More tests with variety of dot ideas

pathfinder/model/__init__.py

@@ -1,5 +0,0 @@
-from pathfinder.model.dot import DotMeasurement
-from pathfinder.model.model import DotDipoleModel
-from pathfinder.model.staticdipole import StaticDipole
-
-__all__ = ['DotMeasurement', 'DotDipoleModel', 'StaticDipole']

pathfinder/model/oscillating/__init__.py

@@ -0,0 +1,5 @@
+from pathfinder.model.oscillating.oscillating_dipole import OscillatingDipole, OscillatingDipoleArrangement
+from pathfinder.model.oscillating.dot import DotMeasurement
+from pathfinder.model.oscillating.model import DotOscillatingDipoleModel
+
+__all__ = ['DotMeasurement', 'OscillatingDipole', 'OscillatingDipoleArrangement', 'DotOscillatingDipoleModel']

pathfinder/model/oscillating/dot.py

@@ -0,0 +1,87 @@
+from dataclasses import dataclass
+import numpy
+import numpy.typing
+
+
+@dataclass
+class DotMeasurement():
+	'''
+	Representation of a dot measuring oscillating dipoles.
+
+	Parameters
+	----------
+	v : float
+		The voltage measured at the dot.
+	r : numpy.ndarray
+		The position of the dot.
+	f : float
+		The measurement frequency.
+	'''
+	v: float
+	r: numpy.ndarray
+	f: float
+
+	def __post_init__(self) -> None:
+		self.r = numpy.array(self.r)
+
+	def v_for_point(self, pt: numpy.ndarray) -> float:
+		'''
+		Returns the voltage for an oscillating dipole represented as a phase space point.
+
+		Parameters
+		----------
+		pt: A length 7 numpy array representing a dipole, as (px, py, pz, sx, sy, sz, w).
+
+		Returns
+		----------
+		Returns the voltage from that dipole at the point.
+		'''
+		p = pt[0:3]  # hardcoded here because chances
+		s = pt[3:6]  # are we'll only ever work in 3d.
+		w = pt[6]
+
+		return (self._alpha(p, s))**2 * self._b(w)
+
+	def _alpha(self, p: numpy.ndarray, s: numpy.ndarray) -> float:
+		diff = self.r - s
+		return p.dot(diff) / (numpy.linalg.norm(diff)**3)
+
+	def _b(self, w: float) -> float:
+		return (1 / numpy.pi) * (w / (self.f**2 + w**2))
+
+	def cost(self, pts: numpy.ndarray) -> float:
+		# 7 because dipole in 3d has 7 degrees of freedom.
+		pt_length = 7
+		# creates numpy.ndarrays in groups of pt_length.
+		# Will throw problems for irregular points, but that's okay for now.
+		chunked_pts = [pts[i: i + pt_length] for i in range(0, len(pts), pt_length)]
+		return sum(self.v_for_point(pt) for pt in chunked_pts) - self.v
+
+	def jac_pt(self, pt: numpy.ndarray) -> numpy.ndarray:
+		p = pt[0:3]  # hardcoded here because chances
+		s = pt[3:6]  # are we'll only ever work in 3d.
+		w = pt[6]
+
+		diff = self.r - s
+		alpha = self._alpha(p, s)
+		b = self._b(w)
+
+		p_divs = 2 * alpha * diff / (numpy.linalg.norm(diff)**3) * b
+
+		r_divs = (-p / (numpy.linalg.norm(diff)**3) + 3 * p.dot(diff) * diff / (numpy.linalg.norm(diff)**5)) * 2 * alpha * b
+
+		f2 = self.f**2
+		w2 = w**2
+
+		w_div = alpha**2 * (1 / numpy.pi) * ((f2 - w2) / ((f2 + w2)**2))
+
+		return numpy.concatenate((p_divs, r_divs, w_div), axis=None)
+
+	def jac(self, pts: numpy.ndarray) -> numpy.ndarray:
+		# 7 because oscillating dipole in 3d has 7 degrees of freedom.
+		pt_length = 7
+		# creates numpy.ndarrays in groups of pt_length.
+		# Will throw problems for irregular points, but that's okay for now.
+		chunked_pts = [pts[i: i + pt_length] for i in range(0, len(pts), pt_length)]
+
+		return numpy.append([], [self.jac_pt(pt) for pt in chunked_pts])

pathfinder/model/oscillating/model.py

@@ -0,0 +1,45 @@
+from typing import Callable, Sequence
+import numpy
+import scipy.optimize
+from pathfinder.model.oscillating.dot import DotMeasurement
+import pathfinder.model.oscillating.util
+
+
+class DotOscillatingDipoleModel():
+	'''
+	Model of n static oscillating with a collection of voltage measurements
+	at dots at different positions and frequencies.
+
+	Parameters
+	----------
+	dots : Sequence[DotMeasurement]
+		A collection of dots representing a series of measured noise spectrum values.
+	n: int
+		The number of dipoles to assume.
+	'''
+	def __init__(self, dots: Sequence[DotMeasurement], n: int) -> None:
+		self.dots = dots
+		self.m = len(dots)
+		self.n = n
+
+	def __repr__(self) -> str:
+		return f'DotOscillatingDipoleModel({repr(list(self.dots))}, {self.n})'
+
+	def costs(self) -> Callable[[numpy.ndarray], numpy.ndarray]:
+		def costs_to_return(pt: numpy.ndarray) -> numpy.ndarray:
+			return numpy.array([dot.cost(pt) for dot in self.dots])
+
+		return costs_to_return
+
+	def jac(self) -> Callable[[numpy.ndarray], numpy.ndarray]:
+		def jac_to_return(pts: numpy.ndarray) -> numpy.ndarray:
+			return numpy.array([dot.jac(pts) for dot in self.dots])
+
+		return jac_to_return
+
+	def sol(self, initial_dipole=(0.1, 0.1, 0.1), initial_position=(.1, .1, .1), initial_frequency=1, use_root=True):
+		initial = numpy.tile(numpy.concatenate((initial_dipole, initial_position, initial_frequency), axis=None), self.n)
+
+		result = scipy.optimize.least_squares(self.costs(), initial, jac=self.jac(), ftol=1e-15, gtol=3e-16)
+		result.pathfinder_x = pathfinder.model.oscillating.util.normalize_oscillating_dipole_list(result.x)
+		return result

