Error using cds_innersrr

Dear elic253,

elic253 said:

when I perform this code line i get the next error in matlab: 

Error using cds_innersrr Command not recognized. 

in the matlab path that i have set above i can see the cds_innersrr.mexa64 but as i understand that matlab doesn't recognized the function. 

Are you sure your understanding of the error "command is not recognized" is correct? I have a feeling the command is located, but the syntax with which you are using it is not correct. The actual error message you include states "Command not recognized". If it were a path problem, not only would you not find the cds_innersrr.mexa64 file in the $MATLABPATH variable directory, but I would expect an error including a term such as "cds_innersrr not defined" or "cds_innersrr not found".

My understanding is the command syntax is something like:

sig = cds_innersrr(dirname, dataset, signame, verbose)

As a guess, your use of the {} nomenclature suggests params_n1 is a cell array. A cell array can have members of different data types - its members are not exclusively strings. If the function cds_innersrr() is expecting a string as the argument "signal", perhaps the result of params_n{1} is not considered a string by the function and hence it is not capable of executing the function and results in the error of "command not recognized".

You might try to execute the command using a very simple case where signame is a quoted net name in your results and see if the command succeeds.

Shawn

Thanks Shawn. i have tried to quote the signal name directly and still the same error. i have read that both cds_srr and cds_innersrr has the same interface so i tired the next commands in order to see what i get: 

struct_n = cds_innersrr(c.outfile, c.sweep_noise);

struct_n = cds_srr(c.outfile, c.sweep_noise);

the first one has returned the same error , the second attempt return a structure that i can debug , what do you think?

The cds_innersrr is not intended for public use - it's an internal function used by cds_srr() and that's the interface you're expected to use tSecondly the Spectre Toolbox shipped with the IC tools is primarily intended for use within the ADE MATLAB interface (i.e. using MATLAB expressions in ADE outputs) rather than for standalone use - it's been modified a little from the version shipped with the SPECTRE release stream (to allow for some of the other objects that you can query over from within ADE). I think it's OK to use either, but I've only ever used the IC version from within ADE (and you don't need to set MATLABPATH in that case). When using the Spectre version, I'd use:

setenv MATLABPATH `cds_root spectre`/tools/spectre/matlab/64bit

The use of cds_srr is that you can do:

>> res='simulation/Diff_LNA_test/spectre/comp1db/psf'

>> cds_srr(res)
PSFversion: 1.00
sweeppss_pss_td-sweep (td.pss).
sweeppss_pss_fd-sweep (fd.pss).
modelParameter-info (info).
element-info (info).
outputParameter-info (info).
designParamVals-info (info).
primitives-info.primitives (info.primitives).
subckts-info.subckts (info.subckts).
variables (design_variables).

ans =

9×1 cell array

{'sweeppss_pss_td-sweep' }
{'sweeppss_pss_fd-sweep' }
{'modelParameter-info' }
{'element-info' }
{'outputParameter-info' }
{'designParamVals-info' }
{'primitives-info.primitives'}
{'subckts-info.subckts' }
{'variables' }

i.e. it will print a summary of the databases available and then return them as an array. If you run with two arguments, the second argument is the name of the database:

>> cds_srr(res,'sweeppss_pss_td-sweep')
Total: 51 properties
'PSFversion' 'PSF style' 'PSF types' 'PSF sweeps' 'PSF sweep points' 'PSF sweep min' 'PSF sweep max' 'PSF groups' 'PSF traces' 'PSF buffer size' 'PSF window size' 'PsfTrailerFileNumber' 'PsfTrailerStart' 'PsfEndTableFileNumber' 'simulator' 'version' 'date' 'design' 'analysis type' 'analysis name' 'analysis description' 'tolerance.relative' 'fundamental' 'load:r' 'load:num' 'load:units' 'rf:r' 'rf:num' 'rf:units' 'start' 'outputstart' 'stop' 'period' 'steadyratio' 'harms' 'step' 'maxstep' 'ic' 'skipdc' 'reltol' 'abstol(V)' 'abstol(I)' 'temp' 'tnom' 'tempeffects' 'errpreset' 'method' 'lteratio' 'relref' 'cmin' 'gmin'

