o
    gk                    @   sP  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 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Z*G dd  d Z+dS )!    )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)_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$   ^/home/ubuntu/cloudmapper/venv/lib/python3.10/site-packages/scipy/stats/tests/test_hypotests.pytest_statistic_1   s
   z"TestEppsSingleton.test_statistic_1c                 C   sB   t d}t d}t||\}}t|ddd t|ddd d S )	N)r   r      r'   r'   r'   r   r   r   r         r)   r)   r)      
   r+   r+   r+   )r+   r(   r   r)   r+   r+   r   r)   r*      r+   r   r   r,   r      r   r)   r-   r+   g!@MbP?atolg&J?r   r   )r   r   r	   r   r   r   r$   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$   r%   test_epps_singleton_array_like-   s   &z0TestEppsSingleton.test_epps_singleton_array_likec                 C   s"   dt d}}ttt|| d S )Nr   r'   r   r(   r+   )r   r7   assert_raises
ValueErrorr	   r   r    r!   r$   r$   r%   test_epps_singleton_size8   s   z*TestEppsSingleton.test_epps_singleton_sizec                 C   s\   dddddt jft d}}ttt|| t ddddddt jf}}ttt|| d S )Nr   r'   r   r(   r)   r+   )r   infr7   rB   rC   r	   nanrD   r$   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   r7   reshaperB   rC   r	   r   r    r$   r$   r%   test_epps_singleton_1d_inputD   s   z.TestEppsSingleton.test_epps_singleton_1d_inputc                 C   s2   t dt d}}t||}d}t|| d S )N   r3   )	statisticpvalue)r   r7   r	   r   )r   r    r!   res
attributesr$   r$   r%   
test_namesH   s   
zTestEppsSingleton.test_namesN)
__name__
__module____qualname__r&   r1   r@   rE   rH   rM   rS   r$   r$   r$   r%   r      s    
r   c                   @   sd   e Zd Zdd Zdd Zdd Zdd Zd	d
 Zdd Zdd Z	dd Z
dd Zdd Zdd ZdS )TestCvmc                 C       t tg ddg ddd d S )N)gy;i?g#^?gE>?gD
)?r(   {Gz?皙?      ?g+?-C6?r/   r   r   r   r$   r$   r%   
test_cdf_4S   
   
zTestCvm.test_cdf_4c                 C   rX   )N)g8*5?g@߾?gHm?g%1 ?r+   )rZ   r[   r\   g333333?r]   r/   r^   r_   r$   r$   r%   test_cdf_10Y   ra   zTestCvm.test_cdf_10c                 C   rX   )N)g}tg?g`?gI5o?gׁsF?  rY   r]   r/   r^   r_   r$   r$   r%   test_cdf_1000_   ra   zTestCvm.test_cdf_1000c                 C   s   t tg dg ddd d S )N)a+e?+?&pn?+MJA?rY   r]   r/   r^   r_   r$   r$   r%   test_cdf_infe   s
   

zTestCvm.test_cdf_infc                 C   s4   t tddgdddg t tddgdddg d S )	NgX(~$?gUUUUU5f@i  r   r   gaah?g"@   )r   r   r_   r$   r$   r%   test_cdf_supportk   s   zTestCvm.test_cdf_supportc                 C   s$   t tg ddtg ddd d S )N)re   rf   rg   rh   rI   '  r]   r/   r^   r_   r$   r$   r%   test_cdf_large_np   s
   

