o
    5ήcu                    @   sb  d dl mZmZmZ d dlmZ d dlZd dlZd dl	Z	d dl
mZmZmZmZ d dl	mZ d dlmZ d dlmZ d dlmZmZmZmZmZmZmZ d dlmZmZ d	d
lm Z  d dl!m"Z" d dl#m$Z$ G dd dZ%G dd dZ&G dd dZ'G dd de'Z(e	j)j*dd Z+G dd de$Z,G dd dZ-G dd dZ.G dd dZ/G dd  d Z0dS )!    )divisionprint_functionabsolute_import)productN)assert_assert_equalassert_allcloseassert_almost_equal)raises)distributions)epps_singleton_2sampcramervonmises_cdf_cvmcramervonmises_2samp_pval_cvm_2samp_exactbarnard_exactboschloo_exact)mannwhitneyu
_mwu_state   )check_named_results)special)_TestPythranFuncc                   @   sD   e Zd Zdd Zdd Zdd Zdd Zd	d
 Zdd Zdd Z	dS )TestEppsSingletonc                 C   sJ   t g d}t g d}t||\}}t|ddd t|ddd d S )N)
gffffffֿgffffff@gGz?\(\?ffffff?gQ@gq=
ףp?gGzgGz׿gp=
#(@)
gffffffg333333ÿgףp=
@g      
@gGz@g)\(@g      @g(\@g(\ @333333!@gHzG.@r   decimalgQ,r?   )nparrayr   r	   selfxywp r(   G/tmp/pip-target-vg8gfxp4/lib/python/scipy/stats/tests/test_hypotests.pytest_statistic_1   s
   z"TestEppsSingleton.test_statistic_1c                 C   sB   t d}t d}t||\}}t|ddd t|ddd d S )	N)r   r      r+   r+   r+   r   r   r   r         r-   r-   r-      
   r/   r/   r/   )r/   r,   r   r-   r/   r/   r   r-   r.      r/   r   r   r0   r      r   r-   r1   r/   g!@MbP?atolg&J?r   r   )r    r!   r   r   r	   r"   r(   r(   r)   test_statistic_2&   s
   

z"TestEppsSingleton.test_statistic_2c           	      C   s   t jd t dt d}}tt|t|\}}tt|t|\}}t||\}}t||  ko8|kn   t||  koI|k d S    d S )N        )r    randomseedaranger   listtupler   )	r#   r$   r%   w1p1w2p2w3p3r(   r(   r)   test_epps_singleton_array_like0   s   &z0TestEppsSingleton.test_epps_singleton_array_likec                 C   s"   dt d}}ttt|| d S )Nr   r+   r   r,   r/   )r    r;   assert_raises
ValueErrorr   r#   r$   r%   r(   r(   r)   test_epps_singleton_size;   s   z*TestEppsSingleton.test_epps_singleton_sizec                 C   s\   dddddt jft d}}ttt|| t ddddddt jf}}ttt|| d S )Nr   r+   r   r,   r-   r/   )r    infr;   rF   rG   r   nanrH   r(   r(   r)   test_epps_singleton_nonfinite@   s   z/TestEppsSingleton.test_epps_singleton_nonfinitec                 C   s$   t ddd}ttt|| d S )Nd   r   )r    r;   reshaperF   rG   r   r#   r$   r(   r(   r)   test_epps_singleton_1d_inputG   s   z.TestEppsSingleton.test_epps_singleton_1d_inputc                 C   s2   t dt d}}t||}d}t|| d S )N   r7   )	statisticpvalue)r    r;   r   r   )r#   r$   r%   res
attributesr(   r(   r)   
test_namesK   s   
zTestEppsSingleton.test_namesN)
__name__
__module____qualname__r*   r5   rD   rI   rL   rQ   rW   r(   r(   r(   r)   r      s    
r   c                   @   sd   e Zd Zdd Zdd Zdd Zdd Zd	d
 Zdd Zdd Z	dd Z
dd Zdd Zdd ZdS )TestCvmc                 C       t tg ddg ddd d S )N)gy;i?g#^?gE>?gD
)?r,   {Gz?皙?      ?g+?-C6?r3   r   r   r#   r(   r(   r)   
test_cdf_4V   
   
zTestCvm.test_cdf_4c                 C   r\   )N)g8*5?g@߾?gHm?g%1 ?r/   )r^   r_   r`   g333333?ra   r3   rb   rc   r(   r(   r)   test_cdf_10\   re   zTestCvm.test_cdf_10c                 C   r\   )N)g}tg?g`?gI5o?gׁsF?  r]   ra   r3   rb   rc   r(   r(   r)   test_cdf_1000b   re   zTestCvm.test_cdf_1000c                 C   s   t tg dg ddd d S )N)a+e?+?&pn?+MJA?r]   ra   r3   rb   rc   r(   r(   r)   test_cdf_infh   s
   

zTestCvm.test_cdf_infc                 C   s4   t tddgdddg t tddgdddg d S )	NgX(~$?gUUUUU5f@i  r   r   gaah?g"@   )r   r   rc   r(   r(   r)   test_cdf_supportn   s   zTestCvm.test_cdf_supportc                 C   s$   t tg ddtg ddd d S )N)ri   rj   rk   rl   rM   i'  ra   r3   rb   rc   r(   r(   r)   test_cdf_large_ns   s
   

