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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