Total: 2 type(s) of signals
Signal type: I Data type: Real
'V1:p' 'V2:p' 'I8.L3.ls:1' 'I8.L4.ls:1' 'I8.L14.ls:1' 'I8.L17.ls:1' 'I8.L22.ls:1' 'I8.L23.ls:1'
Signal type: V Data type: Real
'gnd_rf!' 'inm' 'inp' 'net026' 'net028' 'net034' 'net035' 'outm' 'outp' 'RFin' 'RFout' 'vdd_rf!' 'I8.L3.n1' 'I8.L3.n2' 'I8.L3.n3' 'I8.L4.n1' 'I8.L4.n2' 'I8.L4.n3' 'I8.L14.n1' 'I8.L14.n2' 'I8.L14.n3' 'I8.L17.n1' 'I8.L17.n2' 'I8.L17.n3' 'I8.L22.n1' 'I8.L22.n2' 'I8.L22.n3' 'I8.L23.n1' 'I8.L23.n2' 'I8.L23.n3' 'I8.NM0.bi' 'I8.NM0.db' 'I8.NM0.di' 'I8.NM0.gi' 'I8.NM0.sb' 'I8.NM0.si' 'I8.NM1.bi' 'I8.NM1.db' 'I8.NM1.di' 'I8.NM1.gi' 'I8.NM1.sb' 'I8.NM1.si' 'I8.NM2.bi' 'I8.NM2.db' 'I8.NM2.di' 'I8.NM2.gi' 'I8.NM2.sb' 'I8.NM2.si' 'I8.NM3.bi' 'I8.NM3.db' 'I8.NM3.di' 'I8.NM3.gi' 'I8.NM3.sb' 'I8.NM3.si' 'I8.NM4.bi' 'I8.NM4.db' 'I8.NM4.di' 'I8.NM4.gi' 'I8.NM4.sb' 'I8.NM4.si' 'I8.NM6.bi' 'I8.NM6.db' 'I8.NM6.di' 'I8.NM6.gi' 'I8.NM6.sb' 'I8.NM6.si' 'I8.NM7.bi' 'I8.NM7.db' 'I8.NM7.di' 'I8.NM7.gi' 'I8.NM7.sb' 'I8.NM7.si' 'I8.NM9.bi' 'I8.NM9.db' 'I8.NM9.di' 'I8.NM9.gi' 'I8.NM9.sb' 'I8.NM9.si' 'I8.net2' 'I8.net7' 'I8.net17' 'I8.net20' 'I8.net032' 'I8.net033' 'I8.net034' 'I8.net036' 'I8.net046' 'I8.net055' 'I8.net070' 'I8.net073' 'I8.net076' 'I8.net079'

ans =

struct with fields:

signal_info: {'prop' 'Unknown' 'I' 'Real' 'V' 'Real'}
prop: {51×1 cell}
I: {8×1 cell}
V: {92×1 cell}

then it tells you the available output signals in that result database. The result is a structure with each type - so you can do:

>> ans.I

ans =

8×1 cell array

{'V1:p' }
{'V2:p' }
{'I8.L3.ls:1' }
{'I8.L4.ls:1' }
{'I8.L14.ls:1'}
{'I8.L17.ls:1'}
{'I8.L22.ls:1'}
{'I8.L23.ls:1'}

or:

>> ans.V

ans =

92×1 cell array

{'gnd_rf!' }
{'inm' }
{'inp' }
{'net026' }
{'net028' }
{'net034' }
{'net035' }
{'outm' }
{'outp' }
{'RFin' }
{'RFout' }
{'vdd_rf!' }
{'I8.L3.n1' }
{'I8.L3.n2' }
...

Now I can retrieve a specific signal:

>> rfout=cds_srr(res,'sweeppss_pss_td-sweep','RFout')

rfout =

struct with fields:

info: {'V' 'V' 'time' 's' 'prf' ''}
prf: [-30 -27.5000 -25 -22.5000 -20 -17.5000 -15 -12.5000 -10 -7.5000 -5]
time: [161×11 double]
V: [161×11 double]

In this case, there's a sweep, so I can do:

>> rfout.V

ans =

0.0090 0.0123 0.0171 0.0243 0.0352 0.0524 0.0805 0.1309 0.2201 0.3396 0.4700
0.0081 0.0112 0.0156 0.0223 0.0326 0.0490 0.0760 0.1252 0.2125 0.3293 0.4580
0.0056 0.0078 0.0112 0.0165 0.0249 0.0389 0.0626 0.1082 0.1896 0.2986 0.4219
0.0015 0.0024 0.0040 0.0071 0.0122 0.0223 0.0407 0.0806 0.1521 0.2482 0.3621
-0.0041 -0.0049 -0.0057 -0.0057 -0.0049 -0.0002 0.0111 0.0433 0.1012 0.1801 0.2811
-0.0108 -0.0138 -0.0174 -0.0212 -0.0257 -0.0275 -0.0249 -0.0019 0.0395 0.0979 0.1840
-0.0182 -0.0237 -0.0305 -0.0385 -0.0490 -0.0583 -0.0654 -0.0527 -0.0292 0.0059 0.0789
-0.0260 -0.0340 -0.0442 -0.0567 -0.0735 -0.0906 -0.1081 -0.1063 -0.1004 -0.0908 -0.0264
-0.0335 -0.0440 -0.0576 -0.0745 -0.0974 -0.1224 -0.1503 -0.1600 -0.1699 -0.1851 -0.1271
...

and so on.

