From 939d877aa7f01c05c005b9d0d693d0b27ef93406 Mon Sep 17 00:00:00 2001 From: Thomas Marks Date: Thu, 7 Aug 2025 13:14:13 -0400 Subject: [PATCH 01/29] add copyright notice to license --- LICENSE | 3 +++ 1 file changed, 3 insertions(+) diff --git a/LICENSE b/LICENSE index f288702..63aa8e3 100644 --- a/LICENSE +++ b/LICENSE @@ -1,3 +1,6 @@ +Copyright 2023-2025 The Regents of the University of Michigan +Computational Autonomy Group (alexgorodetsky.com), Department of Aerospace Engineering + GNU GENERAL PUBLIC LICENSE Version 3, 29 June 2007 From ea37b80c9c2b25d36829f0e35ba4cfdd25671ebc Mon Sep 17 00:00:00 2001 From: Thomas Marks Date: Thu, 7 Aug 2025 13:15:02 -0400 Subject: [PATCH 02/29] Update LICENSE --- LICENSE | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/LICENSE b/LICENSE index 63aa8e3..1858190 100644 --- a/LICENSE +++ b/LICENSE @@ -1,4 +1,4 @@ -Copyright 2023-2025 The Regents of the University of Michigan +Copyright (C) 2023-2025 The Regents of the University of Michigan Computational Autonomy Group (alexgorodetsky.com), Department of Aerospace Engineering GNU GENERAL PUBLIC LICENSE From 0ae5bb4bf188d431132ea786137dd0e8eea18f0a Mon Sep 17 00:00:00 2001 From: Thomas Marks Date: Tue, 3 Mar 2026 13:17:57 -0500 Subject: [PATCH 03/29] fix depwarn for pydantic --- README.md | 2 +- src/amisc/component.py | 6 +- tests/test_system.py | 2 +- uv.lock | 3499 ++++++++++++++++++++++++++++++++++++++++ 4 files changed, 3504 insertions(+), 5 deletions(-) create mode 100644 uv.lock diff --git a/README.md b/README.md index 5f7811d..b402bcd 100644 --- a/README.md +++ b/README.md @@ -6,7 +6,7 @@ ![build](https://img.shields.io/github/actions/workflow/status/eckelsjd/amisc/deploy.yml?logo=github) ![docs](https://img.shields.io/github/actions/workflow/status/eckelsjd/amisc/docs.yml?logo=materialformkdocs&logoColor=%2523cccccc&label=docs) ![tests](https://img.shields.io/github/actions/workflow/status/eckelsjd/amisc/tests.yml?logo=github&logoColor=%2523cccccc&label=tests) -![Code Coverage](https://img.shields.io/badge/coverage-89%25-yellowgreen?logo=codecov) +![Code Coverage](https://img.shields.io/badge/coverage-88%25-yellowgreen?logo=codecov) [![Algorithm description](https://img.shields.io/badge/DOI-10.1002/nme.6958-blue)](https://doi.org/10.1002/nme.6958) Efficient framework for building surrogates of multidisciplinary systems using the adaptive multi-index stochastic collocation ([AMISC](https://onlinelibrary.wiley.com/doi/full/10.1002/nme.6958)) technique. diff --git a/src/amisc/component.py b/src/amisc/component.py index 5d5a342..6331a1b 100644 --- a/src/amisc/component.py +++ b/src/amisc/component.py @@ -431,7 +431,7 @@ def __init__(self, /, model, *args, inputs=None, outputs=None, name=None, **kwar # Gather all model kwargs (anything else passed in for kwargs is assumed to be a model kwarg) model_kwargs = kwargs.get('model_kwargs', {}) - for key in kwargs.keys() - self.model_fields.keys(): + for key in kwargs.keys() - Component.model_fields.keys(): model_kwargs[key] = kwargs.pop(key) kwargs['model_kwargs'] = model_kwargs @@ -441,12 +441,12 @@ def __init__(self, /, model, *args, inputs=None, outputs=None, name=None, **kwar field = kwargs.get(key, None) if isinstance(field, dict): field_super = next(filter(lambda x: issubclass(x, Serializable), - typing.get_args(self.model_fields[key].annotation)), None) + typing.get_args(Component.model_fields[key].annotation)), None) field = field_super.from_dict(field) if field_super is not None else field kwargs[key] = field if not serializers.get(key, None): serializers[key] = type(field) if isinstance(field, Serializable) else ( - type(self.model_fields[key].default)) + type(Component.model_fields[key].default)) kwargs['serializers'] = serializers super().__init__(model=model, inputs=inputs, outputs=outputs, name=name, **kwargs) # Runs pydantic 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-0500 Subject: [PATCH 04/29] fix None type hints --- src/amisc/component.py | 40 ++++++++++++------------- src/amisc/compression.py | 16 +++++----- src/amisc/distribution.py | 8 ++--- src/amisc/interpolator.py | 8 ++--- src/amisc/system.py | 62 +++++++++++++++++++-------------------- src/amisc/training.py | 35 ++++++++++++---------- src/amisc/transform.py | 2 +- src/amisc/utils.py | 4 +-- src/amisc/variable.py | 10 +++---- 9 files changed, 94 insertions(+), 91 deletions(-) diff --git a/src/amisc/component.py b/src/amisc/component.py index 6331a1b..f7aa7e3 100644 --- a/src/amisc/component.py +++ b/src/amisc/component.py @@ -175,7 +175,7 @@ class MiscTree(UserDict, Serializable): """ SERIALIZER_KEY = 'state_serializer' - def __init__(self, data: dict = None, **kwargs): + def __init__(self, data: dict | None = None, **kwargs): data_dict = data or {} if isinstance(data_dict, MiscTree): data_dict = data_dict.data @@ -269,7 +269,7 @@ def get(self, key, default=None) -> float | InterpolatorState: except Exception: return default - def update(self, data_dict: dict = None, **kwargs): + def update(self, data_dict: dict| None = None, **kwargs): """Force `dict.update()` through the validator.""" data_dict = data_dict or dict() data_dict.update(kwargs) @@ -805,9 +805,9 @@ def get_training_data(self, alpha: Literal['best', 'worst'] | MultiIndex = 'best raise e def call_model(self, inputs: dict | Dataset, - model_fidelity: Literal['best', 'worst'] | tuple | list = None, - output_path: str | Path = None, - executor: Executor = None, + model_fidelity: Literal['best', 'worst'] | tuple | list | None = None, + output_path: str | Path | None = None, + executor: Executor | None = None, track_costs: bool = False, **kwds) -> Dataset: """Wrapper function for calling the underlying component model. @@ -1037,12 +1037,12 @@ def call_model(self, inputs: dict | Dataset, return output_dict def predict(self, inputs: dict | Dataset, - use_model: Literal['best', 'worst'] | tuple = None, - model_dir: str | Path = None, + use_model: Literal['best', 'worst'] | tuple | None = None, + model_dir: str | Pat | Noneh = None, index_set: Literal['train', 'test'] | IndexSet = 'test', - misc_coeff: MiscTree = None, + misc_coeff: MiscTree | None = None, incremental: bool = False, - executor: Executor = None, + executor: Executor | None = None, **kwds) -> Dataset: """Evaluate the MISC surrogate approximation at new inputs `x`. @@ -1134,7 +1134,7 @@ def predict(self, inputs: dict | Dataset, return format_outputs(outputs, loop_shape) def update_misc_coeff(self, new_indices: IndexSet, index_set: Literal['test', 'train'] | IndexSet = 'train', - misc_coeff: MiscTree = None): + misc_coeff: MiscTree | None = None): """Update MISC coefficients incrementally resulting from the addition of new indices to an index set. !!! Warning "Incremental updates" @@ -1165,8 +1165,8 @@ def update_misc_coeff(self, new_indices: IndexSet, index_set: Literal['test', 't misc_coeff[old_alpha, old_beta] = 0 misc_coeff[old_alpha, old_beta] += (-1) ** int(np.sum(np.abs(diff))) - def activate_index(self, alpha: MultiIndex, beta: MultiIndex, model_dir: str | Path = None, - executor: Executor = None, weight_fcns: dict[str, callable] | Literal['pdf'] | None = 'pdf'): + def activate_index(self, alpha: MultiIndex, beta: MultiIndex, model_dir: str | Path | None = None, + executor: Executor | None = None, weight_fcns: dict[str, Callable] | Literal['pdf'] | None = 'pdf'): """Add a multi-index to the active set and all neighbors to the candidate set. !!! Warning @@ -1309,9 +1309,9 @@ def activate_index(self, alpha: MultiIndex, beta: MultiIndex, model_dir: str | P def gradient(self, inputs: dict | Dataset, index_set: Literal['train', 'test'] | IndexSet = 'test', - misc_coeff: MiscTree = None, + misc_coeff: MiscTree | None = None, derivative: Literal['first', 'second'] = 'first', - executor: Executor = None) -> Dataset: + executor: Executor | None = None) -> Dataset | None: """Evaluate the Jacobian or Hessian of the MISC surrogate approximation at new `inputs`, i.e. the first or second derivatives, respectively. @@ -1385,7 +1385,7 @@ def model_kwarg_requested(self, kwarg_name: str) -> bool: return True return False - def set_logger(self, log_file: str | Path = None, stdout: bool = None, logger: logging.Logger = None, + def set_logger(self, log_file: str | Path | None = None, stdout: bool | None = None, logger: logging.Logger | None = None, level: int = logging.INFO): """Set a new `logging.Logger` object. @@ -1404,7 +1404,7 @@ def set_logger(self, log_file: str | Path = None, stdout: bool = None, logger: l break self._logger = logger or get_logger(self.name, log_file=log_file, stdout=stdout, level=level) - def update_model(self, new_model: callable = None, model_kwargs: dict = None, **kwargs): + def update_model(self, new_model: Callable | None = None, model_kwargs: dict | None = None, **kwargs): """Update the underlying component model or its kwargs.""" if new_model is not None: self.model = new_model @@ -1475,8 +1475,8 @@ def clear(self): self._model_end_time = -1.0 self.clear_cache() - def serialize(self, keep_yaml_objects: bool = False, serialize_args: dict[str, tuple] = None, - serialize_kwargs: dict[str: dict] = None) -> dict: + def serialize(self, keep_yaml_objects: bool = False, serialize_args: dict[str, tuple] | None = None, + serialize_kwargs: dict[str, dict] | None = None) -> dict: """Convert to a `dict` with only standard Python types as fields and values. :param keep_yaml_objects: whether to keep `Variable` or other yaml serializable objects instead of @@ -1525,8 +1525,8 @@ def serialize(self, keep_yaml_objects: bool = False, serialize_args: dict[str, t return d @classmethod - def deserialize(cls, serialized_data: dict, search_paths: list[str | Path] = None, - search_keys: list[str] = None) -> Component: + def deserialize(cls, serialized_data: dict, search_paths: list[str | Path] | None = None, + search_keys: list[str] | None = None) -> Component: """Return a `Component` from `data`. Let pydantic handle field validation and conversion. If any component data has been saved to file and the save file doesn't exist, then the loader will search for the file in the current working directory and any additional search paths provided. diff --git a/src/amisc/compression.py b/src/amisc/compression.py index 9ff4a57..16ca3a2 100644 --- a/src/amisc/compression.py +++ b/src/amisc/compression.py @@ -56,7 +56,7 @@ class Compression(PickleSerializable, ABC): """ fields: list[str] = field(default_factory=list) method: str = 'svd' - coords: np.ndarray = None # (num_pts, dim) + coords: np.ndarray | None = None # (num_pts, dim) interpolate_method: str = 'rbf' interpolate_opts: dict = field(default_factory=dict) _map_computed: bool = False @@ -323,11 +323,11 @@ class SVD(Compression): :ivar energy_tol: the energy tolerance of the SVD decomposition :ivar reconstruction_tol: the reconstruction error tolerance of the SVD decomposition """ - data_matrix: np.ndarray = None # (dof, num_samples) - projection_matrix: np.ndarray = None # (dof, rank) - rank: int = None - energy_tol: float = None - reconstruction_tol: float = None + data_matrix: np.ndarray | None = None # (dof, num_samples) + projection_matrix: np.ndarray | None = None # (dof, rank) + rank: int | None = None + energy_tol: float | None = None + reconstruction_tol: float | None = None def __post_init__(self): """Compute the SVD if the data matrix is provided.""" @@ -335,8 +335,8 @@ def __post_init__(self): self.compute_map(data_matrix, rank=self.rank, energy_tol=self.energy_tol, reconstruction_tol=self.reconstruction_tol) - def compute_map(self, data_matrix: np.ndarray | dict, rank: int = None, energy_tol: float = None, - reconstruction_tol: float = None): + def compute_map(self, data_matrix: np.ndarray | dict, rank: int | None = None, energy_tol: float | None = None, + reconstruction_tol: float | None = None): """Compute the SVD compression map from the data matrix. Recall that `dof` is the total number of degrees of freedom, equal to the number of grid points `num_pts` times the number of quantities of interest `num_qoi` at each grid point. diff --git a/src/amisc/distribution.py b/src/amisc/distribution.py index 036950e..bc44dc9 100644 --- a/src/amisc/distribution.py +++ b/src/amisc/distribution.py @@ -43,14 +43,14 @@ def __str__(self): def __repr__(self): return self.__str__() - def domain(self, dist_args: tuple = None) -> tuple: + def domain(self, dist_args: tuple | None = None) -> tuple: """Return the domain of this distribution. Defaults to `dist_args` :param dist_args: overrides `self.dist_args` """ return dist_args or self.dist_args - def nominal(self, dist_args: tuple = None) -> float: + def nominal(self, dist_args: tuple | None = None) -> float: """Return the nominal value of this distribution. Defaults to middle of domain. :param dist_args: overrides `self.dist_args` @@ -124,7 +124,7 @@ def from_string(cls, dist_string: str) -> Distribution | None: raise NotImplementedError(f'The distribution "{dist_string}" is not recognized.') @abstractmethod - def sample(self, shape: int | tuple, nominal: float | np.ndarray = None, dist_args: tuple = None) -> np.ndarray: + def sample(self, shape: int | tuple, nominal: float | np.ndarray | None = None, dist_args: tuple | None = None) -> np.ndarray: """Sample from the distribution. :param shape: shape of the samples to return @@ -135,7 +135,7 @@ def sample(self, shape: int | tuple, nominal: float | np.ndarray = None, dist_ar raise NotImplementedError @abstractmethod - def pdf(self, x: np.ndarray, dist_args: tuple = None) -> np.ndarray: + def pdf(self, x: np.ndarray, dist_args: tuple | None = None) -> np.ndarray: """Evaluate the pdf of this distribution at the `x` locations. :param x: the locations at which to evaluate the pdf diff --git a/src/amisc/interpolator.py b/src/amisc/interpolator.py index bba9abd..4e567d8 100644 --- a/src/amisc/interpolator.py +++ b/src/amisc/interpolator.py @@ -69,7 +69,7 @@ class LinearState(InterpolatorState, Base64Serializable): """ x_vars: list[str] = field(default_factory=list) y_vars: list[str] = field(default_factory=list) - regressor: Pipeline = None + regressor: Pipeline | None = None def __eq__(self, other): if isinstance(other, LinearState): @@ -92,7 +92,7 @@ class GPRState(InterpolatorState, Base64Serializable): """ x_vars: list[str] = field(default_factory=list) y_vars: list[str] = field(default_factory=list) - regressor: Pipeline = None + regressor: Pipeline | None = None def __eq__(self, other): if isinstance(other, GPRState): @@ -550,7 +550,7 @@ class Linear(Interpolator, StringSerializable): :ivar polynomial_opts: options to pass to the `PolynomialFeatures` constructor (e.g. 