diff --git a/.github/dependabot.yml b/.github/dependabot.yml new file mode 100644 index 0000000..1938a02 --- /dev/null +++ b/.github/dependabot.yml @@ -0,0 +1,10 @@ +version: 2 +updates: + - package-ecosystem: "pip" + directory: "pyproject.toml" + schedule: + interval: "weekly" + - package-ecosystem: "github-actions" + directory: "/" + schedule: + interval: "weekly" diff --git a/.github/workflows/build_test.yml b/.github/workflows/build_test.yml index d277cf3..3e5bd0c 100644 --- a/.github/workflows/build_test.yml +++ b/.github/workflows/build_test.yml @@ -22,14 +22,19 @@ jobs: - "3.9" - "3.10" - "3.11" + - "3.12" env: TOXENV: ${{ matrix.tox-env }} TOX_SKIP_MISSING_INTERPRETERS: False + steps: - - uses: actions/checkout@v2 + - uses: actions/checkout@v4 + + - name: Run pre-commit hook + uses: pre-commit/action@v3.0.1 - name: Set up Python ${{ matrix.python-version }} - uses: actions/setup-python@v2 + uses: actions/setup-python@v5 with: python-version: ${{ matrix.python-version }} @@ -42,16 +47,18 @@ jobs: - name: Run tox run: tox - tag_release: - name: tag current release - if: endsWith(github.ref, '/master') - needs: test + deploy: runs-on: ubuntu-latest + needs: test + if: endsWith(github.ref, '/master') + permissions: + id-token: write + contents: write steps: - - uses: actions/checkout@v2 + - uses: actions/checkout@v4 - - name: Set up Python ${{ matrix.python-version }} - uses: actions/setup-python@v2 + - name: Set up Python + uses: actions/setup-python@v5 with: python-version: 3.8 @@ -61,26 +68,33 @@ jobs: - name: Fetch version id: fetch_version - run: echo "::set-output name=version_nr::$(poetry version -s)" + run: echo "version_nr=$(poetry version -s)" >> $GITHUB_OUTPUT - name: Build a binary wheel and a source tarball run: | - poetry build + poetry build --no-interaction + + - name: Test PyPI Publishing + uses: pypa/gh-action-pypi-publish@release/v1 + with: + password: ${{ secrets.TEST_PYPI_DEPLOYMENT_API_KEY }} + repository-url: https://test.pypi.org/legacy/ + skip-existing: true - - name: Create Release - id: create_release - uses: actions/create-release@v1 + - name: Create GitHub Release + id: create_gh_release + uses: ncipollo/release-action@v1 env: - # use token provided by Actions - GITHUB_TOKEN: ${{ secrets.GITHUB_TOKEN }} VERSION: ${{ steps.fetch_version.outputs.version_nr }} with: - tag_name: ${{env.VERSION}} - release_name: Release ${{env.VERSION}} + tag: ${{env.VERSION}} + name: Release ${{env.VERSION}} draft: false prerelease: false + skipIfReleaseExists: true - name: PyPI Publishing uses: pypa/gh-action-pypi-publish@release/v1 with: password: ${{ secrets.PYPI_DEPLOYMENT_API_KEY }} + skip-existing: true diff --git a/.pre-commit-config.yaml b/.pre-commit-config.yaml index 565deb5..220aa73 100644 --- a/.pre-commit-config.yaml +++ b/.pre-commit-config.yaml @@ -1,82 +1,74 @@ repos: - - repo: https://github.com/pre-commit/pre-commit-hooks - rev: v4.4.0 - hooks: - - id: check-ast # Is it valid Python? - - id: debug-statements # no debugging statements used - - id: trailing-whitespace - - id: end-of-file-fixer - - id: check-yaml - - id: check-added-large-files - - id: check-case-conflict - - id: check-merge-conflict - # - id: name-tests-test - - id: check-docstring-first - - id: requirements-txt-fixer - - id: detect-private-key - # - id: check-executables-have-shebangs + - repo: https://github.com/pre-commit/pre-commit-hooks + rev: v4.6.0 + hooks: + - id: check-ast # Is it valid Python? + - id: debug-statements # no debugging statements used + - id: trailing-whitespace + - id: end-of-file-fixer + - id: check-yaml + - id: check-added-large-files + - id: check-case-conflict + - id: check-merge-conflict + # - id: name-tests-test + - id: check-docstring-first + - id: requirements-txt-fixer + - id: detect-private-key + # - id: check-executables-have-shebangs - - repo: https://github.com/pycqa/isort - rev: 5.12.0 - hooks: - - id: isort - args: - - --profile=black - - --filter-files + - repo: https://github.com/astral-sh/ruff-pre-commit + rev: v0.3.5 + hooks: + # linter. + - id: ruff + args: [ --fix ] + - id: ruff-format - - repo: https://github.com/psf/black - rev: 23.1.0 - hooks: - - id: black - language_version: python3 - args: - - --line-length=120 + - repo: https://github.com/asottile/blacken-docs + rev: 1.16.0 + hooks: + - id: blacken-docs + additional_dependencies: [ black==22.1 ] - - repo: https://github.com/asottile/blacken-docs - rev: 1.13.0 - hooks: - - id: blacken-docs - additional_dependencies: [ black==22.1 ] + - repo: https://github.com/pycqa/flake8 + rev: 7.0.0 + hooks: + - id: flake8 + exclude: (docs|tests) + args: + - --max-line-length=120 + - --ignore=E501,W503 + additional_dependencies: + - flake8-bugbear + - flake8-comprehensions + - flake8-tidy-imports - - repo: https://github.com/pycqa/flake8 - rev: 6.0.0 - hooks: - - id: flake8 - exclude: (docs|tests) - args: - - --max-line-length=120 - - --ignore=E501,W503 - additional_dependencies: - - flake8-bugbear - - flake8-comprehensions - - flake8-tidy-imports + # - repo: https://github.com/mgedmin/check-manifest + # rev: "0.49" + # hooks: + # - id: check-manifest + # args: [ "--no-build-isolation", "--ignore", "*.png,docs/*,paper/*,scripts/*,setup.py,publish.py,readthedocs.yml,poetry.lock" ] + # additional_dependencies: [ numpy, poetry==1.3.2] -# - repo: https://github.com/mgedmin/check-manifest -# rev: "0.49" -# hooks: -# - id: check-manifest -# args: [ "--no-build-isolation", "--ignore", "*.png,docs/*,paper/*,scripts/*,setup.py,publish.py,readthedocs.yml,poetry.lock" ] -# additional_dependencies: [ numpy, poetry==1.3.2] + # TODO sphinx check + # - repo: https://github.com/myint/rstcheck + # rev: 'v3.3.1' + # hooks: + # - id: rstcheck - # TODO sphinx check - # - repo: https://github.com/myint/rstcheck - # rev: 'v3.3.1' - # hooks: - # - id: rstcheck + - repo: https://github.com/asottile/pyupgrade + rev: v3.15.2 + hooks: + - id: pyupgrade - - repo: https://github.com/asottile/pyupgrade - rev: v3.3.1 - hooks: - - id: pyupgrade + # # very detailed linting: + # - repo: https://github.com/pycqa/pylint + # rev: pylint-2.6.0 + # hooks: + # - id: pylint - # # very detailed linting: - # - repo: https://github.com/pycqa/pylint - # rev: pylint-2.6.0 - # hooks: - # - id: pylint - - - repo: https://github.com/pre-commit/mirrors-mypy - rev: v1.0.0 - hooks: - - id: mypy - exclude: ^((tests|scripts)/) + - repo: https://github.com/pre-commit/mirrors-mypy + rev: v1.9.0 + hooks: + - id: mypy + exclude: ^((tests|scripts)/) diff --git a/CHANGELOG.rst b/CHANGELOG.rst index 