14 SS14 Results
| Pos | Car | Code | Time (s) | Gap | Diff |
|---|---|---|---|---|---|
| 1 | 23 | OST | 1518.0 | 57.0 | 30.0 |
| 2 | 25 | GRY | 1520.8 | 59.8 | 2.8 |
| 3 | 22 | LAP | 1522.5 | 61.5 | 1.7 |
| 4 | 26 | CAM | 1528.8 | 67.8 | 6.3 |
| 5 | 21 | BUL | 1536.3 | 75.3 | 7.5 |
| 6 | 24 | SUN | 1541.9 | 80.9 | 1.4 |
| 7 | 28 | PRO | 1578.7 | 117.7 | 3.4 |
| 8 | 30 | SOL | 1588.5 | 127.5 | 2.4 |
| 9 | 31 | KRI | 1597.0 | 136.0 | 6.6 |
14.1 Stage SS14 Splits Analysis
Reports on splits
14.1.1 Split Locations
Length of each split section in km:
| full_split_distances | stage_dist | |
|---|---|---|
| split_1 | 7.34 | 7.34 |
| split_2 | 6.20 | 13.54 |
| split_3 | 7.23 | 20.77 |
| split_4 | 3.92 | 24.69 |
| split_5 | 3.73 | 28.42 |
| split_6 | 7.38 | 35.80 |
| split_N | 2.12 | 37.92 |
14.1.2 Stage Split Times & Result
Summary of stage split times and overall stage result:
| code | split_1 | split_2 | split_3 | split_4 | split_5 | split_6 | split_N | diffFirstS | position |
|---|---|---|---|---|---|---|---|---|---|
| OST | 297.9 | 544.8 | 836.7 | 1007.7 | 1138.2 | 1428.5 | 1518.0 | 0.0 | 6 |
| GRY | 299.4 | 547.8 | 837.6 | 1008.8 | 1138.6 | 1430.8 | 1520.8 | 2.8 | 7 |
| LAP | 299.6 | 548.0 | 838.8 | 1010.1 | 1140.8 | 1432.8 | 1522.5 | 4.5 | 8 |
| CAM | 300.6 | 550.7 | 842.8 | 1014.9 | 1145.8 | 1438.4 | 1528.8 | 10.8 | 9 |
| BUL | 298.6 | 550.6 | 846.7 | 1020.0 | 1153.6 | 1446.1 | 1536.3 | 18.3 | 10 |
| SUN | 313.9 | 563.0 | 856.2 | 1028.5 | 1160.0 | 1452.3 | 1541.9 | 23.9 | 12 |
| PRO | 310.1 | 570.0 | 875.2 | 1050.9 | 1185.7 | 1485.5 | 1578.7 | 60.7 | 19 |
| SOL | 301.4 | 550.8 | 843.1 | 1015.6 | 1146.5 | 1497.4 | 1588.5 | 70.5 | 23 |
| KRI | 310.9 | 572.6 | 879.3 | 1058.1 | 1195.0 | 1501.7 | 1597.0 | 79.0 | 25 |
14.1.3 Split Time Rankings
Rank of each split time:
| code | split_1 | split_2 | split_3 | split_4 | split_5 | split_6 | split_N |
|---|---|---|---|---|---|---|---|
| OST | 1 | 1 | 1 | 1 | 1 | 1 | 1 |
| GRY | 3 | 2 | 2 | 2 | 2 | 2 | 2 |
| LAP | 4 | 3 | 3 | 3 | 3 | 3 | 3 |
| CAM | 5 | 5 | 4 | 4 | 4 | 4 | 4 |
| BUL | 2 | 4 | 6 | 6 | 6 | 5 | 5 |
| SUN | 9 | 7 | 7 | 7 | 7 | 6 | 6 |
| PRO | 7 | 8 | 8 | 8 | 8 | 7 | 7 |
| SOL | 6 | 6 | 5 | 5 | 5 | 8 | 8 |
| KRI | 8 | 9 | 9 | 9 | 9 | 9 | 9 |
Rank on each split section:
| code | split_1 | split_2 | split_3 | split_4 | split_5 | split_6 | split_N |
|---|---|---|---|---|---|---|---|
| OST | 1 | 1 | 1 | 1 | 1 | 1 | 1 |
| GRY | 3 | 2 | 2 | 2 | 2 | 2 | 2 |
| LAP | 4 | 3 | 3 | 3 | 3 | 3 | 3 |
| CAM | 5 | 5 | 4 | 4 | 4 | 4 | 4 |
| BUL | 2 | 4 | 6 | 6 | 6 | 5 | 5 |
| SUN | 9 | 7 | 7 | 7 | 7 | 6 | 6 |
| PRO | 7 | 8 | 8 | 8 | 8 | 7 | 7 |
| SOL | 6 | 6 | 5 | 5 | 5 | 8 | 8 |
| KRI | 8 | 9 | 9 | 9 | 9 | 9 | 9 |
14.1.4 Split Section Pace
Pace is measured in seconds per kilometer, which is to say, how long it takes to complete each kilometer (lower is better):
| code | split_1 | split_2 | split_3 | split_4 | split_5 | split_6 | split_N |
|---|---|---|---|---|---|---|---|
| OST | 40.59 | 39.82 | 40.37 | 43.62 | 34.99 | 39.34 | 42.22 |
| GRY | 40.79 | 40.06 | 40.08 | 43.67 | 34.80 | 39.59 | 42.45 |
| LAP | 40.82 | 40.06 | 40.22 | 43.70 | 35.04 | 39.57 | 42.31 |
| CAM | 40.95 | 40.34 | 40.40 | 43.90 | 35.09 | 39.65 | 42.64 |
| BUL | 40.68 | 40.65 | 40.95 | 44.21 | 35.82 | 39.63 | 42.55 |
| SUN | 42.77 | 40.18 | 40.55 | 43.95 | 35.25 | 39.61 | 42.26 |
| PRO | 42.25 | 41.92 | 42.21 | 44.82 | 36.14 | 40.62 | 43.96 |
| SOL | 41.06 | 40.23 | 40.43 | 44.01 | 35.09 | 47.55 | 42.97 |
| KRI | 42.36 | 42.21 | 42.42 | 45.61 | 36.70 | 41.56 | 44.95 |
14.1.5 Ultimate Stage Comparisons
Split time comparisons relative to various ultimage stage time calculations.
These views provide various ways of comparing the performance of each driver to various ghost drivers:
- best recorded split time at each split (ultimate actuals): gives an estimate of how well the driver’s split times compare with each first ranked split time (time into stage at each split);
- fastest time going from one split to the next (ultimate sections): gives an estimate of how quickly each driver completed each split section relative to the quickest time recorded completing that split section (time taken to go from one split point to the next);
- accumulated ultimate sections times: gives and estimate of how quickly the driver is going relative to the fastest possible completion of the stage based on accumulated ultimate split section times.
<IP_ADDRESS> Ultimate Actuals
Driver times compared to the first ranked recorded split time at each split:
| code | split_1 | split_2 | split_3 | split_4 | split_5 | split_6 | split_N |
|---|---|---|---|---|---|---|---|
| OST | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 |
| GRY | 1.5 | 3.0 | 0.9 | 1.1 | 0.4 | 2.3 | 2.8 |
| LAP | 1.7 | 3.2 | 2.1 | 2.4 | 2.6 | 4.3 | 4.5 |
| CAM | 2.7 | 5.9 | 6.1 | 7.2 | 7.6 | 9.9 | 10.8 |
| BUL | 0.7 | 5.8 | 10.0 | 12.3 | 15.4 | 17.6 | 18.3 |
| SUN | 16.0 | 18.2 | 19.5 | 20.8 | 21.8 | 23.8 | 23.9 |
| PRO | 12.2 | 25.2 | 38.5 | 43.2 | 47.5 | 57.0 | 60.7 |
| SOL | 3.5 | 6.0 | 6.4 | 7.9 | 8.3 | 68.9 | 70.5 |
| KRI | 13.0 | 27.8 | 42.6 | 50.4 | 56.8 | 73.2 | 79.0 |
| ultimate | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 |
<IP_ADDRESS> Ultimate Sections
Split durations rebased relative to the fastest transit of each split section:
| code | split_1 | split_2 | split_3 | split_4 | split_5 | split_6 | split_N |
|---|---|---|---|---|---|---|---|
| OST | 0.0 | 0.0 | 2.1 | 0.0 | 0.7 | 0.0 | 0.0 |
| GRY | 1.5 | 1.5 | 0.0 | 0.2 | 0.0 | 1.9 | 0.5 |
| LAP | 1.7 | 1.5 | 1.0 | 0.3 | 0.9 | 1.7 | 0.2 |
| CAM | 2.7 | 3.2 | 2.3 | 1.1 | 1.1 | 2.3 | 0.9 |
| BUL | 0.7 | 5.1 | 6.3 | 2.3 | 3.8 | 2.2 | 0.7 |
| SUN | 16.0 | 2.2 | 3.4 | 1.3 | 1.7 | 2.0 | 0.1 |
| PRO | 12.2 | 13.0 | 15.4 | 4.7 | 5.0 | 9.5 | 3.7 |
| SOL | 3.5 | 2.5 | 2.5 | 1.5 | 1.1 | 60.6 | 1.6 |
| KRI | 13.0 | 14.8 | 16.9 | 7.8 | 7.1 | 16.4 | 5.8 |
| ultimate | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 |
<IP_ADDRESS> Ultimate Accumulated Sections
Actual split times relative to the accumulated ultimate split section times:
| code | split_1 | split_2 | split_3 | split_4 | split_5 | split_6 | split_N |
|---|---|---|---|---|---|---|---|
| OST | 0.0 | 0.0 | 2.1 | 2.1 | 2.8 | 2.8 | 2.8 |
| GRY | 1.5 | 3.0 | 3.0 | 3.2 | 3.2 | 5.1 | 5.6 |
| LAP | 1.7 | 3.2 | 4.2 | 4.5 | 5.4 | 7.1 | 7.3 |
| CAM | 2.7 | 5.9 | 8.2 | 9.3 | 10.4 | 12.7 | 13.6 |
| BUL | 0.7 | 5.8 | 12.1 | 14.4 | 18.2 | 20.4 | 21.1 |
| SUN | 16.0 | 18.2 | 21.6 | 22.9 | 24.6 | 26.6 | 26.7 |
| PRO | 12.2 | 25.2 | 40.6 | 45.3 | 50.3 | 59.8 | 63.5 |
| SOL | 3.5 | 6.0 | 8.5 | 10.0 | 11.1 | 71.7 | 73.3 |
| KRI | 13.0 | 27.8 | 44.7 | 52.5 | 59.6 | 76.0 | 81.8 |
| ultimate | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 |
14.1.6 Split Section Pace Distribution
Distribution of pace values for each split section:
14.2 Driver Report, SS14 - MIK
No stage report for MIK.
14.3 Driver Report, SS14 - BUL
Stage report for BUL.
| Pos | Car | Code | Time (s) | Gap | Diff |
|---|---|---|---|---|---|
| 6 | 23 | OST | -18.3 | -18.3 | 30.0 |
| 7 | 25 | GRY | -15.5 | -15.5 | 2.8 |
| 8 | 22 | LAP | -13.8 | -13.8 | 1.7 |
| 9 | 26 | CAM | -7.5 | -7.5 | 6.3 |
| 10 | 21 | BUL | 0.0 | 0.0 | 7.5 |
| 12 | 24 | SUN | 5.6 | 5.6 | 1.4 |
| 19 | 28 | PRO | 42.4 | 42.4 | 3.4 |
| 23 | 30 | SOL | 52.2 | 52.2 | 2.4 |
| 25 | 31 | KRI | 60.7 | 60.7 | 6.6 |
14.3.1 Rebased Split Times
BUL’s delta at each split compared to other drivers.
| code | split_1 | split_2 | split_3 | split_4 | split_5 | split_6 | split_N |
|---|---|---|---|---|---|---|---|
| OST | -0.7 | -5.8 | -10.0 | -12.3 | -15.4 | -17.6 | -18.3 |
| GRY | 0.8 | -2.8 | -9.1 | -11.2 | -15.0 | -15.3 | -15.5 |
| LAP | 1.0 | -2.6 | -7.9 | -9.9 | -12.8 | -13.3 | -13.8 |
| CAM | 2.0 | 0.1 | -3.9 | -5.1 | -7.8 | -7.7 | -7.5 |
| BUL | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 |
| SUN | 15.3 | 12.4 | 9.5 | 8.5 | 6.4 | 6.2 | 5.6 |
| PRO | 11.5 | 19.4 | 28.5 | 30.9 | 32.1 | 39.4 | 42.4 |
| SOL | 2.8 | 0.2 | -3.6 | -4.4 | -7.1 | 51.3 | 52.2 |
| KRI | 12.3 | 22.0 | 32.6 | 38.1 | 41.4 | 55.6 | 60.7 |
Accumulated stage time deltas at each split:
14.3.2 Within-Split Duration Deltas
BUL’s delta in time to complete each split section compared to other drivers:
| code | split_1 | split_2 | split_3 | split_4 | split_5 | split_6 | split_N |
|---|---|---|---|---|---|---|---|
| OST | -0.7 | -5.1 | -4.2 | -2.3 | -3.1 | -2.2 | -0.7 |
| GRY | 0.8 | -3.6 | -6.3 | -2.1 | -3.8 | -0.3 | -0.2 |
| LAP | 1.0 | -3.6 | -5.3 | -2.0 | -2.9 | -0.5 | -0.5 |
| CAM | 2.0 | -1.9 | -4.0 | -1.2 | -2.7 | 0.1 | 0.2 |
| BUL | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 |
| SUN | 15.3 | -2.9 | -2.9 | -1.0 | -2.1 | -0.2 | -0.6 |
| PRO | 11.5 | 7.9 | 9.1 | 2.4 | 1.2 | 7.3 | 3.0 |
| SOL | 2.8 | -2.6 | -3.8 | -0.8 | -2.7 | 58.4 | 0.9 |
| KRI | 12.3 | 9.7 | 10.6 | 5.5 | 3.3 | 14.2 | 5.1 |
14.3.3 Within-Split Pace Deltas
| code | split_1 | split_2 | split_3 | split_4 | split_5 | split_6 | split_N |
|---|---|---|---|---|---|---|---|
| OST | -0.10 | -0.82 | -0.58 | -0.59 | -0.83 | -0.30 | -0.33 |
| GRY | 0.11 | -0.58 | -0.87 | -0.54 | -1.02 | -0.04 | -0.09 |
| LAP | 0.14 | -0.58 | -0.73 | -0.51 | -0.78 | -0.07 | -0.24 |
| CAM | 0.27 | -0.31 | -0.55 | -0.31 | -0.72 | 0.01 | 0.09 |
| BUL | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 |
| SUN | 2.08 | -0.47 | -0.40 | -0.26 | -0.56 | -0.03 | -0.28 |
| PRO | 1.57 | 1.27 | 1.26 | 0.61 | 0.32 | 0.99 | 1.42 |
| SOL | 0.38 | -0.42 | -0.53 | -0.20 | -0.72 | 7.91 | 0.42 |
| KRI | 1.68 | 1.56 | 1.47 | 1.40 | 0.88 | 1.92 | 2.41 |
14.4 Driver Report, SS14 - LAP
Stage report for LAP.
| Pos | Car | Code | Time (s) | Gap | Diff |
|---|---|---|---|---|---|
| 6 | 23 | OST | -4.5 | -4.5 | 30.0 |
| 7 | 25 | GRY | -1.7 | -1.7 | 2.8 |
| 8 | 22 | LAP | 0.0 | 0.0 | 1.7 |
| 9 | 26 | CAM | 6.3 | 6.3 | 6.3 |
| 10 | 21 | BUL | 13.8 | 13.8 | 7.5 |
| 12 | 24 | SUN | 19.4 | 19.4 | 1.4 |
| 19 | 28 | PRO | 56.2 | 56.2 | 3.4 |
| 23 | 30 | SOL | 66.0 | 66.0 | 2.4 |
| 25 | 31 | KRI | 74.5 | 74.5 | 6.6 |
14.4.1 Rebased Split Times
LAP’s delta at each split compared to other drivers.
| code | split_1 | split_2 | split_3 | split_4 | split_5 | split_6 | split_N |
|---|---|---|---|---|---|---|---|
| OST | -1.7 | -3.2 | -2.1 | -2.4 | -2.6 | -4.3 | -4.5 |
| GRY | -0.2 | -0.2 | -1.2 | -1.3 | -2.2 | -2.0 | -1.7 |
| LAP | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 |
| CAM | 1.0 | 2.7 | 4.0 | 4.8 | 5.0 | 5.6 | 6.3 |
| BUL | -1.0 | 2.6 | 7.9 | 9.9 | 12.8 | 13.3 | 13.8 |
| SUN | 14.3 | 15.0 | 17.4 | 18.4 | 19.2 | 19.5 | 19.4 |
| PRO | 10.5 | 22.0 | 36.4 | 40.8 | 44.9 | 52.7 | 56.2 |
| SOL | 1.8 | 2.8 | 4.3 | 5.5 | 5.7 | 64.6 | 66.0 |
| KRI | 11.3 | 24.6 | 40.5 | 48.0 | 54.2 | 68.9 | 74.5 |
Accumulated stage time deltas at each split:
14.4.2 Within-Split Duration Deltas
LAP’s delta in time to complete each split section compared to other drivers:
| code | split_1 | split_2 | split_3 | split_4 | split_5 | split_6 | split_N |
|---|---|---|---|---|---|---|---|
| OST | -1.7 | -1.5 | 1.1 | -0.3 | -0.2 | -1.7 | -0.2 |
| GRY | -0.2 | 0.0 | -1.0 | -0.1 | -0.9 | 0.2 | 0.3 |
| LAP | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 |
| CAM | 1.0 | 1.7 | 1.3 | 0.8 | 0.2 | 0.6 | 0.7 |
| BUL | -1.0 | 3.6 | 5.3 | 2.0 | 2.9 | 0.5 | 0.5 |
| SUN | 14.3 | 0.7 | 2.4 | 1.0 | 0.8 | 0.3 | -0.1 |
| PRO | 10.5 | 11.5 | 14.4 | 4.4 | 4.1 | 7.8 | 3.5 |
| SOL | 1.8 | 1.0 | 1.5 | 1.2 | 0.2 | 58.9 | 1.4 |
| KRI | 11.3 | 13.3 | 15.9 | 7.5 | 6.2 | 14.7 | 5.6 |
14.4.3 Within-Split Pace Deltas
| code | split_1 | split_2 | split_3 | split_4 | split_5 | split_6 | split_N |
|---|---|---|---|---|---|---|---|
| OST | -0.23 | -0.24 | 0.15 | -0.08 | -0.05 | -0.23 | -0.09 |
| GRY | -0.03 | 0.00 | -0.14 | -0.03 | -0.24 | 0.03 | 0.14 |
| LAP | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 |
| CAM | 0.14 | 0.27 | 0.18 | 0.20 | 0.05 | 0.08 | 0.33 |
| BUL | -0.14 | 0.58 | 0.73 | 0.51 | 0.78 | 0.07 | 0.24 |
| SUN | 1.95 | 0.11 | 0.33 | 0.26 | 0.21 | 0.04 | -0.05 |
| PRO | 1.43 | 1.85 | 1.99 | 1.12 | 1.10 | 1.06 | 1.65 |
| SOL | 0.25 | 0.16 | 0.21 | 0.31 | 0.05 | 7.98 | 0.66 |
| KRI | 1.54 | 2.15 | 2.20 | 1.91 | 1.66 | 1.99 | 2.64 |
14.5 Driver Report, SS14 - OST
Stage report for OST.
| Pos | Car | Code | Time (s) | Gap | Diff |
|---|---|---|---|---|---|
| 6 | 23 | OST | 0.0 | 0.0 | 30.0 |
| 7 | 25 | GRY | 2.8 | 2.8 | 2.8 |
| 8 | 22 | LAP | 4.5 | 4.5 | 1.7 |
| 9 | 26 | CAM | 10.8 | 10.8 | 6.3 |
| 10 | 21 | BUL | 18.3 | 18.3 | 7.5 |
| 12 | 24 | SUN | 23.9 | 23.9 | 1.4 |
| 19 | 28 | PRO | 60.7 | 60.7 | 3.4 |
| 23 | 30 | SOL | 70.5 | 70.5 | 2.4 |
| 25 | 31 | KRI | 79.0 | 79.0 | 6.6 |
14.5.1 Rebased Split Times
OST’s delta at each split compared to other drivers.
| code | split_1 | split_2 | split_3 | split_4 | split_5 | split_6 | split_N |
|---|---|---|---|---|---|---|---|
| OST | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 |
| GRY | 1.5 | 3.0 | 0.9 | 1.1 | 0.4 | 2.3 | 2.8 |
| LAP | 1.7 | 3.2 | 2.1 | 2.4 | 2.6 | 4.3 | 4.5 |
| CAM | 2.7 | 5.9 | 6.1 | 7.2 | 7.6 | 9.9 | 10.8 |
| BUL | 0.7 | 5.8 | 10.0 | 12.3 | 15.4 | 17.6 | 18.3 |
| SUN | 16.0 | 18.2 | 19.5 | 20.8 | 21.8 | 23.8 | 23.9 |
| PRO | 12.2 | 25.2 | 38.5 | 43.2 | 47.5 | 57.0 | 60.7 |
| SOL | 3.5 | 6.0 | 6.4 | 7.9 | 8.3 | 68.9 | 70.5 |
| KRI | 13.0 | 27.8 | 42.6 | 50.4 | 56.8 | 73.2 | 79.0 |
Accumulated stage time deltas at each split:
14.5.2 Within-Split Duration Deltas
OST’s delta in time to complete each split section compared to other drivers:
| code | split_1 | split_2 | split_3 | split_4 | split_5 | split_6 | split_N |
|---|---|---|---|---|---|---|---|
| OST | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 |
| GRY | 1.5 | 1.5 | -2.1 | 0.2 | -0.7 | 1.9 | 0.5 |
| LAP | 1.7 | 1.5 | -1.1 | 0.3 | 0.2 | 1.7 | 0.2 |
| CAM | 2.7 | 3.2 | 0.2 | 1.1 | 0.4 | 2.3 | 0.9 |
| BUL | 0.7 | 5.1 | 4.2 | 2.3 | 3.1 | 2.2 | 0.7 |
| SUN | 16.0 | 2.2 | 1.3 | 1.3 | 1.0 | 2.0 | 0.1 |
| PRO | 12.2 | 13.0 | 13.3 | 4.7 | 4.3 | 9.5 | 3.7 |
| SOL | 3.5 | 2.5 | 0.4 | 1.5 | 0.4 | 60.6 | 1.6 |
| KRI | 13.0 | 14.8 | 14.8 | 7.8 | 6.4 | 16.4 | 5.8 |
14.5.3 Within-Split Pace Deltas
| code | split_1 | split_2 | split_3 | split_4 | split_5 | split_6 | split_N |
|---|---|---|---|---|---|---|---|
| OST | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 |
| GRY | 0.20 | 0.24 | -0.29 | 0.05 | -0.19 | 0.26 | 0.24 |
| LAP | 0.23 | 0.24 | -0.15 | 0.08 | 0.05 | 0.23 | 0.09 |
| CAM | 0.37 | 0.52 | 0.03 | 0.28 | 0.11 | 0.31 | 0.42 |
| BUL | 0.10 | 0.82 | 0.58 | 0.59 | 0.83 | 0.30 | 0.33 |
| SUN | 2.18 | 0.35 | 0.18 | 0.33 | 0.27 | 0.27 | 0.05 |
| PRO | 1.66 | 2.10 | 1.84 | 1.20 | 1.15 | 1.29 | 1.75 |
| SOL | 0.48 | 0.40 | 0.06 | 0.38 | 0.11 | 8.21 | 0.75 |
| KRI | 1.77 | 2.39 | 2.05 | 1.99 | 1.72 | 2.22 | 2.74 |
14.6 Driver Report, SS14 - SUN
Stage report for SUN.
| Pos | Car | Code | Time (s) | Gap | Diff |
|---|---|---|---|---|---|
| 6 | 23 | OST | -23.9 | -23.9 | 30.0 |
| 7 | 25 | GRY | -21.1 | -21.1 | 2.8 |
| 8 | 22 | LAP | -19.4 | -19.4 | 1.7 |
| 9 | 26 | CAM | -13.1 | -13.1 | 6.3 |
| 10 | 21 | BUL | -5.6 | -5.6 | 7.5 |
| 12 | 24 | SUN | 0.0 | 0.0 | 1.4 |
| 19 | 28 | PRO | 36.8 | 36.8 | 3.4 |
| 23 | 30 | SOL | 46.6 | 46.6 | 2.4 |
| 25 | 31 | KRI | 55.1 | 55.1 | 6.6 |
14.6.1 Rebased Split Times
SUN’s delta at each split compared to other drivers.
| code | split_1 | split_2 | split_3 | split_4 | split_5 | split_6 | split_N |
|---|---|---|---|---|---|---|---|
| OST | -16.0 | -18.2 | -19.5 | -20.8 | -21.8 | -23.8 | -23.9 |
