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!!rwwt}T'9 ! : B B5 I UN :W 5 MM" 6XI :W 5 MM" 6, :W 5 MM2$ 6:W 5 MMA3% 6XXf  :W 5 MM" 64 :W 5 MM" 6 5+6 5 6 5 6 56 56 56 5sHG G>G .G,4G8(HGG G),G58HH c:gd}ddtjg}gd}ddtj g}tj||}tj||}t |j |j t |j |j y)Nrrg@)r r-rrrm)r!rUrArYrrNrP)r$r%ror&y2rRrs r)test_only_ranks_matterz"TestSomersD.test_only_ranks_mattersr #rvv  w mmAq!}}R$S]]DNN3SZZ-r+ctjd}tjd}tj||}t |j tj dy)Nr1)r!r>rArYrreyerQs r)test_contingency_table_returnz)TestSomersD.test_contingency_table_returnsB IIbM IIbMmmAq!SYYr +r+cLgd}gd}tj||d}|jdkDsJtj||d}t|j|jt |j d|j dz z tj||d }t|j|jt |j |j dz |j tj||d}|jdksJtj||d }t|j|jt |j d|j dz z tj||d}t|j|jt |j |j dz tjtd 5tj||d dddy#1swYyxYw) Nr)r/r0r2r3r2rrrrrr-rz`alternative` must be...rJ ekki-ekki) rArYrNrrrPreverserLrrW)r$rnrorrRs r)test_somersd_alternativez$TestSomersD.test_somersd_alternatives ==R[A!!A%%%mmB7S]]H$6$67 A1)<$=>mmB :S]]H$6$67 HOOa$78 ==R[A!!A%%%mmB :S]]H$6$67 A1)<$=>mmB7S]]H$6$67 HOOa$78 ]]:-G H MM"bk :I H Hs 8HH#positive_correlation)FTctjd}|r|ntj|}|rdnd}tj||d}|j |k(sJ|j dk(sJtj||d}|j |k(sJ|j |rdndk(sJtj||d}|j |k(sJ|j |rdndk(sJy) Nr1rrrrrrr)r!r>fliprArYrNrP)r$rrnroexpected_statisticrRs r) test_somersd_perfect_correlationz,TestSomersD.test_somersd_perfect_correlations YYr]'RRWWR["6QBmmB <}} 2222zzQmmB7}} 2222zz#7aQ???mmB :}} 2222zz#7aQ???r+cddg}d}tjdtj||}tj||}d}tj||j }t ||dy) Nrr-@Bi_rgHz YrGr5)r<r=choicesrArYrNr)r$classes n_samplesr%r& val_sklearn val_scipys r)!test_somersd_large_inputs_gh18132z-TestSomersD.test_somersd_large_inputs_gh18132si a&  G NN7i 0 NN7i 0, MM!Q'11  YU;r+N)r^r_r`r]r`rhrprur{rrrrrrLrrrrrar+r)rQrQsl 7F >m7^.2?,1>!F .,';R [[3]C@D@0TestBarnardExactz8Some tests to show that barnard_exact() works correctly.input_sample,expected+rr1')gXyq @g{2s&Q7?r|r-rpr/)gllgEA]0K?r2r3)*)1%g_?r)g_c1?g=?r[)g5PyQgQ@2?rrb)ggJ"?)g_c1gwݝل?rr.)g7@g?r )g~t,?3O?r0)gr?~CY7?cft|}|j|j}}t||g|y)zThe expected values have been generated by R, using a resolution for the nuisance parameter of 1e-6 : ```R library(Barnard) options(digits=10) barnard.test(43, 40, 10, 39, dp=1e-6, pooled=TRUE) ``` NrrNrPrr$ input_samplerrRrNrPs r) test_precisezTestBarnardExact.test_precises.2L)MM3::6 F+X6r+)g7\@gA2?)gXS;gh?)g>!