1347035..d269af9 100755 --- a/CHANGELOG.rst +++ b/CHANGELOG.rst @@ -54,6 +54,18 @@ idea: - the evaluation of subtrees is independent and could theoretically be done in parallel probably not worth the effort. more reasonable to just evaluate multiple polynomials in parallel +3.x.x (TBA) +__________________ + + +internal: + +- updated GitHub Actions workflow: skip publishing existing versions +- included ruff pre commit hook +- updated dependency lock +- included tests for python 3.12 + + 3.1.0 (2023-02-15) __________________ diff --git a/Makefile b/Makefile index f051f6f..24c18f3 100644 --- a/Makefile +++ b/Makefile @@ -6,7 +6,7 @@ update: poetry update install: - poetry install --all-extras + poetry install --with docs,dev --all-extras --sync VENV_NAME=multivar_horner venv: @@ -17,9 +17,16 @@ hook: pre-commit install pre-commit run --all-files -hook2: +hookup: pre-commit autoupdate +test: + poetry run pytest + +tox: + tox + + clean: rm -rf .pytest_cache .coverage coverage.xml tests/__pycache__ src/__pycache__ mlruns/ .mypyp_cache/ diff --git a/docs/conf.py b/docs/conf.py index 35290fd..f848ac1 100644 --- a/docs/conf.py +++ b/docs/conf.py @@ -25,15 +25,15 @@ sys.path.insert(0, os.path.join(project_root)) # needed for auto document, ATTENTION: must then be installed during online build! -import multivar_horner +import multivar_horner # noqa: E402 Module level import not at top of file print(multivar_horner) # -- Project information ----------------------------------------------------- project = "multivar_horner" -copyright = "2018, Jannik Michelfeit" -author = "Jannik Michelfeit" +copyright = "2018, Jannik Kissinger" +author = "Jannik Kissinger" # The full version, including alpha/beta/rc tags. release = subprocess.getoutput("poetry version -s") diff --git a/multivar_horner/__init__.py b/multivar_horner/__init__.py index 52eebe1..c3ae439 100644 --- a/multivar_horner/__init__.py +++ b/multivar_horner/__init__.py @@ -1,5 +1,13 @@ from multivar_horner.classes.abstract_poly import load_pickle -from multivar_horner.classes.horner_poly import HornerMultivarPolynomial, HornerMultivarPolynomialOpt +from multivar_horner.classes.horner_poly import ( + HornerMultivarPolynomial, + HornerMultivarPolynomialOpt, +) from multivar_horner.classes.regular_poly import MultivarPolynomial -__all__ = ["HornerMultivarPolynomial", "MultivarPolynomial", "HornerMultivarPolynomialOpt", "load_pickle"] +__all__ = [ + "HornerMultivarPolynomial", + "MultivarPolynomial", + "HornerMultivarPolynomialOpt", + "load_pickle", +] diff --git a/multivar_horner/_numba_replacements.py b/multivar_horner/_numba_replacements.py index 71b8666..59025ea 100644 --- a/multivar_horner/_numba_replacements.py +++ b/multivar_horner/_numba_replacements.py @@ -1,4 +1,4 @@ -""" 'transparent' numba functionality replacements +"""'transparent' numba functionality replacements njit decorator data types diff --git a/multivar_horner/c_evaluation.py b/multivar_horner/c_evaluation.py index f447385..d7070d8 100644 --- a/multivar_horner/c_evaluation.py +++ b/multivar_horner/c_evaluation.py @@ -36,7 +36,9 @@ def write_c_file( instr = "#include \n" # NOTE: the coefficient array will be used to store intermediary results # -> copy to use independent instance of array (NO pointer to external array!) - func_def = f"{DOUBLE} {EVAL_FCT}({DOUBLE} x[{nr_dims}], {DOUBLE} {COEFFS}[{nr_coeffs}])" + func_def = ( + f"{DOUBLE} {EVAL_FCT}({DOUBLE} x[{nr_dims}], {DOUBLE} {COEFFS}[{nr_coeffs}])" + ) # declare function ("header") instr += f"{func_def};\n" # function definition diff --git a/multivar_horner/classes/abstract_poly.py b/multivar_horner/classes/abstract_poly.py index 32b20ba..fcf516e 100644 --- a/multivar_horner/classes/abstract_poly.py +++ b/multivar_horner/classes/abstract_poly.py @@ -58,16 +58,22 @@ def __init__( self.compute_representation: bool = compute_representation if rectify_input: - coefficients, exponents = rectify_construction_parameters(coefficients, exponents) + coefficients, exponents = rectify_construction_parameters( + coefficients, exponents + ) validate_construction_parameters(coefficients, exponents) self.coefficients: np.ndarray = coefficients self.exponents: np.ndarray = exponents self.num_monomials: int = self.exponents.shape[0] self.dim: int = self.exponents.shape[1] - self.unused_variables = np.where(~np.any(self.exponents.astype(BOOL_DTYPE), axis=1))[0] + self.unused_variables = np.where( + ~np.any(self.exponents.astype(BOOL_DTYPE), axis=1) + )[0] self.total_degree: int = np.max(np.sum(self.exponents, axis=0)) - self.euclidean_degree: float = np.max(np.linalg.norm(self.exponents, ord=2, axis=0)) + self.euclidean_degree: float = np.max( + np.linalg.norm(self.exponents, ord=2, axis=0) + ) self.maximal_degree: int = np.max(self.exponents) self.num_ops: int = 0 self.representation: str @@ -158,7 +164,9 @@ def get_partial_derivative(self, i: int, *args, **kwargs) -> "AbstractPolynomial # multiply the coefficients with the exponent of the i-th coordinate # f(x) = a x^b # f'(x) = ab x^(b-1) - new_coefficients = np.multiply(new_coefficients.flatten(), new_exponents[:, coord_index]) + new_coefficients = np.multiply( + new_coefficients.flatten(), new_exponents[:, coord_index] + ) new_coefficients = new_coefficients.reshape(-1, 1) # reduce the the exponent of the i-th coordinate by 1 @@ -175,7 +183,10 @@ def get_gradient(self, *args, **kwargs) -> List["AbstractPolynomial"]: Returns: the list of all partial derivatives """ - return [self.get_partial_derivative(i, *args, **kwargs) for i in range(1, self.dim + 1)] + return [ + self.get_partial_derivative(i, *args, **kwargs) + for i in range(1, self.dim + 1) + ] def change_coefficients( self, diff --git a/multivar_horner/classes/factorisation.py b/multivar_horner/classes/factorisation.py index 26a6240..682b34a 100644 --- a/multivar_horner/classes/factorisation.py +++ b/multivar_horner/classes/factorisation.py @@ -1,6 +1,10 @@ import numpy as np -from multivar_horner.classes.helpers import AbstractFactor, FactorContainer, PriorityQueue2D +from multivar_horner.classes.helpers import ( + AbstractFactor, + FactorContainer, + PriorityQueue2D, +) from multivar_horner.global_settings import BOOL_DTYPE, ID_ADD, ID_MULT, UINT_DTYPE from multivar_horner.helpers_fcts_numba import ( compile_valid_options, @@ -39,7 +43,9 @@ class FactorisationNode: def __init__(self, factor, node1_fact, node2, factorized_rows, non_factorized_rows): self.factor: AbstractFactor = factor self.node1_fact: BasePolynomialNode = node1_fact - self.node2: BasePolynomialNode = node2 # can be None if all monomials shared the factor + self.node2: BasePolynomialNode = ( + node2 # can be None if all monomials shared the factor + ) self.factorized_rows = factorized_rows self.non_factorized_rows = non_factorized_rows self.value_idx: int @@ -144,7 +150,9 @@ class OptimalFactorisationNode(FactorisationNode): node2: "OptimalPolynomialNode" def __init__(self, factor, node1_fact, node2, factorized_rows, non_factorized_rows): - super().