tensorwaves

See all documentation for this version here.

⚠️ API changes

• Drop Python 3.7 support (#503)

🐛 Bug fixes

• Set correct generic parameter types for ParametrizedFunction and its implementations (#522)
• Avoid jax import error for JAX >=0.4.19 (#504)

📝 Documentation

• Update link to pycompwa website (#513)
• Update links to compwa.github.io (#514)
• Remove .html from page URLs (#515)
• Switch to source code link button (#516)
• Fix typo in amplitude-analysis.ipynb (#520)
• Support AmpForm v0.15.x (#519)

🖱️ Developer Experience

• Remove figure_formats = ["svg"] statement (#507)
• Install Ruff and Git in Jupyter Lab (#508)
• Define docnblive job in tox.ini (#510)
• Switch to Ruff formatter (#518)

The full changelog as commits can be found here.

See all documentation for this version here.

⚠️ Enhancements and optimizations

• Set data keys as first positional arguments (#488)

🐛 Bug fixes

• Improve documentation sidebar (#483)
• Remove simplification step Abs of mass (#482)

📝 Documentation

• Improve documentation sidebar (#483)
• Remove simplification step Abs of mass (#482)
• Improve amplitude analysis tutorial (#489)
• Add CITATION.cff (#494)
• Show kinematic variable expressions (#497)
• Switch to latest version of Sphinx Book Theme (dark mode)

🔨 Maintenance

• Verify installation on Python 3.11 (#484)

🖱️ Developer Experience

• Colorize sphinx-build output (#481)
• Enable language navigation on Jupyter Lab (#495)
• Switch to Ruff as linter (#492)

The full changelog as commits can be found here.

See all documentation for this version here.

✨ New features

• Added migrad_args option to Minuit2 optimizer (#476)
• TensorWaves can now be installed on Python 3.11 and higher (#478)

🖱️ Developer Experience

• Implement GitHub Actions caching (#471)
• GitHub workflows are now outsourced to ComPWA/actions (#477)

The full changelog as commits can be found here.

See all documentation for this version here.

✨ New features

• Implement ChainedDataTransformer (#470)

🐛 Bug fixes

• Allow generating empty phase space samples (#465)
• Remove cast to numpy in UnbinnedNLL (#466)

🖱️ Developer Experience

• Activate and address pyright strict type checking (#467)
• Switch to new VSCode Python extensions (#469)

See all documentation for this version here.

✨ New features

• Support Python 3.10 (#459)
• Support TensorFlow >v2.6 (#459)

See all documentation for this version here.

💡 New features

• Implemented a logging hierarchy so that logs can be enabled and disabled per module (#453)
• UnbinnedNLL can now handle a phase space DataSample that carries a "weights" key (#458). This makes it possible to perform fits with importance-sampled phase space samples (#402).

⚠️ Interface

• Merged WeightedDataGenerator into DataGenerator interface (#458)

🔨 Internal maintenance

• Source code is now formatted with black's default 88 line width (#449)
• Switched from the deprecated sphinx-panels to sphinx-design (#450)

📝 Documentation

• Updated Zenodo author list (#454)

See all documentation for this version here.

🔨 Internal maintenance

• TensorWaves v0.2.9 can be installed with TensorFlow v2.6 and higher versions of phasespace (#447)

See all documentation for this version here.

⚠️ Interface

• Dropped Python 3.6 support (#431)
• Version limit on phasespace has been removed (#445).
  If TensorWaves is installed with phasespace, TensorFlow is limited to below v2.7.

🖱️ Developer Experience

• Documentation is now built with sphinx-build only and cannot be built with make anymore (#433)
• Documentation in EXECUTE_NB mode is now faster on second run due to MyST-NB caching (#433)

See all documentation for this version here.

🐛 Bug fixes

• Expressions that contain sympy.Indexed can now be lambdified (#427)

🔨 Internal maintenance

• TensorWaves can now be installed with any version of AmpForm above v0.13.0 (#426)

📝 Documentation

• Extended API docstrings in the function module (#428)

🖱️ Developer Experience

• All dependencies are now also pinned on Read the Docs (#429)

See all documentation for this version here.

🐛 Bug fixes

• Default weights in ChiSquared are now computed from observed_values (#421)

🔨 Internal maintenance

• TensorWaves can now be installed with AmpForm v0.14.x (#424)

📝 Documentation

• Switched to Chew-Mandelstam S-wave phase space factor in the analytic continuation notebook (#425)

See all documentation for this version here.

