lymph-model - 1.3.6

What's New

This release changes nothing about the actual code. Only the way it's built and tested. So, purely a maintenance update.

Miscellaneous Tasks

• Update pre-commit & ruff rules.

Testing

• Update one doctest example.

Build

• Switch to src layout. Fixes #106.
• Rename opt dependencies to tests.
• Use tests dependency pytest-cov over coverage.

Ci

• Update pre-commit config.

- Python
Published by rmnldwg 11 months ago

lymph-model - 1.3.5

What's new:

Bug Fixes

• Assign only tumor spread probs in midline.
• (mid) Warn instead of raise when out of sync. Fixes [#102].

Documentation

• Fix release badge in README.
• Fix outdated links to rmnldwg.

Testing

• Ensure midline params sync.
• Add failing midline params desync. Related [#102].
• Fix desync test case.

Build

• Add git-cliff to dev dependencies.

- Python
Published by YoelPH 12 months ago

lymph-model - 1.3.4

What's New

Bug Fixes

• Don't use or when param may be 0.\ Since Python's expression a = b or c will assign c to a as soon as b is "falsy", e.g. also when b = 0.0, I should not use this to check if a parameter in the model is None.

Documentation

• Fix misspelled repo link.
• Remove empty mixins page.
• Better reuse of README.
• Move social card to repo root.\ This is actually for LyProX: I want to display the social card of all repos in the lycosystem on LyProX's landing page. Therefore, they all need to be in their expected places.

Miscellaneous Tasks

• Add year range to license.

Testing

• Use val != 0.5 to test matrix deletion.\ 0.5 is the new initial value for most parameters, so it does not make sense to use this to check if upon changing a parameter, the transition matrix gets deleted.

Change

• Init most params with 0.5 instead of 0.0.\ In some cases, initializing with 0.0 may have unintended consequences. E.g., a probability of 0.0 cannot be renormalized.

Ci

• Use OIDC for publishing.

- Python
Published by rmnldwg about 1 year ago

lymph-model - 1.3.3

What's New

Bug Fixes

• Make midext_prob last param in get/set methods
• Midline musn't use last of set_param args.\ Instead, it should use the one at num_dims - 1.

Documentation

• Fix broken quickstart link.
• Add emcee to requirements for quickstart notebook.
• Explain midline extension probability in set/get.

Testing

• midext_prob is last parameter in get/set methods.

- Python
Published by rmnldwg about 1 year ago

lymph-model - 1.3.2

What's New

Bug Fixes

• __init__() without named_params now works. Previously, it raised an exception because the distribution composite was not initialized.

Testing

• __init__() with named_params must work.

- Python
Published by rmnldwg over 1 year ago

lymph-model - 1.3.1

What's New

Bug Fixes

• get_named_params() returns only named params and doesn't raise an error anymore.
• Add deleter to named_params property.

Change

• Move named_params stuff from dedicated mixin to types.Model.
• Raise explicit invalid param name error.\ This ensures that e.g. during sampling, the likelihood does not simply return -np.inf because it sees a ValueError.
• Call set_named_params() in likelihoods.\ This ensures that a model definition is respected during inference and also when reloading sampled parameters. In case no named_params are provided, this will simply behave as set_params().

- Python
Published by rmnldwg over 1 year ago

lymph-model - 1.3.0

What's New

The main two new features of this release are the HPV model (thanks @YoelPH for this) and the ability to only set a subset of parameters. See #95 for an explanation why that was necessary.

No breaking changes this time (phew).

Bug Fixes

• (hpv) Some renaming and import correct symbols.
• (hpv) Send kwargs to constructor correctly.
• Partial globals work in set_named_params().\ Setting ipsi_spread via named_params works now. This was tricky to implement, as the spread params of the ipsi model are all called ipsi_<something>_spread.

Documentation

• Fix typos in readme.
• Fix typo in midline model docstring.
• Fix equation in midline model docstring.
• Change ref to "bilateral" in HPV model.
• Add new mixins to autodoc.
• Add warning about untested HPV model.