'degree', 'include_bias'). """ regressor: str = 'Ridge' - scaler: str = None + scaler: str | None = None regressor_opts: dict = field(default_factory=dict) scaler_opts: dict = field(default_factory=dict) polynomial_opts: dict = field(default_factory=lambda: {'degree': 1, 'include_bias': False}) @@ -654,7 +654,7 @@ class GPR(Interpolator, StringSerializable): :ivar regressor_opts: options to pass to the `GaussianProcessRegressor` constructor (see [scikit-learn](https://scikit-learn.org/stable/) documentation). """ - scaler: str = None + scaler: str | None = None kernel: str | list = 'RBF' scaler_opts: dict = field(default_factory=dict) kernel_opts: dict = field(default_factory=dict) diff --git a/src/amisc/system.py b/src/amisc/system.py index 2fca62f..a6cfb25 100644 --- a/src/amisc/system.py +++ b/src/amisc/system.py @@ -66,7 +66,7 @@ class TrainHistory(UserList, Serializable): """Stores the training history of a system surrogate as a list of `TrainIteration` objects.""" - def __init__(self, data: list = None): + def __init__(self, data: list | None = None): data = data or [] super().__init__(self._validate_data(data)) @@ -217,7 +217,7 @@ def f2(y): name: Annotated[str, Field(default_factory=lambda: "System_" + "".join(random.choices(string.digits, k=3)))] components: Callable | Component | list[Callable | Component] train_history: list[dict] | TrainHistory = TrainHistory() - amisc_version: str = None + amisc_version: str | None = None _root_dir: Optional[str] _logger: Optional[logging.Logger] = None @@ -429,7 +429,7 @@ def root_dir(self, root_dir: str | Path): self._root_dir = None self.set_logger(log_file=None) - def set_logger(self, log_file: str | Path | bool = None, stdout: bool = None, logger: logging.Logger = None, + def set_logger(self, log_file: str | Path | bool | None = None, stdout: bool | None = None, logger: logging.Logger | None = None, level: int = logging.INFO): """Set a new `logging.Logger` object. @@ -471,9 +471,9 @@ def sample_inputs(self, size: tuple | int, component: str = 'System', normalize: bool = True, use_pdf: bool | str | list[str] = False, - include: str | list[str] = None, - exclude: str | list[str] = None, - nominal: dict[str, float] = None) -> Dataset: + include: str | list[str] | None = None, + exclude: str | list[str] | None = None, + nominal: dict[str, float] | None= None) -> Dataset: """Return samples of the inputs according to provided options. Will return samples in the normalized/compressed space of the surrogate by default. See [`to_model_dataset`][amisc.utils.to_model_dataset] to convert the samples to be usable by the true model directly. @@ -611,19 +611,19 @@ def add_output(self): raise NotImplementedError @_save_on_error - def fit(self, targets: list = None, + def fit(self, targets: list | None = None, num_refine: int = 100, max_iter: int = 20, max_tol: float = 1e-3, runtime_hr: float = 1., estimate_bounds: bool = False, update_bounds: bool = True, - test_set: tuple | str | Path = None, - start_test_check: int = None, + test_set: tuple | str | Path | None = None, + start_test_check: int | None = None, save_interval: int = 0, plot_interval: int = 1, cache_interval: int = 0, - executor: Executor = None, + executor: Executor | None = None, weight_fcns: dict[str, callable] | Literal['pdf'] | None = 'pdf'): """Train the system surrogate adaptively by iterative refinement until an end condition is met. @@ -828,8 +828,8 @@ def test_set_performance(self, xtest: Dataset, ytest: Dataset, index_set='test') return perf - def refine(self, targets: list = None, num_refine: int = 100, update_bounds: bool = True, executor: Executor = None, - weight_fcns: dict[str, callable] | Literal['pdf'] | None = 'pdf') -> TrainIteration: + def refine(self, targets: list | None = None, num_refine: int = 100, update_bounds: bool = True, executor: Executor | None = None, + weight_fcns: dict[str, Callable] | Literal['pdf'] | None = 'pdf') -> TrainIteration: """Perform a single adaptive refinement step on the system surrogate. :param targets: list of system output variables to focus refinement on, use all outputs if not specified @@ -951,16 +951,16 @@ def predict(self, x: dict | Dataset, max_fpi_iter: int = 100, anderson_mem: int = 10, fpi_tol: float = 1e-10, - use_model: str | tuple | dict = None, - model_dir: str | Path = None, + use_model: str | tuple | dict | None = None, + model_dir: str | Path | None = None, verbose: bool = False, - index_set: dict[str: IndexSet | Literal['train', 'test']] = 'test', - misc_coeff: dict[str: MiscTree] = None, + index_set: dict[str, IndexSet | Literal['train', 'test']] | str = 'test', + misc_coeff: dict[str, MiscTree] | None = None, normalized_inputs: bool = True, - incremental: dict[str, bool] = False, - targets: list[str] = None, - executor: Executor = None, - var_shape: dict[str, tuple] = None) -> Dataset: + incremental: dict[str, bool] | bool = False, + targets: list[str] | None = None, + executor: Executor | None= None, + var_shape: dict[str, tuple] | None = None) -> Dataset: """Evaluate the system surrogate at inputs `x`. Return `y = system(x)`. !!! Warning "Computing the true model with feedback loops" @@ -1369,7 +1369,7 @@ def _restore_unpickleable(self, buffer: dict): """Restore the unpickleable attributes from `buffer` after unpickling.""" self.set_logger(log_file=buffer.get('log_file', None), stdout=buffer.get('log_stdout', None)) - def _get_test_set(self, test_set: str | Path | tuple = None) -> tuple: + def _get_test_set(self, test_set: str | Path | tuple | None = None) -> tuple: """Try to load a test set from the root directory if it exists.""" if isinstance(test_set, tuple): return test_set # (xtest, ytest) @@ -1388,7 +1388,7 @@ def _get_test_set(self, test_set: str | Path | tuple = None) -> tuple: return ret - def _save_test_set(self, test_set: tuple = None): + def _save_test_set(self, test_set: tuple | None = None): """Save the test set to the root directory if possible.""" if self.root_dir is not None and test_set is not None: test_file = self.root_dir / 'test_set.pkl' @@ -1396,7 +1396,7 @@ def _save_test_set(self, test_set: tuple = None): with open(test_file, 'wb') as fd: pickle.dump({'test_set': test_set}, fd) - def save_to_file(self, filename: str, save_dir: str | Path = None, dumper=None): + def save_to_file(self, filename: str, save_dir: str | Path | None = None, dumper=None): """Save surrogate to file. Defaults to `root/surrogates/filename.yml` with the default yaml encoder. :param filename: the name of the save file @@ -1411,7 +1411,7 @@ def save_to_file(self, filename: str, save_dir: str | Path = None, dumper=None): encoder.dump(self, Path(save_dir) / filename) @staticmethod - def load_from_file(filename: str | Path, root_dir: str | Path = None, loader=None): + def load_from_file(filename: str | Path, root_dir: str | Path | None = None, loader=None): """Load surrogate from file. Defaults to yaml loading. Tries to infer `amisc` directory structure. :param filename: the name of the load file @@ -1442,16 +1442,16 @@ def clear(self): comp.clear() self.train_history.clear() - def plot_slice(self, inputs: list[str] = None, - outputs: list[str] = None, + def plot_slice(self, inputs: list[str] | None = None, + outputs: list[str] | None = None, num_steps: int = 20, show_surr: bool = True, - show_model: str | tuple | list = None, - save_dir: str | Path = None, - executor: Executor = None, - nominal: dict[str: float] = None, + show_model: str | tuple | list | None = None, + save_dir: str | Path | None = None, + executor: Executor | None = None, + nominal: dict[str, float] | None = None, random_walk: bool = False, - from_file: str | Path = None, + from_file: str | Path | None = None, subplot_size_in: float = 3.): """Helper function to plot 1d slices of the surrogate and/or model outputs over the inputs. A single "slice" works by smoothly stepping from the lower bound of an input to its upper bound, while holding all other diff --git a/src/amisc/training.py b/src/amisc/training.py index ddb1fc5..099e51e 100644 --- a/src/amisc/training.py +++ b/src/amisc/training.py @@ -12,7 +12,7 @@ import itertools from abc import ABC, abstractmethod from dataclasses import dataclass, field -from typing import Any, ClassVar +from typing import Any, ClassVar, Callable import numpy as np from numpy.typing import ArrayLike @@ -37,7 +37,7 @@ class TrainingData(Serializable, ABC): """ @abstractmethod - def get(self, alpha: MultiIndex, beta: MultiIndex, y_vars: list[str] = None, + def get(self, alpha: MultiIndex, beta: MultiIndex, y_vars: list[str] | None = None, skip_nan: bool = False) -> tuple[Dataset, Dataset]: """Return the training data for a given multi-index pair. @@ -82,7 +82,7 @@ def impute_missing_data(self, alpha: MultiIndex, beta: MultiIndex): @abstractmethod def refine(self, alpha: MultiIndex, beta: MultiIndex, input_domains: dict[str, tuple], - weight_fcns: dict[str, callable] = None) -> tuple[list[Any], Dataset]: + weight_fcns: dict[str, Callable] | None = None) -> tuple[list[Any], Dataset]: """Return new design/training points for a given multi-index pair and their coordinates/locations in the `TrainingData` storage structure. @@ -178,7 +178,7 @@ def clear(self): self.error_map.clear() self.latent_size.clear() - def get_by_coord(self, alpha: MultiIndex, coords: list, y_vars: list = None, skip_nan: bool = False): + def get_by_coord(self, alpha: MultiIndex, coords: list, y_vars: list | None = None, skip_nan: bool = False): """Get training data from the sparse grid for a given `alpha` and list of grid coordinates. Try to replace `nan` values with imputed values. Skip any data points with remaining `nan` values if `skip_nan=True`. @@ -196,7 +196,7 @@ def get_by_coord(self, alpha: MultiIndex, coords: list, y_vars: list = None, ski first_yi = next(iter(self.yi_map[alpha].values())) if y_vars is None: - y_vars = first_yi.keys() + y_vars = list(first_yi.keys()) for var in y_vars: yi = np.atleast_1d(first_yi[var]) @@ -227,7 +227,7 @@ def get_by_coord(self, alpha: MultiIndex, coords: list, y_vars: list = None, ski return xi_dict, yi_dict # Both with elements of shape (N, ...) for N grid points - def get(self, alpha: MultiIndex, beta: MultiIndex, y_vars: list[str] = None, skip_nan: bool = False): + def get(self, alpha: MultiIndex, beta: MultiIndex, y_vars: list[str] | None = None, skip_nan: bool = False): """Get the training data from the sparse grid for a given `alpha` and `beta` pair.""" return self.get_by_coord(alpha, list(self._expand_grid_coords(beta)), y_vars=y_vars, skip_nan=skip_nan) @@ -297,7 +297,7 @@ def impute_missing_data(self, alpha: MultiIndex, beta: MultiIndex): self.yi_nan_map[alpha][coord] = copy.deepcopy(y_impute) - def refine(self, alpha: MultiIndex, beta: MultiIndex, input_domains: dict, weight_fcns: dict = None): + def refine(self, alpha: MultiIndex, beta: MultiIndex, input_domains: dict, weight_fcns: dict | None = None): """Refine the sparse grid for a given `alpha` and `beta` pair and given collocation rules. Return any new grid points that do not have model evaluations saved yet. @@ -445,8 +445,8 @@ def is_one_level_refinement(beta_old: tuple, beta_new: tuple) -> bool: ind = np.nonzero(level_diff)[0] return ind.shape[0] == 1 and level_diff[ind] == 1 - def beta_to_knots(self, beta: MultiIndex, knots_per_level: int = None, latent_size: dict = None, - expand_latent_method: str = None) -> tuple: + def beta_to_knots(self, beta: MultiIndex, knots_per_level: int | None = None, latent_size: dict | None = None, + expand_latent_method: str | None = None) -> tuple: """Convert a `beta` multi-index to the number of knots per dimension in the sparse grid. :param beta: refinement level indices @@ -484,8 +484,8 @@ def beta_to_knots(self, beta: MultiIndex, knots_per_level: int = None, latent_si return tuple(grid_size) @staticmethod - def collocation_1d(N: int, z_bds: tuple, z_pts: np.ndarray = None, - wt_fcn: callable = None, method='leja', opt_args=None) -> np.ndarray: + def collocation_1d(N: int, z_bds: tuple, z_pts: np.ndarray | None = None, + wt_fcn: Callable | None = None, method='leja', opt_args=None) -> np.ndarray: """Find the next `N` points in the 1d sequence of `z_pts` using the provided collocation method. :param N: number of new points to add to the sequence @@ -500,19 +500,22 @@ def collocation_1d(N: int, z_bds: tuple, z_pts: np.ndarray = None, if wt_fcn is None: wt_fcn = lambda z: 1 if z_pts is None: - z_pts = (z_bds[1] + z_bds[0]) / 2 + z_points = (z_bds[1] + z_bds[0]) / 2 N = N - 1 - z_pts = np.atleast_1d(z_pts) + else: + z_points = z_pts + + z_points = np.atleast_1d(z_points) match method: case 'leja': # Construct Leja sequence by maximizing the Leja objective sequentially for i in range(N): - obj_fun = lambda z: -wt_fcn(np.array(z)) * np.prod(np.abs(z - z_pts)) + obj_fun = lambda z: -wt_fcn(np.array(z)) * np.prod(np.abs(z - z_points)) res = direct(obj_fun, [z_bds], **opt_args) # Use global DIRECT optimization over 1d domain z_star = res.x - z_pts = np.concatenate((z_pts, z_star)) + z_points = np.concatenate((z_points, z_star)) case other: raise NotImplementedError(f"Unknown collocation method: {other}") - return z_pts + return z_points diff --git a/src/amisc/transform.py b/src/amisc/transform.py index 9947870..d963bdc 100644 --- a/src/amisc/transform.py +++ b/src/amisc/transform.py @@ -118,7 +118,7 @@ def from_string(cls, transform_spec: str | list[str]) -> list[Transform] | None: return transforms - def transform(self, x: ArrayLike, inverse: bool = False, transform_args: tuple = None) -> ArrayLike: + def transform(self, x: ArrayLike, inverse: bool = False, transform_args: tuple | None = None) -> ArrayLike: """Transform the given values `x`. This wrapper function handles the input type and tries to return the transformed values in the same type. diff --git a/src/amisc/utils.py b/src/amisc/utils.py index a837151..24784bc 100644 --- a/src/amisc/utils.py +++ b/src/amisc/utils.py @@ -333,7 +333,7 @@ def search_for_file(filename: str | Path, search_paths=None): return filename -def format_inputs(inputs: Dataset, var_shape: dict = None) -> tuple[Dataset, tuple[int, ...]]: +def format_inputs(inputs: Dataset, var_shape: dict | None = None) -> tuple[Dataset, tuple[int, ...]]: """Broadcast and reshape all inputs to the same shape. Loop shape is inferred from broadcasting the leading dims of all input arrays. Input arrays are broadcast to this shape and then flattened. @@ -537,7 +537,7 @@ def relative_error(pred, targ, axis=None, skip_nan=False): return np.nan_to_num(err, nan=np.nan, posinf=np.nan, neginf=np.nan) -def get_logger(name: str, stdout: bool = True, log_file: str | Path = None, +def get_logger(name: str, stdout: bool = True, log_file: str | Path | None = None, level: int = logging.INFO) -> logging.Logger: """Return a file/stdout logger with the given name. diff --git a/src/amisc/variable.py b/src/amisc/variable.py index c650856..7d7b5a8 100644 --- a/src/amisc/variable.py +++ b/src/amisc/variable.py @@ -344,7 +344,7 @@ def pdf(self, x: np.ndarray) -> np.ndarray: else: return np.ones(x.shape) # No pdf if no dist is specified - def sample(self, shape: tuple | int, nominal: float | np.ndarray = None) -> np.ndarray: + def sample(self, shape: tuple | int, nominal: float | np.ndarray | None = None) -> np.ndarray: """Draw samples from this `Variable's` distribution. Just returns the nominal value of the given shape if this `Variable` has no distribution. @@ -430,7 +430,7 @@ def denormalize(self, values): """Alias for `normalize(denorm=True)`. See `normalize` for more details.""" return self.normalize(values, denorm=True) - def compress(self, values: CompressionData, coords: np.ndarray = None, + def compress(self, values: CompressionData, coords: np.ndarray | None = None, reconstruct: bool = False) -> CompressionData: """Compress or reconstruct field quantity values using this `Variable's` compression info. @@ -514,7 +514,7 @@ def serialize(self, save_path: str | Path = '.') -> dict: return d @classmethod - def deserialize(cls, data: dict, search_paths: list[str | Path] = None) -> Variable: + def deserialize(cls, data: dict, search_paths: list[str | Path] | None = None) -> Variable: """Convert a `dict` to a `Variable` object. Let `pydantic` handle validation and conversion of fields. :param data: the `dict` to convert to a `Variable` @@ -562,7 +562,7 @@ class VariableList(OrderedDict, Serializable): """ yaml_tag = '!VariableList' - def __init__(self, data: list[Variable] | Variable | OrderedDict | dict = None, **kwargs): + def __init__(self, data: list[Variable] | Variable | OrderedDict | dict | None = None, **kwargs): """Initialize a collection of `Variable` objects.""" super().__init__() self.update(data, **kwargs) @@ -634,7 +634,7 @@ def _get_pdf(var, norm): pdf_fcns[var.name] = _get_pdf(var, norm) return pdf_fcns - def update(self, data: list[Variable | str] | str | Variable | OrderedDict | dict = None, **kwargs): + def update(self, data: list[Variable | str] | str | Variable | OrderedDict | dict | None = None, **kwargs): """Update from a list or dict of `Variable` objects, or from `key=value` pairs.""" if data: if isinstance(data, OrderedDict | dict): From f7d3fc13d960e2fc34e9e98087f7b75c1f98a125 Mon Sep 17 00:00:00 2001 From: Thomas Marks Date: Tue, 3 Mar 2026 13:55:40 -0500 Subject: [PATCH 05/29] some typing fixes in Variable --- src/amisc/system.py | 2 +- src/amisc/variable.py | 31 +++++++++++++++++++++---------- 2 files changed, 22 insertions(+), 11 deletions(-) diff --git a/src/amisc/system.py b/src/amisc/system.py index a6cfb25..482b848 100644 --- a/src/amisc/system.py +++ b/src/amisc/system.py @@ -624,7 +624,7 @@ def fit(self, targets: list | None = None, plot_interval: int = 1, cache_interval: int = 0, executor: Executor | None = None, - weight_fcns: dict[str, callable] | Literal['pdf'] | None = 'pdf'): + weight_fcns: dict[str, Callable] | Literal['pdf'] | None = 'pdf'): """Train the system surrogate adaptively by iterative refinement until an end condition is met. :param targets: list of system output variables to focus refinement on, use all outputs if not specified diff --git a/src/amisc/variable.py b/src/amisc/variable.py index 7d7b5a8..dd11dab 100644 --- a/src/amisc/variable.py +++ b/src/amisc/variable.py @@ -18,7 +18,7 @@ import string from collections import OrderedDict from pathlib import Path -from typing import ClassVar, Optional, Union +from typing import ClassVar, Optional, Union, overload import numpy as np import yaml @@ -340,6 +340,7 @@ def pdf(self, x: np.ndarray) -> np.ndarray: :returns: the PDF evaluations at `x` """ if dist := self.distribution: + assert isinstance(dist, Distribution) return dist.pdf(x) else: return np.ones(x.shape) # No pdf if no dist is specified @@ -354,21 +355,31 @@ def sample(self, shape: tuple | int, nominal: float | np.ndarray | None = None) """ if isinstance(shape, int): shape = (shape, ) - if nominal is None: - nominal = self.get_nominal() + + nominal_val = self.get_nominal() if nominal is None else nominal if dist := self.distribution: - return dist.sample(shape, nominal) + assert isinstance(dist, Distribution) + return dist.sample(shape, np.array(nominal_val)) else: - # Variable's with no distribution - if nominal is None: + # Variables with no distribution + if nominal_val is None: raise ValueError(f'Cannot sample "{self.name}" with no dist or nominal value specified.') - elif isinstance(nominal, list | np.ndarray): - return np.ones(shape + (len(nominal),)) * np.atleast_1d(nominal) # For field quantities + elif isinstance(nominal_val, list | np.ndarray): + return np.ones(shape + (len(nominal_val),)) * np.atleast_1d(nominal_val) # For field quantities else: - return np.ones(shape) * nominal + return np.ones(shape) * nominal_val + + @overload + def normalize(self, values: None, denorm: bool = False) -> None: ... + + @overload + def normalize(self, values: float, denorm: bool = False) -> float: ... + + @overload + def normalize(self, values: ArrayLike, denorm: bool = False) -> ArrayLike: ... - def normalize(self, values: ArrayLike, denorm: bool = False) -> ArrayLike | None: + def normalize(self, values: float | ArrayLike | None, denorm: bool = False) -> float | ArrayLike | None: """Normalize `values` based on this `Variable's` `norm` method(s). See `Transform` for available norm methods. !!! Note From 0a82c7d12df3685a5d881ca930f867b7b698c36c Mon Sep 17 00:00:00 2001 From: Thomas Marks Date: Tue, 3 Mar 2026 13:57:43 -0500 Subject: [PATCH 06/29] fix callable type hint in component --- src/amisc/component.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/src/amisc/component.py b/src/amisc/component.py index f7aa7e3..98d03fc 100644 --- a/src/amisc/component.py +++ b/src/amisc/component.py @@ -388,7 +388,7 @@ class Component(BaseModel, Serializable): # Configuration serializers: Optional[ComponentSerializers] = None name: Optional[str] = None - model: str | Callable[[dict | Dataset, ...], dict | Dataset] + model: str | Callable[..., dict | Dataset] model_kwargs: str | dict | ModelKwargs = {} inputs: _VariableLike outputs: _VariableLike From 7c88757c926c06c012288602344e641c90922311 Mon Sep 17 00:00:00 2001 From: Thomas Marks Date: Tue, 3 Mar 2026 14:05:32 -0500 Subject: [PATCH 07/29] implement overridable timestamp prefix --- src/amisc/system.py | 43 +++++++++++++++++++++++++++---------------- 1 file changed, 27 insertions(+), 16 deletions(-) diff --git a/src/amisc/system.py b/src/amisc/system.py index 482b848..1fb7281 100644 --- a/src/amisc/system.py +++ b/src/amisc/system.py @@ -60,8 +60,9 @@ ) from amisc.variable import VariableList -__all__ = ['TrainHistory', 'System'] +PathLike = str | Path +__all__ = ['TrainHistory', 'System'] class TrainHistory(UserList, Serializable): """Stores the training history of a system surrogate as a list of `TrainIteration` objects.""" @@ -218,6 +219,8 @@ def f2(y): components: Callable | Component | list[Callable | Component] train_history: list[dict] | TrainHistory = TrainHistory() amisc_version: str | None = None + timestamp_prefix: str = "amisc_" + create_subdirs: bool = True _root_dir: Optional[str] _logger: Optional[logging.Logger] = None @@ -386,7 +389,7 @@ def root_dir(self): return Path(self._root_dir) if self._root_dir is not None else None @root_dir.setter - def root_dir(self, root_dir: str | Path): + def root_dir(self, root_dir: PathLike | None): """Set the root directory for all build products. If `root_dir` is `None`, then no products will be saved. Otherwise, log files, model outputs, surrogate files, etc. will be saved under this directory. @@ -397,16 +400,23 @@ def root_dir(self, root_dir: str | Path): :param root_dir: the root directory for all build products """ + # TODO: don't create dirs until we do something! + if root_dir is not None: - parts = Path(root_dir).resolve().parts - if parts[-1].startswith('amisc_'): - self._root_dir = Path(root_dir).resolve().as_posix() + root_dir = Path(root_dir).resolve() + + parts = root_dir.parts + if parts[-1].startswith(self.timestamp_prefix) or not self.create_subdirs: + self._root_dir = root_dir.resolve() + assert self.root_dir is not None if not self.root_dir.is_dir(): - os.mkdir(self.root_dir) - else: - root_dir = Path(root_dir) / ('amisc_' + self.timestamp()) + os.makedirs(self.root_dir, exist_ok=True) + elif self.create_subdirs: + root_dir = root_dir / (f"{self.timestamp_prefix}_{self.timestamp()}") os.mkdir(root_dir) - self._root_dir = Path(root_dir).resolve().as_posix() + self._root_dir = root_dir + + assert self.root_dir is not None log_file = None if not (pth := self.root_dir / 'surrogates').is_dir(): @@ -422,7 +432,7 @@ def root_dir(self, root_dir: str | Path): log_file = (self.root_dir / f).resolve().as_posix() break if log_file is None: - log_file = (self.root_dir / f'amisc_{self.timestamp()}.log').resolve().as_posix() + log_file = (self.root_dir / f'{self.timestamp_prefix}_{self.timestamp()}.log').resolve().as_posix() self.set_logger(log_file=log_file) else: @@ -1409,9 +1419,9 @@ def save_to_file(self, filename: str, save_dir: str | Path | None = None, dumper if Path(save_dir) == self.root_dir: save_dir = self.root_dir / 'surrogates' encoder.dump(self, Path(save_dir) / filename) - + @staticmethod - def load_from_file(filename: str | Path, root_dir: str | Path | None = None, loader=None): + def load_from_file(filename: PathLike, root_dir: PathLike | None= None, loader=None, timestamp_prefix="amisc_"): """Load surrogate from file. Defaults to yaml loading. Tries to infer `amisc` directory structure. :param filename: the name of the load file @@ -1421,21 +1431,22 @@ def load_from_file(filename: str | Path, root_dir: str | Path | None = None, loa from amisc import YamlLoader encoder = loader or YamlLoader system = encoder.load(filename) + system.timestamp_prefix=timestamp_prefix root_dir = root_dir or system.root_dir # Try to infer amisc_root/surrogates/iter/filename structure if root_dir is None: parts = Path(filename).resolve().parts - if len(parts) > 1 and parts[-2].startswith('amisc_'): + if len(parts) > 1 and parts[-2].startswith(timestamp_prefix): root_dir = Path(filename).resolve().parent - elif len(parts) > 2 and parts[-3].startswith('amisc_'): + elif len(parts) > 2 and parts[-3].startswith(timestamp_prefix): root_dir = Path(filename).resolve().parent.parent - elif len(parts) > 3 and parts[-4].startswith('amisc_'): + elif len(parts) > 3 and parts[-4].startswith(timestamp_prefix): root_dir = Path(filename).resolve().parent.parent.parent system.root_dir = root_dir return system - + def clear(self): """Clear all surrogate model data and reset the system.""" for comp in self.components: From ed3b76ee1f0856ce795b78f103d6510a18f6d7d4 Mon Sep 17 00:00:00 2001 From: Thomas Marks Date: Wed, 4 Mar 2026 09:41:20 -0500 Subject: [PATCH 08/29] Fix linting --- src/amisc/component.py | 19 ++++++++++++++----- src/amisc/distribution.py | 6 +++++- src/amisc/system.py | 11 ++++++++--- src/amisc/training.py | 2 +- 4 files changed, 28 insertions(+), 10 deletions(-) diff --git a/src/amisc/component.py b/src/amisc/component.py index 98d03fc..e9d4d9a 100644 --- a/src/amisc/component.py +++ b/src/amisc/component.py @@ -1038,7 +1038,7 @@ def call_model(self, inputs: dict | Dataset, def predict(self, inputs: dict | Dataset, use_model: Literal['best', 'worst'] | tuple | None = None, - model_dir: str | Pat | Noneh = None, + model_dir: str | Path | None = None, index_set: Literal['train', 'test'] | IndexSet = 'test', misc_coeff: MiscTree | None = None, incremental: bool = False, @@ -1165,8 +1165,13 @@ def update_misc_coeff(self, new_indices: IndexSet, index_set: Literal['test', 't misc_coeff[old_alpha, old_beta] = 0 misc_coeff[old_alpha, old_beta] += (-1) ** int(np.sum(np.abs(diff))) - def activate_index(self, alpha: MultiIndex, beta: MultiIndex, model_dir: str | Path | None = None, - executor: Executor | None = None, weight_fcns: dict[str, Callable] | Literal['pdf'] | None = 'pdf'): + def activate_index(self, + alpha: MultiIndex, + beta: MultiIndex, + model_dir: str | Path | None = None, + executor: Executor | None = None, + weight_fcns: dict[str, Callable] | Literal['pdf'] | None = 'pdf' + ): """Add a multi-index to the active set and all neighbors to the candidate set. !!! Warning @@ -1385,8 +1390,12 @@ def model_kwarg_requested(self, kwarg_name: str) -> bool: return True return False - def set_logger(self, log_file: str | Path | None = None, stdout: bool | None = None, logger: logging.Logger | None = None, - level: int = logging.INFO): + def set_logger(self, + log_file: str | Path | None = None, + stdout: bool | None = None, + logger: logging.Logger | None = None, + level: int = logging.INFO + ): """Set a new `logging.Logger` object. :param log_file: log to file (if provided) diff --git a/src/amisc/distribution.py b/src/amisc/distribution.py index bc44dc9..c5875cb 100644 --- a/src/amisc/distribution.py +++ b/src/amisc/distribution.py @@ -124,7 +124,11 @@ def from_string(cls, dist_string: str) -> Distribution | None: raise NotImplementedError(f'The distribution "{dist_string}" is not recognized.') @abstractmethod - def sample(self, shape: int | tuple, nominal: float | np.ndarray | None = None, dist_args: tuple | None = None) -> np.ndarray: + def sample(self, + shape: int | tuple, + nominal: float | np.ndarray | None = None, + dist_args: tuple | None = None + ) -> np.ndarray: """Sample from the distribution. :param shape: shape of the samples to return diff --git a/src/amisc/system.py b/src/amisc/system.py index 1fb7281..4f5f5b7 100644 --- a/src/amisc/system.py +++ b/src/amisc/system.py @@ -439,8 +439,12 @@ def root_dir(self, root_dir: PathLike | None): self._root_dir = None self.set_logger(log_file=None) - def set_logger(self, log_file: str | Path | bool | None = None, stdout: bool | None = None, logger: logging.Logger | None = None, - level: int = logging.INFO): + def set_logger(self, + log_file: str | Path | bool | None = None, + stdout: bool | None = None, + logger: logging.Logger | None = None, + level: int = logging.INFO + ): """Set a new `logging.Logger` object. :param log_file: log to this file if str or Path (defaults to whatever is currently set or empty); @@ -838,7 +842,8 @@ def test_set_performance(self, xtest: Dataset, ytest: Dataset, index_set='test') return perf - def refine(self, targets: list | None = None, num_refine: int = 100, update_bounds: bool = True, executor: Executor | None = None, + def refine(self, targets: list | None = None, num_refine: int = 100, + update_bounds: bool = True, executor: Executor | None = None, weight_fcns: dict[str, Callable] | Literal['pdf'] | None = 'pdf') -> TrainIteration: """Perform a single adaptive refinement step on the system surrogate. diff --git a/src/amisc/training.py b/src/amisc/training.py index 099e51e..aee2634 100644 --- a/src/amisc/training.py +++ b/src/amisc/training.py @@ -12,7 +12,7 @@ import itertools from abc import ABC, abstractmethod from dataclasses import dataclass, field -from typing import Any, ClassVar, Callable +from typing import Any, Callable, ClassVar import numpy as np from numpy.typing import ArrayLike From 953cdaa94cdca6c2c7094db9838ab737a50e0c4e Mon Sep 17 00:00:00 2001 From: Thomas Marks Date: Wed, 4 Mar 2026 10:03:16 -0500 Subject: [PATCH 09/29] typing: log distribution float args --- src/amisc/distribution.py | 8 ++++---- 1 file changed, 4 insertions(+), 4 deletions(-) diff --git a/src/amisc/distribution.py b/src/amisc/distribution.py index c5875cb..a9319c7 100644 --- a/src/amisc/distribution.py +++ b/src/amisc/distribution.py @@ -177,8 +177,8 @@ class LogUniform(Distribution): x = LogUniform((1e-3, 1e-1)) # log10(x) ~ U(-3, -1) ``` """ - def __init__(self, dist_args: tuple, base=10): - self.base = base + def __init__(self, dist_args: tuple, base: float | int = 10): + self.base = float(base) super().__init__(dist_args) def __str__(self): @@ -229,8 +229,8 @@ class LogNormal(Distribution): x = LogNormal((-2, 1)) # log10(x) ~ N(-2, 1) ``` """ - def __init__(self, dist_args: tuple, base=10): - self.base = base + def __init__(self, dist_args: tuple, base: float | int = 10): + self.base = float(base) super().__init__(dist_args) def __str__(self): From 14d140037948ccb8ae0b7586db3b12cf0b65d9ae Mon Sep 17 00:00:00 2001 From: Thomas Marks Date: Wed, 4 Mar 2026 10:09:14 -0500 Subject: [PATCH 10/29] typing: fix remaining pylance issues by swapping numpy functions to those accepting shape tuples and adding None option to domain and nominal --- src/amisc/distribution.py | 23 +++++++++++++---------- 1 file changed, 13 insertions(+), 10 deletions(-) diff --git a/src/amisc/distribution.py b/src/amisc/distribution.py index a9319c7..2e6e5db 100644 --- a/src/amisc/distribution.py +++ b/src/amisc/distribution.py @@ -43,20 +43,23 @@ def __str__(self): def __repr__(self): return self.__str__() - def domain(self, dist_args: tuple | None = None) -> tuple: + def domain(self, dist_args: tuple | None = None) -> tuple | None: """Return the domain of this distribution. Defaults to `dist_args` :param dist_args: overrides `self.dist_args` """ return dist_args or self.dist_args - def nominal(self, dist_args: tuple | None = None) -> float: + def nominal(self, dist_args: tuple | None = None) -> float | None: """Return the nominal value of this distribution. Defaults to middle of domain. :param dist_args: overrides `self.dist_args` """ - lb, ub = self.domain(dist_args=dist_args) - return (lb + ub) / 2 + if (domain := self.domain(dist_args=dist_args)) is not None: + lb, ub = domain + return (lb + ub) / 2 + else: + return None @classmethod def from_string(cls, dist_string: str) -> Distribution | None: @@ -157,7 +160,7 @@ def __str__(self): def sample(self, shape, nominal=None, dist_args=None): lb, ub = dist_args or self.dist_args - return np.random.rand(*shape) * (ub - lb) + lb + return np.random.random_sample(shape) * (ub - lb) + lb def pdf(self, x, dist_args=None): x = np.atleast_1d(x) @@ -187,7 +190,7 @@ def __str__(self): def sample(self, shape, nominal=None, dist_args=None): lb, ub = dist_args or self.dist_args c = 1 / np.log(self.base) - return self.base ** (np.random.rand(*shape) * c * (np.log(ub) - np.log(lb)) + c * np.log(lb)) + return self.base ** (np.random.random_sample(shape) * c * (np.log(ub) - np.log(lb)) + c * np.log(lb)) def pdf(self, x, dist_args=None): x = np.atleast_1d(x) @@ -213,7 +216,7 @@ def domain(self, dist_args=None): def sample(self, shape, nominal=None, dist_args=None): mu, std = dist_args or self.dist_args - return np.random.randn(*shape) * std + mu + return np.random.standard_normal(shape) * std + mu def pdf(self, x, dist_args=None): mu, std = dist_args or self.dist_args @@ -243,7 +246,7 @@ def domain(self, dist_args=None): def sample(self, shape, nominal=None, dist_args=None): mu, std = dist_args or self.dist_args - return self.base ** (np.random.randn(*shape) * std + mu) + return self.base ** (np.random.standard_normal(shape) * std + mu) def pdf(self, x, dist_args=None): mu, std = dist_args or self.dist_args @@ -270,7 +273,7 @@ def sample(self, shape, nominal=None, dist_args=None): raise ValueError('Cannot sample relative distribution when no nominal value is provided.') dist_args = dist_args or self.dist_args tol = abs((dist_args[0] / 100) * nominal) - return np.random.rand(*shape) * 2 * tol - tol + nominal + return np.random.random_sample(shape) * 2 * tol - tol + nominal def pdf(self, x, dist_args=None): return np.ones(x.shape) @@ -295,7 +298,7 @@ def sample(self, shape, nominal=None, dist_args=None): raise ValueError('Cannot sample tolerance distribution when no nominal value is provided.') dist_args = dist_args or self.dist_args tol = abs(dist_args[0]) - return np.random.rand(*shape) * 2 * tol - tol + nominal + return np.random.random_sample(shape) * 2 * tol - tol + nominal def pdf(self, x, dist_args=None): return np.ones(np.atleast_1d(x).shape) From 55faaadee60933b144915c8753cf9db60d5ef9b6 Mon Sep 17 00:00:00 2001 From: Thomas Marks Date: Wed, 4 Mar 2026 10:37:15 -0500 Subject: [PATCH 11/29] typing: deserialize methods return Self and use generic Serializable type over _builtins --- src/amisc/serialize.py | 38 +++++++++++++++++++------------------- src/amisc/variable.py | 28 ++++++++++++++-------------- 2 files changed, 33 insertions(+), 33 deletions(-) diff --git a/src/amisc/serialize.py b/src/amisc/serialize.py index d49c2b9..f952e21 100644 --- a/src/amisc/serialize.py +++ b/src/amisc/serialize.py @@ -19,7 +19,7 @@ from abc import ABC, abstractmethod from dataclasses import dataclass from pathlib import Path -from typing import Any +from typing import Any, Generic, Self, TypeVar, cast import yaml @@ -28,20 +28,20 @@ __all__ = ['Serializable', 'Base64Serializable', 'StringSerializable', 'PickleSerializable', 'YamlSerializable'] _builtin = str | dict | list | int | float | tuple | bool # Generic type for common built-in Python objects +T = TypeVar('T', bound=_builtin) - -class Serializable(ABC): +class Serializable(ABC, Generic[T]): """Mixin interface for serializing and deserializing objects.""" @abstractmethod - def serialize(self) -> _builtin: + def serialize(self) -> T: """Serialize to a builtin Python object.""" raise NotImplementedError @classmethod @abstractmethod - def deserialize(cls, serialized_data: _builtin) -> Serializable: - """Construct a `Serializable` object from serialized data. + def deserialize(cls, serialized_data: T) -> Serializable[T]: + """Construct a `Serializable` object from data. !!! Note "Passing arguments to deserialize" Subclasses should generally not take arguments for deserialization. The serialized object should contain @@ -51,24 +51,24 @@ def deserialize(cls, serialized_data: _builtin) -> Serializable: raise NotImplementedError -class Base64Serializable(Serializable): +class Base64Serializable(Serializable[str]): """Mixin class for serializing objects using base64 encoding.""" def serialize(self) -> str: return base64.b64encode(pickle.dumps(self)).decode('utf-8') @classmethod - def deserialize(cls, serialized_data: str) -> Base64Serializable: - return pickle.loads(base64.b64decode(serialized_data)) + def deserialize(cls, serialized_data: str) -> Self: + return cast(Self, pickle.loads(base64.b64decode(serialized_data))) -class StringSerializable(Serializable): +class StringSerializable(Serializable[str]): """Mixin class for serializing objects using string representation.""" def serialize(self) -> str: return str(self) @classmethod - def deserialize(cls, serialized_data: str, trust: bool = False) -> StringSerializable: + def deserialize(cls, serialized_data: str, trust: bool = False) -> Self: """Deserialize a string representation of the object. !!! Warning "Security Risk" @@ -89,9 +89,9 @@ def deserialize(cls, serialized_data: str, trust: bool = False) -> StringSeriali raise ValueError(f'String "{serialized_data}" is not a valid class signature.') from e -class PickleSerializable(Serializable): +class PickleSerializable(Serializable[str]): """Mixin class for serializing objects using pickle.""" - def serialize(self, save_path: str | Path = None) -> str: + def serialize(self, save_path: str | Path | None = None) -> str: if save_path is None: raise ValueError('Must provide a save path for Pickle serialization.') with open(Path(save_path), 'wb') as fd: @@ -99,13 +99,13 @@ def serialize(self, save_path: str | Path = None) -> str: return str(Path(save_path).resolve().as_posix()) @classmethod - def deserialize(cls, serialized_data: str | Path) -> PickleSerializable: + def deserialize(cls, serialized_data: str | Path) -> Self: with open(Path(serialized_data), 'rb') as fd: - return pickle.load(fd) + return cast(Self, pickle.load(fd)) @dataclass -class YamlSerializable(Serializable): +class YamlSerializable(Serializable[str]): """Mixin for serializing an object using Yaml load/dump from string.""" obj: Any @@ -117,6 +117,6 @@ def serialize(self) -> str: return s @classmethod - def deserialize(cls, yaml_str: str) -> YamlSerializable: - obj = yaml.load(yaml_str, yaml.Loader) - return YamlSerializable(obj=obj) + def deserialize(cls, serialized_data: str) -> Self: + obj = yaml.load(serialized_data, yaml.Loader) + return cls(obj=obj) diff --git a/src/amisc/variable.py b/src/amisc/variable.py index dd11dab..cd7d0f3 100644 --- a/src/amisc/variable.py +++ b/src/amisc/variable.py @@ -36,7 +36,7 @@ _TransformLike = Union[str, Transform, list[str | Transform]] # something that can be converted to a Transform -class Variable(BaseModel, Serializable): +class Variable(BaseModel, Serializable[dict]): """Object for storing information about variables and providing methods for pdf evaluation, sampling, etc. All fields will undergo pydantic validation and conversion to the correct types. @@ -525,22 +525,22 @@ def serialize(self, save_path: str | Path = '.') -> dict: return d @classmethod - def deserialize(cls, data: dict, search_paths: list[str | Path] | None = None) -> Variable: + def deserialize(cls, serialized_data: dict, search_paths: list[str | Path] | None = None) -> Variable: """Convert a `dict` to a `Variable` object. Let `pydantic` handle validation and conversion of fields. :param data: the `dict` to convert to a `Variable` :param search_paths: the paths to search for compression files (if necessary) :returns: the `Variable` object """ - if isinstance(data, Variable): - return data - elif isinstance(data, str): - return cls(name=data) + if isinstance(serialized_data, Variable): + return serialized_data + elif isinstance(serialized_data, str): + return cls(name=serialized_data) else: - if (compression := data.get('compression', None)) is not None: + if (compression := serialized_data.get('compression', None)) is not None: if isinstance(compression, str): - data['compression'] = search_for_file(compression, search_paths=search_paths) - return cls(**data) + serialized_data['compression'] = search_for_file(compression, search_paths=search_paths) + return cls(**serialized_data) @staticmethod def _yaml_representer(dumper: yaml.Dumper, data: Variable) -> yaml.MappingNode: @@ -714,7 +714,7 @@ def __str__(self): def __repr__(self): return self.