pathfinder/model/oscillating/oscillating_dipole.py

@@ -0,0 +1,77 @@
+from dataclasses import dataclass
+import numpy
+import numpy.typing
+from typing import Sequence, List, Tuple
+from pathfinder.model.oscillating.dot import DotMeasurement
+
+
+DotInput = Tuple[numpy.typing.ArrayLike, float]
+
+
+@dataclass
+class OscillatingDipole():
+	'''
+	Representation of an oscilltaing dipole, either known or guessed.
+
+	Parameters
+	----------
+	p : numpy.ndarray
+		The oscillating dipole moment, with overall sign arbitrary.
+	s : numpy.ndarray
+		The position of the dipole.
+	w : float
+		The oscillation frequency.
+	'''
+	p: numpy.ndarray
+	s: numpy.ndarray
+	w: float
+
+	def __post_init__(self) -> None:
+		'''
+		Coerce the inputs into numpy arrays.
+		'''
+		self.p = numpy.array(self.p)
+		self.s = numpy.array(self.s)
+
+	def s_at_position(self, r: numpy.ndarray, f: float) -> float:
+		'''
+		Returns the noise potential at a point r, at some frequency f.
+
+		Parameters
+		----------
+		r : numpy.ndarray
+			The position of the dot.
+		f : float
+			The dot frequency to sample.
+		'''
+		return (self._alpha(r))**2 * self._b(f)
+
+	def _alpha(self, r: numpy.ndarray) -> float:
+		diff = r - self.s
+		return self.p.dot(diff) / (numpy.linalg.norm(diff)**3)
+
+	def _b(self, f: float) -> float:
+		return (1 / numpy.pi) * (self.w / (f**2 + self.w**2))
+
+
+class OscillatingDipoleArrangement():
+	'''
+	A collection of oscillating dipoles, which we are interested in being able to characterise.
+
+	Parameters
+	--------
+	dipoles : Sequence[OscillatingDipole]
+	'''
+	def __init__(self, dipoles: Sequence[OscillatingDipole]):
+		self.dipoles = dipoles
+
+	def get_dot_measurement(self, dot_input: DotInput) -> DotMeasurement:
+		r = numpy.array(dot_input[0])
+		f = dot_input[1]
+		return DotMeasurement(sum([dipole.s_at_position(r, f) for dipole in self.dipoles]), r, f)
+
+	def get_dot_measurements(self, dot_inputs: Sequence[DotInput]) -> List[DotMeasurement]:
+		'''
+		For a series of points, each with three coordinates and a frequency, return a list of the corresponding DotMeasurements.
+		'''
+		return [self.get_dot_measurement(dot_input) for dot_input in dot_inputs]

pathfinder/model/oscillating/util.py

@@ -0,0 +1,19 @@
+import numpy
+import operator
+
+
+# flips px, py, pz
+SIGN_ARRAY = numpy.array((-1, -1, -1, 1, 1, 1, 1))
+
+
+def flip_chunk_to_positive_px(pt: numpy.ndarray) -> numpy.ndarray:
+	if pt[0] > 0:
+		return pt
+	else:
+		return SIGN_ARRAY * pt
+
+
+def normalize_oscillating_dipole_list(pts: numpy.ndarray) -> numpy.ndarray:
+	pt_length = 7
+	chunked_pts = [flip_chunk_to_positive_px(pts[i: i + pt_length]) for i in range(0, len(pts), pt_length)]
+	return numpy.concatenate(sorted(chunked_pts, key=lambda x: tuple(round(val, 3) for val in operator.itemgetter(0, 1, 2, 3, 4, 5, 6)(x))), axis=None)

pathfinder/model/static/__init__.py

@@ -0,0 +1,5 @@
+from pathfinder.model.static.dot import DotMeasurement
+from pathfinder.model.static.model import DotDipoleModel
+from pathfinder.model.static.staticdipole import StaticDipoleArrangement, StaticDipole
+
+__all__ = ['DotMeasurement', 'DotDipoleModel', 'StaticDipoleArrangement', 'StaticDipole']

pathfinder/model/static/dot.py

@@ -2,8 +2,6 @@ from dataclasses import dataclass
 import numpy
 import numpy.typing
 
-from pathfinder.model.staticdipole import StaticDipole
-
 
 @dataclass
 class DotMeasurement():
@@ -38,9 +36,8 @@ class DotMeasurement():
 		p = pt[0:3]  # hardcoded here because chances
 		s = pt[3:6]  # are we'll only ever work in 3d.
 
-		dipole = StaticDipole(p, s)
-
-		return dipole.v_at_position(self.r)
+		diff = self.r - s
+		return p.dot(diff) / (numpy.linalg.norm(diff)**3)
 
 	def cost(self, pts: numpy.ndarray) -> float:
 		# 6 because dipole in 3d has 6 degrees of freedom.

pathfinder/model/static/model.py

@@ -1,7 +1,7 @@
 from typing import Callable, Sequence
 import numpy
-
-from pathfinder.model.dot import DotMeasurement
+import scipy.optimize
+from pathfinder.model.static.dot import DotMeasurement
 
 
 class DotDipoleModel():
@@ -35,3 +35,10 @@ class DotDipoleModel():
 			return numpy.array([dot.jac(pts) for dot in self.dots])
 
 		return jac_to_return
+
+	def sol(self, initial_dipole=(0.1, 0.1, 0.1), initial_position=(.1, .1, .1), use_root=True):
+		initial = numpy.tile(numpy.append(initial_dipole, initial_position), self.n)
+		if use_root and self.m == 6 * self.n:
+			# We are perfectly specified
+			return scipy.optimize.root(self.costs(), initial, jac=self.jac(), tol=1e-12)
+		return scipy.optimize.least_squares(self.costs(), initial, jac=self.jac(), ftol=1e-15, gtol=3e-16)

pathfinder/model/static/staticdipole.py

@@ -0,0 +1,58 @@
+from dataclasses import dataclass
+import numpy
+import numpy.typing
+from typing import Sequence, List
+from pathfinder.model.static.dot import DotMeasurement
+
+
+@dataclass
+class StaticDipole():
+	'''
+	Representation of a static dipoles, either known or guessed.
+
+	Parameters
+	----------
+	p : numpy.ndarray
+		The static dipole moment.
+	s : numpy.ndarray
+		The position of the dipole.
+	'''
+	p: numpy.ndarray
+	s: numpy.ndarray
+
+	def __post_init__(self) -> None:
+		'''
+		Coerce the inputs into numpy arrays.
+		'''
+		self.p = numpy.array(self.p)
+		self.s = numpy.array(self.s)
+
+	def v_at_position(self, r: numpy.ndarray) -> float:
+		'''
+		Mirrors the same function in pathfinder.model.dot.
+		'''
+		diff = r - self.s
+		return self.p.dot(diff) / (numpy.linalg.norm(diff)**3)
+
+
+class StaticDipoleArrangement():
+	'''
+	A collection of static dipoles, which we are interested in being able to characterise.
+
+	Parameters
+	--------
+	dipoles : Sequence[StaticDipole]
+	'''
+	def __init__(self, dipoles):
+		self.dipoles = dipoles
+
+	def get_dot_measurement(self, dot_position: numpy.typing.ArrayLike) -> DotMeasurement:
+		r = numpy.array(dot_position)
+		return DotMeasurement(sum([dipole.v_at_position(r) for dipole in self.dipoles]), r)
+
+	def get_dot_measurements(self, dot_positions: Sequence[numpy.typing.ArrayLike]) -> List[DotMeasurement]:
+		'''
+		For a series of points, each with three coordinates, return
+		'''
+
+		return [self.get_dot_measurement(dot_position) for dot_position in dot_positions]