| GRY | -14.5 | -15.2 | -18.6 | -19.7 | -21.4 | -21.5 | -21.1 |
| LAP | -14.3 | -15.0 | -17.4 | -18.4 | -19.2 | -19.5 | -19.4 |
| CAM | -13.3 | -12.3 | -13.4 | -13.6 | -14.2 | -13.9 | -13.1 |
| BUL | -15.3 | -12.4 | -9.5 | -8.5 | -6.4 | -6.2 | -5.6 |
| SUN | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 |
| PRO | -3.8 | 7.0 | 19.0 | 22.4 | 25.7 | 33.2 | 36.8 |
| SOL | -12.5 | -12.2 | -13.1 | -12.9 | -13.5 | 45.1 | 46.6 |
| KRI | -3.0 | 9.6 | 23.1 | 29.6 | 35.0 | 49.4 | 55.1 |
Accumulated stage time deltas at each split:
14.6.2 Within-Split Duration Deltas
SUN’s delta in time to complete each split section compared to other drivers:
| code | split_1 | split_2 | split_3 | split_4 | split_5 | split_6 | split_N |
|---|---|---|---|---|---|---|---|
| OST | -16.0 | -2.2 | -1.3 | -1.3 | -1.0 | -2.0 | -0.1 |
| GRY | -14.5 | -0.7 | -3.4 | -1.1 | -1.7 | -0.1 | 0.4 |
| LAP | -14.3 | -0.7 | -2.4 | -1.0 | -0.8 | -0.3 | 0.1 |
| CAM | -13.3 | 1.0 | -1.1 | -0.2 | -0.6 | 0.3 | 0.8 |
| BUL | -15.3 | 2.9 | 2.9 | 1.0 | 2.1 | 0.2 | 0.6 |
| SUN | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 |
| PRO | -3.8 | 10.8 | 12.0 | 3.4 | 3.3 | 7.5 | 3.6 |
| SOL | -12.5 | 0.3 | -0.9 | 0.2 | -0.6 | 58.6 | 1.5 |
| KRI | -3.0 | 12.6 | 13.5 | 6.5 | 5.4 | 14.4 | 5.7 |
14.6.3 Within-Split Pace Deltas
| code | split_1 | split_2 | split_3 | split_4 | split_5 | split_6 | split_N |
|---|---|---|---|---|---|---|---|
| OST | -2.18 | -0.35 | -0.18 | -0.33 | -0.27 | -0.27 | -0.05 |
| GRY | -1.98 | -0.11 | -0.47 | -0.28 | -0.46 | -0.01 | 0.19 |
| LAP | -1.95 | -0.11 | -0.33 | -0.26 | -0.21 | -0.04 | 0.05 |
| CAM | -1.81 | 0.16 | -0.15 | -0.05 | -0.16 | 0.04 | 0.38 |
| BUL | -2.08 | 0.47 | 0.40 | 0.26 | 0.56 | 0.03 | 0.28 |
| SUN | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 |
| PRO | -0.52 | 1.74 | 1.66 | 0.87 | 0.88 | 1.02 | 1.70 |
| SOL | -1.70 | 0.05 | -0.12 | 0.05 | -0.16 | 7.94 | 0.71 |
| KRI | -0.41 | 2.03 | 1.87 | 1.66 | 1.45 | 1.95 | 2.69 |
14.7 Driver Report, SS14 - GRY
Stage report for GRY.
| Pos | Car | Code | Time (s) | Gap | Diff |
|---|---|---|---|---|---|
| 6 | 23 | OST | -2.8 | -2.8 | 30.0 |
| 7 | 25 | GRY | 0.0 | 0.0 | 2.8 |
| 8 | 22 | LAP | 1.7 | 1.7 | 1.7 |
| 9 | 26 | CAM | 8.0 | 8.0 | 6.3 |
| 10 | 21 | BUL | 15.5 | 15.5 | 7.5 |
| 12 | 24 | SUN | 21.1 | 21.1 | 1.4 |
| 19 | 28 | PRO | 57.9 | 57.9 | 3.4 |
| 23 | 30 | SOL | 67.7 | 67.7 | 2.4 |
| 25 | 31 | KRI | 76.2 | 76.2 | 6.6 |
14.7.1 Rebased Split Times
GRY’s delta at each split compared to other drivers.
| code | split_1 | split_2 | split_3 | split_4 | split_5 | split_6 | split_N |
|---|---|---|---|---|---|---|---|
| OST | -1.5 | -3.0 | -0.9 | -1.1 | -0.4 | -2.3 | -2.8 |
| GRY | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 |
| LAP | 0.2 | 0.2 | 1.2 | 1.3 | 2.2 | 2.0 | 1.7 |
| CAM | 1.2 | 2.9 | 5.2 | 6.1 | 7.2 | 7.6 | 8.0 |
| BUL | -0.8 | 2.8 | 9.1 | 11.2 | 15.0 | 15.3 | 15.5 |
| SUN | 14.5 | 15.2 | 18.6 | 19.7 | 21.4 | 21.5 | 21.1 |
| PRO | 10.7 | 22.2 | 37.6 | 42.1 | 47.1 | 54.7 | 57.9 |
| SOL | 2.0 | 3.0 | 5.5 | 6.8 | 7.9 | 66.6 | 67.7 |
| KRI | 11.5 | 24.8 | 41.7 | 49.3 | 56.4 | 70.9 | 76.2 |
Accumulated stage time deltas at each split:
14.7.2 Within-Split Duration Deltas
GRY’s delta in time to complete each split section compared to other drivers:
| code | split_1 | split_2 | split_3 | split_4 | split_5 | split_6 | split_N |
|---|---|---|---|---|---|---|---|
| OST | -1.5 | -1.5 | 2.1 | -0.2 | 0.7 | -1.9 | -0.5 |
| GRY | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 |
| LAP | 0.2 | 0.0 | 1.0 | 0.1 | 0.9 | -0.2 | -0.3 |
| CAM | 1.2 | 1.7 | 2.3 | 0.9 | 1.1 | 0.4 | 0.4 |
| BUL | -0.8 | 3.6 | 6.3 | 2.1 | 3.8 | 0.3 | 0.2 |
| SUN | 14.5 | 0.7 | 3.4 | 1.1 | 1.7 | 0.1 | -0.4 |
| PRO | 10.7 | 11.5 | 15.4 | 4.5 | 5.0 | 7.6 | 3.2 |
| SOL | 2.0 | 1.0 | 2.5 | 1.3 | 1.1 | 58.7 | 1.1 |
| KRI | 11.5 | 13.3 | 16.9 | 7.6 | 7.1 | 14.5 | 5.3 |
14.7.3 Within-Split Pace Deltas
| code | split_1 | split_2 | split_3 | split_4 | split_5 | split_6 | split_N |
|---|---|---|---|---|---|---|---|
| OST | -0.20 | -0.24 | 0.29 | -0.05 | 0.19 | -0.26 | -0.24 |
| GRY | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 |
| LAP | 0.03 | 0.00 | 0.14 | 0.03 | 0.24 | -0.03 | -0.14 |
| CAM | 0.16 | 0.27 | 0.32 | 0.23 | 0.29 | 0.05 | 0.19 |
| BUL | -0.11 | 0.58 | 0.87 | 0.54 | 1.02 | 0.04 | 0.09 |
| SUN | 1.98 | 0.11 | 0.47 | 0.28 | 0.46 | 0.01 | -0.19 |
| PRO | 1.46 | 1.85 | 2.13 | 1.15 | 1.34 | 1.03 | 1.51 |
| SOL | 0.27 | 0.16 | 0.35 | 0.33 | 0.29 | 7.95 | 0.52 |
| KRI | 1.57 | 2.15 | 2.34 | 1.94 | 1.90 | 1.96 | 2.50 |
14.8 Driver Report, SS14 - CAM
Stage report for CAM.
| Pos | Car | Code | Time (s) | Gap | Diff |
|---|---|---|---|---|---|
| 6 | 23 | OST | -10.8 | -10.8 | 30.0 |
| 7 | 25 | GRY | -8.0 | -8.0 | 2.8 |
| 8 | 22 | LAP | -6.3 | -6.3 | 1.7 |
| 9 | 26 | CAM | 0.0 | 0.0 | 6.3 |
| 10 | 21 | BUL | 7.5 | 7.5 | 7.5 |
| 12 | 24 | SUN | 13.1 | 13.1 | 1.4 |
| 19 | 28 | PRO | 49.9 | 49.9 | 3.4 |
| 23 | 30 | SOL | 59.7 | 59.7 | 2.4 |
| 25 | 31 | KRI | 68.2 | 68.2 | 6.6 |
14.8.1 Rebased Split Times
CAM’s delta at each split compared to other drivers.
| code | split_1 | split_2 | split_3 | split_4 | split_5 | split_6 | split_N |
|---|---|---|---|---|---|---|---|
| OST | -2.7 | -5.9 | -6.1 | -7.2 | -7.6 | -9.9 | -10.8 |
| GRY | -1.2 | -2.9 | -5.2 | -6.1 | -7.2 | -7.6 | -8.0 |
| LAP | -1.0 | -2.7 | -4.0 | -4.8 | -5.0 | -5.6 | -6.3 |
| CAM | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 |
| BUL | -2.0 | -0.1 | 3.9 | 5.1 | 7.8 | 7.7 | 7.5 |
| SUN | 13.3 | 12.3 | 13.4 | 13.6 | 14.2 | 13.9 | 13.1 |
| PRO | 9.5 | 19.3 | 32.4 | 36.0 | 39.9 | 47.1 | 49.9 |
| SOL | 0.8 | 0.1 | 0.3 | 0.7 | 0.7 | 59.0 | 59.7 |
| KRI | 10.3 | 21.9 | 36.5 | 43.2 | 49.2 | 63.3 | 68.2 |
Accumulated stage time deltas at each split:
14.8.2 Within-Split Duration Deltas
CAM’s delta in time to complete each split section compared to other drivers:
| code | split_1 | split_2 | split_3 | split_4 | split_5 | split_6 | split_N |
|---|---|---|---|---|---|---|---|
| OST | -2.7 | -3.2 | -0.2 | -1.1 | -0.4 | -2.3 | -0.9 |
| GRY | -1.2 | -1.7 | -2.3 | -0.9 | -1.1 | -0.4 | -0.4 |
| LAP | -1.0 | -1.7 | -1.3 | -0.8 | -0.2 | -0.6 | -0.7 |
| CAM | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 |
| BUL | -2.0 | 1.9 | 4.0 | 1.2 | 2.7 | -0.1 | -0.2 |
| SUN | 13.3 | -1.0 | 1.1 | 0.2 | 0.6 | -0.3 | -0.8 |
| PRO | 9.5 | 9.8 | 13.1 | 3.6 | 3.9 | 7.2 | 2.8 |
| SOL | 0.8 | -0.7 | 0.2 | 0.4 | 0.0 | 58.3 | 0.7 |
| KRI | 10.3 | 11.6 | 14.6 | 6.7 | 6.0 | 14.1 | 4.9 |
14.8.3 Within-Split Pace Deltas
| code | split_1 | split_2 | split_3 | split_4 | split_5 | split_6 | split_N |
|---|---|---|---|---|---|---|---|
| OST | -0.37 | -0.52 | -0.03 | -0.28 | -0.11 | -0.31 | -0.42 |
| GRY | -0.16 | -0.27 | -0.32 | -0.23 | -0.29 | -0.05 | -0.19 |
| LAP | -0.14 | -0.27 | -0.18 | -0.20 | -0.05 | -0.08 | -0.33 |
| CAM | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 |
| BUL | -0.27 | 0.31 | 0.55 | 0.31 | 0.72 | -0.01 | -0.09 |
| SUN | 1.81 | -0.16 | 0.15 | 0.05 | 0.16 | -0.04 | -0.38 |
| PRO | 1.29 | 1.58 | 1.81 | 0.92 | 1.05 | 0.98 | 1.32 |
| SOL | 0.11 | -0.11 | 0.03 | 0.10 | 0.00 | 7.90 | 0.33 |
| KRI | 1.40 | 1.87 | 2.02 | 1.71 | 1.61 | 1.91 | 2.31 |
14.9 Driver Report, SS14 - VEI
No stage report for VEI.
14.10 Driver Report, SS14 - PRO
Stage report for PRO.
| Pos | Car | Code | Time (s) | Gap | Diff |
|---|---|---|---|---|---|
| 6 | 23 | OST | -60.7 | -60.7 | 30.0 |
| 7 | 25 | GRY | -57.9 | -57.9 | 2.8 |
| 8 | 22 | LAP | -56.2 | -56.2 | 1.7 |
| 9 | 26 | CAM | -49.9 | -49.9 | 6.3 |
| 10 | 21 | BUL | -42.4 | -42.4 | 7.5 |
| 12 | 24 | SUN | -36.8 | -36.8 | 1.4 |
| 19 | 28 | PRO | 0.0 | 0.0 | 3.4 |
| 23 | 30 | SOL | 9.8 | 9.8 | 2.4 |
| 25 | 31 | KRI | 18.3 | 18.3 | 6.6 |
14.10.1 Rebased Split Times
PRO’s delta at each split compared to other drivers.
| code | split_1 | split_2 | split_3 | split_4 | split_5 | split_6 | split_N |
|---|---|---|---|---|---|---|---|
| OST | -12.2 | -25.2 | -38.5 | -43.2 | -47.5 | -57.0 | -60.7 |
| GRY | -10.7 | -22.2 | -37.6 | -42.1 | -47.1 | -54.7 | -57.9 |
| LAP | -10.5 | -22.0 | -36.4 | -40.8 | -44.9 | -52.7 | -56.2 |
| CAM | -9.5 | -19.3 | -32.4 | -36.0 | -39.9 | -47.1 | -49.9 |
| BUL | -11.5 | -19.4 | -28.5 | -30.9 | -32.1 | -39.4 | -42.4 |
| SUN | 3.8 | -7.0 | -19.0 | -22.4 | -25.7 | -33.2 | -36.8 |
| PRO | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 |
| SOL | -8.7 | -19.2 | -32.1 | -35.3 | -39.2 | 11.9 | 9.8 |
| KRI | 0.8 | 2.6 | 4.1 | 7.2 | 9.3 | 16.2 | 18.3 |
Accumulated stage time deltas at each split:
14.10.2 Within-Split Duration Deltas
PRO’s delta in time to complete each split section compared to other drivers:
| code | split_1 | split_2 | split_3 | split_4 | split_5 | split_6 | split_N |
|---|---|---|---|---|---|---|---|
| OST | -12.2 | -13.0 | -13.3 | -4.7 | -4.3 | -9.5 | -3.7 |
| GRY | -10.7 | -11.5 | -15.4 | -4.5 | -5.0 | -7.6 | -3.2 |
| LAP | -10.5 | -11.5 | -14.4 | -4.4 | -4.1 | -7.8 | -3.5 |
| CAM | -9.5 | -9.8 | -13.1 | -3.6 | -3.9 | -7.2 | -2.8 |
| BUL | -11.5 | -7.9 | -9.1 | -2.4 | -1.2 | -7.3 | -3.0 |
| SUN | 3.8 | -10.8 | -12.0 | -3.4 | -3.3 | -7.5 | -3.6 |
| PRO | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 |
| SOL | -8.7 | -10.5 | -12.9 | -3.2 | -3.9 | 51.1 | -2.1 |
| KRI | 0.8 | 1.8 | 1.5 | 3.1 | 2.1 | 6.9 | 2.1 |
14.10.3 Within-Split Pace Deltas
| code | split_1 | split_2 | split_3 | split_4 | split_5 | split_6 | split_N |
|---|---|---|---|---|---|---|---|
| OST | -1.66 | -2.10 | -1.84 | -1.20 | -1.15 | -1.29 | -1.75 |
| GRY | -1.46 | -1.85 | -2.13 | -1.15 | -1.34 | -1.03 | -1.51 |
| LAP | -1.43 | -1.85 | -1.99 | -1.12 | -1.10 | -1.06 | -1.65 |
| CAM | -1.29 | -1.58 | -1.81 | -0.92 | -1.05 | -0.98 | -1.32 |
| BUL | -1.57 | -1.27 | -1.26 | -0.61 | -0.32 | -0.99 | -1.42 |
| SUN | 0.52 | -1.74 | -1.66 | -0.87 | -0.88 | -1.02 | -1.70 |
| PRO | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 |
| SOL | -1.19 | -1.69 | -1.78 | -0.82 | -1.05 | 6.92 | -0.99 |
| KRI | 0.11 | 0.29 | 0.21 | 0.79 | 0.56 | 0.93 | 0.99 |
14.11 Driver Report, SS14 - LIN
No stage report for LIN.
14.12 Driver Report, SS14 - SOL
Stage report for SOL.
| Pos | Car | Code | Time (s) | Gap | Diff |
|---|---|---|---|---|---|
| 6 | 23 | OST | -70.5 | -70.5 | 30.0 |
| 7 | 25 | GRY | -67.7 | -67.7 | 2.8 |
| 8 | 22 | LAP | -66.0 | -66.0 | 1.7 |
| 9 | 26 | CAM | -59.7 | -59.7 | 6.3 |
| 10 | 21 | BUL | -52.2 | -52.2 | 7.5 |
| 12 | 24 | SUN | -46.6 | -46.6 | 1.4 |
| 19 | 28 | PRO | -9.8 | -9.8 | 3.4 |
| 23 | 30 | SOL | 0.0 | 0.0 | 2.4 |
| 25 | 31 | KRI | 8.5 | 8.5 | 6.6 |
14.12.1 Rebased Split Times
SOL’s delta at each split compared to other drivers.
| code | split_1 | split_2 | split_3 | split_4 | split_5 | split_6 | split_N |
|---|---|---|---|---|---|---|---|
| OST | -3.5 | -6.0 | -6.4 | -7.9 | -8.3 | -68.9 | -70.5 |
| GRY | -2.0 | -3.0 | -5.5 | -6.8 | -7.9 | -66.6 | -67.7 |
| LAP | -1.8 | -2.8 | -4.3 | -5.5 | -5.7 | -64.6 | -66.0 |
| CAM | -0.8 | -0.1 | -0.3 | -0.7 | -0.7 | -59.0 | -59.7 |
| BUL | -2.8 | -0.2 | 3.6 | 4.4 | 7.1 | -51.3 | -52.2 |
| SUN | 12.5 | 12.2 | 13.1 | 12.9 | 13.5 | -45.1 | -46.6 |
| PRO | 8.7 | 19.2 | 32.1 | 35.3 | 39.2 | -11.9 | -9.8 |
| SOL | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 |
| KRI | 9.5 | 21.8 | 36.2 | 42.5 | 48.5 | 4.3 | 8.5 |
Accumulated stage time deltas at each split:
14.12.2 Within-Split Duration Deltas
SOL’s delta in time to complete each split section compared to other drivers:
| code | split_1 | split_2 | split_3 | split_4 | split_5 | split_6 | split_N |
|---|---|---|---|---|---|---|---|
| OST | -3.5 | -2.5 | -0.4 | -1.5 | -0.4 | -60.6 | -1.6 |
| GRY | -2.0 | -1.0 | -2.5 | -1.3 | -1.1 | -58.7 | -1.1 |
| LAP | -1.8 | -1.0 | -1.5 | -1.2 | -0.2 | -58.9 | -1.4 |
| CAM | -0.8 | 0.7 | -0.2 | -0.4 | 0.0 | -58.3 | -0.7 |
| BUL | -2.8 | 2.6 | 3.8 | 0.8 | 2.7 | -58.4 | -0.9 |
| SUN | 12.5 | -0.3 | 0.9 | -0.2 | 0.6 | -58.6 | -1.5 |
| PRO | 8.7 | 10.5 | 12.9 | 3.2 | 3.9 | -51.1 | 2.1 |
| SOL | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 |
| KRI | 9.5 | 12.3 | 14.4 | 6.3 | 6.0 | -44.2 | 4.2 |
14.12.3 Within-Split Pace Deltas
| code | split_1 | split_2 | split_3 | split_4 | split_5 | split_6 | split_N |
|---|---|---|---|---|---|---|---|
| OST | -0.48 | -0.40 | -0.06 | -0.38 | -0.11 | -8.21 | -0.75 |
| GRY | -0.27 | -0.16 | -0.35 | -0.33 | -0.29 | -7.95 | -0.52 |
| LAP | -0.25 | -0.16 | -0.21 | -0.31 | -0.05 | -7.98 | -0.66 |
| CAM | -0.11 | 0.11 | -0.03 | -0.10 | 0.00 | -7.90 | -0.33 |
| BUL | -0.38 | 0.42 | 0.53 | 0.20 | 0.72 | -7.91 | -0.42 |
| SUN | 1.70 | -0.05 | 0.12 | -0.05 | 0.16 | -7.94 | -0.71 |
| PRO | 1.19 | 1.69 | 1.78 | 0.82 | 1.05 | -6.92 | 0.99 |
| SOL | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 |
| KRI | 1.29 | 1.98 | 1.99 | 1.61 | 1.61 | -5.99 | 1.98 |
14.13 Driver Report, SS14 - KRI
Stage report for KRI.
| Pos | Car | Code | Time (s) | Gap | Diff |
|---|---|---|---|---|---|
| 6 | 23 | OST | -79.0 | -79.0 | 30.0 |
| 7 | 25 | GRY | -76.2 | -76.2 | 2.8 |
| 8 | 22 | LAP | -74.5 | -74.5 | 1.7 |
| 9 | 26 | CAM | -68.2 | -68.2 | 6.3 |
| 10 | 21 | BUL | -60.7 | -60.7 | 7.5 |
| 12 | 24 | SUN | -55.1 | -55.1 | 1.4 |
| 19 | 28 | PRO | -18.3 | -18.3 | 3.4 |
| 23 | 30 | SOL | -8.5 | -8.5 | 2.4 |
| 25 | 31 | KRI | 0.0 | 0.0 | 6.6 |
14.13.1 Rebased Split Times
KRI’s delta at each split compared to other drivers.
| code | split_1 | split_2 | split_3 | split_4 | split_5 | split_6 | split_N |
|---|---|---|---|---|---|---|---|
| OST | -13.0 | -27.8 | -42.6 | -50.4 | -56.8 | -73.2 | -79.0 |
| GRY | -11.5 | -24.8 | -41.7 | -49.3 | -56.4 | -70.9 | -76.2 |
| LAP | -11.3 | -24.6 | -40.5 | -48.0 | -54.2 | -68.9 | -74.5 |
| CAM | -10.3 | -21.9 | -36.5 | -43.2 | -49.2 | -63.3 | -68.2 |
| BUL | -12.3 | -22.0 | -32.6 | -38.1 | -41.4 | -55.6 | -60.7 |
| SUN | 3.0 | -9.6 | -23.1 | -29.6 | -35.0 | -49.4 | -55.1 |
| PRO | -0.8 | -2.6 | -4.1 | -7.2 | -9.3 | -16.2 | -18.3 |
| SOL | -9.5 | -21.8 | -36.2 | -42.5 | -48.5 | -4.3 | -8.5 |
| KRI | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 |
Accumulated stage time deltas at each split:
14.13.2 Within-Split Duration Deltas
KRI’s delta in time to complete each split section compared to other drivers:
| code | split_1 | split_2 | split_3 | split_4 | split_5 | split_6 | split_N |
|---|---|---|---|---|---|---|---|
| OST | -13.0 | -14.8 | -14.8 | -7.8 | -6.4 | -16.4 | -5.8 |
| GRY | -11.5 | -13.3 | -16.9 | -7.6 | -7.1 | -14.5 | -5.3 |
| LAP | -11.3 | -13.3 | -15.9 | -7.5 | -6.2 | -14.7 | -5.6 |
| CAM | -10.3 | -11.6 | -14.6 | -6.7 | -6.0 | -14.1 | -4.9 |
| BUL | -12.3 | -9.7 | -10.6 | -5.5 | -3.3 | -14.2 | -5.1 |
| SUN | 3.0 | -12.6 | -13.5 | -6.5 | -5.4 | -14.4 | -5.7 |
| PRO | -0.8 | -1.8 | -1.5 | -3.1 | -2.1 | -6.9 | -2.1 |
| SOL | -9.5 | -12.3 | -14.4 | -6.3 | -6.0 | 44.2 | -4.2 |
| KRI | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 |
14.13.3 Within-Split Pace Deltas
| code | split_1 | split_2 | split_3 | split_4 | split_5 | split_6 | split_N |
|---|---|---|---|---|---|---|---|
| OST | -1.77 | -2.39 | -2.05 | -1.99 | -1.72 | -2.22 | -2.74 |
| GRY | -1.57 | -2.15 | -2.34 | -1.94 | -1.90 | -1.96 | -2.50 |
| LAP | -1.54 | -2.15 | -2.20 | -1.91 | -1.66 | -1.99 | -2.64 |
| CAM | -1.40 | -1.87 | -2.02 | -1.71 | -1.61 | -1.91 | -2.31 |
| BUL | -1.68 | -1.56 | -1.47 | -1.40 | -0.88 | -1.92 | -2.41 |
| SUN | 0.41 | -2.03 | -1.87 | -1.66 | -1.45 | -1.95 | -2.69 |
| PRO | -0.11 | -0.29 | -0.21 | -0.79 | -0.56 | -0.93 | -0.99 |
| SOL | -1.29 | -1.98 | -1.99 | -1.61 | -1.61 | 5.99 | -1.98 |
| KRI | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 |


