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The "structy" class manages internally a large data matrix of rows x fields, and it logically maps this data to a set of fields that can be scalar values or vectors.Features:- efficient storage of data in single matrix- units- flexible referencing- project- resample of data by time stored in any field- sorting by field- rename of field, prefixing- concatenation vertical or horizontal- import/export to basic structureConstruction is easy: my = struct(data,{'field1','field2'});Construction of vector: my = struct(data,{'field1','field2'},{1:3,4:5}); % field1 is data 1..3 and field2 is 4..5Access is as in struct or more complex:my.field1my(1:10)my(1:10).field1my(1:10).field1(3) if field1 is a vector fieldData size is available as size(my) or size(my,'field')Structy can be cat vertical or horizontal as:[a,b] if a and b have not overlapping fields and same number of elements[a;b] if a and b have same fieldsProjection of data is possible using: project(my,{'field1','...'})Data can be also sorted by given columnFields can be renamed or modified with prefix using raname(my,oldfield,newfield) and addprefix(my,prefix)Finally it is possible to perform simple interpolation using a field as a timefield data. All the other gets interpolated by interp1.It can be stored on MAT file as struct by using asstruct and then constructing it again by this structure.TimeSeries comparison: time entries can be duplicated, construction is simpler, but no events and simpler API at this stage
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Windows Software
Albina Merfyn - I find this to be really easy to use. I can...