__init__(factor, node1_fact, node2, factorized_rows, non_factorized_rows) + super().__init__( + factor, node1_fact, node2, factorized_rows, non_factorized_rows + ) self.cost_estimate: int = 0 # IDEA: when different factorisations have the same cost estimate, # favour the one which is factorised the most already @@ -153,13 +161,17 @@ def __init__(self, factor, node1_fact, node2, factorized_rows, non_factorized_ro self.update_properties() def update_properties(self): - self.cost_estimate = factor_num_ops(*self.factor) + self.node1_fact.cost_estimate + self.cost_estimate = ( + factor_num_ops(*self.factor) + self.node1_fact.cost_estimate + ) self.factorisation_measure = self.node1_fact.factorisation_measure if self.node2 is not None: self.cost_estimate += self.node2.cost_estimate self.factorisation_measure += self.node2.factorisation_measure - self.fully_factorized = self.node1_fact.fully_factorized and self.node2.fully_factorized + self.fully_factorized = ( + self.node1_fact.fully_factorized and self.node2.fully_factorized + ) else: self.fully_factorized = self.node1_fact.fully_factorized @@ -265,7 +277,9 @@ def choose_option(self): return max_usage_option - def get_string_representation(self, coefficients=None, coeff_fmt_str="{:.2}", factor_fmt_str="x_{dim}^{exp}"): + def get_string_representation( + self, coefficients=None, coeff_fmt_str="{:.2}", factor_fmt_str="x_{dim}^{exp}" + ): if self.has_children: return self.get_child().get_string_representation( coefficients=coefficients, @@ -278,13 +292,17 @@ def get_string_representation(self, coefficients=None, coeff_fmt_str="{:.2}", fa if coefficients is None: coeff_repr = "c" else: - coeff_idx = self.value_idxs[i] # look up the correct index of the coefficient + coeff_idx = self.value_idxs[ + i + ] # look up the correct index of the coefficient coeff_repr = coeff_fmt_str.format(coefficients[coeff_idx, 0]) monomial_repr = [coeff_repr] for dim, exp in enumerate(exp_vect): if exp > 0: - monomial_repr.append(factor_fmt_str.format(**{"dim": dim + 1, "exp": exp})) + monomial_repr.append( + factor_fmt_str.format(**{"dim": dim + 1, "exp": exp}) + ) monomial_representations.append(" ".join(monomial_repr)) return " + ".join(monomial_representations) @@ -324,7 +342,9 @@ def factorize(self, dim, exp): # assert exponents1_fact.shape[0] + exponents2.shape[0] == self.num_monomials factor = (dim, exp) - child = self.factorisation_class(factor, node1_fact, node2, factorized_rows, non_factorized_rows) + child = self.factorisation_class( + factor, node1_fact, node2, factorized_rows, non_factorized_rows + ) self.store_child(child) def store_child(self, child: "BasePolynomialNode"): @@ -354,7 +374,9 @@ def compile_factors(self, factor_container: FactorContainer, coefficient_idxs): # for evaluation the sum of all evaluated monomials multiplied with their coefficients has to be computed # p = c1 * mon1 + c2 * mon2 ... # create factors representing the remaining monomials - self.factors = factor_container.get_factors(self.exponents) # retains the ordering! + self.factors = factor_container.get_factors( + self.exponents + ) # retains the ordering! # remember where in the coefficient array the coefficients of this polynomial are being stored self.value_idxs = coefficient_idxs diff --git a/multivar_horner/classes/helpers.py b/multivar_horner/classes/helpers.py index 2d9f30a..85120b1 100644 --- a/multivar_horner/classes/helpers.py +++ b/multivar_horner/classes/helpers.py @@ -133,14 +133,18 @@ class ScalarFactor(AbstractFactor): def __init__(self, factor_dimension, factor_exponent): self.dimension = factor_dimension self.exponent = factor_exponent - self.value_idx = None # initialize the idx with None to catch faulty evaluation tries + self.value_idx = ( + None # initialize the idx with None to catch faulty evaluation tries + ) def __str__(self, factor_fmt_str="x_{dim}^{exp}", *args, **kwargs): # NOTE: variable numbering starts with 1: x_1, x_2, ... # if self.exponent == 1: # return 'x_{}'.format(self.dimension + 1) - return factor_fmt_str.format(**{"dim": self.dimension + 1, "exp": self.exponent}) + return factor_fmt_str.format( + **{"dim": self.dimension + 1, "exp": self.exponent} + ) def __repr__(self, *args, **kwargs): return self.__str__(*args, **kwargs) @@ -348,9 +352,13 @@ def get_factors(self, exponent_matrix): if len(scalar_factors) == 0: factor = None # monomial consists of no factors elif len(scalar_factors) == 1: - factor = scalar_factors[0] # monomial consists of a single scalar factor + factor = scalar_factors[ + 0 + ] # monomial consists of a single scalar factor else: - factor = self.get_factor(property_list) # monomial consists of a multiple scalar factors + factor = self.get_factor( + property_list + ) # monomial consists of a multiple scalar factors all_factors.append(factor) diff --git a/multivar_horner/classes/horner_poly.py b/multivar_horner/classes/horner_poly.py index ecaec3a..5dd1594 100644 --- a/multivar_horner/classes/horner_poly.py +++ b/multivar_horner/classes/horner_poly.py @@ -6,7 +6,12 @@ import numpy as np from multivar_horner import c_evaluation -from multivar_horner.c_evaluation import COMPILED_C_ENDING, compile_c_file, get_compiler, write_c_file +from multivar_horner.c_evaluation import ( + COMPILED_C_ENDING, + compile_c_file, + get_compiler, + write_c_file, +) from multivar_horner.classes.abstract_poly import AbstractPolynomial from multivar_horner.classes.factorisation import ( BasePolynomialNode, @@ -139,7 +144,9 @@ def __init__( *args, **kwargs, ): - super().__init__(coefficients, exponents, rectify_input, compute_representation, verbose) + super().