zTestCvm.test_cdf_large_nc                 C   sL   t dtdd  k odk n   t dtd  k o dk  d S    d S )NgwJ?gt@rg         ?)r   r   rc   r(   r(   r)   test_large_xz   s   "*zTestCvm.test_large_xc                 C   s<   d}t t|d d}tt|j|dk t|jd d S )N   皙?normrq   r   )r   r    onesr   r   rS   r   rT   )r#   nrU   r(   r(   r)   
test_low_p   s   zTestCvm.test_low_pc                 C   s@   t dd}ttt|d tttdgd tttdd d S )Nr/   r+   r-   ru         ?r(   )r    r;   rO   rF   rG   r   rP   r(   r(   r)   test_invalid_input   s   zTestCvm.test_invalid_inputc                 C   s   t g dd}t|jddd t|jddd t g ddd}t|jddd t|jd	dd t g d
d}t|jddd t|jddd d S )N)g333333r+   r   g?r,   皙?333333?ru   gZ	%q?ư>r3   gEж?)r   rz   g!O!W*?gz"W`?)	r   r+   r-   ffffff?gQ?      ?      @exponge.?gnz\(r?)r   r   rS   rT   )r#   rU   r(   r(   r)   test_values_R   s   zTestCvm.test_values_Rc                 C   s|   t dd}}t|tjj}t|d}t|j|jf|j|jf t|tj	j|}t|d|}t|j|jf|j|jf d S )Nr-   )r   ffffff?r   beta)
r    r;   r   r   r   cdfr   rS   rT   r   )r#   r$   argsr1r2r(   r(   r)   test_callable_cdf   s   
zTestCvm.test_callable_cdfN)rX   rY   rZ   rd   rf   rh   rm   ro   rp   rr   rx   r{   r   r   r(   r(   r(   r)   r[   R   s    	r[   c                   @   s<  e Zd Zdd Zdd Zdd Zg dZg dZd	d
ddgdd
ddgdd
ddgd	dddgddddgddddggZe	j
dedd Zd	dddgddddgddddgd	dddgddddgdddd ggZe	j
ded!d" Zd#d$ Zg d%g d&g d'd(Zg d)g d*g d+g d,d-Zg d.g d/g d0g d1g d2d3Zg d4g d5g d6g d7g d8g d9d:Zd;d< Zd=d> Zd?d@ Zd	d
ddAgdd
ddBgdd
ddCgd	dddAgddddBgddddAggZe	j
dDedEdF ZdGdH Ze	j
dId
dgdJdK ZdLdM Zg d-dNdOdPdQejdNdRdSdTdTdUgdVdWfg d-dNdOdPdQejejdRdSdTdTdUgdXdYfdSdRejdTgdNdOdPdQejdNdRdSdTdTdUgdZd[fdSdRejdTgdNdOdPdQejejdRdSdTdTdUgd\d]fdSejejdTgdNdOdPdQejejdRdSdTdTdUgd^d_fgZe	j
d`edadb Zg dcg ddg deg dfg dgg dhg dig djg dkg	Z e	j
dle dmdn Z!dodp Z"dqdr Z#g d(dsdtgddugg d(dsdtgddugg d(dsdtgd	dvgg d(dRgddwgg d(dRgddwgg d(dRgd	dxgdSdRgdSdRgddygdSdRgdSdRgddygdSdRgdSdRgd	dzgg	Z$e	j
g d{e$d|d} Z%d~d Z&dS )TestMannWhitneyUc                 C   
   dt _d S )NTr   
_recursiverc   r(   r(   r)   setup      
zTestMannWhitneyU.setupc                 C   sv  t ddg}t ddg}ttdd tg | W d    n1 s$w   Y  ttdd t|g  W d    n1 s?w   Y  ttdd t||dd	 W d    n1 s\w   Y  ttd
d t||dd W d    n1 syw   Y  ttdd t||dd W d    n1 sw   Y  ttdd t||dd W d    d S 1 sw   Y  d S )Nr   r+   r   r,   `x` and `y` must be of nonzeromatchz`use_continuity` must be oneekki)use_continuityz`alternative` must be one ofalternativez`axis` must be an integerrz   axisz`method` must be one ofmethod)r    r!   rF   rG   r   rH   r(   r(   r)   test_input_validation   s(   "z&TestMannWhitneyU.test_input_validationc                 C   s  t jd d}t j|d }t j|d }t||}t||dd}t||dd}|j|jks3J |j|jks;J t j|d }t j|d }t||}t||dd}t||dd}|j|jksfJ |j|jksnJ t||}t||dd}t||dd}|j|jksJ |j|jksJ t j|d }t j|d }t||}t||dd}t||dd}|j|jksJ |j|jksJ t j|d }t j|d }|d |d< t||}t||dd}t||dd}|j|jksJ |j|jksJ d S )Nr   r1   
asymptoticr   exactr   )r    r9   r:   randr   rT   )r#   rw   r$   r%   autor   r   r(   r(   r)   	test_auto   sH   