Features

• (hpv) Create HPV wrapper.\ The HPV module can be used to build a unilateral lymph model where the b_2 parameter is different for HPV positive patients.\ This fixes #42
• (uni) Add basic working named params mixing. Related to #95
• Add named_params to all models. Fixes #95
• Add named_params to model constructors. Related to #95

Testing

• Add basic tests for NamedParamsMixin. Related to #95
• Check partial globals work.\ E.g. ipsi_spread should set the spread of all LNLs in the ipsi model. Related to #95

Change

• (mid) Set default use_central=False.\ This is a more sane default and does not result in a ValueError when creating the model with the default arguments.
• (hpv) Put data split into HPV class.
• (hpv) Delegate methods via hpv_status arg.\ Instead of re-implementing or copy-pasting methods from the Unilateral class, they simply compute those model's corresponding method that was selected via the hpv_status (keyword) argument.

- Python
Published by rmnldwg over 1 year ago

lymph-model -

What's New

This is very minor and I only release this tiny update, so that I can depend on all models having the binary and trinary constructor in lyscripts.

Features

• (mid) Add missing binary constructor to Midline model. Now all models have a binary and trinary constructor.

Styling

• Add rules to ruff.

Testing

• Make suite testable with pytest.

Ci

• Switch to pytest for testing.

- Python
Published by rmnldwg almost 2 years ago

lymph-model -

What's New

Bug Fixes

• (mid) Correct contra state dist evo. Fixes #85.\ Previously, the model did not correctly marginalize over the possible time when a tumor can grow over the midline. It simply assumed that it did from the onset.

Documentation

• (uni) Remove outdated docstring paragraph. Fixes #88.

Miscellaneous Tasks

• Bump pre-commit versions.

Styling

• Use ruff to fix lint and format code.

Build

• Remove upper cap in deps.

Change

• risk() meth requires involvement. Fixes #87.\ We figured it does not make sense to allow passing involvement=None into the risk() method just to have it return 1. This is except for the midline class, where involvement may reasonably be None while midext isn't.\ Also, I ran ruff over some files, fixing some code style issues.

- Python
Published by rmnldwg almost 2 years ago

lymph-model -

Changelog

All notable changes to this project will be documented in this file.

What's New

Bug fixes and two tiny features.

Bug Fixes

• (uni) load_patient_data should accept None.
• (mid) Correct type hint of marginalize.
• (graph) Wrong dict when trinary.\ The to_dict() method returned a wrong graph dictionary when trinary due to growth edges. This is fixed now.
• Skip marginalize only when safe.\ The marginalization should only be skipped (and 1 returned), when the entire disease state of interest is None. In the midline case, this disease state includes the midline extension.\ Previously, only the involvement pattern was checked. Now, the model is more careful about when to take shortcuts.

Features

• (graph) Modify mermaid graph.\ The get_mermaid() and get_mermaid_url() methods now accept arguments that allow some modifications of the output.
• (uni) Add __repr__().

Refactor

• (uni) Use pandas map instead of apply.\ This saves us a couple of lines in the load_patient_data method and is more readable.

Merge

• Branch 'main' into 'dev'.

Remove

• Remains of callbacks.\ Some callback functionality that was tested in a pre-release has been forgotten in the code base and is now deleted.

- Python
Published by rmnldwg about 2 years ago

lymph-model -

What's New

This feature update brings methods to the models that allow a more modular use of them. Otherwise, nothing spectacular.

Bug Fixes

• (mid) obs_dist may return 3D array.

Documentation

• Fix unknown version in title.
• Add missing blank before list.
• (mid) Add comment about midext marginalizing.

Features

• (mid) Add posterior_state_dist() method.\ The Midline model now has a posterior_state_dist() method, too.
• (types) Base Model has state dist methods.\ Both state_dist() and posterior_state_dist() have been added to the types.Model base class.
• Add marginalize() method.\ With this new method, one can marginalize a (prior or posterior) state distribution over all states that match a provided involvement.\ It is used e.g. to refactor the code of the risk() methods.
• (types) Add obs_dist and marginalize.\ The types.Model base abstract base class now also has the methods obs_dist and marginalize for better autocomplete support in editors.

