- Timestamp:
- Jun 27, 2023, 4:45:40 PM (15 months ago)
- Branches:
- master
- Children:
- a1f0cb6
- Parents:
- 917e1fd
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doc/theses/colby_parsons_MMAth/benchmarks/mutex_stmt/plotData.py
r917e1fd r14e1053 60 60 name = "Aggregate Lock" 61 61 var_name = "" 62 experiment_duration = 10 62 experiment_duration = 10.0 63 63 sendData = [0.0 for j in range(numVariants)] 64 64 data = [[0.0 for i in range(len(procs))] for j in range(numVariants)] … … 87 87 data[currVariant][procCount] = currMedian 88 88 lower, upper = st.t.interval(0.95, numTimes - 1, loc=np.mean(tempData), scale=st.sem(tempData)) 89 bars[currVariant][0][procCount] = currMedian - lower90 bars[currVariant][1][procCount] = upper - currMedian89 bars[currVariant][0][procCount] = max( 0, currMedian - lower ) 90 bars[currVariant][1][procCount] = max( 0, upper - currMedian ) 91 91 count = 0 92 92 procCount += 1 … … 100 100 fig, ax = plt.subplots(layout='constrained') 101 101 plt.title(name + " Benchmark: " + str(currLocks) + " Locks") 102 plt.ylabel("Throughput ( entries)")102 plt.ylabel("Throughput (critical section entries per second)") 103 103 plt.xlabel("Cores") 104 104 for idx, arr in enumerate(data):
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