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fehlende ordner geadded

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jannis.grundmann 2017-09-11 13:03:20 +02:00
parent 991353b1bb
commit 67e6f8845c
33 changed files with 2691 additions and 0 deletions
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2
.gitignore vendored
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@ -26,6 +26,8 @@ wheels/
*.egg-info/ *.egg-info/
.installed.cfg .installed.cfg
*.egg *.egg
openthesaurus.csv
# PyInstaller # PyInstaller
# Usually these files are written by a python script from a template # Usually these files are written by a python script from a template

10
java_LabledLDA/.idea/libraries/lib.xml Normal file
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@ -0,0 +1,10 @@
<component name="libraryTable">
<library name="lib">
<CLASSES>
<root url="file://$PROJECT_DIR$/lib" />
</CLASSES>
<JAVADOC />
<SOURCES />
<jarDirectory url="file://$PROJECT_DIR$/lib" recursive="false" />
</library>
</component>

6
java_LabledLDA/.idea/misc.xml Normal file
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@ -0,0 +1,6 @@
<?xml version="1.0" encoding="UTF-8"?>
<project version="4">
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<output url="file://$PROJECT_DIR$/out" />
</component>
</project>

8
java_LabledLDA/.idea/modules.xml Normal file
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@ -0,0 +1,8 @@
<?xml version="1.0" encoding="UTF-8"?>
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<component name="ProjectModuleManager">
<modules>
<module fileurl="file://$PROJECT_DIR$/LabledLDA.iml" filepath="$PROJECT_DIR$/LabledLDA.iml" />
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</project>

439
java_LabledLDA/.idea/workspace.xml Normal file
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@ -0,0 +1,439 @@
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<item name="java_LabledLDA" type="b2602c69:ProjectViewProjectNode" />
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</path>
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<item name="java_LabledLDA" type="b2602c69:ProjectViewProjectNode" />
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<item name="models" type="462c0819:PsiDirectoryNode" />
<item name="bla" type="462c0819:PsiDirectoryNode" />
</path>
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<select />
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<pane id="Scope" />
<pane id="PackagesPane" />
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<property name="WebServerToolWindowFactoryState" value="false" />
<property name="aspect.path.notification.shown" value="true" />
<property name="last_opened_file_path" value="$PROJECT_DIR$" />
<property name="project.structure.last.edited" value="Libraries" />
<property name="project.structure.proportion" value="0.15" />
<property name="project.structure.side.proportion" value="0.2" />
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<option name="name" value="ConfigurationTypeDashboardGroupingRule" />
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<RuleState>
<option name="name" value="StatusDashboardGroupingRule" />
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<component name="RunManager" selected="Application.LDA">
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<extension name="coverage" enabled="false" merge="false" sample_coverage="true" runner="idea">
<pattern>
<option name="PATTERN" value="jgibblda.*" />
<option name="ENABLED" value="true" />
</pattern>
</extension>
<option name="MAIN_CLASS_NAME" value="jgibblda.LDA" />
<option name="VM_PARAMETERS" value="" />
<option name="PROGRAM_PARAMETERS" value="-dfile test.txt.gz -dir models/test -est -ntopics 4" />
<option name="WORKING_DIRECTORY" value="file://$PROJECT_DIR$" />
<option name="ALTERNATIVE_JRE_PATH_ENABLED" value="false" />
<option name="ALTERNATIVE_JRE_PATH" />
<option name="ENABLE_SWING_INSPECTOR" value="false" />
<option name="ENV_VARIABLES" />
<option name="PASS_PARENT_ENVS" value="true" />
<module name="LabledLDA" />
<envs />
</configuration>
<configuration default="true" type="Applet" factoryName="Applet">
<option name="HTML_USED" value="false" />
<option name="WIDTH" value="400" />
<option name="HEIGHT" value="300" />
<option name="POLICY_FILE" value="$APPLICATION_HOME_DIR$/bin/appletviewer.policy" />
<module />
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<option name="MAIN_CLASS_NAME" />
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<option name="ALTERNATIVE_JRE_PATH" />
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<option name="PASS_PARENT_ENVS" value="true" />
<module name="" />
<envs />
</configuration>
<configuration default="true" type="JUnit" factoryName="JUnit">
<extension name="coverage" enabled="false" merge="false" sample_coverage="true" runner="idea" />
<module name="" />
<option name="ALTERNATIVE_JRE_PATH_ENABLED" value="false" />
<option name="ALTERNATIVE_JRE_PATH" />
<option name="PACKAGE_NAME" />
<option name="MAIN_CLASS_NAME" />
<option name="METHOD_NAME" />
<option name="TEST_OBJECT" value="class" />
<option name="VM_PARAMETERS" value="-ea" />
<option name="PARAMETERS" />
<option name="WORKING_DIRECTORY" value="$MODULE_DIR$" />
<option name="ENV_VARIABLES" />
<option name="PASS_PARENT_ENVS" value="true" />
<option name="TEST_SEARCH_SCOPE">
<value defaultName="singleModule" />
</option>
<envs />
<patterns />
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<configuration default="true" type="#org.jetbrains.idea.devkit.run.PluginConfigurationType" factoryName="Plugin">
<module name="" />
<option name="VM_PARAMETERS" value="-Xmx512m -Xms256m -XX:MaxPermSize=250m -ea" />
<option name="PROGRAM_PARAMETERS" />
<predefined_log_file id="idea.log" enabled="true" />
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<configuration default="true" type="Remote" factoryName="Remote">
<option name="USE_SOCKET_TRANSPORT" value="true" />
<option name="SERVER_MODE" value="false" />
<option name="SHMEM_ADDRESS" value="javadebug" />
<option name="HOST" value="localhost" />
<option name="PORT" value="5005" />
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<extension name="coverage" enabled="false" merge="false" sample_coverage="true" runner="idea" />
<module name="" />
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<option name="ALTERNATIVE_JRE_PATH" />
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<option name="PARAMETERS" />
<option name="WORKING_DIRECTORY" value="$MODULE_DIR$" />
<option name="OUTPUT_DIRECTORY" />
<option name="ANNOTATION_TYPE" />
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<option name="PASS_PARENT_ENVS" value="true" />
<option name="TEST_SEARCH_SCOPE">
<value defaultName="singleModule" />
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<option name="USE_DEFAULT_REPORTERS" value="false" />
<option name="PROPERTIES_FILE" />
<envs />
<properties />
<listeners />
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<recent_temporary>
<list size="1">
<item index="0" class="java.lang.String" itemvalue="Application.LDA" />
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<option name="number" value="Default" />
<option name="presentableId" value="Default" />
<updated>1503915939387</updated>
<workItem from="1503915946354" duration="2197000" />
<workItem from="1503922346467" duration="827000" />
</task>
<servers />
</component>
<component name="TimeTrackingManager">
<option name="totallyTimeSpent" value="3024000" />
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<frame x="1919" y="0" width="1922" height="1081" extended-state="6" />
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<option value="0.2" />
</list>
</option>
</splitter-proportions>
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</state>
<state key="FacetStructureConfigurable.UI">
<settings>
<last-edited>No facets are configured</last-edited>
<splitter-proportions>
<option name="proportions">
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<option value="0.2" />
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</option>
</splitter-proportions>
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<settings>
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<settings>
<last-edited>1.7</last-edited>
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<option name="proportions">
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<option value="0.2" />
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</option>
</splitter-proportions>
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<state key="ModuleStructureConfigurable.UI">
<settings>
<last-edited>LabledLDA</last-edited>
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<option name="proportions">
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<option value="0.2" />
<option value="0.6" />
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</option>
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<last-edited>lib</last-edited>
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</list>
</option>
</splitter-proportions>
</settings>
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</states>
</component>
</project>

