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BIP-0119: Use the same random seed across simulation runs; fix issue where a poisson was used in place of an exponential
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@ -24,6 +24,7 @@ def get_rate(phase):
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return 1.25**(phase)*TXNS_PER_SEC
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return 1.25**(phase)*TXNS_PER_SEC
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def normal():
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def normal():
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np.random.seed(0)
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print("Max Txns Per Sec %f"%TXNS_PER_SEC)
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print("Max Txns Per Sec %f"%TXNS_PER_SEC)
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backlog = 0
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backlog = 0
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results_unconfirmed = [0]*SAMPLES
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results_unconfirmed = [0]*SAMPLES
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@ -43,6 +44,7 @@ def normal():
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results_unconfirmed[i] = backlog/AVG_TX
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results_unconfirmed[i] = backlog/AVG_TX
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return results_unconfirmed, np.cumsum(total_time)/(60*60*24.0)
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return results_unconfirmed, np.cumsum(total_time)/(60*60*24.0)
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def compressed(rate_multiplier = 1):
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def compressed(rate_multiplier = 1):
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np.random.seed(0)
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print("Max Txns Per Sec %f"%TXNS_PER_SEC)
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print("Max Txns Per Sec %f"%TXNS_PER_SEC)
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backlog = 0
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backlog = 0
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secondary_backlog = 0
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secondary_backlog = 0
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@ -54,7 +56,7 @@ def compressed(rate_multiplier = 1):
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total_time = [0]*(SAMPLES)
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total_time = [0]*(SAMPLES)
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for phase in range(PHASES):
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for phase in range(PHASES):
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for i in range(PHASE_LENGTH*phase, PHASE_LENGTH*(1+phase)):
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for i in range(PHASE_LENGTH*phase, PHASE_LENGTH*(1+phase)):
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block_time = np.random.poisson(AVG_INTERVAL)
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block_time = np.random.exponential(AVG_INTERVAL)
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total_time[i] = block_time
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total_time[i] = block_time
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txns = np.random.poisson(rate_multiplier*get_rate(phase)*block_time)
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txns = np.random.poisson(rate_multiplier*get_rate(phase)*block_time)
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postponed = txns * COMPRESSABLE
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postponed = txns * COMPRESSABLE
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