Lines Matching full:start
42 start = 0
45 while (start < ftime):
47 results = [ts.get_value(start, end) for ts in series]
49 start += ctx.interval
54 start = 0
57 while (start < ftime):
59 results = [ts.get_value(start, end) for ts in series]
61 start += ctx.interval
66 start = 0
69 while (start < ftime):
71 results = [ts.get_value(start, end) for ts in series]
73 start += ctx.interval
93 start = 0
95 print('start-time, samples, min, avg, median, 90%, 95%, 99%, max')
96 while (start < ftime): # for each time interval
98 sample_arrays = [ s.get_samples(start, end) for s in series ]
114 start, len(samplevalues),
118 start += ctx.interval
136 start = 0
141 while (start < ftime):
143 results = [ts.get_value(start, end) for ts in series]
145 weights.append(end-start)
146 start += ctx.interval
169 def add_sample(self, start, end, value): argument
170 sample = Sample(ctx, start, end, value)
175 def get_samples(self, start, end): argument
178 if s.start >= start and s.end <= end:
182 def get_value(self, start, end): argument
185 value += sample.get_contribution(start, end)
189 def __init__(self, ctx, start, end, value): argument
191 self.start = start
195 def get_contribution(self, start, end): argument
197 if (end < self.start or start > self.end):
200 sbound = self.start if start < self.start else start
202 ratio = float(ebound-sbound) / (end-start)