Testing

• Remove plain test risk.

Change

• (types) Improve type hints for inv. pattern.
• Rename "diagnose" to "diagnosis" when noun.\ When used as a noun, "diagnosis" is correct, not "diagnose".

Full diff: https://github.com/rmnldwg/lymph/compare/1.1.0...1.2.0

- Python
Published by rmnldwg about 2 years ago

lymph-model -

What's New

With this feature update, it becomes possible to speed up repeated risk predictions by providing it with precomputed state distributions. These state distributions are the most expensive part of most models.

Features

• (utils) Add safe_set_params() function.\ This checks whether the params are a dict, list, or None and handles them accordingly. Just a convencience method that helped refactor some methods.
• Allow to pass state distributions to posterior_state_dist() and risk() methds. Fixes #80.\ With this, one can use precomputed state distributions to speed up computing the posterior or risk for multiple scenarios.

Refactor

• Use safe_set_params() across models.

Testing

• Add checks for midline risk. Related #80.
• (mid) Fix wrong assumption in risk test.

Full Changelog: https://github.com/rmnldwg/lymph/compare/1.0.0...1.1.0

- Python
Published by rmnldwg about 2 years ago

lymph-model -

Finally 🎉

Eventually, I did manage to decide on an API that I want to stick with for the foreseeable future.

If you have used the previous version 0.4.3, then forget everything you knew about that and head over to the documentation to learn everything from scratch. The core concepts stay the same though.

Full diff since last release candidate: https://github.com/rmnldwg/lymph/compare/1.0.0.rc2...1.0.0 Full diff since 0.4.3: https://github.com/rmnldwg/lymph/compare/0.4.3...1.0.0

Bug Fixes

• (uni) Catch error when apply to empty data. Fixes #79.\ For some reason, using apply on an empty DataFrame has an entirely different return type than when it is not empty. This caused the issue #79 and has now been fixed.
• (bi) Data reload loads wrong side.\ Now the data does not get reloaded anymore, which was actually unnecessary in the first place.
• (uni) Return correctly in get_spread_params.
• (mid) Consume & return params in same order.
• (uni) Allow mapping=None when loading data.

Testing

• (uni) Check if loading empty data works. Related #79.
• (uni) Make sure likelihood is deterministic.

Change

• ⚠ BREAKING (uni) Shorten two (unused) method names.
• ⚠ BREAKING helpers are now utils.
• (type) Add type definition for graph dict.
• (diag) Use partials to save parametric dist.

- Python
Published by rmnldwg about 2 years ago

lymph-model -

What's New

Implementing the lymixture brought to light a shortcoming in the way the data and diagnose matrices are computed and stored. As mentioned in issue #77, their rows are now aligned with the patient data, which may have some advantages for different use cases.

Also, since this is probably the last pre-release, I took the liberty to go over some method names once more and make them clearer.

All changes: https://github.com/rmnldwg/lymph/compare/1.0.0.rc1...1.0.0.rc2

Bug Fixes

• Don't use fake T-stage for BN model. Related #77.\ Since we now have access to the full diagnose matrix by default, there is no need for the Bayesian network T-stage fix anymore.
• (uni) Reload data when modalities change.\ Because we only store those diagnoses that are relevant to the model under the "model" header in the `patientdata` table, we need to reload the patient data whenever we modify the modalities.

Documentation

• Update to slightly changed API.
• (bi) Add bilateral quickstart to docs.

Features

• (mod) Add utils to check for modality changes.

Performance

• (uni) Make data & diagnose matrices faster. Related #77.\ The last change caused a dramatic slowdown (factor 500) of the data and diagnose matrix access, because it needed to index them from a DataFrame. Now, I implemented a basic caching scheme with a patient data cache version that brought back the original speed. Also, apparently del dataframe[column] is much slower than dataframe.drop(columns). I replaced the former with the latter and now the tests are fast again.