pathfinder/model/staticdipole.py

@@ -1,31 +0,0 @@
-from dataclasses import dataclass
-import numpy
-import numpy.typing
-
-
-@dataclass
-class StaticDipole():
-	'''
-	Representation of a static dipoles, either known or guessed.
-
-	Parameters
-	----------
-	p : numpy.ndarray
-		The static dipole moment.
-	s : numpy.ndarray
-		The position of the dipole.
-	'''
-	p: numpy.ndarray
-	s: numpy.ndarray
-
-	def __post_init__(self) -> None:
-		'''
-			Coerce the inputs into numpy arrays.
-		'''
-		self.p = numpy.array(self.p)
-		self.s = numpy.array(self.s)
-
-	def v_at_position(self, r: numpy.typing.ArrayLike) -> float:
-
-		diff = r - self.s
-		return self.p.dot(diff) / (numpy.linalg.norm(diff)**3)

poetry.lock

@@ -78,7 +78,7 @@ python-versions = ">=3.5"
 
 [[package]]
 name = "mypy"
-version = "0.790"
+version = "0.910"
 description = "Optional static typing for Python"
 category = "dev"
 optional = false
@@ -86,11 +86,12 @@ python-versions = ">=3.5"
 
 [package.dependencies]
 mypy-extensions = ">=0.4.3,<0.5.0"
-typed-ast = ">=1.4.0,<1.5.0"
+toml = "*"
 typing-extensions = ">=3.7.4"
 
 [package.extras]
 dmypy = ["psutil (>=4.0)"]
+python2 = ["typed-ast (>=1.4.0,<1.5.0)"]
 
 [[package]]
 name = "mypy-extensions"
@@ -218,14 +219,6 @@ category = "dev"
 optional = false
 python-versions = ">=2.6, !=3.0.*, !=3.1.*, !=3.2.*"
 
-[[package]]
-name = "typed-ast"
-version = "1.4.3"
-description = "a fork of Python 2 and 3 ast modules with type comment support"
-category = "dev"
-optional = false
-python-versions = "*"
-
 [[package]]
 name = "typing-extensions"
 version = "3.10.0.0"
@@ -237,7 +230,7 @@ python-versions = "*"
 [metadata]
 lock-version = "1.1"
 python-versions = "^3.8,<3.10"
-content-hash = "223211dbc0d0b43607b649f98a88b1d7c2f07c9d7574508bd8f68f36787966b3"
+content-hash = "daffa6e91d6921845be603d5c0565d1afb511a57bb9a2f4b9c1084754b7a5314"
 
 [metadata.files]
 atomicwrites = [
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+    {file = "mypy-0.910-cp39-cp39-manylinux1_x86_64.whl", hash = "sha256:3c4b8ca36877fc75339253721f69603a9c7fdb5d4d5a95a1a1b899d8b86a4de2"},
+    {file = "mypy-0.910-cp39-cp39-manylinux2010_x86_64.whl", hash = "sha256:c0df2d30ed496a08de5daed2a9ea807d07c21ae0ab23acf541ab88c24b26ab97"},
+    {file = "mypy-0.910-cp39-cp39-win_amd64.whl", hash = "sha256:c6c2602dffb74867498f86e6129fd52a2770c48b7cd3ece77ada4fa38f94eba8"},
+    {file = "mypy-0.910-py3-none-any.whl", hash = "sha256:ef565033fa5a958e62796867b1df10c40263ea9ded87164d67572834e57a174d"},
+    {file = "mypy-0.910.tar.gz", hash = "sha256:704098302473cb31a218f1775a873b376b30b4c18229421e9e9dc8916fd16150"},
 ]
 mypy-extensions = [
     {file = "mypy_extensions-0.4.3-py2.py3-none-any.whl", hash = "sha256:090fedd75945a69ae91ce1303b5824f428daf5a028d2f6ab8a299250a846f15d"},
@@ -435,38 +437,6 @@ toml = [
     {file = "toml-0.10.2-py2.py3-none-any.whl", hash = "sha256:806143ae5bfb6a3c6e736a764057db0e6a0e05e338b5630894a5f779cabb4f9b"},
     {file = "toml-0.10.2.tar.gz", hash = "sha256:b3bda1d108d5dd99f4a20d24d9c348e91c4db7ab1b749200bded2f839ccbe68f"},
 ]
-typed-ast = [
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-    {file = "typed_ast-1.4.3-cp35-cp35m-manylinux2014_aarch64.whl", hash = "sha256:1b3ead4a96c9101bef08f9f7d1217c096f31667617b58de957f690c92378b528"},
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-    {file = "typed_ast-1.4.3-cp35-cp35m-win_amd64.whl", hash = "sha256:777a26c84bea6cd934422ac2e3b78863a37017618b6e5c08f92ef69853e765d3"},
-    {file = "typed_ast-1.4.3-cp36-cp36m-macosx_10_9_x86_64.whl", hash = "sha256:f8afcf15cc511ada719a88e013cec87c11aff7b91f019295eb4530f96fe5ef2f"},
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-    {file = "typed_ast-1.4.3.tar.gz", hash = "sha256:fb1bbeac803adea29cedd70781399c99138358c26d05fcbd23c13016b7f5ec65"},
-]
 typing-extensions = [
     {file = "typing_extensions-3.10.0.0-py2-none-any.whl", hash = "sha256:0ac0f89795dd19de6b97debb0c6af1c70987fd80a2d62d1958f7e56fcc31b497"},
     {file = "typing_extensions-3.10.0.0-py3-none-any.whl", hash = "sha256:779383f6086d90c99ae41cf0ff39aac8a7937a9283ce0a414e5dd782f4c94a84"},

pyproject.toml

@@ -14,7 +14,7 @@ more-itertools = "^8.8.0"
 pytest = ">=6"
 flake8 = "^3.8.4"
 pytest-cov = "^2.10.1"
-mypy = "^0.790"
+mypy = "^0.910"
 
 [build-system]
 requires = ["poetry>=0.12"]
@@ -22,8 +22,15 @@ build-backend = "poetry.masonry.api"
 
 [tool.pytest.ini_options]
 testpaths = ["tests"]
-addopts = "--junitxml pytest.xml --cov pathfinder --cov-report=xml:coverage.xml --cov-fail-under=90"
+addopts = "--junitxml pytest.xml --cov pathfinder --cov-report=xml:coverage.xml --cov-fail-under=90 --cov-report=html"
 junit_family = "xunit1"
 