339
java_LabledLDA/LICENSE Normal file
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GNU GENERAL PUBLIC LICENSE
Version 2, June 1991
Copyright (C) 1989, 1991 Free Software Foundation, Inc.,
51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA
Everyone is permitted to copy and distribute verbatim copies
of this license document, but changing it is not allowed.
Preamble
The licenses for most software are designed to take away your
freedom to share and change it. By contrast, the GNU General Public
License is intended to guarantee your freedom to share and change free
software--to make sure the software is free for all its users. This
General Public License applies to most of the Free Software
Foundation's software and to any other program whose authors commit to
using it. (Some other Free Software Foundation software is covered by
the GNU Lesser General Public License instead.) You can apply it to
your programs, too.
When we speak of free software, we are referring to freedom, not
price. Our General Public Licenses are designed to make sure that you
have the freedom to distribute copies of free software (and charge for
this service if you wish), that you receive source code or can get it
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To protect your rights, we need to make restrictions that forbid
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These restrictions translate to certain responsibilities for you if you
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For example, if you distribute copies of such a program, whether
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you have. You must make sure that they, too, receive or can get the
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rights.
We protect your rights with two steps: (1) copyright the software, and
(2) offer you this license which gives you legal permission to copy,
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Finally, any free program is threatened constantly by software
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The precise terms and conditions for copying, distribution and
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GNU GENERAL PUBLIC LICENSE
TERMS AND CONDITIONS FOR COPYING, DISTRIBUTION AND MODIFICATION
0. This License applies to any program or other work which contains
a notice placed by the copyright holder saying it may be distributed
under the terms of this General Public License. The "Program", below,
refers to any such program or work, and a "work based on the Program"
means either the Program or any derivative work under copyright law:
that is to say, a work containing the Program or a portion of it,
either verbatim or with modifications and/or translated into another
language. (Hereinafter, translation is included without limitation in
the term "modification".) Each licensee is addressed as "you".
Activities other than copying, distribution and modification are not
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is covered only if its contents constitute a work based on the
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Whether that is true depends on what the Program does.
1. You may copy and distribute verbatim copies of the Program's
source code as you receive it, in any medium, provided that you
conspicuously and appropriately publish on each copy an appropriate
copyright notice and disclaimer of warranty; keep intact all the
notices that refer to this License and to the absence of any warranty;
and give any other recipients of the Program a copy of this License
along with the Program.
You may charge a fee for the physical act of transferring a copy, and
you may at your option offer warranty protection in exchange for a fee.
2. You may modify your copy or copies of the Program or any portion
of it, thus forming a work based on the Program, and copy and
distribute such modifications or work under the terms of Section 1
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a) You must cause the modified files to carry prominent notices
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b) You must cause any work that you distribute or publish, that in
whole or in part contains or is derived from the Program or any
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c) If the modified program normally reads commands interactively
when run, you must cause it, when started running for such
interactive use in the most ordinary way, to print or display an
announcement including an appropriate copyright notice and a
notice that there is no warranty (or else, saying that you provide
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does not normally print such an announcement, your work based on
the Program is not required to print an announcement.)
These requirements apply to the modified work as a whole. If
identifiable sections of that work are not derived from the Program,
and can be reasonably considered independent and separate works in
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entire whole, and thus to each and every part regardless of who wrote it.
Thus, it is not the intent of this section to claim rights or contest
your rights to work written entirely by you; rather, the intent is to
exercise the right to control the distribution of derivative or
collective works based on the Program.
In addition, mere aggregation of another work not based on the Program
with the Program (or with a work based on the Program) on a volume of
a storage or distribution medium does not bring the other work under
the scope of this License.
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under Section 2) in object code or executable form under the terms of
Sections 1 and 2 above provided that you also do one of the following:
a) Accompany it with the complete corresponding machine-readable
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c) Accompany it with the information you received as to the offer
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except as expressly provided under this License. Any attempt
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license would not permit royalty-free redistribution of the Program by
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implemented by public license practices. Many people have made
generous contributions to the wide range of software distributed
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This section is intended to make thoroughly clear what is believed to
be a consequence of the rest of this License.
8. If the distribution and/or use of the Program is restricted in
certain countries either by patents or by copyrighted interfaces, the
original copyright holder who places the Program under this License
may add an explicit geographical distribution limitation excluding
those countries, so that distribution is permitted only in or among
countries not thus excluded. In such case, this License incorporates
the limitation as if written in the body of this License.
9. The Free Software Foundation may publish revised and/or new versions
of the General Public License from time to time. Such new versions will
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Each version is given a distinguishing version number. If the Program
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either of that version or of any later version published by the Free
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NO WARRANTY
11. BECAUSE THE PROGRAM IS LICENSED FREE OF CHARGE, THERE IS NO WARRANTY
FOR THE PROGRAM, TO THE EXTENT PERMITTED BY APPLICABLE LAW. EXCEPT WHEN
OTHERWISE STATED IN WRITING THE COPYRIGHT HOLDERS AND/OR OTHER PARTIES
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WILL ANY COPYRIGHT HOLDER, OR ANY OTHER PARTY WHO MAY MODIFY AND/OR
REDISTRIBUTE THE PROGRAM AS PERMITTED ABOVE, BE LIABLE TO YOU FOR DAMAGES,
INCLUDING ANY GENERAL, SPECIAL, INCIDENTAL OR CONSEQUENTIAL DAMAGES ARISING
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PROGRAMS), EVEN IF SUCH HOLDER OR OTHER PARTY HAS BEEN ADVISED OF THE
POSSIBILITY OF SUCH DAMAGES.
END OF TERMS AND CONDITIONS
How to Apply These Terms to Your New Programs
If you develop a new program, and you want it to be of the greatest
possible use to the public, the best way to achieve this is to make it
free software which everyone can redistribute and change under these terms.
To do so, attach the following notices to the program. It is safest
to attach them to the start of each source file to most effectively
convey the exclusion of warranty; and each file should have at least
the "copyright" line and a pointer to where the full notice is found.
<one line to give the program's name and a brief idea of what it does.>
Copyright (C) <year> <name of author>
This program is free software; you can redistribute it and/or modify
it under the terms of the GNU General Public License as published by
the Free Software Foundation; either version 2 of the License, or
(at your option) any later version.
This program is distributed in the hope that it will be useful,
but WITHOUT ANY WARRANTY; without even the implied warranty of
MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
GNU General Public License for more details.
You should have received a copy of the GNU General Public License along
with this program; if not, write to the Free Software Foundation, Inc.,
51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA.
Also add information on how to contact you by electronic and paper mail.
If the program is interactive, make it output a short notice like this
when it starts in an interactive mode:
Gnomovision version 69, Copyright (C) year name of author
Gnomovision comes with ABSOLUTELY NO WARRANTY; for details type `show w'.
This is free software, and you are welcome to redistribute it
under certain conditions; type `show c' for details.
The hypothetical commands `show w' and `show c' should show the appropriate
parts of the General Public License. Of course, the commands you use may
be called something other than `show w' and `show c'; they could even be
mouse-clicks or menu items--whatever suits your program.
You should also get your employer (if you work as a programmer) or your
school, if any, to sign a "copyright disclaimer" for the program, if
necessary. Here is a sample; alter the names:
Yoyodyne, Inc., hereby disclaims all copyright interest in the program
`Gnomovision' (which makes passes at compilers) written by James Hacker.
<signature of Ty Coon>, 1 April 1989
Ty Coon, President of Vice
This General Public License does not permit incorporating your program into
proprietary programs. If your program is a subroutine library, you may
consider it more useful to permit linking proprietary applications with the
library. If this is what you want to do, use the GNU Lesser General
Public License instead of this License.

