@tests: PosteriorErrorProbabilityModel PosteriorErrorProbabilityModel.__init__
()
| 1669 | |
| 1670 | @report |
| 1671 | def testPosteriorErrorProbabilityModel(): |
| 1672 | """ |
| 1673 | @tests: PosteriorErrorProbabilityModel |
| 1674 | PosteriorErrorProbabilityModel.__init__ |
| 1675 | """ |
| 1676 | model = pyopenms.PosteriorErrorProbabilityModel() |
| 1677 | p = model.getDefaults() |
| 1678 | _testParam(p) |
| 1679 | |
| 1680 | assert pyopenms.PosteriorErrorProbabilityModel().fit is not None |
| 1681 | assert pyopenms.PosteriorErrorProbabilityModel().computeProbability is not None |
| 1682 | |
| 1683 | scores = [float(i) for i in range(10)] |
| 1684 | model.fit(scores, "none") |
| 1685 | model.fit(scores, scores, "none") |
| 1686 | |
| 1687 | model.fillLogDensities(scores, scores, scores) |
| 1688 | |
| 1689 | assert model.computeLogLikelihood is not None |
| 1690 | assert model.pos_neg_mean_weighted_posteriors is not None |
| 1691 | |
| 1692 | GaussFitResult = model.getCorrectlyAssignedFitResult() |
| 1693 | GaussFitResult = model.getIncorrectlyAssignedFitResult() |
| 1694 | model.getNegativePrior() |
| 1695 | model.computeProbability(5.0) |
| 1696 | |
| 1697 | # model.InitPlots |
| 1698 | |
| 1699 | target = [float(i) for i in range(10)] |
| 1700 | model.getGumbelGnuplotFormula(GaussFitResult) |
| 1701 | model.getGaussGnuplotFormula(GaussFitResult) |
| 1702 | model.getBothGnuplotFormula(GaussFitResult, GaussFitResult) |
| 1703 | model.plotTargetDecoyEstimation(target, target) |
| 1704 | model.getSmallestScore() |
| 1705 | |
| 1706 | @report |
| 1707 | def testSeedListGenerator(): |
nothing calls this directly
no test coverage detected