Refactor

• ⚠ BREAKING Rename methods for brevity & clarity.\ Method names have been changed, e.g comp_dist_evolution() has been renamed to state_dist_evo() which is both shorter and (imho) clearer.
• (uni) Move data/diag matrix generation.

Testing

• Update to slightly changed API.
• (uni) Check reset of data on modality change.\ Added a test to make sure the patient data gets reloaded when the modalities change. This test is still failing.
• Finally suppress all PerformanceWarnings.

Change

• ⚠ BREAKING Store data & diagnose matrices in data. Fixes #77.\ Instead of weird, dedicated UserDicts, I simply use the patient data to store the data encoding and diagnose probabilities for each patient. This has the advantage that the entire matrix (irrespective of T-stage) is aligned with the patients.
• ⚠ BREAKING (bi) Shorten kwargs.\ The (uni|ipsi|contra)lateral_kwargs in the Bilateral constructor were shortened by removing the "lateral".

Merge

• Branch 'main' into 'dev'.
• Branch '77-diagnose-matrices-not-aligned-with-data' into 'dev'.

Remove

• Unused helpers.

- Python
Published by rmnldwg about 2 years ago

lymph-model -

What's New

This release hopefully represents the last major change before releasing version 1.0.0. It was necessary because during the implementation of the midline model, managing the symmetries in a transparent and user-friendly way became impossible in the old implementation.

Now, a composite pattern is used for both the modalities and the distributions over diagnose times. This furhter separates the logic and will allow more hierarchical models based on the ones provided here to work seamlessly almost out of the box. This may become relevant with the mixture model.

Big thanks to @YoelPH for implementing large parts of the midline model! 👏🏻

The full diff can be found here: https://github.com/rmnldwg/lymph/compare/1.0.0.a6...1.0.0.rc1

Add

• Midline module added. This makes the code now feature complete again (compared to version 0.4.3). It also implements the evolution of the midline extension as random variable.

Bug Fixes

• (diag) Delete frozen distributions when params change.
• (diag) Correct max time & params.\ The max_time is now correctly accessed and set. Also, the distribution params are not used up by synched distributions, but only by the distributions in composite leafs.
• (graph) Avoid warning for micro mod setting.
• ⚠ BREAKING Make likelihood work with emcee again.\ The way the likelihood was defined, it did not actually play nicely with how the emcee package works. This is now fixed.
• (bi) Fix uninitialized is_symmetric dict.
• (mid) Add missing dict in init.
• (mid) Update call to transition_matrix() & state_list.
• (mid) Finish draw_patients method.\ Some bugs in the method for drawing synthetic patients from the Midline were fixed. This seems to be working now.

Documentation

• (mid) Improve midline docstrings slightly.
• Go over set_params() docstrings.
• Update quickstart guide to new API.
• Adapt tests to new API (now passing).
• Update index & fix some docstrings.
• Fix some typos and cross-references.

Features

• (helper) Add popfirst() and flatten().\ Two new helper function in relation to getting and setting params.
• (type) Add model ABC to inherit from.\ I added an abstract base class from which all model-like classes should inherit. It defines all the methods that need to be present in a model.\ The idea behind this is that any subclass of this can be part of a composite that correctly delegates getting/setting parameters, diagnose time distributions, and modalities.
• ⚠ BREAKING (graph) Add __hash__ to edge, node, graph.\ This replaces the dedicated parameter_hash() method.
• (mod) Add method to delete modality del_modality().
• Add more get/set params methods.
• (mid) Implement set_params.
• (mid) Implement the load_patient_data meth.
• (mid) Finish midline (feature complete).
• Complete set/get methods on model classes.\ The Unilateral, Bilateral, and Midline model now all have the six methods set_tumor_spread_params, set_lnl_spread_params, set_spread_params, set_params, get_tumor_spread_params, get_lnl_spread_params, get_spread_params, and get_params.
• (mid) Reimplement the midline evolution.\ The midline evolution that Lars Widmer worked on is now reimplemented. However, although this implementation is analogous to the one used in previsou version of the code and should thus work, it is still untested at this point.
• Add helper to draw diagnoses.\ The new helper functiondraw_diagnoses is a re-implementation of the Unilateral class's method with the same name for easier reusing.
• (mid) Allow marginalization over unknown midline extension.\ This is implemented differently than before: If data with unknown midline extension is added, it gets loaded into an attribute named unknown, which is a Bilateral model only used to store that data and generate diagnose matrices.