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<?xml version="1.0" encoding="UTF-8"?>
<module type="JAVA_MODULE" version="4">
<component name="NewModuleRootManager" inherit-compiler-output="true">
<exclude-output />
<content url="file://$MODULE_DIR$">
<sourceFolder url="file://$MODULE_DIR$/src" isTestSource="false" />
<sourceFolder url="file://$MODULE_DIR$/bin" isTestSource="false" generated="true" />
</content>
<orderEntry type="inheritedJdk" />
<orderEntry type="sourceFolder" forTests="false" />
<orderEntry type="library" name="lib" level="project" />
</component>
</module>

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Labeled LDA in Java (based on JGibbLDA)
=======================================
This is a Java implementation of Labeled LDA based on the popular
[JGibbLDA](http://jgibblda.sourceforge.net/) package. The code has been heavily
refactored and a few additional options have been added. See sections below for
more details.
Data Format
-----------
The input data format is similar to the [JGibbLDA input data
format](http://jgibblda.sourceforge.net/#_2.3._Input_Data_Format), with some
minor cosmetic changes and additional support for document labels necessary for
Labeled LDA. We first describe the (modified) input format for unlabeled
documents, followed by the (new) input format for labeled documents.
**Changed from JGibbLDA**: All input/output files must be Gzipped.
### Unlabeled Documents
Unlabeled documents have the following format:
document_1
document_2
...
document_m
where each document is a space-separated list of terms, i.e.,:
document_i = term_1 term_2 ... term_n
**Changed from JGibbLDA**: The first line *should not* be an integer indicating
the number of documents in the file. The original JGibbLDA code has been
modified to identify the number of documents automatically.
**Note**: Labeled and unlabeled documents may be mixed in the input file, thus
you must ensure that unlabeled documents do not begin with a left square bracket
(see Labeled Document input format below). One easy fix is to prepend a space
character (' ') to each unlabeled document line.
### Labeled Documents
Labeled documents follow a format similar to unlabeled documents, but the with
labels given at the beginning of each line and surrounded by square brackets,
e.g.:
[label_1,1 label_1,2 ... label_1,l_1] document_1
[label_2,1 label_2,2 ... label_2,l_2] document_2
...
[label_m,1 label_m,2 ... label_m,l_m] document_m
where each label is an integer in the range [0, K-1], for K equal to the number
of topics (-ntopics).
**Note**: Labeled and unlabeled documents may be mixed in the input file. An
unlabeled document is equivalent to labeling a document with every label in the
range [0, K-1].
Usage
-----
Please see the [JGibbLDA usage](http://jgibblda.sourceforge.net/#_2.2._Command_Line_&_Input_Parameter), noting the following changes:
* All input files must be Gzipped. All output files are also Gzipped.
* New options have been added:
**-nburnin <int>**: Discard this many initial iterations when taking samples.
**-samplinglag <int>**: The number of iterations between samples.
**-infseparately**: Inference is done separately for each document, as if
inference for each document was performed in isolation.
**-unlabeled**: Ignore document labels, i.e., treat every document as
unlabeled.
* Some options have been deleted:
**-wordmap**: Filename is automatically built based on model path.
Contact
-------
Please direct questions to [Myle Ott](myleott@gmail.com).
License
-------
Following JGibbLDA, this code is licensed under the GPLv2. Please see the
LICENSE file for the full license.
Labeled LDA in Java
Copyright (C) 2008-2013 Myle Ott (Labeled LDA), Xuan-Hieu Phan and Cam-Tu Nguyen (JGibbLDA)
This program is free software; you can redistribute it and/or
modify it under the terms of the GNU General Public License
as published by the Free Software Foundation; either version 2
of the License, or (at your option) any later version.
This program is distributed in the hope that it will be useful,
but WITHOUT ANY WARRANTY; without even the implied warranty of
MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
GNU General Public License for more details.
You should have received a copy of the GNU General Public License
along with this program; if not, write to the Free Software
Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301, USA.

