I need to create about 2 million vectors w/ 1000 slots in each (each slot merely contains an integer).
采用这一数据的最佳数据结构是什么? 这可能是,我低估了所涉处理/主题的数量。
我需要反复收集档案(总共约34.5GB),每当200万件物品(与病媒相对应的每件)中一带遇到时,更新病媒。
我可以轻而易举地为此撰写法典,但我知道,处理数据量的最佳时机是,为什么我向各位专家提出要求。
Best, Georgina
你可能记得你的机器。 不清理运行方案:
a = numpy.zeros((1000000,1000),dtype=int)
would。 但是,一般来说,如果你能够打破问题,这样你就不需要一整块记忆,或者你可以使用一种稀有的代表性,那么我会使用<条码>numpy(scipy,用于代表人数稀少)。
另外,您可考虑将数据储存在<代码>hdf5上,并登录<编码>h5py或>pytablesnetcdf4上,并可在软盘上查阅所需的部分。
假设大部分条目为零,则使用零散矩阵。
如果在援助团工作时需要scipy.sparsemap变量。 它包括高效操纵混凝土算法。
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