🔨 Internal maintenance

• TensorWaves can now be installed with AmpForm v0.13.x (#419)

See all documentation for this version here.

💡 New features

• Added minuit_modifier constructor argument (#399)

🐛 Bug fixes

• Speed-up prepare_caching() with sympy.Basic.xreplace (#403)

🔨 Internal maintenance

AmpForm v0.12.3 introduces a small change through https://github.com/ComPWA/ampform/pull/211: BoostZ etc becomes BoostZMatrix. This needs to be fixed in the TensorFlow printer.

Added TensorFlow printer instructions for _BoostZMatrixImplementation etc. See release notes AmpForm v0.12.4.

See import attrs and attrs TNG.

📝 Documentation

Closes https://github.com/ComPWA/repo-maintenance/issues/43

Also fixes a small bug: callbacks that write to disk skip writing when computing the Hesse.

Preview here.

Improved the docstrings of both functions, preview here.

• All code examples are now clickable with links to corresponding reference documentation (also external links APIs) with sphinx-codeautolink. Closes https://github.com/ComPWA/compwa-org/issues/106
• Installed jupyterlab-myst
• Updated to the first non-beta black release 22.1.0. Most important style effect: no space around power operator **.

Links to graphviz's API are now also embedded correctly. Follow-up to #405.

Closes https://github.com/ComPWA/compwa-org/issues/109

Preview here.

Rewrote the installation page a bit so that it's clearer how to pin all dependencies with Conda. Preview here.

Added an example of how to use create_cached_function() in combination with an Estimator. Preview here.

Added an additional install example that shows how to install a specific branch or tag with pip from Git with optional dependencies. Preview here.

🖱️ Developer Experience

Automated changes by create-pull-request GitHub action

Closes https://github.com/ComPWA/repo-maintenance/issues/43

See https://github.com/ComPWA/ampform/pull/207

Compare API v0.4.1 and preview of this PR.

See jupyterlab-myst

Adds a workflow_dispatch with inputs that allows running all tests manually with the latest version of AmpForm installed.

See all documentation for this version here.

💡 New features

Closes #358

Expression tree optimizations sketched here have been bundled in a new function create_cached_function(). A usage notebook can be previewed here.

⚠️ Interface

All computational backends are now optional dependencies (apart from NumPy). So for instance, to install TensorWaves with JAX, run:

pip install tensorwaves[jax]

To do amplitude analysis, install with:

pip install tensorwaves[jax,pwa]

🐛 Bug fixes

Closes #395

import ampform
import qrules
from ampform.dynamics.builder import create_relativistic_breit_wigner_with_ff
from tensorwaves.data import (
    IntensityDistributionGenerator,
    TFPhaseSpaceGenerator,
    TFUniformRealNumberGenerator,
)
from tensorwaves.data.transform import SympyDataTransformer
from tensorwaves.function.sympy import create_parametrized_function

reaction = qrules.generate_transitions(
    initial_state="J/psi(1S)",
    final_state=["gamma", "pi0", "pi0"],
    allowed_intermediate_particles=["f(0)"],
    allowed_interaction_types=["strong", "EM"],
)

builder = ampform.get_builder(reaction)
resonances = reaction.get_intermediate_particles()
for p in resonances:
    builder.set_dynamics(p.name, create_relativistic_breit_wigner_with_ff)
model = builder.formulate()

intensity = create_parametrized_function(
    model.expression.doit(),
    parameters=model.parameter_defaults,
    backend="jax",
)
helicity_transformer = SympyDataTransformer.from_sympy(
    model.kinematic_variables, backend="jax"
)

phsp_generator = TFPhaseSpaceGenerator(
    initial_state_mass=reaction.initial_state[-1].mass,
    final_state_masses={i: p.mass for i, p in reaction.final_state.items()},
)
data_generator = IntensityDistributionGenerator(
    function=intensity,
    domain_generator=phsp_generator,
    domain_transformer=helicity_transformer,
)
rng = TFUniformRealNumberGenerator(seed=0)
phsp_momenta = phsp_generator.generate(1_000_000, rng)
data_momenta = data_generator.generate(100_000, rng)

🖱️ Developer Experience

• Wrote some additional tests for the tensorwaves.function module
• TYPE_CHECKING is now ignored in test coverage

See all documentation for this specific version here.