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/*
* Copyright (C) 2007 by
*
* Xuan-Hieu Phan
* hieuxuan@ecei.tohoku.ac.jp or pxhieu@gmail.com
* Graduate School of Information Sciences
* Tohoku University
*
* Cam-Tu Nguyen
* ncamtu@gmail.com
* College of Technology
* Vietnam National University, Hanoi
*
* JGibbsLDA is a free software; you can redistribute it and/or modify
* it under the terms of the GNU General Public License as published
* by the Free Software Foundation; either version 2 of the License,
* or (at your option) any later version.
*
* JGibbsLDA is distributed in the hope that it will be useful, but
* WITHOUT ANY WARRANTY; without even the implied warranty of
* MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
* GNU General Public License for more details.
*
* You should have received a copy of the GNU General Public License
* along with JGibbsLDA; if not, write to the Free Software Foundation,
* Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA.
*/
package jgibblda;
import java.io.BufferedReader;
import java.io.BufferedWriter;
import java.io.FileInputStream;
import java.io.FileOutputStream;
import java.io.InputStreamReader;
import java.io.OutputStreamWriter;
import java.util.zip.GZIPInputStream;
import java.util.zip.GZIPOutputStream;
import gnu.trove.map.hash.TObjectIntHashMap;
import gnu.trove.map.hash.TIntObjectHashMap;
public class Dictionary {
public TObjectIntHashMap<String> word2id;
public TIntObjectHashMap<String> id2word;
//--------------------------------------------------
// constructors
//--------------------------------------------------
public Dictionary(){
word2id = new TObjectIntHashMap<String>();
id2word = new TIntObjectHashMap<String>();
}
//---------------------------------------------------
// get/set methods
//---------------------------------------------------
public String getWord(int id){
return id2word.get(id);
}
public int getID(String word){
return word2id.get(word);
}
//----------------------------------------------------
// checking methods
//----------------------------------------------------
/**
* check if this dictionary contains a specified word
*/
public boolean contains(String word){
return word2id.containsKey(word);
}
public boolean contains(int id){
return id2word.containsKey(id);
}
//---------------------------------------------------
// manupulating methods
//---------------------------------------------------
/**
* add a word into this dictionary
* return the corresponding id
*/
public int addWord(String word){
if (!contains(word)){
int id = word2id.size();
word2id.put(word, id);
id2word.put(id,word);
return id;
}
else return getID(word);
}
//---------------------------------------------------
// I/O methods
//---------------------------------------------------
/**
* read dictionary from file
*/
public boolean readWordMap(String wordMapFile)
{
try {
BufferedReader reader = new BufferedReader(new InputStreamReader(
new GZIPInputStream(
new FileInputStream(wordMapFile)), "UTF-8"));
String line;
for (int i = 0; (line = reader.readLine()) != null; i++) {
String word = line.trim();
id2word.put(i, word);
word2id.put(word, i);
}
reader.close();
return true;
}
catch (Exception e) {
System.out.println("Error while reading dictionary:" + e.getMessage());
e.printStackTrace();
return false;
}
}
public boolean writeWordMap(String wordMapFile)
{
try {
BufferedWriter writer = new BufferedWriter(new OutputStreamWriter(
new GZIPOutputStream(
new FileOutputStream(wordMapFile)), "UTF-8"));
//write word to id
for (int i = 0; i < id2word.size(); i++) {
writer.write(id2word.get(i) + "\n");
}
writer.close();
return true;
}
catch (Exception e) {
System.out.println("Error while writing word map " + e.getMessage());
e.printStackTrace();
return false;
}
}
}

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/*
* Copyright (C) 2007 by
*
* Xuan-Hieu Phan
* hieuxuan@ecei.tohoku.ac.jp or pxhieu@gmail.com
* Graduate School of Information Sciences
* Tohoku University
*
* Cam-Tu Nguyen
* ncamtu@gmail.com
* College of Technology
* Vietnam National University, Hanoi
*
* JGibbsLDA is a free software; you can redistribute it and/or modify
* it under the terms of the GNU General Public License as published
* by the Free Software Foundation; either version 2 of the License,
* or (at your option) any later version.
*
* JGibbsLDA is distributed in the hope that it will be useful, but
* WITHOUT ANY WARRANTY; without even the implied warranty of
* MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
* GNU General Public License for more details.
*
* You should have received a copy of the GNU General Public License
* along with JGibbsLDA; if not, write to the Free Software Foundation,
* Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA.
*/
package jgibblda;
import gnu.trove.list.array.TIntArrayList;
public class Document {
//----------------------------------------------------
//Instance Variables
//----------------------------------------------------
public int[] words;
public String rawStr = "";
public int length;
public int[] labels = null;
public Document(TIntArrayList doc){
this.length = doc.size();
this.words = new int[length];
for (int i = 0; i < length; i++){
this.words[i] = doc.get(i);
}
}
public Document(TIntArrayList doc, String rawStr)
{
this(doc);
this.rawStr = rawStr;
}
public Document(TIntArrayList doc, String rawStr, TIntArrayList tlabels)
{
this(doc, rawStr);
this.labels = tlabels != null ? tlabels.toArray() : null;
}
}