__str__() - def serialize(self, save_path='.') -> list[dict]: + def serialize(self, save_path: Path | str ='.') -> list[dict]: """Convert to a list of `dict` objects for each `Variable` in the list. :param save_path: the path to save the compression data to (defaults to current directory) @@ -748,11 +748,11 @@ def _get_best_variable(var1, var2): return merged_vars @classmethod - def deserialize(cls, data: dict | list[dict], search_paths=None) -> VariableList: + def deserialize(cls, serialized_data: dict | list[dict], search_paths=None) -> VariableList: """Convert a `dict` or list of `dict` objects to a `VariableList` object. Let `pydantic` handle validation.""" - if not isinstance(data, list): - data = [data] - return cls([Variable.deserialize(d, search_paths=search_paths) for d in data]) + if not isinstance(serialized_data, list): + serialized_data = [serialized_data] + return cls([Variable.deserialize(d, search_paths=search_paths) for d in serialized_data]) @staticmethod def _yaml_representer(dumper: yaml.Dumper, data: VariableList) -> yaml.SequenceNode: From c047b4bdd13491f33ce85298de4700cebd07611d Mon Sep 17 00:00:00 2001 From: Thomas Marks Date: Wed, 4 Mar 2026 11:03:23 -0500 Subject: [PATCH 12/29] typing: variable name is always a string and transform.from_string takes same args as at call sites --- src/amisc/transform.py | 13 +++++++++++-- src/amisc/variable.py | 12 ++++++------ 2 files changed, 17 insertions(+), 8 deletions(-) diff --git a/src/amisc/transform.py b/src/amisc/transform.py index d963bdc..14ae4df 100644 --- a/src/amisc/transform.py +++ b/src/amisc/transform.py @@ -13,6 +13,7 @@ from __future__ import annotations from abc import ABC, abstractmethod +from typing import TypeAlias, overload import numpy as np from numpy.typing import ArrayLike @@ -20,7 +21,7 @@ from amisc.utils import parse_function_string __all__ = ['Transform', 'Linear', 'Log', 'Minmax', 'Zscore'] - +_TransformLike: TypeAlias = "str | Transform | list[str | Transform]" # something that can be converted to a Transform class Transform(ABC): """A base class for all transformations. @@ -36,8 +37,16 @@ def __str__(self): """Serialize a `Transform` object to string.""" return f'{type(self).__name__}{self.transform_args}' + @overload + @classmethod + def from_string(cls, transform_spec: None) -> None: ... + + @overload + @classmethod + def from_string(cls, transform_spec: _TransformLike) -> list[Transform]: ... + @classmethod - def from_string(cls, transform_spec: str | list[str]) -> list[Transform] | None: + def from_string(cls, transform_spec: _TransformLike | None) -> list[Transform] | None: """Return a list of `Transforms` given a list of string specifications. Available transformations are: - **linear** — $x_{norm} = mx + b$ specified as `linear(m, b)` or `linear(slope=m, offset=b)`. `m=1, b=0` if not diff --git a/src/amisc/variable.py b/src/amisc/variable.py index cd7d0f3..4ae49d3 100644 --- a/src/amisc/variable.py +++ b/src/amisc/variable.py @@ -88,7 +88,7 @@ class Variable(BaseModel, Serializable[dict]): yaml_tag: ClassVar[str] = u'!Variable' model_config = ConfigDict(validate_assignment=True, arbitrary_types_allowed=True, validate_default=True) - name: Optional[str] = None + name: str = "" nominal: Optional[float] = None description: Optional[str] = None units: Optional[str] = None @@ -99,9 +99,9 @@ class Variable(BaseModel, Serializable[dict]): domain: Optional[str | tuple[float, float] | list] = None norm: Optional[_TransformLike] = None - def __init__(self, /, name=None, **kwargs): + def __init__(self, /, name="", **kwargs): # Try to set the variable name if instantiated as "x = Variable()" - if name is None: + if not name: name = _inspect_assignment('Variable') name = name or "X_" + "".join(random.choices(string.digits, k=3)) super().__init__(name=name, **kwargs) @@ -181,7 +181,7 @@ def _validate_domain(cls, domain: list | tuple | str, info: ValidationInfo) -> t def _validate_norm(cls, norm: _TransformLike, info: ValidationInfo) -> list[Transform] | None: if norm is None: return norm - norm = Transform.from_string(norm) + tfs = Transform.from_string(norm) # Set default values for minmax and zscore transforms domain = info.data['domain'] @@ -189,7 +189,7 @@ def _validate_norm(cls, norm: _TransformLike, info: ValidationInfo) -> list[Tran if dist := info.data['distribution']: if isinstance(dist, Normal): normal_args = dist.dist_args - for transform in norm: + for transform in tfs: if isinstance(transform, Minmax): if domain and np.any(np.isnan(transform.transform_args[0:2])): transform.update(lb=domain[0], ub=domain[1]) @@ -197,7 +197,7 @@ def _validate_norm(cls, norm: _TransformLike, info: ValidationInfo) -> list[Tran if normal_args and np.any(np.isnan(transform.transform_args)): transform.update(mu=normal_args[0], std=normal_args[1]) - return norm + return tfs def __getitem__(self, item): return getattr(self, item) From 8eaf8789c36b600881ed5ba14d1b40ec226fdb8c Mon Sep 17 00:00:00 2001 From: Thomas Marks Date: Wed, 4 Mar 2026 11:15:17 -0500 Subject: [PATCH 13/29] typing: variable domain is always a tuple or list --- src/amisc/variable.py | 9 ++++++--- 1 file changed, 6 insertions(+), 3 deletions(-) diff --git a/src/amisc/variable.py b/src/amisc/variable.py index 4ae49d3..3a3991f 100644 --- a/src/amisc/variable.py +++ b/src/amisc/variable.py @@ -96,7 +96,7 @@ class Variable(BaseModel, Serializable[dict]): tex: Optional[str] = None compression: Optional[str | dict | Compression] = None distribution: Optional[str | Distribution] = None - domain: Optional[str | tuple[float, float] | list] = None + domain: Optional[tuple[float, float] | list[tuple[float, float]]] = None norm: Optional[_TransformLike] = None def __init__(self, /, name="", **kwargs): @@ -143,7 +143,7 @@ def _validate_dist(cls, dist: str | Distribution) -> Distribution | None: else: raise ValueError(f'Cannot convert {dist} to a Distribution object.') - @field_validator('domain') + @field_validator('domain', mode='before') @classmethod def _validate_domain(cls, domain: list | tuple | str, info: ValidationInfo) -> tuple | list | None: """Try to extract the domain from the distribution if not provided, or convert from a string. @@ -255,7 +255,7 @@ def get_nominal(self) -> float | list | None: return nominal - def get_domain(self) -> tuple | list | None: + def get_domain(self) -> tuple[float, float] | list[tuple[float, float]] | None: """Return a tuple of the defined domain of this variable. Returns a list of domains for each latent dimension if this is a field quantity with compression. @@ -376,6 +376,9 @@ def normalize(self, values: None, denorm: bool = False) -> None: ... @overload def normalize(self, values: float, denorm: bool = False) -> float: ... + @overload + def normalize(self, values: tuple, denorm: bool = False) -> tuple: ... + @overload def normalize(self, values: ArrayLike, denorm: bool = False) -> ArrayLike: ... From 050ba461f4ccec3d246374be7bb52b4e367e22ff Mon Sep 17 00:00:00 2001 From: Thomas Marks Date: Wed, 4 Mar 2026 11:19:32 -0500 Subject: [PATCH 14/29] typing: variable distribution is always a distribution (or None) --- src/amisc/variable.py | 10 +++++----- 1 file changed, 5 insertions(+), 5 deletions(-) diff --git a/src/amisc/variable.py b/src/amisc/variable.py index 3a3991f..6f81628 100644 --- a/src/amisc/variable.py +++ b/src/amisc/variable.py @@ -95,7 +95,7 @@ class Variable(BaseModel, Serializable[dict]): category: Optional[str] = None tex: Optional[str] = None compression: Optional[str | dict | Compression] = None - distribution: Optional[str | Distribution] = None + distribution: Optional[Distribution] = None domain: Optional[tuple[float, float] | list[tuple[float, float]]] = None norm: Optional[_TransformLike] = None @@ -131,7 +131,7 @@ def _validate_compression(cls, compression: str | dict | Compression, info: Vali compression.fields = compression.fields or [info.data['name']] return compression - @field_validator('distribution') + @field_validator('distribution', mode='before') @classmethod def _validate_dist(cls, dist: str | Distribution) -> Distribution | None: if dist is None: @@ -249,7 +249,7 @@ def get_nominal(self) -> float | list | None: nominal = self.nominal if nominal is None: if dist := self.distribution: - nominal = float(dist.nominal()) + nominal = dist.nominal() elif domain := self.get_domain(): nominal = [np.mean(d) for d in domain] if isinstance(domain, list) else float(np.mean(domain)) @@ -312,11 +312,11 @@ def update_domain(self, domain: tuple[float, float] | list[tuple], override: boo :param override: will simply set the domain to the new values rather than update against the current domain; (default `False`) """ - def _update_domain(domain, curr_domain): + def _update_domain(domain, curr_domain) -> tuple[float, float]: lb, ub = domain ret = (lb, ub) if override else (min(lb, curr_domain[0]) if curr_domain is not None else lb, max(ub, curr_domain[1]) if curr_domain is not None else ub) - return tuple(map(float, ret)) + return (float(ret[0]), float(ret[1])) curr_domain = self.get_domain() if isinstance(domain, list): From a357de8caba85a25e29d1b0004dd97adfa45153b Mon Sep 17 00:00:00 2001 From: Thomas Marks Date: Wed, 4 Mar 2026 11:26:36 -0500 Subject: [PATCH 15/29] typing: variable compression is always a Compression (or None) --- src/amisc/variable.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/src/amisc/variable.py b/src/amisc/variable.py index 6f81628..9385432 100644 --- a/src/amisc/variable.py +++ b/src/amisc/variable.py @@ -94,7 +94,7 @@ class Variable(BaseModel, Serializable[dict]): units: Optional[str] = None category: Optional[str] = None tex: Optional[str] = None - compression: Optional[str | dict | Compression] = None + compression: Optional[Compression] = None distribution: Optional[Distribution] = None domain: Optional[tuple[float, float] | list[tuple[float, float]]] = None norm: Optional[_TransformLike] = None From 7fe96f72a31ada7d678ad778aeb91e1a123b6375 Mon Sep 17 00:00:00 2001 From: Thomas Marks Date: Wed, 4 Mar 2026 11:41:23 -0500 Subject: [PATCH 16/29] typing: variable norm is always a list of transforms or None --- src/amisc/variable.py | 18 +++++++++--------- 1 file changed, 9 insertions(+), 9 deletions(-) diff --git a/src/amisc/variable.py b/src/amisc/variable.py index 9385432..e076473 100644 --- a/src/amisc/variable.py +++ b/src/amisc/variable.py @@ -18,7 +18,7 @@ import string from collections import OrderedDict from pathlib import Path -from typing import ClassVar, Optional, Union, overload +from typing import ClassVar, Optional, Sequence, Union, overload import numpy as np import yaml @@ -97,7 +97,7 @@ class Variable(BaseModel, Serializable[dict]): compression: Optional[Compression] = None distribution: Optional[Distribution] = None domain: Optional[tuple[float, float] | list[tuple[float, float]]] = None - norm: Optional[_TransformLike] = None + norm: Optional[list[Transform]] = None def __init__(self, /, name="", **kwargs): # Try to set the variable name if instantiated as "x = Variable()" @@ -176,7 +176,7 @@ def _validate_domain(cls, domain: list | tuple | str, info: ValidationInfo) -> t return domain - @field_validator('norm') + @field_validator('norm', mode='before') @classmethod def _validate_norm(cls, norm: _TransformLike, info: ValidationInfo) -> list[Transform] | None: if norm is None: @@ -397,10 +397,11 @@ def normalize(self, values: float | ArrayLike | None, denorm: bool = False) -> f """ if not self.norm or values is None: return values - if dist := self.distribution: - normal_dist = isinstance(dist, Normal) + + if (dist := self.distribution) and isinstance(dist, Normal): + dist_args = self.distribution.dist_args else: - normal_dist = False + dist_args = [] def _normalize_single(values, transform, inverse, domain, dist_args): """Do a single transform. Might need to override transform_args depending on the transform.""" @@ -413,7 +414,6 @@ def _normalize_single(values, transform, inverse, domain, dist_args): return transform.transform(values, inverse=inverse, transform_args=transform_args) domain = self.get_domain() or () - dist_args = self.distribution.dist_args if normal_dist else [] if isinstance(domain, list): domain = () # For field quantities, domain is not used in normalization @@ -648,14 +648,14 @@ def _get_pdf(var, norm): pdf_fcns[var.name] = _get_pdf(var, norm) return pdf_fcns - def update(self, data: list[Variable | str] | str | Variable | OrderedDict | dict | None = None, **kwargs): + def update(self, data: Sequence[Variable | str] | str | Variable | OrderedDict | dict | None = None, **kwargs): # type: ignore[override] """Update from a list or dict of `Variable` objects, or from `key=value` pairs.""" if data: if isinstance(data, OrderedDict | dict): for key, value in data.items(): self.__setitem__(key, value) else: - data = [data] if not isinstance(data, list | tuple) else data + data = [data] if not isinstance(data, Sequence | list | tuple) else data for variable in data: self.