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| From: | Ramiro Aceves |
| Subject: | Re: [Help-gnucap] Convergence problem |
| Date: | Wed, 20 Jul 2011 16:46:24 +0200 |
| User-agent: | Mozilla/5.0 (X11; U; Linux x86_64; en-US; rv:1.9.1.16) Gecko/20110505 Iceowl/1.0b1 Icedove/3.0.11 |
Oh, I am sorry Andy, it was a mistake, I meant "Al" El 20/07/11 14:54, Andy Fierman escribió:
Hi Ramiro, Um, it was Al who replied, not me. It might be a good idea to take me off the email address list if you are posting to the Gnucap help list as I am now subscribed to it anyway. Cheers, Andy. signality.co.uk On 20 July 2011 13:28, Ramiro Aceves<address@hidden> wrote:Many thanks dear Andy for detailed response. I have made it work following your guidelines. I have done the following, not sure if it is the right way to compile only the modules required, not the full set of modules: cd gnucap-2009-12-07/models-spice3f5/bjt make then I copied the bjt.so file to the directory in which I have the circuit file I loaded the library: gnucap> load ./bjt.so Q: already installed, replacing stashing as Q:0 npn: already installed, replacing stashing as npn:0 pnp: already installed, replacing stashing as pnp:0 npn1: already installed, replacing stashing as npn1:0 pnp1: already installed, replacing stashing as pnp1:0 gnucap> get LVDS-TTL-interface.cir LVDS TTL interface by PY2WM gnucap> gnucap> print tran v(2) v(4) gnucap> tran 0.1n 50n #Time v(2) v(4) 0. 0.85 4.2814 100.p 1.55 4.1288 200.p 1.55 0.96156 300.p 1.55 0.31304 400.p 1.55 0.23195 500.p 1.55 0.24185 600.p 1.55 0.23245 700.p 1.55 0.20509 800.p 1.55 0.18063 900.p 1.55 0.17625 1.n 1.55 0.19033 1.1n 1.55 0.20642 1.2n 1.55 0.20952 1.3n 1.55 0.19855 1.4n 1.55 0.18501 1.5n 1.55 0.18119 1.6n 1.55 0.18946 1.7n 1.55 0.20162 1.8n 1.55 0.20731 1.9n 1.55 0.2029 2.n 1.55 0.191 2.1n 1.55 0.19825 2.2n 1.55 0.19598 2.3n 1.55 0.19343 2.4n 1.55 0.20056 2.5n 1.55 0.18954 2.6n 1.55 0.20379 2.7n 1.55 0.18734 2.8n 1.55 0.2051 2.9n 1.55 0.18714 3.n 1.55 0.20446 3.1n 1.55 0.18875 3.2n 1.55 0.20227 3.3n 1.55 0.19158 3.4n 1.55 0.19924 3.5n 1.55 0.19485 3.6n 1.55 0.19621 3.7n 1.55 0.19774 3.8n 1.55 0.19388 3.9n 1.55 0.19966 4.n 1.55 0.19272 4.1n 1.55 0.20032 4.2n 1.55 0.19284 4.3n 1.55 0.19977 4.4n 1.55 0.19402 4.5n 1.55 0.19838 4.6n 1.55 0.19579 4.7n 1.55 0.19667 4.8n 1.55 0.1976 4.9n 1.55 0.1952 5.n 1.55 0.19893 5.1n 1.55 0.1944 5.2n 0.85 -0.13994 5.3n 0.85 -0.021841 5.4n 0.85 0.038978 5.5n 0.85 0.079093 5.6n 0.85 0.094834 5.7n 0.85 0.11366 5.8n 0.85 0.12116 5.9n 0.85 0.1194 6.n 0.85 0.12327 6.1n 0.85 