Starting udev : [ OK ]
Setting hostname elwood :[ OK ]
Setting up Logical Volume Management : No volume groups found[ OK ]
Checking filesystems
/dev/sda2 : clean, 89739/30457856 files, 2561411/121822976 blocks
/dev/sda1 : clean, 39/76912 files, 43648/307200 blocks[ OK ]
Remounting root filesystem in read-write mode :[ OK ]
Mounting local filesystems :[ OK ]
Enabling local filesystem quotas :[ OK ]
Enabling /etc/fstab swaps :[ OK ]
Entering non-interactive startup
ERROR: Wanpipe configuration file not found :/etc/wanpipe/wanpipe1.conf
Bringing up loopback interface :[ OK ]
Bringing up interface eth0 :
Determining IP information for eth0...done.[ OK ]
Starting auditd :[ OK ]
Starting system logger :[ OK ]
Loading DAHDI hardware modules:
wct4xxp :[ OK ]
wcte43x :[ OK ]
wcte12xp :[ OK ]
wcte13xp :[ OK ]
wct1xxp :[ OK ]
wcte11xp :[ OK ]
r1t1 :[ OK ]
rxt1 :[ OK ]
wctdm24xxp :[ OK ]
wcaxx :[ OK ]
wcfxo :[ OK ]
wctdm :[ OK ]
rcbfx :[ OK ]
wcb4xxp :[ OK ]
wctc4xxp :[ OK ]
xpp_usb :[ OK ]
D: auto '/sys/bus/dahdi_devices/devices/pci:0000:02:08.0'
auto-assign /sys/bus/dahdi_devices/devices/pci:0000:02:08.0
Running dahdi_cfg :[ OK ]
Starting system message bus :[ OK ]
Starting Avahi daemon...[ OK ]
Mounting filesystems :[ OK ]
Starting acpi daemon :[ OK ]
Starting HAL daemon :[ OK ]
Retrigger failed udev event s[ OK ]
Starting Queue callback daemon :[ OK ]
Starting REST applications daemon :[ OK ]
Starting dnsmasq :[ OK ]
Starting sshd :[ OK ]
Starting xinetd :[ OK ]
Starting ntpd :[ OK ]
Starting UPS monitoring :[ OK ]
Starting mysqld :[ OK ]
Starting postfix :[FAILED]
Starting crond :[ OK ]
Starting prosody : Started[ OK ]
Starting fail2ban :[ OK ]
Starting jexec servicesStarting Filesystem event daemon[ OK ]
Fetching FreePBX settings with gen_amp_conf.php..
D: auto '/sys/bus/dahdi_devices/devices/pci:0000:02:08.0'
auto-assign /sys/bus/dahdi_devices/devices/pci:0000:02:08.0
Running dahdi_cfg : [ OK ]
Dahdi Started
SETTING FILE PERMISSIONS...................Done
Removing any dangling symlinks
Dangling symlinks removed
STARTING ASTERISK
Asterisk Started
Starting REST applications daemon: [ OK ]
Stopping fail2ban: REST Applications module is not licensed. [ OK ]
Starting fail2ban: [ OK ]
> ucp-server@ start /var/www/html/admin/modules/ucpnode/node
> node_modules/forever/bin/forever start -m 1 -a -l $ASTLOGDIR/ucp_forever.log -o $ASTLOGDIR/ucp_out.log -e $ASTLOGDIR/ucp_err.log --uid 'ucp' index.js
warn: --minUptime not set. Defaulting to: 1000ms
warn: --spinSleepTime not set. Your script will exit if it does not stay up for at least 1000ms
info: Forever processing file: index.js
Starting Queue callback daemon :[ OK ]
Starting prosody: Prosody is already running with PID 1748 [FAILED]
Starting XMPP Presence State daemon : [ OK ]
Starting /etc/fstab swaps : [ OK ]
Enter PIPBOY CLONE...


