0.11.0

• A new topic model tomotopy.PTModel for short texts was added into the package.
• An issue was fixed where tomotopy.HDPModel.infer causes a segmentation fault sometimes.
• A mismatch of numpy API version was fixed.
• Now asymmetric document-topic priors are supported.
• Serializing topic models to bytes in memory is supported.
• An argument normalize was added to get_topic_dist(), get_topic_word_dist() and get_sub_topic_dist() for controlling normalization of results.
• Now tomotopy.DMRModel.lambdas and tomotopy.DMRModel.alpha give correct values.
• Categorical metadata supports for tomotopy.GDMRModel were added (see https://github.com/bab2min/tomotopy/blob/main/examples/gdmr_both_categorical_and_numerical.py ).
• Python3.5 support was dropped.

0.10.2

• An issue was fixed where tomotopy.CTModel.train fails with large K.
• An issue was fixed where tomotopy.utils.Corpus loses their uid values.

0.10.1

• An issue was fixed where tomotopy.utils.Corpus.extract_ngrams craches with empty input.
• An issue was fixed where tomotopy.LDAModel.infer raises exception with valid input.
• An issue was fixed where tomotopy.HLDAModel.infer generates wrong tomotopy.Document.path.
• Since a new parameter freeze_topics for tomotopy.HLDAModel.train was added, you can control whether to create a new topic or not when training.

0.10.0

• The interface of tomotopy.utils.Corpus and of tomotopy.LDAModel.docs were unified. Now you can access the document in corpus with the same manner.
• getitem of tomotopy.utils.Corpus was improved. Not only indexing by int, but also by Iterable[int], slicing are supported. Also indexing by uid is supported.
• New methods tomotopy.utils.Corpus.extract_ngrams and tomotopy.utils.Corpus.concat_ngrams were added. They extracts n-gram collocations using PMI and concatenates them into a single words.
• A new method tomotopy.LDAModel.add_corpus was added, and tomotopy.LDAModel.infer can receive corpus as input.
• A new module tomotopy.coherence was added. It provides the way to calculate coherence of the model.
• A paramter window_size was added to tomotopy.label.FoRelevance.
• An issue was fixed where NaN often occurs when training tomotopy.HDPModel.
• Now Python3.9 is supported.
• A dependency to py-cpuinfo was removed and the initializing of the module was improved.

0.9.1

• Memory leaks of version 0.9.0 was fixed.
• tomotopy.CTModel.summary() was fixed.

0.9.0

• The tomotopy.LDAModel.summary() method, which prints human-readable summary of the model, has been added.
• The random number generator of package has been replaced with EigenRand. It speeds up the random number generation and solves the result difference between platforms.
• Due to above, even if seed is the same, the model training result may be different from the version before 0.9.0.
• Fixed a training error in tomotopy.HDPModel.
• tomotopy.DMRModel.alpha now shows Dirichlet prior of per-document topic distribution by metadata.
• tomotopy.DTModel.get_count_by_topics() has been modified to return a 2-dimensional ndarray.
• tomotopy.DTModel.alpha has been modified to return the same value as tomotopy.DTModel.get_alpha().
• Fixed an issue where the metadata value could not be obtained for the document of tomotopy.GDMRModel.
• tomotopy.HLDAModel.alpha now shows Dirichlet prior of per-document depth distribution.
• tomotopy.LDAModel.global_step has been added.
• tomotopy.MGLDAModel.get_count_by_topics() now returns the word count for both global and local topics.
• tomotopy.PAModel.alpha, tomotopy.PAModel.subalpha, and tomotopy.PAModel.get_count_by_super_topic() have been added.

0.8.2

• New properties tomotopy.DTModel.num_timepoints and tomotopy.DTModel.num_docs_by_timepoint have been added.
• A bug which causes different results with the different platform even if seeds were the same was partially fixed.
  As a result of this fix, now tomotopy in 32 bit yields different training results from earlier version.

0.8.1

• A bug where tomotopy.LDAModel.used_vocabs returned an incorrect value was fixed.
• Now tomotopy.CTModel.prior_cov returns a covariance matrix with shape [k, k].
• Now tomotopy.CTModel.get_correlations with empty arguments returns a correlation matrix with shape [k, k].

0.8.0

• Since NumPy was introduced in tomotopy, many methods and properties of tomotopy return not just list, but numpy.ndarray now.
• Tomotopy has a new dependency NumPy >= 1.10.0.
• A wrong estimation of tomotopy.HDPModel.infer was fixed.
• A new method about converting HDPModel to LDAModel was added.
• New properties including tomotopy.LDAModel.used_vocabs, tomotopy.LDAModel.used_vocab_freq and tomotopy.LDAModel.used_vocab_df were added into topic models.
• A new g-DMR topic model(tomotopy.GDMRModel) was added.
• An error at initializing tomotopy.label.FoRelevance in macOS was fixed.
• An error that occured when using tomotopy.utils.Corpus created without raw parameters was fixed.

0.7.1

• tomotopy.Document.path was added for tomotopy.HLDAModel.
• A memory corruption bug in tomotopy.label.PMIExtractor was fixed.
• A compile error in gcc 7 was fixed.