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    jdsp.jpanner node issue

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    • C
      crd
      last edited by

      The jdsp.jpanner node works with a sine generator but doesn't not work with samplers with multi mic samples as a polyphonic scriptnode fx.

      1 Reply Last reply Reply Quote 0
      • Christoph HartC
        Christoph Hart
        last edited by

        well, it's a stereo panner, so I'm not surprised it fails with more channels. Just use a container.multi node and duplicate the panners.

        C 2 Replies Last reply Reply Quote 0
        • C
          crd @Christoph Hart
          last edited by

          @christoph-hart
          duh.. sorry. Yes that works perfectly.

          1 Reply Last reply Reply Quote 0
          • C
            crd @Christoph Hart
            last edited by crd

            @christoph-hart

            For some reason when using the jdsp.panner node, I am unable to hard pan to the left when playing short notes in a sequence. It works as expected with long notes. It seems like it has something to do with the peak node because going directly from the global mod input to the panner works as expected.

            Here is a snippet demonstrating the issue:

            HiseSnippet 3956.3oc6cs7baabFGjRfxj100twMMSmzoXzzGzMNxDfjxRMI0xVObzDKaUSEmzISp6JfUhHBDKK.ndjFeoSmo8Puz68efdoG5wdIYl9OPuz+.RtzSclzqsGZ+1cwiEj.7AHEscFpCRD6teO2e6te6G1kZWGhN10k3Hkq3dm0FKk6RxMNy1q45MQl1RaugTtWUtsMYO7odcbvtOogoM9Dzw2Ca+jiUQR28r1HWWrgTtbycOJE4JNuD6mu712EYgr0wQEII8XhoN99lsL8hJc20dGSKqsPF38LaIz5ZqssNwdchEoCncyIWQpMR+Hzg3GfnMKurTtBaZX5QbZ3g7vtR4l+tDiyZzjbhMu8O1z0beKL8AUoF.i3EuEwxfpwzRkVuookwtAdAWIfo6F4Sli6Stl7NlFlgkG4atBqBkHJD8G4xGW8lKl5oJpdUDTuDTo4ETo44pzUkan6X11KpFp9bQ4ss8vNGf.2tnpvaqTtOSdcBz.aukZgNBukC7PHAkWtRkan.+55uwAcr08LI1JD6GP7vOzt70K8qJUrzSKozcUGbPh0QEiCwxB6jX0zdZm9QXY6Ns1G6bCkiQVcvgMDL+39T4z8ohc45bqVngD6ssM8dXarcZ.AIeWE7o2c6MPdHniHmeYP6Zic7LopPtMvGCnZd2RQ4MvtG4QZC35grO6k7KMBEolXe2eTVYV+xTre4BxsQ16PLD6Lx62Yj+6uX3HIWr2aiMOroW4pzwNkDJ+8LM7ZVVsBq7Rk.q00C7bNJbNeezYXGUk2RgMi6RGh817fCv5dkWTr9EozxIkW76XS12En5C9PnBgh9fJeHTZf3QFrRKuH1936zhzw1awannVuxOBFjyTGQJUSjx6u0CUiQpJmTQJ0RiRsXTp0KkUSixpwnrZuTVKQJWec0tsS0JcSZ8zHsGCsWZWNQZeL1hna5cV2lauzeqDo+QHaCRqtMYUeHyADGkxl.cUdCESk2TYE3Ou1qQG2o.