In your example, it's not clear what c.sweep_noise or c.outfile are, or why you are trying to use cds_innersrr.

Andrew

The cds_innersrr is not intended for public use - it's an internal function used by cds_srr() and that's the interface you're expected to use tSecondly the Spectre Toolbox shipped with the IC tools is primarily intended for use within the ADE MATLAB interface (i.e. using MATLAB expressions in ADE outputs) rather than for standalone use - it's been modified a little from the version shipped with the SPECTRE release stream (to allow for some of the other objects that you can query over from within ADE). I think it's OK to use either, but I've only ever used the IC version from within ADE (and you don't need to set MATLABPATH in that case). When using the Spectre version, I'd use:

setenv MATLABPATH `cds_root spectre`/tools/spectre/matlab/64bit

The use of cds_srr is that you can do:

>> res='simulation/Diff_LNA_test/spectre/comp1db/psf'

>> cds_srr(res)
PSFversion: 1.00
sweeppss_pss_td-sweep (td.pss).
sweeppss_pss_fd-sweep (fd.pss).
modelParameter-info (info).
element-info (info).
outputParameter-info (info).
designParamVals-info (info).
primitives-info.primitives (info.primitives).
subckts-info.subckts (info.subckts).
variables (design_variables).

ans =

9×1 cell array

{'sweeppss_pss_td-sweep' }
{'sweeppss_pss_fd-sweep' }
{'modelParameter-info' }
{'element-info' }
{'outputParameter-info' }
{'designParamVals-info' }
{'primitives-info.primitives'}
{'subckts-info.subckts' }
{'variables' }

i.e. it will print a summary of the databases available and then return them as an array. If you run with two arguments, the second argument is the name of the database:

>> cds_srr(res,'sweeppss_pss_td-sweep')
Total: 51 properties
'PSFversion' 'PSF style' 'PSF types' 'PSF sweeps' 'PSF sweep points' 'PSF sweep min' 'PSF sweep max' 'PSF groups' 'PSF traces' 'PSF buffer size' 'PSF window size' 'PsfTrailerFileNumber' 'PsfTrailerStart' 'PsfEndTableFileNumber' 'simulator' 'version' 'date' 'design' 'analysis type' 'analysis name' 'analysis description' 'tolerance.relative' 'fundamental' 'load:r' 'load:num' 'load:units' 'rf:r' 'rf:num' 'rf:units' 'start' 'outputstart' 'stop' 'period' 'steadyratio' 'harms' 'step' 'maxstep' 'ic' 'skipdc' 'reltol' 'abstol(V)' 'abstol(I)' 'temp' 'tnom' 'tempeffects' 'errpreset' 'method' 'lteratio' 'relref' 'cmin' 'gmin'

