| LTPDA Toolbox™ | contents | |
The following example shows you how to create a symbolic model.
>> s = smodel('a.*x.^2+b.*x+c');
You define with the command above the symbolic model. Please take care that each symbolic can represent a vector/matrix of numbers. This mean that you should use the array operators like '.*' or '.+' or ... and not the matrix operators like '*' or '^' or ....
Now, it is necessary to define the parameters with their default values
>> s.setParams({'a', 'b', 'c'}, {1 2 3})
---- symbolic model 1 ----
name: None
expr: a.*x.^2+b.*x+c
params: {'a', 'b', 'c'}
values: {1, 2, 3}
xvar:
xvals: []
xunits: []
yunits: []
description:
UUID: 7a084750-89c2-47f0-8c6b-65e9079bf6b3
--------------------------
Finally it is necessary to set the 'x' variable and the values.
>> s.setXvar('x')
---- symbolic model 1 ----
name: None
expr: a.*x.^2+b.*x+c
params: {'a', 'b', 'c'}
values: {1, 2, 3}
xvar: x
xvals: []
xunits: []
yunits: []
description:
UUID: ca9276b0-cc97-4001-9135-00c6799ec8b1
--------------------------
>> s.setXvals(-100:100)
---- symbolic model 1 ----
name: None
expr: a.*x.^2+b.*x+c
params: {'a', 'b', 'c'}
values: {1, 2, 3}
xvar: x
xvals: [-100 -99 -98 -97 -96 -95 -94 -93 -92 -91 -90 -89 -88 -87 -86 ...]
xunits: []
yunits: []
description:
UUID: f43e2f9b-3fb6-4e3c-92ba-7cba31c6a6c3
--------------------------
After all steps above it is possible to plot the model.
>> s.setXunits('s'); >> s.setYunits('V'); >> s.setName('Just a test'); >> iplot(s.eval)
| |
Constructor examples of the AO class | Constructor examples of the MFIR class | |
©LTP Team