Miscellaneous Tasks

• Move timing data.
• Make changelog super detailed.

Refactor

• (mid) Split likelihood method.

Testing

• Fix long-running test.
• Add integration tests with emcee.
• Add checks for bilateral symmetries.
• (mid) Add first check of set_params() method.
• (mid) Check likelihood function.

Add

• Added doc strings.

Change

• Non-mixture midline implemented.\ fixed the non mixture midline extension model and added documentation
• ⚠ BREAKING Make get_params() uniform and chainable.\ The API of all get_params() methods is now nice and uniform, allowing arbitrary chaining of these methods.
• ⚠ BREAKING Make set_params() uniform and chainable.\ The API of all set_params() methods is now nice and uniform, allowing arbitrary chaining of these methods.
• ⚠ BREAKING Make set_params() not return kwargs.\ It does make sense to "use up" the positional arguments one by one in the set_params() methods, but doing the same thing with keyword arguments is pointless, difficult and error prone.
• ⚠ BREAKING (graph) Replace name with get_name().\ In the Edge class, the name property is replaced by a function get_name() that is more flexible and allows us to have edge names without underscores when we need it.
• ⚠ BREAKING (bi) Reintroduce is_symmetric attribute.\ This will once again manage the symmetry of the Bilateral class's different ipsi- and contralateral attributes.
• ⚠ BREAKING (diag) Use composite for distributions.\ Instead of a dict that holds the T-stages and corresponding distributions over diagnose times, this implements them as a composite pattern. This replaces the dict-like API entirely with methods. This has several advantages:
  1. It is more explicit and thus more readable
  2. The composite pattern is designed to work naturally with tree-like structures, which we have here when dealing with bilateral models.
• ⚠ BREAKING (mod) Use composite for modalities.\ Instead of a dict that holds the names and corresponding sens/spec for diagnostic modalities, this implements them as a composite pattern. This replaces the dict-like API entirely with methods. This has several advantages:
  1. It is more explicit and thus more readable
  2. The composite pattern is designed to work naturally with tree-like structures, which we have here when dealing with bilateral models.
• ⚠ BREAKING (uni) Transform to composite pattern.\ Use the new composite pattern for the distribution over diagnose times and modalities.
• (bi) Update for new composite API.
• ⚠ BREAKING (mod) Shorten to sens/spec.\ Also, add a clear_modalities() and a clear_distributions() method to the respective composites.
• (matrix) Use hashables over arg0 cache.\ Instead of using this weird arg0_cache for the observation and transition matrix, I use the necessary arguments only, which are all hashable now.
• ⚠ BREAKING Adapt risk to likelihood call signature.
• (type) Add risk to abstract methods.
• (type) Abstract methods raise error.

Merge

• Branch 'yoel-dev' into 'dev'.
• Branch '74-synchronization-is-unreadable-and-error-prone' into 'dev'. Fixes #74.
• Branch 'main' into 'dev'.
• Branch 'add-midext-evolution' into 'dev'.

Remove

• Unused helper functions.

- Python
Published by rmnldwg about 2 years ago

lymph-model -

What's New

With this (still alpha) release, we most notably fixed a long unnoticed bug in the computation of the Bayesian network likelihood.

Bug Fixes

• (uni) Leftover kwargs now correctly returned in assign_params()
• ⚠ BREAKING (uni) Remove is_<x>_shared entirely, as it was unused anyways. Fixes #72.
• T-stage mapping may be dictionary or callable
• (uni) Raise exception when there are no tumors or LNLs in graph

Documentation

• Fix typo in modalities

Testing

• (uni) Check constructor raises exceptions
• Check the Bayesian network likelihood

Change

• (uni) Trinary params are shared by default
• (uni) Prohibit setting max_time
• ⚠ BREAKING Change likelihood() API: We don't allow setting the data via the likelihood() anymore. It convoluted the method and setting it beforehand is more explicit anyways.