+HxcyOjh3JuXKhAF3yh6hroHmTaloMzpWWcIlfJlXSPmRUn9zBWOb6FleLUdUVphJzrmFGWsRhl7c77fUxW7F7dIsdbTqDSG84bhMfqgUpjNK78FzI1VLUwXXXg2k3ZRmqCZMLNdodFhrZhlxFXczYbKQMAKY0AYIqNPKY0trj6CAfgbn1xMuYxhZXrF0jmqnQGWODUW4f3dMHfttrnzagH7IdSRd5lGgsvHWLW3USR3pCxcF0hT8mQMY.NTAoMTdzjmI7sgfMCQ506QYzFn6TKQKJdaRdpTnI9qfvjesazCuqNPoWcvcl05qv0BDduyGBTNHwWavhudeEe0.wm.Zp9.Ee8AK9kSS7PDX.sbwWuWW+xCT3KmnvCWPPsJeEA0ke9eIAlRqqXZKJ2qWpnNkF+HKWGYYsOrrPYhsPi7qjsVXISaKXrpXTo81xx5jVsI1PugXLpvRzHKP9F3SAWm.UKwJ6gGDQFUTEcOwzSuI3no0BJJvhh27lPjTve0g4nTp7igOUz7fxLYn7SfEnuNsDZCKVTL7MpIBK34XteGOb430vjhZX2+HPZah6lAw0EXnLF7T5uvVfJlc0QcjUGa7gBpyNHHZVz9tbmy04rhqbvu22AiN5MXNTqCHpAdT0t7nbmxHaDD1vtHe5n6.zxX+QTzxozgDZau4Dx1xhoko9VQSqb28t8ZlJ914a8ViugVe75H.pKNFFKk7.naHxM.5pE.c0ljPWsr28VM6HWsoAxc7Lsrhb0l9HWsrib0FOjq1PgbqFfbqNIQtUyd2asribqNMPtimokUja0oOxsZ1QtUGOja09hbYEbyat95gwKTqGnqfMGrStjjs5xYuyrdFwog4lZHfoSGyPcjAjB1vPfGEfiijAUerbtUxxHsDoOQrWH3q9KXfuuRf9d9E9M13ugB.drellC.gKOIW7tV16OuUFwkwyb946B3im4koEv617ldKhWKiH4t03LrPdRrHsEycXu4i.z7sljn45Yu6dkLhlEeONmuX4wy3xDVNtwM8Px0yHRNt9lAbbuLHYTb.VFwdkVEC.yqv.yCo3tSHbgKj3iRLnugoPFu5nv3M5Kic4uqmPVqVYT3ci9xaG9qxIh2piBueTe4cShkQDi0FEF+18kwPSUrXMLj6UGEtuKx1m+2TiMHKlPhKhvbGox2GSrHSzhKjpURVsiywv8zqVuWNVMUN1SSqMhBmOPUglh+VDiNVHZp4C0kk80k0I1tDK7RscLs8De+HInAIDXVhZPIZ9jeJ8kjO6XwHdrXxcUesBZpG6.tbY+C3RCKSCrijoA8jhEdtPjXJs3wzSZHXvkjiRT5XvAswlCUGGNbQ4vc+kUUHJ78rwgqHGOnorwkKKKtjU13wEj4mLirQ8BxrCCQ1Htnr+QOHqj6e3AxF4Ejoul9rhfBeO6iKCzFWFTcLX.e93DXPVNjczof7eep.rZnlD5TQgdl3CwO+EwqQ7.G+otcN3.ySoSPdeI567FluUFVTl5CFBkI1DZQZyms+ZOyzFsd0FmmcZS0dzFkO4Yh1HNocZvle1ZSMWivB.oAalZZSOKljFzYpoQcsvTZfmIr9TbvKxkFxwLMMAbfAmtE+xV6y+3eysizN9inHF+69aqwUvBxr61fnFtv.WHMMvjYFTCQIKODqBmFrIYYOb1UzhzoABFWKqvfVgOk970HIK3zkzEFp3AD7h+5gclxzP2cMHXTUFsTUl9Mx6bRYplpxXNYUF4gJlmHko8uMd2Thf8rewNpN6hcLUuXGWQdGdJIhemsnWTscByUQr9D5sgxFfdmIdQ1lXWjqgUEup7tzr0lrNlOAcD7TmG5n+0e6qIyuWJQJ37xa89mO20MQweAt3+1x2yhrOxJxQAXBPSv7gYeG+pUBqWIrAp84BJ92G1KnX6g9BJlat9cgDUy3ERb9m6tPhCKN9k5oqwcJNZK2BBpYAtZ9p9yIS6IeLxwDY6EpaLUt.aWfCVKuqYahExQbd7uPXd71N31HG7djcsPmU1E0psE9Qf8bCE9mc2E6bWHP8i5cJ41bklUa48g07vNotXvDechAsZf7P22n1eDTzb8O.6cBw4HZGVN+OCnJZegLsuP5NVVjSnqoa5OWH3xYksKw5r1MI1l5zh3s.CfOaark+tMxImKOaxwGvCCeKjNn8msKxqIcVV8f4IVRODyxEZT+OCkAV3tHGTKrG1wkacTNFL1WNGOSKsZwh5fd0jmiVuajnko79RxP.Lq7j8ocsRwzkWVPWDZSb0HKh7pxm3fZSb0govnfb03x8kDjqM4IPvWlYTn4hYmQBTpGetCdIgpGMoQ6ksvmFDcvFltsgAX2kMJwsmRfm2ldB9oKX85vbqB8gz64cvSfn1wz9w7LeIKWYoJR6fNM74ZvyMBCDTVVEdlOUwNTS9Nc7HsfgCASfKv1BQrs.ksZB7sfrZkXL9ZPKXWuG3G0ZqVQUcYXLzQ3S3NPdCzzVc0J0purlV0ZqbqUp6equ2xA+K6fs0OqeZSLiTMlQBJyxoXkWhwbkGQG6IEibog0AplpC7dfllNSmePLkxjEj2sIcOkwZ3HykBrfB6VUhB5LN1IVM4x4+Dr9PdtGaa2GSqUGYEvQXZHgwGKH2FiNpqghWjOzfVynMnX9I2fh3lbT7m6gbND6MocCEkcMOTC1JWbGwkkaQOeAA0MR9h7wFhmazAS7h5BLkFNPPb9KYsfbilHHPiAMexi6NM6rc5XiYqC6F+QfFpUusQWSrFJ6sMBmLZTmGSpaCn.a3tzfbVg5uay+v+5St8+318U+KLX8WbNry+YMyDx8tDxQsPrHUF6MnNRgipMKbzYgiNKbzYgiNKbzYgiNKbzYgid9EN5m+wW6OeuO++b6WLCGkVYMoYghd9EJZ0YghNKTzYghNKTzYghNKTzYghNKTzyuPQ+4+0suT9Wag0dQMyn+dq+4+8O8u+hYYFczBGsT34I.VwMJlL+HPVe8Q6cy+tt38Pr3thR0911GC5Ck9nxhDzCXw2IxtFsHDulwO6GlqsA9.TGKudSje9IUffCoSo.6.HOk8J+f0dNvq3e9fJEdlmY9iuY3iQG6jyG2yFXcy8wVroWNus0E315E7OM09GuF9CSR6jyQVwrww70NNGLnLe92l6q1m+sGQ53YZe3NHOG5gcUFF40.VSWOX+atAacy+4JAq12.aavd3+A+3WoJ84b9UpFTonIdYtIdQY5Wr+ruGpYF3KydV48PGiUtGF1CTunKgSS2u3m9t+kI+oo6g5df32yAY6BaSKFiafaYtGwl5oiJDfyzUJ4wiGaVLjShU8k2dKvHSjlFHuNNLnWv9kEfZyNkeOubfZYAnz0+.KtB.coQ8uoM8KLEnDpN9Mj8WYJnz3X4cH1jfDlHLWHFFCd3gwiFHQCx+JkDVx0VK3pNDVz2aM9WzvwWsXj7EpCuune8Wuh+MfQgN.T4E2CB8WsWHHotyKKSyrGOqpfboJv2RNJYeJ922fsdesDunAeW4jRn4ypbXdY5MvvFVpaaWWHXwgKYl4GljYJODIyrKo2+MOGqCdtrt29tS.YIYXS7bMJlBeMAENrEoqf4qkKvVTXtZEjqB9z1.NEanbhoWSEKBTmMA5TWpToSZhsUnI8fRfaShiGupanXYdDVAo3xl9TwkuoSLkhyTLcs+gdJldJMQNFzuAksw.2svG34yQPSUfOfsflpf7TTUtcoRk0ahgIZ7ZhUZZ5hUfXaZ2wSgs21qWpDvtVcb8T1GjFAJrIUk7HJFDtdSoqDMsO7uZIvPC0QcneAy34apLQSa1g7CZNUK.4qy2hMngFlNvGrNixVZ6XZtSoRSv9z4hkeWth7jdxcie9cEptOXtutrf6ztKkc9AkJpb45tPXiCAIZPVFYXDOCCA41YSaZX+r6XRThFhlYMJWCB6MN9EjhG6jPNFhZ4lm11AlefMxFFRIMpolKuep43gvtIrcTCHbJ9dTBBqMsLbUX3LmJq0q4.lXhlCOkVbcpK1bg0DSkG2eGCJThmFOZ4iv7N4SOYah15BS9ttDx+WDIBoUOdNLKvRka5YxcDL8wCwWT9i3i5ii54Wdv9h4+xO8EJLe7GhkU8VPnulRottHu5rtHnTRuoqHudWov9iLbauTPcSF7e99i+G2tQ9vXJZY.n+QeJmWYDmxof7if0Ak5wX5CNXrSN6zHiDSCYzBo6PdhNOrWJr4BrRfEvsY+GErn7NzmUB+dbgmfe5a98I55AuTnjoQKCzTMCzTKCzTOCzrbFn4VYflU5KMzrb3OBiNGJTvtaxm8KWz71yI8+ArxEcdG
            

