chore(deps): update dependency mypy to ^0.940

CHANGELOG.md

@@ -2,6 +2,27 @@
 
 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.
 
+### [0.3.5](https://gitea.deepak.science:2222/physics/deepdog/compare/0.3.4...0.3.5) (2022-03-07)
+
+
+### Features
+
+* makes chunksize configurable ([88d9613](https://gitea.deepak.science:2222/physics/deepdog/commit/88d961313c1db0d49fd96939aa725a8706fa0412))
+
+### [0.3.4](https://gitea.deepak.science:2222/physics/deepdog/compare/0.3.3...0.3.4) (2022-03-06)
+
+
+### Features
+
+* Changes chunksize for multiprocessing ([0784cd5](https://gitea.deepak.science:2222/physics/deepdog/commit/0784cd53d79e00684506604f094b5d820b3994d4))
+
+### [0.3.3](https://gitea.deepak.science:2222/physics/deepdog/compare/0.3.2...0.3.3) (2022-03-06)
+
+
+### Bug Fixes
+
+* Fixes count to use cycles as well ([8617e4d](https://gitea.deepak.science:2222/physics/deepdog/commit/8617e4d2742b112cc824068150682ce3b2cdd879))
+
 ### [0.3.2](https://gitea.deepak.science:2222/physics/deepdog/compare/0.3.1...0.3.2) (2022-03-06)
 
 

deepdog/alt_bayes_run.py

@@ -10,8 +10,7 @@ import numpy
 
 
 # TODO: remove hardcode
-COST_THRESHOLD = 1e-10
+CHUNKSIZE = 50
-
 
 # TODO: It's garbage to have this here duplicated from pdme.
 DotInput = Tuple[numpy.typing.ArrayLike, float]
@@ -44,7 +43,7 @@ class AltBayesRun():
 	run_count: int
 		The number of runs to do.
 	'''
-	def __init__(self, dot_inputs: Sequence[DotInput], discretisations_with_names: Sequence[Tuple[str, pdme.model.Discretisation]], actual_model: pdme.model.Model, filename_slug: str, run_count: int, low_error: float = 0.9, high_error: float = 1.1, monte_carlo_count: int = 10000, monte_carlo_cycles: int = 10, max_frequency: float = 20, end_threshold: float = None) -> None:
+	def __init__(self, dot_inputs: Sequence[DotInput], discretisations_with_names: Sequence[Tuple[str, pdme.model.Discretisation]], actual_model: pdme.model.Model, filename_slug: str, run_count: int, low_error: float = 0.9, high_error: float = 1.1, monte_carlo_count: int = 10000, monte_carlo_cycles: int = 10, max_frequency: float = 20, end_threshold: float = None, chunksize: int = CHUNKSIZE) -> None:
 		self.dot_inputs = dot_inputs
 		self.dot_inputs_array = pdme.measurement.oscillating_dipole.dot_inputs_to_array(dot_inputs)
 		self.discretisations = [disc for (_, disc) in discretisations_with_names]
@@ -58,6 +57,7 @@ class AltBayesRun():
 		self.high_error = high_error
 		self.csv_fields = ["dipole_moment", "dipole_location", "dipole_frequency"]
 		self.compensate_zeros = True
+		self.chunksize = chunksize
 		for name in self.model_names:
 			self.csv_fields.extend([f"{name}_success", f"{name}_count", f"{name}_prob"])
 
@@ -98,7 +98,7 @@ class AltBayesRun():
 				_logger.debug(f"Doing discretisation #{disc_count}")
 				with multiprocessing.Pool(multiprocessing.cpu_count() - 1 or 1) as pool:
 					results.append(sum(
-						pool.imap_unordered(get_a_result, [(discretisation, self.dot_inputs_array, lows, highs, self.monte_carlo_count, self.max_frequency)] * self.monte_carlo_cycles)
+						pool.imap_unordered(get_a_result, [(discretisation, self.dot_inputs_array, lows, highs, self.monte_carlo_count, self.max_frequency)] * self.monte_carlo_cycles, self.chunksize)
 					))
 
 			_logger.debug("Done, constructing output now")
@@ -112,9 +112,9 @@ class AltBayesRun():
 			for model_index, (name, result) in enumerate(zip(self.model_names, results)):
 
 				row[f"{name}_success"] = result
-				row[f"{name}_count"] = self.monte_carlo_count
+				row[f"{name}_count"] = self.monte_carlo_count * self.monte_carlo_cycles
 				successes.append(max(result, 0.5))
-				counts.append(self.monte_carlo_count)
+				counts.append(self.monte_carlo_count * self.monte_carlo_cycles)
 
 			success_weight = sum([(succ / count) * prob for succ, count, prob in zip(successes, counts, self.probabilities)])
 			new_probabilities = [(succ / count) * old_prob / success_weight for succ, count, old_prob in zip(successes, counts, self.probabilities)]

poetry.lock

@@ -260,7 +260,7 @@ python-versions = "*"
 
 [[package]]
 name = "mypy"
-version = "0.931"
+version = "0.940"
 description = "Optional static typing for Python"
 category = "dev"
 optional = false
@@ -274,6 +274,7 @@ typing-extensions = ">=3.10"
 [package.extras]
 dmypy = ["psutil (>=4.0)"]
 python2 = ["typed-ast (>=1.4.0,<2)"]
+reports = ["lxml"]
 
 [[package]]
 name = "mypy-extensions"
@@ -697,7 +698,7 @@ testing = ["pytest (>=6)", "pytest-checkdocs (>=2.4)", "pytest-flake8", "pytest-
 [metadata]
 lock-version = "1.1"
 python-versions = "^3.8,<3.10"
-content-hash = "ba794e6f69d42e44e2b1abc40731fd78d2f417cdc9be12d6e752dbcfa95adaad"
+content-hash = "ac69ab9be2cde12f64be445f46af378b6943d3c19cbf9fd3e1b6b81371c7a5a6"
 
 [metadata.files]
 atomicwrites = [
@@ -898,26 +899,29 @@ mccabe = [
     {file = "mccabe-0.6.1.tar.gz", hash = "sha256:dd8d182285a0fe56bace7f45b5e7d1a6ebcbf524e8f3bd87eb0f125271b8831f"},
 ]
 mypy = [
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+    {file = "mypy-0.940-cp310-cp310-macosx_10_9_universal2.whl", hash = "sha256:0fdc9191a49c77ab5fa0439915d405e80a1118b163ab03cd2a530f346b12566a"},
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+    {file = "mypy-0.940-cp310-cp310-macosx_10_9_x86_64.whl", hash = "sha256:1903c92ff8642d521b4627e51a67e49f5be5aedb1fb03465b3aae4c3338ec491"},
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 ]
 mypy-extensions = [
     {file = "mypy_extensions-0.4.3-py2.py3-none-any.whl", hash = "sha256:090fedd75945a69ae91ce1303b5824f428daf5a028d2f6ab8a299250a846f15d"},

pyproject.toml

@@ -1,6 +1,6 @@
 [tool.poetry]
 name = "deepdog"
-version = "0.3.2"
+version = "0.3.5"
 description = ""
 authors = ["Deepak Mallubhotla <dmallubhotla+github@gmail.com>"]
 
@@ -12,7 +12,7 @@ pdme = "^0.5.4"
 pytest = ">=6"
 flake8 = "^4.0.1"
 pytest-cov = "^3.0.0"
-mypy = "^0.931"
+mypy = "^0.940"
 python-semantic-release = "^7.24.0"
 
 [build-system]