circuitpython/tests/circuitpython/synth_block_max.py.exp

-1.978606282552083 2.0 2.0 2.0
-1.957273600260416 2.0 2.0 2.0
-1.93594091796875 2.0 2.0 2.0
-1.914608235677083 2.0 2.0 2.0
-1.893275553385417 2.0 2.0 2.0
-1.87194287109375 2.0 2.0 2.0
-1.850610188802083 2.0 2.0 2.0
-1.829277506510417 2.0 2.0 2.0
-1.80794482421875 2.0 2.0 2.0
-1.786612141927083 2.0 2.0 2.0
-1.765279459635417 2.0 2.0 2.0
-1.74394677734375 2.0 2.0 2.0
-1.722614095052083 2.0 2.0 2.0
-1.701281412760417 2.0 2.0 2.0
-1.67994873046875 2.0 2.0 2.0
-1.658616048177083 2.0 2.0 2.0
-1.637283365885417 2.0 2.0 2.0
-1.61595068359375 2.0 2.0 2.0
-1.594618001302083 2.0 2.0 2.0
-1.573285319010417 2.0 2.0 2.0
-1.55195263671875 2.0 2.0 2.0
-1.530619954427083 2.0 2.0 2.0
-1.509287272135417 2.0 2.0 2.0
-1.48795458984375 2.0 2.0 2.0
-1.466621907552084 2.0 2.0 2.0
-1.445289225260417 2.0 2.0 2.0
-1.42395654296875 2.0 2.0 2.0
-1.402623860677084 2.0 2.0 2.0
-1.381291178385417 2.0 2.0 2.0
-1.35995849609375 2.0 2.0 2.0
-1.338625813802083 2.0 2.0 2.0
-1.317293131510417 2.0 2.0 2.0
-1.29596044921875 2.0 2.0 2.0
-1.274627766927084 2.0 2.0 2.0
-1.253295084635417 2.0 2.0 2.0
-1.23196240234375 2.0 2.0 2.0
-1.210629720052084 2.0 2.0 2.0
-1.189297037760417 2.0 2.0 2.0
-1.16796435546875 2.0 2.0 2.0
-1.146631673177084 2.0 2.0 2.0
-1.125298990885417 2.0 2.0 2.0
-1.10396630859375 2.0 2.0 2.0
-1.082633626302084 2.0 2.0 2.0
-1.061300944010417 2.0 2.0 2.0
-1.039968261718751 2.0 2.0 2.0
-1.018635579427084 2.0 2.0 2.0
-0.9973028971354172 2.0 2.0 2.0
-0.9759702148437505 2.0 2.0 2.0
-0.9546375325520838 2.0 2.0 2.0
-0.9333048502604168 2.0 2.0 2.0
-0.9119721679687501 2.0 2.0 2.0
-0.8906394856770833 2.0 2.0 2.0
-0.8693068033854166 2.0 2.0 2.0
-0.8479741210937499 2.0 2.0 2.0
-0.8266414388020831 2.0 2.0 2.0
-0.8053087565104164 2.0 2.0 2.0
-0.7839760742187497 2.0 2.0 2.0
-0.7626433919270829 2.0 2.0 2.0
-0.7413107096354159 2.0 2.0 2.0
-0.7199780273437493 2.0 2.0 2.0
-0.6986453450520828 2.0 2.0 2.0
-0.6773126627604157 2.0 2.0 2.0
-0.6559799804687488 2.0 2.0 2.0
-0.6346472981770823 2.0 2.0 2.0
-0.6133146158854156 2.0 2.0 2.0
-0.5919819335937487 2.0 2.0 2.0
-0.5706492513020819 2.0 2.0 2.0
-0.5493165690104153 2.0 2.0 2.0
-0.5279838867187485 2.0 2.0 2.0
-0.5066512044270817 2.0 2.0 2.0
-0.4853185221354149 2.0 2.0 2.0
-0.4639858398437481 2.0 2.0 2.0
-0.4426531575520815 2.0 2.0 2.0
-0.4213204752604147 2.0 2.0 2.0
-0.3999877929687479 2.0 2.0 2.0
-0.3786551106770811 2.0 2.0 2.0
-0.3573224283854145 2.0 2.0 2.0
-0.3359897460937477 2.0 2.0 2.0
-0.3146570638020807 2.0 2.0 2.0
-0.2933243815104141 2.0 2.0 2.0
-0.2719916992187476 2.0 2.0 2.0
-0.2506590169270807 2.0 2.0 2.0
-0.2293263346354136 2.0 2.0 2.0
-0.2079936523437471 2.0 2.0 2.0
-0.1866609700520805 2.0 2.0 2.0
-0.1653282877604135 2.0 2.0 2.0
-0.1439956054687467 2.0 2.0 2.0
-0.1226629231770801 2.0 2.0 2.0
-0.1013302408854133 2.0 2.0 2.0
-0.07999755859374647 2.0 2.0 2.0
-0.05866487630207972 2.0 2.0 2.0
-0.0373321940104131 2.0 2.0 2.0
