Regular
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		@ -146,7 +146,7 @@ def exponential(seq, lmdks, epsilon):
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  # Otherwise
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					  # Otherwise
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  bgts = np.zeros([len(seq)])
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					  bgts = np.zeros([len(seq)])
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  if len(seq) != len(lmdks):
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					  if len(seq) != len(lmdks):
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    # Find worst case regural point
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					    # Find worst case regular point
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    p_sel = 0
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					    p_sel = 0
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    for p in seq:
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					    for p in seq:
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      if not np.any(lmdks[:] == p):
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					      if not np.any(lmdks[:] == p):
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@ -190,7 +190,7 @@ def linear_zero(seq, lmdks, epsilon):
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      bgts - The privacy budget allocation.
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					      bgts - The privacy budget allocation.
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  '''
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					  '''
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  bgts = np.zeros([len(seq)])
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					  bgts = np.zeros([len(seq)])
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  # Find worst case regural point
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					  # Find worst case regular point
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  p_sel = 0
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					  p_sel = 0
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  for p in seq:
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					  for p in seq:
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    if not np.any(lmdks[:] == p):
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					    if not np.any(lmdks[:] == p):
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@ -227,7 +227,7 @@ def linear(seq, lmdks, epsilon):
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  # Fallback to uniform if zero or max landmarks
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					  # Fallback to uniform if zero or max landmarks
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  if len(lmdks) == 0 or len(lmdks) == len(seq):
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					  if len(lmdks) == 0 or len(lmdks) == len(seq):
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    return uniform(seq, lmdks, epsilon)
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					    return uniform(seq, lmdks, epsilon)
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  # Find worst case regural point
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					  # Find worst case regular point
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  p_sel = 0
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					  p_sel = 0
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  for p in seq:
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					  for p in seq:
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    if not np.any(lmdks[:] == p):
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					    if not np.any(lmdks[:] == p):
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