feat: adds fixedorientation model

pdme/model/log_spaced_random_choice_fixed_orientation_model.py

@@ -0,0 +1,140 @@
+import numpy
+import numpy.random
+from pdme.model.model import DipoleModel
+from pdme.measurement import (
+	OscillatingDipole,
+	OscillatingDipoleArrangement,
+)
+
+
+class LogSpacedRandomCountMultipleDipoleFixedMagnitudeFixedOrientationModel(
+	DipoleModel
+):
+	"""
+	Model of multiple oscillating dipoles with a fixed magnitude and fixed rotation. Spaced log uniformly in relaxation time.
+
+	Parameters
+	----------
+
+	wexp_min: log-10 lower bound for dipole frequency
+	wexp_min: log-10 upper bound for dipole frequency
+
+	pfixed : float
+	The fixed dipole magnitude.
+
+	thetafixed: float
+	The fixed theta (polar angle).
+	Should be between 0 and pi.
+
+	phifixed: float
+	The fixed phi (azimuthal angle).
+	Should be between 0 and 2 pi.
+
+	n_max : int
+	The maximum number of dipoles.
+
+	prob_occupancy : float
+	The probability of dipole occupancy
+	"""
+
+	def __init__(
+		self,
+		xmin: float,
+		xmax: float,
+		ymin: float,
+		ymax: float,
+		zmin: float,
+		zmax: float,
+		wexp_min: float,
+		wexp_max: float,
+		pfixed: float,
+		thetafixed: float,
+		phifixed: float,
+		n_max: int,
+		prob_occupancy: float,
+	) -> None:
+		self.xmin = xmin
+		self.xmax = xmax
+		self.ymin = ymin
+		self.ymax = ymax
+		self.zmin = zmin
+		self.zmax = zmax
+		self.wexp_min = wexp_min
+		self.wexp_max = wexp_max
+		self.pfixed = pfixed
+		self.thetafixed = thetafixed
+		self.phifixed = phifixed
+		self.rng = numpy.random.default_rng()
+		self.n_max = n_max
+
+		px = self.pfixed * numpy.sin(self.thetafixed) * numpy.cos(self.phifixed)
+		py = self.pfixed * numpy.sin(self.thetafixed) * numpy.sin(self.phifixed)
+		pz = self.pfixed * numpy.cos(self.thetafixed)
+
+		self.moment_fixed = numpy.array([px, py, pz])
+		if prob_occupancy >= 1 or prob_occupancy <= 0:
+			raise ValueError(
+				f"The probability of a dipole site occupancy must be between 0 and 1, got {prob_occupancy}"
+			)
+		self.prob_occupancy = prob_occupancy
+
+	def __repr__(self) -> str:
+		return f"LogSpacedRandomCountMultipleDipoleFixedMagnitudeFixedOrientationModel({self.xmin}, {self.xmax}, {self.ymin}, {self.ymax}, {self.zmin}, {self.zmax}, {self.wexp_min}, {self.wexp_max}, {self.pfixed}, {self.thetafixed}, {self.phifixed}, {self.n_max}, {self.prob_occupancy})"
+
+	def get_dipoles(
+		self, max_frequency: float, rng_to_use: numpy.random.Generator = None
+	) -> OscillatingDipoleArrangement:
+		rng: numpy.random.Generator
+		if rng_to_use is None:
+			rng = self.rng
+		else:
+			rng = rng_to_use
+
+		dipoles = []
+
+		n = rng.binomial(self.n_max, self.prob_occupancy)
+
+		for i in range(n):
+			s_pts = numpy.array(
+				(
+					rng.uniform(self.xmin, self.xmax),
+					rng.uniform(self.ymin, self.ymax),
+					rng.uniform(self.zmin, self.zmax),
+				)
+			)
+			frequency = 10 ** rng.uniform(self.wexp_min, self.wexp_max)
+
+			dipoles.append(OscillatingDipole(self.moment_fixed, s_pts, frequency))
+		return OscillatingDipoleArrangement(dipoles)
+
+	def get_monte_carlo_dipole_inputs(
+		self,
+		monte_carlo_n: int,
+		_: float,
+		rng_to_use: numpy.random.Generator = None,
+	) -> numpy.ndarray:
+
+		rng: numpy.random.Generator
+		if rng_to_use is None:
+			rng = self.rng
+		else:
+			rng = rng_to_use
+
+		shape = (monte_carlo_n, self.n_max)
+
+		p_mask = rng.binomial(1, self.prob_occupancy, shape)
+
+		dipoles = numpy.einsum("ij,k->ijk", p_mask, self.moment_fixed)
+		# Is there a better way to create the final array? probably! can create a flatter guy then reshape.
+		# this is easier to reason about.
+		px = dipoles[:, :, 0]
+		py = dipoles[:, :, 1]
+		pz = dipoles[:, :, 2]
+
+		sx = rng.uniform(self.xmin, self.xmax, shape)
+		sy = rng.uniform(self.ymin, self.ymax, shape)
+		sz = rng.uniform(self.zmin, self.zmax, shape)
+
+		w = 10 ** rng.uniform(self.wexp_min, self.wexp_max, shape)
+
+		return numpy.stack([px, py, pz, sx, sy, sz, w], axis=-1)