0.12556 6.2n 0.85 0.12698 6.3n 0.85 0.12816 6.4n 0.85 0.12906 6.5n 0.85 0.12507 6.6n 0.85 0.12974 6.7n 0.85 0.12586 6.8n 0.85 0.13014 6.9n 0.85 0.12699 7.n 0.85 0.13038 7.1n 0.85 0.1286 7.2n 0.85 0.13061 7.3n 0.85 0.13081 7.4n 0.85 0.13116 7.5n 0.85 0.13387 7.6n 0.85 0.13293 7.7n 0.85 0.14006 7.8n 0.85 0.14247 7.9n 0.85 0.34613 8.n 0.85 0.88974 8.1n 0.85 1.6287 8.2n 0.85 2.0306 8.3n 0.85 2.3938 8.4n 0.85 2.7543 8.5n 0.85 3.0696 8.6n 0.85 3.3279 8.7n 0.85 3.5341 8.8n 0.85 3.6993 8.9n 0.85 3.8339 9.n 0.85 3.9451 9.1n 0.85 4.0361 9.2n 0.85 4.1078 9.3n 0.85 4.1611 9.4n 0.85 4.199 9.5n 0.85 4.2264 9.6n 0.85 4.2485 9.7n 0.85 4.2689 9.8n 0.85 4.2885 9.9n 0.85 4.3057 10.n 0.85 4.3186 10.1n 1.55 4.1344 10.2n 1.55 0.99845 10.3n 1.55 0.31618 10.4n 1.55 0.24518 10.5n 1.55 0.18808 10.6n 1.55 0.16927 10.7n 1.55 0.18742 10.8n 1.55 0.21575 10.9n 1.55 0.22626 11.n 1.55 0.21206 11.1n 1.55 0.18886 11.2n 1.55 0.17744 11.3n 1.55 0.18512 11.4n 1.55 0.2071 11.5n 1.55 0.19352 11.6n 1.55 0.19835 11.7n 1.55 0.20205 11.8n 1.55 0.1907 11.9n 1.55 0.20852 12.n 1.55 0.18594 12.1n 1.55 0.21151 12.2n 1.55 0.18502 12.3n 1.55 0.21057 12.4n 1.55 0.18786 12.5n 1.55 0.20628 12.6n 1.55 0.19345 12.7n 1.55 0.2 12.8n 1.55 0.2002 12.9n 1.55 0.19346 13.n 1.55 0.20634 13.1n 1.55 0.18832 13.2n 1.55 0.2104 13.3n 1.55 0.1858 13.4n 1.55 0.21152 13.5n 1.55 0.18635 13.6n 1.55 0.20963 13.7n 1.55 0.18967 13.8n 1.55 0.20539 13.9n 1.55 0.19481 14.n 1.55 0.19997 14.1n 1.55 0.20044 14.2n 1.55 0.19475 14.3n 1.55 0.20524 14.4n 1.55 0.19094 14.5n 1.55 0.20816 14.6n 1.55 0.18933 14.7n 1.55 0.2087 14.8n 1.55 0.19014 14.9n 1.55 0.20694 15.n 1.55 0.193 15.1n 1.55 0.20351 15.2n 0.85 -0.14231 15.3n 0.85 -0.022093 15.4n 0.85 0.035938 15.5n 0.85 0.083438 15.6n 0.85 0.10343 15.7n 0.85 0.11467 15.8n 0.85 0.1245 15.9n 0.85 0.12788 16.n 0.85 0.12667 16.1n 0.85 0.12449 16.2n 0.85 0.12434 16.3n 0.85 0.12677 16.4n 0.85 0.13068 16.5n 0.85 0.12906 16.6n 0.85 0.12988 16.7n 0.85 0.13116 16.8n 0.85 0.12927 16.9n 0.85 0.133 17.n 0.85 0.12922 17.1n 0.85 0.13456 17.2n 0.85 0.12997 17.3n 0.85 0.13602 17.4n 0.85 0.1317 17.5n 0.85 0.13792 17.6n 0.85 0.13561 17.7n 0.85 0.14322 17.8n 0.85 0.15278 17.9n 0.85 0.43123 18.n 0.85 1.1791 18.1n 0.85 1.821 18.2n 0.85 2.2169 18.3n 0.85 2.6105 18.4n 0.85 2.9523 18.5n 0.85 3.2628 18.6n 0.85 3.489 18.7n 0.85 3.6946 18.8n 0.85 3.8374 18.9n 0.85 3.9698 19.n 0.85 4.0586 19.1n 0.85 4.1402 19.2n 0.85 4.1966 19.3n 0.85 4.2437 19.4n 0.85 4.282 19.5n 0.85 4.3058 19.6n 0.85 4.3345 19.7n 0.85 4.343 19.8n 0.85 4.3664 19.9n 0.85 4.3656 20.n 0.85 4.3853 20.1n 1.55 