def testArrays(rtData, rtData2, grad, grad2, total_npts): " Test various parallel algorithms." if rank == 0: print('-----------------------') PRINT("SUM ones:", algs.sum(rtData / rtData) - total_npts) PRINT( "SUM sin:", (algs.sum(algs.sin(rtData) + 1) - numpy.sum(numpy.sin(rtData2) + 1)) / numpy.sum(numpy.sin(rtData2) + 1)) PRINT("rtData min:", algs.min(rtData) - numpy.min(rtData2)) PRINT("rtData max:", algs.max(rtData) - numpy.max(rtData2)) PRINT("rtData sum:", (algs.sum(rtData) - numpy.sum(rtData2)) / (2 * numpy.sum(rtData2))) PRINT("rtData mean:", (algs.mean(rtData) - numpy.mean(rtData2)) / (2 * numpy.mean(rtData2))) PRINT("rtData var:", (algs.var(rtData) - numpy.var(rtData2)) / numpy.var(rtData2)) PRINT("rtData std:", (algs.std(rtData) - numpy.std(rtData2)) / numpy.std(rtData2)) PRINT("grad min:", algs.min(grad) - numpy.min(grad2)) PRINT("grad max:", algs.max(grad) - numpy.max(grad2)) PRINT("grad min 0:", algs.min(grad, 0) - numpy.min(grad2, 0)) PRINT("grad max 0:", algs.max(grad, 0) - numpy.max(grad2, 0)) PRINT("grad min 1:", algs.sum(algs.min(grad, 1)) - numpy.sum(numpy.min(grad2, 1))) PRINT("grad max 1:", algs.sum(algs.max(grad, 1)) - numpy.sum(numpy.max(grad2, 1))) PRINT("grad sum 1:", algs.sum(algs.sum(grad, 1)) - numpy.sum(numpy.sum(grad2, 1))) PRINT("grad var:", (algs.var(grad) - numpy.var(grad2)) / numpy.var(grad2)) PRINT("grad var 0:", (algs.var(grad, 0) - numpy.var(grad2, 0)) / numpy.var(grad2, 0))
def testArrays(rtData, rtData2, grad, grad2, total_npts): " Test various parallel algorithms." if rank == 0: print "-----------------------" PRINT("SUM ones:", algs.sum(rtData / rtData) - total_npts) PRINT( "SUM sin:", (algs.sum(algs.sin(rtData) + 1) - numpy.sum(numpy.sin(rtData2) + 1)) / numpy.sum(numpy.sin(rtData2) + 1), ) PRINT("rtData min:", algs.min(rtData) - numpy.min(rtData2)) PRINT("rtData max:", algs.max(rtData) - numpy.max(rtData2)) PRINT("rtData sum:", (algs.sum(rtData) - numpy.sum(rtData2)) / (2 * numpy.sum(rtData2))) PRINT("rtData mean:", (algs.mean(rtData) - numpy.mean(rtData2)) / (2 * numpy.mean(rtData2))) PRINT("rtData var:", (algs.var(rtData) - numpy.var(rtData2)) / numpy.var(rtData2)) PRINT("rtData std:", (algs.std(rtData) - numpy.std(rtData2)) / numpy.std(rtData2)) PRINT("grad min:", algs.min(grad) - numpy.min(grad2)) PRINT("grad max:", algs.max(grad) - numpy.max(grad2)) PRINT("grad min 0:", algs.min(grad, 0) - numpy.min(grad2, 0)) PRINT("grad max 0:", algs.max(grad, 0) - numpy.max(grad2, 0)) PRINT("grad min 1:", algs.sum(algs.min(grad, 1)) - numpy.sum(numpy.min(grad2, 1))) PRINT("grad max 1:", algs.sum(algs.max(grad, 1)) - numpy.sum(numpy.max(grad2, 1))) PRINT("grad sum 1:", algs.sum(algs.sum(grad, 1)) - numpy.sum(numpy.sum(grad2, 1))) PRINT("grad var:", (algs.var(grad) - numpy.var(grad2)) / numpy.var(grad2)) PRINT("grad var 0:", (algs.var(grad, 0) - numpy.var(grad2, 0)) / numpy.var(grad2, 0))
def get_center(self): """Return the center of the data. """ if self._composite: return algs.mean(self.dataset.Points, axis=0) else: return self.dataset.GetCenter()