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import numpy as np |
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def _fast_cross(a, b): |
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return np.concatenate([ |
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a[...,1:2]*b[...,2:3] - a[...,2:3]*b[...,1:2], |
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a[...,2:3]*b[...,0:1] - a[...,0:1]*b[...,2:3], |
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a[...,0:1]*b[...,1:2] - a[...,1:2]*b[...,0:1]], axis=-1) |
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def eye(shape, dtype=np.float32): |
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return np.ones(list(shape) + [4], dtype=dtype) * np.asarray([1, 0, 0, 0], dtype=dtype) |
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def length(x): |
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return np.sqrt(np.sum(x * x, axis=-1)) |
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def normalize(x, eps=1e-8): |
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return x / (length(x)[...,None] + eps) |
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def abs(x): |
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return np.where(x[...,0:1] > 0.0, x, -x) |
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def inv(q): |
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return np.array([1, -1, -1, -1], dtype=np.float32) * q |
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def dot(x, y): |
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return np.sum(x * y, axis=-1)[...,None] if x.ndim > 1 else np.sum(x * y, axis=-1) |
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def mul(x, y): |
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x0, x1, x2, x3 = x[..., 0:1], x[..., 1:2], x[..., 2:3], x[..., 3:4] |
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y0, y1, y2, y3 = y[..., 0:1], y[..., 1:2], y[..., 2:3], y[..., 3:4] |
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return np.concatenate([ |
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y0 * x0 - y1 * x1 - y2 * x2 - y3 * x3, |
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y0 * x1 + y1 * x0 - y2 * x3 + y3 * x2, |
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y0 * x2 + y1 * x3 + y2 * x0 - y3 * x1, |
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y0 * x3 - y1 * x2 + y2 * x1 + y3 * x0], axis=-1) |
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def inv_mul(x, y): |
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return mul(inv(x), y) |
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def mul_inv(x, y): |
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return mul(x, inv(y)) |
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def mul_vec(q, x): |
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t = 2.0 * _fast_cross(q[..., 1:], x) |
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return x + q[..., 0][..., None] * t + _fast_cross(q[..., 1:], t) |
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def inv_mul_vec(q, x): |
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return mul_vec(inv(q), x) |
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def unroll(x): |
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y = x.copy() |
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for i in range(1, len(x)): |
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d0 = np.sum( y[i] * y[i-1], axis=-1) |
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d1 = np.sum(-y[i] * y[i-1], axis=-1) |
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y[i][d0 < d1] = -y[i][d0 < d1] |
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return y |
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def between(x, y): |
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return np.concatenate([ |
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np.sqrt(np.sum(x*x, axis=-1) * np.sum(y*y, axis=-1))[...,None] + |
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np.sum(x * y, axis=-1)[...,None], |
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_fast_cross(x, y)], axis=-1) |
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def log(x, eps=1e-5): |
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length = np.sqrt(np.sum(np.square(x[...,1:]), axis=-1))[...,None] |
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halfangle = np.where(length < eps, np.ones_like(length), np.arctan2(length, x[...,0:1]) / length) |
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return halfangle * x[...,1:] |
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def exp(x, eps=1e-5): |
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halfangle = np.sqrt(np.sum(np.square(x), axis=-1))[...,None] |
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c = np.where(halfangle < eps, np.ones_like(halfangle), np.cos(halfangle)) |
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s = np.where(halfangle < eps, np.ones_like(halfangle), np.sinc(halfangle / np.pi)) |
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return np.concatenate([c, s * x], axis=-1) |
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def fk(lrot, lpos, parents): |
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gp, gr = [lpos[...,:1,:]], [lrot[...,:1,:]] |
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for i in range(1, len(parents)): |
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gp.append(mul_vec(gr[parents[i]], lpos[...,i:i+1,:]) + gp[parents[i]]) |
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gr.append(mul (gr[parents[i]], lrot[...,i:i+1,:])) |
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return np.concatenate(gr, axis=-2), np.concatenate(gp, axis=-2) |
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def fk_rot(lrot, parents): |
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gr = [lrot[...,:1,:]] |
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for i in range(1, len(parents)): |
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gr.append(mul(gr[parents[i]], lrot[...,i:i+1,:])) |
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return np.concatenate(gr, axis=-2) |
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def ik(grot, gpos, parents): |
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return ( |
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np.concatenate([ |
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grot[...,:1,:], |
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mul(inv(grot[...,parents[1:],:]), grot[...,1:,:]), |
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], axis=-2), |
