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authorleochanj105 <leochanj@live.unc.edu>2021-10-29 03:40:38 -0400
committerleochanj105 <leochanj@live.unc.edu>2021-10-29 03:40:38 -0400
commit92df3dcae6747e4410574e7bf1f14dd1c07c3471 (patch)
treefafe9dbe89a4f7f715eee72644b906e698af29dc /smt_analysis/computeSMTslowdown.py
parent895707a76ef3711474eb98c4358588a96926739f (diff)
tmp 10/29
Diffstat (limited to 'smt_analysis/computeSMTslowdown.py')
-rwxr-xr-xsmt_analysis/computeSMTslowdown.py13
1 files changed, 12 insertions, 1 deletions
diff --git a/smt_analysis/computeSMTslowdown.py b/smt_analysis/computeSMTslowdown.py
index d612ea6..cf09402 100755
--- a/smt_analysis/computeSMTslowdown.py
+++ b/smt_analysis/computeSMTslowdown.py
@@ -81,7 +81,7 @@ for b1 in reliableNames:
81 else: 81 else:
82 if not TIMES_ONLY: print("{:>10}".format("N/A"), end=" ") 82 if not TIMES_ONLY: print("{:>10}".format("N/A"), end=" ")
83 83
84 if TIMES_ONLY and (not OK_PAIRS_ONLY or Cj * 10 > Ci): 84 if TIMES_ONLY:# and (not OK_PAIRS_ONLY or Cj * 10 > Ci):
85 print("{:>12}".format(Cij), end=" ") 85 print("{:>12}".format(Cij), end=" ")
86 elif OK_PAIRS_ONLY and Cj * 10 <= Ci: 86 elif OK_PAIRS_ONLY and Cj * 10 <= Ci:
87 print("{:>12}".format("0"), end=" ") 87 print("{:>12}".format("0"), end=" ")
@@ -93,6 +93,17 @@ for b1 in reliableNames:
93 M_vals.append(M) 93 M_vals.append(M)
94 print("{:>10.3}".format(M), end=" ") 94 print("{:>10.3}".format(M), end=" ")
95 print("") 95 print("")
96
97# Output baselines
98print("Baselines ", end=" ")
99print()
100# Print rows
101for b1 in reliableNames:
102 print("{:<14.14}:".format(b1), end=" ")
103 Ci = sample_f(baseline_times[b1])
104 print("{:>12}".format(Ci), end=" ")
105 print("")
106
96# Print some statistics about the distribution 107# Print some statistics about the distribution
97print("Overall average is {:>5.3} with standard deviation {:>5.3} using `{}`".format(np.mean(M_vals), np.std(M_vals), sample_f.__name__)) 108print("Overall average is {:>5.3} with standard deviation {:>5.3} using `{}`".format(np.mean(M_vals), np.std(M_vals), sample_f.__name__))
98Ms = np.asarray(M_vals, dtype=np.float32) 109Ms = np.asarray(M_vals, dtype=np.float32)