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/*
* Copyright (C) 2007 by
*
* Xuan-Hieu Phan
* hieuxuan@ecei.tohoku.ac.jp or pxhieu@gmail.com
* Graduate School of Information Sciences
* Tohoku University
*
* Cam-Tu Nguyen
* ncamtu@gmail.com
* College of Technology
* Vietnam National University, Hanoi
*
* JGibbsLDA is a free software; you can redistribute it and/or modify
* it under the terms of the GNU General Public License as published
* by the Free Software Foundation; either version 2 of the License,
* or (at your option) any later version.
*
* JGibbsLDA is distributed in the hope that it will be useful, but
* WITHOUT ANY WARRANTY; without even the implied warranty of
* MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
* GNU General Public License for more details.
*
* You should have received a copy of the GNU General Public License
* along with JGibbsLDA; if not, write to the Free Software Foundation,
* Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA.
*/
package jgibblda;
import java.io.FileNotFoundException;
import java.io.IOException;
public class Estimator
{
// output model
protected Model trnModel;
LDACmdOption option;
public Estimator(LDACmdOption option) throws FileNotFoundException, IOException
{
this.option = option;
trnModel = new Model(option);
if (option.est){
trnModel.init(true);
}
else if (option.estc){
trnModel.init(false);
}
}
public void estimate()
{
System.out.println("Sampling " + trnModel.niters + " iterations!");
System.out.print("Iteration");
for (int startIter = ++trnModel.liter; trnModel.liter <= startIter - 1 + trnModel.niters; trnModel.liter++){
System.out.format("%6d", trnModel.liter);
// for all z_i
for (int m = 0; m < trnModel.M; m++){
for (int n = 0; n < trnModel.data.docs.get(m).length; n++){
// z_i = z[m][n]
// sample from p(z_i|z_-i, w)
int topic = sampling(m, n);
trnModel.z[m].set(n, topic);
}// end for each word
}// end for each document
if ((trnModel.liter == startIter - 1 + trnModel.niters) ||
(trnModel.liter > trnModel.nburnin && trnModel.liter % trnModel.samplingLag == 0)) {
trnModel.updateParams();
}
System.out.print("\b\b\b\b\b\b");
}// end iterations
trnModel.liter--;
System.out.println("\nSaving the final model!");
trnModel.saveModel();
}
/**
* Do sampling
* @param m document number
* @param n word number
* @return topic id
*/
public int sampling(int m, int n)
{
// remove z_i from the count variable
int topic = trnModel.z[m].get(n);
int w = trnModel.data.docs.get(m).words[n];
trnModel.nw[w][topic] -= 1;
trnModel.nd[m][topic] -= 1;
trnModel.nwsum[topic] -= 1;
trnModel.ndsum[m] -= 1;
double Vbeta = trnModel.V * trnModel.beta;
// get labels for this document
int[] labels = trnModel.data.docs.get(m).labels;
// determine number of possible topics for this document
int K_m = (labels == null) ? trnModel.K : labels.length;
// do multinominal sampling via cumulative method
double[] p = trnModel.p;
for (int k = 0; k < K_m; k++) {
topic = labels == null ? k : labels[k];
p[k] = (trnModel.nd[m][topic] + trnModel.alpha) *
(trnModel.nw[w][topic] + trnModel.beta) /
(trnModel.nwsum[topic] + Vbeta);
}
// cumulate multinomial parameters
for (int k = 1; k < K_m; k++) {
p[k] += p[k - 1];
}
// scaled sample because of unnormalized p[]
double u = Math.random() * p[K_m - 1];
for (topic = 0; topic < K_m; topic++){
if (p[topic] > u) //sample topic w.r.t distribution p
break;
}
// map [0, K_m - 1] topic to [0, K - 1] topic according to labels
if (labels != null) {
topic = labels[topic];
}
// add newly estimated z_i to count variables
trnModel.nw[w][topic] += 1;
trnModel.nd[m][topic] += 1;
trnModel.nwsum[topic] += 1;
trnModel.ndsum[m] += 1;
return topic;
}
}

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/*
* Copyright (C) 2007 by
*
* Xuan-Hieu Phan
* hieuxuan@ecei.tohoku.ac.jp or pxhieu@gmail.com
* Graduate School of Information Sciences
* Tohoku University
*
* Cam-Tu Nguyen
* ncamtu@gmail.com
* College of Technology
* Vietnam National University, Hanoi
*
* JGibbsLDA is a free software; you can redistribute it and/or modify
* it under the terms of the GNU General Public License as published