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np.concatenate([ |
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gpos[...,:1,:], |
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mul_vec( |
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inv(grot[...,parents[1:],:]), |
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gpos[...,1:,:] - gpos[...,parents[1:],:]), |
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], axis=-2)) |
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def ik_rot(grot, parents): |
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return np.concatenate([grot[...,:1,:], |
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mul(inv(grot[...,parents[1:],:]), grot[...,1:,:]), |
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], axis=-2) |
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def fk_vel(lrot, lpos, lvel, lang, parents): |
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gp, gr, gv, ga = [lpos[...,:1,:]], [lrot[...,:1,:]], [lvel[...,:1,:]], [lang[...,:1,:]] |
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for i in range(1, len(parents)): |
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gp.append(mul_vec(gr[parents[i]], lpos[...,i:i+1,:]) + gp[parents[i]]) |
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gr.append(mul (gr[parents[i]], lrot[...,i:i+1,:])) |
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gv.append(mul_vec(gr[parents[i]], lvel[...,i:i+1,:]) + |
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_fast_cross(ga[parents[i]], mul_vec(gr[parents[i]], lpos[...,i:i+1,:])) + |
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gv[parents[i]]) |
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ga.append(mul_vec(gr[parents[i]], lang[...,i:i+1,:]) + ga[parents[i]]) |
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return ( |
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np.concatenate(gr, axis=-2), |
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np.concatenate(gp, axis=-2), |
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np.concatenate(gv, axis=-2), |
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np.concatenate(ga, axis=-2)) |
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def lerp(x, y, t): |
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return (1 - t) * x + t * y |
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def quat_lerp(x, y, t): |
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return normalize(lerp(x, y, t)) |
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def slerp(x, y, t): |
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if t == 0: |
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return x |
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elif t == 1: |
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return y |
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if dot(x, y) < 0: |
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y = - y |
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ca = dot(x, y) |
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theta = np.arccos(np.clip(ca, 0, 1)) |
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r = normalize(y - x * ca) |
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return x * np.cos(theta * t) + r * np.sin(theta * t) |
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def to_euler(x, order='zyx'): |
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q0 = x[...,0:1] |
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q1 = x[...,1:2] |
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q2 = x[...,2:3] |
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q3 = x[...,3:4] |
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if order == 'zyx': |
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return np.concatenate([ |
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np.arctan2(2 * (q0 * q3 + q1 * q2), 1 - 2 * (q2 * q2 + q3 * q3)), |
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np.arcsin((2 * (q0 * q2 - q3 * q1)).clip(-1,1)), |
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np.arctan2(2 * (q0 * q1 + q2 * q3), 1 - 2 * (q1 * q1 + q2 * q2))], axis=-1) |
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elif order == 'yzx': |
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return np.concatenate([ |
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np.arctan2(2 * (q2 * q0 - q1 * q3), q1 * q1 - q2 * q2 - q3 * q3 + q0 * q0), |
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np.arcsin((2 * (q1 * q2 + q3 * q0)).clip(-1,1)), |
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np.arctan2(2 * (q1 * q0 - q2 * q3), -q1 * q1 + q2 * q2 - q3 * q3 + q0 * q0)],axis=-1) |
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elif order == 'zxy': |
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return np.concatenate([ |
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np.arctan2(2 * (q0 * q3 - q1 * q2), q0 * q0 - q1 * q1 + q2 * q2 - q3 * q3), |
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np.arcsin((2 * (q0 * q1 + q2 * q3)).clip(-1,1)), |
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np.arctan2(2 * (q0 * q2 - q1 * q3), q0 * q0 - q1 * q1 - q2 * q2 + q3 * q3)], axis=-1) |
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elif order == 'yxz': |
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return np.concatenate([ |
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np.arctan2(2 * (q1 * q3 + q0 * q2), q0 * q0 - q1 * q1 - q2 * q2 + q3 * q3), |
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np.arcsin((2 * (q0 * q1 - q2 * q3)).clip(-1,1)), |
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np.arctan2(2 * (q1 * q2 + q0 * q3), q0 * q0 - q1 * q1 + q2 * q2 - q3 * q3)], axis=-1) |
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else: |
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raise NotImplementedError('Cannot convert from ordering %s' % order) |
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def to_xform(x): |
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qw, qx, qy, qz = x[...,0:1], x[...,1:2], x[...,2:3], x[...,3:4] |
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x2, y2, z2 = qx + qx, qy + qy, qz + qz |
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xx, yy, wx = qx * x2, qy * y2, qw * x2 |
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xy, yz, wy = qx * y2, qy * z2, qw * y2 |
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xz, zz, wz = qx * z2, qz * z2, qw * z2 |
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return np.concatenate([ |