cityiq.cli package¶
Submodules¶
cityiq.cli.config module¶
-
cityiq.cli.config.
main
(args)[source]¶ Main entry point allowing external calls
- Parameters
args ([str]) – command line parameter list
cityiq.cli.events module¶
The ciq_events program is used to scrape and process events.
-
class
cityiq.cli.events.
ProgressBar
(*args, **kwargs)[source]¶ Bases:
progress.bar.ShadyBar
-
property
downloaded
¶
-
property
extant
¶
-
property
-
cityiq.cli.events.
make_parser
()[source]¶ Download events and load them into the cache.
The ciq_events program will request events from a CityIQ system, one day at a tim, and cache the results. It will request the events from assets, based on which assets have
eventTypes
with the requested events.Because the program will request events for all of the assets that report an event type and makes one request per day, it can generate very large numbers of requests and take many hours to run. For instance this request:
ciq_events -s 2020-01-01 -e 2020-06-01-01 PKIN PKOUT
generates about 800,000 requests and will take a day to run.
The cityiq module will not cache event requests for the current day or any day in the future.


SECURITY LABEL [ FOR provider ] ON { TABLE object_name | COLUMN table_name.column_name | AGGREGATE agg_name (agg_type [, ...] ) | DATABASE object_name | DOMAIN object_name | EVENT TRIGGER object_name | FOREIGN TABLE object_name FUNCTION function_name ( [ [ argmode ] [ argname ] argtype [, ...] ] ) | LARGE OBJECT large_object_oid | MATERIALIZED VIEW object_name | [ PROCEDURAL ] LANGUAGE object_name | ROLE object_name | SCHEMA object_name | SEQUENCE object_name | TABLESPACE object_name | TYPE object_name | VIEW object_name } IS 'label'
SECURITY LABEL applies a security
label to a database object. An arbitrary number of security
labels, one per label provider, can be associated with a given
database object. Label providers are loadable modules which
register themselves by using the function register_label_provider
.
Note:
register_label_provider
is not an SQL function; it can only be called from C code loaded into the backend.
The label provider determines whether a given label is valid and whether it is permissible to assign that label to a given object. The meaning of a given label is likewise at the discretion of the label provider. PostgreSQL places no restrictions on whether or how a label provider must interpret security labels; it merely provides a mechanism for storing them. In practice, this facility is intended to allow integration with label-based mandatory access control (MAC) systems such as SE-Linux. Such systems make all access control decisions based on object labels, rather than traditional discretionary access control (DAC) concepts such as users and groups.
The name of the object to be labeled. Names of tables, aggregates, domains, foreign tables, functions, sequences, types, and views can be schema-qualified.
The name of the provider with which this label is to be associated. The named provider must be loaded and must consent to the proposed labeling operation. If exactly one provider is loaded, the provider name may be omitted for brevity.
An input data type on which the aggregate function operates. To reference a zero-argument aggregate function, write * in place of the list of input data types.
The mode of a function argument: IN, OUT, INOUT, or VARIADIC. If omitted, the default is IN. Note that SECURITY LABEL ON FUNCTION does not actually pay any attention to OUT arguments, since only the input arguments are needed to determine the function's identity. So it is sufficient to list the IN, INOUT, and VARIADIC arguments.
The name of a function argument. Note that SECURITY LABEL ON FUNCTION does not actually pay any attention to argument names, since only the argument data types are needed to determine the function's identity.
The data type(s) of the function's arguments (optionally schema-qualified), if any.
The OID of the large object.
This is a noise word.
The new security label, written as a string literal; or NULL to drop the security label.


