/* support_float.ino - Small floating point support for Tasmota Copyright (C) 2020 Theo Arends and Stephan Hadinger This program is free software: you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation, either version 3 of the License, or (at your option) any later version. This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details. You should have received a copy of the GNU General Public License along with this program. If not, see . */ //#ifdef ARDUINO_ESP8266_RELEASE_2_3_0 // Functions not available in 2.3.0 float fmodf(float x, float y) { // https://github.com/micropython/micropython/blob/master/lib/libm/fmodf.c union {float f; uint32_t i;} ux = {x}, uy = {y}; int ex = ux.i>>23 & 0xff; int ey = uy.i>>23 & 0xff; uint32_t sx = ux.i & 0x80000000; uint32_t i; uint32_t uxi = ux.i; if (uy.i<<1 == 0 || isnan(y) || ex == 0xff) return (x*y)/(x*y); if (uxi<<1 <= uy.i<<1) { if (uxi<<1 == uy.i<<1) return 0*x; return x; } // normalize x and y if (!ex) { for (i = uxi<<9; i>>31 == 0; ex--, i <<= 1); uxi <<= -ex + 1; } else { uxi &= -1U >> 9; uxi |= 1U << 23; } if (!ey) { for (i = uy.i<<9; i>>31 == 0; ey--, i <<= 1); uy.i <<= -ey + 1; } else { uy.i &= -1U >> 9; uy.i |= 1U << 23; } // x mod y for (; ex > ey; ex--) { i = uxi - uy.i; if (i >> 31 == 0) { if (i == 0) return 0*x; uxi = i; } uxi <<= 1; } i = uxi - uy.i; if (i >> 31 == 0) { if (i == 0) return 0*x; uxi = i; } for (; uxi>>23 == 0; uxi <<= 1, ex--); // scale result up if (ex > 0) { uxi -= 1U << 23; uxi |= (uint32_t)ex << 23; } else { uxi >>= -ex + 1; } uxi |= sx; ux.i = uxi; return ux.f; } //#endif // ARDUINO_ESP8266_RELEASE_2_3_0 double FastPrecisePow(double a, double b) { // https://martin.ankerl.com/2012/01/25/optimized-approximative-pow-in-c-and-cpp/ // calculate approximation with fraction of the exponent int e = abs((int)b); union { double d; int x[2]; } u = { a }; u.x[1] = (int)((b - e) * (u.x[1] - 1072632447) + 1072632447); u.x[0] = 0; // exponentiation by squaring with the exponent's integer part // double r = u.d makes everything much slower, not sure why double r = 1.0; while (e) { if (e & 1) { r *= a; } a *= a; e >>= 1; } return r * u.d; } float FastPrecisePowf(const float x, const float y) { // return (float)(pow((double)x, (double)y)); return (float)FastPrecisePow(x, y); } double TaylorLog(double x) { // https://stackoverflow.com/questions/46879166/finding-the-natural-logarithm-of-a-number-using-taylor-series-in-c if (x <= 0.0) { return NAN; } double z = (x + 1) / (x - 1); // We start from power -1, to make sure we get the right power in each iteration; double step = ((x - 1) * (x - 1)) / ((x + 1) * (x + 1)); // Store step to not have to calculate it each time double totalValue = 0; double powe = 1; for (uint32_t count = 0; count < 10; count++) { // Experimental number of 10 iterations z *= step; double y = (1 / powe) * z; totalValue = totalValue + y; powe = powe + 2; } totalValue *= 2; /* char logxs[33]; dtostrfd(x, 8, logxs); double log1 = log(x); char log1s[33]; dtostrfd(log1, 8, log1s); char log2s[33]; dtostrfd(totalValue, 8, log2s); AddLog_P2(LOG_LEVEL_DEBUG, PSTR("input %s, log %s, taylor %s"), logxs, log1s, log2s); */ return totalValue; } // Following code adapted from: http://www.ganssle.com/approx.htm // ============================================================== // The following code implements approximations to various trig functions. // // This is demo code to guide developers in implementing their own approximation // software. This code is merely meant to illustrate algorithms. inline float sinf(float x) { return sin_52(x); } inline float cosf(float x) { return cos_52(x); } inline float tanf(float x) { return tan_56(x); } inline float atanf(float x) { return atan_66(x); } inline float asinf(float x) { return asinf1(x); } inline float acosf(float x) { return acosf1(x); } inline float sqrtf(float x) { return sqrt1(x); } inline float powf(float x, float y) { return FastPrecisePow(x, y); } // Math constants we'll use double const f_pi = 3.1415926535897932384626433; // f_pi double const f_twopi = 2.0 * f_pi; // f_pi times 2 double const f_two_over_pi = 2.0 / f_pi; // 2/f_pi double const f_halfpi = f_pi / 2.0; // f_pi divided by 2 double const f_threehalfpi = 3.0 * f_pi / 2.0; // f_pi times 3/2, used