README.rst in tomoto-0.2.0

- old
+ new

@@ -30,30 +30,29 @@
 * Hierarchical LDA (`tomotopy.HLDAModel`)
 * Multi Grain LDA (`tomotopy.MGLDAModel`) 
 * Pachinko Allocation (`tomotopy.PAModel`)
 * Hierarchical PA (`tomotopy.HPAModel`)
 * Correlated Topic Model (`tomotopy.CTModel`)
-* Dynamic Topic Model (`tomotopy.DTModel`).
+* Dynamic Topic Model (`tomotopy.DTModel`)
+* Pseudo-document based Topic Model (`tomotopy.PTModel`).
 
 Please visit https://bab2min.github.io/tomotopy to see more information.
 
-The most recent version of tomotopy is 0.10.2.
-
 Getting Started
 ---------------
 You can install tomotopy easily using pip. (https://pypi.org/project/tomotopy/)
 ::
 
     $ pip install --upgrade pip
     $ pip install tomotopy
 
 The supported OS and Python versions are:
 
-* Linux (x86-64) with Python >= 3.5 
-* macOS >= 10.13 with Python >= 3.5
-* Windows 7 or later (x86, x86-64) with Python >= 3.5
-* Other OS with Python >= 3.5: Compilation from source code required (with c++11 compatible compiler)
+* Linux (x86-64) with Python >= 3.6 
+* macOS >= 10.13 with Python >= 3.6
+* Windows 7 or later (x86, x86-64) with Python >= 3.6
+* Other OS with Python >= 3.6: Compilation from source code required (with c++14 compatible compiler)
 
 After installing, you can start tomotopy by just importing.
 ::
 
     import tomotopy as tp
@@ -259,10 +258,32 @@
 `tomotopy` is licensed under the terms of MIT License, 
 meaning you can use it for any reasonable purpose and remain in complete ownership of all the documentation you produce.
 
 History
 -------
+* 0.12.0 (2021-04-26)
+    * Now `tomotopy.DMRModel` and `tomotopy.GDMRModel` support multiple values of metadata (see https://github.com/bab2min/tomotopy/blob/main/examples/dmr_multi_label.py )
+    * The performance of `tomotopy.GDMRModel` was improved.
+    * A `copy()` method has been added for all topic models to do a deep copy.
+    * An issue was fixed where words that are excluded from training (by `min_cf`, `min_df`) have incorrect topic id. Now all excluded words have `-1` as topic id.
+    * Now all exceptions and warnings that generated by `tomotopy` follow standard Python types.
+    * Compiler requirements have been raised to C++14.
+
+* 0.11.1 (2021-03-28)
+    * A critical bug of asymmetric alphas was fixed. Due to this bug, version 0.11.0 has been removed from releases.
+
+* 0.11.0 (2021-03-26) (removed)
+    * 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 (2021-02-16)
     * 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 (2021-02-14)
@@ -271,10 +292,10 @@
     * 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 (2020-12-19)
     * 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.
+    * `__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`.