 [tool.mypy]
 plugins = "numpy.typing.mypy_plugin"
+
+[[tool.mypy.overrides]]
+module = [
+	"scipy",
+	"scipy.optimize"
+]
+ignore_missing_imports = true

tests/model/oscillating/test_osc_model_sol.py

@@ -0,0 +1,109 @@
+import numpy
+import pathfinder.model.oscillating
+
+
+def chunk_n_sort(pts):
+	pt_length = 7
+	chunked_pts = [pts[i: i + pt_length] for i in range(0, len(pts), pt_length)]
+
+	return chunked_pts
+
+
+def print_result(msg, result):
+	print(msg)
+	print(f"\tResult: {result.pathfinder_x}")
+	print(f"\tSuccess: {result.success}. {result.message}")
+	try:
+		print(f"\tFunc evals: {result.nfev}")
+	except AttributeError:
+		pass
+	try:
+		print(f"\tJacb evals: {result.njev}")
+	except AttributeError:
+		pass
+
+
+def test_one_dipole_six_dot_two_frequencies():
+	# setup
+	dot_inputs = [
+		([0, 0, .01], 5), ([-1, 0, -.01], 5), ([-2, 0, -.01], 5), ([0, -1, .01], 5), ([-1, -1, 0], 5), ([-2, -1, 0], 5),
+		([0, 0, .01], 1), ([-1, 0, -.01], 1), ([-2, 0, -.01], 1), ([0, -1, .01], 1), ([-1, -1, 0], 1), ([-2, -1, 0], 1),
+	]
+	dipole = pathfinder.model.oscillating.OscillatingDipole([1, 2, 3], [0, 4, -1], 7)
+	expected_result = numpy.array([1, 2, 3, 0, 4, -1, 7])
+	dipole_arrangement = pathfinder.model.oscillating.OscillatingDipoleArrangement([dipole])
+	dot_measurements = dipole_arrangement.get_dot_measurements(dot_inputs)
+
+	model = pathfinder.model.oscillating.DotOscillatingDipoleModel(dot_measurements, 1)
+	res = model.sol()
+
+	print_result("one oscillating dipole six dots", res)
+	assert res.success, "The solution for a single dipole and six dots should have succeeded."
+	numpy.testing.assert_allclose(res.pathfinder_x, expected_result, err_msg="Dipole wasn't as expected.", rtol=1e-6, atol=1e-6)
+
+
+def test_two_dipole_six_dot_two_frequencies():
+	# setup
+	dot_inputs = [
+		([0, 0, .01], 5), ([-1, 0, -.01], 5), ([-2, 0, -.01], 5), ([0, -1, .01], 5), ([-1, -1, 0], 5), ([-2, -1, 0], 5),
+		([0, -2, .01], 5), ([-1, -2, -.01], 5), ([-2, -2, -.01], 5), ([0, -3, .01], 5), ([-1, -3, 0], 5), ([-2, -3, 0], 5),
+		([0, 0, .01], 1), ([-1, 0, -.01], 1), ([-2, 0, -.01], 1), ([0, -1, .01], 1), ([-1, -1, 0], 1), ([-2, -1, 0], 1),
+		([0, -2, .01], 1), ([-1, -2, -.01], 1), ([-2, -2, -.01], 1), ([0, -3, .01], 1), ([-1, -3, 0], 1), ([-2, -3, 0], 1),
+	]
+	dipole = pathfinder.model.oscillating.OscillatingDipole([1, 2, 3], [0, 4, -1], 7)
+	dipole2 = pathfinder.model.oscillating.OscillatingDipole([-1, 2, 0], [2, -1, 1], 4)
+	expected_result = numpy.array([1, -2, 0, 2, -1, 1, 4, 1, 2, 3, 0, 4, -1, 7])
+	dipole_arrangement = pathfinder.model.oscillating.OscillatingDipoleArrangement([dipole, dipole2])
+	dot_measurements = dipole_arrangement.get_dot_measurements(dot_inputs)
+
+	model = pathfinder.model.oscillating.DotOscillatingDipoleModel(dot_measurements, 2)
+	res = model.sol()
+
+	print_result("two oscillating dipole six dots", res)
+	assert res.success, "The solution for two dipole and six dots should have succeeded."
+	numpy.testing.assert_allclose(res.pathfinder_x, expected_result, err_msg="Dipole wasn't as expected.", rtol=1e-6, atol=1e-6)
+
+
+def test_two_dipole_six_dot_two_frequencies_morerealistic():
+	# setup
+	dot_inputs = [
+		([0, 0, .01], 5), ([-1, 0, -.01], 5), ([-2, 0, -.01], 5), ([-3, 0, 0], 5), ([0, -1, .01], 5), ([-1, -1, 0], 5), ([-2, -1, 0], 5), ([-3, -1, 0], 5),
+		([0, -2, .01], 5), ([-1, -2, -.01], 5), ([-2, -2, -.01], 5), ([-3, -2, 0], 5), ([0, -3, .01], 5), ([-1, -3, 0], 5), ([-2, -3, 0], 5), ([-3, -3, 0], 5),
+		([0, 0, .01], 1), ([-1, 0, -.01], 1), ([-2, 0, -.01], 1), ([-3, 0, 0], 1), ([0, -1, .01], 1), ([-1, -1, 0], 1), ([-2, -1, 0], 1), ([-3, -1, 0], 1),
+		([0, -2, .01], 1), ([-1, -2, -.01], 1), ([-2, -2, -.01], 1), ([-3, -2, 0], 1), ([0, -3, .01], 1), ([-1, -3, 0], 1), ([-2, -3, 0], 1), ([-3, -3, 0], 1),
+	]
+	dipole = pathfinder.model.oscillating.OscillatingDipole([1, 2, 3], [0, 4, -1], 7)
+	dipole2 = pathfinder.model.oscillating.OscillatingDipole([-1, 2, 0], [-1, 2, 1], 4)
+	expected_result = numpy.array([1, -2, 0, -1, 2, 1, 4, 1, 2, 3, 0, 4, -1, 7])
+	dipole_arrangement = pathfinder.model.oscillating.OscillatingDipoleArrangement([dipole, dipole2])
+	dot_measurements = dipole_arrangement.get_dot_measurements(dot_inputs)
+
+	model = pathfinder.model.oscillating.DotOscillatingDipoleModel(dot_measurements, 2)
+	res = model.sol()
+
+	print_result("two oscillating dipole six dots", res)
+	numpy.testing.assert_allclose(res.pathfinder_x, expected_result, err_msg="Dipole wasn't as expected.", rtol=1e-6, atol=1e-6)
+
+
+def test_two_dipole_eighteen_dot_two_frequencies_morerealistic():
+	# setup
+	dot_inputs = [
+		([0, 0, .01], 5), ([-1, 0, -.01], 5), ([-2, 0, -.01], 5), ([0, -1, .01], 5), ([-1, -1, 0], 5), ([-2, -1, 0], 5),
+		([0, -2, .01], 5), ([-1, -2, -.01], 5), ([-2, -2, -.01], 5), ([0, -3, .01], 5), ([-1, -3, 0], 5), ([-2, -3, 0], 5),
+		([0, -4, .01], 5), ([-1, -4, -.01], 5), ([-2, -4, -.01], 5), ([0, -5, .01], 5), ([-1, -5, 0], 5), ([-2, -5, 0], 5),
+		([0, 0, .01], 1), ([-1, 0, -.01], 1), ([-2, 0, -.01], 1), ([0, -1, .01], 1), ([-1, -1, 0], 1), ([-2, -1, 0], 1),
+		([0, -2, .01], 1), ([-1, -2, -.01], 1), ([-2, -2, -.01], 1), ([0, -3, .01], 1), ([-1, -3, 0], 1), ([-2, -3, 0], 1),
+		([0, -4, .01], 1), ([-1, -4, -.01], 1), ([-2, -4, -.01], 1), ([0, -5, .01], 1), ([-1, -5, 0], 1), ([-2, -5, 0], 1),
+	]
+	dipole = pathfinder.model.oscillating.OscillatingDipole([1, 2, 3], [0, 4, -1], 7)
+	dipole2 = pathfinder.model.oscillating.OscillatingDipole([-1, 2, 0], [-1, 2, 1], 4)
+	expected_result = numpy.array([1, -2, 0, -1, 2, 1, 4, 1, 2, 3, 0, 4, -1, 7])
+	dipole_arrangement = pathfinder.model.oscillating.OscillatingDipoleArrangement([dipole, dipole2])
+	dot_measurements = dipole_arrangement.get_dot_measurements(dot_inputs)
+
+	model = pathfinder.model.oscillating.DotOscillatingDipoleModel(dot_measurements, 2)
+	res = model.sol()
+
+	print_result("two oscillating dipole six dots", res)
+	assert res.success, "The solution for two dipole and six dots should have succeeded."
+	numpy.testing.assert_allclose(res.pathfinder_x, expected_result, err_msg="Dipole wasn't as expected.", rtol=1e-6, atol=1e-6)