4.2156 20.2n 1.55 1.0442 20.3n 1.55 0.32282 20.4n 1.55 0.25686 20.5n 1.55 0.20011 20.6n 1.55 0.22197 20.7n 1.55 0.23369 20.8n 1.55 0.2219 20.9n 1.55 0.19755 21.n 1.55 0.18143 21.1n 1.55 0.18444 21.2n 1.55 0.19987 21.3n 1.55 0.212 21.4n 1.55 0.21091 21.5n 1.55 0.19237 21.6n 1.55 0.20586 21.7n 1.55 0.19825 21.8n 1.55 0.19968 21.9n 1.55 0.20444 22.n 1.55 0.19404 22.1n 1.55 0.20935 22.2n 1.55 0.19033 22.3n 1.55 0.21183 22.4n 1.55 0.1894 22.5n 1.55 0.21141 22.6n 1.55 0.1913 22.7n 1.55 0.20839 22.8n 1.55 0.19541 22.9n 1.55 0.2037 23.n 1.55 0.20059 23.1n 1.55 0.1986 23.2n 1.55 0.20552 23.3n 1.55 0.19436 23.4n 1.55 0.20905 23.5n 1.55 0.19198 23.6n 1.55 0.21043 23.7n 1.55 0.19191 23.8n 1.55 0.20947 23.9n 1.55 0.19405 24.n 1.55 0.20657 24.1n 1.55 0.19778 24.2n 1.55 0.20254 24.3n 1.55 0.20214 24.4n 1.55 0.1984 24.5n 1.55 0.20612 24.6n 1.55 0.1951 24.7n 1.55 0.20887 24.8n 1.55 0.19333 24.9n 1.55 0.2099 25.n 1.55 0.19337 25.1n 1.55 0.20914 25.2n 0.85 -0.14433 25.3n 0.85 -0.018908 25.4n 0.85 0.046426 25.5n 0.85 0.082641 25.6n 0.85 0.10003 25.7n 0.85 0.11086 25.8n 0.85 0.1229 25.9n 0.85 0.13022 26.n 0.85 0.12829 26.1n 0.85 0.13103 26.2n 0.85 0.13216 26.3n 0.85 0.13252 26.4n 0.85 0.1328 26.5n 0.85 0.13098 26.6n 0.85 0.13345 26.7n 0.85 0.13174 26.8n 0.85 0.13405 26.9n 0.85 0.13265 27.n 0.85 0.1347 27.1n 0.85 0.13392 27.2n 0.85 0.13549 27.3n 0.85 0.13583 27.4n 0.85 0.13666 27.5n 0.85 0.13893 27.6n 0.85 0.13984 27.7n 0.85 0.14722 27.8n 0.85 0.16968 27.9n 0.85 0.51178 28.n 0.85 1.29 28.1n 0.85 1.754 28.2n 0.85 2.1537 28.3n 0.85 2.578 28.4n 0.85 2.9599 28.5n 0.85 3.2755 28.6n 0.85 3.5259 28.7n 0.85 3.7163 28.8n 0.85 3.8878 28.9n 0.85 4.0087 29.n 0.85 4.1122 29.1n 0.85 4.1907 29.2n 0.85 4.2484 29.3n 0.85 4.3023 29.4n 0.85 4.3302 29.5n 0.85 4.3699 29.6n 0.85 4.3794 29.7n 0.85 4.4101 29.8n 0.85 4.4094 29.9n 0.85 4.4333 30.n 0.85 4.4283 30.1n 1.55 4.274 30.2n 1.55 1.0952 30.3n 1.55 0.33674 30.4n 1.55 0.26684 30.5n 1.55 0.20314 30.6n 1.55 0.17895 30.7n 1.55 0.18767 30.8n 1.55 0.21362 30.9n 1.55 0.19124 31.n 1.55 0.18523 31.1n 1.55 0.19653 31.2n 1.55 0.21176 31.3n 1.55 0.21688 31.4n 1.55 0.20912 31.5n 1.55 0.19964 31.6n 1.55 0.20292 31.7n 1.55 0.20579 31.8n 1.55 0.19734 31.9n 1.55 0.21062 32.n 1.55 0.19372 32.1n 1.55 0.213 32.2n 1.55 0.19286 32.3n 1.55 0.21251 32.4n 1.55 0.19479 32.5n 1.55 0.2095 32.6n 1.55 0.19885 32.7n 1.55 0.20489 32.8n 1.55 0.20391 32.9n 1.55 0.19992 33.n 1.55 0.20868 33.1n 1.55 0.19586 33.2n 1.55 0.21202 33.3n 1.55 0.19365 33.4n 1.55 0.21324 33.5n 1.55 0.19371 33.6n 1.55 0.21219 33.7n 1.55 0.19591 33.8n 1.55 0.20927 