chore(deps): update dependency scipy to ~1.12

CHANGELOG.md

@@ -2,6 +2,31 @@
 
 All notable changes to this project will be documented in this file. See [standard-version](https://github.com/conventional-changelog/standard-version) for commit guidelines.
 
+### [0.9.2](https://gitea.deepak.science:2222/physics/pdme/compare/0.9.1...0.9.2) (2023-07-24)
+
+
+### Bug Fixes
+
+* update tests but for git also don't wrap costs ([50f98ed](https://gitea.deepak.science:2222/physics/pdme/commit/50f98ed89b2a05cd47c41958036dd50bc872e07c))
+
+### [0.9.1](https://gitea.deepak.science:2222/physics/pdme/compare/0.9.0...0.9.1) (2023-07-24)
+
+
+### Bug Fixes
+
+* fixes some of the shape mangling of our mcmc code ([e01d0e1](https://gitea.deepak.science:2222/physics/pdme/commit/e01d0e14a9bcd6d7e8fe9449ce562dbf1b8fd25c))
+
+## [0.9.0](https://gitea.deepak.science:2222/physics/pdme/compare/0.8.9...0.9.0) (2023-07-24)
+
+
+### ⚠ BREAKING CHANGES
+
+* separates threshold cost and the seed_cost in mcmc
+
+### Features
+
+* separates threshold cost and the seed_cost in mcmc ([ca710e3](https://gitea.deepak.science:2222/physics/pdme/commit/ca710e359fd0cfbb620a3574a2fa4fab1be2b52a))
+
 ### [0.8.9](https://gitea.deepak.science:2222/physics/pdme/compare/0.8.8...0.8.9) (2023-07-23)
 
 

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]
-		py = dipoles[:, :, 1]
-		pz = dipoles[:, :, 2]
+		p_magnitude = self.pfixed * p_mask
+
+		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

@@ -47,6 +47,7 @@ class DipoleModel:
 		seed,
 		cost_function,
 		chain_length,
+		threshold_cost: float,
 		stdevs: pdme.subspace_simulation.MCMCStandardDeviation,
 		initial_cost: Optional[float] = None,
 		rng_arg: Optional[numpy.random.Generator] = None,
@@ -71,15 +72,16 @@ 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:
-			cost_to_compare = cost_function(current)
+			current_cost = cost_function(numpy.array([seed]))
 		else:
-			cost_to_compare = initial_cost
-		current_cost = cost_to_compare
+			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
@@ -89,11 +91,11 @@ class DipoleModel:
 			dips_array = pdme.subspace_simulation.sort_array_of_dipoles_by_frequency(
 				dips
 			)
-			tentative_cost = cost_function(dips_array)
-			if tentative_cost < cost_to_compare:
-				chain.append((tentative_cost, dips_array))
+			tentative_cost = cost_function(numpy.array([dips_array]))[0]
+			if tentative_cost < threshold_cost:
+				chain.append((numpy.squeeze(tentative_cost).item(), dips_array))
 				current = dips_array
 				current_cost = tentative_cost
 			else:
-				chain.append((current_cost, current))
+				chain.append((numpy.squeeze(current_cost).item(), current))
 		return chain

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

@@ -1,6 +1,6 @@
 [tool.poetry]
 name = "pdme"
-version = "0.8.9"
+version = "0.9.2"
 description = "Python dipole model evaluator"
 authors = ["Deepak <dmallubhotla+github@gmail.com>"]
 license = "GPL-3.0-only"
@@ -9,7 +9,7 @@ readme = "README.md"
 [tool.poetry.dependencies]
 python = ">=3.8.1,<3.10"
 numpy = "^1.22.3"
-scipy = "~1.11"
+scipy = "~1.12"
 
 [tool.poetry.dev-dependencies]
 pytest = ">=6"
@@ -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 = "WARNING"
 
 [tool.mypy]
 plugins = "numpy.typing.mypy_plugin"

tests/model/__snapshots__/test_log_spaced_fixed_orientation_fixedxy_orientation_mcmc.ambr