__setitem__(str(variable), variable) if kwargs: From b7665b9e4df52bed08bdbad520a203ea816f19a6 Mon Sep 17 00:00:00 2001 From: Thomas Marks Date: Wed, 4 Mar 2026 11:45:36 -0500 Subject: [PATCH 17/29] tests: fix flaky matplotlib issues by changing background and fix import error on coverage exceptions --- README.md | 2 +- tests/conftest.py | 6 ++++++ 2 files changed, 7 insertions(+), 1 deletion(-) diff --git a/README.md b/README.md index b402bcd..5f7811d 100644 --- a/README.md +++ b/README.md @@ -6,7 +6,7 @@ ![build](https://img.shields.io/github/actions/workflow/status/eckelsjd/amisc/deploy.yml?logo=github) ![docs](https://img.shields.io/github/actions/workflow/status/eckelsjd/amisc/docs.yml?logo=materialformkdocs&logoColor=%2523cccccc&label=docs) ![tests](https://img.shields.io/github/actions/workflow/status/eckelsjd/amisc/tests.yml?logo=github&logoColor=%2523cccccc&label=tests) -![Code Coverage](https://img.shields.io/badge/coverage-88%25-yellowgreen?logo=codecov) +![Code Coverage](https://img.shields.io/badge/coverage-89%25-yellowgreen?logo=codecov) [![Algorithm description](https://img.shields.io/badge/DOI-10.1002/nme.6958-blue)](https://doi.org/10.1002/nme.6958) Efficient framework for building surrogates of multidisciplinary systems using the adaptive multi-index stochastic collocation ([AMISC](https://onlinelibrary.wiley.com/doi/full/10.1002/nme.6958)) technique. diff --git a/tests/conftest.py b/tests/conftest.py index 5c2d46e..805d060 100644 --- a/tests/conftest.py +++ b/tests/conftest.py @@ -3,7 +3,13 @@ from pathlib import Path from urllib.parse import quote +# Make sure we don't try and open any interactive windows when running tests +# This fixes some sporadic test failures on windows. +import matplotlib +matplotlib.use('Agg') + import coverage +import coverage.exceptions from coverage import Coverage PROJECT_DIR = Path(__file__).parent.parent From 0cd59b25a817331d1e7975754f93ec6a20f0f145 Mon Sep 17 00:00:00 2001 From: Thomas Marks Date: Wed, 4 Mar 2026 11:53:37 -0500 Subject: [PATCH 18/29] typing: add overloads to specify type for transform --- src/amisc/transform.py | 14 +++++++++++++- 1 file changed, 13 insertions(+), 1 deletion(-) diff --git a/src/amisc/transform.py b/src/amisc/transform.py index 14ae4df..93ee44c 100644 --- a/src/amisc/transform.py +++ b/src/amisc/transform.py @@ -127,7 +127,19 @@ def from_string(cls, transform_spec: _TransformLike | None) -> list[Transform] | return transforms - def transform(self, x: ArrayLike, inverse: bool = False, transform_args: tuple | None = None) -> ArrayLike: + @overload + def transform(self, x: int | float, inverse: bool = ..., transform_args: tuple | None = ...) -> float: ... + + @overload + def transform(self, x: tuple, inverse: bool = ..., transform_args: tuple | None = ...) -> tuple: ... + + @overload + def transform(self, x: list, inverse: bool = ..., transform_args: tuple | None = ...) -> list: ... + + @overload + def transform(self, x: np.ndarray, inverse: bool = ..., transform_args: tuple | None = ...) -> np.ndarray: ... + + def transform(self, x: int | float | tuple | list | np.ndarray, inverse: bool = False, transform_args: tuple | None = None) -> float | list | tuple | np.ndarray: """Transform the given values `x`. This wrapper function handles the input type and tries to return the transformed values in the same type. From 2bb3b47104c670aacc55e88252d2121acd585912 Mon Sep 17 00:00:00 2001 From: Thomas Marks Date: Wed, 4 Mar 2026 12:01:22 -0500 Subject: [PATCH 19/29] typing: Fix remaining type errors in variable.py --- src/amisc/variable.py | 17 +++++++++-------- 1 file changed, 9 insertions(+), 8 deletions(-) diff --git a/src/amisc/variable.py b/src/amisc/variable.py index e076473..1df9fef 100644 --- a/src/amisc/variable.py +++ b/src/amisc/variable.py @@ -18,7 +18,7 @@ import string from collections import OrderedDict from pathlib import Path -from typing import ClassVar, Optional, Sequence, Union, overload +from typing import ClassVar, Optional, Sequence, Union, cast, overload import numpy as np import yaml @@ -478,27 +478,28 @@ def compress(self, values: CompressionData, coords: np.ndarray | None = None, field_coords = values.pop('coords', coords) if field_coords is None: field_coords = self.compression.coords + assert field_coords is not None ret_dict = {'coords': field_coords} # For reconstruction: decompress -> denormalize -> interpolate if reconstruct: - try: - states = np.atleast_1d(values['latent']) # (..., rank) - except KeyError as e: - raise ValueError('Must pass values["latent"] in for reconstruction.') from e + latent = values.get('latent') + if latent is None: + raise ValueError('Must pass values["latent"] in for reconstruction.') + states = np.atleast_1d(latent) # (..., rank) states = self.compression.reconstruct(states) # (..., dof) - states = self.denormalize(states) # (..., dof) + states = np.asarray(self.denormalize(states)) # (..., dof) states = self.compression.interpolate_from_grid(states, field_coords) ret_dict.update(states) # For compression: interpolate -> normalize -> compress else: states = self.compression.interpolate_to_grid(field_coords, values) - states = self.normalize(states) # (..., dof) + states = np.asarray(self.normalize(states)) # (..., dof) states = self.compression.compress(states) # (..., rank) ret_dict['latent'] = states - return ret_dict + return cast(CompressionData, ret_dict) def reconstruct(self, values, coords=None): """Alias for `compress(reconstruct=True)`. See `compress` for more details.""" From 87e69d7c6260fe0abf1cc8cf1e10a37e43f30c40 Mon Sep 17 00:00:00 2001 From: Thomas Marks Date: Wed, 4 Mar 2026 12:02:43 -0500 Subject: [PATCH 20/29] lint: fix lint errors --- src/amisc/transform.py | 3 +-- tests/conftest.py | 1 + 2 files changed, 2 insertions(+), 2 deletions(-) diff --git a/src/amisc/transform.py b/src/amisc/transform.py index 93ee44c..4fb3d25 100644 --- a/src/amisc/transform.py +++ b/src/amisc/transform.py @@ -16,7 +16,6 @@ from typing import TypeAlias, overload import numpy as np -from numpy.typing import ArrayLike from amisc.utils import parse_function_string @@ -139,7 +138,7 @@ def transform(self, x: list, inverse: bool = ..., transform_args: tuple | None = @overload def transform(self, x: np.ndarray, inverse: bool = ..., transform_args: tuple | None = ...) -> np.ndarray: ... - def transform(self, x: int | float | tuple | list | np.ndarray, inverse: bool = False, transform_args: tuple | None = None) -> float | list | tuple | np.ndarray: + def transform(self, x, inverse: bool = False, transform_args: tuple | None = None): """Transform the given values `x`. This wrapper function handles the input type and tries to return the transformed values in the same type. diff --git a/tests/conftest.py b/tests/conftest.py index 805d060..b507117 100644 --- a/tests/conftest.py +++ b/tests/conftest.py @@ -6,6 +6,7 @@ # Make sure we don't try and open any interactive windows when running tests # This fixes some sporadic test failures on windows. import matplotlib + matplotlib.use('Agg') import coverage From 8dbd7049e70b09610e9c2674d81d6eeff045aea3 Mon Sep 17 00:00:00 2001 From: Thomas Marks Date: Wed, 4 Mar 2026 12:17:29 -0500 Subject: [PATCH 21/29] typing: fix remaing type errors in compression.py with judicious asserts --- src/amisc/compression.py | 17 +++++++++++++---- 1 file changed, 13 insertions(+), 4 deletions(-) diff --git a/src/amisc/compression.py b/src/amisc/compression.py index 16ca3a2..8b62285 100644 --- a/src/amisc/compression.py +++ b/src/amisc/compression.py @@ -156,6 +156,7 @@ def _iterate_coords_and_states(): ret_dict = {} loop_shape = state.shape[:-1] coords_shape = n_coords.shape[:-1] + assert self.num_pts is not None state = state.reshape((*loop_shape, self.num_pts, self.num_qoi)) n_coords = n_coords.reshape((-1, self.dim)) for i, qoi in enumerate(self.fields): @@ -171,9 +172,11 @@ def _iterate_coords_and_states(): if coords_obj_array: # Make an object array for each qoi, where each element is a unique `(*loop_shape, *coord_shape)` array + _first_dict = None for _, _first_dict in np.ndenumerate(all_qois): if _first_dict is not None: break + assert _first_dict is not None ret = {qoi: np.empty(all_qois.shape, dtype=object) for qoi in _first_dict} for qoi in ret: for index, qoi_dict in np.ndenumerate(all_qois): @@ -232,6 +235,7 @@ def _iterate_coords_and_fields(): coords_shape = f_coords.shape[:-1] loop_shape = next(iter(f_values.values())).shape[:-len(coords_shape)] + assert self.num_pts is not None states = np.empty((*loop_shape, self.num_pts, self.num_qoi)) f_coords = f_coords.reshape(-1, self.dim) for i, qoi in enumerate(self.fields): @@ -243,7 +247,7 @@ def _iterate_coords_and_fields(): interp = self.interpolator()(f_coords, field_vals, **self.interpolate_opts) yg = interp(grid_coords) states[..., i] = yg.T.reshape(*loop_shape, self.num_pts) - all_states[j] = states.reshape((*loop_shape, self.dof)) + all_states[j] = states.reshape((*loop_shape, self.num_pts * self.num_qoi)) # All fields now on the same dof grid, so stack them in same array state_shape = () @@ -262,7 +266,7 @@ def _iterate_coords_and_fields(): return ret_states @abstractmethod - def compute_map(self, **kwargs): + def compute_map(self, data_matrix, **kwargs): """Compute and store the compression map. Must set the value of `coords` and `_is_computed`. Should use the same normalization as the parent `Variable` object. @@ -297,7 +301,7 @@ def latent_size(self) -> int: raise NotImplementedError @abstractmethod - def estimate_latent_ranges(self) -> list[tuple[float, float]]: + def estimate_latent_ranges(self) -> list[tuple[float, float]] | None: """Estimate the range of the latent space coefficients.""" raise NotImplementedError @@ -336,7 +340,7 @@ def __post_init__(self): reconstruction_tol=self.reconstruction_tol) def compute_map(self, data_matrix: np.ndarray | dict, rank: int | None = None, energy_tol: float | None = None, - reconstruction_tol: float | None = None): + reconstruction_tol: float | None = None, **kwargs): """Compute the SVD compression map from the data matrix. Recall that `dof` is the total number of degrees of freedom, equal to the number of grid points `num_pts` times the number of quantities of interest `num_qoi` at each grid point. @@ -371,6 +375,7 @@ def compute_map(self, data_matrix: np.ndarray | dict, rank: int | None = None, e if relative_error(u[:, :r] @ u[:, :r].T @ data_matrix, data_matrix) <= reconstruction_tol: rank = r break + assert rank is not None energy_tol = energy_frac[rank - 1] else: energy_tol = energy_tol or self.energy_tol or 0.95 @@ -386,16 +391,20 @@ def compute_map(self, data_matrix: np.ndarray | dict, rank: int | None = None, e self._map_computed = True def compress(self, data): + assert self.projection_matrix is not None return np.squeeze(self.projection_matrix.T @ data[..., np.newaxis], axis=-1) def reconstruct(self, compressed): + assert self.projection_matrix is not None return np.squeeze(self.projection_matrix @ compressed[..., np.newaxis], axis=-1) def latent_size(self): + assert self.rank is not None return self.rank def estimate_latent_ranges(self): if self.map_exists: + assert self.data_matrix is not None latent_data = self.compress(self.data_matrix.T) # (rank, num_samples) latent_min = np.min(latent_data, axis=0) latent_max = np.max(latent_data, axis=0) From 5d21559cca2f205da92011722bb56195ffb46c8d Mon Sep 17 00:00:00 2001 From: Thomas Marks Date: Wed, 4 Mar 2026 12:24:08 -0500 Subject: [PATCH 22/29] typing: narrow types in Component --- src/amisc/component.py | 34 +++++++++++++++++----------------- 1 file changed, 17 insertions(+), 17 deletions(-) diff --git a/src/amisc/component.py b/src/amisc/component.py index e9d4d9a..be977c7 100644 --- a/src/amisc/component.py +++ b/src/amisc/component.py @@ -388,25 +388,25 @@ class Component(BaseModel, Serializable): # Configuration serializers: Optional[ComponentSerializers] = None name: Optional[str] = None - model: str | Callable[..., dict | Dataset] + model: Callable[..., dict | Dataset] model_kwargs: str | dict | ModelKwargs = {} - inputs: _VariableLike - outputs: _VariableLike - model_fidelity: str | tuple = MultiIndex() - data_fidelity: str | tuple = MultiIndex() - surrogate_fidelity: str | tuple = MultiIndex() + inputs: VariableList + outputs: VariableList + model_fidelity: tuple = MultiIndex() + data_fidelity: tuple = MultiIndex() + surrogate_fidelity: tuple = MultiIndex() interpolator: Any | Interpolator = Lagrange() vectorized: bool = False call_unpacked: Optional[bool] = None # If the model expects inputs/outputs like `func(x1, x2, ...)->(y1, y2, ...) ret_unpacked: Optional[bool] = None # Data storage/states for a MISC component - active_set: list | set | IndexSet = IndexSet() # set of active (alpha, beta) multi-indices - candidate_set: list | set | IndexSet = IndexSet() # set of candidate (alpha, beta) multi-indices - misc_states: dict | MiscTree = MiscTree() # (alpha, beta) -> Interpolator state - misc_costs: dict | MiscTree = MiscTree() # (alpha, beta) -> Added computational cost for this mult-index - misc_coeff_train: dict | MiscTree = MiscTree() # (alpha, beta) -> c_[alpha, beta] (active set only) - misc_coeff_test: dict | MiscTree = MiscTree() # (alpha, beta) -> c_[alpha, beta] (including candidate set) + active_set: IndexSet = IndexSet() # set of active (alpha, beta) multi-indices + candidate_set: IndexSet = IndexSet() # set of candidate (alpha, beta) multi-indices + misc_states: MiscTree = MiscTree() # (alpha, beta) -> Interpolator state + misc_costs: MiscTree = MiscTree() # (alpha, beta) -> Added computational cost for this mult-index + misc_coeff_train: MiscTree = MiscTree() # (alpha, beta) -> c_[alpha, beta] (active set only) + misc_coeff_test: MiscTree = MiscTree() # (alpha, beta) -> c_[alpha, beta] (including candidate set) model_costs: dict = dict() # Average single fidelity model costs (for each alpha) model_evals: dict = dict() # Number of evaluations for each alpha training_data: Any | TrainingData = SparseGrid() # Stores surrogate training data @@ -574,7 +574,7 @@ def _validate_serializers(cls, serializers: ComponentSerializers) -> ComponentSe serializers[key] = YamlSerializable(obj=serializer) return serializers - @field_validator('model') + @field_validator('model', mode='before') @classmethod def _validate_model(cls, model: str | Callable) -> Callable: """Expects model as a callable or a yaml !!python/name string representation.""" @@ -583,7 +583,7 @@ def _validate_model(cls, model: str | Callable) -> Callable: else: return model - @field_validator('inputs', 'outputs') + @field_validator('inputs', 'outputs', mode='before') @classmethod def _validate_variables(cls, variables: _VariableLike) -> VariableList: if isinstance(variables, VariableList): @@ -591,17 +591,17 @@ def _validate_variables(cls, variables: _VariableLike) -> VariableList: else: return VariableList.deserialize(variables) - @field_validator('model_fidelity', 'data_fidelity', 'surrogate_fidelity') + @field_validator('model_fidelity', 'data_fidelity', 'surrogate_fidelity', mode='before') @classmethod def _validate_indices(cls, multi_index) -> MultiIndex: return MultiIndex(multi_index) - @field_validator('active_set', 'candidate_set') + @field_validator('active_set', 'candidate_set', mode='before') @classmethod def _validate_index_set(cls, index_set) -> IndexSet: return IndexSet.deserialize(index_set) - @field_validator('misc_states', 'misc_costs', 'misc_coeff_train', 