ILNumerics Ultimate VS

H5StringAttributeGet Method (NullableStringPadding)

ILNumerics Ultimate VS Documentation
ILNumerics - Technical Application Development
Retrieve the attribute value(s) as ILNumerics array.

[ILNumerics HDF5 Module]

Namespace:  ILNumerics.IO.HDF5
Assembly:  ILNumerics.IO.HDF5 (in ILNumerics.IO.HDF5.dll) Version: 5.5.0.0 (5.5.7503.3146)
Syntax

public RetArray<string> Get(
	Nullable<StringPadding> padding = 0
)

Parameters

padding (Optional)
Type: SystemNullableStringPadding
For fixed length string storage only: specifies how to handle the padding bytes/characters. Default: NULLTERM (cut-off remaining characters).

Return Value

Type: RetArrayString
Whole attribute string array.
Remarks

This function is used to retrieve the value from the attribute as ILNumerics array.

The padding parameter is used to specify how to retrieve strings which are stored as fixed length strings. By default (NULLTERM) superfluous characters up to the end of the (fixed) length are removed. In this case the strings returned will not expose any whitespace after the first 0-character. This has a similar effect as using Trim on the string elements. Other values (SPACEPAD and ZEROPAD) retain those characters in the string.

Provide ROUNDTRIP for padding in order to return the strings in their natural padding mode as had been used at the time of creating the attribute.

For variable length strings the setting of padding does not has any effect. Those strings are always returned without padding characters.

HDF5 attributes do not utilize partial I/O. This means, attribute values are completely retrieved from the attribute object in the HDF5 file - regardless if only a subset of the attribute value is needed by the user. However, since the value is returned as regular ILNumerics array, all subarray options for ILNumerics arrays are available on the return value.

This API corresponds to the expectation/recommendation for attribute values being rather small (compared with regular dataset content). If you are working with large data and have the need for frequent access to only a part of it, consider using HDF5 datasets instead. Their hyperslab feature helps to prevent from performance degradation.

[ILNumerics HDF5 Module]

See Also

Reference