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poly.lowpass.maxpat
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poly.lowpass.maxpat
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"code" : "// padé approximation of tan by michael massberg\r\n\r\ntan_a(x) {\n\tx2 = x * x;\n\treturn x * (0.999999492001 + x2 * -0.096524608111) / \r\n\t(1 + x2 * (-0.429867256894 + x2 * 0.009981877999));\n}\r\n\r\n// asymmetrical nonlinearity for filter loop\r\n\r\nasym(x) {\r\n\treturn (exp(x * 1.19) - exp(-x * 1.047)) / (exp(x * 1.2) + exp(-x));\r\n}\r\n\r\n// sallen-key lowpass coefficients calculation\r\n\r\nlp_calc(cf, q) {\r\n\tT = 1 / samplerate;\n T_div_two = T / 2;\n two_div_T = 2 / T;\n\n wd = twopi * cf;\n wa = two_div_T * tan_a(wd * T_div_two);\n g = wa * T_div_two;\n G = g / (1 + g);\r\n\r\n\tK = 0.1 + ((2 - 0.1) * (q / 10));\r\n\r\n\tlpf2_beta = (K - (K * G)) / (1 + g);\n hpf1_beta = -1 / (1 + g);\n alpha = 1 / (1 - (K * G) + (K * G * G));\r\n\r\n\treturn wd, wa, g, G, K, lpf2_beta, hpf1_beta, alpha;\r\n}\r\n\r\n// sallen-key lowpass filter process\r\n\r\nlp_process(xin, wd, wa, g, G, K, lpf2_beta, hpf1_beta, alpha) {\n History z1(0), z2(0), z3(0), S35(0);\n\n v1 = (xin - z1) * G;\n lp1 = v1 + z1;\n z1 = lp1 + v1;\n\r\n\trand0 = noise() > 0.925;\r\n\trand1 = latch(noise(), delta(rand0));\r\n\trand2 = rand0 * rand1;\r\n\n u = alpha * (lp1 + S35);\r\n\tu = asym(u);\n\n v2 = (u - z2) * G;\n lp2 = v2 + z2;\n z2 = lp2 + v2;\n y = K * lp2;\n\n v3 = (y - z3) * G;\n lp3 = v3 + z3;\n z3 = lp3 + v3;\n\n S35 = (lpf2_beta * z2) + (hpf1_beta * z3);\n\n return ((K > 0) ? (y / K) : y) + rand2 * 0.0001;\n}\r\n\r\nxin = in1;\ncut = in2;\nres = in3;\r\n\r\nwd, wa, g, G, K, lpf2_beta, hpf1_beta, alpha = lp_calc(cut, res);\n\nlp0 = lp_process(xin * 0.25, wd, wa, g, G, K, lpf2_beta, hpf1_beta, alpha);\r\nlp1 = lp_process(lp0 * 0.25, wd, wa, g, G, K, lpf2_beta, hpf1_beta, alpha);\r\n\r\nout1 = lp1 / clip(res * 0.26, 1, 9);",
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