Ɏg6?)gSy@?g^F?)g-gXI#?)gaЍgo?)gb]?gFugH ?)g 6ҭ@g?)gi( r)gNXzrcjt|d}|j|j}}t||g|y)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)pooledNrrs r)test_pooled_paramz"TestBarnardExact.test_pooled_param"s02L7MM3::6 F+X6r+c d}tt|5tddgddggddddd }tt|5ttjd j dddddd }tt|5td dgddggdddd }tt|5tddgddggddddy#1swYxYw#1swYqxYw#1swYPxYw#1swYyxYw)N7Number of points `n` must be strictly positive, found 0rJrr-r r.rr,The input `table` must be of shape \(2, 2\).r0*All values in `table` must be nonnegative.rzI`alternative` should be one of {'two-sided', 'less', 'greater'}, found .* not-correct)rVrWrr!r>rr$ error_msgs r) test_raiseszTestBarnardExact.test_raises?s F :Y 7 Aq6Aq6*a 08E :Y 7 "))A,..q!4 58A :Y 7 B7QF+ ,8   :Y 7 Aq6Aq6*M :8 7%8 7 8 7 8 78 7/C/C" C.:C:C"C+.C7:Drlct|}|j|j}}t||dt||dyNrrrrNrPrrs r)test_edge_casesz TestBarnardExact.test_edge_casesYs;L)MM3::6 VXa[)Y ,r+rct|}|j|j}}t||dt||dyrrrs r)test_row_or_col_zeroz%TestBarnardExact.test_row_or_col_zeroes;L)MM3::6 VXa[)Y ,r+)rgE\/??,)ggQ5rkr;i)g&X}>rkrrrc|\}}|dk(r"tj|dddddf}| }t||}|j|j}}t ||g||gdy)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. rNrrHz>r5)r!r"rrNrPr) r$rrr expected_statless_pvalue_expectrRrNrPs r)test_less_greaterz"TestBarnardExact.test_less_greaterrsp,-5) ) ) #88L1!TrT':L*NMLkBMM3::6   -1C!D4 r+N)r^r_r`__doc__rLrrrrrrr!rOrrrar+r)rrsuB [[2hR !#C DAhq "$E F!fq!f @ A!fr2h !A B"gBx "C D"gBx "C D1gAw !B C!fq!f ? @!fq!f @ A!fq!f @ A!fq!f @ A  7! 7 [[2hR !#C DAhq "$E F!fq!f @ A!fr2h !A B"gBx "C D"gBx "C D1gAw !B C!fq!f ? @!fq!f @ A!fq!f @ A!fq!f @ A  7! 7;4 [[!fq!f x (  -  -  [[!fq"g bff .!fr1g bff . --  [[!fq!f @ A#ha !#: ;2hq "$; <  [[]Y,?@ A r+rceZdZdZdZej jdddgddggdfdd gd d ggd fdd gd dggdfd dgd d ggdfddgd dggdfdd gddggdfddgddggdfddgddggdfd dgddggdfg dZej jdddgd dggdfddgddggd fdd gd d ggd!fdd"gd d ggd#fdd gd dggd$fddgd dggd%fdd gddggdfddgd&dggdfddgddggd fddgddggd'fd dgddggd(fg d)Z ej jdddgd dggd*fddgddggd+fdd gd d ggd,fdd gd dggd-fddgd dggd.fdd gddggd/fddgddggd+fddgddggd0fgd1Z d2Z ej jdddgdd gge je jffddgd dgge je jffgd3Zd4Zej jd5d6d7Zy8)9TestBoschlooExactz9Some tests to show that boschloo_exact() works correctly.rrr-r2r3)<vB\?g/??r/rr1)gM?gA>?rr[rb)_VѶ?g֭?)u%?gc'?rr.rrr )rhg?r)+f?gXc}v?