zTestCvm.test_cdf_large_nc                 C   sL   t dtdd  k odk n   t dtd  k o dk  d S    d S )NgwJ?gt@rc         ?)r   r   r_   r$   r$   r%   test_large_xw   s   "*zTestCvm.test_large_xc                 C   s<   d}t t|d d}tt|j|dk t|jd d S )N   皙?normrn   r   )r
   r   onesr   r   rO   r   rP   )r   nrQ   r$   r$   r%   
test_low_p   s   zTestCvm.test_low_pc                 C   s@   t dd}ttt|d tttdgd tttdd d S )Nr+   r'   r)   rr         ?r$   )r   r7   rK   rB   rC   r
   rL   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?rr   gZ	%q?ư>r/   gEж?)r   rw   g!O!W*?gz"W`?)	r   r'   r)   ffffff?gQ?      ?      @exponge.?gnz\(r?)r
   r   rO   rP   )r   rQ   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   r7   r
   r   r   cdfr   rO   rP   r   )r   r    argsr1r2r$   r$   r%   test_callable_cdf   s   
zTestCvm.test_callable_cdfN)rT   rU   rV   r`   rb   rd   ri   rk   rm   ro   ru   rx   r   r   r$   r$   r$   r%   rW   O   s    	rW   c                   @   s<  e Zd Zdd Zdd Zdd Zg dZg dZd	d
ddgdd
ddgdd
ddgd	dddgddddgddddggZe	j
dedd Zd	dddgddddgddddgd	dddgddddgdddd ggZe	j
ded!d" Zd#d$ 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   
_recursiver_   r$   r$   r%   setup_method      
zTestMannWhitneyU.setup_methodc                 C   sv  t ddg}t ddg}ttdd tg | W d    n1 s$w   Y  ttdd t|g  W d    n1 s?w   Y  ttdd t||dd	 W d    n1 s\w   Y  ttd
d t||dd W d    n1 syw   Y  ttdd t||dd W d    n1 sw   Y  ttdd t||dd W d    d S 1 sw   Y  d S )Nr   r'   r   r(   `x` and `y` must be of nonzeromatchz`use_continuity` must be oneekki)use_continuityz`alternative` must be one ofalternativez`axis` must be an integerrw   axisz`method` must be one ofmethod)r   r   rB   rC   r   rD   r$   r$   r%   test_input_validation   s(   "z&TestMannWhitneyU.test_input_validationc                 C   s  t jd d}t j|d }t j|d }t||}t||dd}t||dd}|j|jks3J |j|jks;J t j|d }t j|d }t||}t||dd}t||dd}|j|jksfJ |j|jksnJ t||}t||dd}t||dd}|j|jksJ |j|jksJ t j|d }t j|d }t||}t||dd}t||dd}|j|jksJ |j|jksJ t j|d }t j|d }|d |d< t||}t||dd}t||dd}|j|jksJ |j|jksJ d S )Nr   r-   
asymptoticr   exactr   )r   r5   r6   randr   rP   )r   rt   r    r!   autor   r   r$   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   rQ   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 )NrA   r   r'   r   r(   r)   )r   r   r   r   r   rZ   )r   r   r   r   r   rJ   r   )r   r   )r+   	         !@r-   r   r,   r*   )r   g]U?g[?gi\?gZX<_?gx.?g 
?)r   r   r   r   rO   r   rP   )	r   r    y0dydy2r!   rQ   
U_expected
p_expectedr$   r$   r%   test_tie_correct:  s   *z!TestMannWhitneyU.test_tie_correct)g      ?r\   g      ?)ry   皙?皙?rz   )r[   ry   r   r   r\   g?r   r'   r   )r   r   rz   )gx&?g/$?gJ+?r   rz   )y&1?v/?gv/?r   gjt?~jt?ʡE?)	gy&1?gV-?r   ry   gS?gv?gʡE?g'1Z?gm?rA   )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?rZ   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?)r.   r   r   r   g9v?g/$?r   r   gL7A`?g
ףp=
?gQ?r   gK7?g`"?g7A`?r   gV-?gjt?gˡE?)r   r'   r   r(   r)   r*   c           
   	   C   s   | j | j| j| jd}| D ]f\}}| D ]]\}}tdt|}tt	j
|||d|dd td|| d }tt	j
|||dt	j|||d t	j|||d d t	j|||d}t||d d d  t	j|||d}	t||	 qqd S )N)r   r(   r)   r*   r   )kmrt   r.   r/   r   rJ   )pn3pn4pm5pm6itemsr   r7   lenr   r   r   sfpmf)
r   p_tablesrt   tabler   r#   uu2r   pmf2r$   r$   r%   test_exact_distributionj  s&   z(TestMannWhitneyU.test_exact_distributionc                 C   s   t jd t jd}t jd}t||dd}t||dd}|j|jks(J t |j|j dks5J t jd}t jd}t||dd}t||dd}|j|jksWJ t |j|j dk sdJ d S )	Nr   r)   r   r   r   rZ   (   r.   )r   r5   r6   r   r   rO   absrP   )r   r    r!   res1res2r$   r$   r%   test_asymptotic_behavior  s   z)TestMannWhitneyU.test_asymptotic_behaviorc                 C   sr   t g dddgddd}t g dddgddd}t|j|j |jdks&J t g dddgd	dd}t|d
 d S )Nr   rw         @r   r   r   r   r\   r   )r   r   )r   r   rP   )r   res_lres_grQ   r$   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$   r%   test_scalar_data  s   z!TestMannWhitneyU.test_scalar_datac                 C   sH   t tddddd t tddddd t tddddddtjf d S )	Nr   r   r   )r\   r   r   F)r   r   r\   )r   r   r   rG   r_   r$   r$   r%   test_equal_scalar_data  s   
z'TestMannWhitneyU.test_equal_scalar_datar   c                 C   sz  t jd d}d\}}t j|dd}t jd|ddd }t||||d	}d
}|jj|ks1J |jj|ks9J t ||dt ||d}}|d }|j	|j	ksTJ t 
|||f }t 
|||f }|jd d |ksqJ |jd d |ks|J t |}	t |}
tdd |D  D ]}|| }|| }t|||d}|j|	|< |j|
|< qt j|j|
 t j|j|	 d S )Nr   )r,   r+   r   r-   r*   r   ry   )r   r   )r*   r   r-   rJ   )N.c                 S   s   g | ]}t |qS r$   )range).0ir$   r$   r%   
<listcomp>  s    z8TestMannWhitneyU.test_gh_12837_11113.<locals>.<listcomp>r   )r   r5   r6   r   r   rP   shaperO   moveaxisndimbroadcast_tozerosr   testingr   )r   r   r   r   rt   r    r!   rQ   r   
statisticspvaluesindicesxiyitempr$   r$   r%   test_gh_12837_11113  s4   