@@ -2,52 +2,52 @@
 # name: test_log_spaced_fixedxy_orientation_mcmc_basic
   list([
     tuple(
-      array([3984.46179656]),
+      3984.461796565,
       array([[ 9.55610128,  2.94634152,  0.        ,  9.21529051, -2.46576127,
            2.42481096,  9.19034554]]),
     ),
     tuple(
-      array([8583.99087872]),
+      8583.9908787152,
       array([[ 9.99991539,  0.04113671,  0.        ,  8.71258954, -2.26599865,
            2.60452102,  6.37042214]]),
     ),
     tuple(
-      array([6215.6376616]),
+      6215.6376616016,
       array([[ 9.81950685, -1.89137124,  0.        ,  8.90637055, -2.48043039,
            2.28444435,  8.84239221]]),
     ),
     tuple(
-      array([424.73328466]),
+      424.7332846598,
       array([[ 1.00028483,  9.94984574,  0.        ,  8.53064898, -2.59230757,
            2.33774773,  8.6714416 ]]),
     ),
     tuple(
-      array([300.92203808]),
+      300.9220380849,
       array([[ 1.4003442 ,  9.90146636,  0.        ,  8.05557992, -2.6753126 ,
            2.65915755, 13.02021385]]),
     ),
     tuple(
-      array([2400.01072771]),
+      2400.0107277085,
       array([[ 9.97761813,  0.66868263,  0.        ,  8.69171028, -2.73145011,
            2.90140456, 19.94999593]]),
     ),
     tuple(
-      array([5001.46205113]),
+      5001.4620511303,
       array([[ 9.93976109, -1.09596962,  0.        ,  8.95245025, -2.59409162,
            2.90140456,  9.75535945]]),
     ),
     tuple(
-      array([195.21980745]),
+      195.2198074488,
       array([[ 0.20690762,  9.99785923,  0.        ,  9.59636585, -2.83240984,
            2.90140456, 16.14771567]]),
     ),
     tuple(
-      array([2698.2588445]),
+      2698.258844498,
       array([[-9.68130127, -2.50447712,  0.        ,  8.94823619, -2.92889659,
            2.77065328, 13.63173263]]),
     ),
     tuple(
-      array([1193.69854739]),
+      1193.6985473944,
       array([[-6.16597091, -7.87278875,  0.        ,  9.62210721, -2.75993924,
            2.77065328,  5.64553534]]),
     ),

tests/model/__snapshots__/test_log_spaced_fixed_orientation_free_orientation_mcmc.ambr

@@ -2,52 +2,52 @@
 # name: test_log_spaced_free_orientation_mcmc_basic
   list([
     tuple(
-      array([3167.67112687]),
+      3167.6711268743,
       array([[ 9.60483896, -1.41627817, -2.3960853 , -4.76615152, -1.80902942,
            2.11809123, 16.17452242]]),
     ),
     tuple(
-      array([3167.67112687]),
+      3167.6711268743,
       array([[ 9.60483896, -1.41627817, -2.3960853 , -4.76615152, -1.80902942,
            2.11809123, 16.17452242]]),
     ),
     tuple(
-      array([3167.67112687]),
+      3167.6711268743,
       array([[ 9.60483896, -1.41627817, -2.3960853 , -4.76615152, -1.80902942,
            2.11809123, 16.17452242]]),
     ),
     tuple(
-      array([736.03065271]),
+      736.0306527136,
       array([[ 4.1660069 , -8.11557337,  4.0965663 , -4.35968351, -1.97945216,
            2.43615641, 12.92143144]]),
     ),
     tuple(
-      array([736.03065271]),
+      736.0306527136,
       array([[ 4.1660069 , -8.11557337,  4.0965663 , -4.35968351, -1.97945216,
            2.43615641, 12.92143144]]),
     ),
     tuple(
-      array([736.03065271]),
+      736.0306527136,
       array([[ 4.1660069 , -8.11557337,  4.0965663 , -4.35968351, -1.97945216,
            2.43615641, 12.92143144]]),
     ),
     tuple(
-      array([2248.07799863]),
+      2248.0779986277,
       array([[-1.71755535, -5.59925137,  8.10545419, -4.03306318, -1.81098441,
            2.77407111, 32.28020575]]),
     ),
     tuple(
-      array([1663.31067274]),
+      1663.310672736,
       array([[-5.16785855,  2.7558756 ,  8.10545419, -3.34620897, -1.74763642,
            2.42770463, 52.98214008]]),
     ),
     tuple(
-      array([1329.27041439]),
+      1329.2704143918,
       array([[ -1.39600464,   9.69718343,  -2.00394725,  -2.59147366,
            -1.91246681,   2.07361175, 123.01833742]]),
     ),
     tuple(
-      array([355.76955919]),
+      355.7695591897,
       array([[  9.76047401,   0.84696075,  -2.00394725,  -3.04310053,
            -1.99338573,   2.1185589 , 271.35743739]]),
     ),