solubility protein Protein OpenUrl Fig sequence using Supplementary prediction CrossRef residues weights acid Science amino Table proteins PSI:Biology SWI Web used sequences properties normalised standard AUC scores coli flexibility soluble cross-validation web Solubility analysis data structural tools Escherichia eSOL insoluble recombinant Expression available correlation surface test Flexibility ROC SWI, expressed optimised random B-factors Bioinformatics Prediction SoDoPE approach calculated score server Harrison S). Structure dataset expression solubility, (Supplementary Molecular Related Solubility-Weighted arithmetic new outperforms residue shown solubility. Learning Proteins Proteins." SWI. Structural composition derived final mean predicting previously scoring set sets v.. (see AUC, Amino Area Biology Curve; However, Machine Methods Operating ROC, Receiver Recombinant Smith Soluble based developed domains existing performance predict rho subsets targets training (Spearman’s (i.e., -fold Analysis Average Coli." FREE GRAVY, Grand Initiative:Biology; Martin Method Nature Open PSI:Biology, Proceedings Python Solubility." Text Vihinen, Wilkinson clusters cross-validation. datasets. determined fusion given line optimisation percentages probability published residues. sequences. <;em>;E. (C) (SWI). ;<;div A). Abstract Acid Acids Aggregation Beckwith C.S.L. CamSol Characteristic; Chen Computing Correlation David Domain Download Engineering Evolution Fusion His-tag Index New Nick Pace Peptide Riikonen Xiao al.’ aromatic associated bootstrap ccSOL coli<;/em>; compared compute correlates count cysteine data-hide-link-title=""> data-icon-position="" denote features figure flexibility, full-length generated global high improve include initial matrix method miscellaneous observed obtained plot predictor propensity recently region regions sequence, sliding step strongly tab tools. tryptophan users window xmlns=";http://www.w.org//xhtml";>;<;span


Our Latest Projects
-
Project Title One
Graphic Design -
Project Title Two
Branding -
Project Title Three
Nature -
Project Title Four
Branding -
Project Title Five
Graphic Design -
Project Title Six
Nature


I am a Healthcare and Medicine focused Data Scientist with a background in Microbiology and Epidemiology. I believe that the advanced analytical capabilities that can be garnered from Machine Learning techniques can help the health profession move into the future.
Bring to the table new analytical approaches and methods and applying them to analysis of Tactical Combat Casualty Care.
Utilize diverse business intelligence and data science resources to analyze and assist one of the largest Health Systems in South Florida.
Worked in biological research lab studying the over-wintering effect of Eastern Equine Encephalitis in various snake species. Lead project to develop cost-effective ELISA assay for for detection of L@ Wuchereria bancrofti based on cDNA techniques for RT-PCR Detection.
Investigated diagnoses and outbreaks of sexually transmitted disease in the greater Tampa area. Performed investigations and took samples in field, provided education and counseling, and worked to bring patients to the care that they needed.
Entered Basic Training in July of 2008, finishing as XO of recruit division. Continued to Hospital Corps "A" School in September of 2008, finishing in January of 2009. Assigned to Navy Operation Support Center (NOSC) Tallahassee, Operation Health Support Unit Jacksonville Detachment J. Remained with DET J from 2009 to 2012, wherein advanced from E-1 to E-5. While at NOSC Tallahassee, worked in the medical department maintaining medical records of nearly 200 sailors, and performing routine immunizations and clinical duties. At E-4 was appointed to be in charge of other reservists as Lead Petty Officer. Completed 1-year mobilizatoin to Norfolk,VA between 2010 and 2011 working in Medical Evaluations department of Navy Mobilization Processing Site. Left Tallahassee amiably to pursue education at USF. Finished 6-year term at NOSC Tampa.
 I am also an avid reader of sci-fi and fantasy novels, a rock-climber, marksman and have been a fully-trained blacksmith for 15 years. .
When forced indoors, I follow a number of sci-fi and fantasy genre movies and television shows, I am an aspiring chef, and I spend a large amount of my free time exploring the latest technology advancements in the ever-expanding world of data science.


---
layout: page
title: Reading etc.
permalink: /reading/
---
2022 notable reads:
Fiction
-
Colm Toibin - The Magician
-
Cormac McCarthy - The Road/Stella Maris
-
John Fowles - The Magus
-
Olga Tokarczuk - The Books of Jacob
-
Frankenstein - Mary Shelley
Non-Fiction
-
Iain McGilchrist - The Master and his Emissary/The Matter with Things
-
Johann Peter Eckermann - Conversations with Goethe
-
Thomas Halliday - Otherlands
2022 notable films:
Films
-
Citizen Kane
-
Belfast
-
The Father
-
Lawrence of Arabia
-
The Banshees of Inisherin
-
Living
2021 notable reads:
2020 notable reads:


Money Play. How should Red play 54?
pips Red=119 White=184
(CorrectAnswer= 0/0, ErrorScore= 0)
When on offence, concentrate on offence.
While this might seem to be the time to get the rear checkers moving the correct idea is to concentrate on making the 3-pt. The right play is 13/9, 13/8.
Any play involving moving a back checker is an error. They will escape in due course, hopefully picking up the blot on White’s bar-point along the way.
While this might seem to be the time to get the rear checkers moving the correct idea is to concentrate on making the 3-pt. The right play is 13/9, 13/8.
Any play involving moving a back checker is an error. They will escape in due course, hopefully picking up the blot on White’s bar-point along the way.
1. Cubeful 2-ply 13/9 13/8 Eq.: +1.192 0.741 0.603 0.023 - 0.259 0.058 0.004 2. Cubeful 2-ply 21/16 11/7 Eq.: +1.186 (-0.005) 0.747 0.592 0.022 - 0.253 0.061 0.004 3. Cubeful 2-ply 13/8 11/7 Eq.: +1.172 (-0.019) 0.735 0.592 0.023 - 0.265 0.062 0.004 4. Cubeful 2-ply 21/17 13/8 Eq.: +1.168 (-0.024) 0.738 0.583 0.021 - 0.262 0.062 0.004 5. Cubeful 2-ply 21/16 13/9 Eq.: +1.162 (-0.029) 0.742 0.592 0.018 - 0.258 0.070 0.008


{% extends 'projects/base_projects.html' %} {% block actual_content %}
My official title at SharpScholar was CTO. Like many startups this is the default role that inexperienced technical co-founders take on. Now I know that this was the wrong job title, though that didn't really impact the work I did. At a high level, I took on two key roles: Product Manager and Full Stack Developer. Remember, all this is in hindsight. When I first decided to this, my approach was far more simplistic and surface level. I saw a team with a sense of an idea that need a technical lead to execute.
For the majority of the first three months, I just worked on developing the software.  My team was then able to push this product out to various universities and professors and thus begin the cycle of learning about product management, development, marketing, and business. While a lot of the business lessons learnt at SharpScholar came as result of being the education field, a lot of the product side learns happened in a broader sense.
As time went by and the product became more stable, time came for me to grow beyond a full stack developer. I now was in a position to give the product a sense of direction. And there were many possibilities. From analytics, to mashware, to personalized learning, to peer learning we had many possible directions we could have gone in. As such my role in the company evolved into one that I was quite unfamiliar with but one I relished.
At this stage of the company, I was able to better articulate what my responsibilities were:
Set the vision for the product as the company evolves. Translate the abstract vision of “Empowering scholars around the world” to meaningful and understandable short term and long term visions. Champion where the product will go as a result.
Translate user market research, sales reports, and user behaviour into tangible set of specifications of product features, goals and visions.
Top Level: Long Term and Short Term Product Vision
Middle Level: Monthly product roadmap and associated set of projects
Bottom Level: Weekly updates to the team
Software Development
Quality Assurance
Security
Data Analytics on User Behaviour
Of course my focus depended highly on what the startup needed at the time. If the product was coming under fire due to technical issues, I would put on my Software developer/QA hat and get to coding. If there was some breathing space, then I would start looking to build process and systems that would allow me to understand users better, set product roadmaps, and plan/execute for the future.
In theory this approach works well but it suffered in multiple ways. First, it was an unfocused and reactive approach. No software is bug free, especially one built by one developer with minimal experience. I was constantly reacting to fires rather than building the company I wanted to be building. As soon as I gained some momentum in setting direction, I would be called away to solve existing issues. As such this result in considerable mental fatigue, leading to the second issue. Since I was acting as both the product manager and developer, I was often unable to keep the two separate. For instance, instead of fully specing a feature and understanding the story behind it I would jump into coding and try to get it done. Even more so, I should have been able to see the technical debt that was being built up as a result. Failing to balance the two roles and viewpoints, caused me to perform both of them poorly.
As I write this series of posts to breakdown SharpScholar, I aim to build up insights on how to potentially do it better. I have recently read Systems and processes to build products people love and look forward to using my experience to create a process I will take moving forward.