-0.01599951171874625 2.0 2.0 2.0
0.005333170572920487 2.0 2.0 2.0
0.026665852864587 2.0 2.0 2.0
0.04799853515625363 2.0 2.0 2.0
0.06933121744792015 2.0 2.0 2.0
0.09066389973958666 2.0 2.0 2.0
0.1119965820312533 2.0 2.0 2.0
0.1333292643229198 2.0 2.0 2.0
0.1546619466145862 2.0 2.0 2.0
0.1759946289062527 2.0 2.0 2.0
0.1973273111979195 2.0 2.0 2.0
0.2186599934895859 2.0 2.0 2.0
0.2399926757812524 2.0 2.0 2.0
0.261325358072919 2.0 2.0 2.0
0.2826580403645855 2.0 2.0 2.0
0.303990722656252 2.0 2.0 2.0
0.3253234049479187 2.0 2.0 2.0
0.3466560872395852 2.0 2.0 2.0
0.3679887695312516 2.0 2.0 2.0
0.3893214518229181 2.0 2.0 2.0
0.4106541341145848 2.0 2.0 2.0
0.4319868164062513 2.0 2.0 2.0
0.4533194986979177 2.0 2.0 2.0
0.4746521809895844 2.0 2.0 2.0
0.4959848632812509 2.0 2.0 2.0
0.5173175455729173 2.0 2.0 2.0
0.5386502278645841 2.0 2.0 2.0
0.5599829101562506 2.0 2.0 2.0
0.581315592447917 2.0 2.0 2.0
0.6026482747395835 2.0 2.0 2.0
0.6239809570312501 2.0 2.0 2.0
0.6453136393229166 2.0 2.0 2.0
0.6666463216145831 2.0 2.0 2.0
0.6879790039062498 2.0 2.0 2.0
0.7093116861979163 2.0 2.0 2.0
0.7306443684895827 2.0 2.0 2.0
0.7519770507812495 2.0 2.0 2.0
0.773309733072916 2.0 2.0 2.0
0.7946424153645824 2.0 2.0 2.0
0.8159750976562488 2.0 2.0 2.0
0.8373077799479155 2.0 2.0 2.0
0.858640462239582 2.0 2.0 2.0
0.8799731445312485 2.0 2.0 2.0
0.9013058268229152 2.0 2.0 2.0
0.9226385091145817 2.0 2.0 2.0
0.9439711914062482 2.0 2.0 2.0
0.9653038736979148 2.0 2.0 2.0
0.9866365559895813 2.0 2.0 2.0
1.007969238281248 2.0 2.0 2.0
1.029301920572914 2.0 2.0 2.0
1.050634602864581 2.0 2.0 2.0
1.071967285156247 2.0 2.0 2.0
1.093299967447914 2.0 2.0 2.0
1.114632649739581 2.0 2.0 2.0
1.135965332031247 2.0 2.0 2.0
1.157298014322913 2.0 2.0 2.0
1.17863069661458 2.0 2.0 2.0
1.199963378906247 2.0 2.0 2.0
1.221296061197913 2.0 2.0 2.0
1.24262874348958 2.0 2.0 2.0
1.263961425781246 2.0 2.0 2.0
1.285294108072913 2.0 2.0 2.0
1.306626790364579 2.0 2.0 2.0
1.327959472656246 2.0 2.0 2.0
1.349292154947912 2.0 2.0 2.0
1.370624837239579 2.0 2.0 2.0
1.391957519531245 2.0 2.0 2.0
1.413290201822912 2.0 2.0 2.0
1.434622884114579 2.0 2.0 2.0
1.455955566406245 2.0 2.0 2.0
1.477288248697912 2.0 2.0 2.0
1.498620930989578 2.0 2.0 2.0
1.519953613281245 2.0 2.0 2.0
1.541286295572911 2.0 2.0 2.0
1.562618977864578 2.0 2.0 2.0
1.583951660156244 2.0 2.0 2.0
1.605284342447911 2.0 2.0 2.0
1.626617024739577 2.0 2.0 2.0
1.647949707031244 2.0 2.0 2.0
1.66928238932291 2.0 2.0 2.0
1.690615071614577 2.0 2.0 2.0
1.711947753906244 2.0 2.0 2.0
1.73328043619791 2.0 2.0 2.0
1.754613118489577 2.0 2.0 2.0
1.775945800781243 2.0 2.0 2.0
1.79727848307291 2.0 2.0 2.0
1.818611165364576 2.0 2.0 2.0
1.839943847656243 2.0 2.0 2.0
1.861276529947909 2.0 2.0 2.0
1.882609212239576 2.0 2.0 2.0
1.903941894531243 2.0 2.0 2.0
1.925274576822909 2.0 2.0 2.0
1.946607259114575 2.0 2.0 2.0
1.967939941406242 2.0 2.0 2.0
1.989272623697909 2.0 2.0 2.0
1.99981689825654 2.0 2.0 2.0