Adds test for 6 dots and adds some perfect satisfaction checks

pathfinder/model/model.py

@@ -37,5 +37,8 @@ class DotDipoleModel():
 		return jac_to_return
 
 	def sol(self):
-		initial = numpy.zeros(6 * self.n)
+		initial = numpy.zeros(6 * self.n) + .1
+		if 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)

tests/model/test_model_sol.py

@@ -0,0 +1,32 @@
+import numpy
+import pathfinder.model
+
+
+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_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.StaticDipole([1, 2, 3], [0, 4, 0])
+	expected_result = numpy.array([1, 2, 3, 0, 4, 0])
+	dipole_arrangement = pathfinder.model.StaticDipoleArrangement([dipole])
+	dot_measurements = dipole_arrangement.get_dot_measurements(dot_positions)
+
+	model = pathfinder.model.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)