z$TestMannWhitneyU.test_gh_12837_11113c                 C   s~   g d}g d}t ||}tj|d< t ||}t|j|j t|j|j tj|d< t ||}t|jtj t|jtj d S )NrA   )r   r*   r,   r-   r   r   r'   r   r(   r(   r)   r(   )r   r   rF   r   rO   rP   rG   )r   r    r!   r   r   res3r$   r$   r%   test_gh_11355  s   




zTestMannWhitneyU.test_gh_11355r   r*   r,   r-   r'   r   r(   r)   r+   g+zQ?r   g}$k\?g     1@g!˛G*?r   g,s?     8@gFHQ?)r    r!   rO   rP   c                 C   s2   t ||dd}t|j|dd t|j|dd d S )Nr   r   -q=r/   )r   r   rO   rP   )r   r    r!   rO   rP   rQ   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#   )
rq   g(\?g=
ףp=?gp=
ף?g333333?gGz?g(\?g=
ףp=?r   g\(\?)gffffff?g)\(?r   gGz?g\(\?r   r   r   )r   r   rO   r   rP   )	r   r   r   r   r  statistic_expr    r!   rQ   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   )rB   rC   r   r_   r$   r$   r%   test_gh_6897F  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   rG   r   r   rO   rP   )r   abrQ   r$   r$   r%   test_gh_4067K  s
   
zTestMannWhitneyU.test_gh_4067rw   r   )r   ga׀}?)r   rn   )rw   g?h?)rw   r   )r'   g5&#\?)r'   r   )r    r!   r   r   c                 C   s$   t ||d|dd}t||dd d S )NTr   r	  r  )rtol)r   r   )r   r    r!   r   r   rQ   r$   r$   r%   test_gh_2118c  s   
zTestMannWhitneyU.test_gh_2118c                 C   
   d t _d S r   r   r_   r$   r$   r%   teardown_methodk  r   z TestMannWhitneyU.teardown_methodN)'rT   rU   rV   r   r   r   r    r!   cases_basicpytestmarkparametrizer   cases_continuityr   r   r   r   r   r   r   r   r   cases_scalarr   r   r  r  r   rF   cases_11355r  
cases_9184r  r  r  
cases_2118r  r  r$   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   r_   r$   r$   r%   r   p  r   z'TestMannWhitneyU_iterative.setup_methodc                 C   r  r   r   r_   r$   r$   r%   r  s  r   z*TestMannWhitneyU_iterative.teardown_methodN)rT   rU   rV   r   r  r$   r$   r$   r%   r  o  s    r  c                  C   s   d t _td t _tjd} | d}| d}tj||dd t	t jdks,J | d}tj||dd t	t jdkrCJ d S )	N)r   r   r   l   7cE"r)   i  r   r   rJ   i  )
r   r   r   rs   _fmnksr5   default_rngstatsr   all)rngr    r!   r$   r$   r%   test_mann_whitney_u_switchw  s   


r#  c                   @   sz   e Zd Zdd Zdd Zdd Zdd Zd	d
 Zdd Zdd Z	dd Z
dd Zdd Zdd Zejdddd ZdS )TestSomersDc                    st    j  j  _td j  j ftd j  j fd _ fdd jD }tjtj	dd _
 j
|  _d S )Nr+   r   c                    s   g | ]	} j | d  qS )r   )	arguments)r   idxr_   r$   r%   r     s    z,TestSomersD.setup_method.<locals>.<listcomp>r   r   )ALL_INTEGER	ALL_FLOATdtypesr   r7   r%  	functoolspartialr   somersdpartialfuncr   )r   input_arrayr$   r_   r%   r     s   