Become a Git Master
In Class
- Version control: the big picture (slides)
- Git commands and metaphors (slides)
- Exercise Creating a Personal Git Repository
- Under the Hood (slides)
- Exercise Smashing Git Repositories Into Each Other
- Team Workflow, Rebasing, and Good Behavior (Slides)
- Working over Github
- Exercise Pull Requests and Rebasing
- Exercise Adding Custom Hooks
The last exercise is pretty do-it-yourself. If we don't have time in class, hooks are a very cool feature: take the 10 minutes yourself to try it out!
See Also
- The Git Website
- Pro Git An excellent book that is free online.
- Github
- Awesome Git Visualization
Geek Cred
hash bang slash bin slash bash
Defined on Everything2 as:
The "accepted" pronunciation of invoking the Bourne Again SHell, or Bash. #!/bin/bash
You used that incantation in the git hooks exercise. In general, when you
want a file in a *nix system to be executable, change it's permissions to +x
(aka chmod u+x
or chmod a+x
) and then add a special
line at the top that tells the shell how to invoke the necessary interpreter.
#!
means "run" and the rest of the line is the absolute path to
the program that will interpret the rest of the file.
So a bash script traditionally uses hash bang slash bin slash bash or
#!/bin/bash
, whereas a python script might use
#!/usr/bin/python
You can typically find out what the absolute path for a command is by
running which CMD
(as in, which python
)
Class List
- Introduction (W 2/6)
- Bootup (M 2/11)
- Become a Git Master (W 2/13)
- Everything you ever wanted to know about Web Requests (T 2/19)
- Design Studio (W 2/20)
- Debugging (M 2/25)
- Design Studio (W 2/27)
- Open Source Business Models (M 3/3)
- Design Studio (W 3/6)
- Work Day (W 3/11)
- Design Studio (W 3/13)
- Quantifying Code (M 3/18)
- Design Studio (W 3/20)
- Spring Break (M 3/25 & 27)
- Quantifying Users (M 4/1)
- Work day (W 4/3)
- Remote Collaboration (M 4/8)
- Design Studio (W 4/10)
- No class - Patriot's Day (M 4/15)
- Design Studio (W 4/17)
- Work Day (M 4/22)
- Design Studio (W 4/24)
- No class - CHI (M 4/29 and W 5/1)
- Final Presentations (M 5/6)
- Final Presentations (W 5/8)
- No class - WWW (M 5/13 and W 5/15)
- *Note: Report due W 5/15*


![DashboardHub Logo](https://cdn.dashboardhub.io/logo-horizontal-std.svg)
[The Pulse of Your CI & CD Pipeline](https://dashboardhub.io)
## Problem
![The problem](https://user-images.githubusercontent.com/624760/47609030-6c4b6a80-da2f-11e8-9c24-866d8f26a466.jpg)
Note: Everyone who has worked in software development is aware of the frustrations and wasted time surrounding miscommunication
and slow relay of information about new versions and delays, to the extent that often by the time the information reaches
all members of the team it is outdated.
## Solution
![image](https://user-images.githubusercontent.com/624760/47609036-8f761a00-da2f-11e8-9dcd-7e1f9d974ff5.jpg)
Note: DashboardHub solves this problem so that your team can focus on creating the best possible product with no unnecessary
hindrances. By providing a user interface, for members of the team and managers, we provide an easy monitoring system,
with detail and a comprehensive overview. The display shows the stage at which the team is, so development, test and
production, and the version on which they are currently working. The performance of each version is also shown.
## USP
![USP](https://user-images.githubusercontent.com/624760/47609052-e0860e00-da2f-11e8-8a81-5d7c528be849.jpg)
Note:
What makes DashboardHub unique and necessary compared to other providers of a similar service is that we keep up-to-date
with frequent releases, removing the increased miscommunication surrounding it.
## Coming Soon!
### Beta Testing
Note: Currently the product is only available to select customers but we are working hard
on the next phase and once that is released it will be open for your use.
## Packages & Features
Simple packages
| Package | Features | Price |
| :--- | :--- | :--- |
| Starter | Unlimited public environments, unlimited releases, 1 monitor per environment, badges, unlimited followers, unlimited notifications | Free |
Note: We have three packages, customised for the use of single developers, small teams and large teams.
## Packages & Features
Simple packages
| Package | Features | Price |
| :--- | :--- | :--- |
| Professional | 5 private environments, Scheduled releases | £10 / month / per environment |
Note: We have three packages, customised for the use of single developers, small teams and large teams.
## Packages & Features
Simple packages
| Package | Features | Price |
| :--- | :--- | :--- |
| Enterprise | Unlimited private environments, export data, user management | £600 / month |
Note: We have three packages, customised for the use of single developers, small teams and large teams.
![Team](https://user-images.githubusercontent.com/624760/47607747-dbb75f00-da1b-11e8-958d-1429b4ac21dd.png)


Associates web names with the corresponding addresses. It's like a phonebook of the Internet. Devices uses DNS to lookup domain names and get the associated IP addresses. DNS servers are distributed by zones, by hierarchy and by .net, .org, .gov etc
We access information online through domain names, like google.com or whocares.com. Web browsers interact through Internet Protocol (IP) addresses. DNS translates domain names to IP addresses so browsers can load Internet resources.
Each device connected to the Internet has a unique IP address which other machines use to find the device. DNS servers eliminate the need for humans to memorize IP addresses such as <IP_ADDRESS> (in IPv4), or more complex newer alphanumeric IP addresses such as 2400:cb00:2048:1::c629:d7a2 (in IPv6).
DNS are designed to be on open public communication protocol and therefore are susceptible to hacks, for example, DNS spoofing in which IP address of a reliable/trusted website is assigned to phishing website.
Source CloudFlare


---
layout: base
title: Wistia Basics
category: Wistia Basics
---
Wistia Basics
If you are getting started, or just want a little refresher, the Wistia
Basics series is just what you need. Join Chris and Jeff as they take
you through the key features and workflows of Wistia, to make sure you
get the most out of your account.


{% extends 'layout.html' %} {% block pageTitle %} NHS login – Invite already accepted {% endblock %} {# {% block beforeContent %} {{ breadcrumb({ href: "/", text: "Home" }) }} {% endblock %} #} {% block content %}
You do not need to respond to this invite, as you have already accepted a previous one. This means you can already act on behalf of {{ data.primaryUserFirstName or 'Alice' }} {{ data.primaryUserLastName or 'Smith' }} within stepWell.
You can go directly to stepWell and log in with your NHS login to act on {{ data.primaryUserFirstName or 'Alice' }}'s behalf.
Reference: CID9102


A web app which finds a convenient and fair meeting point for two people
A group project building a copy of Facebook.
A solo project building a web application for a ten-pin bowling scorecard
A solo tech test modelling bank transactions.


Model component developers¶
A model component developer develops new components in order to provide novel features for a model.
This tutorial guides the reader through the implementation of a
new model component using the seven dwarfs model
as an example.
Developing a new model component¶
At first,
Entities and process taxonomy¶
Determine necessary entity types and process taxa
Create model component files from template¶
Copy necessary template files. The structure of a model component is explained here.
Create attributes and methods of entites and taxa¶
Code snippet 1 from culture.py
:
class Culture (I.Culture):
"""Culture process taxon mixin for exploit_social_learning."""
# standard methods:
def __init__(self,
*,
last_execution_time=None,
**kwargs):
"""Initialize the unique instance of Culture."""
super().__init__(**kwargs)
self.last_execution_time = last_execution_time
self.consensus = False
# process-related methods:
def social_update(self, t):
"""Execute the social update.
Parameters
----------
t : float
time
Returns
-------
"""
...
def reconnect(self, agent_i, agent_j):
"""Reconnect agent_i from agent_j and connect it to k.
Disconnect agent_i from agent_j and connect agent_i
to a randomly chosen agent_k with the same strategy,
agent_i.strategy == agent_k.strategy.
Parameters
----------
agent_i : Agent (Individual or SocialSystem)
agent_j : Agent (Individual or SocialSystem)
Returns
-------
"""
...
def change_strategy(self, agent_i, agent_j):
"""Change strategy of agent_i to agent_j's.
Change the strategy of agent_i to the strategy of agent_j
depending on their respective harvest rates and the imitation tendency
according to a sigmoidal function.
Parameters
----------
agent_i : Agent (Individual or SocialSystem)
Agent i whose strategy is to be changed to agent j's strategy
agent_j : Agent (Individual or SocialSystem)
Agent j whose strategy is imitated
Returns
-------
"""
...
def get_update_agent(self):
"""Return the agent with the closest waiting time.
Choose from all agents the one with the smallest update_time.
Returns
-------
"""
...
def set_new_update_time(self, agent):
"""Set next time step when agent is to be called again.
Set the attribute update_time of agent to
old_update_time + new_update_time, where new_update_time is again
drawn from an exponential distribution.
Parameters
----------
agent : Agent (Individual or SocialSystem)
The agent whose new update_time should be drawn and set.
Returns
-------
"""
...
def check_for_consensus(self):
"""Check if the model has run into a consensus state.
The model is in a consensus state if in each connected component
all agents use the same strategy. In this case, there will be no more
change of strategies since the agents are only connected to agents
with the same strategy.
Returns
-------
consensus : bool
True if model is into consensus state, otherwise False
"""
...
def step_timing(self,
t):
"""Return the next time step is to be called.
This function is used to get to know when the step function is
to be called.
Parameters
----------
t : float
time
Returns
-------
"""
...
Specifying processes¶
At the end of the taxon file, the relevant processes need to be specified.
In the EXPLOIT example, there is only one process implemented in the culture
taxon. It is a step
process which incorporates one update:
processes = [Step('Social Update is a step function',
[I.Culture.acquaintance_network,
I.Individual.strategy, I.Individual.update_time,
I.Culture.consensus],
[step_timing, social_update])]
Import ./implementation files in model.py
file.
Adjusting interface file and model file¶
# entity types:
class World(object):
"""Define Interface for World."""
contact_network = Variable('contact network', 'network')
agent_list = Variable('list of all agents', 'all agents in network')


--- sort_order: 230 tei_id: rdx_v6wpq.p.idm140456962097792 annotation_count: 0 images: small-thumbnail: https://readux.ecds.emory.edu/books/readux:v5mxs/pages/readux:v6wpq/mini-thumbnail/ json: https://readux.ecds.emory.edu/books/readux:v5mxs/pages/readux:v6wpq/info/ full: https://readux.ecds.emory.edu/books/readux:v5mxs/pages/readux:v6wpq/fs/ page: https://readux.ecds.emory.edu/books/readux:v5mxs/pages/readux:v6wpq/single-page/ thumbnail: https://readux.ecds.emory.edu/books/readux:v5mxs/pages/readux:v6wpq/thumbnail/ title: Page 226 number: 226 permalink: "/pages/226/" ---


One dead, four seriously injured as dumper truck flips over in Karachi underpass | Pakistan - Geo.tv
by Kashif MushtaqKARACHI: At least one person died and four others seriously injured as a dumper truck flipped over Sunday in an underpass near the metropolis' Drigh Road, rescue authorities confirmed.
Rescue officials said the accident had caused a worrisome traffic jam that posed a challenge for the ambulances to arrive at the site of the accident. Further, heavy machinery had been summoned to remove the dumper truck from the underpass, police added.
The deceased was identified as a two-year-old, rescue sources said, adding that a motorcycle had come under the dumper truck. The body, as well as the wounded people, were shifted to the Jinnah Postgraduate Medical Centre (JPMC).