zTestMannWhitneyU.test_auto)gm9Aj@g+H3[@gi>s@)g#hA{@glz@gcDf@gǳ*h@gZA@gI9^YQa@g`@g՞p@g:q@g&@gZ|@g`r@gMc3g@	two-sidedr   r   r   )   
+?less)r   
+?greater)r   缌%c?r   )r   g9:?)r   g9:?)r   g*::?)kwdsexpectedc                 C   s$   t | j| jfi |}t|| d S N)r   r$   r%   r   r#   r   r   rU   r(   r(   r)   
test_basic  s   zTestMannWhitneyU.test_basicT)r   r   )   r   )r   r   )r   r   F)r   gl,KNh?)r   giژ?)r   gl,KNh?c                 C   s(   t | j| jfddi|}t|| d S )Nr   r   )r   r%   r$   r   r   r(   r(   r)   test_continuity/  s   z TestMannWhitneyU.test_continuityc           	      C   s   g d}t g d}t g dd }t g dd }|d || || ||| || |d g}t||ddd}g d	}g d
}t|j| t|j| d S )NrE   r   r+   r   r,   r-   )r   r   r   r   r   r^   )r   r   r   r   r   rN   r   )r   r   )r/   	         !@r1   r   r0   r.   )r   g]U?g[?gi\?gZX<_?gx.?g 
?)r    r!   r   r   rS   r   rT   )	r#   r$   y0dydy2r%   rU   
U_expected
p_expectedr(   r(   r)   test_tie_correct=  s   *z!TestMannWhitneyU.test_tie_correct)g      ?r`   g      ?)r|   皙?皙?r}   )r_   r|   r   r   r`   g?r   r+   r   )r   r   r}   )gx&?g/$?gJ+?r   r}   )y&1?v/?gv/?r   gjt?~jt?ʡE?)	gy&1?gV-?r   r|   gS?gv?gʡE?g'1Z?gm?rE   )gK7A`?gZd;O?r`   gMbX?)Mb?RQ?RQ?M?r   r   )	g;On?;On?V-?g      ?gJ+?r   gx&?r`   gCl?)Mb?Mb?Mb?gy&1?r   M?g|?5^?gn?g\(\?!rh?K7?)Mbp?r   r   r   ~jt?g333333?g"~j?ףp=
?gzG?K7?gGz?gl?r`   gI+?r   )r   r   g1Zd?r   )r   r   r   1Zd?g%C?r   r   )
g~jt?g~jt?r   gsh|??gS㥛?r   r   g+?r   r   )g{Gzt?r^   g~jt?gL7A`?r   gjt?gPn?gI+?gX9v?gQ?gMb?gsh|??gK7A`?)Mb`?r   g;On?gQ?g9v?gˡE?gT㥛 ?gbX9ȶ?grh|?gQ?r   gx&?gv/?gMbX?g(\?gQ?)r2   r   r   r   g9v?g/$?r   r   gL7A`?g
ףp=
?gQ?r   gK7?g`"?g7A`?r   gV-?gjt?gˡE?)r   r+   r   r,   r-   r.   c           
   	   C   s   | j | j| j| jd}| D ]f\}}| D ]]\}}tdt|}tt	j
|||d|dd td|| d }tt	j
|||dt	j|||d t	j|||d d t	j|||d}t||d d d  t	j|||d}	t||	 qqd S )N)r   r,   r-   r.   r   )kmrw   r2   r3   r   rN   )pn3pn4pm5pm6itemsr    r;   lenr   r   r   sfpmf)
r#   p_tablesrw   tabler   r'   uu2r   pmf2r(   r(   r)   test_exact_distributionm  s&   z(TestMannWhitneyU.test_exact_distributionc                 C   s   t jd t jd}t jd}t||dd}t||dd}|j|jks(J t |j|j dks5J t jd}t jd}t||dd}t||dd}|j|jksWJ t |j|j dk sdJ d S )	Nr   r-   r   r   r   r^   (   r2   )r    r9   r:   r   r   rS   absrT   )r#   r$   r%   res1res2r(   r(   r)   test_asymptotic_behavior  s   z)TestMannWhitneyU.test_asymptotic_behaviorc                 C   sr   t g dddgddd}t g dddgddd}t|j|j |jdks&J t g dddgd	dd}t|d
 d S )Nr   rz         @r   r   r   r   r`   r   )r   r   )r   r   rT   )r#   res_lres_grU   r(   r(   r)   test_exact_U_equals_mean  s   z)TestMannWhitneyU.test_exact_U_equals_meanr   r   )r   r`   )r   g郡E?)r   resultc                 C   s   t tdi || d S )Nr   r+   r   r+   )r   r   )r#   r   r   r(   r(   r)   test_scalar_data  s   z!TestMannWhitneyU.test_scalar_datac                 C   sH   t tddddd t tddddd t tddddddtjf d S )	Nr   r   r   )r`   r   r   F)r   r   r`   )r   r   r    rK   rc   r(   r(   r)   test_equal_scalar_data  s   
z'TestMannWhitneyU.test_equal_scalar_datar   c                 C   sz  t jd d}d\}}t j|dd}t jd|ddd }t||||d	}d
}|jj|ks1J |jj|ks9J t ||dt ||d}}|d }|j	|j	ksTJ t 
|||f }t 
|||f }|jd d |ksqJ |jd d |ks|J t |}	t |}
tdd |D  D ]}|| }|| }t|||d}|j|	|< |j|
|< qt j|j|
 t j|j|	 d S )Nr   )r0   r/   r   r1   r.   r   r|   )r   r   )r.   r   r1   rN   )N.c                 S   s   g | ]}t |qS r(   )range).0ir(   r(   r)   
<listcomp>  s    z8TestMannWhitneyU.test_gh_12837_11113.<locals>.<listcomp>r   )r    r9   r:   r   r   rT   shaperS   moveaxisndimbroadcast_tozerosr   testingr   )r#   r   r   r   rw   r$   r%   rU   r   
statisticspvaluesindicesxiyitempr(   r(   r)   test_gh_12837_11113  s4   


z$TestMannWhitneyU.test_gh_12837_11113c                 C   s~   g d}g d}t ||}tj|d< t ||}t|j|j t|j|j tj|d< t ||}t|jtj t|jtj d S )NrE   )r   r.   r0   r1   r   r   r+   r   r,   r,   r-   r,   )r   r    rJ   r   rS   rT   rK   )r#   r$   r%   r   r   res3r(   r(   r)   test_gh_11355  s   




zTestMannWhitneyU.test_gh_11355r   r.   r0   r1   r+   r   r,   r-   r/   g+zQ?r   g}$k\?g     1@g!˛G*?r   g,s?     8@gFHQ?)r$   r%   rS   rT   c                 C   s2   t ||dd}t|j|dd t|j|dd d S )Nr   r   -q=r3   )r   r   rS   rT   )r#   r$   r%   rS   rT   rU   r(   r(   r)   test_gh_11355b  s   zTestMannWhitneyU.test_gh_11355b)Tr   r   g&?)Tr   r   gO?)Tr   r   gO?)Fr   r   g9@VN!x?)Fr   r   g9M>?)Fr   r   g9M>?)Tr   r   g?UV?)Tr   r   gߺVJH?)Tr   r   gVJH?)r   r   r   
pvalue_expc           	      C   s:   d}d}d}t |||||d}t|j| t|j| d S )N#   )
rt   g(\?g=
ףp=?gp=
ף?g333333?gGz?g(\?g=
ףp=?r   g\(\?)gffffff?g)\(?r   gGz?g\(\?r   r   r   )r   r   rS   r   rT   )	r#   r   r   r   r
  statistic_expr$   r%   rU   r(   r(   r)   test_gh_9184*  s   zTestMannWhitneyU.test_gh_9184c                 C   s<   t tdd tg g  W d    d S 1 sw   Y  d S )Nr   r   )rF   rG   r   rc   r(   r(   r)   test_gh_6897I  s   "zTestMannWhitneyU.test_gh_6897c                 C   sf   t t jt jt jt jt jg}t t jt jt jt jt jg}t||}t|jt j t|jt j d S r   )r    r!   rK   r   r   rS   rT   )r#   abrU   r(   r(   r)   test_gh_4067N  s
   
zTestMannWhitneyU.test_gh_4067rz   r   )r   ga׀}?)r   rq   )rz   g?h?)rz   r   )r+   g5&#\?)r+   r   )r$   r%   r   r   c                 C   s$   t ||d|dd}t||dd d S )NTr   r  r  )rtol)r   r   )r#   r$   r%   r   r   rU   r(   r(   r)   test_gh_2118f  s   
zTestMannWhitneyU.test_gh_2118c                 C   
   d t _d S r   r   rc   r(   r(   r)   teardownn  r   zTestMannWhitneyU.teardownN)'rX   rY   rZ   r   r   r   r$   r%   cases_basicpytestmarkparametrizer   cases_continuityr   r   r   r   r   r   r   r   r   cases_scalarr   r   r  r  r    rJ   cases_11355r	  
cases_9184r  r  r  
cases_2118r  r  r(   r(   r(   r)   r      s   5