zTestSomersD.setup_methodc                 G   s6   | j | }t|j| jjdd t|j| jjdd d S )NV瞯<r/   )r-  r   rO   r   rP   )r   r   rQ   r$   r$   r%   pythranfunc  s   
zTestSomersD.pythranfuncc                 C   sf   g dg dg dg}t |}| t j}t j|fi |}t|j|jdd t|j|jdd d S )N)rj         r,   r   )r,   r2     r  rp   )r   r   r'   r,      r/  r/   )r   r,  get_optional_argsr   rO   rP   )r   r   r   optional_argsr   r$   r$   r%   test_pythranfunc_keywords  s   
z%TestSomersD.test_pythranfunc_keywordsc                 C   sn  g d}g d}d}t ||}t|j|d dd t|j|d dd g d}g d	}d}t ||}t|j|d dd t|j|d dd g d
}g d}d}t ||}t|j|d dd t|j|d dd td}td}d}t ||}t|j|d dd t|j|d dd td}tg d}d}t ||}t|j|d dd t|j|d dd td}tdd d d }d}t ||}t|j|d dd t|j|d dd td}tg d}d}t ||}t|j|d dd t|j|d dd g d}g d}d}t ||}t|j|d dd t|j|d dd t g dg d}t|jtj t|jtj t g dg d}t|jtj t|jtj t g dg d}t|jtj t|jtj t dgdg}t|jtj t|jtj t g g }t|jtj t|jtj td}td}t	t
t j|| d S )N)r)   r'   r   r   r*   r(   r,   r-   )r)   r'   r*   r   r   r-   r,   r(           rn   r   r/  r/   r   )	r   r)   r'   r   r   r*   r(   r,   r-   )	r)   r'   r   r*   r   r   r-   r,   r(   )r)   r'   r   r   r*   r(   r,   )r)   r'   r*   r   r   r,   r(   )g+$I$I¿g=/3n+?r+   rn   r   )
r   r'   r   r   r(   r*   r)   r,   r-   r   )gs'}'?r9  rJ   )g      r   )
r   r,   r-   r*   r)   r   r(   r'   r   r   )g}'}'r9  )rp   r'   r   rp   r'   )r   r(   r,   r   r   )      g.ʂ?)r'   r'   r'   )r'   r   r'   g      $@g      4@)r   r,  r   rO   rP   r   r7   r   rG   rB   rC   )r   r    r!   r   rQ   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?r/  r/   r]   )r   r'   r'   r   )r   r,  r   rO   rP   r   r   r   )r   r    r!   d_crd_rcr#   rQ   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 )Nr-   r'   r*   r)   r   r(   r   gHHHHHH?r1  r   U   r3   )gM&w?rn   gtE]t)r   r   Tr   r   r,  rO   )r   r   dyxdxyr$   r$   r%   test_somers_original9  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 )NrI   r(   r*   r   r#   r'   r   r   gayr/  r/   gPj$?)r   prodr5   r6   r   multinomialrvsrs   rK   r,  insertr   r   rO   rP   )r   Nr   sizesrQ   s2r   s3r  s4res4r$   r$   r%   *test_contingency_table_with_zero_rows_colsO  s(   
 


 
z6TestSomersD.test_contingency_table_with_zero_rows_colsc           	      C   s  d}d}t |}t jd tjj|t || d|}|d }d}t	t
|d t| W d    n1 s;w   Y  |d }d	}t	t
|d t| W d    n1 s\w   Y  d
}t	t
|d tg g W d    n1 szw   Y  t	t
|d tdgg W d    n1 sw   Y  t d}t	t
|d t| W d    n1 sw   Y  d|d< t	t
|d t| W d    d S 1 sw   Y  d S )NrI   rH  r   rI  r'   z:All elements of the contingency table must be non-negativer   rZ   z5All elements of the contingency table must be integerz?At least two elements of the contingency table must be nonzero.r   )r   r   r   )r   rJ  r5   r6   r   rK  rL  rs   rK   rB   rC   r,  r   )	r   rN  r   rO  rP  s5messages6s7r$   r$   r%   test_invalid_contingency_tablesn  s<   
 