Full diff

- Python
Published by rmnldwg over 2 years ago

lymph-model -

What's New

In this alpha release we fixed more bugs and issues that emerged during more rigorous testing.

Most notably, we backed away from storing the transition matrix in a model's instance. Because it created opaque and confusion calls to functions trying to delete them when parameters were updated.

Instead, the function computing the transition matrix is now globally cached using a hash function from the graph representation. This has the drawback of slightly more computation time when calculating the hash. But the advantage is that e.g. in a bilateral symmetric model, the transition matrix of the two sides is only ever computed once when (synched) parameters are updated.

Bug Fixes

• (graph) Assume nodes is dictionary, not a list. Fixes #64
• (uni) Update draw_patients() method to output LyProX style data. Fixes #65
• (bi) Update bilateral data generation method to also generate LyProX style data. Fixes #65
• (bi) Syntax error in init_synchronization. Fixes #69
• (uni) Remove need for transition matrix deletion via a global cache. Fixes #68
• (uni) Use cached matrices & simplify stuff. Fixes #68
• (uni) Observation matrix only property, not cached anymore

Documentation

• Fix typos & formatting errors in docstrings

Features

• (graph) Implement graph hash for global cache of transition matrix
• (helper) Add an arg0 cache decorator that caches based on the first argument only
• (matrix) Use cache for observation & diagnose matrices. Fixes #68

Miscellaneous Tasks

• Update dependencies & classifiers

Refactor

• Variables inside generate_transition()

Testing

• Make doctests discoverable by unittest
• Update tests to changed API
• (uni) Assert format & distribution of drawn patients
• (uni) Allow larger delta for synthetic data distribution
• (bi) Check bilateral data generation method
• Check the bilateral model with symmetric tumor spread
• Make sure delete & recompute synced edges' tensor work
• Adapt tests to changed Edge API
• (bi) Evaluate transition matrix recomputation
• Update tests to match new transition matrix code
• Update trinary unilateral tests

Change

• ⚠ BREAKING Compute transition tensor globally. Fixes #69
• ⚠ BREAKING Make transition matrix a method instead of a property. Fixes #40
• ⚠ BREAKING Make observation matrix a method instead of a property. Fixes #40

Ci

• Add coverage test dependency back into project

Remove

• Unused files and directories

Full diff

- Python
Published by rmnldwg over 2 years ago

lymph-model -

What's New

Again, thanks to @YoelPH for finding (and coming up with solutions to fix) some critical bugs, especially w.r.t. the trinary model. Below is a list of notable changes since the last pre-release.

Bug Fixes

• Use lnls.keys() consistently everywhere
• Warn about symmetric params in asymmetric graph
• Make allowed_states accessible
• Provide base keyword argument to compute_encoding(). This is necessary for the trinary model (see #45)
• Ensure confusion matrix of trinary diagnostic modality has correct shape
• Make diagnostic encoding always binary
• Correct joint state/diagnose matrix (fixes #61)
• Send kwargs to both assign_params methods (fixes #60)
• Enable two-way sync between lookup dicts (fixes #62)

Documentation

• Add "see also" to get/set methods, thereby making them reference each other

Features

• Add trinary & keywords in encoding: When computing the risk for a certain pattern in a trinary model, one may now provide different kewords like "macro" to differentiate between different involvements of interest.
• Add convenience constructors to create binary and trinary bilateral models
• Allow bilateral model with an asymmetric graph structure
• Add get/set methods to DistributionsUserDict, which makes all get_params() and set_params() methods consistent across their occurences

Refactor

• Pull initialization of ipsi- & contralateral models out of Bilateral model's __init__()
• Restructure Bilateral model's __init__() method slightly

