2024-06-19 17:10:49 +00:00
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from __future__ import annotations
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2024-06-20 17:19:55 +00:00
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from abc import ABC, abstractmethod
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2024-06-19 17:10:49 +00:00
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import numpy as np
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from numpy.random import Generator
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2024-06-20 17:19:55 +00:00
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class BaseMotion(ABC):
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def __init__(self, delta: float, eta: float, rng: Generator):
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self._delta = delta
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self._eta = eta
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2024-06-20 17:19:55 +00:00
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self._rng = rng
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2024-06-19 17:10:49 +00:00
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2024-06-20 17:19:55 +00:00
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@abstractmethod
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def __repr__(self):
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pass
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2024-06-19 17:10:49 +00:00
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2024-06-30 10:06:44 +00:00
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@property
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def name(self) -> str:
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return self.__class__.__name__
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2024-06-20 17:19:55 +00:00
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def start(self):
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pass
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2024-06-19 17:10:49 +00:00
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2024-06-20 17:19:55 +00:00
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@abstractmethod
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2024-08-01 16:46:28 +00:00
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def jump(self, size: int = 1) -> 'ArrayLike':
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2024-06-20 17:19:55 +00:00
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pass
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2024-06-19 17:10:49 +00:00
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2024-06-20 17:19:55 +00:00
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class RandomJump(BaseMotion):
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def __repr__(self):
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return 'Random Jump'
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2024-08-01 16:46:28 +00:00
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def jump(self, size: int = 1) -> 'ArrayLike':
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2024-06-20 17:19:55 +00:00
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return omega_q(self._delta, self._eta, *draw_orientation(self._rng, size=size))
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class TetrahedralJump(BaseMotion):
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def __init__(self, delta: float, eta: float, rng: Generator):
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super().__init__(delta, eta, rng)
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self._orientation = None
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self._start = None
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def __repr__(self):
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return 'Tetrahedral Jump'
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def start(self):
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self._orientation = self._make_tetrahedron()
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self._start = self._rng.choice([0, 1, 2, 3])
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def _make_tetrahedron(self) -> np.ndarray:
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beta = np.arccos(-1/3) # tetrahedral angle 109.5 degrees
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sin_beta = np.sin(beta)
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cos_beta = np.cos(beta)
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# corners of a tetrahedron
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alpha = 2 * np.pi * self._rng.random()
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corners = np.array([
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[0, 0, 1],
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[sin_beta * np.cos(alpha), sin_beta * np.sin(alpha), cos_beta],
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[sin_beta * np.cos(alpha+2*np.pi/3), sin_beta * np.sin(alpha+2*np.pi/3), cos_beta],
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[sin_beta * np.cos(alpha+4*np.pi/3), sin_beta * np.sin(alpha+4*np.pi/3), cos_beta]
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])
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# orientation in lab system
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cos_theta0, phi0 = draw_orientation(self._rng)
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rot = get_rotation_matrix(
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corners[0],
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np.array(spherical_to_xyz(1., np.arccos(cos_theta0), phi0)),
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)
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2024-08-01 16:46:28 +00:00
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2024-06-20 17:19:55 +00:00
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orientations = np.zeros(4)
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for i in range(4):
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corner_lab = rot @ corners[i]
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_, theta_i, phi_i = xyz_to_spherical(*corner_lab)
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orientations[i] = omega_q(self._delta, self._eta, theta_i, phi_i)
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2024-08-01 16:46:28 +00:00
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# print(orientations)
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#
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# theta0 = np.arccos(cos_theta0)
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# v0 = np.array([np.sin(theta0) * np.cos(phi0), np.sin(theta0)*np.sin(theta0), cos_theta0])
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# norm = np.linalg.norm(v0)
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# print(norm)
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#
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#
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# corners = np.zeros((4, 3))
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# corners[0] = v0
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return orientations
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def jump(self, size: int = 1) -> 'ArrayLike':
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jumps = self._rng.choice([1, 2, 3], size=size)
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jumps = np.cumsum(jumps) + self._start
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jumps %= 4
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self._start = jumps[-1]
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return self._orientation[jumps]
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2024-06-30 10:06:44 +00:00
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# Helper functions
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def xyz_to_spherical(x_in: float, y_in: float, z_in: float) -> tuple[np.floating, float, float]:
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r = np.linalg.norm([x_in, y_in, z_in])
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theta: float = np.arccos(z_in)
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phi: float = np.arctan2(y_in, x_in)
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return r, theta, phi
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def spherical_to_xyz(r: float, theta: float, phi: float) -> tuple[float, float, float]:
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sin_theta = np.sin(theta)
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return r*np.cos(phi)*sin_theta, r*np.sin(phi)*sin_theta, r*np.cos(theta)
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def get_rotation_matrix(vec_in: np.ndarray, vec_out: np.ndarray):
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rotation = np.eye(3)
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# rotation by angle around given axis
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cos_angle = np.dot(vec_in, vec_out)
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# check for parallel / anti-parallel vectors
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if cos_angle == 1:
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return rotation
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elif cos_angle == -1:
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return -rotation
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else:
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axis = np.cross(vec_in, vec_out)
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scale = np.linalg.norm(axis)
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axis /= scale
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sin_angle = scale / np.linalg.norm(vec_in) / np.linalg.norm(vec_out)
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v_cross = np.array([
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[0, -axis[2], axis[1]],
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[axis[2], 0, -axis[0]],
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[-axis[1], axis[0], 0],
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])
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rotation += sin_angle * v_cross
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rotation += (1-cos_angle) * v_cross @ v_cross
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return rotation
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def omega_q(delta: float, eta: float, cos_theta: ArrayLike, phi: ArrayLike) -> ArrayLike:
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# sin_theta = np.sin(cos_theta)
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# cos_theta = np.cos(cos_theta)
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sin_theta_sq = 1 - cos_theta**2
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return np.pi * delta * (3 * cos_theta**2 - 1 + eta * sin_theta_sq * np.cos(2*phi))
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def draw_orientation(rng: Generator, size: int | None = None) -> tuple[ArrayLike, ArrayLike]:
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if size is not None:
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z_theta, z_phi = rng.random((2, size))
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else:
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z_theta, z_phi = rng.random(2)
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cos_theta = 1 - 2 * z_theta
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phi = 2 * np.pi * z_phi
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return cos_theta, phi
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