Total: 2 type(s) of signals
Signal type: I Data type: Real
'V1:p' 'V2:p' 'I8.L3.ls:1' 'I8.L4.ls:1' 'I8.L14.ls:1' 'I8.L17.ls:1' 'I8.L22.ls:1' 'I8.L23.ls:1'
Signal type: V Data type: Real
'gnd_rf!' 'inm' 'inp' 'net026' 'net028' 'net034' 'net035' 'outm' 'outp' 'RFin' 'RFout' 'vdd_rf!' 'I8.L3.n1' 'I8.L3.n2' 'I8.L3.n3' 'I8.L4.n1' 'I8.L4.n2' 'I8.L4.n3' 'I8.L14.n1' 'I8.L14.n2' 'I8.L14.n3' 'I8.L17.n1' 'I8.L17.n2' 'I8.L17.n3' 'I8.L22.n1' 'I8.L22.n2' 'I8.L22.n3' 'I8.L23.n1' 'I8.L23.n2' 'I8.L23.n3' 'I8.NM0.bi' 'I8.NM0.db' 'I8.NM0.di' 'I8.NM0.gi' 'I8.NM0.sb' 'I8.NM0.si' 'I8.NM1.bi' 'I8.NM1.db' 'I8.NM1.di' 'I8.NM1.gi' 'I8.NM1.sb' 'I8.NM1.si' 'I8.NM2.bi' 'I8.NM2.db' 'I8.NM2.di' 'I8.NM2.gi' 'I8.NM2.sb' 'I8.NM2.si' 'I8.NM3.bi' 'I8.NM3.db' 'I8.NM3.di' 'I8.NM3.gi' 'I8.NM3.sb' 'I8.NM3.si' 'I8.NM4.bi' 'I8.NM4.db' 'I8.NM4.di' 'I8.NM4.gi' 'I8.NM4.sb' 'I8.NM4.si' 'I8.NM6.bi' 'I8.NM6.db' 'I8.NM6.di' 'I8.NM6.gi' 'I8.NM6.sb' 'I8.NM6.si' 'I8.NM7.bi' 'I8.NM7.db' 'I8.NM7.di' 'I8.NM7.gi' 'I8.NM7.sb' 'I8.NM7.si' 'I8.NM9.bi' 'I8.NM9.db' 'I8.NM9.di' 'I8.NM9.gi' 'I8.NM9.sb' 'I8.NM9.si' 'I8.net2' 'I8.net7' 'I8.net17' 'I8.net20' 'I8.net032' 'I8.net033' 'I8.net034' 'I8.net036' 'I8.net046' 'I8.net055' 'I8.net070' 'I8.net073' 'I8.net076' 'I8.net079'

ans =

struct with fields:

signal_info: {'prop' 'Unknown' 'I' 'Real' 'V' 'Real'}
prop: {51×1 cell}
I: {8×1 cell}
V: {92×1 cell}

then it tells you the available output signals in that result database. The result is a structure with each type - so you can do:

>> ans.I

ans =

8×1 cell array

{'V1:p' }
{'V2:p' }
{'I8.L3.ls:1' }
{'I8.L4.ls:1' }
{'I8.L14.ls:1'}
{'I8.L17.ls:1'}
{'I8.L22.ls:1'}
{'I8.L23.ls:1'}

or:

>> ans.V

ans =

92×1 cell array

{'gnd_rf!' }
{'inm' }
{'inp' }
{'net026' }
{'net028' }
{'net034' }
{'net035' }
{'outm' }
{'outp' }
{'RFin' }
{'RFout' }
{'vdd_rf!' }
{'I8.L3.n1' }
{'I8.L3.n2' }
...

Now I can retrieve a specific signal:

>> rfout=cds_srr(res,'sweeppss_pss_td-sweep','RFout')

rfout =

struct with fields:

info: {'V' 'V' 'time' 's' 'prf' ''}
prf: [-30 -27.5000 -25 -22.5000 -20 -17.5000 -15 -12.5000 -10 -7.5000 -5]
time: [161×11 double]
V: [161×11 double]

In this case, there's a sweep, so I can do:

>> rfout.V

ans =

0.0090 0.0123 0.0171 0.0243 0.0352 0.0524 0.0805 0.1309 0.2201 0.3396 0.4700
0.0081 0.0112 0.0156 0.0223 0.0326 0.0490 0.0760 0.1252 0.2125 0.3293 0.4580
0.0056 0.0078 0.0112 0.0165 0.0249 0.0389 0.0626 0.1082 0.1896 0.2986 0.4219
0.0015 0.0024 0.0040 0.0071 0.0122 0.0223 0.0407 0.0806 0.1521 0.2482 0.3621
-0.0041 -0.0049 -0.0057 -0.0057 -0.0049 -0.0002 0.0111 0.0433 0.1012 0.1801 0.2811
-0.0108 -0.0138 -0.0174 -0.0212 -0.0257 -0.0275 -0.0249 -0.0019 0.0395 0.0979 0.1840
-0.0182 -0.0237 -0.0305 -0.0385 -0.0490 -0.0583 -0.0654 -0.0527 -0.0292 0.0059 0.0789
-0.0260 -0.0340 -0.0442 -0.0567 -0.0735 -0.0906 -0.1081 -0.1063 -0.1004 -0.0908 -0.0264
-0.0335 -0.0440 -0.0576 -0.0745 -0.0974 -0.1224 -0.1503 -0.1600 -0.1699 -0.1851 -0.1271
...

and so on.

In your example, it's not clear what c.sweep_noise or c.outfile are, or why you are trying to use cds_innersrr.

Andrew

I changed to cds_srr and it all good now, thanks