fix: fixes some of the shape mangling of our mcmc code

pdme/model/log_spaced_random_choice_fixed_orientation_model.py

@@ -129,12 +129,14 @@ class LogSpacedRandomCountMultipleDipoleFixedMagnitudeFixedOrientationModel(
 
 		p_mask = rng.binomial(1, self.prob_occupancy, shape)
 
-		dipoles = numpy.einsum("ij,k->ijk", p_mask, self.moment_fixed)
+		# 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]
+		p_magnitude = self.pfixed * p_mask
-		py = dipoles[:, :, 1]
+
-		pz = dipoles[:, :, 2]
+		px = p_magnitude * numpy.sin(self.thetafixed) * numpy.cos(self.phifixed)
+		py = p_magnitude * numpy.sin(self.thetafixed) * numpy.sin(self.phifixed)
+		pz = p_magnitude * numpy.cos(self.thetafixed)
 
 		sx = rng.uniform(self.xmin, self.xmax, shape)
 		sy = rng.uniform(self.ymin, self.ymax, shape)

pdme/model/model.py

@@ -72,24 +72,24 @@ class DipoleModel:
 			f"Starting Markov Chain Monte Carlo with seed: {seed} for chain length {chain_length} and provided stdevs {stdevs}"
 		)
 		chain: List[Tuple[float, numpy.ndarray]] = []
-		current = seed
 		if initial_cost is None:
-			current_cost = cost_function(current)
+			current_cost = cost_function(numpy.array([seed]))
 		else:
 			current_cost = initial_cost
+		current = seed
 		for i in range(chain_length):
 			dips = []
 			for dipole_index, dipole in enumerate(current):
+				_logger.debug(dipole_index)
+				_logger.debug(dipole)
 				stdev = stdevs[dipole_index]
 				tentative_dip = self.markov_chain_monte_carlo_proposal(
 					dipole, stdev, rng_arg
 				)
 
 				dips.append(tentative_dip)
-			dips_array = pdme.subspace_simulation.sort_array_of_dipoles_by_frequency(
+			dips_array = pdme.subspace_simulation.sort_array_of_dipoles_by_frequency(dips)
-				dips
+			tentative_cost = cost_function(numpy.array([dips_array]))
-			)
-			tentative_cost = cost_function(dips_array)
 			if tentative_cost < threshold_cost:
 				chain.append((tentative_cost, dips_array))
 				current = dips_array

pdme/subspace_simulation/mcmc_costs.py

@@ -15,6 +15,6 @@ def proportional_costs_vs_actual_measurement(
 	dipoles_to_test: numpy.ndarray,
 ) -> numpy.ndarray:
 	vals = pdme.util.fast_v_calc.fast_vs_for_dipoleses(
-		dot_inputs_array, numpy.array([dipoles_to_test])
+		dot_inputs_array, dipoles_to_test
 	)
 	return proportional_cost(actual_measurement_array, vals)

pyproject.toml

@@ -28,6 +28,8 @@ build-backend = "poetry.core.masonry.api"
 testpaths = ["tests"]
 addopts = "--junitxml pytest.xml --cov pdme --cov-report=xml:coverage.xml --cov-fail-under=50 --cov-report=html"
 junit_family = "xunit1"
+log_format = "%(asctime)s | %(levelname)s | %(pathname)s:%(lineno)d | %(message)s"
+log_level = "DEBUG"
 
 [tool.mypy]
 plugins = "numpy.typing.mypy_plugin"

tests/model/test_log_spaced_fixed_orientation_fixedxy_orientation_mcmc.py

@@ -5,6 +5,9 @@ import pdme.inputs
 import pdme.measurement.input_types
 import pdme.subspace_simulation
 import numpy
+import logging
+
+_logger = logging.getLogger(__name__)
 
 SEED_TO_USE = 42
 
@@ -43,9 +46,9 @@ def get_cost_function():
 	actual_measurements = actual_dipoles.get_dot_measurements(dot_inputs)
 	actual_measurements_array = numpy.array([m.v for m in actual_measurements])
 
-	def cost_to_use(sample_dipoles: numpy.ndarray) -> numpy.ndarray:
+	def cost_to_use(sample_dipoleses: numpy.ndarray) -> numpy.ndarray:
 		return pdme.subspace_simulation.proportional_costs_vs_actual_measurement(
-			dot_input_array, actual_measurements_array, sample_dipoles
+			dot_input_array, actual_measurements_array, sample_dipoleses
 		)
 
 	return cost_to_use
@@ -77,14 +80,19 @@ def test_log_spaced_fixedxy_orientation_mcmc_basic(snapshot):
 	)
 	model.rng = numpy.random.default_rng(1234)
 