+




r   c                   @   s   e Zd Zdd Zdd ZdS )TestMannWhitneyU_iterativec                 C   r   )NFr   rc   r(   r(   r)   r   s  r   z TestMannWhitneyU_iterative.setupc                 C   r  r   r   rc   r(   r(   r)   r  v  r   z#TestMannWhitneyU_iterative.teardownN)rX   rY   rZ   r   r  r(   r(   r(   r)   r   r  s    r   c                  C   s   d t _td t _tjd} | d}| d}tj||dd t	t jdks,J | d}tj||dd t	t jdkrCJ d S )	N)r   r   r   l   7cE"r-   i  r   r   rN   i  )
r   r   r    rv   _fmnksr9   default_rngstatsr   all)rngr$   r%   r(   r(   r)   test_mann_whitney_u_switchz  s   


r&  c                   @   sz   e Zd Zdd Zdd Zdd Zdd Zd	d
 Zdd Zdd Z	dd Z
dd Zdd Zdd Zejdddd ZdS )TestSomersDc                    st    j  j  _td j  j ftd j  j fd _ fdd jD }tjtj	dd _
 j
|  _d S )Nr/   r   c                    s   g | ]	} j | d  qS )r   )	arguments)r   idxrc   r(   r)   r     s    z,TestSomersD.setup_method.<locals>.<listcomp>r   r   )ALL_INTEGER	ALL_FLOATdtypesr    r;   r(  	functoolspartialr#  somersdpartialfuncr   )r#   input_arrayr(   rc   r)   setup_method  s   

zTestSomersD.setup_methodc                 G   s6   | j | }t|j| jjdd t|j| jjdd d S )NV瞯<r3   )r0  r   rS   r   rT   )r#   r   rU   r(   r(   r)   pythranfunc  s   
zTestSomersD.pythranfuncc                 C   sf   g dg dg dg}t |}| t j}t j|fi |}t|j|jdd t|j|jdd d S )N)rn         r0   r   )r0   r6     r  rs   )r   r   r+   r0      r3  r3   )r#  r/  get_optional_argsr   rS   rT   )r#   r   r   optional_argsr   r(   r(   r)   test_pythranfunc_keywords  s   
z%TestSomersD.test_pythranfunc_keywordsc                 C   sn  g d}g d}d}t ||}t|j|d dd t|j|d dd g d}g d	}d}t ||}t|j|d dd t|j|d dd g d
}g d}d}t ||}t|j|d dd t|j|d dd td}td}d}t ||}t|j|d dd t|j|d dd td}tg d}d}t ||}t|j|d dd t|j|d dd td}tdd d d }d}t ||}t|j|d dd t|j|d dd td}tg d}d}t ||}t|j|d dd t|j|d dd g d}g d}d}t ||}t|j|d dd t|j|d dd t g dg d}t|jtj t|jtj t g dg d}t|jtj t|jtj t g dg d}t|jtj t|jtj t dgdg}t|jtj t|jtj t g g }t|jtj t|jtj td}td}t	t
t j|| d S )N)r-   r+   r   r   r.   r,   r0   r1   )r-   r+   r.   r   r   r1   r0   r,           rq   r   r3  r3   r   )	r   r-   r+   r   r   r.   r,   r0   r1   )	r-   r+   r   r.   r   r   r1   r0   r,   )r-   r+   r   r   r.   r,   r0   )r-   r+   r.   r   r   r0   r,   )g+$I$I¿g=/3n+?r/   rq   r   )
r   r+   r   r   r,   r.   r-   r0   r1   r   )gs'}'?r=  rN   )g      r   )
r   r0   r1   r.   r-   r   r,   r+   r   r   )g}'}'r=  )rs   r+   r   rs   r+   )r   r,   r0   r   r   )      g.ʂ?)r+   r+   r+   )r+   r   r+   g      $@g      4@)r#  r/  r   rS   rT   r    r;   r!   rK   rF   rG   )r#   r$   r%   r   rU   x1x2r(   r(   r)   test_like_kendalltau  s   







z TestSomersD.test_like_kendalltauc                 C   s   g d}g d}d}d}d}t ||}t|j|dd t|j|dd t|jjd	 t ||}t|j|dd t|j|dd t|jjd
 d S )N)r   r   r   r+   r+   r+   r+   r+   r   r   r   r+   r+   r+   r+   r+   r+   r+   r   r   r   r   r   r   )r   r   r   r   r   r   r   r   r   r   r+   r+   r+   r+   r+   r+   r+   r+   r+   r+   r+   r+   r+   r+   gCE]t?g^_?gO((Ƿ?r3  r3   ra   )r   r+   r+   r   )r#  r/  r   rS   rT   r   r   r   )r#   r$   r%   d_crd_rcr'   rU   r(   r(   r)   test_asymmetry#  s   zTestSomersD.test_asymmetryc                 C   s   t ddgddgddgddgddgg}|j}d}tt|j| t d	d
gdd
gd
dgg}d\}}tt|j| tt|jj| t d	d
gd
dgdd
gg}d}tt|jj| d S )Nr1   r+   r.   r-   r   r,   r   gHHHHHH?r5  r   U   r7   )gM&w?rq   gtE]t)r    r!   Tr   r#  r/  rS   )r#   r   dyxdxyr(   r(   r)   test_somers_original<  s   (z TestSomersD.test_somers_originalc                 C   s6  d}d}t |}t jd tjj|t || d|}t	|}t j
|dt |d dd}t	|}t j
|dt |d dd}t	|}	t j
|dt |d d dd}
t	|
}t|jdd	d
 t|j|j t|j|	j t|j|j t|jdd	d
 t|j|j t|j|	j t|j|j d S )NrM   r,   r.   r   r'   r+   r   r   gayr3  r3   gPj$?)r    prodr9   r:   r#  multinomialrvsrv   rO   r/  insertr   r   rS   rT   )r#   Nr   sizesrU   s2r   s3r  s4res4r(   r(   r)   *test_contingency_table_with_zero_rows_colsR  s(   
 


 
z6TestSomersD.test_contingency_table_with_zero_rows_colsc           	      C   s  d}d}t |}t jd tjj|t || d|}|d }d}t	t
|d t| W d    n1 s;w   Y  |d }d	}t	t
|d t| W d    n1 s\w   Y  d
}t	t
|d tg g W d    n1 szw   Y  t	t
|d tdgg W d    n1 sw   Y  t d}t	t
|d t| W d    n1 sw   Y  d|d< t	t
|d t| W d    d S 1 sw   Y  d S )NrM   rL  r   rM  r+   z:All elements of the contingency table must be non-negativer   r^   z5All elements of the contingency table must be integerz?At least two elements of the contingency table must be nonzero.r   )r   r   r   )r    rN  r9   r:   r#  rO  rP  rv   rO   rF   rG   r/  r   )	r#   rR  r   rS  rT  s5messages6s7r(   r(   r)   test_invalid_contingency_tablesq  s<   
 
