def quantiles(self, *quantiles):
"""Return the estimated data value for the given quantile(s).
The requested quantile(s) must be between 0 and 1. Note that even if a
single quantile is input, a list is always returned.
"""
temp = bin_sums(self.bins)
sums = list(accumulate(temp))
result = []
for x in quantiles:
target_sum = x * self.total
if x <= 0:
qq = self._min
elif x >= self.total:
qq = self._max
else:
index = bisect_left(sums, target_sum)
bin_i = self.bins[index]
if index < len(sums):
bin_i1 = self.bins[index+1]
else:
bin_i1 = self.bins[index]
if index:
prev_sum = sums[index-1]
else:
prev_sum = 0.0
qq = _compute_quantile(target_sum, bin_i, bin_i1, prev_sum+1)
result.append(qq)
return result
def quantiles(self, *quantiles):
"""Return the estimated data value for the given quantile(s).
The requested quantile(s) must be between 0 and 1. Note that even if a
single quantile is input, a list is always returned.
"""
temp = bin_sums(self.bins)
sums = list(accumulate(temp))
result = []
for x in quantiles:
target_sum = x * self.total
if x <= 0:
qq = self._min
elif x >= self.total:
qq = self._max
else:
index = bisect_left(sums, target_sum)
bin_i = self.bins[index]
if index < len(sums):
bin_i1 = self.bins[index + 1]
else:
bin_i1 = self.bins[index]
if index:
prev_sum = sums[index - 1]
else:
prev_sum = 0.0
qq = _compute_quantile(target_sum, bin_i, bin_i1, prev_sum + 1)
result.append(qq)
return result
def sum(self, x):
"""Return the estimated number of points in the interval [−∞, b]."""
x = float(x)
if x < self._min:
ss = 0.0 # Sum is zero!
elif x >= self._max:
ss = float(self.total)
elif x == self.bins[-1].value:
# Shortcut for when i == max bin (see Steps 3-6)
last = self.bins[-1]
ss = float(self.total) - (float(last.count) / 2.0)
# elif x <= self.bins[0].value:
# # Shortcut for when i == min bin (see Steps 3-6)
# first = self.bins[0]
# ss = float(first.count) / 2.0
else:
bin_i = self.floor(x)
if bin_i is None:
bin_i = Bin(value=self._min, count=0)
bin_i1 = self.higher(x)
if bin_i1 is None:
bin_i1 = Bin(value=self._max, count=0)
if bin_i.value == self._min:
prev_sum = self.bins[0].count / 2.0
else:
temp = bin_sums(self.bins, less=x)
if len(temp):
prev_sum = sum(temp)
else:
prev_sum = 0.0
ss = _compute_sum(x, bin_i, bin_i1, prev_sum)
return ss
def sum(self, x):
"""Return the estimated number of points in the interval [−∞, b]."""
x = float(x)
if x < self._min:
ss = 0.0 # Sum is zero!
elif x >= self._max:
ss = float(self.total)
elif x == self.bins[-1].value:
# Shortcut for when i == max bin (see Steps 3-6)
last = self.bins[-1]
ss = float(self.total) - (float(last.count) / 2.0)
# elif x <= self.bins[0].value:
# # Shortcut for when i == min bin (see Steps 3-6)
# first = self.bins[0]
# ss = float(first.count) / 2.0
else:
bin_i = self.floor(x)
if bin_i is None:
bin_i = Bin(value=self._min, count=0)
bin_i1 = self.higher(x)
if bin_i1 is None:
bin_i1 = Bin(value=self._max, count=0)
if bin_i.value == self._min:
prev_sum = self.bins[0].count / 2.0
else:
temp = bin_sums(self.bins, less=x)
if len(temp):
prev_sum = sum(temp)
else:
prev_sum = 0.0
ss = _compute_sum(x, bin_i, bin_i1, prev_sum)
return ss
