diff options
| author | leochanj105 <leochanj@live.unc.edu> | 2021-10-29 03:40:38 -0400 |
|---|---|---|
| committer | leochanj105 <leochanj@live.unc.edu> | 2021-10-29 03:40:38 -0400 |
| commit | 92df3dcae6747e4410574e7bf1f14dd1c07c3471 (patch) | |
| tree | fafe9dbe89a4f7f715eee72644b906e698af29dc /smt_analysis/computeSMTslowdown.py | |
| parent | 895707a76ef3711474eb98c4358588a96926739f (diff) | |
tmp 10/29
Diffstat (limited to 'smt_analysis/computeSMTslowdown.py')
| -rwxr-xr-x | smt_analysis/computeSMTslowdown.py | 13 |
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 | ||
| 98 | print("Baselines ", end=" ") | ||
| 99 | print() | ||
| 100 | # Print rows | ||
| 101 | for 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 |
| 97 | print("Overall average is {:>5.3} with standard deviation {:>5.3} using `{}`".format(np.mean(M_vals), np.std(M_vals), sample_f.__name__)) | 108 | print("Overall average is {:>5.3} with standard deviation {:>5.3} using `{}`".format(np.mean(M_vals), np.std(M_vals), sample_f.__name__)) |
| 98 | Ms = np.asarray(M_vals, dtype=np.float32) | 109 | Ms = np.asarray(M_vals, dtype=np.float32) |