'misc_coeff_test') + @field_validator('misc_states', 'misc_costs', 'misc_coeff_train', 'misc_coeff_test', mode='before') @classmethod def _validate_misc_tree(cls, misc_tree) -> MiscTree: return MiscTree.deserialize(misc_tree) From 75dc37ea973e2b3c86417901d4725a43680ed6a8 Mon Sep 17 00:00:00 2001 From: Thomas Marks Date: Wed, 4 Mar 2026 12:29:23 -0500 Subject: [PATCH 23/29] typing: narrow types in System and make component name a str --- README.md | 2 +- src/amisc/component.py | 6 +++--- src/amisc/system.py | 13 ++++++------- 3 files changed, 10 insertions(+), 11 deletions(-) diff --git a/README.md b/README.md index 5f7811d..1249aaa 100644 --- a/README.md +++ b/README.md @@ -6,7 +6,7 @@ ![build](https://img.shields.io/github/actions/workflow/status/eckelsjd/amisc/deploy.yml?logo=github) ![docs](https://img.shields.io/github/actions/workflow/status/eckelsjd/amisc/docs.yml?logo=materialformkdocs&logoColor=%2523cccccc&label=docs) ![tests](https://img.shields.io/github/actions/workflow/status/eckelsjd/amisc/tests.yml?logo=github&logoColor=%2523cccccc&label=tests) -![Code Coverage](https://img.shields.io/badge/coverage-89%25-yellowgreen?logo=codecov) +![Code Coverage](https://img.shields.io/badge/coverage-85%25-yellowgreen?logo=codecov) [![Algorithm description](https://img.shields.io/badge/DOI-10.1002/nme.6958-blue)](https://doi.org/10.1002/nme.6958) Efficient framework for building surrogates of multidisciplinary systems using the adaptive multi-index stochastic collocation ([AMISC](https://onlinelibrary.wiley.com/doi/full/10.1002/nme.6958)) technique. diff --git a/src/amisc/component.py b/src/amisc/component.py index be977c7..e71e0a4 100644 --- a/src/amisc/component.py +++ b/src/amisc/component.py @@ -387,7 +387,7 @@ class Component(BaseModel, Serializable): protected_namespaces=(), extra='allow') # Configuration serializers: Optional[ComponentSerializers] = None - name: Optional[str] = None + name: str = "" model: Callable[..., dict | Dataset] model_kwargs: str | dict | ModelKwargs = {} inputs: VariableList @@ -417,8 +417,8 @@ class Component(BaseModel, Serializable): _model_end_time: float = -1.0 # Temporarily store the most recent model end timestamp from call_model _cache: dict = dict() # Temporary cache for faster access to training data and similar - def __init__(self, /, model, *args, inputs=None, outputs=None, name=None, **kwargs): - if name is None: + def __init__(self, /, model, *args, inputs=None, outputs=None, name="", **kwargs): + if not name: name = _inspect_assignment('Component') # try to assign the name from inspection name = name or model.__name__ or "Component_" + "".join(random.choices(string.digits, k=3)) diff --git a/src/amisc/system.py b/src/amisc/system.py index 4f5f5b7..8ad2395 100644 --- a/src/amisc/system.py +++ b/src/amisc/system.py @@ -216,7 +216,7 @@ def f2(y): extra='allow') name: Annotated[str, Field(default_factory=lambda: "System_" + "".join(random.choices(string.digits, k=3)))] - components: Callable | Component | list[Callable | Component] + components: list[Component] train_history: list[dict] | TrainHistory = TrainHistory() amisc_version: str | None = None timestamp_prefix: str = "amisc_" @@ -261,7 +261,7 @@ def __repr__(self): def __str__(self): return self.__repr__() - @field_validator('components') + @field_validator('components', mode='before') @classmethod def _validate_components(cls, comps) -> list[Component]: if not isinstance(comps, list): @@ -276,7 +276,7 @@ def _validate_components(cls, comps) -> list[Component]: return comps - @field_validator('train_history') + @field_validator('train_history', mode='before') @classmethod def _validate_train_history(cls, history) -> TrainHistory: if isinstance(history, TrainHistory): @@ -318,13 +318,13 @@ def wrap(self, *args, **kwargs): def insert_components(self, components: list | Callable | Component): """Insert new components into the system.""" components = components if isinstance(components, list) else [components] - self.components = self.components + components + self.components = System._validate_components(self.components + components) def swap_component(self, old_component: str | Component, new_component: Callable | Component): """Replace an old component with a new component.""" old_name = old_component if isinstance(old_component, str) else old_component.name comps = [comp if comp.name != old_name else new_component for comp in self.components] - self.components = comps + self.components = System._validate_components(comps) def remove_component(self, component: str | Component): """Remove a component from the system.""" @@ -400,8 +400,6 @@ def root_dir(self, root_dir: PathLike | None): :param root_dir: the root directory for all build products """ - # TODO: don't create dirs until we do something! - if root_dir is not None: root_dir = Path(root_dir).resolve() @@ -419,6 +417,7 @@ def root_dir(self, root_dir: PathLike | None): assert self.root_dir is not None log_file = None + # TODO: don't create surrogate or components dirs until necessary if not (pth := self.root_dir / 'surrogates').is_dir(): os.mkdir(pth) if not (pth := self.root_dir / 'components').is_dir(): From 6e58d6fb7a25db2e68134f76e1f53d38689e7eeb Mon Sep 17 00:00:00 2001 From: Thomas Marks Date: Wed, 4 Mar 2026 12:37:19 -0500 Subject: [PATCH 24/29] fix: use null logger pattern to resolve Optional[Logger] type errors The logger property in System and Component now returns a shared NullHandler logger as a fallback instead of None, making the return type a non-optional logging.Logger. Setters are widened to accept None to preserve the pickling behaviour in _remove_unpickleable. --- README.md | 2 +- src/amisc/component.py | 7 ++++++- src/amisc/system.py | 11 ++++++++--- 3 files changed, 15 insertions(+), 5 deletions(-) diff --git a/README.md b/README.md index 1249aaa..5f7811d 100644 --- a/README.md +++ b/README.md @@ -6,7 +6,7 @@ ![build](https://img.shields.io/github/actions/workflow/status/eckelsjd/amisc/deploy.yml?logo=github) ![docs](https://img.shields.io/github/actions/workflow/status/eckelsjd/amisc/docs.yml?logo=materialformkdocs&logoColor=%2523cccccc&label=docs) ![tests](https://img.shields.io/github/actions/workflow/status/eckelsjd/amisc/tests.yml?logo=github&logoColor=%2523cccccc&label=tests) -![Code Coverage](https://img.shields.io/badge/coverage-85%25-yellowgreen?logo=codecov) +![Code Coverage](https://img.shields.io/badge/coverage-89%25-yellowgreen?logo=codecov) [![Algorithm description](https://img.shields.io/badge/DOI-10.1002/nme.6958-blue)](https://doi.org/10.1002/nme.6958) Efficient framework for building surrogates of multidisciplinary systems using the adaptive multi-index stochastic collocation ([AMISC](https://onlinelibrary.wiley.com/doi/full/10.1002/nme.6958)) technique. diff --git a/src/amisc/component.py b/src/amisc/component.py index e71e0a4..5486c28 100644 --- a/src/amisc/component.py +++ b/src/amisc/component.py @@ -651,10 +651,15 @@ def has_surrogate(self) -> bool: @property def logger(self) -> logging.Logger: + if self._logger is None: + _null = logging.getLogger('amisc.null') + if not _null.handlers: + _null.addHandler(logging.NullHandler()) + return _null return self._logger @logger.setter - def logger(self, logger: logging.Logger): + def logger(self, logger: logging.Logger | None): self._logger = logger def __eq__(self, other): diff --git a/src/amisc/system.py b/src/amisc/system.py index 8ad2395..7d3549a 100644 --- a/src/amisc/system.py +++ b/src/amisc/system.py @@ -36,7 +36,7 @@ from concurrent.futures import ALL_COMPLETED, Executor, wait from datetime import timezone from pathlib import Path -from typing import Annotated, Callable, ClassVar, Literal, Optional +from typing import Annotated, Callable, ClassVar, Literal, Optional, cast import matplotlib.pyplot as plt import networkx as nx @@ -103,7 +103,7 @@ def _validate_item(cls, item: dict): item['added_error'] = float(item['added_error']) item['overhead_s'] = float(item['overhead_s']) item['model_s'] = float(item['model_s']) - return item + return cast(TrainIteration, item) def append(self, item: dict): super().append(self._validate_item(item)) @@ -370,10 +370,15 @@ def refine_level(self) -> int: @property def logger(self) -> logging.Logger: + if self._logger is None: + _null = logging.getLogger('amisc.null') + if not _null.handlers: + _null.addHandler(logging.NullHandler()) + return _null return self._logger @logger.setter - def logger(self, logger: logging.Logger): + def logger(self, logger: logging.Logger | None): self._logger = logger for comp in self.components: comp.logger = logger From 7492c5f584425a92572b27e9e0bbeb484b583d49 Mon Sep 17 00:00:00 2001 From: Thomas Marks Date: Wed, 4 Mar 2026 13:14:14 -0500 Subject: [PATCH 25/29] typing: fix type errors in IndexSet, MiscTree, and Kwargs classes, as well as some in component --- src/amisc/component.py | 69 +++++++++++++++++++++++---------------- src/amisc/interpolator.py | 8 ++--- src/amisc/variable.py | 25 +++++++++++--- 3 files changed, 65 insertions(+), 37 deletions(-) diff --git a/src/amisc/component.py b/src/amisc/component.py index 5486c28..6d93714 100644 --- a/src/amisc/component.py +++ b/src/amisc/component.py @@ -33,12 +33,12 @@ from collections import UserDict, deque from concurrent.futures import ALL_COMPLETED, Executor, wait from pathlib import Path -from typing import Any, Callable, ClassVar, Iterable, Literal, Optional +from typing import Any, Callable, ClassVar, Iterator, Literal, Optional, cast import numpy as np import yaml from pydantic import BaseModel, ConfigDict, ValidationInfo, field_validator -from typing_extensions import TypedDict +from typing_extensions import Self, TypedDict from amisc.interpolator import Interpolator, InterpolatorState, Lagrange from amisc.serialize import PickleSerializable, Serializable, StringSerializable, YamlSerializable @@ -66,12 +66,12 @@ class ModelKwargs(UserDict, Serializable): more complicated serialization/specification than a plain `dict`, then you can subclass from here. """ - def serialize(self): + def serialize(self) -> dict | str: return self.data @classmethod - def deserialize(cls, serialized_data): - return ModelKwargs(**serialized_data) + def deserialize(cls, serialized_data) -> Self: + return cls(**serialized_data) @classmethod def from_dict(cls, config: dict) -> ModelKwargs: @@ -125,8 +125,16 @@ def __repr__(self): def add(self, __element): super().add(self._validate_element(__element)) - def update(self, __elements): - super().update([self._validate_element(ele) for ele in __elements]) + def update(self, *s): + super().update([self._validate_element(ele) for iterable in s for ele in iterable]) + + def __iter__(self) -> Iterator[tuple[MultiIndex, MultiIndex]]: + return cast(Iterator[tuple[MultiIndex, MultiIndex]], super().__iter__()) + + def union(self, *others) -> 'IndexSet': + """Return the union of this set with others as an IndexSet.""" + result = super().union(*others) + return IndexSet(result) @classmethod def _validate_element(cls, element): @@ -143,7 +151,7 @@ def inner(self, *args): if isinstance(result, set): result = cls(result) return result - inner.fn_name = name + inner.__name__ = name setattr(cls, name, inner) for name in names: @@ -263,13 +271,13 @@ def _is_alpha_beta_access(key): return (isinstance(key, tuple) and len(key) == 2 and isinstance(key[0], str | tuple) and isinstance(key[1], str | tuple)) - def get(self, key, default=None) -> float | InterpolatorState: + def get(self, key, default=None) -> float | InterpolatorState | None: try: return self.__getitem__(key) except Exception: return default - def update(self, data_dict: dict| None = None, **kwargs): + def update(self, data_dict: Any = None, **kwargs): """Force `dict.update()` through the validator.""" data_dict = data_dict or dict() data_dict.update(kwargs) @@ -309,7 +317,7 @@ def __eq__(self, other): else: return False - def __iter__(self) -> Iterable[tuple[tuple, tuple, float | InterpolatorState]]: + def __iter__(self) -> Iterator[tuple[tuple, tuple, float | InterpolatorState]]: for alpha, beta_dict in self.data.items(): if alpha == self.SERIALIZER_KEY: continue @@ -392,9 +400,9 @@ class Component(BaseModel, Serializable): model_kwargs: str | dict | ModelKwargs = {} inputs: VariableList outputs: VariableList - model_fidelity: tuple = MultiIndex() - data_fidelity: tuple = MultiIndex() - surrogate_fidelity: tuple = MultiIndex() + model_fidelity: MultiIndex = MultiIndex() + data_fidelity: MultiIndex = MultiIndex() + surrogate_fidelity: MultiIndex = MultiIndex() interpolator: Any | Interpolator = Lagrange() vectorized: bool = False call_unpacked: Optional[bool] = None # If the model expects inputs/outputs like `func(x1, x2, ...)->(y1, y2, ...) @@ -495,15 +503,15 @@ def _validate_model_signature(cls, model, args=(), inputs=None, outputs=None, inputs = inputs or [] inputs = VariableList.merge(inputs, arg_inputs) if len(inputs) == 0: - inputs = inputs_inspect + inputs = VariableList.deserialize(inputs_inspect) call_unpacked = True if len(inputs) == 0: raise ValueError("Could not infer input variables from model signature. Either your model does not " "accept input arguments or an error occurred during inspection.\nPlease provide the " "inputs directly as `Component(inputs=[...])` or fix the model signature.") if call_unpacked: - if not all([var == inputs_inspect[i] for i, var in enumerate(inputs)]): - warnings.warn(f"Mismatch between provided inputs: {inputs.values()} and inputs inferred from " + if not all([str(var) == str(inputs_inspect[i]) for i, var in enumerate(inputs)]): + warnings.warn(f"Mismatch between provided inputs: {inputs} and inputs inferred from " f"model signature: {inputs_inspect}. This may cause unexpected results.") else: if len(inputs_inspect) > 1: @@ -524,15 +532,15 @@ def _validate_model_signature(cls, model, args=(), inputs=None, outputs=None, outputs = outputs or [] outputs = VariableList.merge(outputs, *arg_outputs) if len(outputs) == 0: - outputs = outputs_inspect + outputs = VariableList.deserialize(outputs_inspect) ret_unpacked = True if len(outputs) == 0: raise ValueError("Could not infer output variables from model inspection. Either your model does not " "return outputs or an error occurred during inspection.\nPlease provide the " "outputs directly as `Component(outputs=[...])` or fix the model return values.") if ret_unpacked: - if not all([var == outputs_inspect[i] for i, var in enumerate(outputs)]): - warnings.warn(f"Mismatch between provided outputs: {outputs.values()} and outputs inferred " + if not all([str(var) == str(outputs_inspect[i]) for i, var in enumerate(outputs)]): + warnings.warn(f"Mismatch between provided outputs: {outputs} and outputs inferred " f"from model: {outputs_inspect}. This may cause unexpected results.") else: if len(outputs_inspect) > 1: @@ -642,7 +650,7 @@ def max_alpha(self) -> MultiIndex: @property def max_beta(self) -> MultiIndex: """The maximum surrogate fidelity multi-index is a combination of training and interpolator indices.""" - return self.data_fidelity + self.surrogate_fidelity + return MultiIndex(self.data_fidelity + self.surrogate_fidelity) @property def has_surrogate(self) -> bool: @@ -722,7 +730,8 @@ def _surrogate_outputs(self): y_vars.append(var.name) return y_vars - def _match_index_set(self, index_set, misc_coeff): + def _match_index_set(self, index_set: Literal['train', 'test'] | IndexSet, + misc_coeff: MiscTree | None) -> tuple[IndexSet, MiscTree]: """Helper function to grab the correct data structures for the given index set and MISC coefficients.""" if misc_coeff is None: match index_set: @@ -738,11 +747,11 @@ def _match_index_set(self, index_set, misc_coeff): case 'train': index_set = self.active_set case 'test': - index_set = self.active_set.union(self.candidate_set) + index_set = cast(IndexSet, self.active_set.union(self.candidate_set)) case other: raise ValueError(f"Index set must be 'train' or 'test'. {other} not recognized.") - return index_set, misc_coeff + return cast(IndexSet, index_set), misc_coeff def cache(self, kind: list | Literal["training"] = "training"): """Cache data for quicker access. Only `"training"` is supported. @@ -1117,10 +1126,12 @@ def predict(self, inputs: dict | Dataset, coeffs = [] for alpha, beta in index_set: comb_coeff = misc_coeff[alpha, beta] + assert isinstance(comb_coeff, (int, float)) if np.abs(comb_coeff) > 0: coeffs.append(comb_coeff) - args = (self.misc_states.get((alpha, beta)), - self.get_training_data(alpha, beta, y_vars=y_vars, cached=True)) + state = self.misc_states[alpha, beta] + assert isinstance(state, InterpolatorState) + args = (state, self.get_training_data(alpha, beta, y_vars=y_vars, cached=True)) results.append(self.interpolator.predict(inputs, *args) if executor is None else executor.submit(self.interpolator.predict, inputs, *args)) @@ -1353,11 +1364,13 @@ def gradient(self, inputs: dict | Dataset, coeffs = [] for alpha, beta in index_set: comb_coeff = misc_coeff[alpha, beta] + assert isinstance(comb_coeff, (int, float)) if np.abs(comb_coeff) > 0: coeffs.append(comb_coeff) func = self.interpolator.gradient if derivative == 'first' else self.interpolator.hessian - args = (self.misc_states.get((alpha, beta)), - self.get_training_data(alpha, beta, y_vars=y_vars, cached=True)) + state = self.misc_states[alpha, beta] + assert isinstance(state, InterpolatorState) + args = (state, self.get_training_data(alpha, beta, y_vars=y_vars, cached=True)) results.append(func(inputs, *args) if executor is None else executor.submit(func, inputs, *args)) diff --git a/src/amisc/interpolator.py b/src/amisc/interpolator.py index 4e567d8..dde9590 100644 --- a/src/amisc/interpolator.py +++ b/src/amisc/interpolator.py @@ -118,7 +118,7 @@ class Interpolator(Serializable, ABC): @abstractmethod def refine(self, beta: MultiIndex, training_data: tuple[Dataset, Dataset], - old_state: InterpolatorState, input_domains: dict[str, tuple]) -> InterpolatorState: + old_state: InterpolatorState | None, input_domains: dict[str, tuple]) -> InterpolatorState: """Refine the interpolator state with new training data. :param beta: a multi-index specifying the fidelity "levels" of the new interpolator state (starts at (0,... 0)) @@ -234,7 +234,7 @@ def _extend_grids(x_grids: dict[str, np.ndarray], x_points: dict[str, np.ndarray return extended_grids def refine(self, beta: MultiIndex, training_data: tuple[Dataset, Dataset], - old_state: LagrangeState, input_domains: dict[str, tuple]) -> LagrangeState: + old_state: LagrangeState | None, input_domains: dict[str, tuple]) -> LagrangeState: """Refine the interpolator state with new training data. :param beta: the refinement level indices for the interpolator (not used for `Lagrange`) @@ -568,7 +568,7 @@ def __post_init__(self): raise ImportError(f"Scaler '{self.scaler}' not found in sklearn.preprocessing") def refine(self, beta: MultiIndex, training_data: tuple[Dataset, Dataset], - old_state: LinearState, input_domains: dict[str, tuple]) -> InterpolatorState: + old_state: LinearState | None, input_domains: dict[str, tuple]) -> InterpolatorState: """Train a new linear regression model. :param beta: if not empty, then the first element is the number of degrees to add to the polynomial features. @@ -707,7 +707,7 @@ def __post_init__(self): raise ImportError(f"Scaler '{self.scaler}' not found in sklearn.preprocessing") def refine(self, beta: MultiIndex, training_data: tuple[Dataset, Dataset], - old_state: GPRState, input_domains: dict[str, tuple]) -> InterpolatorState: + old_state: GPRState | None, input_domains: dict[str, tuple]) -> InterpolatorState: """Train a new gaussian process regression model. :param beta: refinement level indices (Not used for 'GPR') diff --git a/src/amisc/variable.py b/src/amisc/variable.py index 1df9fef..0890252 100644 --- a/src/amisc/variable.py +++ b/src/amisc/variable.py @@ -752,11 +752,26 @@ def _get_best_variable(var1, var2): return merged_vars @classmethod - def deserialize(cls, serialized_data: dict | list[dict], search_paths=None) -> VariableList: - """Convert a `dict` or list of `dict` objects to a `VariableList` object. Let `pydantic` handle validation.""" - if not isinstance(serialized_data, list): - serialized_data = [serialized_data] - return cls([Variable.deserialize(d, search_paths=search_paths) for d in serialized_data]) + def deserialize( + cls, serialized_data: dict | str | Variable | Sequence[dict | str | Variable], + search_paths=None + ) -> VariableList: + """Convert a `dict`, `str`, `Variable`, or sequence of `dict`/`str`/`Variable` objects to a `VariableList`.""" + # Convert single items to a list + if isinstance(serialized_data, (dict, str, Variable)): + items: Sequence[dict | str | Variable] = [serialized_data] + else: + items = serialized_data + + result = [] + for item in items: + if isinstance(item, Variable): + result.append(item) + elif isinstance(item, str): + result.append(Variable(name=item)) + else: + result.append(Variable.deserialize(item, search_paths=search_paths)) + return cls(result) @staticmethod def _yaml_representer(dumper: yaml.Dumper, data: VariableList) -> yaml.SequenceNode: From e74514785d85487a2dce19f618b0eb3d2c4b1fb4 Mon Sep 17 00:00:00 2001 From: Thomas Marks Date: Wed, 4 Mar 2026 13:22:36 -0500 Subject: [PATCH 26/29] typing: narrow ModelKwargs --- src/amisc/component.py | 20 ++++++++++++-------- 1 file changed, 12 insertions(+), 8 deletions(-) diff --git a/src/amisc/component.py b/src/amisc/component.py index 6d93714..c8fe49f 100644 --- a/src/amisc/component.py +++ b/src/amisc/component.py @@ -397,7 +397,7 @@ class Component(BaseModel, Serializable): serializers: Optional[ComponentSerializers] = None name: str = "" model: Callable[..., dict | Dataset] - model_kwargs: str | dict | ModelKwargs = {} + model_kwargs: ModelKwargs = ModelKwargs() inputs: VariableList outputs: VariableList model_fidelity: MultiIndex = MultiIndex() @@ -624,15 +624,19 @@ def _validate_model_costs(cls, model_costs: dict) -> dict: def _validate_model_evals(cls, model_evals: dict) -> dict: return {MultiIndex(key): int(value) for key, value in model_evals.items()} - @field_validator('model_kwargs', 'interpolator', 'training_data') + @field_validator('model_kwargs', 'interpolator', 'training_data', mode='before') @classmethod def _validate_arbitrary_serializable(cls, data: Any, info: ValidationInfo) -> Any: """Use the stored custom serialization classes to deserialize arbitrary objects.""" - serializer = info.data.get('serializers').get(info.field_name).obj + if isinstance(data, Serializable): return data - else: - return serializer.deserialize(data) + + serializers = info.data.get('serializers') or {} + serializer_obj = serializers.get(info.field_name) + assert serializer_obj is not None, f"Serializer not found for {info.field_name}" + serializer = serializer_obj.obj + return serializer.deserialize(data) @property def xdim(self) -> int: @@ -683,7 +687,7 @@ def __eq__(self, other): else: return False - def _neighbors(self, alpha: MultiIndex, beta: MultiIndex, active_set: IndexSet = None, forward: bool = True): + def _neighbors(self, alpha: MultiIndex, beta: MultiIndex, active_set: IndexSet | None = None, forward: bool = True): """Get all possible forward or backward multi-index neighbors (distance of one unit vector away). :param alpha: the model fidelity index @@ -778,7 +782,7 @@ def clear_cache(self): def get_training_data(self, alpha: Literal['best', 'worst'] | MultiIndex = 'best', beta: Literal['best', 'worst'] | MultiIndex = 'best', - y_vars: list = None, + y_vars: list | None = None, cached: bool = False) -> tuple[Dataset, Dataset]: """Get all training data for a given multi-index pair `(alpha, beta)`. @@ -1438,7 +1442,7 @@ def update_model(self, new_model: Callable | None = None, model_kwargs: dict | new_kwargs = self.model_kwargs.data new_kwargs.update(model_kwargs or {}) new_kwargs.update(kwargs) - self.model_kwargs = new_kwargs + self.model_kwargs = ModelKwargs(new_kwargs) def get_cost(self, alpha: MultiIndex, beta: MultiIndex) -> int: """Return the total cost (i.e. number of model evaluations) required to add $(\\alpha, \\beta)$ to the From de778c031ba219f9774a2b1a40f5c4e6a896c9ac Mon Sep 17 00:00:00 2001 From: Thomas Marks Date: Wed, 4 Mar 2026 13:26:37 -0500 Subject: [PATCH 27/29] fix: MultiIndex allows slicing --- src/amisc/component.py | 8 ++++---- src/amisc/typing.py | 6 ++++++ 2 files changed, 10 insertions(+), 4 deletions(-) diff --git a/src/amisc/component.py b/src/amisc/component.py index c8fe49f..00d4a44 100644 --- a/src/amisc/component.py +++ b/src/amisc/component.py @@ -799,9 +799,9 @@ def get_training_data(self, alpha: Literal['best', 'worst'] | MultiIndex = 'best for a, _ in self.active_set.union(self.candidate_set): if sum(a) > sum(alpha_best): alpha_best = a - alpha = alpha_best + alpha = MultiIndex(alpha_best) elif alpha == 'worst': - alpha = (0,) * len(self.max_alpha) + alpha = MultiIndex((0,) * len(self.max_alpha)) # Find the best beta for the given alpha if beta == 'best': @@ -809,9 +809,9 @@ def get_training_data(self, alpha: Literal['best', 'worst'] | MultiIndex = 'best for a, b in self.active_set.union(self.candidate_set): if a == alpha and sum(b) > sum(beta_best): beta_best = b - beta = beta_best + beta = MultiIndex(beta_best) elif beta == 'worst': - beta = (0,) * len(self.max_beta) + beta = MultiIndex((0,) * len(self.max_beta)) try: if cached and (data := self._cache.get("training", {}).get(alpha, {}).get(beta)) is not None: diff --git a/src/amisc/typing.py b/src/amisc/typing.py index b4bac97..f8e9878 100644 --- a/src/amisc/typing.py +++ b/src/amisc/typing.py @@ -31,6 +31,12 @@ def __new__(cls, __tuple=()): else: return super().__new__(cls, map(int, __tuple)) + def __getitem__(self, key): + result = super().__getitem__(key) + if isinstance(key, slice): + return MultiIndex(result) + return result + class Dataset(_TypedDict, total=False): """Type hint for the input/output `dicts` of a call to `Component.model`. The keys are the variable names and the From 01674590de9e0d81f69647f0de2aac91446d8df3 Mon Sep 17 00:00:00 2001 From: Thomas Marks Date: Wed, 4 Mar 2026 13:32:13 -0500 Subject: [PATCH 28/29] fix: update date on copyright notice --- LICENSE | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/LICENSE b/LICENSE index 1858190..85cad28 100644 --- a/LICENSE +++ b/LICENSE @@ -1,4 +1,4 @@ -Copyright (C) 2023-2025 The Regents of the University of Michigan +Copyright (C) 2023-2026 The Regents of the University of Michigan Computational Autonomy Group (alexgorodetsky.com), Department of Aerospace Engineering GNU GENERAL PUBLIC LICENSE From ad5d48afe40b7db6ae59b7393c7c36e6eab19c6f Mon Sep 17 00:00:00 2001 From: Thomas Marks Date: Thu, 19 Mar 2026 17:03:23 -0400 Subject: [PATCH 29/29] fix package versioning for pydantic to support python 3.14 also add requirements.txt --- pdm.lock | 3596 ++++++++++++++++++++++++++++------------------ pyproject.toml | 2 +- requirements.txt | 24 + 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dependencies = [ "matplotlib>=3.9", "networkx>=3.2", "pyyaml>=6.0.2", - "pydantic>=2.9.1, !=2.12.*", "dill>=0.3.9", "scikit-learn>=1.6.1", + "pydantic>=2.11.10", ] requires-python = ">=3.11" readme = "README.md" diff --git a/requirements.txt b/requirements.txt new file mode 100644 index 0000000..cf36143 --- /dev/null +++ b/requirements.txt @@ -0,0 +1,24 @@ +amisc @ file:///Users/archermarks/projects/pem/amisc +annotated-types==0.7.0 +contourpy==1.3.3 +cycler==0.12.1 +dill==0.4.1 +fonttools==4.62.1 +joblib==1.5.3 +kiwisolver==1.5.0 +matplotlib==3.10.8 +networkx==3.6.1 +numpy==2.4.3 +packaging==26.0 +pillow==12.1.1 +pydantic==2.12.5 +pydantic_core==2.41.5 +pyparsing==3.3.2 +python-dateutil==2.9.0.post0 +PyYAML==6.0.3 +scikit-learn==1.8.0 +scipy==1.17.1 +six==1.17.0 +threadpoolctl==3.6.0 +typing-inspection==0.4.2 +typing_extensions==4.15.0 diff --git a/uv.lock b/uv.lock index 2836f5a..72a697f 100644 --- a/uv.lock +++ b/uv.lock @@ -1,5 +1,5 @@ version = 1 -revision = 3 +revision = 2 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