Attempt to extract field 'ThermocoupleType' from 'mxArray'.

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haryana thomas
haryana thomas 2018-6-8
编辑： cristina9 2018-10-12
I'm trying to write code in simulink block editor to take live input data from a thermocouple, through a DAQ system, to display the data on a scope. The thermocouple is a K type thermocouple. If I don't specify the type, I get an error message asking for the thermocouple type. When I specify K type, I get the error 'Attempt to extract field 'ThermocoupleType' from 'mxArray'.'
What should I do?
Code:
function data = Thermocouple()
coder.extrinsic('daq.createSession','addAnalogInputChannel','startForeground','T')
T = daq.createSession('ni');
ch0 = addAnalogInputChannel(T,'cDAQ9185-1D2BD3AMod2',0,'Thermocouple');
ch0.ThermocoupleType = 'k';
data = zeros(1,1000);
data = startForeground(T);
Thanks in advance!
  2 个评论
Venkata Siva Krishna Madala
Venkata Siva Krishna Madala 2018-6-12
Since "addAnalogInputChannel" is extrinsic, it returns an "mxArray" object, which overrides the data type of "ch0" to be an "mxArray" as well.
In order to solve this error pre-initialize the desired fields / variables, and then assign the value to the field.
Bob Dekraker
Bob Dekraker 2018-6-19
编辑：Bob Dekraker 2018-6-19
I'm not exactly sure what to preinitialize it to. Is this what you were thinking?
function data = Thermocouple()
coder.extrinsic('daq.createSession','addAnalogInputChannel','startForeground','T')
T = daq.createSession('ni');
ch0 = addAnalogInputChannel(T,'cDAQ9185-1D2BD3AMod2',0,'Thermocouple');
ch0.ThermocoupleType = zeros(1,1)
ch0.ThermocoupleType = 'k';
data = zeros(1,1000);
data = startForeground(T);
Thanks

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回答（1 个）

cristina9
cristina9 2018-10-12
编辑：cristina9 2018-10-12
Same quesiton! I call "timedelaynet" to train a neural network on line in the simulink, and then hope to get the weight value of the neural network. I specify the type of the variable in advance, but it does not work.
coder.extrinsic('net'); net.IW{1,1}=zeros(5,4); %error message:Attempt to extract field 'IW' from 'mxArray' [net,tr]=train(net,inputs,targets,inputStates,layerStates);
What should I do?

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