tests/model/__snapshots__/test_log_spaced_fixed_orientation_mcmc.ambr

@@ -2,52 +2,52 @@
 # name: test_log_spaced_fixed_orientation_mcmc_basic
   list([
     tuple(
-      array([50.56831193]),
+      50.5683119299,
       array([[ 0.        ,  0.        , 10.        , -2.3960853 ,  4.23246234,
            2.26169242, 39.39900844]]),
     ),
     tuple(
-      array([50.56831193]),
+      50.5683119299,
       array([[ 0.        ,  0.        , 10.        , -2.3960853 ,  4.23246234,
            2.26169242, 39.39900844]]),
     ),
     tuple(
-      array([47.40865455]),
+      47.408654554,
       array([[ 0.        ,  0.        , 10.        , -2.03666518,  4.14084039,
            2.21309317, 47.82371559]]),
     ),
     tuple(
-      array([47.40865455]),
+      47.408654554,
       array([[ 0.        ,  0.        , 10.        , -2.03666518,  4.14084039,
            2.21309317, 47.82371559]]),
     ),
     tuple(
-      array([47.40865455]),
+      47.408654554,
       array([[ 0.        ,  0.        , 10.        , -2.03666518,  4.14084039,
            2.21309317, 47.82371559]]),
     ),
     tuple(
-      array([47.40865455]),
+      47.408654554,
       array([[ 0.        ,  0.        , 10.        , -2.03666518,  4.14084039,
            2.21309317, 47.82371559]]),
     ),
     tuple(
-      array([22.93279028]),
+      22.9327902847,
       array([[ 0.        ,  0.        , 10.        , -1.63019717,  3.97041764,
            2.53115835, 38.2051999 ]]),
     ),
     tuple(
-      array([28.81197733]),
+      28.8119773322,
       array([[ 0.        ,  0.        , 10.        , -1.14570315,  4.07709911,
            2.48697441, 49.58615195]]),
     ),
     tuple(
-      array([28.81197733]),
+      28.8119773322,
       array([[ 0.        ,  0.        , 10.        , -1.14570315,  4.07709911,
            2.48697441, 49.58615195]]),
     ),
     tuple(
-      array([40.97406005]),
+      40.9740600543,
       array([[ 0.        ,  0.        , 10.        , -0.50178755,  3.83878089,
            2.93560796, 82.07827571]]),
     ),

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 +80,21 @@ 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, 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
+	chain_rounded = [(round(cost, 10), dipoles) for (cost, dipoles) in chain]
+
+	assert chain_rounded == 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 +80,21 @@ 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, 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
+	chain_rounded = [(round(cost, 10), dipoles) for (cost, dipoles) in chain]
+
+	assert chain_rounded == 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 +88,21 @@ 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, 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
+	chain_rounded = [(round(cost, 10), dipoles) for (cost, dipoles) in chain]
+
+	assert chain_rounded == 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