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This is a low-priority wishlist todo reminder for when someone is bored.
The tensor data model schema and I/O methods should be "hardened". Right now we hand-craft I/O converters between higher level WCT structures (ICluster, PointCloud::Dataset, etc) and file representations. It requires careful human attention at every point to develop and maintain.
Better would be to add a subsystem that goes something like this:
Formally represent the TDM schema with moo schema.
Develop a C++ moo template file operating on a TDM moo schema object that renders to a C++ struct representing that TDM object.
Develop a C++ moo template file operating on a TDM moo schema object that generates I/O methods converting between the above struct and a file representation. One template targeting the WCT json+numpy+archive format and one targeting hdf5.
Develop a C++ moo template operating on a collection of all TDM moo schema objects that generates the necessary dynamic-static type conversion needed to serialize a file of multiple TDM records of differing types.
See #267 for recent work in this area and in particular not the use of the located index which is required to speed up I/O operations. This index might live as part of the generated code in 3 or 4.
The text was updated successfully, but these errors were encountered:
This is a low-priority wishlist todo reminder for when someone is bored.
The tensor data model schema and I/O methods should be "hardened". Right now we hand-craft I/O converters between higher level WCT structures (
ICluster
,PointCloud::Dataset
, etc) and file representations. It requires careful human attention at every point to develop and maintain.Better would be to add a subsystem that goes something like this:
moo
schema.See #267 for recent work in this area and in particular not the use of the
located
index which is required to speed up I/O operations. This index might live as part of the generated code in 3 or 4.The text was updated successfully, but these errors were encountered: