annotate ngsutils/support/stats.py @ 2:7a68005de299 draft

planemo upload for repository https://github.com/galaxyproject/tools-iuc/tree/master/tools/ngsutils commit 9a243c616a4a3156347e38fdb5f35863ae5133f9
author iuc
date Sun, 27 Nov 2016 15:01:21 -0500
parents 4e4e4093d65d
children
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4e4e4093d65d planemo upload for repository https://github.com/galaxyproject/tools-iuc/tree/master/tools/ngsutils commit 09194687c74a424732f8b0c017cbb942aad89068
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1 '''
4e4e4093d65d planemo upload for repository https://github.com/galaxyproject/tools-iuc/tree/master/tools/ngsutils commit 09194687c74a424732f8b0c017cbb942aad89068
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2 various statistical tests and methods...
4e4e4093d65d planemo upload for repository https://github.com/galaxyproject/tools-iuc/tree/master/tools/ngsutils commit 09194687c74a424732f8b0c017cbb942aad89068
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3 '''
4e4e4093d65d planemo upload for repository https://github.com/galaxyproject/tools-iuc/tree/master/tools/ngsutils commit 09194687c74a424732f8b0c017cbb942aad89068
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4 import math
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4e4e4093d65d planemo upload for repository https://github.com/galaxyproject/tools-iuc/tree/master/tools/ngsutils commit 09194687c74a424732f8b0c017cbb942aad89068
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6 from ngsutils.support import memoize
4e4e4093d65d planemo upload for repository https://github.com/galaxyproject/tools-iuc/tree/master/tools/ngsutils commit 09194687c74a424732f8b0c017cbb942aad89068
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7
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9 def median(vals):
4e4e4093d65d planemo upload for repository https://github.com/galaxyproject/tools-iuc/tree/master/tools/ngsutils commit 09194687c74a424732f8b0c017cbb942aad89068
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10 '''
4e4e4093d65d planemo upload for repository https://github.com/galaxyproject/tools-iuc/tree/master/tools/ngsutils commit 09194687c74a424732f8b0c017cbb942aad89068
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11 >>> median([1,2,3])
4e4e4093d65d planemo upload for repository https://github.com/galaxyproject/tools-iuc/tree/master/tools/ngsutils commit 09194687c74a424732f8b0c017cbb942aad89068
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12 2
4e4e4093d65d planemo upload for repository https://github.com/galaxyproject/tools-iuc/tree/master/tools/ngsutils commit 09194687c74a424732f8b0c017cbb942aad89068
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13 >>> median([1,2,3,4])
4e4e4093d65d planemo upload for repository https://github.com/galaxyproject/tools-iuc/tree/master/tools/ngsutils commit 09194687c74a424732f8b0c017cbb942aad89068
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14 2.5
4e4e4093d65d planemo upload for repository https://github.com/galaxyproject/tools-iuc/tree/master/tools/ngsutils commit 09194687c74a424732f8b0c017cbb942aad89068
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15 '''
4e4e4093d65d planemo upload for repository https://github.com/galaxyproject/tools-iuc/tree/master/tools/ngsutils commit 09194687c74a424732f8b0c017cbb942aad89068
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16 vals.sort()
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18 if len(vals) % 2 == 1:
4e4e4093d65d planemo upload for repository https://github.com/galaxyproject/tools-iuc/tree/master/tools/ngsutils commit 09194687c74a424732f8b0c017cbb942aad89068
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19 return vals[len(vals) / 2]
4e4e4093d65d planemo upload for repository https://github.com/galaxyproject/tools-iuc/tree/master/tools/ngsutils commit 09194687c74a424732f8b0c017cbb942aad89068
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20 else:
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21 a = vals[(len(vals) / 2) - 1]
4e4e4093d65d planemo upload for repository https://github.com/galaxyproject/tools-iuc/tree/master/tools/ngsutils commit 09194687c74a424732f8b0c017cbb942aad89068
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22 b = vals[(len(vals) / 2)]
4e4e4093d65d planemo upload for repository https://github.com/galaxyproject/tools-iuc/tree/master/tools/ngsutils commit 09194687c74a424732f8b0c017cbb942aad89068
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23 return float(a + b) / 2
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25
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26 def mean_stdev(l):
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27 '''
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28 >>> mean_stdev([1,2,2,2])
4e4e4093d65d planemo upload for repository https://github.com/galaxyproject/tools-iuc/tree/master/tools/ngsutils commit 09194687c74a424732f8b0c017cbb942aad89068
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29 (1.75, 0.5)
4e4e4093d65d planemo upload for repository https://github.com/galaxyproject/tools-iuc/tree/master/tools/ngsutils commit 09194687c74a424732f8b0c017cbb942aad89068
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30 >>> mean_stdev([2,2,2,2])
4e4e4093d65d planemo upload for repository https://github.com/galaxyproject/tools-iuc/tree/master/tools/ngsutils commit 09194687c74a424732f8b0c017cbb942aad89068
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31 (2.0, 0.0)
4e4e4093d65d planemo upload for repository https://github.com/galaxyproject/tools-iuc/tree/master/tools/ngsutils commit 09194687c74a424732f8b0c017cbb942aad89068
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32 '''
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33
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34 acc = 0
4e4e4093d65d planemo upload for repository https://github.com/galaxyproject/tools-iuc/tree/master/tools/ngsutils commit 09194687c74a424732f8b0c017cbb942aad89068
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35 for el in l:
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36 acc += el
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37
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38 mean = float(acc) / len(l)
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39 acc = 0
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40 for el in l:
4e4e4093d65d planemo upload for repository https://github.com/galaxyproject/tools-iuc/tree/master/tools/ngsutils commit 09194687c74a424732f8b0c017cbb942aad89068
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41 acc += (el - mean) ** 2
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42
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43 if len(l) > 2:
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44 stdev = math.sqrt(float(acc) / (len(l) - 1))
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45 else:
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46 stdev = 0.0
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47
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48 return (mean, stdev)
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49
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50
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51 def counts_median(d):
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52 '''
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53 Calculate the median from counts stored in a dictionary
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54 >>> counts_median({ 1: 4, 2: 1, 3: 4 })
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55 2
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56 >>> counts_median({ 1: 4, 3: 4 })