            I've spent an embarrassing amount of time to try and get a modulation system working for panning and this issue is stumping me.

            1 Reply Last reply Reply Quote 0
            • C
              crd
              last edited by

              Here is a gif of the issue if that helps:peaknodeissue.gif

              Any guidance would be appreciated.

              Using this same system works well on filters... The mul node is there so I can control the amount of modulation.

              1 Reply Last reply Reply Quote 0
              • Christoph HartC
                Christoph Hart
                last edited by

                Your doing a lot of unnecesary conversions between control and audio signals. You just need three nodes

                global_mod -> pma (Or bipolar) -> panner

                C 1 Reply Last reply Reply Quote 0
                • C
                  crd @Christoph Hart
                  last edited by

                  @christoph-hart

                  the multiplier is an amount knob. I suppose I can just use the bi polar node's scale as an amount knob...

                  I intend to sum many modulators before sending them to the panner which is why I am using the peak module.

                  Here is a snippet that shows the whole system:

                  HiseSnippet 5396.3oc68jzbaikdfR5QIRuz1ic2yTYoBhRpNpy3VF6jL8zoksVbqZrrUY5wyT0Tc4.Q9jDJCBv.BIa0c02leBoxobK2y0bLSkSysjpxufI+.RMmykj2B1df.D.jfKRMYWUaA7V9Veeeeuu2BN1wtCbv.aGtJ0d8U8gbUtMn8UVtmu645FVbGtGWk+XPeK6WC+f6ENvAussgE785W9Ln0auTh6oW0Wev.XWtJUV8Y3FTo1Zbbb676+1+gu5o5l5Vcfduh76M1FcfO2nmga3aOdmetgo4A5cgu1nWjZqrygcrs101z9BDxsJPfqudm2oeF7E53psBfqR086Z3Z6z1U2ENfqxZO0t6UsO298Vz5+FiAFmXBwOHx0F0QzWefsYWLFieK2tmaX18Xelv.NTmdbHKYUJK4gfiL5ZD79PVy8HEvG1hn7iJqvhdqxfdhogdIfRqDAkVihR2GztiiQe2vRv3ys.GZ4BcNUGw1ihJz5xU42B10FUAK2s6o+N3ANnGBZvVZBBOhG8+9ru3zKr53ZXawaa8BaW3Ks15yp+c0qU+6qyGunSOMwxvfww1zD5jXwXIsynZ3VVWz6Dnyi3uT27BXPEQjOKOEjOdZGJUGoh1VGZY39x9PqzTD37XUn+5Wb3d5t5HAQEu2gpWeniqAFEprG7RjVMUrTCrGbv6bs6izqyoLaCPecqir6lj.akU3CjXCfteMz3ryc2RFKitS8HE7KM55d9VhBzBv+GhhG3h3dN7zd+45WAcD4+Rdxf6sOC5t+omB63t0lQKeSZyoMlVvO2x9jAn18q+FRQQd4uV3aPu2GKz6Rd6VaBst7I8ruvxcyGwKpJ7WiTp7vpnsULw197CdoHSiE8ZbzlJkVSkXZpTBMUNslJyzT4DZpRhMc2cEiSrhBC0V0zZ6PDaBMVKwF+FnocGC2qhSxIzAMRrCdktUW6dwIawPMnSsc32x.0Tguf2f+mw2D8O+ze5mcm5e2cpyi9EEDFeCVKbqM6Y2Eh5rMOV2hnJkZ8LrPU6yE2lBtZIVG8OfwqQUkAtv9sM9VLHE1VPDWuuOthVyDo9m35hblr4inxLogYZMYvT+dOwZPwSAgQzIdrErYuMSGRc6ZBO1dfA1T3lDSwH3N7PmVIRQ6A6neEkfDShfZkIA0JaBpULB54nfAzcHjziebxPKFQImLMIlrsj1WLvUGivTs6DHKTCiQWinJLZTwpTxFjdEzDpO.RQ.4DQ.wLYrgUIcNaXcxh0FAf4j2lrAyuFEFTv..0gQHorYrRISWwpUxFcQUwymCAGTdzvcub1XfbdDsJiDAj7QfDLchZZlnfRdPA0QhBx9nPR5WpYiBp4AEzRCEPwvgZMEETSPLnkMBnkBBD3CQTl5DQT65iWDBx2g2vJJvQXdsN314En5t5llmfbkrksUjZ4UHkI73G+xCNn89ulWiG4xm26gF3GBdpI+9u3M3JaXYhF3GMh3g61s5X2qusERN5GeLgcVCEQftIBe6B+.hkGocaSd2KOMrgTLq1f2a314bjHBWNlzvcSsG+XTLb3+nCxzGuveC9OqYb5VDXw+2RUAHujT8Z0hFBIl2f7t5XbxEtvsXJou8f88CNzGy+hB0CVvyhzC9phn1+8j+OzDguAH5OarQTVvLNHJKolAh9keYIwRovo1DyRQsNDYOwAp+tufpWXdpsXfhgXYpXDF4+XqYDsKllpFSJpFiZSCU4KEsiggTsImuln9QfFhTfFhTIqgHM4ZHRyHMDoIWCQZlogHM4ZHREQCQNPCQtj0PjmbMD4YjFh7jqgHOyzPjmbMD4b4igpifBMJPEQoLUQBxWyXqgDoGllJHSHhxRpSW0ig.TsIlmlp4i.0iP8C0RV+nDTPlUZHkfJxrSGoDTRJlVxkdoHMPSQqL0TXS.6XqsDuallZLkAJm.kOc0bRFZ0JG9bfFD8ei6Fxgji7.8mFko9Sz7uO1ZOrcxzT2YxQ2gn4oqdSRvpVYveGQfKgZN5j0WnVfpSSppSNg7SB3v0RVwrKNY+g8dqB066kUuOfl08v9WTnP.ncV.vglU8H.PrP.3UYAfysM6Fo2kJTu+0Y06nZyaRpaHHjKDHNV2xCHOVJpRE6LkBfS3LpE8hF1eIAnYvlERxBoQ.w51vogIplP2JmZ2NbcUJNJXSR6LONKq8r6dgoNNemgXjlOFsqs0.aS318cLrbilv5jviXLcQszwCzSjz798dK240l87P0xZOOL5MBS39enx88vPTUcI6jg65sSFZaZzE5vYzEu0SBV3eNBADce+vkiN31fvDMMA8fzD2CxSRObKPvjYFWTHLP2wqGtGfMXmwqWtKHpyuwqO1.PWmclVuyu+a+MeUdZ85.xZZGCz+je6N4ow0.dqcLSy4kk+u9p70buU9ks4f+t+4bA8p.7pqFmo8WtS9zfBVZzwUELXoMmzNPdB5.pU5D5fwY2TgMA4szUH0pbYD5CbU.Uvv6J++fcAyihS8Lh73e3eavEmdpwGvFFeNGdwHQc..4xFS64.IXLjQvh+w4EVHEEKdTk4DVHGEK92mCXQTixrpEcmkrhHF1YUKlgXwPNGXUMlgXRLGLrJGkNdTKamTrZF+tzwf9+q63umAh5SyCq9tG9u7Lxi5nNrV068W4gyDDqJfrImihYqmoCPVkELhUbvGEhfb30jUsHMXlO5HzYJqPdxojpY4AlUl9+lF.SGBajK+zDv7qVIWV1RSaMlRcQQBoXHQ24ARHGCI9ckMR.xULGDj3+Ip3HQk2g2g12CbDcpnraxe7Ia3nf4nxrQswaedKDocUDL9qhuy+WK8YrIj6ClPdQ26CNFuodRFeWIA7Ee.Clx3q24n3N.5lNODYWCbvuZjGZhRGU1fhJ+QfmYZehtYHCDEKJBqfzMk+epWw7AkyGTAwzN0Kne+m48TuzO2m5kJqlaNRANkKqMsNkKyTc8GLjXZPwGctZ9v3DXhqGAMqRQy+DOKSXo5azcLzsbCvMBJWkL6frwxmZz21T2I5o24+FDl0n9Nv95NvWaero9UaMPuWeS3qPzyi3o+8figNOEEn26FNgS8oHMozsNAYCF5jZptJ8rfkUtt.kzYlJxo24EP22a67Nr.qh2eizpvxB.VVv8DSS62i8wX3YuDwxIu6Xayq5etskQG7qn0.hT9rrfldQshburBGoiog2cfdGD1e0w5tmisD2w2lw1cBzYo.MT9SzxPT3w5N58ftPmATpC2i91AnNwPXPOhWP7YeaUb4jCGFEz.beea.xgZy2dBVzxwfKeRDbIRcXQiwAj2G7dG891C5fLmgUxEYg6Ch.WK62hBFvXLAZEF5LDfbCwycfaGo3hAMrT1D9A+LTrmwf9nAXOkLJYvPuA87g3sNK1Q1miLjEQFhOHg9Og.0QFVuglID.PXaAtiz+PvyJnmaGDfB.HhdlZp3HLI+jKbs6gFN3asLR2VMraqh6VoH8aUfn.SG+PTMH6QezOQkVBhhZnwPuC9dJCjVAIoVsDTT0jjjUZ1nop2wJ7.G3e+EPqNWMJrggHEYHRDxnkBUdaRmy+J7XONllykWFnXpLvmgvzz6z0xpSwcx5fiOGO2ElJV3doJIHx3nRXhuX0cXJoREumP9GVgxwNbvavk1Q2zuGQlghL9XcPen96hMT7VzgF3RJ1fh0JuAErjbXLpuV24LnaYyFpAFXblDZpErLh6BPJvmuseYEhWrByP7JEWYh9pXJSooGDAbdtrVGz9bcTfFYYOw6g0ARa2rkFMWqVPhW3AbLOhZAllOraLypAP9vtAlhJpULt3neUxfctrXUdOfMHo1RRHxOwQSJUylThZLa5a9brTgmzyabghEUZYrnKiEcYrnKiEcYrnKiEcYrnKiEcYrnKiEcNEKp7xXQWFK5xXQWFK5xXQWFK5xXQWFK5xXQWFKZ4EKZ8fsR.xcaX.Ydger6tEaY4+ECfuVmDzU3V83PqKQ3Ct8guKDPufDbWztqcOaa2yY2BHF6rG7T8KLceS7sNcocihlWlRUxdVcFyU9zcV.3JdaSn5AaWVB+3iCdLbGmLcXO6A6XbBzjXcYZSqqSo0M71Ptd6rF5CkIcR6QxqIiioNNlBDzXu83V8GlaOtWYegqg0YGo65f2Ol.zHx1HG8c7mT2.