"z+TestSomersD.test_invalid_contingency_tablesc                 C   sb   g d}ddt jg}g d}ddt j g}t||}t||}t|j|j t|j|j d S )Nr   rN   g @)r   r+   r   r   r?  )r    rJ   r#  r/  r   rS   rT   )r#   r$   rA  r%   y2rU   r   r(   r(   r)   test_only_ranks_matter  s   z"TestSomersD.test_only_ranks_matterc                 C   s6   t d}t d}t||}t|jt d d S )Nr/   )r    r;   r#  r/  r   r   eye)r#   r$   r%   rU   r(   r(   r)   test_contingency_table_return  s   

z)TestSomersD.test_contingency_table_returnc                 C   s`  g d}g d}t j||dd}|jdksJ t j||dd}t|j|j t|jd|jd   t j||d	d}t|j|j t|j|jd  |  t j||dd}|jdk s\J t j||d	d}t|j|j t|jd|jd   t j||dd}t|j|j t|j|jd  tjt	d
d t j||dd W d    d S 1 sw   Y  d S )Nr   )r-   r.   r0   r1   r0   r   r   r   r   r   r+   r   zalternative must be 'less'...r   z	ekki-ekki)
r#  r/  rS   r   r   rT   reverser  r
   rG   )r#   r@  rA  r   rU   r(   r(   r)   test_somersd_alternative  s,   "z$TestSomersD.test_somersd_alternativepositive_correlation)FTc                 C   s   t d}|r	|nt |}|rdnd}tj||dd}|j|ks#J |jdks*J tj||dd}|j|ks9J |j|r?dndksDJ tj||dd}|j|ksSJ |j|rYdndks^J d S )	Nr/   r   rN   r   r   r   r   r   )r    r;   flipr#  r/  rS   rT   )r#   re  r@  rA  expected_statisticrU   r(   r(   r)    test_somersd_perfect_correlation  s   
z,TestSomersD.test_somersd_perfect_correlationN)rX   rY   rZ   r2  r4  r;  rB  rF  rK  rY  r^  r`  rb  rd  r  r  r  rh  r(   r(   r(   r)   r'    s    o#)r'  c                   @   s  e Zd ZdZejdddgddggdfdd	gd
dggdfd	dgdd	ggdfddgddggdfddgddggdfddgddggdfddgddggdfddgddggdfddgdd	ggdfdd	gddggdfd	dgdd	ggdfgd d! Zejdddgddggd"fdd	gd
dggd#fd	dgdd	ggd$fddgddggd%fddgddggd&fddgddggd'fddgddggd(fddgddggd)fddgdd	ggd*fdd	gddggd+fd	dgdd	ggd$fgd,d- Zd.d/ Z	ejdddgddggd0fgd1d2 Z
ejdddgddggd3ejffddgddggd3ejffgd4d5 Zejdd	dgdd	ggd6fdd7gd8dggd9fd:d;gd<dggd=fgejd>d?d@gdAdB ZdCS )DTestBarnardExactz8Some tests to show that barnard_exact() works correctly.input_sample,expected+   r   r/   '   )gXyq@g{2s&Q7?rM   r+   rg   r-   )gllgEA]0K?r0   r1   )*)1%g_  ?r   )g_c1?g= ?   rR   )g5PyQgQ@2?r   r5  )ggJ"?)g_c1gwݝل?r   r,   )g7@g      ?r   )g~t,?3O?r.   )gr?~CY7?c                 C   s(   t |}|j|j}}t||g| dS )zThe expected values have been generated by R, using a resolution
        for the nuisance parameter of 1e-6 :
        ```R
        library(Barnard)
        options(digits=10)
        barnard.test(43, 40, 10, 39, dp=1e-6, pooled=TRUE)
        ```
        Nr   rS   rT   r   r#   input_sampler   rU   rS   rT   r(   r(   r)   test_precise  s   zTestBarnardExact.test_precise)g7\@gA2?)gXS;gh?)g>!Ɏg6  ?)gSy@?g^F?)g-gXI#?)gaЍgo?)gb]?gFugH	?)g6ҭ@g      ?)gi(	ro  )gNXzrp  c                 C   s,   t |dd}|j|j}}t||g| dS )zThe expected values have been generated by R, using a resolution
        for the nuisance parameter of 1e-6 :
        ```R
        library(Barnard)
        options(digits=10)
        barnard.test(43, 40, 10, 39, dp=1e-6, pooled=FALSE)
        ```
        F)pooledNrq  rr  r(   r(   r)   test_pooled_param	  s   z"TestBarnardExact.test_pooled_paramc                 C     d}t t|d tddgddggdd W d    n1 sw   Y  d	}t t|d ttd
dd W d    n1 sBw   Y  d}t t|d tddgddgg W d    n1 sdw   Y  d}t t|d tddgddggd W d    d S 1 sw   Y  d S )N7Number of points `n` must be strictly positive, found 0r   r   r+   r   r,   r   rw   ,The input `table` must be of shape \(2, 2\).r.   *All values in `table` must be nonnegative.rN   zI`alternative` should be one of {'two-sided', 'less', 'greater'}, found .*not-correct)rF   rG   r   r    r;   rO   r#   	error_msgr(   r(   r)   test_raises&  $   "zTestBarnardExact.test_raisesr>  c                 C   6   t |}|j|j}}t||d  t||d  d S Nr   r   r   rS   rT   r   rr  r(   r(   r)   test_edge_cases@  s   z TestBarnardExact.test_edge_casesrq   c                 C   r  r  r  rr  r(   r(   r)   test_row_or_col_zeroL     z%TestBarnardExact.test_row_or_col_zero)rm  gE\/??   i,  )ggQ5r=     r8   i  )g&X}>r=  r   r   r   c           	      C   sf   |\}}|dkrt |dddddf }| }t||d}|j|j}}t||g||gdd dS )a  
        "The expected values have been generated by R, using a resolution
        for the nuisance parameter of 1e-6 :
        ```R
        library(Barnard)
        options(digits=10)
        a = barnard.test(2, 7, 8, 2, dp=1e-6, pooled=TRUE)
        a$p.value[1]
        ```
        In this test, we are using the "one-sided" return value `a$p.value[1]`
        to test our pvalue.
        r   NrN   r   Hz>r3   )r    r!   r   rS   rT   r   )	r#   rs  r   r   expected_statless_pvalue_expectrU   rS   rT   r(   r(   r)   test_less_greaterY  s   
z"TestBarnardExact.test_less_greaterN)rX   rY   rZ   __doc__r  r  r  rt  rv  r  r  r    rK   r  r  r(   r(   r(   r)   ri    sr    