tests/model/oscillating/test_oscdot.py

@@ -0,0 +1,43 @@
+import numpy
+import numpy.testing
+
+import pathfinder.model.oscillating as model
+
+
+def test_dot_v_from_dipole():
+
+	dot_position1 = (-1, -1, -1)
+	dot_frequency1 = 11
+	expected_v1 = 0.00001421963287022476
+	dot = model.DotMeasurement(expected_v1, dot_position1, dot_frequency1)
+
+	# and dipole located at (4, 5, 6) with p=(1, 2, 3) and w = 7
+	pt = numpy.array((1, 2, 3, 4, 5, 6, 7))
+
+	numpy.testing.assert_allclose(dot.v_for_point(pt), dot.v, err_msg="v from dipole at a dot was incorrect!")
+	numpy.testing.assert_allclose(dot.cost(pt), 0, atol=1e-12, err_msg="cost should be zero")
+
+
+def test_jac():
+	expected_jac = [
+		3.742008650059147e-6, 4.4904103800709765e-6, 5.238812110082806e-6,
+		-3.12967996186765e-6, -3.1568945702317167e-6, -3.184109178595783e-6,
+		8.603475350051953e-7
+	]
+
+	expected_jac2 = [
+		-4.428720903021825e-6, 3.5429767224174605e-6, 4.428720903021825e-6,
+		-6.804125751006259e-6, -4.0261099118380183e-7, 2.3754048479844336e-6,
+		5.181603456535536e-6
+	]
+
+	dot = model.DotMeasurement(50, (-1, -1, -1), 11)
+
+	# dipole located at (4, 5, 6) with p=(1, 2, 3) and w = 7
+	pt = numpy.array((1, 2, 3, 4, 5, 6, 7))
+	pt2 = numpy.array((2, 5, 3, 4, -5, -6, 2))
+	pts = numpy.append(pt, pt2)
+	expected_jac_all = expected_jac + expected_jac2
+	assert len(dot.jac_pt(pt)) == 7
+	numpy.testing.assert_allclose(dot.jac_pt(pt), expected_jac, err_msg="Jac pt doesn't match Mathematica result.")
+	numpy.testing.assert_allclose(dot.jac(pts), expected_jac_all, err_msg="whole row should match")

tests/model/oscillating/test_oscillatingdipole.py

@@ -0,0 +1,22 @@
+import numpy
+import pathfinder.model.oscillating as model
+
+
+def test_static_dipole():
+	d1 = model.OscillatingDipole((1, 2, 3), (4, 5, 6), 7)
+	d2 = model.OscillatingDipole((2, 5, 3), (4, -5, -6), 2)
+	dipoles = model.OscillatingDipoleArrangement([d1, d2])
+
+	dot_position1 = (-1, -1, -1)
+	dot_frequency1 = 11
+	expected_v1 = 0.00001421963287022476
+	expected_v2 = 0.00001107180225755457
+
+	numpy.testing.assert_allclose(d1.s_at_position(dot_position1, dot_frequency1), expected_v1, err_msg="Voltage at dot isn't as expected.")
+
+	dot_measurements = dipoles.get_dot_measurements([(dot_position1, dot_frequency1)])
+	assert len(dot_measurements) == 1, "Should have only had one dot measurement."
+	measurement = dot_measurements[0]
+	numpy.testing.assert_allclose(measurement.r, dot_position1, err_msg="Dot position should have been passed over")
+	numpy.testing.assert_allclose(measurement.f, dot_frequency1, err_msg="Dot frequency should have been passed over")
+	numpy.testing.assert_allclose(measurement.v, expected_v1 + expected_v2, err_msg="Voltage at dot isn't as expected.")

tests/model/oscillating/test_oscmodel.py

@@ -0,0 +1,35 @@
+import numpy
+import pathfinder.model.oscillating as model
+
+
+def test_dotdipolemodel_repr():
+	mod = model.DotOscillatingDipoleModel((), 1)
+	assert repr(mod) == "DotOscillatingDipoleModel([], 1)"
+
+
+def test_dotdipolemodel_m():
+	mod = model.DotOscillatingDipoleModel([model.DotMeasurement(1, (-1, -1, -1), 11), model.DotMeasurement(2, (0, 0, 0), 3)], 1)
+	assert mod.m == 2
+
+
+def test_dotdipolemodel_cost():
+	mod = model.DotOscillatingDipoleModel([model.DotMeasurement(.05, (-1, -1, -1), 11), model.DotMeasurement(.002, (0, 0, 0), 3)], 1)
+	costs = mod.costs()
+	jac = mod.jac()
+
+	pt_to_test = numpy.array((1, 2, 3, 4, 5, 6, 7))
+	expected_cost = [-0.04998578036712978, -0.00191383161468913]
+	expected_jacobian = [
+		[
+			3.742008650059147e-6, 4.4904103800709765e-6, 5.238812110082806e-6,
+			-3.12967996186765e-6, -3.1568945702317167e-6, -3.184109178595783e-6,
+			8.603475350051953e-7
+		], [
+			0.000021542096327717702, 0.000026927620409647127, 0.000032313144491576555,
+			-0.000021472154456523818, -0.0000228010500092077, -0.000024129945561891588,
+			-8.489496089740964e-6
+		]
+	]
+
+	numpy.testing.assert_allclose(costs(pt_to_test), expected_cost, err_msg="Costs aren't as expected.")
+	numpy.testing.assert_allclose(jac(pt_to_test), expected_jacobian, err_msg="Jacobian aren't as expected.")

