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()
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()