* by the Free Software Foundation; either version 2 of the License,
* or (at your option) any later version.
*
* JGibbsLDA is distributed in the hope that it will be useful, but
* WITHOUT ANY WARRANTY; without even the implied warranty of
* MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
* GNU General Public License for more details.
*
* You should have received a copy of the GNU General Public License
* along with JGibbsLDA; if not, write to the Free Software Foundation,
* Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA.
*/
package jgibblda;
import java.io.FileNotFoundException;
import java.io.IOException;
public class Inferencer
{
// Train model
public Model trnModel;
public Dictionary globalDict;
private LDACmdOption option;
private Model newModel;
//-----------------------------------------------------
// Init method
//-----------------------------------------------------
public Inferencer(LDACmdOption option) throws FileNotFoundException, IOException
{
this.option = option;
trnModel = new Model(option);
trnModel.init(false);
globalDict = trnModel.data.localDict;
}
//inference new model ~ getting data from a specified dataset
public Model inference() throws FileNotFoundException, IOException
{
newModel = new Model(option, trnModel);
newModel.init(true);
newModel.initInf();
System.out.println("Sampling " + newModel.niters + " iterations for inference!");
System.out.print("Iteration");
for (newModel.liter = 1; newModel.liter <= newModel.niters; newModel.liter++){
System.out.format("%6d", newModel.liter);
// for all newz_i
for (int m = 0; m < newModel.M; ++m){
for (int n = 0; n < newModel.data.docs.get(m).length; n++){
// sample from p(z_i|z_-1,w)
int topic = infSampling(m, n);
newModel.z[m].set(n, topic);
}
}//end foreach new doc
if ((newModel.liter == newModel.niters) ||
(newModel.liter > newModel.nburnin && newModel.liter % newModel.samplingLag == 0)) {
newModel.updateParams(trnModel);
}
System.out.print("\b\b\b\b\b\b");
}// end iterations
newModel.liter--;
System.out.println("\nSaving the inference outputs!");
String outputPrefix = newModel.dfile;
if (outputPrefix.endsWith(".gz")) {
outputPrefix = outputPrefix.substring(0, outputPrefix.length() - 3);
}
newModel.saveModel(outputPrefix + ".");
return newModel;
}
/**
* do sampling for inference
* m: document number
* n: word number?
*/
protected int infSampling(int m, int n)
{
// remove z_i from the count variables
int topic = newModel.z[m].get(n);
int _w = newModel.data.docs.get(m).words[n];
int w = newModel.data.lid2gid.get(_w);
newModel.nw[_w][topic] -= 1;
newModel.nd[m][topic] -= 1;
newModel.nwsum[topic] -= 1;
newModel.ndsum[m] -= 1;
int[] nw_inf_m__w = null;
if (option.infSeparately) {
nw_inf_m__w = newModel.nw_inf.get(m).get(_w);
nw_inf_m__w[topic] -= 1;
newModel.nwsum_inf[m][topic] -= 1;
}
double Vbeta = trnModel.V * newModel.beta;
// get labels for this document
int[] labels = newModel.data.docs.get(m).labels;
// determine number of possible topics for this document
int K_m = (labels == null) ? newModel.K : labels.length;
// do multinomial sampling via cumulative method
double[] p = newModel.p;
for (int k = 0; k < K_m; k++) {
topic = labels == null ? k : labels[k];
int nw_k, nwsum_k;
if (option.infSeparately) {
nw_k = nw_inf_m__w[topic];
nwsum_k = newModel.nwsum_inf[m][topic];
} else {
nw_k = newModel.nw[_w][topic];
nwsum_k = newModel.nwsum[topic];
}
p[k] = (newModel.nd[m][topic] + newModel.alpha) *
(trnModel.nw[w][topic] + nw_k + newModel.beta) /
(trnModel.nwsum[topic] + nwsum_k + Vbeta);
}
// cumulate multinomial parameters
for (int k = 1; k < K_m; k++){
p[k] += p[k - 1];
}
// scaled sample because of unnormalized p[]
double u = Math.random() * p[K_m - 1];
for (topic = 0; topic < K_m; topic++){
if (p[topic] > u)
break;
}
// map [0, K_m - 1] topic to [0, K - 1] topic according to labels
if (labels != null) {
topic = labels[topic];
}
// add newly estimated z_i to count variables
newModel.nw[_w][topic] += 1;
newModel.nd[m][topic] += 1;
newModel.nwsum[topic] += 1;
newModel.ndsum[m] += 1;
if (option.infSeparately) {
nw_inf_m__w[topic] += 1;
newModel.nwsum_inf[m][topic] += 1;
}
return topic;
}
}