in tan routines double const f_four_over_pi = 4.0 / f_pi; // 4/f_pi, used in tan routines double const f_qtrpi = f_pi / 4.0; // f_pi/4.0, used in tan routines double const f_sixthpi = f_pi / 6.0; // f_pi/6.0, used in atan routines double const f_tansixthpi = tan(f_sixthpi); // tan(f_pi/6), used in atan routines double const f_twelfthpi = f_pi / 12.0; // f_pi/12.0, used in atan routines double const f_tantwelfthpi = tan(f_twelfthpi); // tan(f_pi/12), used in atan routines float const f_180pi = 180 / f_pi; // 180 / pi for angles in degrees // ******************************************************************* // *** // *** Routines to compute sine and cosine to 5.2 digits of accuracy. // *** // ******************************************************************* // // cos_52s computes cosine (x) // // Accurate to about 5.2 decimal digits over the range [0, f_pi/2]. // The input argument is in radians. // // Algorithm: // cos(x)= c1 + c2*x**2 + c3*x**4 + c4*x**6 // which is the same as: // cos(x)= c1 + x**2(c2 + c3*x**2 + c4*x**4) // cos(x)= c1 + x**2(c2 + x**2(c3 + c4*x**2)) // float cos_52s(float x) { const float c1 = 0.9999932946; const float c2 = -0.4999124376; const float c3 = 0.0414877472; const float c4 = -0.0012712095; float x2 = x * x; // The input argument squared return (c1 + x2 * (c2 + x2 * (c3 + c4 * x2))); } // // This is the main cosine approximation "driver" // It reduces the input argument's range to [0, f_pi/2], // and then calls the approximator. // See the notes for an explanation of the range reduction. // float cos_52(float x) { x = fmodf(x, f_twopi); // Get rid of values > 2* f_pi if (x < 0) { x = -x; } // cos(-x) = cos(x) int quad = int(x * (float)f_two_over_pi); // Get quadrant # (0 to 3) we're in switch (quad) { case 0: return cos_52s(x); case 1: return -cos_52s((float)f_pi - x); case 2: return -cos_52s(x-(float)f_pi); case 3: return cos_52s((float)f_twopi - x); } } // // The sine is just cosine shifted a half-f_pi, so // we'll adjust the argument and call the cosine approximation. // float sin_52(float x) { return cos_52((float)f_halfpi - x); } // ******************************************************************* // *** // *** Routines to compute tangent to 5.6 digits of accuracy. // *** // ******************************************************************* // // tan_56s computes tan(f_pi*x/4) // // Accurate to about 5.6 decimal digits over the range [0, f_pi/4]. // The input argument is in radians. Note that the function // computes tan(f_pi*x/4), NOT tan(x); it's up to the range // reduction algorithm that calls this to scale things properly. // // Algorithm: // tan(x)= x(c1 + c2*x**2)/(c3 + x**2) // float tan_56s(float x) { const float c1 = -3.16783027; const float c2 = 0.134516124; const float c3 = -4.033321984; float x2 = x * x; // The input argument squared return (x * (c1 + c2 * x2) / (c3 + x2)); } // // This is the main tangent approximation "driver" // It reduces the input argument's range to [0, f_pi/4], // and then calls the approximator. // See the notes for an explanation of the range reduction. // Enter with positive angles only. // // WARNING: We do not test for the tangent approaching infinity, // which it will at x=f_pi/2 and x=3*f_pi/2. If this is a problem // in your application, take appropriate action. // float tan_56(float x) { x = fmodf(x, (float)f_twopi); // Get rid of values >2 *f_pi int octant = int(x * (float)f_four_over_pi); // Get octant # (0 to 7) switch (octant){ case 0: return tan_56s(x * (float)f_four_over_pi); case 1: return 1.0f / tan_56s(((float)f_halfpi - x) * (float)f_four_over_pi); case 2: return -1.0f / tan_56s((x-(float)f_halfpi) * (float)f_four_over_pi); case 3: return - tan_56s(((float)f_pi - x) * (float)f_four_over_pi); case 4: return tan_56s((x-(float)f_pi) * (float)f_four_over_pi); case 5: return 1.0f / tan_56s(((float)f_threehalfpi - x) * (float)f_four_over_pi); case 6: return -1.0f / tan_56s((x-(float)f_threehalfpi) * (float)f_four_over_pi); case 7: return - tan_56s(((float)f_twopi - x) * (float)f_four_over_pi); } } // ******************************************************************* // *** // *** Routines to compute arctangent to 6.6 digits of accuracy. // *** // ******************************************************************* // // atan_66s