tests/model/oscillating/test_util.py

@@ -0,0 +1,20 @@
+import pathfinder.model.oscillating.util as util
+import numpy
+
+
+def test_util_flip():
+	pt = numpy.array((1, 2, 3, 4, 5, 6, 7))
+	expected = (1, 2, 3, 4, 5, 6, 7)
+	numpy.testing.assert_allclose(util.flip_chunk_to_positive_px(pt), expected, err_msg="Point should remain unchanged.")
+
+
+def test_util_flip_negative():
+	pt = numpy.array((-1, -2, 3, 4, 5, 6, 7))
+	expected = (1, 2, -3, 4, 5, 6, 7)
+	numpy.testing.assert_allclose(util.flip_chunk_to_positive_px(pt), expected, err_msg="Point should remain unchanged.")
+
+
+def test_util_normalise_two():
+	pt = numpy.array((1, 2, 3, 4, 5, 6, 7, -.5, 1, 1.5, 2, 2.5, 3, 3.5))
+	expected = (.5, -1, -1.5, 2, 2.5, 3, 3.5, 1, 2, 3, 4, 5, 6, 7)
+	numpy.testing.assert_allclose(util.normalize_oscillating_dipole_list(pt), expected, err_msg="Sort should have happened.")

tests/model/static/test_dot.py

@@ -1,7 +1,7 @@
 import numpy
 import numpy.testing
 
-import pathfinder.model as model
+import pathfinder.model.static as model
 
 
 def test_dot():

tests/model/static/test_model.py

@@ -0,0 +1,76 @@
+import numpy
+import pathfinder.model.static as model
+
+
+def test_dotdipolemodel_repr():
+	mod = model.DotDipoleModel((), 1)
+	assert repr(mod) == "DotDipoleModel([], 1)"
+
+
+def test_dotdipolemodel_m():
+	mod = model.DotDipoleModel([model.DotMeasurement(1, (0, 0, 0)), model.DotMeasurement(2, (0, 0, 0))], 1)
+	assert mod.m == 2
+
+
+def test_dotdipolemodel_cost():
+	mod = model.DotDipoleModel([model.DotMeasurement(1, (0, 0, 1)), model.DotMeasurement(2, (1, 0, 0))], 1)
+	costs = mod.costs()
+	jac = mod.jac()
+
+	pt_to_test = numpy.array((1, 2, 3, 4, 5, 6))
+	expected_cost = [-1.05408565512728256, -2.05293155269909457]
+	expected_jacobian = [
+		[
+			-0.007460090362383803, -0.009325112952979752, -0.009325112952979752,
+			0.007968732887091788, 0.00856214916591777, 0.006697126575321822
+		], [
+			-0.00512240832571883, -0.008537347209531383, -0.01024481665143766,
+			0.005098015905120168, 0.007927536694564856, 0.008488562368334061
+		]
+	]
+
+	numpy.testing.assert_allclose(costs(pt_to_test), expected_cost, err_msg="Costs aren't as expected.")
+	numpy.testing.assert_allclose(jac(pt_to_test), expected_jacobian, err_msg="Jacobian aren't as expected.")
+
+
+def print_result(msg, result):
+	print(msg)
+	print(f"\tResult: {result.x}")
+	print(f"\tSuccess: {result.success}. {result.message}")
+	try:
+		print(f"\tFunc evals: {result.nfev}")
+	except AttributeError:
+		pass
+	try:
+		print(f"\tJacb evals: {result.njev}")
+	except AttributeError:
+		pass
+
+
+def test_dot_dipole_model_solution():
+	v1 = -0.05547767706400186526225414
+	v2 = -0.06018573388098888319642888
+	v3 = -0.06364032191901859480476888
+	v4 = -0.06488383879243851188402150
+	v5 = -0.06297148063759813929659130
+	v6 = -0.05735489606460216
+	v7 = -0.07237320672886623
+	v8 = -0.1082531754730548
+	v9 = -0.04471694936155558
+
+	c1 = model.DotMeasurement(v1, [0, 0, 1])
+	c2 = model.DotMeasurement(v2, [0, 0, 2])
+	c3 = model.DotMeasurement(v3, [0, 0, 3])
+	c4 = model.DotMeasurement(v4, [0, 0, 4])
+	c5 = model.DotMeasurement(v5, [0, 0, 5])
+	c6 = model.DotMeasurement(v6, [0, 0, 6])
+	c7 = model.DotMeasurement(v7, [1, 1, 7])
+	c8 = model.DotMeasurement(v8, [1, 2, 3])
+	c9 = model.DotMeasurement(v9, [0, -1, 0])
+
+	expected_result = numpy.array([1, 3, 5, 5, 6, 7])
+
+	mod = model.DotDipoleModel([c1, c2, c3, c4, c5, c6, c7, c8, c9], 1)
+	res = mod.sol()
+	assert res.success, "The solution for a single dipole should have succeeded."
+	numpy.testing.assert_allclose(res.x, expected_result, err_msg="Dipole wasn't as expected.")