%)gZыD?ggi]?ct|d}|j|j}}t||g||jy)aThe 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) ``` rrr5NrrNrPrATOLrs r) test_lesszTestBoschlooExact.test_lesss62\v>MM3::6 F+XDIIFr+rrr) k\2?g0,%?)gKv?gN3?)rg'&5?r)gw@_?g7?)gi{?gɑ)z?)օa?g1|?r0)gY<;?gND?)ge?gG`?ct|d}|j|j}}t||g||jy)aThe 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) ``` rrr5Nrrs r) test_greaterzTestBoschlooExact.test_greaters66\yAMM3::6 F+XDIIFr+)rgqQS,5?)rgG?/??)rgKE`?)rghr1ֽ?)rgrfb?)rhg?)rgP:pRv?ct|dd}|j|j}}t||g||jy)aThe 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@)rrr5Nrrs r)test_two_sidedz TestBoschlooExact.test_two_sideds80\{bIMM3::6 F+XDIIFr+c d}tt|5tddgddggddddd }tt|5ttjd j dddddd }tt|5td dgddggdddd }tt|5tddgddggddddy#1swYxYw#1swYqxYw#1swYPxYw#1swYyxYw)NrrJrr-r r.rrrr0rrzK`alternative` should be one of \('two-sided', 'less', 'greater'\), found .*r)rVrWrr!r>rrs r)rzTestBoschlooExact.test_raisess F :Y 7 QFQF+q 18E :Y 7 299Q<//15 68A :Y 7 RGaV, -8  % :Y 7 QFQF+] ;8 7%8 7 8 7 8 78 7rct|}|j|j}}t||dt||dyr)rrNrPrrs r)rz&TestBoschlooExact.test_row_or_col_zero s;\*MM3::6 VXa[)Y ,r+cddgddgg}t|dj}t|dj}dt||zdkDsJt|dj}|d k(sJy) Nrrrrrrr-rr)rrPrC)r$tblplpgpts r)test_two_sided_gt_1z%TestBoschlooExact.test_two_sided_gt_1sp1vBx  CV 4 ; ; CY 7 > >R}q   C[ 9 @ @Syyr+r)rrcddgddgg}t||j}tj||d}t ||y)Nr-r2r3rr)rrNrA fisher_exactr)r$rr boschloo_statfisher_ps r)test_against_fisher_exactz+TestBoschlooExact.test_against_fisher_exact$sI1v1v&s DNN %%c{CAF x0r+N)r^r_r`rrrLrrrrrrr!rOrrrrar+r)rrsC D [[!fq!f 8 9!fr2h !7 8"gBx ": ;1gAw !8 9!fq!f v &!fq!f ~ .!fq!f 8 9"g1v  8 92hR !#9 :   G  G [[2hR !#? @!fq!f 5 6!fr2h !8 9"gBx "8 9"gBx "7 8!fq!f 8 9!fq!f v &!fq!f v &!fq!f 5 6"g1v  6 72hR !#9 :  G! G [[2hR !#? @!fq!f 7 8!fr2h !7 8"gBx "8 9!fq!f 7 8!fq!f } -!fq!f 7 8"g1v  8 9  G G <4 [[!fq"g  0 1!fr1g  0 1 --  [[],?@1A1r+rcBeZdZejj dgejdfejddgfgdZdZ dZ dZ ejj dgd d Z ejjd Zd Zd ZdZy) TestCvm_2samprr/rc tjtt5t |}t |j tjt |jtjdddy#1swYyxYw)NrJ) rLrMrrr rrNr!rOrPr_s r)test_too_small_inputz"TestCvm_2samp.test_too_small_input/sO\\,4I J&-C  / RVV ,K J Js AA::Bctjd}d}tjt|5t ||ddddy#1swYyxYw)Nr/z/method must be either auto, exact or asymptoticrJxyz)r!r>rLrrWr )r$r&msgs r)rz TestCvm_2samp.test_invalid_input7s: IIaL? ]]:S 1 Au -2 1 1s A  Acgd}gd}t||}ttj|tj|}t|j|j f|j|j fy)N)r-r r.r2r0)rrrrd)r r!r"rrNrPr$r%r&rrs r)test_list_inputzTestCvm_2samp.test_list_input=sX   !!Q ' !"