33.9n 1.55 0.19962 34.n 1.55 0.20529 34.1n 1.55 0.20389 34.2n 1.55 0.20125 34.3n 1.55 0.20774 34.4n 1.55 0.19809 34.5n 1.55 0.21034 34.6n 1.55 0.19646 34.7n 1.55 0.21123 34.8n 1.55 0.1966 34.9n 1.55 0.21041 35.n 1.55 0.19833 35.1n 1.55 0.20823 35.2n 0.85 -0.13829 35.3n 0.85 -0.025077 35.4n 0.85 0.048248 35.5n 0.85 0.086672 35.6n 0.85 0.10457 35.7n 0.85 0.11291 35.8n 0.85 0.12259 35.9n 0.85 0.13055 36.n 0.85 0.13497 36.1n 0.85 0.1357 36.2n 0.85 0.13422 36.3n 0.85 0.1327 36.4n 0.85 0.1324 36.5n 0.85 0.13316 36.6n 0.85 0.13406 36.7n 0.85 0.13454 36.8n 0.85 0.13611 36.9n 0.85 0.13525 37.n 0.85 0.13708 37.1n 0.85 0.13624 37.2n 0.85 0.13831 37.3n 0.85 0.13785 37.4n 0.85 0.14003 37.5n 0.85 0.14074 37.6n 0.85 0.14438 37.7n 0.85 0.15019 37.8n 0.85 0.29837 37.9n 0.85 0.74561 38.n 0.85 1.522 38.1n 0.85 1.9135 38.2n 0.85 2.2985 38.3n 0.85 2.7232 38.4n 0.85 3.0782 38.5n 0.85 3.3999 38.6n 0.85 3.6318 38.7n 0.85 3.8218 38.8n 0.85 3.9768 38.9n 0.85 4.1023 39.n 0.85 4.1973 39.1n 0.85 4.2628 39.2n 0.85 4.3144 39.3n 0.85 4.3631 39.4n 0.85 4.4019 39.5n 0.85 4.4252 39.6n 0.85 4.4419 39.7n 0.85 4.4558 39.8n 0.85 4.468 39.9n 0.85 4.4788 40.n 0.85 4.4875 40.1n 1.55 4.3273 40.2n 1.55 1.1408 40.3n 1.55 0.34243 40.4n 1.55 0.27132 40.5n 1.55 0.20765 40.6n 1.55 0.2362 40.7n 1.55 0.24506 40.8n 1.55 0.22431 40.9n 1.55 0.19815 41.n 1.55 0.20647 41.1n 1.55 0.21256 41.2n 1.55 0.19135 41.3n 1.55 0.22497 41.4n 1.55 0.18112 41.5n 1.55 0.23197 41.6n 1.55 0.17747 41.7n 1.55 0.23218 41.8n 1.55 0.18063 41.9n 1.55 0.22613 42.n 1.55 0.18922 42.1n 1.55 0.21582 42.2n 1.55 0.2007 42.3n 1.55 0.2041 42.4n 1.55 0.21208 42.5n 1.55 0.19394 42.6n 1.55 0.22064 42.7n 1.55 0.18763 42.8n 1.55 0.2246 42.9n 1.55 0.18635 43.n 1.55 0.22344 43.1n 1.55 0.18997 43.2n 1.55 0.21793 43.3n 1.55 0.19717 43.4n 1.55 0.2098 43.5n 1.55 0.20591 43.6n 1.55 0.20128 43.7n 1.55 0.21394 43.8n 1.55 0.19447 43.9n 1.55 0.21941 44.n 1.55 0.19088 44.1n 1.55 0.22124 44.2n 1.55 0.19111 44.3n 1.55 0.21934 44.4n 1.55 0.19476 44.5n 1.55 0.21452 44.6n 1.55 0.20067 44.7n 1.55 0.20824 44.8n 1.55 0.20721 44.9n 1.55 0.20215 45.n 1.55 0.21277 45.1n 1.55 0.19775 45.2n 0.85 -0.12329 45.3n 0.85 -0.020915 45.4n 0.85 0.046305 45.5n 0.85 0.090732 45.6n 0.85 0.11417 45.7n 0.85 0.12002 45.8n 0.85 0.1219 45.9n 0.85 0.12946 46.n 0.85 0.13108 46.1n 0.85 0.1333 46.2n 0.85 0.13499 46.3n 0.85 0.13548 46.4n 0.85 0.13704 46.5n 0.85 0.13603 46.6n 0.85 0.13807 46.7n 0.85 0.13649 46.8n 0.85 0.13898 46.9n 0.85 0.13724 47.n 0.85 0.13982 47.1n 0.85 0.13855 47.2n 0.85 0.14071 47.3n 0.85 0.14078 47.4n 0.85 0.14198 47.5n 0.85 