ri  c                   @   s  e Zd ZdZdZejdddgddggdfdd	gd
d
ggdfddgddggdfd
dgd
d	ggdfddgd	dggdfdd	gddggdfddgddggdfddgddggdfd
dgddggdfg	dd Zejdddgd
dggd fddgddggd!fdd	gd
d
ggd"fdd#gddggd$fddgddggd%fddgd	dggd&fdd	gddggdfddgd'dggdfddgddggd!fddgddggd(fd
dgddggd)fgd*d+ Z	ejdddgd
dggd,fddgddggd-fdd	gd
d
ggd.fddgddggd/fddgd	dggd0fdd	gddggd1fddgddggd-fddgddggd2fgd3d4 Z
d5d6 Zejdddgdd
ggejejffddgd
dggejejffgd7d8 Zd9d: Zejd;d<d=d> Zd?S )@TestBoschlooExactz9Some tests to show that boschloo_exact() works correctly.r  rj  r+   r0   r1   )<vB\?g/??r-   r   r/   )gM?gA>?r   rR   r5  )_VѶ?g֭?)u %?gc'?r   r,   )r   r   r   )r`   g      ?rs   )+f?gXc}v?   %   )gZыD?ggi]?c                 C   2   t |dd}|j|j}}t||g|| jd dS )a  The expected values have been generated by R, using a resolution
        for the nuisance parameter of 1e-8 :
        ```R
        library(Exact)
        options(digits=10)
        data <- matrix(c(43, 10, 40, 39), 2, 2, byrow=TRUE)
        a = exact.test(data, method="Boschloo", alternative="less",
                       tsmethod="central", np.interval=TRUE, beta=1e-8)
        ```
        r   r   r3   Nr   rS   rT   r   ATOLrr  r(   r(   r)   	test_less  s   zTestBoschlooExact.test_lessrk  r   rl  )k\2?g0,%?)gKv?gN3?)r  g'&5?rn  )gw@_?g7?)gi{?gɑ)z?)օa?g1|?r.   )gY<;?gND?)ge?gG`?c                 C   r  )a  The expected values have been generated by R, using a resolution
        for the nuisance parameter of 1e-8 :
        ```R
        library(Exact)
        options(digits=10)
        data <- matrix(c(43, 10, 40, 39), 2, 2, byrow=TRUE)
        a = exact.test(data, method="Boschloo", alternative="greater",
                       tsmethod="central", np.interval=TRUE, beta=1e-8)
        ```
        r   r   r3   Nr  rr  r(   r(   r)   test_greater  s   zTestBoschlooExact.test_greater)r  gqQS,5?)r  gG?/??)r  gKE`?)r  ghr1ֽ?)r  grfb?)r`   g      ?)r  gP:pRv?c                 C   s4   t |ddd}|j|j}}t||g|| jd dS )a  The expected values have been generated by R, using a resolution
        for the nuisance parameter of 1e-8 :
        ```R
        library(Exact)
        options(digits=10)
        data <- matrix(c(43, 10, 40, 39), 2, 2, byrow=TRUE)
        a = exact.test(data, method="Boschloo", alternative="two.sided",
                       tsmethod="central", np.interval=TRUE, beta=1e-8)
        ```
        r   @   )r   rw   r3   Nr  rr  r(   r(   r)   test_two_sided  s   z TestBoschlooExact.test_two_sidedc                 C   rw  )Nrx  r   r   r+   r   r,   r   ry  rz  r.   r{  rN   zK`alternative` should be one of \('two-sided', 'less', 'greater'\), found .*r|  )rF   rG   r   r    r;   rO   r}  r(   r(   r)   r    r  zTestBoschlooExact.test_raisesc                 C   r  r  )r   rS   rT   r   rr  r(   r(   r)   r    r  z&TestBoschlooExact.test_row_or_col_zeroc                 C   s`   ddgddgg}t |ddj}t |ddj}dt|| dks!J t |ddj}|d	ks.J d S )
Nr   r   rs   r   r   r   r+   r   rq   )r   rT   min)r#   tblplpgptr(   r(   r)   test_two_sided_gt_1  s   z%TestBoschlooExact.test_two_sided_gt_1r   )r   r   c                 C   s>   ddgddgg}t ||dj}tj||dd }t|| d S )Nr+   r0   r1   r   r   )r   rS   r#  fisher_exactr   )r#   r   r  boschloo_statfisher_pr(   r(   r)   test_against_fisher_exact  s   z+TestBoschlooExact.test_against_fisher_exactN)rX   rY   rZ   r  r  r  r  r  r  r  r  r  r    rK   r  r  r  r(   r(   r(   r)   r  |  sr    




r  c                   @   s^   e Zd Zdd Zdd Zdd Zejdg dd	d
 Z	dd Z
dd Zdd Zdd ZdS )TestCvm_2sampc                 C   sH  t dd}t d}d}tjt|d t|| W d    n1 s&w   Y  tjt|d t|| W d    n1 sBw   Y  d}tjt|d tg | W d    n1 s`w   Y  tjt|d t|dg W d    n1 s}w   Y  d}tjt|d t||d	 W d    d S 1 sw   Y  d S )
Nr/   ry   r-   z#The samples must be one-dimensionalr   z/x and y must contain at least two observations.r   z/method must be either auto, exact or asymptoticxyz)r    r;   rO   r  r
   rG   r   )r#   r$   r%   msgr(   r(   r)   r{     s(   
"z TestCvm_2samp.test_invalid_inputc                 C   sN   g d}g d}t ||}t t|t|}t|j|jf|j|jf d S )N)r+   r   r,   r0   r.   )r   r   rs   r7  )r   r    r!   r   rS   rT   r#   r$   r%   r   r   r(   r(   r)   test_list_input'  s
   
zTestCvm_2samp.test_list_inputc                 C   s>   g d}g d}t ||}t|jddd t|jddd d S )N)	gffffff@g @r   gffffff!@皙"@g#@g333333$@g333333%@gffffff&@)g@g@g@      @333333@gffffff @g333333"@g#@g%@g&@g      '@g(@g      )@g*@g333333-@gS㥛?r2   r3   g
ףp=
?r^   )r   r   rS   rT   r#   r$   r%   rr(   r(   r)   test_example_conover.  s
   