"z+TestSomersD.test_invalid_contingency_tablesc                 C   sb   g d}ddt jg}g d}ddt j g}t||}t||}t|j|j t|j|j d S )Nr   rJ   g @)r   r'   r   r   r;  )r   rF   r   r,  r   rO   rP   )r   r    r=  r!   y2rQ   r   r$   r$   r%   test_only_ranks_matter  s   z"TestSomersD.test_only_ranks_matterc                 C   s6   t d}t d}t||}t|jt d d S )Nr+   )r   r7   r   r,  r   r   eye)r   r    r!   rQ   r$   r$   r%   test_contingency_table_return  s   

z)TestSomersD.test_contingency_table_returnc                 C   s`  g d}g d}t j||dd}|jdksJ t j||dd}t|j|j t|jd|jd   t j||d	d}t|j|j t|j|jd  |  t j||dd}|jdk s\J t j||d	d}t|j|j t|jd|jd   t j||dd}t|j|j t|j|jd  tjt	d
d t j||dd W d    d S 1 sw   Y  d S )Nr   )r)   r*   r,   r-   r,   r   r   r   r   r   r'   r   zalternative must be 'less'...r   z	ekki-ekki)
r   r,  rO   r   r   rP   reverser  r   rC   )r   r<  r=  r   rQ   r$   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   rJ   r   r   r   r   r   )r   r7   flipr   r,  rO   rP   )r   ra  r<  r=  expected_statisticrQ   r$   r$   r%    test_somersd_perfect_correlation  s   
z,TestSomersD.test_somersd_perfect_correlationN)rT   rU   rV   r   r0  r7  r>  rB  rG  rU  rZ  r\  r^  r`  r  r  r  rd  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$fgd,d- Zd.d/ Z	ejdddgddggd0fgd1d2 Z
ejdddgddggd3ejffddgddggd3ejffgd4d5 Zejdd	dgdd	ggd6fdd7gd8dggd9fd:d;gd<dggd=fgejd>d?d@gdAdB ZdCS )DTestBarnardExactz8Some tests to show that barnard_exact() works correctly.input_sample,expected+   r   r+   '   )gXyq@g{2s&Q7?rI   r'   rc   r)   )gllgEA]0K?r,   r-   )*)1%g_  ?r   )g_c1?g= ?   rN   )g5PyQgQ@2?r   r1  )ggJ"?)g_c1gwݝل?r   r(   )g7@g      ?r   )g~t,?3O?r*   )gr?~CY7?c                 C   s(   t |}|j|j}}t||g| dS )zThe expected values have been generated by R, using a resolution
        for the nuisance parameter of 1e-6 :
        ```R
        library(Barnard)
        options(digits=10)
        barnard.test(43, 40, 10, 39, dp=1e-6, pooled=TRUE)
        ```
        Nr   rO   rP   r   r   input_sampler   rQ   rO   rP   r$   r$   r%   test_precise  s   zTestBarnardExact.test_precise)g7\@gA2?)gXS;gh?)g>!Ɏg6  ?)gSy@?g^F?)g-gXI#?)gaЍgo?)gb]?gFugH	?)g6ҭ@g      ?)gi(	rk  )gNXzrl  c                 C   s,   t |dd}|j|j}}t||g| dS )zThe expected values have been generated by R, using a resolution
        for the nuisance parameter of 1e-6 :
        ```R
        library(Barnard)
        options(digits=10)
        barnard.test(43, 40, 10, 39, dp=1e-6, pooled=FALSE)
        ```
        F)pooledNrm  rn  r$   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   rt   ,The input `table` must be of shape \(2, 2\).r*   *All values in `table` must be nonnegative.rJ   zI`alternative` should be one of {'two-sided', 'less', 'greater'}, found .*not-correct)rB   rC   r   r   r7   rK   r   	error_msgr$   r$   r%   test_raises#  $   "zTestBarnardExact.test_raisesr:  c                 C   6   t |}|j|j}}t||d  t||d  d S Nr   r   r   rO   rP   r   rn  r$   r$   r%   test_edge_cases=  s   z TestBarnardExact.test_edge_casesrn   c                 C   r}  r~  r  rn  r$   r$   r%   test_row_or_col_zeroI     z%TestBarnardExact.test_row_or_col_zero)ri  gE\/??   ,  )ggQ5r9     r4   i  )g&X}>r9  r   r   r   c           	      C   sf   |\}}|dkrt |dddddf }| }t||d}|j|j}}t||g||gdd dS )a  
        "The expected values have been generated by R, using a resolution
        for the nuisance parameter of 1e-6 :
        ```R
        library(Barnard)
        options(digits=10)
        a = barnard.test(2, 7, 8, 2, dp=1e-6, pooled=TRUE)
        a$p.value[1]
        ```
        In this test, we are using the "one-sided" return value `a$p.value[1]`
        to test our pvalue.
        r   NrJ   r   Hz>r/   )r   r   r   rO   rP   r   )	r   ro  r   r   expected_statless_pvalue_expectrQ   rO   rP   r$   r$   r%   test_less_greaterV  s   
z"TestBarnardExact.test_less_greaterN)rT   rU   rV   __doc__r  r  r  rp  rr  r{  r  r   rG   r  r  r$   r$   r$   r%   re    sr    