((1+rxx{ ;bllBII.ryy0IJr+cgd}gd}t||}t|jddt|jddy)N) gffffff@g @rgffffff!@皙"@g#@g333333$@g333333%@gffffff&@)g@g@g@@333333@gffffff @g333333"@g#@g%@g&@g'@g(@g)@g*@g333333-@gS㥛?r4r5g ףp= ?rf)r rrNrPr$r%r&rs r)test_example_conoverz"TestCvm_2samp.test_example_conoverDs< =  A & U6$T2r+zstatistic, m, n, pval))ir/r0gcj`?)iir2r2gtE]t?)i@r.r0g88?)ir0r2gXwS?c2tt||||yr)rr)r$rNrrpvals r)test_exact_pvaluezTestCvm_2samp.test_exact_pvalueNs *9a;TBr+ctjjdtjj d}tjj d}t ||}td|jcxkxrdknct ||dz}td|jcxkxr dkycy)Nirr=i rrr) r!r<r=r rrr rrPrs r)test_large_samplezTestCvm_2samp.test_large_sampleYs t    " " " 0    " " " / A &AHH q ! AcE *AHH q ! !r+cztjjdtjjd}tjjd}t ||d}t ||d}t |j |j t|j|jdy) Nrr2r3rrrrfr5) r!r<r=rr rrNrrPrs r)test_exact_vs_asymptoticz&TestCvm_2samp.test_exact_vs_asymptoticesx q IINN1  IINN1  !!Qw 7 !!Q| <R\\2<<0 29948r+cPtjd}gd}t||d}t||d}t|j|jtjd}t||d}t||d}t|j|jy)Nr[)rhg@g333333*@rrrrr)r!r>r rrPrs r)test_method_autozTestCvm_2samp.test_method_autons} IIbM  !!Qw 7 !!Qv 6RYY * IIbM !!Q| < !!Qv 6RYY *r+ctjd}t||}t|j|j fdt|dd|dd}t|j|j fdy)Nrrjr.)r!r>r rrNrPrs r)test_same_inputzTestCvm_2samp.test_same_inputzsc IIbM"1a(cmmSZZ0*="1Ra5!BQ%0cmmSZZ0*=r+N)r^r_r`rLrrr!r>rrrrrxslowrr r rrar+r)rr.s [[Vr9299Q<&8'0ryy|aS&9&;<-<- . K3 [[456 C 6 C  [[ " "9 + >r+rceZdZgdgdgdfZgdgdgdfZgdgdgdfZdZdZd Ze jjd eed feed feed ffgd dZ dZ dZe jjd ee dfeedffddgdZdZdZdZdZdZdZe jjdddZe jjd gd!d"Zd#Zy$)% TestTukeyHSD)r)7@ffffff:@皙;@fffff=@)ffffff<@皙A@=@皙@@皙>@)g:@gL<@gL8@g333333:@g;@)r)rgHzG:@rrrrr)r)rr) rrrrrrrrrraK 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 zdata,res_expect_str,atolrig|=)equal size samplezunequal sample sizezextreme sample size differences)idsc"tj|jddjddtj d}t j|}|j}|D]\}}} } } } t|dz t|dz }}t|j||f| |t|j||f| |t|j||f| |t|j||fd k| dk(y) 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/Ndtype)r0r0rr5rgr!asarrayreplacesplitfloatrrA tukey_hsdconfidence_intervalintrlowrNhighrP) r$datares_expect_strr6 res_expect res_tukeyconfr jlrhsigs r)test_compare_saszTestTukeyHSD.test_compare_sassBZZ 6 6uc B H H J12 N&+--4WV_ OOT* ,,.", Aq!Q3q6A:s1vzqA DHHQTNAD 9 I//15qt D DIIadOQT : Y--ad3s:SAX F #-r+z 1 2 -8.2491590248597 -4.6 -0.9508409751403 0.0144483269098 1 3 -3.9091590248597 -0.26 3.3891590248597 0.9803107240900 2 