   getrandbitsr0  rO  rR  rU  rY  r^  ri  rl  rj  rn  rp  rx  rz  r{  r~  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  betavariater  r  r  r  expovariater  r  r  r  r  r  r  r  r  r  lognormvariater  r  paretovariater  r  r  weibullvariater  r  r  r  vonmisesvariater  r  r  r  r  r  r  r  r  r   r  r$  r#  r*  r)  r+  r8  r7  r:  r;  r<  r?  rA  r>  rC  rD  rE  rG  rH  rF  rJ  rN  rL  negative_binomialrP  rO  rS  rb  rc  rj  rh  ro  rp  rs  rq  rt  rv  ru  rw  r{  rz  r|  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r   r   r   r   <module>   s<   
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