__init__( + coefficients, exponents, rectify_input, compute_representation, verbose + ) self.root_class: Type = HeuristicFactorisationRoot self.keep_tree: bool = keep_tree self.value_array_length: int @@ -196,10 +203,15 @@ def _compute_factorisation(self): # NOTE: do NOT automatically create all scalar factors with exponent 1 # (they might be unused, since the polynomial must not actually depend on all variables) factor_container = FactorContainer() - factorisation_tree: BasePolynomialNode = self.root_class(self.exponents, factor_container) + factorisation_tree: BasePolynomialNode = self.root_class( + self.exponents, factor_container + ) self.root_value_idx = factorisation_tree.value_idx self.value_array_length = self.num_monomials + len(factor_container) - self.factorisation: Tuple[BasePolynomialNode, FactorContainer] = (factorisation_tree, factor_container) + self.factorisation: Tuple[BasePolynomialNode, FactorContainer] = ( + factorisation_tree, + factor_container, + ) @property def factorisation_tree(self) -> BasePolynomialNode: @@ -223,11 +235,15 @@ def compute_string_representation( repre = f"[#ops={self.num_ops}] p(x)" try: tree = self.factorisation_tree - repre += " = " + tree.get_string_representation(self.coefficients, coeff_fmt_str, factor_fmt_str) + repre += " = " + tree.get_string_representation( + self.coefficients, coeff_fmt_str, factor_fmt_str + ) # exponentiation with 1 won't cause an operation in this representation # but are present in the string representation due to string formatting restrictions # -> they should not be displayed (misleading) - repre = repre.replace("^1", "") # <- workaround for the default string format + repre = repre.replace( + "^1", "" + ) # <- workaround for the default string format except AttributeError: pass # self.factorisation_tree does not exist self.representation = repre @@ -291,7 +307,9 @@ def _compile_recipes(self): for monomial_factor in self.factor_container.monomial_factors: monomial_factor.value_idx = value_idx value_idx += 1 - monomial_factor.factorisation_idxs = [f.value_idx for f in monomial_factor.scalar_factors] + monomial_factor.factorisation_idxs = [ + f.value_idx for f in monomial_factor.scalar_factors + ] monomial_instr = monomial_factor.get_recipe() monomial_recipe += monomial_instr self.num_ops += 1 # every monomial instruction encodes one multiplication @@ -301,20 +319,33 @@ def _compile_recipes(self): # convert the recipes into the data types expected by the jit compiled functions # and store them tree_ops = np.array(tree_ops, dtype=BOOL_DTYPE) - self.num_ops += len(tree_ops) - np.count_nonzero(tree_ops) # every 0/False encodes a multiplication + self.num_ops += len(tree_ops) - np.count_nonzero( + tree_ops + ) # every 0/False encodes a multiplication copy_recipe = np.array(copy_recipe, dtype=UINT_DTYPE).reshape((-1, 2)) scalar_recipe = np.array(scalar_recipe, dtype=UINT_DTYPE).reshape((-1, 3)) monomial_recipe = np.array(monomial_recipe, dtype=UINT_DTYPE).reshape((-1, 3)) tree_recipe = np.array(tree_recipe, dtype=UINT_DTYPE).reshape((-1, 2)) # IMPORTANT: strict ordering required! - self.recipe = (copy_recipe, scalar_recipe, monomial_recipe, tree_recipe, tree_ops) + self.recipe = ( + copy_recipe, + scalar_recipe, + monomial_recipe, + tree_recipe, + tree_ops, + ) self._pickle_recipe() def _pickle_recipe(self): path = self.recipe_file self.print(f'storing recipe in file "{path}"') - pickle_obj = (self.recipe, self.num_ops, self.value_array_length, self.root_value_idx) + pickle_obj = ( + self.recipe, + self.num_ops, + self.value_array_length, + self.root_value_idx, + ) with open(path, "wb") as f: pickle.dump(pickle_obj, f) @@ -325,7 +356,9 @@ def _load_recipe(self): self.print(f'loading recipe from file "{path}"') with open(path, "rb") as f: pickle_obj = pickle.load(f) - self.recipe, self.num_ops, self.value_array_length, self.root_value_idx = pickle_obj + self.recipe, self.num_ops, self.value_array_length, self.root_value_idx = ( + pickle_obj + ) def eval(self, x: TYPE_1D_FLOAT, rectify_input: bool = False) -> float: """computes the value of the polynomial at query point x @@ -451,7 +484,9 @@ def _write_c_file(self): "need a stored factorisation tree, but the reference to it has already been deleted. " "initialise class with 'keep_tree=True`" ) - self.num_ops = write_c_file(self.num_monomials, self.dim, path_out, factorisation, self.verbose) + self.num_ops = write_c_file( + self.num_monomials, self.dim, path_out, factorisation, self.verbose + ) def get_c_instructions(self) -> str: path = self.c_file diff --git a/multivar_horner/classes/regular_poly.py b/multivar_horner/classes/regular_poly.py index d6ea4f1..124af2d 100644 --- a/multivar_horner/classes/regular_poly.py +++ b/multivar_horner/classes/regular_poly.py @@ -51,7 +51,9 @@ def __init__( *args, **kwargs, ): - super().__init__(coefficients, exponents, rectify_input, compute_representation, verbose) + super().__init__( + coefficients, exponents, rectify_input, compute_representation, verbose + ) # NOTE: count the number of multiplications of the representation # not the actual amount of operations required by the naive evaluation with numpy arrays @@ -73,7 +75,9 @@ def compute_string_representation( monomial = [coeff_fmt_str.format(self.coefficients[i, 0])] for dim, exp in enumerate(exp_vect): # show all operations, even 1 * x_i^0 - monomial.append(factor_fmt_str.format(**{"dim": dim + 1, "exp": exp})) + monomial.append( + factor_fmt_str.format(**{"dim": dim + 1, "exp": exp}) + ) monomials.append(" ".join(monomial)) diff --git a/multivar_horner/global_settings.py b/multivar_horner/global_settings.py index 2e3814c..2480c50 100644 --- a/multivar_horner/global_settings.py +++ b/multivar_horner/global_settings.py @@ -11,7 +11,9 @@ UINT_DTYPE = numpy.uint32 # u4 = 4byte unsigned integer FLOAT_DTYPE = numpy.float64 # f8 = 8byte float, default # FLOAT_DTYPE = numpy.float128 # high precision for numerical tests, also disable jit compilation -COMPLEX_DTYPE = numpy.cdouble # Complex number, represented by two double-precision floats +COMPLEX_DTYPE = ( + numpy.cdouble +) # Complex number, represented by two double-precision floats BOOL_DTYPE = bool # python typing diff --git a/multivar_horner/helper_fcts.py b/multivar_horner/helper_fcts.py index b2c3767..ca77ce7 100644 --- a/multivar_horner/helper_fcts.py +++ b/multivar_horner/helper_fcts.py @@ -6,7 +6,9 @@ def rectify_coefficients(coefficients): - rectified_coefficients = np.atleast_2d(np.asarray(coefficients, dtype=FLOAT_DTYPE)).reshape(-1, 1) + rectified_coefficients = np.atleast_2d( + np.asarray(coefficients, dtype=FLOAT_DTYPE) + ).reshape(-1, 1) return rectified_coefficients @@ -43,7 +45,9 @@ def validate_coefficients(coefficients) -> None: if not isinstance(coefficients, np.ndarray): raise TypeError("coefficients must be given as numpy.ndarray") if coefficients.dtype.type is not FLOAT_DTYPE: - raise TypeError(f"coefficients must have dtype {FLOAT_DTYPE} but have dtype {coefficients.dtype.type}") + raise TypeError( + f"coefficients