computes atan(x) // // Accurate to about 6.6 decimal digits over the range [0, f_pi/12]. // // Algorithm: // atan(x)= x(c1 + c2*x**2)/(c3 + x**2) // float atan_66s(float x) { const float c1 = 1.6867629106; const float c2 = 0.4378497304; const float c3 = 1.6867633134; float x2 = x * x; // The input argument squared return (x * (c1 + x2 * c2) / (c3 + x2)); } // // This is the main arctangent approximation "driver" // It reduces the input argument's range to [0, f_pi/12], // and then calls the approximator. // float atan_66(float x) { float y; // return from atan__s function bool complement= false; // true if arg was >1 bool region= false; // true depending on region arg is in bool sign= false; // true if arg was < 0 if (x < 0) { x = -x; sign = true; // arctan(-x)=-arctan(x) } if (x > 1.0) { x = 1.0 / x; // keep arg between 0 and 1 complement = true; } if (x > (float)f_tantwelfthpi) { x = (x - (float)f_tansixthpi) / (1 + (float)f_tansixthpi * x); // reduce arg to under tan(f_pi/12) region = true; } y = atan_66s(x); // run the approximation if (region) { y += (float)f_sixthpi; } // correct for region we're in if (complement) { y = (float)f_halfpi-y; } // correct for 1/x if we did that if (sign) { y = -y; } // correct for negative arg return (y); } float asinf1(float x) { float d = 1.0f - x * x; if (d < 0.0f) { return NAN; } return 2 * atan_66(x / (1 + sqrt1(d))); } float acosf1(float x) { float d = 1.0f - x * x; if (d < 0.0f) { return NAN; } float y = asinf1(sqrt1(d)); if (x >= 0.0f) { return y; } else { return (float)f_pi - y; } } // https://www.codeproject.com/Articles/69941/Best-Square-Root-Method-Algorithm-Function-Precisi float sqrt1(const float x) { union { int i; float x; } u; u.x = x; u.i = (1 << 29) + (u.i >> 1) - (1 << 22); // Two Babylonian Steps (simplified from:) // u.x = 0.5f * (u.x + x/u.x); // u.x = 0.5f * (u.x + x/u.x); u.x = u.x + x / u.x; u.x = 0.25f * u.x + x / u.x; return u.x; } // // changeUIntScale // Change a value for range a..b to c..d, using only unsigned int math // // New version, you don't need the "to_min < to_max" precondition anymore // // PRE-CONDITIONS (if not satisfied, you may 'halt and catch fire') // from_min < from_max (not checked) // from_min <= num <= from-max (chacked) // POST-CONDITIONS // to_min <= result <= to_max // uint16_t changeUIntScale(uint16_t inum, uint16_t ifrom_min, uint16_t ifrom_max, uint16_t ito_min, uint16_t ito_max) { // guard-rails if (ifrom_min >= ifrom_max) { if (ito_min > ito_max) { return ito_max; } else { return ito_min; // invalid input, return arbitrary value } } // convert to uint31, it's more verbose but code is more compact uint32_t num = inum; uint32_t from_min = ifrom_min; uint32_t from_max = ifrom_max; uint32_t to_min = ito_min; uint32_t to_max = ito_max; // check source range num = (num > from_max ? from_max : (num < from_min ? from_min : num)); // check to_* order if (to_min > to_max) { // reverse order num = (from_max - num) + from_min; to_min = ito_max; to_max = ito_min; } uint32_t numerator = (num - from_min) * (to_max - to_min); uint32_t result; if (numerator >= 0x80000000L) { // don't do rounding as it would create an overflow result = numerator / (from_max - from_min) + to_min; } else { result = (((numerator * 2) / (from_max - from_min)) + 1) / 2 + to_min; } return (uint32_t) (result > to_max ? to_max : (result < to_min ? to_min : result)); } // Force a float value between two ranges, and adds or substract the range until we fit float ModulusRangef(float f, float a, float b) { if (b <= a) { return a; } // inconsistent, do what we can float range = b - a; float x = f - a; // now range of x should be 0..range x = fmodf(x, range); // actual range is now -range..range if (x < 0.0f) { x += range; } // actual range is now 0..range return x + a; // returns range a..b } // Compute a n-degree polynomial for value x and an array of coefficient (by increasing order) // Ex: // For factors = { f0, f1, f2, f3 } // Returns : f0 + f1 x + f2 x^2, + f3 x^3 // Internally computed as : f0 + x (f1 + x (f2 + x f3)) float Polynomialf(const float *factors, uint32_t degree, float x) { float r = 0.0f; for (uint32_t i = degree - 1; i >= 0; i--) { r = r * x + factors[i]; } return r; }