z"TestCvm_2samp.test_example_conoverzstatistic, m, n, pval))i  r-   r.   gcj`?)ii  r0   r0   gtE]t?)i@  r,   r.   g88?)i  r.   r0   gXwS?c                 C   s   t t|||| d S r   )r   r   )r#   rS   r   rw   pvalr(   r(   r)   test_exact_pvalue8  s   	zTestCvm_2samp.test_exact_pvaluec                 C   s   t jd tjjdd}tjjdd}t||}td|j  k o$dk n   t||d }td|j  k o=dk  d S    d S )Ni  i@B )rS  i r   r   r|   )	r    r9   r:   r   ru   rP  r   r   rT   r  r(   r(   r)   test_large_sampleC  s   
(zTestCvm_2samp.test_large_samplec                 C   sd   t jd t jd}t jd}t||dd}t||dd}t|j|j t|j|jdd d S )	Nr   r0   r1   r   r   r   r^   r3   )	r    r9   r:   r   r   r   rS   r   rT   r  r(   r(   r)   test_exact_vs_asymptoticN  s   z&TestCvm_2samp.test_exact_vs_asymptoticc                 C   st   t d}g d}t||dd}t||dd}t|j|j t d}t||dd}t||dd}t|j|j d S )Nr/   )r`   g@g333333*@r   r   r   r   r   )r    r;   r   r   rT   r  r(   r(   r)   test_method_autoW  s   

zTestCvm_2samp.test_method_autoc                 C   sV   t d}t||}t|j|jfd t|d d |d d }t|j|jfd d S )Nrn  r<  r,   )r    r;   r   r   rS   rT   )r#   r$   rU   r(   r(   r)   test_same_inputc  s
   

zTestCvm_2samp.test_same_inputN)rX   rY   rZ   r{   r  r  r  r  r  r  r  r  r  r  r(   r(   r(   r)   r    s    

	r  c                   @   s.  e Zd Zg dg dg dfZg dg dg dfZg dg dg dfZdZdZd	Ze	j
jd
eedfeedfeedffg dddd ZdZdZe	j
jd
eedfeedffddgddd Zdd Zdd Zdd Zdd  Zd!d" Zd#d$ Ze	j
d%d&d'd( Ze	j
d)g d*d+d, Zd-d. Zd/S )0TestTukeyHSD)r       7@ffffff:@皙;@fffff=@)ffffff<@皙A@     =@皙@@皙>@)g:@gL<@gL8@g333333:@g;@)r  r  gHzG:@r  r  r  r  r  )r  r  r  )
r  r  r  r  r  r  r  r  r  r  aK  
    Comparison LowerCL Difference UpperCL Significance
    2 - 3	0.6908830568	4.34	7.989116943	    1
    2 - 1	0.9508830568	4.6 	8.249116943 	1
    3 - 2	-7.989116943	-4.34	-0.6908830568	1
    3 - 1	-3.389116943	0.26	3.909116943	    0
    1 - 2	-8.249116943	-4.6	-0.9508830568	1
    1 - 3	-3.909116943	-0.26	3.389116943	    0
    aS  
    Comparison LowerCL Difference UpperCL Significance
    2 - 1	0.2679292645	3.645	7.022070736	    1
    2 - 3	0.5934764007	4.34	8.086523599	    1
    1 - 2	-7.022070736	-3.645	-0.2679292645	1
    1 - 3	-2.682070736	0.695	4.072070736	    0
    3 - 2	-8.086523599	-4.34	-0.5934764007	1
    3 - 1	-4.072070736	-0.695	2.682070736	    0
    aS  
    Comparison LowerCL Difference UpperCL Significance
    2 - 3	1.561605075	    4.34	7.118394925	    1
    2 - 1	2.740784879	    6.08	9.419215121	    1
    3 - 2	-7.118394925	-4.34	-1.561605075	1
    3 - 1	-1.964526566	1.74	5.444526566	    0
    1 - 2	-9.419215121	-6.08	-2.740784879	1
    1 - 3	-5.444526566	-1.74	1.964526566	    0
    zdata,res_expect_str,atolra   g|=)equal size samplezunequal sample sizezextreme sample size differences)idsc                 C   s   t j|dd dd tdd}tj| }| }|D ]G\}}}	}
}}t	|d t	|d }}t
|j||f |	|d t
|j||f |
|d t
|j||f ||d t
|j||f d	k|dk qdS )
a  
        SAS code used to generate results for each sample:
        DATA ACHE;
        INPUT BRAND RELIEF;
        CARDS;
        1 24.5
        ...
        3 27.8
        ;
        ods graphics on;   ODS RTF;ODS LISTING CLOSE;
           PROC ANOVA DATA=ACHE;
           CLASS BRAND;
           MODEL RELIEF=BRAND;
           MEANS BRAND/TUKEY CLDIFF;
           TITLE 'COMPARE RELIEF ACROSS MEDICINES  - ANOVA EXAMPLE';
           ods output  CLDiffs =tc;
        proc print data=tc;
            format LowerCL 17.16 UpperCL 17.16 Difference 17.16;
            title "Output with many digits";
        RUN;
        QUIT;
        ODS RTF close;
        ODS LISTING;
         -  r-   Ndtype)r.   r.   r   r3   r_   r    asarrayreplacesplitfloatrO   r#  	tukey_hsdconfidence_intervalintr   lowrS   highrT   )r#   datares_expect_strr4   
res_expect	res_tukeyconfr   jlrT  hsigr(   r(   r)   test_compare_sas  s   !
zTestTukeyHSD.test_compare_sasz
        1	2	-8.2491590248597	-4.6	-0.9508409751403	0.0144483269098
        1	3	-3.9091590248597	-0.26	3.3891590248597	0.9803107240900
        2	3	0.6908409751403	4.34	7.9891590248597	0.0203311368795
        z
        1	2	-7.02207069748501	-3.645	-0.26792930251500 0.03371498443080
        1	3	-2.68207069748500	0.695	4.07207069748500 0.85572267328807
        2	3	0.59347644287720	4.34	8.08652355712281 0.02259047020620
        r  r  r  zunequal size samplec                 C   s   t j| tdd}tj| }| }|D ]E\}}}	}
}}t|d t|d }}t	|j
||f |	|d t	|j||f |
|d t	|j||f ||d t	|j||f ||d qdS )an  
        vals = [24.5, 23.5,  26.4, 27.1, 29.9, 28.4, 34.2, 29.5, 32.2, 30.1,
         26.1, 28.3, 24.3, 26.2, 27.8]
        names = {'zero', 'zero', 'zero', 'zero', 'zero', 'one', 'one', 'one',
         'one', 'one', 'two', 'two', 'two', 'two', 'two'}
        [p,t,stats] = anova1(vals,names,"off");
        [c,m,h,nms] = multcompare(stats, "CType","hsd");
        r  r   r.   r   r3   N)r    r  r  r  rO   r#  r  r  r  r   r  rS   r  rT   )r#   r  r  r4   r  r  r  r   r  r  rT  r  r'   r(   r(   r)   test_compare_matlab  s   