TensorWaves v0.4 has a more general interface than v0.3. Major changes are the removal of the Model interface (#357) and generalization of the data module (#392). This affects the way in which computational backend functions are created and the way in which hit-and-miss distributions are generated.

Some examples of syntax changes for an AmpForm HelicityModel (model):

v0.4.x (new)

# create function and data transformer
from tensorwaves.function.sympy import create_parametrized_function

intensity = create_parametrized_function(
    expression=model.expression.doit(),
    parameters=model.parameter_defaults,
    backend="jax",
)
helicity_transformer = SympyDataTransformer.from_sympy(
    model.kinematic_variables, backend="numpy"
)

# generate data
from tensorwaves.data import (
    IntensityDistributionGenerator,
    SympyDataTransformer,
    TFPhaseSpaceGenerator,
    TFUniformRealNumberGenerator,
)

phsp_generator = TFPhaseSpaceGenerator(
    initial_state_mass=3.069,
    final_state_masses={0: 0.0, 1: 0.135, 2: 0.135},
)
data_generator = IntensityDistributionGenerator(
    domain_generator=phsp_generator,
    function=intensity,
    domain_transformer=helicity_transformer,
)
rng = TFUniformRealNumberGenerator(seed=0)
phsp = phsp_generator.generate(100_000, rng)
data = data_generator.generate(10_000, rng)

Note that this works for general SymPy expressions: there is no AmpForm dependency. See this page.

v0.3.x (old)

from tensorwaves.model import LambdifiedFunction, SympyModel

# create function and data transformer
sympy_model = SympyModel(
    expression=model.expression.doit(),
    parameters=model.parameter_defaults,
)
intensity = LambdifiedFunction(sympy_model, backend="jax")
helicity_transformer = HelicityTransformer(model.adapter)

# generate data
from tensorwaves.data import TFUniformRealNumberGenerator, generate_data, generate_phsp
from tensorwaves.data.transform import HelicityTransformer

rng = TFUniformRealNumberGenerator(seed=0)
phsp = generate_phsp(
    size=100_000,
    initial_state_mass=3.069,
    final_state_masses={0: 0.0, 1: 0.135, 2: 0.135},
    random_generator=rng,
)
data = generate_data(
    size=10_000,
    initial_state_mass=3.069,
    final_state_masses={0: 0.0, 1: 0.135, 2: 0.135},
    data_transformer=helicity_transformer,
    intensity=intensity,
    random_generator=rng,
)

💡 New features

Also includes improvements to the documentation of estimator module.

Closes #323

• Added a convenience function tensorwaves.function.get_source_code()
• Added read-only properties function and argument_order to ParametrizedBackendFunction (parallels attrs-decorated PositionalArgumentFunction class).
• PositionalArgumentFunction is now used internally in ParametrizedBackendFunction (simplifies its __call__() method).
• Symbols are not force-dummified anymore if use_cse=False

It's now possible to do

from tensorwaves.optimizer import Minuit2

instead of

from tensorwaves.optimizer.minuit import Minuit2

⚠️ Interface

Adapts the data module implementation so that it can work with AmpForm v0.12.x. Closes https://github.com/ComPWA/ampform/issues/182.

Some major changes:

• Keys in a DataSample are now str only, not int. This means that momentum samples have keys "p0", "p1", etc. instead of 0, 1. This is in accordance with the Symbol names used in AmpForm's HelicityModel.kinematic_variables.
• Added a function create_function() that creates a PositionalArgumentFunction. This is a Function without parameters (compare ParametrizedFunction). The function and related class is used in the DataTransformer implementation, which doesn't need parameters.
• Data conversion can now be done with different back-ends.

This PR removes the Model interface and related implementations. The interface was introduced with the idea to implement different types of expression trees later on (see ADR-001), but this seems to be a premature optimisation. For now, the Function interface suffices: Function instances can be created through specific functions.