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np.concatenate([1.0 - (yy + zz), xy - wz, xz + wy], axis=-1)[...,None,:], |
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np.concatenate([xy + wz, 1.0 - (xx + zz), yz - wx], axis=-1)[...,None,:], |
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np.concatenate([xz - wy, yz + wx, 1.0 - (xx + yy)], axis=-1)[...,None,:], |
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], axis=-2) |
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def to_xform_xy(x): |
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qw, qx, qy, qz = x[...,0:1], x[...,1:2], x[...,2:3], x[...,3:4] |
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x2, y2, z2 = qx + qx, qy + qy, qz + qz |
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xx, yy, wx = qx * x2, qy * y2, qw * x2 |
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xy, yz, wy = qx * y2, qy * z2, qw * y2 |
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xz, zz, wz = qx * z2, qz * z2, qw * z2 |
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return np.concatenate([ |
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np.concatenate([1.0 - (yy + zz), xy - wz], axis=-1)[...,None,:], |
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np.concatenate([xy + wz, 1.0 - (xx + zz)], axis=-1)[...,None,:], |
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np.concatenate([xz - wy, yz + wx], axis=-1)[...,None,:], |
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], axis=-2) |
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def to_scaled_angle_axis(x, eps=1e-5): |
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return 2.0 * log(x, eps) |
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def from_angle_axis(angle, axis): |
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c = np.cos(angle / 2.0)[..., None] |
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s = np.sin(angle / 2.0)[..., None] |
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q = np.concatenate([c, s * axis], axis=-1) |
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return q |
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def from_axis_angle(rots): |
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angle = np.linalg.norm(rots, axis=-1) |
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axis = rots / angle[...,None] |
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return from_angle_axis(angle, axis) |
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def from_euler(e, order='zyx'): |
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axis = { |
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'x': np.asarray([1, 0, 0], dtype=np.float32), |
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'y': np.asarray([0, 1, 0], dtype=np.float32), |
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'z': np.asarray([0, 0, 1], dtype=np.float32)} |
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q0 = from_angle_axis(e[..., 0], axis[order[0]]) |
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q1 = from_angle_axis(e[..., 1], axis[order[1]]) |
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q2 = from_angle_axis(e[..., 2], axis[order[2]]) |
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return mul(q0, mul(q1, q2)) |
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def from_xform(ts): |
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return normalize( |
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np.where((ts[...,2,2] < 0.0)[...,None], |
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np.where((ts[...,0,0] > ts[...,1,1])[...,None], |
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np.concatenate([ |
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(ts[...,2,1]-ts[...,1,2])[...,None], |
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(1.0 + ts[...,0,0] - ts[...,1,1] - ts[...,2,2])[...,None], |
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(ts[...,1,0]+ts[...,0,1])[...,None], |
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(ts[...,0,2]+ts[...,2,0])[...,None]], axis=-1), |
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np.concatenate([ |
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(ts[...,0,2]-ts[...,2,0])[...,None], |
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(ts[...,1,0]+ts[...,0,1])[...,None], |
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(1.0 - ts[...,0,0] + ts[...,1,1] - ts[...,2,2])[...,None], |
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(ts[...,2,1]+ts[...,1,2])[...,None]], axis=-1)), |
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np.where((ts[...,0,0] < -ts[...,1,1])[...,None], |
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np.concatenate([ |
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(ts[...,1,0]-ts[...,0,1])[...,None], |
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(ts[...,0,2]+ts[...,2,0])[...,None], |
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(ts[...,2,1]+ts[...,1,2])[...,None], |
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(1.0 - ts[...,0,0] - ts[...,1,1] + ts[...,2,2])[...,None]], axis=-1), |
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np.concatenate([ |
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(1.0 + ts[...,0,0] + ts[...,1,1] + ts[...,2,2])[...,None], |
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(ts[...,2,1]-ts[...,1,2])[...,None], |
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(ts[...,0,2]-ts[...,2,0])[...,None], |
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(ts[...,1,0]-ts[...,0,1])[...,None]], axis=-1)))) |
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def from_xform_xy(x): |
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c2 = _fast_cross(x[...,0], x[...,1]) |
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c2 = c2 / np.sqrt(np.sum(np.square(c2), axis=-1))[...,None] |
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c1 = _fast_cross(c2, x[...,0]) |
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c1 = c1 / np.sqrt(np.sum(np.square(c1), axis=-1))[...,None] |
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c0 = x[...,0] |
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return from_xform(np.concatenate([ |
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c0[...,None], |
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c1[...,None], |
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c2[...,None]], axis=-1)) |
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def from_scaled_angle_axis(x, eps=1e-5): |
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return exp(x / 2.0, eps) |