z TestTukeyHSD.test_compare_matlabc                 C   s   d}t j|dd dd tdd}g dg d	g d
f}tj| }| }|D ]E\}}}}	}
}t	|d t	|d }}t
|j||f |	dd t
|j||f |dd t
|j||f |
dd t
|j||f |dd q,dS )a+  
        Testing against results and p-values from R:
        from: https://www.rdocumentation.org/packages/stats/versions/3.6.2/
        topics/TukeyHSD
        > require(graphics)
        > summary(fm1 <- aov(breaks ~ tension, data = warpbreaks))
        > TukeyHSD(fm1, "tension", ordered = TRUE)
        > plot(TukeyHSD(fm1, "tension"))
        Tukey multiple comparisons of means
        95% family-wise confidence level
        factor levels have been ordered
        Fit: aov(formula = breaks ~ tension, data = warpbreaks)
        $tension
        z
                diff        lwr      upr     p adj
        2 - 3  4.722222 -4.8376022 14.28205 0.4630831
        1 - 3 14.722222  5.1623978 24.28205 0.0014315
        1 - 2 10.000000  0.4401756 19.55982 0.0384598
        r  r  r-   Nr  r  )   r7   6   r5  F   4   3   r  C   rn   r6        r     )   rR   ,   )r7  r  r  r8  rs   r7  r  r7   $   *   r  r  r   rl  r8   r  rl  r  )r  r  r  r7  r/   rk  r8   rn  r  rR   r  r  r8  r   rn  rn  r   r8   r   r  r3   r~   gh㈵>r  )r#   str_resr  r  r  r  r   r  rT  r  r  r'   r(   r(   r)   test_compare_r  s&   
zTestTukeyHSD.test_compare_rc                 C   s   g d}g d}g d}g d}t ||||}| }tg dg dg dg dg}tg d	g d
g dg dg}dD ]$\}	}
t|j|	|
f ||	|
f dd t|j|	|
f ||	|
f dd q@dS )zp
        Example sourced from:
        https://www.itl.nist.gov/div898/handbook/prc/section4/prc471.htm
        )皙@g@333333@gffffff@g      @)g @r  g333333@gffffff"@r  )g       @g      %@g333333 @r  r  )r  gffffff@gffffff@gffffff@g@)r   r   r   g      )g(\?r   gq=
ףpgp=
ף?)gGz?r   r   g
ףp=
?)r   r   r   r   )r   r   r   gzG?)gzG@r   g      ?g=
ףp=@)g=
ףp=@r   r   g@)r   r   )r+   r   )r   r   r   rC  r^   r3   N)r#  r  r  r    r  r   r  r  )r#   group1group2group3group4rU   r  lowerupperr   r  r(   r(   r)   test_engineering_stat_handbook  s,    "z+TestTukeyHSD.test_engineering_stat_handbookc                 C   s   t jd t jdd}tj| }| }t|j|j	j
  tt |j	|j	d  tt |j|jd  t|j|jj
  tt |jd t|j|jj
 tt |jd d S )Nr6   r   rM   )r   r   r   r   )r    r9   r:   r   r#  r  r  r   r  r  rH  diagonalrS   rT   )r#   r  rU   r  r(   r(   r)   test_rand_symm0  s   
zTestTukeyHSD.test_rand_symmc                 C   sN   t tdd tg ddtjgg d W d    d S 1 s w   Y  d S )Nz...must be finite.r   r   r+   )r.   r0   r   )rF   rG   r#  r  r    rJ   rc   r(   r(   r)   test_no_infC  s   "zTestTukeyHSD.test_no_infc                 C   sT   t tdd tddgddggddgg d W d    d S 1 s#w   Y  d S )Nz...must be one-dimensionalr   r   r+   r   r-   )r-   r   r.   rF   rG   r#  r  rc   r(   r(   r)   
test_is_1dG  s   $"zTestTukeyHSD.test_is_1dc                 C   sH   t tdd tg ddgg d W d    d S 1 sw   Y  d S )Nz...must be greater than oner   r+   r-   )r,   r-   r.   r  rc   r(   r(   r)   test_no_emptyK  s   "zTestTukeyHSD.test_no_emptynargsr   c                 C   sF   t tdd tjg dg|   W d    d S 1 sw   Y  d S )Nz...more than 1 treatment.r   r   r0   r   r  )r#   r  r(   r(   r)   test_not_enough_treatmentsO  s   "z'TestTukeyHSD.test_not_enough_treatmentscl)r?  r   r   r+   c                 C   sV   t tdd tg dddgddg}|| W d    d S 1 s$w   Y  d S )Nzmust be between 0 and 1r   r  r   r,   r   )rF   rG   r#  r  r  )r#   r  r  r(   r(   r)   test_conf_level_invalidT  s   "z$TestTukeyHSD.test_conf_level_invalidc                 C   sP   t j| jd d  }t j| jd d  }t|j|jd  t|j|jd  d S )Nr+   r   r  )r#  r  data_diff_size	ttest_indr   rT   )r#   r  	res_ttestr(   r(   r)   test_2_args_ttestZ  s   zTestTukeyHSD.test_2_args_ttestN)rX   rY   rZ   data_same_sizer  extreme_sizesas_same_sizesas_diff_sizesas_extremer  r  r  r  matlab_sm_sizmatlab_diff_szr  r  r  r  r  r  r  r   r  r  r(   r(   r(   r)   r  o  s\    



%
)

r  )1
__future__r   r   r   	itertoolsr   numpyr    r-  r  numpy.testingr   r   r   r	   r
   rF   scipy.statsr#  r   scipy.stats._hypotestsr   r   r   r   r   r   r   scipy.stats._mannwhitneyur   r   common_testsr   scipyr   scipy._lib._testutilsr   r   r[   r   r   r  xslowr&  r'  ri  r  r  r  r(   r(   r(   r)   <module>   s@    $:\   G
  W  Z