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/*
* Copyright (C) 2007 by
*
* Xuan-Hieu Phan
* hieuxuan@ecei.tohoku.ac.jp or pxhieu@gmail.com
* Graduate School of Information Sciences
* Tohoku University
*
* Cam-Tu Nguyen
* ncamtu@gmail.com
* College of Technology
* Vietnam National University, Hanoi
*
* JGibbsLDA is a free software; you can redistribute it and/or modify
* it under the terms of the GNU General Public License as published
* by the Free Software Foundation; either version 2 of the License,
* or (at your option) any later version.
*
* JGibbsLDA is distributed in the hope that it will be useful, but
* WITHOUT ANY WARRANTY; without even the implied warranty of
* MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
* GNU General Public License for more details.
*
* You should have received a copy of the GNU General Public License
* along with JGibbsLDA; if not, write to the Free Software Foundation,
* Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA.
*/
package jgibblda;
import java.io.FileNotFoundException;
import org.kohsuke.args4j.*;
public class LDA
{
public static void main(String args[])
{
LDACmdOption option = new LDACmdOption();
CmdLineParser parser = new CmdLineParser(option);
try {
if (args.length == 0){
showHelp(parser);
return;
}
parser.parseArgument(args);
if (option.est || option.estc){
Estimator estimator = new Estimator(option);
estimator.estimate();
}
else if (option.inf){
Inferencer inferencer = new Inferencer(option);
Model newModel = inferencer.inference();
}
} catch (CmdLineException cle){
System.out.println("Command line error: " + cle.getMessage());
showHelp(parser);
return;
} catch (FileNotFoundException e) {
e.printStackTrace();
return;
} catch (Exception e){
System.out.println("Error in main: " + e.getMessage());
e.printStackTrace();
return;
}
}
public static void showHelp(CmdLineParser parser){
System.out.println("LDA [options ...] [arguments...]");
parser.printUsage(System.out);
}
}

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package jgibblda;
import org.kohsuke.args4j.*;
public class LDACmdOption {
@Option(name="-est", usage="Specify whether we want to estimate model from scratch")
public boolean est = false;
@Option(name="-estc", usage="Specify whether we want to continue the last estimation")
public boolean estc = false;
@Option(name="-inf", usage="Specify whether we want to do inference")
public boolean inf = true;
@Option(name="-infseparately", usage="Do inference for each document separately")
public boolean infSeparately = false;
@Option(name="-unlabeled", usage="Ignore document labels")
public boolean unlabeled = false;
@Option(name="-dir", usage="Specify directory")
public String dir = "";
@Option(name="-dfile", usage="Specify data file (*.gz)")
public String dfile = "";
@Option(name="-model", usage="Specify the model name")
public String modelName = "";
@Option(name="-alpha", usage="Specify alpha")
public double alpha = -1;
@Option(name="-beta", usage="Specify beta")
public double beta = -1;
@Option(name="-ntopics", usage="Specify the number of topics")
public int K = 100;
@Option(name="-niters", usage="Specify the number of iterations")
public int niters = 1000;
@Option(name="-nburnin", usage="Specify the number of burn-in iterations")
public int nburnin = 500;
@Option(name="-samplinglag", usage="Specify the sampling lag")
public int samplingLag = 5;
@Option(name="-twords", usage="Specify the number of most likely words to be printed for each topic")
public int twords = 100;
}