Some major changes:

• The Model interface and its implementation SympyModel have been removed
• tensorwaves.model has been renamed to tensorwaves.function
• There is no way to use performance_optimize() (for now—see #358)

This means that the workflow becomes:

# helicity_model: ampform.helicity.HelicityModel
function = create_parametrized_function(
    expression=helicity_model.expression.doit(),
    parameters=helicity_model.parameter_defaults,
    backend="numpy",
)

instead of

model = SympyModel(
    expression=helicity_model.expression.doit(),
    parameters=helicity_model.parameter_defaults,
    max_complexity=max_complexity,
)
function = LambdifiedFunction(model, backend="numpy")

The existing Function interface has too many responsibilities: it (1) converts a DataSample to an array or tensor and (2) distinguishes parameter variables from domain variables. This worked fine so far, because Function was only used when optimizing, where you need to tweak those parameters. In #345 though, we need to a Function that only does (1), for the conversion of one DataSample (four-momenta) to another DataSample (kinematic variables) with different back-ends.

This PR creates a new ParametrizedFunction interface that does (1) and (2) and a 'bare' Function interface that does only (1). The input and output types of the Function interface are generic, so that it can be used in different types of function-like interfaces.

Related changes:

• Renamed LambdifiedFunction to ParametrizedBackendFunction.
• DataTransformer.transform() has become a __call__ and DataTransformer derives from Function.
• Estimator also derives from Function: it computes an estimator value for a set of parameters.

Large refactoring of the data module with the aim to generalize its hit-and-miss mechanisms to general domain DataSample types.

Interface changes

• Removed generate_data() and generate_phsp() façade functions. The new way to generate phase space and hit-and-miss data samples is:

  from tensorwaves.data import IntensityDistributionGenerator
  from tensorwaves.data.phasespace import TFPhaseSpaceGenerator
  from tensorwaves.data.rng import TFUniformRealNumberGenerator
  
  # intensity: Function
  # helicity_transformer: SympyDataTransformer
  rng = TFUniformRealNumberGenerator(seed=0)
  phsp_generator = TFPhaseSpaceGenerator(
      initial_state_mass=3.0969,
      final_state_masses={0: 0.0, 1: 0.135, 2: 0.135},
  )
  data_generator = IntensityDistributionGenerator(
      domain_generator=phsp_generator,
      domain_transformer=helicity_transformer,
      function=intensity,
  )
  phsp = phsp_generator.generate(100_000, rng)
  data = data_generator.generate(10_000, rng)
  

• UniformRealNumberGenerator -> RealNumberGenerator

• PhaseSpaceGenerator -> DataGenerator

• PhaseSpaceGenerator.setup() has been merged into the constructor (DataGenerator.__init__()) and removed from the interface.

• Split old TFPhaseSpaceGenerator into an unweighted TFPhaseSpaceGenerator (implements DataGenerator) and a TFWeightedPhaseSpaceGenerator (implements WeightedDataGenerator). TFPhaseSpaceGenerator can be used instead of the old generate_phsp() function.

• Collected RNGs under a new sub-module data.rng

New features

• New interface: DataGenerator, which does not generate weights as opposed to FourMomentumGenerator.
• IntensityDistributionGenerator, which should be used instead of generate_data()
• IdentityTransformer, which is just the identity implementation of a DataTransformer.
• NumpyUniformRNG

Only accepts a single str now.

🐛 Bug fixes

Fix-up to #374

Additional fixes:

• Enforce specifying use_cse argument in hidden functions.
• Remove **kwargs from lambdify functions. This helps mypy/pyright identify whether functions calls miss certain arguments.

🔨 Internal maintenance

sympy.lambdify() doesn't work when SymPy is too old.

📝 Documentation

Preview here: https://tensorwaves--381.org.readthedocs.build/en/381/install.html

Additional improvements:

• Check link anchors with linkcheck_anchors = True.
• Removed typing-extensions from requirements.

Follow-up to #387. Generalizes the documentation with more non-PWA examples.

All example notebooks for amplitude analysis have been isolated under tensorwaves.rtfd.io/en/latest/amplitude-analysis. Examples under usage show more general expressions.

Note that resource-intensive examples like the Scipy fit on an amplitude model and the fit anination have been substituted with simpler examples, which should speed up CI on the docs.

Closes #379

The amplitude analysis notebook now shows how to optimize the expression tree with SymPy, so that the fit is much faster. This also allows showing a more complicated fit, with more free parameters and larger initial offset.

🖱️ Developer Experience

Closes #135

Adds a test under the tests/unit folder that fits a small model with all back-ends and optimizers plus a unit test for generate_data. This also helped fishing out some bugs (see commit history).

Closes #103

Large improvements to the testing suite:

• Added benchmark tests
• If run on the main branch, the results are pushed to the branch with the continuous-benchmark action.
• The performance results per commit are visualised on compwa.github.io/tensorwaves.
• If run on pull request, a warning will be commented on any commit that decreases performance. Example: https://github.com/ComPWA/tensorwaves/commit/b5c1f075eff9f9b9c82e52faf22acbb81865fdc6#commitcomment-61330128
• Integration tests have been removed so that there are only unit tests (coverage of the unit tests is sufficient since #351).
• Test folder structure has been simplified: tests/unit moved one folder up.

See all documentation for this version here.

💡 New features

CSVSummary was writing "estimator_type" incorrectly (it was writing the optimizer type). This PR fixes that and adds the optimizer type as an additional entry, also to YAMLSummary.

See cse argument in sympy.lambdify(). This fixes https://github.com/ComPWA/tensorwaves/pull/345#commitcomment-61398587.

Note that lambdified source code becomes significantly smaller in larger expressions. Finding common sub-expressions has a small hit in performance when lambdifying, but in larger expressions, this is overcome by the fact that the output source code is smaller.

⚠️ Interface

Extracted all SymPy functionality under tensorwaves.model into a separate sub-module tensorwaves.model.sympy.

Closes #280

This means that doit() has to be called on the expression first.

🐛 Bug fixes

CSVSummary was writing "estimator_type" incorrectly (it was writing the optimizer type). This PR fixes that and adds the optimizer type as an additional entry, also to YAMLSummary.

JAX and TensorFlow printing is forwarded to the NumPy printer, but with jax.numpy and tensorflow.experimental.numpy as Printer._module respectively.

Other improvements:

• Extended tests for find_function and wrote a test for lambdifying AmpForm's ComplexSqrt
• Allow getting tensorflow.Tensor with find_function
• Moved _backend module to function, because function is most related to back-ends.

🔨 Internal maintenance

Closes #322

The role of _backend_lambdify and _sympy_lambdify is now swapped:

• _backend_lambdify is now purely a wrapper around sympy.lambdify.
• _sympy_lambdify offers a switch between _backend_lambdify and optimized_lambdify.

These functions will change further in #292, but this is PR focuses only on the problem describe din #322.

All tests that require AmpForm have been seperated from proper unit tests (that require no additional dependencies). The folder structure under tests is now:

tests
├── integration
└── unit

Additional improvements:

• Fixtures for the AmpForm tests have been parametrized:
  • qrules.ReactionInfo is parametrized with the canonica-helicity and helicity formalism.
  • SympyModel is constructed with and without max_complexity argument in the constructor, so that optimized_lambdify is tested as well.
• Improved error message of LambdifiedFunction.update_parameters: over-defined parameters were computed incorrectly. In addition, the error message now prints the expected parameters.
• Callbacks can now take pathlib.Path (previously only str). This makes it possible to convert the output_dir fixture into a Path as well.

#344 created a module tensorwaves.model.backend with the intention to collect functions that handle back-ends. This PR moves _find_function_in_backend (which was under tensorwaves.estimator) there as well, moves the module to the top, and hides it altogether, as these functions are implementation details.

Additional fixes:

• The faster-lambdify notebook was failing due to the interface change introduced by #348. This was not noticed, because the %%time statement in the cell makes the error code of that cell return 'success'. The error has been fixed and a hidden test cell has been added to prevent such failures in the future.
• optimized_lambdify now directly calls _backend_lambdify is max_complexity is higher than the number of nodes in the expression.

Integration tests have become unstable since #349, see e.g. https://github.com/ComPWA/tensorwaves/actions/runs/1504632721, because the callback output is written to the same file when using optimized_lambdify / _backend_lambdify.

Closes #135

Adds a test under the tests/unit folder that fits a small model with all back-ends and optimizers plus a unit test for generate_data. This also helped fishing out some bugs (see commit history).

Other improvements:

• Import optimizers directly from the tensorwaves.optimizer module, e.g.:

    from tensorwaves.optimizer import Minuit2
  

  instead of

    from tensorwaves.optimizer.minuit import Minuit2
  

• CSVSummary writes estimator value as float (was complex by mistake)
• Latest function call number is also stored in Loadable callbacks.
• Scipy now works with TF

Import expensive modules inline to speed up importing tensorwaves. This makes import tensorwaves (and collecting tests) about 8x as fast. Profiling done with tuna as follows (see stackoverflow):

python3 -X importtime -c "import tensorwaves" 2> tw.log && tuna tw.log

Previously, if no callback was specified in the optimizer constructor, an empty CallbackList would be created and on_optimize_end etc were always called. This is (theoretically) slower.

