Mercurial > hg > nsaunier > traffic-intelligence
comparison trafficintelligence/tests/indicators.txt @ 1287:76f5693b530c
updated tests for numpy 2
| author | Nicolas Saunier <nicolas.saunier@polymtl.ca> |
|---|---|
| date | Sat, 20 Jul 2024 20:35:21 -0400 |
| parents | 56d0195d043e |
| children |
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| 1284:8e30c9a6ac6f | 1287:76f5693b530c |
|---|---|
| 19 >>> indic1[2] | 19 >>> indic1[2] |
| 20 0 | 20 0 |
| 21 | 21 |
| 22 >>> ttc = SeverityIndicator('TTC', {t:t-1 for t in TimeInterval(1,11)}, mostSevereIsMax = False) | 22 >>> ttc = SeverityIndicator('TTC', {t:t-1 for t in TimeInterval(1,11)}, mostSevereIsMax = False) |
| 23 >>> ttc.getMostSevereValue(1) | 23 >>> ttc.getMostSevereValue(1) |
| 24 0.0 | 24 np.float64(0.0) |
| 25 >>> ttc.getMostSevereValue(2) | 25 >>> ttc.getMostSevereValue(2) |
| 26 0.5 | 26 np.float64(0.5) |
| 27 >>> ttc.getMostSevereValue(centile = 10.) | 27 >>> ttc.getMostSevereValue(centile = 10.) |
| 28 1.0 | 28 np.float64(1.0) |
| 29 >>> ttc.mostSevereIsMax = True | 29 >>> ttc.mostSevereIsMax = True |
| 30 >>> ttc.getMostSevereValue(1) | 30 >>> ttc.getMostSevereValue(1) |
| 31 10.0 | 31 np.float64(10.0) |
| 32 >>> ttc.getMostSevereValue(2) | 32 >>> ttc.getMostSevereValue(2) |
| 33 9.5 | 33 np.float64(9.5) |
| 34 >>> ttc.getMostSevereValue(centile = 10.) | 34 >>> ttc.getMostSevereValue(centile = 10.) |
| 35 9.0 | 35 np.float64(9.0) |
| 36 | 36 |
| 37 >>> t1 = Trajectory([[0.5,1.5,2.5],[0.5,3.5,6.5]]) | 37 >>> t1 = Trajectory([[0.5,1.5,2.5],[0.5,3.5,6.5]]) |
| 38 >>> m = indicatorMap([1,2,3], t1, 1) | 38 >>> m = indicatorMap([1,2,3], t1, 1) |
| 39 >>> m[(1.0, 3.0)] | 39 >>> m[(1.0, 3.0)] |
| 40 2.0 | 40 np.float64(2.0) |
| 41 >>> m[(2.0, 6.0)] | 41 >>> m[(2.0, 6.0)] |
| 42 3.0 | 42 np.float64(3.0) |
| 43 >>> m[(0.0, 0.0)] | 43 >>> m[(0.0, 0.0)] |
| 44 1.0 | 44 np.float64(1.0) |
| 45 >>> m = indicatorMap([1,2,3], t1, 4) | 45 >>> m = indicatorMap([1,2,3], t1, 4) |
| 46 >>> m[(0.0, 1.0)] | 46 >>> m[(0.0, 1.0)] |
| 47 3.0 | 47 np.float64(3.0) |
| 48 >>> m[(0.0, 0.0)] | 48 >>> m[(0.0, 0.0)] |
| 49 1.5 | 49 np.float64(1.5) |