Testing

• Cover bilateral risk computation
• Cover unilateral risk method
• Check asymmetric model implementation
• Check binary/trinary & allowed_states
• Add trinary likelihood test
• Add risk check for trinary model
• Add checks for delegation of attrbutes & setting of params
• Check cached_property delegation works
• Check param assign thoroughly

Change

• Don't use custom subclass of cached_property that forbids setting and use the default cached_property instead
• Encode symmetries of Bilateral model in a special dict called is_summetric with keys "tumor_spread", "lnl_spread", and "modalities"

Full diff

- Python
Published by rmnldwg over 2 years ago

lymph-model -

What's New

Fourth alpha release. @YoelPH noticed some more bugs that have been fixed now. Most notably, the risk prediction raised exceptions, because of a missing transponed matrix .T.

Bug Fixes

• Raise ValueError if diagnose time parameters are invalid (Fixes #53)
• Use names of LNLs in unilateral comp_encoding() (Fixes #56)
• Wrong shape in unilateral posterior computation (missing .T) (Fixes #57)
• Wrong shape in bilateral joint posterior computation (missing .T) (Fixes #57)

Documentation

• Add info on diagnose time distribution's ValueError

Testing

• ValueError raised in diagnose time distribution's set_params
• Check comp_encoding_diagnoses() for shape and dtype
• Test unilateral posterior state distribution for shape and sum
• Test bilateral posterior joint state distribution for shape and sum

Full diff

- Python
Published by rmnldwg over 2 years ago

lymph-model -

What's New

Third alpha release. I am pretty confident that the lymph.models.Unilateral class works as intended since it does yield the same results as the 0.4.3 version.

The lymph.models.Bilateral class is presumably finished now as well, although there may still be issues with that. It does however compute a likelihood if asked to do so, and the results don't look implausible. So, it might be worth giving it a spin.

Also, I am now quite satisfied with the look and usability of the new API. Hopefully, this means only minor changes from here on.

Full changelog: 1.0.0.a1...1.0.0.a2

Bug Fixes

• (bi) Sync callback was wrong way around
• Assigning new modalities now preserves the trigger_callbacks
• Set diag_time_dists params won't fail anymore
• (bi) Don't change dict size during modalities sync
• (bi) Delegted generator attribute now resets
• (bi) Make modalities/diag_time_dists syncable
• (uni) Evolution is now running through all time-steps

Documentation

• Switch to MyST style sphinx theme
• 🛠️ Start with bilateral quickstart guide
• (uni) Reproduce llh with old and new model

Features

• Re-implement bilateral model class
• (bi) Continue rewriting bilateral class
• (helper) Add DelegatorMixin to helpers
• (uni) Use delegator to pull graph attrs up
• (bi) Add delegation of uni attrs to bilateral
• (bi) Reimplement joint state/obs dists & llh
• (uni) Allow global setting of micro & growth
• (uni) Reimplement Bayesian network model
• (log) Add logging to sync callback creation
• Get params also as iterator
• (uni) Get only edge/dist params

Refactor

• state_list is now a member of the graph.Representation & computation of involvement pattern encoding is separate function now
• subclasses of cached_property are used for e.g. transition and observation matrix instead of convoluted descriptors

Testing

• (uni) Add tests w.r.t. delegator mixin
• (bi) Check the delegation of ipsi attrs
• (bi) Check sync for bilateral model
• Refactor out fixtures from test suite
• Make sure bilateral llh is deterministic
• Catch warnings for cleaner output
• (uni) Add likelihood value tests

Change

• assign_params & joint posterior
• ⚠ BREAKING (graph) Remove edge_params lookup in favour of an edge dictionary in the graph.Representation
• ⚠ BREAKING The edge's and dist's get_params() and set_params() methods now have the same function signature, making a combined loop over both possible
• (bi) Rewrite the bilateral risk method
• ⚠ BREAKING Allow setting params as positional & keyword arguments in both the likelihood and the risk method

Ci

• Bump codecov action to v3

Merge

• Branch 'main' into 'dev'
• Branch 'dev' into 'reimplement-bilateral'
• Branch 'delegation-pattern' into 'dev'
• Branch 'dev' into 'reimplement-bilateral'
• Branch 'remove-descriptors' into 'reimplement-bilateral'
• Branch 'reimplement-bilateral' into 'dev'

- Python
Published by rmnldwg over 2 years ago

lymph-model -

Second alpha release to allow early testing of the new API.