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57 2
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58
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59 '''
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60 count = 0
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61 for k in d:
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62 count += d[k]
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63
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64 if count == 0:
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65 return 0
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66
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67 acc = 0.0
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68 last = 0
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69 for k in sorted(d):
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70 if last:
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71 return (last + k) / 2
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72 acc += d[k]
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73 if acc / count == 0.5:
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74 last = k
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75 elif acc / count > 0.5:
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76 return k
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77
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78
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79 def counts_mean_stdev(d):
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80 '''
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81
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82 calc mean / stdev when data is stored as counts in a dictionary
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83
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84 Ex:
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85 { 1: 4, 2: 1, 3: 4 } = [1, 1, 1, 1, 2, 3, 3, 3, 3]
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86
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87 >>> counts_mean_stdev({ 1: 4, 2: 1, 3: 4 })
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88 (2.0, 1.0)
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89
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90 '''
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91
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92 acc = 0
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93 count = 0
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94 for k in d:
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95 acc += k * d[k]
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96 count += d[k]
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97
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98 mean = float(acc) / count
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99
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100 acc = 0
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101 for k in d:
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102 acc += (((k - mean) ** 2) * d[k])
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103
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104 if count > 2:
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105 stdev = math.sqrt(float(acc) / (count - 1))
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106 else:
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107 stdev = 0.0
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108
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109 return (mean, stdev)
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110
2
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111
0
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112 @memoize
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113 def poisson_prob(x, mean):
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114 '''
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115 Return the probability that you could get x counts in
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116 a Poisson test with a mean value.
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117
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118 prob(x) = sum(i=1..x){poisson(i)}
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119
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120 >>> poisson_prob(6,10)
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121 0.1300960209527205
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122 >>> poisson_prob(8,10)
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123 0.33277427882095645
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124 '''
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125 acc = 0.0
2
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126 for i in xrange(1, x + 1):
0
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127 acc += poisson_func(i, mean)
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128 return acc
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129
2
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130
0
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131 @memoize
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132 def poisson_func(mu, lambd):
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133 '''
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134 This is the Poisson distribution function
2
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135
0
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136 p(mu) = (lambda^mu * e^(-lambda)) / (mu!)
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137
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138 mu is a count
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139 lambd is the mean
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140
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141 >>> poisson_func(1,10)
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142 0.00045399929762484856
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143 >>> poisson_func(2,10)
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144 0.0022699964881242427
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145 >>> poisson_func(3,10)
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146 0.007566654960414142
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147 '''
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148 return (lambd ** mu) * (math.exp(-1 * lambd)) / _factorial(mu)
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149
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150
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151 @memoize
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152 def _factorial(x):
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153 '''
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154 >>> _factorial(1)
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155 1
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156 >>> _factorial(2)
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157 2
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158 >>> _factorial(3)
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159 6
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160 '''
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161 return math.factorial(x)
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162
2
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163
0
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164 if __name__ == '__main__':
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165 import doctest
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166 doctest.testmod()