+4y48rfeH.sgVcIO7+g94UnH94JdEJ5WXTx8tTx8V.7cIM49nkPreB4Y9eo9kP9mAQSLZXstna1teyG8eT9a1tW1wEA9W6naM.M2MlNtMrmwqssvb8vWhTywdMoAoyXcS2Iwh9Ce0AHhLw1zV28BGhJo+jninBNoaBPgataBvIe+4N96.vJGOz8m98Ppw3oEruE9Bn.8FLN9i.ddu7eKqd8Q1V19YTIh8RHZ73YmwFwPhDj2IXH3Mati+NtO3U+S6PuQQY8nTHdgX94EiRd8S7NvE73Ai72L1W0W6bbTph46BvoDjlNVDbwHvcAQOU1IdYz+mARJAnyqbd9wdH7aonmEZXxaj3FJemXXkThQGYVPWI+YAMYzn7xJZ8HoAnN.MMeJnYvrGFAyBpw3kbx0h.tM.5m2cP7DgdO7Q1jXRbaRwECPfQNMxOBGISDNk+boIREt1jK+zfLrTYknufan4SuRz4Sul+7oqANwKnWlIS6mOirlPOWhcZc+NUdL60QRIbEMsUqDMsU6ilrVWj4ofH3YSLyFImE133YM.IkAEOQBhsZn0PTqonlhjprjr2mPAOGf4MIriNQoeBtbAeTQogRqFJphDHcGOH8bHRmM8DnNynb+iHX9xE9zEW7NxcScYP3gTbQfpCObikIg2h9qQCMklRpMkXT918BmKYRUpZ4uj.j7ulTdnYRirusuDbrg7kusewEy2QBPsRk3uLR1YqBz61UJYKk6agy1fmDIZVM+bwjraxXJa0wMI1iPQHm8S6N5lEQgRkoejvx3X5tZxBsjP5uMEZppznUCO.8L8d8zG0pu3E4Bs1cPJ5wD12ltlAzRXkyQCictu5ALg8D3cctp2Bv5sW6TaS.GDV.0aKykK6VAwIKMSBT91fyHmpw2NzJz4sJ9QJtXKXYRpnqLBUza4OTQTnPJpoDVZtfjXY.oRb6JTIetVGwJ4uNf16YZl0SaKjmOOrOUkwupZYXfJjoPVNQwYfEqBDDjGNs.64cCpmWwq8tdiNJetpauNV2VQ95uxcJtiW30tKI+yqy5eVtv9miNRY37pUX+2UoySKzAsXwbfWfAtSfyboYlyb4e35LuJqAOohYvq.JBEdhGDiehpWOl5wMQG4RWmcjGSuVdtqWGyot5Rm5WycpWk0otxD4TeRcfKsH5.WYl4.W8luCbo7YnSYAyAtjxRG3yKG3x2fbfqtn4.WaoC7aVNvUKrC7.0H.nSGwLz4x1Gt7b2Gd0g1ZGkgK7gUxyCjUmJPdw1Gu7nrEFQlrf4hu4RW7yKW7Mu16hOx.9EK0ZkFW6TqW5POpCcsw2g95XG5h0mXW5pKNSKOXbl1TdV4A.pwM+IkqjKKaZKXV1jEV5vdd4vV8liC6FKZSIu4xojeyxCdi4ZN00V.mOdyYz7wG1adqa9dyUykYulKXl8jutt+ftNuKy87lqcywadqEMu4st9qV+Cqcgdrc4VyB67Noc1VY5PWYQbQx0lYKR9O.lOtV9VLwEsIjKos7bgMi7X23FzZhunMAbUgktruVevwDmZGbrGFAddmDVFPUmNNDeTCC5f6C5aOfGZcIuN4hpndlvNeCDSQuaj5JobRQnGNxLoj6ArfmEgRV7HDuSQUlTxegW3T7FV8uvkWjudcrPx7TawxPJAJt0gwgZ8OWMYRt+HhfCQc7hkfnaVRch4PX9iYElR0qinToEvgY9aY5znnR5NfcVJejTxV97wLxGYh3QdQU5nciR5zLaoyeNizQod8NcD4wFC8rCtvNNpQdb8hIFrsuEVWu9qjYlzxlLxIUhb55gfpYdbPQnlRRRMKGhImC2ueJinSqd8K8uWaKKw2LMfiV4wje.IFJSutPfRZYSfOhQj1ndcG5