re  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$fddgddggd%fddgd	dggd&fdd	gddggdfddgd'dggdfddgddggd!fddgddggd(fd
dgddggd)fgd*d+ Z	ejdddgd
dggd,fddgddggd-fdd	gd
d
ggd.fddgddggd/fddgd	dggd0fdd	gddggd1fddgddggd-fddgddggd2fgd3d4 Z
d5d6 Zejdddgdd
ggejejffddgd
dggejejffgd7d8 Zd9d: Zejd;d<d=d> Zd?S )@TestBoschlooExactz9Some tests to show that boschloo_exact() works correctly.r  rf  r'   r,   r-   )<vB\?g/??r)   r   r+   )gM?gA>?r   rN   r1  )_VѶ?g֭?)u %?gc'?r   r(   r   r   r   )r\   g      ?rp   )+f?gXc}v?   %   )gZыD?ggi]?c                 C   2   t |dd}|j|j}}t||g|| jd dS )a  The expected values have been generated by R, using a resolution
        for the nuisance parameter of 1e-8 :
        ```R
        library(Exact)
        options(digits=10)
        data <- matrix(c(43, 10, 40, 39), 2, 2, byrow=TRUE)
        a = exact.test(data, method="Boschloo", alternative="less",
                       tsmethod="central", np.interval=TRUE, beta=1e-8)
        ```
        r   r   r/   Nr   rO   rP   r   ATOLrn  r$   r$   r%   	test_less~  s   zTestBoschlooExact.test_lessrg  r   rh  )k\2?g0,%?)gKv?gN3?)r  g'&5?rj  )gw@_?g7?)gi{?gɑ)z?)օa?g1|?r*   )gY<;?gND?)ge?gG`?c                 C   r  )a  The expected values have been generated by R, using a resolution
        for the nuisance parameter of 1e-8 :
        ```R
        library(Exact)
        options(digits=10)
        data <- matrix(c(43, 10, 40, 39), 2, 2, byrow=TRUE)
        a = exact.test(data, method="Boschloo", alternative="greater",
                       tsmethod="central", np.interval=TRUE, beta=1e-8)
        ```
        r   r   r/   Nr  rn  r$   r$   r%   test_greater  s   zTestBoschlooExact.test_greater)r  gqQS,5?)r  gG?/??)r  gKE`?)r  ghr1ֽ?)r  grfb?)r\   g      ?)r  gP:pRv?c                 C   s4   t |ddd}|j|j}}t||g|| jd dS )a  The expected values have been generated by R, using a resolution
        for the nuisance parameter of 1e-8 :
        ```R
        library(Exact)
        options(digits=10)
        data <- matrix(c(43, 10, 40, 39), 2, 2, byrow=TRUE)
        a = exact.test(data, method="Boschloo", alternative="two.sided",
                       tsmethod="central", np.interval=TRUE, beta=1e-8)
        ```
        r   @   )r   rt   r/   Nr  rn  r$   r$   r%   test_two_sided  s   z TestBoschlooExact.test_two_sidedc                 C   rs  )Nrt  r   r   r'   r   r(   r   ru  rv  r*   rw  rJ   zK`alternative` should be one of \('two-sided', 'less', 'greater'\), found .*rx  )rB   rC   r   r   r7   rK   ry  r$   r$   r%   r{    r|  zTestBoschlooExact.test_raisesc                 C   r}  r~  )r   rO   rP   r   rn  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~   rp   r   r   r   r'   r   rn   )r   rP   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'   r,   r-   r   r   )r   rO   r   fisher_exactr   )r   r   r  boschloo_statfisher_pr$   r$   r%   test_against_fisher_exact  s   z+TestBoschlooExact.test_against_fisher_exactN)rT   rU   rV   r  r  r  r  r  r  r  r  r{  r   rG   r  r  r  r$   r$   r$   r%   r  y  sr    