-	seed = model.get_monte_carlo_dipole_inputs(1, -1)[0]
+	seed = model.get_monte_carlo_dipole_inputs(1, -1)
 
 	cost_function = get_cost_function()
 	stdev = pdme.subspace_simulation.DipoleStandardDeviation(2, 2, 1, 0.25, 0.5, 1)
 	stdevs = pdme.subspace_simulation.MCMCStandardDeviation([stdev])
 
 	chain = model.get_mcmc_chain(
-		seed, cost_function, 10, cost_function(seed)[0], stdevs, rng_arg=numpy.random.default_rng(1515)
+		seed[0],
+		cost_function,
+		10,
+		cost_function(seed)[0],
+		stdevs,
+		rng_arg=numpy.random.default_rng(1515),
 	)
 
 	assert chain == snapshot

tests/model/test_log_spaced_fixed_orientation_free_orientation_mcmc.py

@@ -5,6 +5,9 @@ import pdme.inputs
 import pdme.measurement.input_types
 import pdme.subspace_simulation
 import numpy
+import logging
+
+_logger = logging.getLogger(__name__)
 
 SEED_TO_USE = 42
 
@@ -43,9 +46,9 @@ def get_cost_function():
 	actual_measurements = actual_dipoles.get_dot_measurements(dot_inputs)
 	actual_measurements_array = numpy.array([m.v for m in actual_measurements])
 
-	def cost_to_use(sample_dipoles: numpy.ndarray) -> numpy.ndarray:
+	def cost_to_use(sample_dipoleses: numpy.ndarray) -> numpy.ndarray:
 		return pdme.subspace_simulation.proportional_costs_vs_actual_measurement(
-			dot_input_array, actual_measurements_array, sample_dipoles
+			dot_input_array, actual_measurements_array, sample_dipoleses
 		)
 
 	return cost_to_use
@@ -77,14 +80,19 @@ def test_log_spaced_free_orientation_mcmc_basic(snapshot):
 	)
 	model.rng = numpy.random.default_rng(1234)
 
-	seed = model.get_monte_carlo_dipole_inputs(1, -1)[0]
+	seed = model.get_monte_carlo_dipole_inputs(1, -1)
 
 	cost_function = get_cost_function()
 	stdev = pdme.subspace_simulation.DipoleStandardDeviation(2, 2, 1, 0.25, 0.5, 1)
 	stdevs = pdme.subspace_simulation.MCMCStandardDeviation([stdev])
 
 	chain = model.get_mcmc_chain(
-		seed, cost_function, 10, cost_function(seed)[0], stdevs, rng_arg=numpy.random.default_rng(1515)
+		seed[0],
+		cost_function,
+		10,
+		cost_function(seed)[0],
+		stdevs,
+		rng_arg=numpy.random.default_rng(1515),
 	)
 
 	assert chain == snapshot

tests/model/test_log_spaced_fixed_orientation_mcmc.py

@@ -5,6 +5,9 @@ import pdme.inputs
 import pdme.measurement.input_types
 import pdme.subspace_simulation
 import numpy
+import logging
+
+_logger = logging.getLogger(__name__)
 
 SEED_TO_USE = 42
 
@@ -47,9 +50,9 @@ def get_cost_function():
 	actual_measurements = actual_dipoles.get_dot_measurements(dot_inputs)
 	actual_measurements_array = numpy.array([m.v for m in actual_measurements])
 
-	def cost_to_use(sample_dipoles: numpy.ndarray) -> numpy.ndarray:
+	def cost_to_use(sample_dipoleses: numpy.ndarray) -> numpy.ndarray:
 		return pdme.subspace_simulation.proportional_costs_vs_actual_measurement(
-			dot_input_array, actual_measurements_array, sample_dipoles
+			dot_input_array, actual_measurements_array, sample_dipoleses
 		)
 
 	return cost_to_use
@@ -85,14 +88,19 @@ def test_log_spaced_fixed_orientation_mcmc_basic(snapshot):
 	)
 	model.rng = numpy.random.default_rng(1234)
 
-	seed = model.get_monte_carlo_dipole_inputs(1, -1)[0]
+	seed = model.get_monte_carlo_dipole_inputs(1, -1)
 
 	cost_function = get_cost_function()
 	stdev = pdme.subspace_simulation.DipoleStandardDeviation(2, 2, 1, 0.25, 0.5, 1)
 	stdevs = pdme.subspace_simulation.MCMCStandardDeviation([stdev])
 
 	chain = model.get_mcmc_chain(
-		seed, cost_function, 10, cost_function(seed)[0], stdevs, rng_arg=numpy.random.default_rng(1515)
+		seed[0],
+		cost_function,
+		10,
+		cost_function(seed)[0],
+		stdevs,
+		rng_arg=numpy.random.default_rng(1515),
 	)
 
 	assert chain == snapshot

tests/model/test_log_spaced_random_count_multiple_dipole_fixed_orientation_fixed_magnitude_model.py

@@ -116,7 +116,6 @@ def test_random_count_multiple_dipole_fixed_mag_model_get_dipoles_invariant():
 
 
 def test_random_count_multiple_dipole_fixed_or_fixed_mag_model_get_n_dipoles(snapshot):
-	# TODO: this test is a bit garbage just calls things without testing.
 	x_min = -10
 	x_max = 10
 	y_min = -5