What's New

Bug Fixes

• (matrix) Wrong shape of observation matrix for trinary model

Documentation

• Fix wrong python version in rtd config file
• Remove outdated sampling tutorial
• Remove deprecated read-the-docs config
• Tell read-the-docs to install extra requirements
• Execute quickstart notebook

Testing

• Check correct shapes for trinary model matrices

Full changelog: 1.0.0.a0...1.0.0.a1

- Python
Published by rmnldwg almost 3 years ago

lymph-model -

This alpha release is a reimplementation most of the package's API. It aims to solve some issues that accumulated for a while.

Features

• parameters can now be assigned centrally via a assign_params() method, either using args or keyword arguments. This resolves #46
• expensive operations generally look expensive now, and do not just appear as if they were attribute assignments. Fixes #40
• computations around the the likelihood and risk predictions are now more modular. I.e., several conditional and joint probability vectors/matrices can now be computed conveniently and are not burried in large methods. Resolves isse #41
• support for the trinary model was added. This means lymph node levels (LNLs) can be in one of three states (healthy, microscopic involvement, macroscopic metatsasis), instead of only two (healthy, involved). Resolves #45

Documentation

• module, class, method, and attribute docstrings should now be more detailed and helpful. We switched from strictly adhering to Numpy-style docstrings to something more akin to Python's core library docstrings. I.e., parameters and behaviour are explained in natural language.
• quickstart guide has been adapted to the new API

Code Refactoring

• all matrices related to the underlying hidden Markov model (HMM) have been decoupled from the Unilateral model class
• the representation of the directed acyclic graph (DAG) that determined the directions of spread from tumor to and among the LNLs has been implemented in a separate class of which an instance provides access to it as an attribute of Unilateral
• access to all parameters of the graph (i.e., the edges) is bundled in a descriptor holding a UserDict

BREAKING CHANGES

Almost the entire API has changed. I'd therefore recommend to have a look at the quickstart guide to see how the new model is used. Although most of the core concepts are still the same.

- Python
Published by rmnldwg almost 3 years ago

lymph-model -

Minimal bug fix to get a script running again.

What's new

Bug Fixes

• incomplete involvement for unilateral risk method does not raise KeyError anymore. Fixes issue #38

all changes

- Python
Published by rmnldwg over 3 years ago

lymph-model -

Minor bump that was mostly about getting the documentation's build to pass again and add a changelog to the project. The actual library's API has been left untouched.

What's new

Documentation

• fix the issue of docs failing to build
• remove outdated line in install instructions
• move conf.py back into source dir
• bundle sphinx requirements
• update the quickstart & sampling notebooks
• more stable sphinx-build & update old index

Maintenance

• fine-tune git-chglog settings to my needs
• start with a CHANGELOG
• add description to types of allowed commits

all changes

- Python
Published by rmnldwg almost 4 years ago

lymph-model -

Fixes:

• fix a typo in the pyproject.toml that caused the README to disappear from PyPI

- Python
Published by rmnldwg almost 4 years ago

lymph-model -

What's new:

• a dict-like class has been added that elegantly takes care of defining and updating the distributions that are used to marginalize over the diagnose times
• the API for the likelihood got an overhaul, using the mentioned new class. It should be much more readable and easier to use, since one does not have to worry about providing time distributions as arguments anymore
• the API for the risk was changed similarly. Therefore, the most important user-facing methods have gotten a facelift

Unfortunately, I currently do not have the time to update the entire test suite. I managed to write a somewhat realistic integration test, but dropped some unit tests. I will at some point catch up on this.

- Python
Published by rmnldwg almost 4 years ago

lymph-model -

First release 🥳

This marks the first release, which will also be pushed to PyPI.

What's new

• faster tests
• fix graph-order issue #31

- Python
Published by rmnldwg almost 4 years ago