[bugfixing] quantile function loops inifinte for small epsilon. See docstring.
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@ -295,18 +295,44 @@ class ProbabilityDensityFunction(object):
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return self.data[find_nearest(self.axis, value)] * self.incr
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def quantile(self, prob_value, eps=0.01):
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'''
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Function can loop infinite because the pdf does not have enough resolution for small epsilon.
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example:
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pdfs[1]['P'].quantile(0.4)
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printing (l, r, m, prob_value, self.prob_lt_val(m), diff)
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(1413410073.2067008, 1413410073.3557007, 1413410073.2812009, 0.4, 0.1439571627967223, 0.2560428372032777)
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(1413410073.2812009, 1413410073.3557007, 1413410073.3184509, 0.4, 1.0029471675557042, -0.60294716755570421)
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(1413410073.2812009, 1413410073.3184509, 1413410073.2998259, 0.4, 0.95737816620865313, -0.5573781662086531)
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(1413410073.2812009, 1413410073.2998259, 1413410073.2905135, 0.4, 0.43642464167700817, -0.036424641677008152)
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(1413410073.2812009, 1413410073.2905135, 1413410073.2858572, 0.4, 0.26658460954149427, 0.13341539045850576)
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(1413410073.2858572, 1413410073.2905135, 1413410073.2881854, 0.4, 0.34109285366651082, 0.058907146333489202)
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(1413410073.2881854, 1413410073.2905135, 1413410073.2893496, 0.4, 0.38582585185826251, 0.014174148141737508)
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(1413410073.2893496, 1413410073.2905135, 1413410073.2899315, 0.4, 0.43642464167700817, -0.036424641677008152)
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(1413410073.2893496, 1413410073.2899315, 1413410073.2896404, 0.4, 0.38582585185826251, 0.014174148141737508)
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(1413410073.2896404, 1413410073.2899315, 1413410073.2897859, 0.4, 0.43642464167700817, -0.036424641677008152)
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(1413410073.2896404, 1413410073.2897859, 1413410073.2897131, 0.4, 0.43642464167700817, -0.036424641677008152)
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(1413410073.2896404, 1413410073.2897131, 1413410073.2896767, 0.4, 0.38582585185826251, 0.014174148141737508)
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(1413410073.2896767, 1413410073.2897131, 1413410073.2896948, 0.4, 0.38582585185826251, 0.014174148141737508)
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:param prob_value:
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:param eps:
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:return:
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'''
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l = self.axis[0]
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r = self.axis[-1]
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m = (r + l) / 2
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diff = prob_value - self.prob_lt_val(m)
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while abs(diff) > eps:
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print (l,r,m,prob_value,self.prob_lt_val(m),diff)
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if diff > 0:
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l = m
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else:
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r = m
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m = (r + l) / 2
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diff = prob_value - self.prob_lt_val(m)
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print(m, prob_value, self.prob_lt_val(m))
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#print(m, prob_value, self.prob_lt_val(m))
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return m
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def quantile_distance(self, prob_value):
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