r  c                   @   s^   e Zd Zdd Zdd Zdd Zejdg dd	d
 Z	dd Z
dd Zdd Zdd ZdS )TestCvm_2sampc                 C   sH  t dd}t d}d}tjt|d t|| W d    n1 s&w   Y  tjt|d t|| W d    n1 sBw   Y  d}tjt|d tg | W d    n1 s`w   Y  tjt|d t|dg W d    n1 s}w   Y  d}tjt|d t||d	 W d    d S 1 sw   Y  d S )
Nr+   rv   r)   z#The samples must be one-dimensionalr   z/x and y must contain at least two observations.r   z/method must be either auto, exact or asymptoticxyz)r   r7   rK   r  r   rC   r   )r   r    r!   msgr$   r$   r%   rx     s(   
"z TestCvm_2samp.test_invalid_inputc                 C   sN   g d}g d}t ||}t t|t|}t|j|jf|j|jf d S )N)r'   r   r(   r,   r*   )r   r   rp   r3  )r   r   r   r   rO   rP   r   r    r!   r   r   r$   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$@g333333%@gffffff&@)g@g@g@      @333333@gffffff @g333333"@g#@g%@g&@g      '@g(@g      )@g*@g333333-@gS㥛?r.   r/   g
ףp=
?rZ   )r   r   rO   rP   r   r    r!   rr$   r$   r%   test_example_conover+  s
   
z"TestCvm_2samp.test_example_conoverzstatistic, m, n, pval))i  r)   r*   gcj`?)ii  r,   r,   gtE]t?)i@  r(   r*   g88?)i  r*   r,   gXwS?c                 C   s   t t|||| d S r   )r   r   )r   rO   r   rt   pvalr$   r$   r%   test_exact_pvalue5  s   	zTestCvm_2samp.test_exact_pvaluec                 C   s   t jd tjjdd}tjjdd}t||}td|j  k o$dk n   t||d }td|j  k o=dk  d S    d S )Ni  i@B )rO  i r   r   ry   )	r   r5   r6   r   rr   rL  r   r   rP   r  r$   r$   r%   test_large_sample@  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   r,   r-   r   r   r   rZ   r/   )	r   r5   r6   r   r   r   rO   r   rP   r  r$   r$   r%   test_exact_vs_asymptoticK  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 )NrN   )r\   g@g333333*@r   r   r   r  r   )r   r7   r   r   rP   r  r$   r$   r%   test_method_autoT  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 )Nrj  r8  r(   )r   r7   r   r   rO   rP   )r   r    rQ   r$   r$   r%   test_same_input`  s
   

zTestCvm_2samp.test_same_inputN)rT   rU   rV   rx   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,atolr]   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   r/   r[   r   asarrayreplacesplitfloatrK   r   	tukey_hsdconfidence_intervalintr   lowrO   highrP   )r   datares_expect_strr0   
res_expect	res_tukeyconfr   jlrP  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   r/   N)r   r  r  r  rK   r   r  r  r  r   r  rO   r  rP   )r   r  r  r0   r  r  r  r   r  r  rP  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)
        $tension
        z
                diff        lwr      upr     p adj
        2 - 3  4.722222 -4.8376022 14.28205 0.4630831
        1 - 3 14.722222  5.1623978 24.28205 0.0014315
        1 - 2 10.000000  0.4401756 19.55982 0.0384598
        r  r  r)   Nr  r  )   r3   6   r1  F   4   3   r  C   rj   r2        r     )   rN   ,   )r3  r  r  r4  rp   r3  r  r3   $   *   r  r  r   rh  r4   r  rh  r  )r  r  r  r3  r+   rg  r4   rj  r  rN   r  r  r4  r~   rj  rj  r   r4   r   r  r/   r{   gh㈵>r  )r   str_resr  r  r  r  r   r  rP  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 ]$\}	}
t|j|	|
f ||	|
f dd t|j|	|
f ||	|
f dd q@dS )zp
        Example sourced from:
        https://www.itl.nist.gov/div898/handbook/prc/section4/prc471.htm
        )皙@g@333333@gffffff@g      @)g @r  g333333@gffffff"@r  )g       @g      %@g333333 @r  r  )r  gffffff@gffffff@gffffff@g@)r   r   r   g      )g(\?r   gq=
ףpgp=
ף?)gGz?r   r   g
ףp=
?)r   r   r   r   )r   r   r   gzG?)gzG@r   g      ?g=
ףp=@)g=
ףp=@r   r   g@)r   r   )r'   r   )r   r   r   r?  rZ   r/   N)r   r  r  r   r  r   r  r  )r   group1group2group3group4rQ   r  lowerupperr   r  r$   r$   r%   test_engineering_stat_handbook  s,    "z+TestTukeyHSD.test_engineering_stat_handbookc                 C   s   t jd t jdd}tj| }| }t|j|j	j
  tt |j	|j	d  tt |j|jd  t|j|jj
  tt |jd t|j|jj
 tt |jd d S )Nr2   r   rI   r   r   r   r   )r   r5   r6   r   r   r  r  r   r  r  rD  diagonalrO   rP   )r   r  rQ   r  r$   r$   r%   test_rand_symm-  s   
zTestTukeyHSD.test_rand_symmc                 C   sN   t tdd tg ddtjgg d W d    d S 1 s w   Y  d S )Nz...must be finite.r   r   r'   )r*   r,   r   )rB   rC   r   r  r   rF   r_   r$   r$   r%   test_no_inf@  s   "zTestTukeyHSD.test_no_infc                 C   sT   t tdd tddgddggddgg d W d    d S 1 s#w   Y  d S )Nz...must be one-dimensionalr   r   r'   r   r)   )r)   r   r*   rB   rC   r   r  r_   r$   r$   r%   
test_is_1dD  s   $"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  r_   r$   r$   r%   test_no_emptyH  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   r,   r   r  )r   r  r$   r$   r%   test_not_enough_treatmentsL  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$w   Y  d S )Nzmust be between 0 and 1r   r  r   r(   r   )rB   rC   r   r  r  )r   r   r  r$   r$   r%   test_conf_level_invalidQ  s   "z$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   rP   )r   r  	res_ttestr$   r$   r%   test_2_args_ttestW  s   zTestTukeyHSD.test_2_args_ttestN)rT   rU   rV   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$   r%   r  l  s\    



