Adds unrestricted model and adds util for normalising

tests/model/test_unrestricted_basic_solve.py

@@ -0,0 +1,24 @@
+from pdme.model import UnrestrictedModel
+from pdme.measurement import OscillatingDipole, OscillatingDipoleArrangement
+import logging
+import numpy
+import itertools
+
+
+def test_unrestricted_model_solve_basic():
+	# Initialise our dipole arrangement and create dot measurements along a square.
+	dipoles = OscillatingDipoleArrangement([OscillatingDipole((.2, 0, 2), (1, 2, 4), 1)])
+	dot_inputs = list(itertools.chain.from_iterable(
+		(([1, 2, 0.01], f), ([1, 1, -0.2], f), ([1.5, 2, 0.01], f), ([1.5, 1, -0.2], f), ([2, 1, 0], f), ([2, 2, 0], f), ([0, 2, -.1], f), ([0, 1, 0.04], f), ([2, 0, 0], f), ([1, 0, 0], f)) for f in numpy.arange(1, 10, 2)
+	))
+	dots = dipoles.get_dot_measurements(dot_inputs)
+
+	model = UnrestrictedModel(1)
+
+	# from the dipole, these are the unspecified variables in ((0, 0, 2), (1, 2, 4), 1)
+	expected_solution = [0.2, 0, 2, 1, 2, 4, 1]
+
+	result = model.solve(dots)
+	logging.info(result)
+	assert result.success
+	numpy.testing.assert_allclose(result.normalised_x, expected_solution, err_msg="Even well specified problem solution was wrong.", rtol=1e-6, atol=1e-11)

tests/model/test_unrestricted_model.py

@@ -0,0 +1,38 @@
+from pdme.model import UnrestrictedModel
+from pdme.measurement import DotMeasurement
+import logging
+import numpy
+
+
+def test_unrestricted_plane_model_repr():
+	model = UnrestrictedModel(6)
+	assert repr(model) == "UnrestrictedModel(6)"
+
+
+def test_unrestricted_model_cost_and_jac_single():
+	model = UnrestrictedModel(1)
+	measured_v = 0.000191292  # from dipole with p=(0, 0, 2) at (1, 2, 4) with w = 1
+	dot = DotMeasurement(measured_v, (1, 2, 0), 5)
+	pt = [0, 0, 2, 2, 2, 4, 2]
+
+	cost_function = model.costs([dot])
+
+	expected_cost = [0.0000946746]
+	actual_cost = cost_function(pt)
+
+	numpy.testing.assert_allclose(actual_cost, expected_cost, err_msg="Cost wasn't as expected.", rtol=1e-6, atol=1e-11)
+
+	jac_function = model.jac([dot])
+
+	expected_jac = [
+		[
+			0.00007149165379592005, 0, 0.0002859666151836802,
+			-0.0001009293935942401, 0, -0.0002607342667851202,
+			0.0001035396365320221
+		]
+	]
+	actual_jac = jac_function(pt)
+
+	logging.warning(actual_jac)
+
+	numpy.testing.assert_allclose(actual_jac, expected_jac, err_msg="Jac wasn't as expected.", rtol=1e-6, atol=1e-11)