diff options
Diffstat (limited to 'klippy/extras/shaper_defs.py')
| -rw-r--r-- | klippy/extras/shaper_defs.py | 95 |
1 files changed, 52 insertions, 43 deletions
diff --git a/klippy/extras/shaper_defs.py b/klippy/extras/shaper_defs.py index 611fed16..1cd7aeed 100644 --- a/klippy/extras/shaper_defs.py +++ b/klippy/extras/shaper_defs.py @@ -5,98 +5,107 @@ # This file may be distributed under the terms of the GNU GPLv3 license. import collections, math -SHAPER_VIBRATION_REDUCTION=20. +SHAPER_VIBRATION_REDUCTION = 20.0 DEFAULT_DAMPING_RATIO = 0.1 InputShaperCfg = collections.namedtuple( - 'InputShaperCfg', ('name', 'init_func', 'min_freq')) + "InputShaperCfg", ("name", "init_func", "min_freq") +) + def get_none_shaper(): return ([], []) + def get_zv_shaper(shaper_freq, damping_ratio): - df = math.sqrt(1. - damping_ratio**2) + df = math.sqrt(1.0 - damping_ratio**2) K = math.exp(-damping_ratio * math.pi / df) - t_d = 1. / (shaper_freq * df) - A = [1., K] - T = [0., .5*t_d] + t_d = 1.0 / (shaper_freq * df) + A = [1.0, K] + T = [0.0, 0.5 * t_d] return (A, T) + def get_zvd_shaper(shaper_freq, damping_ratio): - df = math.sqrt(1. - damping_ratio**2) + df = math.sqrt(1.0 - damping_ratio**2) K = math.exp(-damping_ratio * math.pi / df) - t_d = 1. / (shaper_freq * df) - A = [1., 2.*K, K**2] - T = [0., .5*t_d, t_d] + t_d = 1.0 / (shaper_freq * df) + A = [1.0, 2.0 * K, K**2] + T = [0.0, 0.5 * t_d, t_d] return (A, T) + def get_mzv_shaper(shaper_freq, damping_ratio): - df = math.sqrt(1. - damping_ratio**2) - K = math.exp(-.75 * damping_ratio * math.pi / df) - t_d = 1. / (shaper_freq * df) + df = math.sqrt(1.0 - damping_ratio**2) + K = math.exp(-0.75 * damping_ratio * math.pi / df) + t_d = 1.0 / (shaper_freq * df) - a1 = 1. - 1. / math.sqrt(2.) - a2 = (math.sqrt(2.) - 1.) * K + a1 = 1.0 - 1.0 / math.sqrt(2.0) + a2 = (math.sqrt(2.0) - 1.0) * K a3 = a1 * K * K A = [a1, a2, a3] - T = [0., .375*t_d, .75*t_d] + T = [0.0, 0.375 * t_d, 0.75 * t_d] return (A, T) + def get_ei_shaper(shaper_freq, damping_ratio): - v_tol = 1. / SHAPER_VIBRATION_REDUCTION # vibration tolerance - df = math.sqrt(1. - damping_ratio**2) + v_tol = 1.0 / SHAPER_VIBRATION_REDUCTION # vibration tolerance + df = math.sqrt(1.0 - damping_ratio**2) K = math.exp(-damping_ratio * math.pi / df) - t_d = 1. / (shaper_freq * df) + t_d = 1.0 / (shaper_freq * df) - a1 = .25 * (1. + v_tol) - a2 = .5 * (1. - v_tol) * K + a1 = 0.25 * (1.0 + v_tol) + a2 = 0.5 * (1.0 - v_tol) * K a3 = a1 * K * K A = [a1, a2, a3] - T = [0., .5*t_d, t_d] + T = [0.0, 0.5 * t_d, t_d] return (A, T) + def get_2hump_ei_shaper(shaper_freq, damping_ratio): - v_tol = 1. / SHAPER_VIBRATION_REDUCTION # vibration tolerance - df = math.sqrt(1. - damping_ratio**2) + v_tol = 1.0 / SHAPER_VIBRATION_REDUCTION # vibration tolerance + df = math.sqrt(1.0 - damping_ratio**2) K = math.exp(-damping_ratio * math.pi / df) - t_d = 1. / (shaper_freq * df) + t_d = 1.0 / (shaper_freq * df) V2 = v_tol**2 - X = pow(V2 * (math.sqrt(1. - V2) + 1.), 1./3.) - a1 = (3.*X*X + 2.*X + 3.*V2) / (16.*X) - a2 = (.5 - a1) * K + X = pow(V2 * (math.sqrt(1.0 - V2) + 1.0), 1.0 / 3.0) + a1 = (3.0 * X * X + 2.0 * X + 3.0 * V2) / (16.0 * X) + a2 = (0.5 - a1) * K a3 = a2 * K a4 = a1 * K * K * K A = [a1, a2, a3, a4] - T = [0., .5*t_d, t_d, 1.5*t_d] + T = [0.0, 0.5 * t_d, t_d, 1.5 * t_d] return (A, T) + def get_3hump_ei_shaper(shaper_freq, damping_ratio): - v_tol = 1. / SHAPER_VIBRATION_REDUCTION # vibration tolerance - df = math.sqrt(1. - damping_ratio**2) + v_tol = 1.0 / SHAPER_VIBRATION_REDUCTION # vibration tolerance + df = math.sqrt(1.0 - damping_ratio**2) K = math.exp(-damping_ratio * math.pi / df) - t_d = 1. / (shaper_freq * df) + t_d = 1.0 / (shaper_freq * df) - K2 = K*K - a1 = 0.0625 * (1. + 3. * v_tol + 2. * math.sqrt(2. * (v_tol + 1.) * v_tol)) - a2 = 0.25 * (1. - v_tol) * K - a3 = (0.5 * (1. + v_tol) - 2. * a1) * K2 + K2 = K * K + a1 = 0.0625 * (1.0 + 3.0 * v_tol + 2.0 * math.sqrt(2.0 * (v_tol + 1.0) * v_tol)) + a2 = 0.25 * (1.0 - v_tol) * K + a3 = (0.5 * (1.0 + v_tol) - 2.0 * a1) * K2 a4 = a2 * K2 a5 = a1 * K2 * K2 A = [a1, a2, a3, a4, a5] - T = [0., .5*t_d, t_d, 1.5*t_d, 2.*t_d] + T = [0.0, 0.5 * t_d, t_d, 1.5 * t_d, 2.0 * t_d] return (A, T) + # min_freq for each shaper is chosen to have projected max_accel ~= 1500 INPUT_SHAPERS = [ - InputShaperCfg('zv', get_zv_shaper, min_freq=21.), - InputShaperCfg('mzv', get_mzv_shaper, min_freq=23.), - InputShaperCfg('zvd', get_zvd_shaper, min_freq=29.), - InputShaperCfg('ei', get_ei_shaper, min_freq=29.), - InputShaperCfg('2hump_ei', get_2hump_ei_shaper, min_freq=39.), - InputShaperCfg('3hump_ei', get_3hump_ei_shaper, min_freq=48.), + InputShaperCfg("zv", get_zv_shaper, min_freq=21.0), + InputShaperCfg("mzv", get_mzv_shaper, min_freq=23.0), + InputShaperCfg("zvd", get_zvd_shaper, min_freq=29.0), + InputShaperCfg("ei", get_ei_shaper, min_freq=29.0), + InputShaperCfg("2hump_ei", get_2hump_ei_shaper, min_freq=39.0), + InputShaperCfg("3hump_ei", get_3hump_ei_shaper, min_freq=48.0), ] |