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View Code? Open in Web Editor NEWA Python library for numpy arrays that persist on disk in a format that is simple, self-documented and tool-independent, and maximizes universal readability.
License: Other
A Python library for numpy arrays that persist on disk in a format that is simple, self-documented and tool-independent, and maximizes universal readability.
License: Other
README now is unnecessarily complex if the subarrays are 1-dimensions. Also, right at the topic specific information of the shape of the subarrays may be included to make things less abstract.
Not all languages can directly read all numeric types. Sometimes this is quite inconvenient, for example when working with float16 data that Matlab cannot read as such, or complex types. Matlab has these types, but cannot read them. Darr should produce read code for those cases that circumvents this problem .
Investigate and implement if possible read code in other languages (at least R and hopefully Matlab and Julia) based on a memory mapped file.
Enable the setting of values in RaggedArrays, like a[5,:3] = 2.0 . Now only creating, appending and reading ragged arrays is supported.
For 1-D arrays you do not necessarily need numpy, but you can also use the array module from the standard library:
Although it would be short, it would be good to have a description in the documentation what the specification of a Darr Array (and RaggedArray) is.
Now only Python, R and Matlab are included. But for plain Arrays we have also Mathematica, GDL, Julia (old and new) and Maple.
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