ó £áSc@`s¿dZddlmZmZmZddddddd d d d d ddddddddddddgZeZddlj j Z ddl Z ddd„Zd„Zgd„Z gd„Zdgd„Zd gd!„Zd"„Zgd#„Zgd$„Zgd%„Zgd&„Zgd'„Zgd(„Zgd)„Zgd*„Zgd+„Zgd,„Zgd-„Zgd.„Z gd/„Z!gd0„Z"gd1„Z#d2„Z$e%d3kr»e$ƒndS(4s,Backward compatible module for RandomArray i(tdivisiontabsolute_importtprint_functiont ArgumentErrortFtbetatbinomialt chi_squaret exponentialtgammatget_seedt mean_var_testt multinomialtmultivariate_normaltnegative_binomialt noncentral_Ftnoncentral_chi_squaretnormalt permutationtpoissontrandinttrandomtrandom_integerstseedtstandard_normaltuniformNcC`s<|dks|dkr%tjƒntj||fƒdS(Ni(tmtR(txty((sW/opt/xtal/ccp4-6.5-linux32/lib/python2.7/site-packages/numpy/oldnumeric/random_array.pyRs cC`stdƒ‚dS(NsšIf you want to save the state of the random number generator. Then you should use obj = numpy.random.get_state() followed by. numpy.random.set_state(obj).(tNotImplementedError(((sW/opt/xtal/ccp4-6.5-linux32/lib/python2.7/site-packages/numpy/oldnumeric/random_array.pyR scC`s"|gkrd}ntj|ƒS(s@random(n) or random([n, m, ...]) returns array of random numbersN(tNoneRt random_sample(tshape((sW/opt/xtal/ccp4-6.5-linux32/lib/python2.7/site-packages/numpy/oldnumeric/random_array.pyRs  cC`s(|gkrd}ntj|||ƒS(scuniform(minimum, maximum, shape=[]) returns array of given shape of random reals in given rangeN(RRR(tminimumtmaximumR ((sW/opt/xtal/ccp4-6.5-linux32/lib/python2.7/site-packages/numpy/oldnumeric/random_array.pyR$s  cC`s£t|tƒstdƒ‚n|dkr9|}d}nt|tƒsWtdƒ‚n||t|ƒ}t|tjƒr‘||jtjƒS|t|ƒSdS(skrandint(min, max, shape=[]) = random integers >=min, < max If max not given, random integers >= 0, dd>gd?ƒ}t|ƒtd@tj|ddƒdAƒdS(LNisFailed seed test.sFirst random number iss"Average of 10000 random numbers isi'R:igˆÃ@i ièisrandom returned wrong shapes'Average of 100 by 100 random numbers isgà?g333333ã?suniform returned wrong shapes%uniform returned out of desired rangesrandint(1, 10, shape=[50])R i2spermutation(10)s randint(3,9)ii srandom_integers(10, shape=[20])ig@g@s$standard_normal returned wrong shapes8normally distributed numbers with mean 2 and variance %fs5random numbers exponentially distributed with mean %fis A multivariate normals(multivariate_normal returned wrong shapes-A 4x3x2 array containing multivariate normalsiœÿÿÿids<Average of 10000 multivariate normals with mean [-100,0,100]s\Estimated covariance of 10000 multivariate normals with covariance [[3,2,1],[2,2,1],[1,1,1]]g€‡Ã@g@g$@sbeta(5.,10.) random numbersgZd;ßOÕ?gyé&1¬Œ?g{®Gáz„?sgamma(.01,2.) random numbersg&@s5chi squared random numbers with 11 degrees of freedomi is1F random numbers with 5 and 10 degrees of freedomgô?gš™™™™™õ?gI@s#poisson random numbers with mean 50gìQ¸…ëÁ?sG Each element is the result of 16 binomial trials with probability 0.5:isP Each element is the result of 16 negative binomial trials with probability 0.5:sX Each row is the result of 16 multinomial trials with probabilities [0.1, 0.5, 0.1 0.3]:gš™™™™™¹?isMean = g @(i'(ièi (i'(i'(i(iiiiÈiÈi NgF]tÑEÇ?("Rt get_statet set_statetanyt SystemExitR=RR%R<R;R RR!treduceR"RRRRR RR tarraytdott transposeRR RtsqrtRRRRR (tobjtobj2RRtsRARB((sW/opt/xtal/ccp4-6.5-linux32/lib/python2.7/site-packages/numpy/oldnumeric/random_array.pyttestÊs„   &;  ; 0  ; %!9 B  Q    ##    t__main__(&t__doc__t __future__RRRt__all__t ValueErrorRtnumpy.random.mtrandRtmtrandRtnumpyR%RR RRRRRRRR RRR RRRRRRR RR RQt__name__(((sW/opt/xtal/ccp4-6.5-linux32/lib/python2.7/site-packages/numpy/oldnumeric/random_array.pytsF                      B