Some other improvements:

• Use attrs next-generation API (see also https://github.com/ComPWA/compwa-org/issues/90).
• Avoid creating stream on creation of Loadable callback.
• Fail pytest on warnings (this helped fishing out the above bug)

📝 Documentation

Added links to the 'fit result' objects in the iminuit and SciPy APIs.

🖱️ Developer Experience

Fix-up to #349

Writing with a callback in a pytest fixture and then loading it back in a test led to instable CI. This PR should fix that.

Switch from pytest-notebook to nbmake. Now it's again possible to run specific notebooks from the terminal with e.g.:

pytest --nbmake docs/usage/basics.ipynb

Other small fixes:

• Avoid fast_lambdify() in Jupyter notebooks to speed up docs workflow.
• Cast to tuple in ParametrizedBackendFunction.

Reorganise GitHub Action workflow for pytest. Extracted from #366 in order to identify potential performance issues. Notebooks slow after the changes introduced in #366, which may be caused by the changes to the callbacks.

Other changes;

• Treat warnings raised under pytest as errors.
• Renamed tox job for testing notebooks to nb.

Should speed up pre-commit job.

Import expensive modules in the tests inline so that pytest --collect-only is faster.

See all documentation for this version here.

🔨 Internal maintenance

• Improved some of the type hints
• Enforcing the use of mypy error codes (# type: ignore[error-code]) with flake8-type-ignore.

📝 Documentation

• docs: pin more intersphinx pages
• fix: correct intersphinx links that were not previously checked
• fix: exclude version 'module' from API
• fix: move docstrings from init to class definition
• refactor: get intersphinx version through function
• style: capitalize conf.py global vars that are no Sphinx options

🖱️ Developer Experience

The .flake8 config file was using not using the same comment style as described in
https://flake8.pycqa.org/en/latest/user/configuration.html#project-configuration
Consequence not all errors were identified anymore.

See all documentation for this version here.

Release for first Zenodo DOI

💡 New features

📝 Documentation

See ComPWA/ampform#104

Some platforms like Zenodo and conda-forge require the license file to be packaged.

Closes https://github.com/ComPWA/compwa-org/issues/61

Automated changes by create-pull-request GitHub action

🔨 Internal maintenance

See https://github.com/ComPWA/ampform/pull/147

🖱️ Developer Experience

See ComPWA/qrules#87

Note https://github.com/ComPWA/tensorwaves/pull/309#issuecomment-908152365. This comment is still relevant.

See all documentation for this version here.

🐛 Bug fixes

Fix-up to #310

https://github.com/ComPWA/tensorwaves/blob/57f6ec0f04e0afc0cebcc955783d20cde2646be6/setup.cfg#L44

resulted in version conflicts downstream. AmpForm is now also correctly updated: 626abe1.

See all documentation for this version here.

🔨 Internal maintenance

See AmpForm v0.11.0 and v0.11.1

📝 Documentation

See https://github.com/ComPWA/PWA-pages/pull/111

See all documentation for this version here.

💡 New features

Closes #290

Added a method FitResult.count_number_of_parameters()

FitResult(
minimum_valid=True,
execution_time=2.9841978549957275,
function_calls=166,
estimator_value=-7579.247627538372,
parameter_values={
'm_f(0)(980)': 0.989885368944097,
'Gamma_f(0)(980)': 0.060228379644260165,
},
parameter_errors={
'm_f(0)(980)': 0.0010628340144144574,
'Gamma_f(0)(980)': 0.0016523232241513362,
},
)

⚠️ Interface

Removes AmpForm/QRules's ReactionInfo from the main interface. This makes generate_phsp and generate_data a bit more clumsy in usage, but the benefit is that ampform is not imported into TensorWaves's interface module.

Use HelicityModel.sum_components instead.

🔨 Internal maintenance

Using type alias ParameterValue where possible instead of Union[...].

📝 Documentation

Show how to generate a deterministic data and phase space sample in step 2 of the documentation.