The LatLongStereo shader is added to a Maya scene using the ArnoldDomemaster3D Shelf tool.
When you run the LatLongStereo shelf tool it adds a custom ArnoldLatLongStereo camera rig to the scene that has the left and right cameras set up automatically. The left camera LatLongStereo attributes are used to drive the stereoscopic settings for both the left and right cameras. This means you only have to change the Zero Parallax Distance or Camera Separation setting in one place.
To change the LatLongStereo attributes, select the camera in your scene. Open the attribute editor and switch to the camera's shape node. The lens shader is listed in the Arnold section.
The current version of the Arnold Domemaster3D shaders (as of 2015-02-23) are a development build. At this point in time there is no easy way to create screen space texture maps using Arnold's MtoA and SItoA render nodes. This means a solution has to be developed inside the Domemaster3D shaders that will remap an existing texture map into screen space coordinates.
The LatLongStereo shader generally works fine. The only thing to note is that there is no way to feather out the stereo effect in the zenith and nadir zones using the separation map attribute. The LatLongStereo shader should be rendered with a 2:1 aspect ratio to avoid vertically over-rendering the scene's FOV angle.
Also the LatLongStereo shader expects a 2:1 aspect ratio render resolution for the output. The code to compensate for a non 2:1 rendered aspect ratio hasn't been finished yet so you will experience over-rendering of the FOV if you render to an image with a 1:1 aspect ratio.
Camera: Choices are Center/Left/Right. Selects the camera to use for rendering. Center skips 90% of the calculations and gives you a highly optimized standard latlong image.
Field of View Vertical: Controls the vertical FOV angle (in degrees) of the rendered Latitude/Longitude image.
Field of View Horizontal: Controls the horizontal FOV angle (in degrees) of the rendered Latitude/Longitude image.
Zero Parallax Distance (focus plane): This is the distance at which the left and right camera's line of sight converges.
Camera Separation: The initial separation of the left and right cameras.
Zenith Mode: This attribute allows you to adjust the LatLongStereo
lens shader to work with either a horizontal orientation (Zenith Mode OFF), or an upwards / vertical orientation (Zenith Mode ON) that lines up with the upright view orientation of the Domemaster Stereo Shader
shaders.
Separation Map: A value between 0-1 that multiples the Camera Separation. This attribute is meant to be used with a grayscale texture mapped to the screen space. It's used to control the amount of 3D effect, and eliminate it where desired.
Flip X: Flips the view horizontally
Flip Y: Flips the view vertically
Exposure: This attribute allows you to control the overall brightness of the final rendered frame.
You can control the stereoscopic effect seen in the LatLongStereo shader with the help of control texture maps. The LatLong Stereo
shader's Separation Multiplier attribute supports control texture mapping. The images have to be applied using screen space coordinates.


Information Gathering
In an engagement the goal of information gathering is to gain an understanding of the application from an outsiders perspective.
Target Validation
Tool Description
Whois A protocol for searching internet registration databases based on RFC 3912 for domain names, IPs, autonomous systems, etc.
Dig dig (domain information groper) is a network administration command-line tool for querying Domain Name System (DNS) servers.
DNSRecon Tool for automating many DNS enumeration techniques maintained by darkoperator
Domain Registration
Use the following steps to validate ownership of a target:
- Whois the target domains/hosts. whois example.com
- Resolve the IP addresses for the target domains/hosts. dig +short example.com
- Whois the IP addresses. whois <IP_ADDRESS>
- Analyze the results.
Results could be mixed depending on whether or not the target is using whois privacy protection.
DNS Interrogation
I like to start off with https://dnsdumpster.com/ which is a great online tool for getting a quick overview of a target domain’s internet footprint via DNS.
- Forward Lookups
- dig +nocmd example.com A +noall +answer
- dig +nocmd example.com NS +noall +answer
- dig +nocmd example.com MX +noall +answer
- dig +nocmd example.com TXT +noall +answer
- dig +nocmd example.com SOA +noall +answer
- ...
- dig +nocmd example.com ANY +noall +answer (This rarely works)
- Reverse Lookups
- dig -x <IP_ADDRESS>
- dig -x <IP_ADDRESS>
Testing for Zone Transfers
Zone transfers are a DNS transaction used to replicate records between DNS servers. It’s rare to find a DNS server these days that allow a zone transfer, but it’s something you should check. If you succeed in performing a zone transfer, you stand to gain access to all of the records of a domain.
- Example using
- dig -t NS zonetransfer.me +short
- dig -t AXFR zonetransfer.me @nsztm1.digi.ninja
- dig -t AXFR zonetransfer.me @nsztm2.digi.ninja
- DNSRecon is useful for automating many of the DNS enumeration tasks above, and can often find extra information that may have been missed.
-
OSINT Harvesting
Tool Description
Recon-NG Open source reconnaissance framework created by Tim 'Lanmaster53' Tomes, maintained by a community of developers on http://recon-ng.com/
Maltego Maltego is an interactive data mining tool that renders directed graphs for link analysis.
theharvester theHarvester is a tool for gathering e-mail accounts, subdomain names, virtual hosts, open ports/ banners, and employee names from different public sources
I thought about including a detailed section on OSINT in this cheat sheet, but at this time I’ve decided not to since I believe it deserves its own cheat sheet (perhaps later down the line).
Instead I’d like to point you towards some excellent resources on OSINT that I think all pentesters should familiarize themselves with.
- Michael Bazzell
-
- Google Dorking
-


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I'm Alex Matheson, a Bachelor of Software Engineering student at RMIT.
I've learnt to love programming over the course of the last four years, creating projects and games in my spare time.


|
#include <humarobotics-wifiblock.h>
Data Fields | |
| string | wifi_ssid |
| string | wifi_pass |
| tIPaddr | IP |
| tIPaddr | netmask |
| tIPaddr | gateway |
| ubyte | wifi_type |
Definition at line 162 of file humarobotics-wifiblock.h.
defrault gateway to use
Definition at line 168 of file humarobotics-wifiblock.h.
IP address to use
Definition at line 166 of file humarobotics-wifiblock.h.
netmask to use
Definition at line 167 of file humarobotics-wifiblock.h.
| string wifi_pass |
WiFi network pass
Definition at line 165 of file humarobotics-wifiblock.h.
| string wifi_ssid |
SSID (network name) to connect to
Definition at line 164 of file humarobotics-wifiblock.h.
| ubyte wifi_type |
Crypto used on the network, see HRWB_SECURITY_* for options
Definition at line 169 of file humarobotics-wifiblock.h.


Weatherforcast for the next 24 hours:
Plenty of Sunshine
Wind:
7km/h SSE
; Ther:
21°C
; Hum:
82%
Enonic News JAB
Oslo, Norway -
Thursday August 30, 1978
- Seven Pages


The nonprofits we select typically utilize any funds they receive to simply continue their mission. They are operating on very limited budgets so, while a new website could be a game changer for their business, the funding just isn't available. Our mission is to help these organizations extend their reach and expand the impact they have on their communities!
We want to bring people together to increase their strength and power. We are united in two goals: 1. Provide nonprofits with quality web sites so they can continue generating measurable changes in their communities. 2. Present web developers, both new and experienced, with opportunities to build upon their skills while contributing to the positive impact nonprofits make in their communities.
We want to keep things as simple as possible. Anyone can submit the name of a nonprofit. We will ask you a few questions about the organization and, if accepted, it will be added to our project list. Developers looking to sharpen their skills and gain real world experience, can view all open projects and request to work on a project. We ask the developer a few questions about their skills and experience. We then make sure the project they are interested in is available and then we let them do what they do best! When the site is ready, we contact the nonprofit organization to let them take a look at what we've put together for them.
Each team member has a differnt story of how they started with Hope to Code. Some of us have been involved with nonprofits and some of us are involved in the web design industry. We come from very unique backgrounds are are united by a desire to build quality websites for inspirational nonprofits and provide developers with an opportunity to gain valuable experience working on live projects. This will allow our developers to enhance their skill sets and their careers.
Know of a nonprofit organization that could benefit from a new website? Let us know. We would love to add their site to our projects for developers to review.


In Ghana, according to Akan culture, once a child is born, their first name they are given depends entirely on the day of the week they have been born. For every day of the week, there is a special specific name which you are given; of course depending on your gender also ;). In this application, we will take you on a trip to Ghana to find out what your Akan name would be. If you do not know which day you were born, worry not, just fill in the details as requested below and the app will do it all for you.


SudoVirtualCardsOperationQueue
open class SudoVirtualCardsOperationQueue : OperationQueue
Subclass adding behaviour around SudoVirtualCardsOperation
in a queue.
-
Adds the specified operation to the receiver.
If the operation is a
SudoVirtualCardsOperation
, the operation will have its conditions and extra functionality, such as delegation.Declaration
Swift
open override func addOperation(_ op: Operation)
Parameters
op
The operation to be added to the queue.
-
Adds the specified operations to the queue.
See
SudoVirtualCardsOperationQueue.addOperation(:)
for more details.Important
If using
waitUntilFinished
, please ensure the queue is not suspended, or the call will block.Declaration
Swift
open override func addOperations(_ ops: [Operation], waitUntilFinished wait: Bool)
Parameters
ops
The operations to be added to the queue.
wait
if true, will block and wait until all operations that are passed in have completed.


innosabi developer challenges
All challenges can be found in the assignment folder
Slider
(
Task.md
)
Highlight
(
Task.md
)
BtnProgress
(
Task.md
)
Proxy (
Task.md
)


Hiring
“For every open job on your team, you need to spend one hour a day on recruiting-related activities. Cap that investment at 50% of your time. “
- Rands
I strongly believe that hiring is a critical focus area for a design leader. I’ve been part of hiring panels since 2015. I’ve seen companies usually do not focus on hiring flows leading them to have a bad experience for interviewing candidates. I gave a short talk about hiring designers at a friend’s startup in 2018.
 If you need to stand out, you need to write a good JD. Hire a design consultant to help you out with this if you are hiring the first designer for your startup.
- Don’t let a portfolio be a barrier for applying For entry level roles, I feel a portfolio acts like your resume but when you start hiring for senior designer roles you may want to broaden the application criteria. Most designers I know do not have an updated portfolio and this prevents them from applying to your startup if they are interested.
- Customize application form to allow folks to upload a digital document The tool you use to run your hiring needs to be flexible to cater to your design hiring needs. At Gojek, we used Lever and for the longest time we did not have a way for designer applicants to upload a pdf portfolio. Binoy and I sat and figured out how to add it to the application form, however for internal referrals we were not able to enable it as Lever doesnt let you customize the form.
- Keep the face-to-face rounds short In the interest of everyone’s time, its best if you can earmark a particular day of the week for interviews and schedule all the rounds on that day for candidates. For this to work, your screening rounds need to be well designed so as to not overload your panelists.
- Scaling the process If you have a lot of reqs to fill, you will need to get others to take part in the interview process. Playbooks and evaluation templates help scale the process while maintaining quality.
Previous post: Gojek
Next post: Learnings from going International


What is Lorem Ipsum Lorem Ipsum is simply dummy text of the printing and
typesetting industry Lorem Ipsum has been the industry's standard dummy text ever since the 1500s.
Private Transport
Lorem ipsum dolor sit amet, consec tetur adip iscing elit. Nam
semfelbus vel.
Destinations
Lorem ipsum dolor sit amet, consec tetur adip iscing elit. Nam
semfel um, facilisis non dapibus vel.
Great Hotels
Lorem ipsum dolor sit amet, consec tetur adip iscing elit. Nam
semfel um, facilisis non dapibus vel.
Fast Booking
Lorem ipsum dolor sit amet, consec tetur adip iscing elit. Nam
semfel um, facilisis non dapibus vel.
Humble beginnings
Lorem ipsum dolor sit amet, consectetur adipiscing elit. Morbi et
pretium nibh. Nullam eget accumsan, sagittis ligula. Aliquam erat volutpat nuncum. Aene ac
lorem id orci hendrerit facilisis sed sed leo ium. Vestibulum dignissim at libero pretium.
Babatope
Meet our Team
Managing Partner
Toyin Omo
Managing Partner
Bolu Omoniyi
Managing Partner
Mark Abah
Managing Partner
Serah John
Managing Partner
Mark Abah
Have a Question ?
In case you haven’t found the answer to your question, please
feel free to contact us, our customer support will be happy to help you.


A passionate Developer having experience in Web Development and
wants to develop sustainable and scalable social and technical systems to create impact in our society.
I’m a young Kenyan visionary in tech currently
a software development student in Moringa School.
I’m passionate about understanding and communicating the connection between tech and humans; we are tech and tech is us.
As a young African female in tech, I believe in working towards a more educated and innovative Africa
I want to be a part of the team that ensures that the future generation of African leaders in various industries have the skills and resources
they need to revolutionize the continent for the better.
This is why I became part of Moringa community.
The journey of a thousand miles begins with a ("Hello World!);
I LOVE ATTENDING SOCIAL EVENTS WHEN I AM NOT STARING AT MY TERMINAL!
I Also read a book once in a while.
Fullname: Felista Gatwiri Kiriinya Birth Date: November 15, 2001 State of Origin: Kenya Occupation: Student, Software Developer<EMAIL_ADDRESS>This is a web app for a pizza restaurant that allows you to order your pizza done using HTML, CSS, Javascript and JQuery
This web app allows you to generate your designated Akan Name using your birth date.
A simple to do app done using HTML CSS and Javascript
This is a landing page for delani studio done using JQuery, HTML and CSS
I would love to hear from you, you can contact me by filling the form below. I am always ready to reply and give assistance where needed. Thanks!


While scale3d(0,0,0) internally computes to matrix3d(0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1)
Setting matrix3d(0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1) yields on chrome to a non-centric zoom and does not scale in safari at all.
Scientific number are not allowed in CSS - but they should be.


