old_contents: #!/usr/bin/env python2.7
  #
  # Copyright 2017 gRPC authors.
  #
  # Licensed under the Apache License, Version 2.0 (the "License");
  # you may not use this file except in compliance with the License.
  # You may obtain a copy of the License at
  #
  #     http://www.apache.org/licenses/LICENSE-2.0
  #
  # Unless required by applicable law or agreed to in writing, software
  # distributed under the License is distributed on an "AS IS" BASIS,
  # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
  # See the License for the specific language governing permissions and
  # limitations under the License.
  
  from scipy import stats
  import math
  
  
  def scale(a, mul):
    return [x * mul for x in a]
  
  
  def cmp(a, b):
    return stats.ttest_ind(a, b)
  
  
  def speedup(new, old, threshold):
    if (len(set(new))) == 1 and new == old: return 0
    s0, p0 = cmp(new, old)
    if math.isnan(p0): return 0
    if s0 == 0: return 0
    if p0 > threshold: return 0
    if s0 < 0:
      pct = 1
      while pct < 100:
        sp, pp = cmp(new, scale(old, 1 - pct / 100.0))
        if sp > 0: break
        if pp > threshold: break
        pct += 1
      return -(pct - 1)
    else:
      pct = 1
      while pct < 10000:
        sp, pp = cmp(new, scale(old, 1 + pct / 100.0))
        if sp < 0: break
        if pp > threshold: break
        pct += 1
      return pct - 1
  
  
  if __name__ == "__main__":
    new = [0.0, 0.0, 0.0, 0.0] 
    old=[2.96608e-06, 3.35076e-06, 3.45384e-06, 3.34407e-06]
    print speedup(new, old, 1e-5)
    print speedup(old, new, 1e-5)
  
new_contents: #!/usr/bin/env python2.7
  #
  # Copyright 2017 gRPC authors.
  #
  # Licensed under the Apache License, Version 2.0 (the "License");
  # you may not use this file except in compliance with the License.
  # You may obtain a copy of the License at
  #
  #     http://www.apache.org/licenses/LICENSE-2.0
  #
  # Unless required by applicable law or agreed to in writing, software
  # distributed under the License is distributed on an "AS IS" BASIS,
  # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
  # See the License for the specific language governing permissions and
  # limitations under the License.
  
  from scipy import stats
  import math
  
  _DEFAULT_THRESHOLD = 1e-10
  
  def scale(a, mul):
    return [x * mul for x in a]
  
  
  def cmp(a, b):
    return stats.ttest_ind(a, b)
  
  
  def speedup(new, old, threshold = _DEFAULT_THRESHOLD):
    if (len(set(new))) == 1 and new == old: return 0
    s0, p0 = cmp(new, old)
    if math.isnan(p0): return 0
    if s0 == 0: return 0
    if p0 > threshold: return 0
    if s0 < 0:
      pct = 1
      while pct < 100:
        sp, pp = cmp(new, scale(old, 1 - pct / 100.0))
        if sp > 0: break
        if pp > threshold: break
        pct += 1
      return -(pct - 1)
    else:
      pct = 1
      while pct < 10000:
        sp, pp = cmp(new, scale(old, 1 + pct / 100.0))
        if sp < 0: break
        if pp > threshold: break
        pct += 1
      return pct - 1
  
  
  if __name__ == "__main__":
    new = [0.0, 0.0, 0.0, 0.0] 
    old = [2.96608e-06, 3.35076e-06, 3.45384e-06, 3.34407e-06]
    print speedup(new, old, 1e-5)
    print speedup(old, new, 1e-5)
  
subject: Address github comments