tests/model/static/test_model_sol.py

@@ -0,0 +1,120 @@
+import numpy
+import pathfinder.model.static
+
+import pytest
+
+
+def chunk_n_sort(pts):
+	pt_length = 6
+	chunked_pts = [pts[i: i + pt_length] for i in range(0, len(pts), pt_length)]
+
+	return sorted(chunked_pts, key=lambda x: x[0])
+
+
+def print_result(msg, result):
+	print(msg)
+	print(f"\tResult: {chunk_n_sort(result.x)}")
+	print(f"\tSuccess: {result.success}. {result.message}")
+	try:
+		print(f"\tFunc evals: {result.nfev}")
+	except AttributeError:
+		pass
+	try:
+		print(f"\tJacb evals: {result.njev}")
+	except AttributeError:
+		pass
+
+
+def test_one_dipole_six_dot():
+	# setup
+	dot_positions = [[0, 0, 0], [-1, 0, 0], [-2, 0, 0], [-1, -1, 0], [-1, -1, 1], [0, -2, 0]]
+	dipole = pathfinder.model.static.StaticDipole([1, 2, 3], [0, 4, 0])
+	expected_result = numpy.array([1, 2, 3, 0, 4, 0])
+	dipole_arrangement = pathfinder.model.static.StaticDipoleArrangement([dipole])
+	dot_measurements = dipole_arrangement.get_dot_measurements(dot_positions)
+
+	model = pathfinder.model.static.DotDipoleModel(dot_measurements, 1)
+	res = model.sol()
+
+	print_result("one dipole six dots", res)
+	assert res.success, "The solution for a single dipole and six dots should have succeeded."
+	numpy.testing.assert_allclose(res.x, expected_result, err_msg="Dipole wasn't as expected.", rtol=1e-6, atol=1e-6)
+
+
+@pytest.mark.skip(reason="don't care at the moment")
+def test_two_dipole_thirteen_dot():
+	dot_positions = [[x, y, 0] for x in (-4, -1, 1, 4) for y in (-1, -5, -9)]
+	dot_positions.append((1, -1, 2))
+	# dot_positions.append((-1, -1, -2))
+	dipole = pathfinder.model.static.StaticDipole([0, 8, 0], [0, 5, 0])
+	dipole2 = pathfinder.model.static.StaticDipole([8, 1, 1], [2, 2, -2])
+	expected_result = numpy.array([0, 8, 0, 0, 5, 0, 8, 1, 1, 2, 2, -2])
+	dipole_arrangement = pathfinder.model.static.StaticDipoleArrangement([dipole, dipole2])
+	dot_measurements = dipole_arrangement.get_dot_measurements(dot_positions)
+
+	model = pathfinder.model.static.DotDipoleModel(dot_measurements, 2)
+	res = model.sol(initial_dipole=(2, 2, 0), initial_position=(0, 3, 0))
+	print(model.costs()(res.x))
+	print(res.x)
+	print_result("two dipole 13 dot", res)
+	assert res.success, "The solution for two dipoles and twelve dots should have succeeded."
+	numpy.testing.assert_allclose(chunk_n_sort(res.x), chunk_n_sort(expected_result), err_msg="Dipole wasn't as expected.", rtol=1e-6, atol=1e-4)
+
+
+@pytest.mark.skip(reason="don't care at the moment")
+def test_two_dipole_twelve_dot():
+	dot_positions = [[x, y, 0] for x in (-4, -1, 1, 4) for y in (-1, -5, -9)][:-1]
+	dot_positions.append((1, -1, 2))
+	# dot_positions.append((-1, -1, -2))
+	dipole = pathfinder.model.static.StaticDipole([0, 8, 0], [0, 5, 0])
+	dipole2 = pathfinder.model.static.StaticDipole([8, 1, 1], [2, 2, -2])
+	expected_result = numpy.array([0, 8, 0, 0, 5, 0, 8, 1, 1, 2, 2, -2])
+	dipole_arrangement = pathfinder.model.static.StaticDipoleArrangement([dipole, dipole2])
+	dot_measurements = dipole_arrangement.get_dot_measurements(dot_positions)
+
+	model = pathfinder.model.static.DotDipoleModel(dot_measurements, 2)
+	res = model.sol(initial_dipole=(2, 2, 0), initial_position=(0, 3, 0), use_root=False)
+	print(model.costs()(res.x))
+	print(res.x)
+	print_result("two dipole 13 dot", res)
+	assert res.success, "The solution for two dipoles and twelve dots should have succeeded."
+	numpy.testing.assert_allclose(chunk_n_sort(res.x), chunk_n_sort(expected_result), err_msg="Dipole wasn't as expected.", rtol=1e-6, atol=1e-4)
+
+
+@pytest.mark.skip(reason="don't care at the moment")
+def test_two_dipole_twelve_dot_smallguy():
+	dot_positions = [[x, y, 0] for x in (-4, -1, 1, 4) for y in (-1, -5, -9)][:-1]
+	dot_positions.append((1, -1, 2))
+	# dot_positions.append((-1, -1, -2))
+	dipole = pathfinder.model.static.StaticDipole([0, 1, 0], [0, 5, 0])
+	dipole2 = pathfinder.model.static.StaticDipole([8, 1, 1], [2, 2, -2])
+	expected_result = numpy.array([0, 1, 0, 0, 5, 0, 8, 1, 1, 2, 2, -2])
+	dipole_arrangement = pathfinder.model.static.StaticDipoleArrangement([dipole, dipole2])
+	dot_measurements = dipole_arrangement.get_dot_measurements(dot_positions)
+
+	model = pathfinder.model.static.DotDipoleModel(dot_measurements, 2)
+	res = model.sol(initial_dipole=(2, 2, 0), initial_position=(0, 3, 0), use_root=False)
+	print(model.costs()(res.x))
+	print(res.x)
+	print_result("two dipole 13 dot", res)
+	assert res.success, "The solution for two dipoles and twelve dots should have succeeded."
+	numpy.testing.assert_allclose(chunk_n_sort(res.x), chunk_n_sort(expected_result), err_msg="Dipole wasn't as expected.", rtol=1e-6, atol=1e-4)
+
+
+def test_two_dipole_twelve_dot_2():
+	dot_positions = [[x, y, 0] for x in (-4, -1, 1, 4) for y in (-1, -5, -9)]
+	dot_positions.append((1, -1, 2))
+	dot_positions.append((-1, -1, -2))
+	dipole = pathfinder.model.static.StaticDipole([0, 8, 0], [0, 5, 0])
+	dipole2 = pathfinder.model.static.StaticDipole([8, 1, 1], [2, 2, -2])
+	expected_result = numpy.array([0, 8, 0, 0, 5, 0, 8, 1, 1, 2, 2, -2])
+	dipole_arrangement = pathfinder.model.static.StaticDipoleArrangement([dipole, dipole2])
+	dot_measurements = dipole_arrangement.get_dot_measurements(dot_positions)
+
+	model = pathfinder.model.static.DotDipoleModel(dot_measurements, 2)
+	res = model.sol()
+	print(model.costs()(res.x))
+
+	print_result("two dipole twelve dot", res)
+	# assert res.success, "The solution for two dipoles and twelve dots should have succeeded."
+	numpy.testing.assert_allclose(chunk_n_sort(res.x), chunk_n_sort(expected_result), err_msg="Dipole wasn't as expected.", rtol=1e-6, atol=1e-4)

tests/model/static/test_staticdipole.py

@@ -0,0 +1,23 @@
+import numpy
+import pathfinder.model.static as model
+
+
+def test_static_dipole():
+	d1 = model.StaticDipole((1, 2, 3), (4, 5, 6))
+	d2 = model.StaticDipole((4, 5, 6), (1, 2, 3))
+	dipoles = model.StaticDipoleArrangement([d1, d2])
+
+	dot_position1 = (-1, -1, -1)
+	expected_v1 = -0.3338923121348659
+
+	numpy.testing.assert_allclose(dipoles.get_dot_measurement(dot_position1).v, expected_v1, err_msg="Voltage at dot isn't as expected.")
+	numpy.testing.assert_allclose(dipoles.get_dot_measurement(dot_position1).r, dot_position1, err_msg="Dot isn't where expected.")
+
+	# test multiple dots
+	dot_position2 = (-1, -1, -5)
+	expected_v2 = -0.1254445237566694
+
+	both_measurements = dipoles.get_dot_measurements([dot_position1, dot_position2])
+	measured_voltages = numpy.sort([m.v for m in both_measurements])
+	expected_measured_voltages = numpy.sort([expected_v1, expected_v2])
+	numpy.testing.assert_allclose(measured_voltages, expected_measured_voltages, err_msg="Didn't get the measured voltages expected")