3 0.6908409751403 4.34 7.9891590248597 0.0203311368795 z 1 2 -7.02207069748501 -3.645 -0.26792930251500 0.03371498443080 1 3 -2.68207069748500 0.695 4.07207069748500 0.85572267328807 2 3 0.59347644287720 4.34 8.08652355712281 0.02259047020620 r+rrzunequal size samplectj|jtj d}t j |}|j}|D]\}}} } } } t|dz t|dz }}t|j||f| |t|j||f| |t|j||f| |t|j||f| |y)an vals = [24.5, 23.5, 26.4, 27.1, 29.9, 28.4, 34.2, 29.5, 32.2, 30.1, 26.1, 28.3, 24.3, 26.2, 27.8] names = {'zero', 'zero', 'zero', 'zero', 'zero', 'one', 'one', 'one', 'one', 'one', 'two', 'two', 'two', 'two', 'two'} [p,t,stats] = anova1(vals,names,"off"); [c,m,h,nms] = multcompare(stats, "CType","hsd"); r r r0rr5N)r!r#r%r&rrAr'r(r)rr*rNr+rP) r$r,r-r6r.r/r0r r1r2rr3r(s r)test_compare_matlabz TestTukeyHSD.test_compare_matlabsZZ 4 4 6&+--4WV_ OOT* ,,. * Aq!Q1q6A:s1vzqA DHHQTNAD 9 I//15qt D DIIadOQT : I,,QT2AD A !+r+c4d}tj|jddjddtj d}gdgd gd f}t j|}|j}|D]\}}}} } } t|d z t|d z }}t|j||f| d t|j||f|d t|j||f| d t|j||f| d y)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) $tension z diff lwr upr p adj 2 - 3 4.722222 -4.8376022 14.28205 0.4630831 1 - 3 14.722222 5.1623978 24.28205 0.0014315 1 - 2 10.000000 0.4401756 19.55982 0.0384598 rrr/Nr r7)r:6rbF43r:Cryrcr@)r[,)rdrr@rerrdr/r:$*r:rArrr;rrr@)rErrrdr1rr;rr:r[rrrerrrrr;rrr5rgh㈵>r") r$str_resr.r,r/r0r r1rr2r3r(s r)test_compare_rzTestTukeyHSD.test_compare_rs  ZZs ; A A CAB G&+--4WV_ 555 6OOT* ,,. * Aq!Q1q6A:s1vzqA DHHQTNAD 9 I//15qt D DIIadOQT : I,,QT2AD A !+r+cgd}gd}gd}gd}tj||||}|j}tjgdgdgdgdg}tjgd gd gd gdg}d D]I\} } t |j | | f|| | fd t |j| | f|| | fd Ky)zp Example sourced from: https://www.itl.nist.gov/div898/handbook/prc/section4/prc471.htm )皙@g@333333@gffffff@g@)g @rg333333@gffffff"@r)g @g%@g333333 @rJr)rKgffffff@gffffff@gffffff@g@)rrrg)g(\?rgq= ףpgp= ף?)gGz?rrg ףp= ?)rrrr)rrrgzG?)gzG@rg?g= ףp=@)g= ףp=@rrg@)rr)r-r)rr rrrrfr5N)rAr'r(r!r#rr*r+) r$group1group2group3group4rRr0lowerupperr r1s r)test_engineering_stat_handbookz+TestTukeyHSD.test_engineering_stat_handbook-s +*+*ooffff=&&(       !    ?FQ DHHQTNE!Q$Kd C DIIadOU1a4[t D?r+cBtjjdtjjdd}t j |}|j }t|j|jj ttj|j|jdttj|j|jdt|j|jj ttj|jdt|j|jjttj|jdy)Nr9r r|rrrr)r!r<r=rrAr'r(rr*r+rxdiagonalrNrP)r$r,rRr0s r)test_rand_symmzTestTukeyHSD.test_rand_symmGs tyy~~a%oot$&&(TXX |, R[[+TYYt_=R[[*DHHTN;S]]S]]__$45R[[/3SZZ.R[[,a0r+cttd5tjgddtj ggddddy#1swYyxYw)Nz...must be finite.rJrr-)r0r2r )rVrWrAr'r!rUrks r) test_no_infzTestTukeyHSD.test_no_infZs2 :-A B OOI266{I >C B Bs ,AActtd5tjddgddggddggddddy#1swYyxYw)Nz...must be one-dimensionalrJrr-r r/)r/rr0rVrWrAr'rks r) test_is_1dzTestTukeyHSD.test_is_1d^s; :-I J OOaVaV,q!fj AK J Js "=Acttd5tjgddggddddy#1swYyxYw)Nz...must be greater than onerJr-r/)r.r/r0r[rks r) test_no_emptyzTestTukeyHSD.test_no_emptybs. :-J K OOBA 2L K Ks 7Anargsrcttd5tjgdg|zdddy#1swYyxYw)Nz...more than 1 treatment.rJrr2r r[)r$r_s r)test_not_enough_treatmentsz'TestTukeyHSD.test_not_enough_treatmentsfs- :-H I OOzlU2 4J I Is4=cl)rmrrr-cttd5tjgdddgddg}|j |dddy#1swYyxYw)Nzmust be between 0 and 1rJrar r.r)rVrWrAr'r()r$rcrs r)test_conf_level_invalidz$TestTukeyHSD.test_conf_level_invalidksB :-F G QFQF;A ! !" %H G Gs /A  Ac tj|jdd}tj|jdd}t |j |j dt |j |j dy)Nr-rrL)rAr'data_diff_size ttest_indrrP)r$r/ res_ttests r)test_2_args_ttestzTestTukeyHSD.test_2_args_ttestqsnOOT%8%8!%<= OOT%8%8!%<=  (()*:*:4*@A (()*:*:4*@Ar+N)r^r_r`data_same_sizerg extreme_size sas_same_size sas_diff_size sas_extremerLrrr5 matlab_sm_sizmatlab_diff_szr8rHrSrWrYr\r^rbrerjrar+r)rrsy4446NH446N'24L MMK [[7-}dC-}dC+[%@ "E F#GF#GJ M  N  [[7-}eD-~tDF"5"7"9: B : B*'BRE41&?B3 [[Wf-5.5 [[T>2&3& Br+rc eZdZejj dgdgdfdZejj dgdgdgdgd gd gd gd gd fdZdZdZ dZ y)TestPoissonMeansTestzc1, n1, c2, n2, p_expect)rr|r r|gea?)r-r|r0r|g c?cdtj||||}t|j|dy)Nrir5rApoisson_means_testrrP)r$c1n1c2n2p_expectrRs r)test_paper_examplesz(TestPoissonMeansTest.test_paper_exampleszs* &&r2r26 H48r+z c1, n1, c2, n2, p_expect, alt, d)r[r1r[r1g{}?rr)r1r1r1r1goPF?rr)2rrrgae?rrg)r r|r[rg/V-=?rr)r rr.r[g")?rr)r.r[r r|g_'Qm~?rr)r.r[r r1g|?rr)rrr}rg 0ݷ?rrcltj||||||}t|j|ddy)N)rdiffg>gؗҜ<r6r9ru) r$rwrxryrzr{altdrRs r)test_fortran_authorsz)TestPoissonMeansTest.test_fortran_authorss0$&&r2r23QO H4eDr+ctd\}}d\}}tj||||}t|jdy)N)r}r}rrur$count1count2nobs1nobs2rRs r)test_different_resultsz+TestPoissonMeansTest.test_different_resultss:&# u&&vufeD A&r+ctd\}}d\}}tj||||}t|jdy)NrUrrrurs r)test_less_than_zero_lambda_hat2z4TestPoissonMeansTest.test_less_than_zero_lambda_hat2s: u&&vufeD A&r+cd\}}d\}}d}tt|5tjd|||dddtt|5tj||d|dddd}tt|5tjd|||dddtt|5tj||d|dddd}tt|5tj|d||dddtt|5tj|||ddddd }tt|5tj||||d dddd }tt|5tjd d d d ddddy#1swYuxYw#1swYPxYw#1swY)xYw#1swYxYw#1swYxYw#1swYxYw#1swYxYw#1swYyxYw)NrUrz`k1` and `k2` must be integers.rJrz1`k1` and `k2` must be greater than or equal to 0.rz%`n1` and `n2` must be greater than 0.z(diff must be greater than or equal to 0.)rzAlternative must be one of ...rr-errorr)rV TypeErrorrArvrW)r$rrrrrs r)rz*TestPoissonMeansTest.test_input_validations u4 9G 4  $ $R >5 9G 4  $ $VUB >5F :W 5  $ $R >6 :W 5  $ $VUB >6: :W 5  $ $VR ?6 :W 5  $ $VUFB ?6= :W 5  $ $VUFE K63 :W 5  $ $Q1aW E6 555 4 4 4 6 5 5 5 6 5 5 5 6 5 6 5s_F*F7G6G*GG*G6H*F47GGGG'*G36G?H N) r^r_r`rLrrr|rrrrrar+r)rsrsys [[7  : 9  9 [[? =<=>9; 66B"E#"E''!Fr+rsceZdZdZdZej jdgddZej jdgddZ dZ d Z y ) TestBWSTestcltjjd}|jd\}}d}tjt |5t j||g||gdddd}tjt |5t jtjg|dddd}tjt |5t j|gdddd}tjt |5t j||d dddd }tjt |5t j||d dddy#1swYxYw#1swYxYw#1swYxYw#1swYmxYw#1swYyxYw)N " &nnQ{; u48SZZ)r+)rrNrP))rg -?g4B/?)r -g0&v?)rrg(?ctjjd}|jd\}}tj|||}t |j |dt |j|dd y) Nrrr=rvIh%<=r8rfrrr!r<r?rArrrNrPr$rrNrPrDr%r&rRs r)test_against_RzTestBWSTest.test_against_Rsaii##$78zzvz&1nnQ{; yu= FDAr+))rgD5H?gdԕ?)r`ч?gȲךX?)rrg4)?ctjjd}|jd}|jd}tj|||}t |j |dt |j|dd y) Nl.sZrr=r3rrr8rfrrrrs r)test_against_R_imbalancedz%TestBWSTest.test_against_R_imbalancedsmii##$78 JJAJ  JJAJ nnQ{; yu= FDAr+c tjjd}|jd\}}tjjd}tjd|}tj |||}t |jdk(sJtjjd}tjd|}tj |||}t|j|jtjjd}tjd|}tj |||}tj|j|jrJy)N/HN()r-r1r=r1) n_resamples random_staterlVC A) r!r<r?rArHrrnull_distributionrallclose)r$rDr%r&rrrr's r) test_methodzTestBWSTest.test_methods(ii##$78zzwz'1ii##$78((RcJ~~a624))*b000ii##$78((RcJ~~a62..0F0FGii##$78((RcJ~~a62;;t55t7M7MNNNNr+ctjjd}|jd}|dz }tj||d}|j dkDsJt |jdt|jz tj||d}|j dkDsJt |jdtj||d}|j dksJt |jdt|jz tj||d}|j dksJt |jdy) Nrr/r=rrrrr) r!r<r?rArrNrrPrr)r$rDr%r&rRs r)test_directionszTestBWSTest.test_directions-sii##$78 JJAJ  EnnQy9}}q   SZZS)>)>%?!?@nnQv6}}q   SZZ#nnQv6}}q   SZZS)>)>%?!?@nnQy9}}q   SZZ#r+N) r^r_r`rrrLrrrrrrrar+r)rrsw,4* [[CNO B O B [[CNO B O BO.$r+r)- itertoolsrnumpyr!r<rWrL numpy.testingrrrrrrV scipy.statsrAr scipy.stats._hypotestsr r r r rrrscipy.stats._mannwhitneyurr common_testsrscipy._lib._testutilsrscipy.stats._axis_nan_policyrrrrcrrQrrrrrsrrar+r)rs  00*%444?-2R4-4-nZKZKzg=g=Tj<"jU>ppBpBfQFQFht$t$r+