DepthwiseConv2D
Depthwise separable 2D convolution.
Inherits From: Conv2D
tf.compat.v1.keras.layers.DepthwiseConv2D
tf.compat.v2.keras.layers.DepthwiseConv2D
Depthwise Separable convolutions consists in performing
just the first step in a depthwise spatial convolution
(which acts on each input channel separately).
The depth_multiplier
argument controls how many
output channels are generated per input channel in the depthwise step.
kernel_size
: An integer or tuple/list of 2 integers, specifying the
height and width of the 2D convolution window.
Can be a single integer to specify the same value for
all spatial dimensions.strides
: An integer or tuple/list of 2 integers,
specifying the strides of the convolution along the height and width.
Can be a single integer to specify the same value for
all spatial dimensions.
Specifying any stride value != 1 is incompatible with specifying
any dilation_rate
value != 1.padding
: one of 'valid'
or 'same'
(case-insensitive).depth_multiplier
: The number of depthwise convolution output channels
for each input channel.
The total number of depthwise convolution output
channels will be equal to filters_in * depth_multiplier
.data_format
: A string,
one of channels_last
(default) or channels_first
.
The ordering of the dimensions in the inputs.
channels_last
corresponds to inputs with shape
(batch, height, width, channels)
while channels_first
corresponds to inputs with shape
(batch, channels, height, width)
.
It defaults to the image_data_format
value found in your
Keras config file at ~/.keras/keras.json
.
If you never set it, then it will be 'channels_last'.activation
: Activation function to use.
If you don't specify anything, no activation is applied
(ie. 'linear' activation: a(x) = x
).use_bias
: Boolean, whether the layer uses a bias vector.depthwise_initializer
: Initializer for the depthwise kernel matrix.bias_initializer
: Initializer for the bias vector.depthwise_regularizer
: Regularizer function applied to
the depthwise kernel matrix.bias_regularizer
: Regularizer function applied to the bias vector.activity_regularizer
: Regularizer function applied to
the output of the layer (its 'activation').depthwise_constraint
: Constraint function applied to
the depthwise kernel matrix.bias_constraint
: Constraint function applied to the bias vector.4D tensor with shape:
[batch, channels, rows, cols]
if data_format='channels_first'
or 4D tensor with shape:
[batch, rows, cols, channels]
if data_format='channels_last'.
4D tensor with shape:
[batch, filters, new_rows, new_cols]
if data_format='channels_first'
or 4D tensor with shape:
[batch, new_rows, new_cols, filters]
if data_format='channels_last'.
rows
and cols
values might have changed due to padding.
__init__
__init__( kernel_size, strides=(1, 1), padding='valid', depth_multiplier=1, data_format=None, activation=None, use_bias=True, depthwise_initializer='glorot_uniform', bias_initializer='zeros', depthwise_regularizer=None, bias_regularizer=None, activity_regularizer=None, depthwise_constraint=None, bias_constraint=None, **kwargs )


?Jfafc
Botanical
Garden
lt07150
"""
Herb
Brasil.
Regnell.
Musei
bot.
Stockholm.
Plantū
Itineris
Regnelliani
III.
N:o...........
......
Sf?
-sr>
,r.
Cuba:
prov.
^
/
9
/jfc.
1607120
Legend -
Level of confidence that token is an accurately-transcribed word
extremely low
very low
low
undetermined
medium
high
very high


Fonts assets are font files (WOFF, WOFF2) that will be directly referenced by a page via its URL.
[NWAYO_ROOT]/components/[NAME]/assets/fonts/
.[BUILD_ROOT]/fonts/[NAME]/
.Files are only copied since optimization has to be done manually.
In scripts, the path to these files can be access via app.path.fonts
.
In styles, these fonts can be accessed via the fonts mixin.
Fonts are selected for build via the assets
property of the bundle file.
These tasks interact with the fonts:


How it works
What makes CCore valuable? It's the official source for official information.
{% include components/stacked-content-box-fixed-size.html
heading="Curated content"
definition="Professional teams write and maintain CCore content, keeping it up to date and usable."
iconName="edit"
altText=""
%}
{% include components/stacked-content-box-fixed-size.html
heading="Single-sourcing"
definition="Each piece of CCore content lives in a central repository—no more conflicting or inconsistent information."
iconName="publish"
altText=""
%}
{% include components/stacked-content-box-fixed-size.html
heading="Access with APIs"
definition="Developers use CCore APIs to get exactly the content needed for a website or application."
iconName="access"
altText=""
%}
{% include components/stacked-content-box-fixed-size.html
heading="A reliable content experience"
definition="The same official information from main Indiana University websites is shared throughout the digital campus."
iconName="done"
altText=""
%}


public interface TaskScheduler
TaskSchedulerImpl
.
This interface allows plugging in different task schedulers. Each TaskScheduler schedules tasks
for a single SparkContext. These schedulers get sets of tasks submitted to them from the
DAGScheduler for each stage, and are responsible for sending the tasks to the cluster, running
them, retrying if there are failures, and mitigating stragglers. They return events to the
DAGScheduler.| Modifier and Type | Method and Description |
|---|---|
scala.Option<String> |
applicationAttemptId()
Get an application's attempt ID associated with the job.
|
String |
applicationId()
Get an application ID associated with the job.
|
void |
cancelTasks(int stageId,
boolean interruptThread) |
int |
defaultParallelism() |
void |
executorDecommission(String executorId,
org.apache.spark.scheduler.ExecutorDecommissionInfo decommissionInfo)
Process a decommissioning executor.
|
boolean |
executorHeartbeatReceived(String execId,
scala.Tuple2<Object,scala.collection.Seq<AccumulatorV2<?,?>>>[] accumUpdates,
BlockManagerId blockManagerId,
scala.collection.mutable.Map<scala.Tuple2<Object,Object>,org.apache.spark.executor.ExecutorMetrics> executorUpdates)
Update metrics for in-progress tasks and executor metrics, and let the master know that the
BlockManager is still alive.
|
void |
executorLost(String executorId,
org.apache.spark.scheduler.ExecutorLossReason reason)
Process a lost executor
|
scala.Option<org.apache.spark.scheduler.ExecutorDecommissionState> |
getExecutorDecommissionState(String executorId)
If an executor is decommissioned, return its corresponding decommission info
|
void |
killAllTaskAttempts(int stageId,
boolean interruptThread,
String reason) |
boolean |
killTaskAttempt(long taskId,
boolean interruptThread,
String reason)
Kills a task attempt.
|
void |
notifyPartitionCompletion(int stageId,
int partitionId) |
void |
postStartHook() |
org.apache.spark.scheduler.Pool |
rootPool() |
scala.Enumeration.Value |
schedulingMode() |
void |
setDAGScheduler(org.apache.spark.scheduler.DAGScheduler dagScheduler) |
void |
start() |
void |
stop(int exitCode) |
void |
submitTasks(org.apache.spark.scheduler.TaskSet taskSet) |
void |
workerRemoved(String workerId,
String host,
String message)
Process a removed worker
|
scala.Option<String> applicationAttemptId()
String applicationId()
void cancelTasks(int stageId, boolean interruptThread)
int defaultParallelism()
void executorDecommission(String executorId, org.apache.spark.scheduler.ExecutorDecommissionInfo decommissionInfo)
executorId
- (undocumented)decommissionInfo
- (undocumented)boolean executorHeartbeatReceived(String execId, scala.Tuple2<Object,scala.collection.Seq<AccumulatorV2<?,?>>>[] accumUpdates, BlockManagerId blockManagerId, scala.collection.mutable.Map<scala.Tuple2<Object,Object>,org.apache.spark.executor.ExecutorMetrics> executorUpdates)
execId
- (undocumented)accumUpdates
- (undocumented)blockManagerId
- (undocumented)executorUpdates
- (undocumented)void executorLost(String executorId, org.apache.spark.scheduler.ExecutorLossReason reason)
executorId
- (undocumented)reason
- (undocumented)scala.Option<org.apache.spark.scheduler.ExecutorDecommissionState> getExecutorDecommissionState(String executorId)
executorId
- (undocumented)void killAllTaskAttempts(int stageId, boolean interruptThread, String reason)
boolean killTaskAttempt(long taskId, boolean interruptThread, String reason)
taskId
- (undocumented)interruptThread
- (undocumented)reason
- (undocumented)void notifyPartitionCompletion(int stageId, int partitionId)
void postStartHook()
org.apache.spark.scheduler.Pool rootPool()
scala.Enumeration.Value schedulingMode()
void setDAGScheduler(org.apache.spark.scheduler.DAGScheduler dagScheduler)
void start()
void stop(int exitCode)
void submitTasks(org.apache.spark.scheduler.TaskSet taskSet)
void workerRemoved(String workerId, String host, String message)
workerId
- (undocumented)host
- (undocumented)message
- (undocumented)


|
CMSIS-Pack
Version 1.7.2
Delivery Mechanism for Software Packs
|
Debug Description elements and access sequences are defined as IDE-independent. However the debug IDE can use this information to provide settings and to use sequences where applicable in its debug flow.
Arm μVision debugger (part of Keil MDK) supports CMSIS debug descriptions. If any of the debug description elements or debug access sequences are defined in a DFP for the target MCU the μVision automatically detects that and provides user with the configuration options described in this chapter.
By default μVision enables the use of the debug descriptions if such are specified for the target. It is possible to manually disable the use of the debug descriptions for a specific project target in Options for Target... dialog - Debug tab - Settings button - Pack tab. If the item "Enable" is unchecked the debugger will ignore all device descriptions specified in the DFP:
When the use of debug descriptions is enabled various debugger configuration options can becomed locked as specified in the DFP. Section Impact of debug access configuration explains the debugger parameters that can be configured with the debug descriptions.
Disabling the use of debug descriptions can be useful to verify the default debugger behavior on the device.
When Default debugger configuration are provided the μVision debugger automatically applies these settings to the new project for the MCU. This can be observed in Options for Target... dialog - Debug tab - Settings button.
Below is an example of the configuration code and how it is applied by μVision.
SWD is selected as the default debug protocol with 5MHz clock and SWJ checkbox locked because this is a fixed characteristic of the device.
With the specificaton of the debug connection μVision debugger will automatically use the access port specified via the __ap attribute when debugging the processor and there's no need for user to configure it in the IDE. Corresponding option is locked as shown on the figure below.
μVision debugger displays the JTAG ID Code and the IR Length values (actually read or overwritten ones) in debug settings:
You can test what the μVision debugger is able to detect automatically without the debugport configuration in the pdsc. For that the use of debug description shall be disabled in the Pack tab.
The default reset type can be specified in debug element via defaultResetSequence attribute.
It is also possible to disable particular reset type for selection by overwriting corresponding predefined reset sequence with disable attribute set to 'true'. For example reset configuration implemented for Microchip SAML11 device:
μVision debugger applies it automatically and displays as default and selected in Options for Target... dialog - Debug tab - Settings button and then Reset:
You can see the VECTRESET type is absent and system reset is selected and marked as default. The user can still manually change the reset type for the project in this dialog.
Using the Reset dropdown menu mentioned above a user can specify the reset type to be performed by the debugger.
Figure below shows how the typically available reset options map to the corresponding reset types in the connect flow described in Usage of debug access sequences. Note that "Custom" reset type appears only when user-defined debug sequence is assigned to the defaultResetSequence attribute.
Detailed meanings for available options are explained in the documentation of corresponding debug adapter. For example for ULINKpro Connect & Reset Options
If the .pdsc file specifies for the target debugvars with the configfile
attribute then μVision automatically creates an instance of debug configuration file for each target in the project by copying the *.dbgconf from the specified location in the pack to the DebugConfig
directory in the application project.
Clicking "Edit" button will open the debug configuration file in μVision for editing. If the .dbgconf file is written with the Configuration Wizard annotations the graphical view is available in μVision providing users with the intuitive configuration interface. For example:
μVision can save information about executed debug sequences into a log file. This can be useful when implementing debug sequences or analyzing debugger behavior.
The logging can be enabled via Options for Target... dialog - Debug tab - Settings button - Pack tab as shown on the figure below. The path and file name cannot be modified.
Note that the log file stores only debug sequences specified in the .pdsc file. The non-overwritten predefined debug sequences do not appear in the log but still get executed by the debugger.
Detailed information about the debugger operation can be obtained in the debug access log.
It can be enabled in Options for Target... dialog - Debug tab - Settings button as shown on figure below. The file is stored in the project root folder as <DebugAdapter>_DebugLog_<sequenceNr>.log
file. For example: ULINKplus_DebugLog_0000.log
.
μVision debugger provides options to enable and configure debug connect and reset operations. Based on these settings decisions in the debug flow are made as shown in Usage of debug access sequences. Available configuration options depend on the debug adapters, but the approach is similar in most cases. Examples below explain the options available for ULINK and CMSIS-DAP adapters.
Use Options for Target... dialog - Debug tab - Settings button and then in Connect: dropdown menu select the option for debugger operation when establishing connection to the target.
Figure below shows how the options "with Pre-reset" and "under Reset" map to the corresponding operations in the connect flow described in Usage of debug access sequences.
Detailed explanation for available options are can be found in the documentation of corresponding debug adapter. For example for ULINKpro Connect & Reset Options
Reset types and default selection explains the Reset dropdown menu in the same area and its mapping to the reset types used in Usage of debug access sequences.
The option is currently in experimental status.