%
)

r  c                   @   s   e Zd Zejdg dg dfdd Zejdg dg dg d	g d
g dg dg dg dfdd Zdd Zdd Z	dd Z
dS )TestPoissonMeansTestzc1, n1, c2, n2, p_expect)r   rI   r   rI   gea?)r'   rI   r*   rI   g	c?c                 C   s$   t ||||}t|j|dd d S )Nr]   r/   r   poisson_means_testr   rP   )r   c1n1c2n2p_expectrQ   r$   r$   r%   test_paper_examples`  s   z(TestPoissonMeansTest.test_paper_examplesz c1, n1, c2, n2, p_expect, alt, d)rN   r+   rN   r+   g{}?r   r   )r+   r+   r+   r+   goPF?r   r   )2   rj  r   r   gae?r   r[   )r   rI   rN   r  g/V-=?r   r   )r   rp   r(   rN   g")?r   r   )r(   rN   r   rI   g_'Qm~?r   r   )r(   rN   r   r+   g|?r   r   )r   r   r  rj  g0ݷ?r   r   c           	      C   s,   t j||||||d}t|j|ddd d S )N)r   diffg>gؗҜ<)r0   r  r  )	r   r  r  r  r  r  altdrQ   r$   r$   r%   test_fortran_authorsi  s   z)TestPoissonMeansTest.test_fortran_authorsc                 C   s0   d\}}d\}}t ||||}t|jd d S )N)rl   rl   r   r  r   count1count2nobs1nobs2rQ   r$   r$   r%   test_different_results~  s   z+TestPoissonMeansTest.test_different_resultsc                 C   s0   d\}}d\}}t ||||}t|jd d S )Nr  r  r   r  r  r$   r$   r%   test_less_than_zero_lambda_hat2  s   z4TestPoissonMeansTest.test_less_than_zero_lambda_hat2c                 C   s  d\}}d\}}d}t t|d td||| W d    n1 s#w   Y  t t|d t||d| W d    n1 sAw   Y  d}t t|d td||| W d    n1 saw   Y  t t|d t||d| W d    n1 sw   Y  d}t t|d t|d|| W d    n1 sw   Y  t t|d t|||d W d    n1 sw   Y  d	}t t|d tj||||dd
 W d    n1 sw   Y  d}t t|d tjdddddd W d    d S 1 sw   Y  d S )Nr  r  z`k1` and `k2` must be integers.r   r   z1`k1` and `k2` must be greater than or equal to 0.rJ   z%`n1` and `n2` must be greater than 0.z(diff must be greater than or equal to 0.)r  zAlternative must be one of ...r   r'   errorr   )rB   	TypeErrorr   r  rC   )r   r  r  r  r  rW  r$   r$   r%   r     s>   $z*TestPoissonMeansTest.test_input_validationN)rT   rU   rV   r  r  r  r  r  r   r!  r   r$   r$   r$   r%   r  _  s(    

	r  ),	itertoolsr   numpyr   r*  r  numpy.testingr   r   r   r   r   rB   scipy.statsr   r   scipy.stats._hypotestsr	   r
   r   r   r   r   r   scipy.stats._mannwhitneyur   r   common_testsr   scipy._lib._testutilsr   r   rW   r   r  r  xslowr#  r$  re  r  r  r  r  r$   r$   r$   r%   <module>   s@    $:\   G
  W  Z t