0.14472 47.6n 0.85 0.1462 47.7n 0.85 0.16037 47.8n 0.85 0.34105 47.9n 0.85 1.0725 48.n 0.85 1.7907 48.1n 0.85 2.2304 48.2n 0.85 2.6501 48.3n 0.85 3.0353 48.4n 0.85 3.3584 48.5n 0.85 3.6216 48.6n 0.85 3.8371 48.7n 0.85 3.9944 48.8n 0.85 4.1245 48.9n 0.85 4.2239 49.n 0.85 4.2972 49.1n 0.85 4.3626 49.2n 0.85 4.3995 49.3n 0.85 4.4453 49.4n 0.85 4.4601 49.5n 0.85 4.4938 49.6n 0.85 4.4964 49.7n 0.85 4.5213 49.8n 0.85 4.5189 49.9n 0.85 4.5361 50.n 0.85 4.5337 gnucap> Thanks Ramiro. El 20/07/11 04:25, al davis escribió:On Tuesday 19 July 2011, Ramiro Aceves wrote:I have a convergence problem:Quick answer, based on experience, so I can give you an immediate response .. Convergence problems are often tied to the model used. You are using the old "modelgen" BJT model, which will be phased out. Try instead to use the Spice BJT model from the spice models tarball. The modelgen models in gnucap (analogous to the spice "code- models") check convergence by recursively checking the subcircuit. This often results in overly critical checking, where really everything is ok, but it indicates non-convergence. Convergence checking in the spice models is less critical, so often just switching to the other model will solve the problem. Try this .. get the plugin tarball http://gnucap.org/devel/gnucap-2009-12-07-models-spice3f5.tar.gz unpack it, compile the "bjt" model .. "load" it as a plugin. More detailed response, for the curious .. The modelgen models use an underlying subcircuit, and check every part of it individually for convergence, the equivalent of checking every state variable and the derivatives separately, then a check pass checks all of the voltages node-to-node. To accept, all must pass. This includes the internal nonlinear capacitances, and all strays. The down side is that occasionally one of the strays can get stuck on amplified numerical noise and never be accepted, when in fact it could be ignored. Spice uses a quick check for convergence, where only a few parameters are checked, as a composite. This method often accepts incorrect values as converged, sometimes leading to believable incorrect results. Gnucap with the spice model is somewhere in the middle .. It first uses the spice method, it's part of the model code, then checks node-to-node voltages. The node-to-node check seems to catch the false convergence problems. Convergence handling is a big issue in simulator and model design. There are trade-offs, impossible to really know what is best in general.
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