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/*
* Copyright (C) 2007 by
*
* Xuan-Hieu Phan
* hieuxuan@ecei.tohoku.ac.jp or pxhieu@gmail.com
* Graduate School of Information Sciences
* Tohoku University
*
* Cam-Tu Nguyen
* ncamtu@gmail.com
* College of Technology
* Vietnam National University, Hanoi
*
* JGibbsLDA is a free software; you can redistribute it and/or modify
* it under the terms of the GNU General Public License as published
* by the Free Software Foundation; either version 2 of the License,
* or (at your option) any later version.
*
* JGibbsLDA is distributed in the hope that it will be useful, but
* WITHOUT ANY WARRANTY; without even the implied warranty of
* MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
* GNU General Public License for more details.
*
* You should have received a copy of the GNU General Public License
* along with JGibbsLDA; if not, write to the Free Software Foundation,
* Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA.
*/
package jgibblda;
import java.io.BufferedReader;
import java.io.FileInputStream;
import java.io.FileNotFoundException;
import java.io.IOException;
import java.io.InputStreamReader;
import java.util.ArrayList;
import java.util.zip.GZIPInputStream;
import gnu.trove.list.array.TIntArrayList;
import gnu.trove.map.hash.TIntIntHashMap;
import gnu.trove.set.hash.TIntHashSet;
public class LDADataset {
//---------------------------------------------------------------
// Instance Variables
//---------------------------------------------------------------
public Dictionary localDict = new Dictionary(); // local dictionary
public ArrayList<Document> docs = new ArrayList<Document>(); // a list of documents
public int M = 0; // number of documents
public int V = 0; // number of words
// map from local coordinates (id) to global ones
// null if the global dictionary is not set
public TIntIntHashMap lid2gid = null;
//link to a global dictionary (optional), null for train data, not null for test data
public Dictionary globalDict = null;
//-------------------------------------------------------------
//Public Instance Methods
//-------------------------------------------------------------
public void setM(int M)
{
this.M = M;
}
public void setDictionary(Dictionary globalDict)
{
lid2gid = new TIntIntHashMap();
this.globalDict = globalDict;
}
/**
* set the document at the index idx if idx is greater than 0 and less than M
* @param doc document to be set
* @param idx index in the document array
*/
public void setDoc(Document doc, int idx){
if (idx < docs.size()) {
docs.set(idx, doc);
} else {
docs.add(idx, doc);
}
}
/**
* add a new document
* @param str string contains doc
*/
public void addDoc(String str, boolean unlabeled)
{
// read document labels (if provided)
TIntArrayList labels = null;
if (str.startsWith("[")) {
String[] labelsBoundary = str.
substring(1). // remove initial '['
split("]", 2); // separate labels and str between ']'
String[] labelStrs = labelsBoundary[0].trim().split("[ \\t]");
str = labelsBoundary[1].trim();
// parse labels (unless we're ignoring the labels)
if (!unlabeled) {
// store labels in a HashSet to ensure uniqueness
TIntHashSet label_set = new TIntHashSet();
for (String labelStr : labelStrs) {
try {
label_set.add(Integer.parseInt(labelStr.trim()));
} catch (NumberFormatException nfe) {
System.err.println("Unknown document label ( " + labelStr + " ) for document " + docs.size() + ".");
}
}
labels = new TIntArrayList(label_set);
labels.sort();
}
}
String[] words = str.split("[ \\t\\n]");
TIntArrayList ids = new TIntArrayList();
for (String word : words){
if (word.trim().equals("")) {
continue;
}
int _id = localDict.word2id.size();
if (localDict.contains(word))
_id = localDict.getID(word);
if (globalDict != null) {
//get the global id
if (globalDict.contains(word)) {
localDict.addWord(word);
lid2gid.put(_id, globalDict.getID(word));
ids.add(_id);
}
}
else {
localDict.addWord(word);
ids.add(_id);
}
}
setDoc(new Document(ids, str, labels), docs.size());
V = localDict.word2id.size();
}
//---------------------------------------------------------------
// I/O methods
//---------------------------------------------------------------
/**
* read a dataset from a file
* @return true if success and false otherwise
*/
public boolean readDataSet(String filename, boolean unlabeled) throws FileNotFoundException, IOException
{
BufferedReader reader = new BufferedReader(new InputStreamReader(
new GZIPInputStream(
new FileInputStream(filename)), "UTF-8"));
try {
String line;
while ((line = reader.readLine()) != null) {
addDoc(line, unlabeled);
}
setM(docs.size());
// debug output
System.out.println("Dataset loaded:");
System.out.println("\tM:" + M);
System.out.println("\tV:" + V);
return true;
} finally {
reader.close();
}
}
}

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/*
* Copyright (C) 2007 by
*
* