_distr_params.py 4.4 KB

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  1. """
  2. Sane parameters for stats.distributions.
  3. """
  4. distcont = [
  5. ['alpha', (3.5704770516650459,)],
  6. ['anglit', ()],
  7. ['arcsine', ()],
  8. ['argus', (1.0,)],
  9. ['beta', (2.3098496451481823, 0.62687954300963677)],
  10. ['betaprime', (5, 6)],
  11. ['bradford', (0.29891359763170633,)],
  12. ['burr', (10.5, 4.3)],
  13. ['burr12', (10, 4)],
  14. ['cauchy', ()],
  15. ['chi', (78,)],
  16. ['chi2', (55,)],
  17. ['cosine', ()],
  18. ['crystalball', (2.0, 3.0)],
  19. ['dgamma', (1.1023326088288166,)],
  20. ['dweibull', (2.0685080649914673,)],
  21. ['erlang', (10,)],
  22. ['expon', ()],
  23. ['exponnorm', (1.5,)],
  24. ['exponpow', (2.697119160358469,)],
  25. ['exponweib', (2.8923945291034436, 1.9505288745913174)],
  26. ['f', (29, 18)],
  27. ['fatiguelife', (29,)], # correction numargs = 1
  28. ['fisk', (3.0857548622253179,)],
  29. ['foldcauchy', (4.7164673455831894,)],
  30. ['foldnorm', (1.9521253373555869,)],
  31. ['frechet_l', (3.6279911255583239,)],
  32. ['frechet_r', (1.8928171603534227,)],
  33. ['gamma', (1.9932305483800778,)],
  34. ['gausshyper', (13.763771604130699, 3.1189636648681431,
  35. 2.5145980350183019, 5.1811649903971615)], # veryslow
  36. ['genexpon', (9.1325976465418908, 16.231956600590632, 3.2819552690843983)],
  37. ['genextreme', (-0.1,)],
  38. ['gengamma', (4.4162385429431925, 3.1193091679242761)],
  39. ['gengamma', (4.4162385429431925, -3.1193091679242761)],
  40. ['genhalflogistic', (0.77274727809929322,)],
  41. ['genlogistic', (0.41192440799679475,)],
  42. ['gennorm', (1.2988442399460265,)],
  43. ['halfgennorm', (0.6748054997000371,)],
  44. ['genpareto', (0.1,)], # use case with finite moments
  45. ['gilbrat', ()],
  46. ['gompertz', (0.94743713075105251,)],
  47. ['gumbel_l', ()],
  48. ['gumbel_r', ()],
  49. ['halfcauchy', ()],
  50. ['halflogistic', ()],
  51. ['halfnorm', ()],
  52. ['hypsecant', ()],
  53. ['invgamma', (4.0668996136993067,)],
  54. ['invgauss', (0.14546264555347513,)],
  55. ['invweibull', (10.58,)],
  56. ['johnsonsb', (4.3172675099141058, 3.1837781130785063)],
  57. ['johnsonsu', (2.554395574161155, 2.2482281679651965)],
  58. ['kappa4', (0.0, 0.0)],
  59. ['kappa4', (-0.1, 0.1)],
  60. ['kappa4', (0.0, 0.1)],
  61. ['kappa4', (0.1, 0.0)],
  62. ['kappa3', (1.0,)],
  63. ['ksone', (1000,)], # replace 22 by 100 to avoid failing range, ticket 956
  64. ['kstwobign', ()],
  65. ['laplace', ()],
  66. ['levy', ()],
  67. ['levy_l', ()],
  68. ['levy_stable', (1.8, -0.5)],
  69. ['loggamma', (0.41411931826052117,)],
  70. ['logistic', ()],
  71. ['loglaplace', (3.2505926592051435,)],
  72. ['lognorm', (0.95368226960575331,)],
  73. ['lomax', (1.8771398388773268,)],
  74. ['maxwell', ()],
  75. ['mielke', (10.4, 3.6)],
  76. ['moyal', ()],
  77. ['nakagami', (4.9673794866666237,)],
  78. ['ncf', (27, 27, 0.41578441799226107)],
  79. ['nct', (14, 0.24045031331198066)],
  80. ['ncx2', (21, 1.0560465975116415)],
  81. ['norm', ()],
  82. ['norminvgauss', (1., 0.5)],
  83. ['pareto', (2.621716532144454,)],
  84. ['pearson3', (0.1,)],
  85. ['powerlaw', (1.6591133289905851,)],
  86. ['powerlognorm', (2.1413923530064087, 0.44639540782048337)],
  87. ['powernorm', (4.4453652254590779,)],
  88. ['rayleigh', ()],
  89. ['rdist', (0.9,)], # feels also slow
  90. ['recipinvgauss', (0.63004267809369119,)],
  91. ['reciprocal', (0.0062309367010521255, 1.0062309367010522)],
  92. ['rice', (0.7749725210111873,)],
  93. ['semicircular', ()],
  94. ['skewnorm', (4.0,)],
  95. ['t', (2.7433514990818093,)],
  96. ['trapz', (0.2, 0.8)],
  97. ['triang', (0.15785029824528218,)],
  98. ['truncexpon', (4.6907725456810478,)],
  99. ['truncnorm', (-1.0978730080013919, 2.7306754109031979)],
  100. ['truncnorm', (0.1, 2.)],
  101. ['tukeylambda', (3.1321477856738267,)],
  102. ['uniform', ()],
  103. ['vonmises', (3.9939042581071398,)],
  104. ['vonmises_line', (3.9939042581071398,)],
  105. ['wald', ()],
  106. ['weibull_max', (2.8687961709100187,)],
  107. ['weibull_min', (1.7866166930421596,)],
  108. ['wrapcauchy', (0.031071279018614728,)]]
  109. distdiscrete = [
  110. ['bernoulli',(0.3,)],
  111. ['binom', (5, 0.4)],
  112. ['boltzmann',(1.4, 19)],
  113. ['dlaplace', (0.8,)], # 0.5
  114. ['geom', (0.5,)],
  115. ['hypergeom',(30, 12, 6)],
  116. ['hypergeom',(21,3,12)], # numpy.random (3,18,12) numpy ticket:921
  117. ['hypergeom',(21,18,11)], # numpy.random (18,3,11) numpy ticket:921
  118. ['logser', (0.6,)], # re-enabled, numpy ticket:921
  119. ['nbinom', (5, 0.5)],
  120. ['nbinom', (0.4, 0.4)], # from tickets: 583
  121. ['planck', (0.51,)], # 4.1
  122. ['poisson', (0.6,)],
  123. ['randint', (7, 31)],
  124. ['skellam', (15, 8)],
  125. ['zipf', (6.5,)],
  126. ['yulesimon',(11.0,)]
  127. ]