tests/model/test_model.py

@@ -1,107 +0,0 @@
-import numpy
-import pathfinder.model as model
-import scipy.optimize
-import pytest
-
-
-def test_dotdipolemodel_repr():
-	mod = model.DotDipoleModel((), 1)
-	assert repr(mod) == "DotDipoleModel([], 1)"
-
-
-def test_dotdipolemodel_m():
-	mod = model.DotDipoleModel([model.DotMeasurement(1, (0, 0, 0)), model.DotMeasurement(2, (0, 0, 0))], 1)
-	assert mod.m == 2
-
-
-def print_result(msg, result):
-	print(msg)
-	print(f"\tResult: {result.x}")
-	print(f"\tSuccess: {result.success}. {result.message}")
-	try:
-		print(f"\tFunc evals: {result.nfev}")
-	except AttributeError:
-		pass
-	try:
-		print(f"\tJacb evals: {result.njev}")
-	except AttributeError:
-		pass
-
-
-@pytest.mark.skip(reason="old")
-def test_dot_dipole_model_jac():
-	v1 = -0.05547767706400186526225414
-	v2 = -0.06018573388098888319642888
-	v3 = -0.06364032191901859480476888
-	v4 = -0.06488383879243851188402150
-	v5 = -0.06297148063759813929659130
-	v6 = -0.05735489606460216
-	v7 = -0.07237320672886623
-	v8 = -0.1082531754730548
-
-	c1 = model.DotMeasurement(v1, [0, 0, 1])
-	c2 = model.DotMeasurement(v2, [0, 0, 2])
-	c3 = model.DotMeasurement(v3, [0, 0, 3])
-	c4 = model.DotMeasurement(v4, [0, 0, 4])
-	c5 = model.DotMeasurement(v5, [0, 0, 5])
-	c6 = model.DotMeasurement(v6, [0, 0, 6])
-	c7 = model.DotMeasurement(v7, [1, 1, 7])
-	c8 = model.DotMeasurement(v8, [1, 2, 3])
-
-	mod = model.DotDipoleModel([c1, c2, c3, c4, c5, c6], 1)
-	res = scipy.optimize.least_squares(mod.costs(), numpy.array([1, 2, 3, 4, 5, 6]), jac=mod.jac(), ftol=1e-12)
-	print_result("6 dots, least sq", res)
-	mod2 = model.DotDipoleModel([c1, c2, c3, c4, c5, c6, c7, c8], 1)
-	res2 = scipy.optimize.least_squares(mod2.costs(), numpy.array([0, 0, 0, 0, 0, 0]), jac=mod2.jac(), ftol=1e-12, gtol=3e-16)
-	print_result("7 dots, least squares", res2)
-	print(mod2.costs()(res2.x))
-	print(mod2.costs()(numpy.array([1, 3, 5, 5, 6, 7])))
-
-
-@pytest.mark.skip(reason="bad test")
-def test_dot_2dipoles_model_jac():
-	dots_12andone = [
-		model.DotMeasurement(-0.1978319326584865, [-4, -1, 0]),
-		model.DotMeasurement(-0.1273171638293727, [-4, -5, 0]),
-		model.DotMeasurement(-0.05545025617224288, [-4, -9, 0]),
-		model.DotMeasurement(-0.4960209997369774, [-1, -1, 0]),
-		model.DotMeasurement(-0.1763373289754278, [-1, -5, 0]),
-		model.DotMeasurement(-0.04946346672578462, [-1, -9, 0]),
-		model.DotMeasurement(-0.5633156098386561, [1, -1, 0]),
-		model.DotMeasurement(-0.113765134433174, [1, -5, 0]),
-		model.DotMeasurement(-0.0294893572499722, [1, -9, 0]),
-		model.DotMeasurement(0.7794941616360612, [4, -1, 0]),
-		model.DotMeasurement(0.1110683086477768, [4, -5, 0]),
-		model.DotMeasurement(0.01183272220840589, [4, -9, 0]),
-		model.DotMeasurement(-0.1096485462119833, [1, 1, 1]),
-		model.DotMeasurement(-0.3925851888077783, [1, 1, -1])
-	]
-	# dots = [
-	# 	model.Dot(-0.1978319326584865, [-4, -1, 0]),
-	# 	model.Dot(-0.1273171638293727, [-4, -5, 0]),
-	# 	model.Dot(-0.05545025617224288, [-4, -9, 0]),
-	# 	model.Dot(-0.4960209997369774, [-1, -1, 0]),
-	# 	model.Dot(-0.1763373289754278, [-1, -5, 0]),
-	# 	model.Dot(-0.04946346672578462, [-1, -9, 0]),
-	# 	model.Dot(-0.5633156098386561, [1, -1, 0]),
-	# 	model.Dot(-0.113765134433174, [1, -5, 0]),
-	# 	model.Dot(-0.0294893572499722, [1, -9, 0]),
-	# 	model.Dot(0.7794941616360612, [4, -1, 0]),
-	# 	model.Dot(0.1110683086477768, [4, -5, 0]),
-	# 	model.Dot(0.01183272220840589, [4, -9, 0]),
-	# 	model.Dot(-0.0261092728062841, [-4, -13, 0]),
-	# 	model.Dot(-0.02035559593904894, [-1, -13, 0]),
-	# 	model.Dot(-0.01296894715810522, [1, -13, 0]),
-	# 	model.Dot(0.0003306001626435171, [4, -13, 0]),
-	# 	model.Dot(0.2612817068810759, [7, -1, 0]),
-	# 	model.Dot(0.1203841445911355, [7, -5, 0]),
-	# 	model.Dot(0.03425933872931543, [7, -9, 0]),
-	# 	model.Dot(0.01068547688208644, [7, -13, 0]),
-	# ]
-
-	mod = model.DotDipoleModel(dots_12andone, 2)
-	res = scipy.optimize.least_squares(mod.costs(), numpy.array([0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0]), jac=mod.jac(), ftol=1e-12)
-	print_result("6 dots, least sq", res)
-	print(mod.costs()(res.x))
-	for val in res.x:
-		print(val)

tests/test_pathfinder.py

@@ -1,5 +1,7 @@
 from pathfinder import __version__
+import pathfinder
 
 
 def test_version():
 	assert __version__ == '0.0.1'
+	assert pathfinder.get_version() == __version__