must have dtype {FLOAT_DTYPE} but have dtype {coefficients.dtype.type}" + ) if len(coefficients.shape) != 2 or coefficients.shape[1] != 1: raise ValueError("coefficients must be given as a [M, 1] ndarray") if coefficients.shape[0] == 0: @@ -52,7 +56,9 @@ def validate_coefficients(coefficients) -> None: # NOTE: "0 coefficients" are allowed because coefficients should be changeable! -def validate_construction_parameters(coefficients: np.ndarray, exponents: np.ndarray) -> None: +def validate_construction_parameters( + coefficients: np.ndarray, exponents: np.ndarray +) -> None: validate_coefficients(coefficients) if not isinstance(exponents, np.ndarray): @@ -62,7 +68,9 @@ def validate_construction_parameters(coefficients: np.ndarray, exponents: np.nda # value check is being done in rectification fct raise TypeError(f"exponents must have dtype {UINT_DTYPE}") if len(exponents.shape) != 2: - raise ValueError("exponents must be given as a [M, N] ndarray (a list of exponent vectors)") + raise ValueError( + "exponents must be given as a [M, N] ndarray (a list of exponent vectors)" + ) if np.any(exponents < 0): raise ValueError("exponents must not be negative") if exponents.shape != np.unique(exponents, axis=0).shape: @@ -79,4 +87,6 @@ def validate_query_point(x: np.ndarray, dim: int, dtype: Type = FLOAT_DTYPE) -> if len(x.shape) != 1: raise ValueError("the query point x must be given as a ndarray of shape [N]") if x.shape[0] != dim: - raise ValueError(f"the query point x does not have the required dimensionality {dim}") + raise ValueError( + f"the query point x does not have the required dimensionality {dim}" + ) diff --git a/multivar_horner/helpers_fcts_numba.py b/multivar_horner/helpers_fcts_numba.py index 638acc0..da1ed81 100644 --- a/multivar_horner/helpers_fcts_numba.py +++ b/multivar_horner/helpers_fcts_numba.py @@ -209,7 +209,9 @@ def compile_usage(dim, usage_vector, unique_exponents, exponent_matrix): @njit(void(INT, BOOL_1D, UINT_1D, UINT_1D, UINT_2D), cache=True) -def compile_valid_options(dim, valid_option_vector, usage_vector, unique_exponents, exponent_matrix): +def compile_valid_options( + dim, valid_option_vector, usage_vector, unique_exponents, exponent_matrix +): """compute the vector of valid options :param dim: diff --git a/poetry.lock b/poetry.lock index 0c56370..4d08907 100644 --- a/poetry.lock +++ b/poetry.lock @@ -1,10 +1,9 @@ -# This file is automatically @generated by Poetry and should not be changed by hand. +# This file is automatically @generated by Poetry 1.8.2 and should not be changed by hand. 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{file = "zipp-3.13.0-py3-none-any.whl", hash = "sha256:e8b2a36ea17df80ffe9e2c4fda3f693c3dad6df1697d3cd3af232db680950b0b"}, - {file = "zipp-3.13.0.tar.gz", hash = "sha256:23f70e964bc11a34cef175bc90ba2914e1e4545ea1e3e2f67c079671883f9cb6"}, + {file = "zipp-3.18.1-py3-none-any.whl", hash = "sha256:206f5a15f2af3dbaee80769fb7dc6f249695e940acca08dfb2a4769fe61e538b"}, + {file = "zipp-3.18.1.tar.gz", hash = "sha256:2884ed22e7d8961de1c9a05142eb69a247f120291bc0206a00a7642f09b5b715"}, ] [package.extras] -docs = ["furo", "jaraco.packaging (>=9)", "jaraco.tidelift (>=1.4)", "rst.linker (>=1.9)", "sphinx (>=3.5)", "sphinx-lint"] -testing = ["flake8 (<5)", "func-timeout", "jaraco.functools", "jaraco.itertools", "more-itertools", "pytest (>=6)", "pytest-black (>=0.3.7)", "pytest-checkdocs (>=2.4)", "pytest-cov", "pytest-enabler (>=1.3)", "pytest-flake8", "pytest-mypy (>=0.9.1)"] +docs = ["furo", "jaraco.packaging (>=9.3)", "jaraco.tidelift (>=1.4)", "rst.linker (>=1.9)", "sphinx (>=3.5)", "sphinx-lint"] +testing = ["big-O", "jaraco.functools", "jaraco.itertools", "more-itertools", "pytest (>=6)", "pytest-checkdocs (>=2.4)", "pytest-cov", "pytest-enabler (>=2.2)", "pytest-ignore-flaky", "pytest-mypy", "pytest-ruff (>=0.2.1)"] [extras] -numba = ["numba"] +numba = ["numba", "numba"] [metadata] lock-version = "2.0" python-versions = ">=3.8,<4" -content-hash = "4be543fbaa2a56a2501bdea8cddd1eb6447d8c002ceb726ac6de797d46577994" +content-hash = "088d85a91038f3f49dfa60875ce9ce2b26e6a8fa200fb91f0f3e627262fbc163" diff --git a/pyproject.toml b/pyproject.toml index 247e1d7..cb5e988 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -36,12 +36,27 @@ include = [ [tool.poetry.dependencies] python = ">=3.8,<4" -numpy = ">=1.18,<2" -numba = { version = ">=0.56,<1", optional = true } +numpy = [ + { version = ">=1.21,<2", python = "<3.9" }, + { version = ">=1.23,<2", python = ">=3.9" } +] +numba = [ + { version = ">=0.56,<1", python = "<3.12", optional = true }, + { version = ">=0.59,<1", python = ">=3.12", optional = true } +] [tool.poetry.extras] numba = ["numba"] + +[tool.poetry.group.docs] +optional = true + +[tool.poetry.group.docs.dependencies] +Sphinx = "^5" +sphinx-rtd-theme = "^1" +sphinxcontrib-bibtex = "*" + [tool.poetry.group.dev.dependencies] pytest = "^7" pytest-cov = "*" @@ -51,11 +66,49 @@ twine = "*" pre-commit = "*" rstcheck = "*" #build = "^0.8.0" -# docs -Sphinx = "^5" -sphinxcontrib-bibtex = "*" -sphinx-rtd-theme = "*" +ruff = "^0.3.2" [build-system] requires = ["poetry-core>=1.0.7", "poetry==1.3.2"] build-backend = "poetry.core.masonry.api" + + +[tool.ruff] +target-version = "py38" +src = ["multivar_horner", "tests"] + +[tool.ruff.lint.isort] +known-local-folder = ["multivar_horner"] + +[tool.tox] +legacy_tox_ini = """ + [tox] + isolated_build = true + envlist = + docs,py{38,39,310,311,312}{,-numba} + + [gh-actions] + python = + 3.8: py38{,-numba} + 3.9: py39{,-numba} + 3.10: py310{,-numba} + 3.11: py311{,-numba} + 3.12: py312{,-numba} + + + [testenv:docs] + description = build documentation + basepython = python3.12 + allowlist_externals = poetry,sphinx-build + commands = + poetry install -v --with docs + sphinx-build -d "{envtmpdir}{/}doctree" docs "{toxworkdir}{/}docs_out" --color -b html + python -c 'print(r"documentation available under file://{toxworkdir}{/}docs_out{/}index.html")' + + [testenv] + allowlist_externals = poetry + commands = + !numba: poetry install -v + numba: poetry install -v --extras numba + poetry run pytest {posargs} +""" diff --git a/scripts/numerical_stability.py b/scripts/numerical_stability.py index 0ec2214..9176307 100644 --- a/scripts/numerical_stability.py +++ b/scripts/numerical_stability.py @@ -44,7 +44,9 @@ def evaluate_numerical_error(dim, max_degree): # debug: validate_input=True nr_monomials = exponents.shape[0] # find factorisation (expensive) - poly_horner = HornerMultivarPolynomial(coefficients, exponents, validate_input=True) + poly_horner = HornerMultivarPolynomial( + coefficients, exponents, validate_input=True + ) poly = MultivarPolynomial(coefficients, exponents) # # for evaluating only the polynomial properties without the numerical errors: @@ -53,7 +55,9 @@ def evaluate_numerical_error(dim, max_degree): # continue coefficients = coefficients.astype(DTYPE_HIGH_PREC) - poly_high_prec = MultivarPolynomial(coefficients, exponents, validate_input=False) + poly_high_prec = MultivarPolynomial( + coefficients, exponents, validate_input=False + ) for coeff_ctr in range(NR_COEFF_CHANGES): # evaluation @ uniformly random point @@ -61,11 +65,15 @@ def evaluate_numerical_error(dim, max_degree): x = x.astype(FLOAT_DTYPE) # simply change coefficients of the found factorisation (cheap) - coefficients = (np.random.rand(nr_monomials, 1) - 0.5) * (2 * MAX_COEFF_MAGNITUDE) + coefficients = (np.random.rand(nr_monomials, 1) - 0.5) * ( + 2 * MAX_COEFF_MAGNITUDE + ) coefficients = coefficients.astype(FLOAT_DTYPE) # is testing for in_place=True at the same time - poly_horner.change_coefficients(coefficients, validate_input=True, in_place=True) + poly_horner.change_coefficients( + coefficients, validate_input=True, in_place=True + ) p_x_horner = poly_horner.eval(x) poly.change_coefficients(coefficients, validate_input=True, in_place=True) @@ -85,7 +93,9 @@ def evaluate_numerical_error(dim, max_degree): # NOTE: need to deactivate jit compilation of naive approach # use higher prevision # suppress input validation - poly_high_prec.change_coefficients(coefficients, validate_input=False, in_place=True) + poly_high_prec.change_coefficients( + coefficients, validate_input=False, in_place=True + ) x = x.astype(DTYPE_HIGH_PREC) p_x_expected = poly_high_prec.eval(x) @@ -104,7 +114,9 @@ def evaluate_numerical_error(dim, max_degree): # pickle.dump(coefficients, f) # with open('exponents.pickle', 'wb') as f: # pickle.dump(exponents, f) - raise AssertionError(f"numerical error {max_error:.2e} exceeded limit of {MAX_NUMERICAL_ERROR :.2e} ") + raise AssertionError( + f"numerical error {max_error:.2e} exceeded limit of {MAX_NUMERICAL_ERROR :.2e} " + ) ctr_total += 1 sys.stdout.write("\n") # move the cursor to the next line @@ -124,7 +136,9 @@ def test_numerical_stability(self): print("\nevaluating the numerical error:") results = [] for dim, max_degree in product(DIM_RANGE, DEGREE_RANGE): - results += evaluate_numerical_error(dim, max_degree) # do not append list as entry + results += evaluate_numerical_error( + dim, max_degree + ) # do not append list as entry with open(TEST_RESULTS_PICKLE, "wb") as f: print(f"exporting numerical test results in {TEST_RESULTS_PICKLE}") diff --git a/tests/helpers.py b/tests/helpers.py index 9d1cbe3..492ca60 100644 --- a/tests/helpers.py +++ b/tests/helpers.py @@ -23,7 +23,9 @@ def proto_test_case(data, fct): assert all_good -def get_rnd_poly_properties(all_exponents, degree, max_abs_coeff=1.0, integer_coeffs=False, enforce_degree=False): +def get_rnd_poly_properties( + all_exponents, degree, max_abs_coeff=1.0, integer_coeffs=False, enforce_degree=False +): """ for meaningful test results uniformly distributed random test polynomials are required -> every possible polynomial should appear with equal probability @@ -63,7 +65,9 @@ def get_rnd_poly_properties(all_exponents, degree, max_abs_coeff=1.0, integer_co exponents = all_exponents[row_idxs, :] nr_monomials = exponents.shape[0] - coefficients = (np.random.rand(nr_monomials, 1) - 0.5) * (2 * max_abs_coeff) # [ -max_abs_coeff; max_abs_coeff] + coefficients = (np.random.rand(nr_monomials, 1) - 0.5) * ( + 2 * max_abs_coeff + ) # [ -max_abs_coeff; max_abs_coeff] coefficients = coefficients.astype(FLOAT_DTYPE) if integer_coeffs: coefficients = np.round(coefficients) @@ -106,7 +110,10 @@ def all_possible_exponents(dim: int, deg: int) -> np.ndarray: def rnd_settings_list(length, dim, degree, *args, **kwargs): all_exponent_vect = all_possible_exponents(dim, degree) - settings_list = [get_rnd_poly_properties(all_exponent_vect, degree, *args, **kwargs) for _ in range(length)] + settings_list = [ + get_rnd_poly_properties(all_exponent_vect, degree, *args, **kwargs) + for _ in range(length) + ] # # random settings should have approx. half the amount of maximal entries on average # num_monomial_entries = 0 @@ -129,4 +136,6 @@ def vectorize(obj): # vectorised version of naive_eval() in multivar_horner.helpers_fcts_numba def naive_eval_reference(X, exponents, coefficients): - return np.dot(np.array([[(x**ex).prod() for ex in exponents] for x in X]), coefficients) + return np.dot( + np.array([[(x**ex).prod() for ex in exponents] for x in X]), coefficients + ) diff --git a/tests/hypothesis_tests.py b/tests/hypothesis_tests.py index 2cb1996..03dea3b 100644 --- a/tests/hypothesis_tests.py +++ b/tests/hypothesis_tests.py @@ -7,7 +7,10 @@ from multivar_horner import HornerMultivarPolynomial, MultivarPolynomial from multivar_horner.global_settings import COMPLEX_DTYPE, FLOAT_DTYPE -from multivar_horner.helper_fcts import rectify_construction_parameters, rectify_query_point +from multivar_horner.helper_fcts import ( + rectify_construction_parameters, + rectify_query_point, +) from tests.helpers import all_possible_exponents REQUIRED_REL_PRECISION = 1e-4 @@ -23,7 +26,10 @@ dimensions = s.integers(min_value=1, max_value=MAX_DIM) poly_degrees = s.integers(min_value=0, max_value=MAX_DEG) unsigned_float_sampling = s.floats( - min_value=FLOAT_MIN_VAL, max_value=FLOAT_MAX_VAL, allow_infinity=False, allow_nan=False + min_value=FLOAT_MIN_VAL, + max_value=FLOAT_MAX_VAL, + allow_infinity=False, + allow_nan=False, ) @@ -57,24 +63,40 @@ def poly_param_sampling(draw) -> Tuple[np.ndarray, np.ndarray]: nr_monomials = draw(s.integers(min_value=1, max_value=nr_monomials_max)) exponent_matrix = possible_exponents[:nr_monomials] - coefficients = draw(s.lists(float_sampling(), min_size=nr_monomials, max_size=nr_monomials)) + coefficients = draw( + s.lists(float_sampling(), min_size=nr_monomials, max_size=nr_monomials) + ) - coefficients, exponent_matrix = rectify_construction_parameters(coefficients, exponent_matrix) + coefficients, exponent_matrix = rectify_construction_parameters( + coefficients, exponent_matrix + ) return coefficients, exponent_matrix @s.composite def poly_sampling(draw) -> Tuple[MultivarPolynomial, HornerMultivarPolynomial]: coefficients, exponents = draw(poly_param_sampling()) - poly = MultivarPolynomial(coefficients, exponents, rectify_input=False, compute_representation=True, verbose=True) + poly = MultivarPolynomial( + coefficients, + exponents, + rectify_input=False, + compute_representation=True, + verbose=True, + ) poly_h = HornerMultivarPolynomial( - coefficients, exponents, rectify_input=False, compute_representation=True, verbose=True + coefficients, + exponents, + rectify_input=False, + compute_representation=True, + verbose=True, ) return poly, poly_h @s.composite -def example_case_sampling(draw) -> Tuple[MultivarPolynomial, HornerMultivarPolynomial, np.ndarray]: +def example_case_sampling( + draw, +) -> Tuple[MultivarPolynomial, HornerMultivarPolynomial, np.ndarray]: poly, poly_h = draw(poly_sampling()) nr_dims = poly.dim x = draw(s.lists(float_sampling(), min_size=nr_dims, max_size=nr_dims)) @@ -83,10 +105,14 @@ def example_case_sampling(draw) -> Tuple[MultivarPolynomial, HornerMultivarPolyn @s.composite -def example_case_sampling_complex(draw) -> Tuple[MultivarPolynomial, HornerMultivarPolynomial, np.ndarray]: +def example_case_sampling_complex( + draw, +) -> Tuple[MultivarPolynomial, HornerMultivarPolynomial, np.ndarray]: poly, poly_h = draw(poly_sampling()) nr_dims = poly.dim - x = draw(s.lists(query_point_sampling_complex(), min_size=nr_dims, max_size=nr_dims)) + x = draw( + s.lists(query_point_sampling_complex(), min_size=nr_dims, max_size=nr_dims) + ) x = rectify_query_point(x, dtype=COMPLEX_DTYPE) return poly, poly_h, x @@ -136,6 +162,10 @@ def test_complex_eval(params): def all_close(res1, res2, coefficients, exponents, x): err_msg = f"{x=}\n{coefficients=}\n{exponents=}" if abs(res1) < 1e-5: - np.testing.assert_almost_equal(res1, res2, decimal=REQUIRED_ABS_PRECISION, err_msg=err_msg) + np.testing.assert_almost_equal( + res1, res2, decimal=REQUIRED_ABS_PRECISION, err_msg=err_msg + ) else: - np.testing.assert_allclose(res1, res2, rtol=REQUIRED_REL_PRECISION, err_msg=err_msg) + np.testing.assert_allclose( + res1, res2, rtol=REQUIRED_REL_PRECISION, err_msg=err_msg + ) diff --git a/tests/main_test.py b/tests/main_test.py index f242ba4..8f868c2 100755 --- a/tests/main_test.py +++ b/tests/main_test.py @@ -9,7 +9,11 @@ import numpy as np import pytest -from multivar_horner import HornerMultivarPolynomial, HornerMultivarPolynomialOpt, MultivarPolynomial +from multivar_horner import ( + HornerMultivarPolynomial, + HornerMultivarPolynomialOpt, + MultivarPolynomial, +) from multivar_horner.global_settings import COMPLEX_DTYPE, FLOAT_DTYPE, UINT_DTYPE from tests.helpers import naive_eval_reference, proto_test_case, vectorize from tests.settings import ( @@ -59,7 +63,9 @@ def test_construction_basic(self): assert len(str(p1)) < len(str(p2)) assert str(p1) == p1.representation - return_str_repr = p1.compute_string_representation(coeff_fmt_str="{:1.1e}", factor_fmt_str="(x{dim} ** {exp})") + return_str_repr = p1.compute_string_representation( + coeff_fmt_str="{:1.1e}", factor_fmt_str="(x{dim} ** {exp})" + ) # the representation should get updated assert return_str_repr == p1.representation @@ -93,11 +99,15 @@ def test_eval_api(self): vals = [True, False] max_dim = 3 degree_range = range(1, 4) - exponents = np.array(list(itertools.product(degree_range, repeat=max_dim)), dtype=UINT_DTYPE) + exponents = np.array( + list(itertools.product(degree_range, repeat=max_dim)), dtype=UINT_DTYPE + ) coeffs = np.random.rand(exponents.shape[0]) X = np.random.rand(NR_TEST_POLYNOMIALS, max_dim) p_ref = naive_eval_reference(X, exponents, coeffs) - for kwargs in [dict(zip(keys, tf)) for tf in itertools.product(*[vals] * len(keys))]: + for kwargs in [ + dict(zip(keys, tf)) for tf in itertools.product(*[vals] * len(keys)) + ]: p_mv = vectorize(self.class2test(coeffs[:, None], exponents, **kwargs)) assert np.allclose(p_ref, p_mv(X)) @@ -123,7 +133,9 @@ def test_eval_compare_vandermonde_nd(self): degree_range = range(1, 4) dim_range = range(1, 4) for dim, deg in itertools.product(dim_range, degree_range): - exponents = np.array(list(itertools.product(range(deg), repeat=dim)), dtype=UINT_DTYPE) + exponents = np.array( + list(itertools.product(range(deg), repeat=dim)), dtype=UINT_DTYPE + ) coeffs = np.random.rand(exponents.shape[0]) X = np.random.rand(NR_TEST_POLYNOMIALS, dim) p_ref = naive_eval_reference(X, exponents, coeffs) diff --git a/tests/plotting.py b/tests/plotting.py index d05b9b3..4c16da9 100644 --- a/tests/plotting.py +++ b/tests/plotting.py @@ -30,7 +30,9 @@ def get_plot_name(file_name="plot"): file_name = file_name.replace(" ", "_") Path(PLOTTING_DIR).mkdir(parents=True, exist_ok=True) - return os.path.abspath(os.path.join(PLOTTING_DIR, file_name + "_" + str(time.time())[:-7] + ".png")) + return os.path.abspath( + os.path.join(PLOTTING_DIR, file_name + "_" + str(time.time())[:-7] + ".png") + ) def export_plot(fig, plot_title): @@ -126,7 +128,9 @@ def speed_test_run(dim, degree, nr_samples, template): poly_settings_list = rnd_settings_list(nr_samples, dim, degree) input_list = rnd_input_list(nr_samples, dim, max_abs_val=1.0) - setup_time_naive = timeit.timeit("test_setup_time_naive()", globals=globals(), number=1) + setup_time_naive = timeit.timeit( + "test_setup_time_naive()", globals=globals(), number=1 + ) setup_time_naive = setup_time_naive / NR_SAMPLES_SPEED_TEST # = avg. per sample # poly_class_instances is not populated with the naive polynomial class instances @@ -136,7 +140,9 @@ def speed_test_run(dim, degree, nr_samples, template): eval_time_naive = timeit.timeit("eval_time_fct()", globals=globals(), number=1) eval_time_naive = eval_time_naive / NR_SAMPLES_SPEED_TEST # = avg. per sample - setup_time_horner = timeit.timeit("test_setup_time_horner()", globals=globals(), number=1) + setup_time_horner = timeit.timeit( + "test_setup_time_horner()", globals=globals(), number=1 + ) setup_time_horner = setup_time_horner / NR_SAMPLES_SPEED_TEST # = avg. per sample # poly_class_instances is not populated with the horner polynomial class instances @@ -149,7 +155,9 @@ def speed_test_run(dim, degree, nr_samples, template): setup_delta = difference(setup_time_naive, setup_time_horner) eval_delta = difference(eval_time_naive, eval_time_horner) ops_delta = difference(num_ops_naive, num_ops_horner) - lucrative_after = compute_lucrativity(setup_time_horner, setup_time_naive, eval_time_horner, eval_time_naive) + lucrative_after = compute_lucrativity( + setup_time_horner, setup_time_naive, eval_time_horner, eval_time_naive + ) if lucrative_after < 0: lucrative_after = "-" # never lucrative @@ -184,14 +192,18 @@ def speed_test_run(dim, degree, nr_samples, template): # TODO def run_speed_benchmark(): if os.path.isfile(SPEED_RUN_PICKLE): - print(f"result file {SPEED_RUN_PICKLE} is already present. skipping data generation.") + print( + f"result file {SPEED_RUN_PICKLE} is already present. skipping data generation." + ) return # this also fulfills the purpose of testing the robustness of the code # (many random polygons are being created and evaluated) print("\nSpeed test:") - print("testing {} evenly distributed random polynomials".format(NR_SAMPLES_SPEED_TEST)) + print( + "testing {} evenly distributed random polynomials".format(NR_SAMPLES_SPEED_TEST) + ) print("average timings per polynomial:\n") print( @@ -231,7 +243,9 @@ def run_speed_benchmark(): for dim in DIM_RANGE: dim_run_results = [] for maximal_degree in DEGREE_RANGE: - result_single_run = speed_test_run(dim, maximal_degree, NR_SAMPLES_SPEED_TEST, template) + result_single_run = speed_test_run( + dim, maximal_degree, NR_SAMPLES_SPEED_TEST, template + ) dim_run_results.append(result_single_run) print() # empty line @@ -306,7 +320,9 @@ def extract_data_abs_horner(results, data_idx): fig, ax = plt.subplots() obj_handles = [] - extra = Rectangle((0, 0), 1, 1, fc="w", fill=False, edgecolor="none", linewidth=0) + extra = Rectangle( + (0, 0), 1, 1, fc="w", fill=False, edgecolor="none", linewidth=0 + ) obj_handles.append(extra) # data = extract_data(all_results, run_idx) @@ -401,17 +417,23 @@ def extract_maximal_degree(result): def extract_num_ops_naive(result): - poly_dim, poly_degree, num_ops_naive, num_ops_horner = extract_poly_properties(result) + poly_dim, poly_degree, num_ops_naive, num_ops_horner = extract_poly_properties( + result + ) return num_ops_naive def extract_num_ops_horner(result): - poly_dim, poly_degree, num_ops_naive, num_ops_horner = extract_poly_properties(result) + poly_dim, poly_degree, num_ops_naive, num_ops_horner = extract_poly_properties( + result + ) return num_ops_horner def extract_num_ops_benefit(result): - poly_dim, poly_degree, num_ops_naive, num_ops_horner = extract_poly_properties(result) + poly_dim, poly_degree, num_ops_naive, num_ops_horner = extract_poly_properties( + result + ) return num_ops_horner - num_ops_naive @@ -499,7 +521,9 @@ def plot_num_err_heatmap(results): # average for dim and degree for dim in DIM_RANGE: for maximal_deg in DEGREE_RANGE: - selection_idxs = (df[attr_name_dim] == dim) & (df[attr_name_deg] == maximal_deg) + selection_idxs = (df[attr_name_dim] == dim) & ( + df[attr_name_deg] == maximal_deg + ) if not selection_idxs.any(): continue df_selected = df[selection_idxs] @@ -529,7 +553,9 @@ def plot_num_err_heatmap(results): # size=attr_name_numerical_err_rel, # sizes=(100,300), # ) - heatmap_data = df_avg.pivot(attr_name_deg, attr_name_dim, attr_name_numerical_err_rel) + heatmap_data = df_avg.pivot( + attr_name_deg, attr_name_dim, attr_name_numerical_err_rel + ) heatmap_data = heatmap_data.iloc[::-1] # reverse sns.heatmap( @@ -539,7 +565,9 @@ def plot_num_err_heatmap(results): linewidths=3, # cmap="YlGnBu", ) - plot_title = "avg. numerical error with canonical form relative to Horner factorisation" + plot_title = ( + "avg. numerical error with canonical form relative to Horner factorisation" + ) plt.title(plot_title) # plt.xlabel() # locs, labels = plt.xticks() # Get locations and labels @@ -555,11 +583,19 @@ def plot_num_error_growth_comparison(results): num_coeffs = list(map(extract_nr_coeffs, results)) # average first! before removing zeros - numerical_err_naive_avg, num_coeffs_unique_naive = average_discrete(numerical_err_naive, num_coeffs) - numerical_err_horner_avg, num_coeffs_unique_horner = average_discrete(numerical_err_horner, num_coeffs) + numerical_err_naive_avg, num_coeffs_unique_naive = average_discrete( + numerical_err_naive, num_coeffs + ) + numerical_err_horner_avg, num_coeffs_unique_horner = average_discrete( + numerical_err_horner, num_coeffs + ) - numerical_err_naive_avg, num_coeffs_unique_naive = rmv_zeros(numerical_err_naive_avg, num_coeffs_unique_naive) - numerical_err_horner_avg, num_coeffs_unique_horner = rmv_zeros(numerical_err_horner_avg, num_coeffs_unique_horner) + numerical_err_naive_avg, num_coeffs_unique_naive = rmv_zeros( + numerical_err_naive_avg, num_coeffs_unique_naive + ) + numerical_err_horner_avg, num_coeffs_unique_horner = rmv_zeros( + numerical_err_horner_avg, num_coeffs_unique_horner + ) attr_name_representation = "representation" attr_name_num_coeff = "number of coefficients" @@ -611,7 +647,9 @@ def plot_num_error_growth_comparison(results): def filter_results(filter_fct, results): results_filtered = list(filter(filter_fct, results)) - print(f"filtering data: out of {len(results)} entries {len(results_filtered)} remain") + print( + f"filtering data: out of {len(results)} entries {len(results_filtered)} remain" + ) return results_filtered @@ -706,7 +744,9 @@ def plot_num_coeffs2num_ops(results): def plot_numerical_error(): - print(f"generating numerical benchmark plots. reading data from {TEST_RESULTS_PICKLE}...") + print( + f"generating numerical benchmark plots. reading data from {TEST_RESULTS_PICKLE}..." + ) try: with open(TEST_RESULTS_PICKLE, "rb") as f: results = pickle.load(f) diff --git a/tests/settings.py b/tests/settings.py index ffd3737..f363bfc 100644 --- a/tests/settings.py +++ b/tests/settings.py @@ -1,7 +1,6 @@ from math import log10 from os.path import abspath, join, pardir -import numpy as np from numpy import array as a from multivar_horner.global_settings import FLOAT_DTYPE, UINT_DTYPE diff --git a/tox.ini b/tox.ini deleted file mode 100644 index 1195e2d..0000000 --- a/tox.ini +++ /dev/null @@ -1,53 +0,0 @@ -[tox] -isolated_build = true -envlist = - py{38,39,310}{,-numba},py311 - -skip_missing_interpreters = {env:TOX_SKIP_MISSING_INTERPRETERS:True} - -[gh-actions] -python = - 3.8: py38{,-numba} - 3.9: py39{,-numba} - 3.10: py310{,-numba} - # TODO numba does not have python 3.11 support (starting with 0.57) - 3.11: py311 - -[testenv] -allowlist_externals = poetry -commands = - numba: poetry install -v --extras "numba" - !numba: poetry install -v - poetry run pytest {posargs} - - -[isort] -;https://github.com/timothycrosley/isort/wiki/isort-Settings -known_first_party = multivar_horner -known_third_party = numpy, numba -line_length = 120 - -[flake8] -max_line_length = 120 -;trailing comma -ignore = C819 - -[tool:pytest] -testpaths = tests -;addopts = --cov=multivar_horner -; --cov-report term-missing - -[coverage:run] -;branch = True -include = */multivar_horner/* - -[coverage:paths] -source = - multivar_horner - .tox/*/site-packages - -[coverage:report] -show_missing = True - -[mypy] -plugins = pydantic.mypy