E3KpW4srcg0iHYWPGWplCiNOD3QWWCGYpjC5qJ9B.bAmh7VeCuOT.xE3qHvh5ESPUxGFhx56BQQSU4FfObpdWnyhUZjSkYEftwtHG8SRlWoEimwjpkUx2E43p.o.rzupdeQFBXJu5n1E9pdL4OcBUAmgSSSru+Cjqj5PoxFH1nfvH2nIYdWy8.f51JRRRMDZzPoohnrPqLtRGSAiWmfwhyKTtTG.SyoG4VwqopVKklMUkm9eoTVGz6BSWCtTu4VoEO4etn7TtRx.zYEN4fqjZdcqN8E6Q9p9Ld2OiaPteFK90ynrfnfr.9tSroRqFdd0tEf9wjvv5r3atzYNW41fWAG.cKheI+QvK0KVpWLBmyLx0OM9GWn6hS2+9VW5cqTmyOxPzGFoilruEjoqqSlAsLLFihtOILNkEQh4g7gxoeGKGGmSAlCgz0.CH9nEyOGNAzkYQuvc6pfmD+6wjXF2lsdUZnZjunFBtmtY3KA2wxyhKV2DXB6UP.OM3A921xyZVvZTVP6IRwJkusYISog2wxS7U1bBxxWMQxxbXXpZVTm+c17bRR904Bvdu3A.DXPO2TUnIxOVilhRSD06cOcOWH8OB6J54G7Rwh5KJ+F1GwcV5X5M5ivdiRDoKO2Qi39OcR8GIUZ9iXDgRktHLO2Tc4SDNhc5RLYpTAkodkVT5XbCxHaBwWJKOcjxxyBorxzVJKOajxpScorR4JkqArO8TzTODKzWdTAYjwcQAEkVRhManjanHULnnzRF4rSSTVB4wSM2PQtHPQoUylJZnIF1TCCF4LgBYtT6tq3zaXQ52PHk0nBxrqRhFlX2YfrurQJ8gDpSACe3u5oy.Ir1T0tWhDwTPD2XpKh0JWQ7CvhX+OjqSu.QS+nENlwg9.rTMU7dJHYaM0krMlN9yTJlO.sF3UUnQiVRszZ1HSnP19rzOlsyhownURpO2Gq9jBZOMlHSixdhLMKnTsoffDZxphZBhpZ4V2oj8m..GqawRzw2953m8d3GiKUPnklrnZKwFX0QUAA0bx682jAY7QiKyS4RLNh1zYP5TZreyIraK5BFR9lS9Ta620Sm7gkb79J0OK9DLOKfQO8NN1u0am.P9f.RdChMYoS9zKCNB+LuH2kQkB8L5Z71Nc72FBI2FownMxiQaTFi1nNFsQaLZSiwnMMGYaveVm8VPNr0DzKNde5G2wJA67jJqx8+2jD7QA
                  

                  Using two gain nodes works -- but I'd love to make use of the pan law in the jpanner if possible.

                  C 1 Reply Last reply Reply Quote 0
                  • C
                    crd @crd
                    last edited by

                    @Christoph-Hart

                    Do you have any advice about how to sum modulation signals?

                    It gets complicated when it is different types of modulation like add a bi polar LFO with midi CC1 and env. Sometimes negative amounts become positive ...

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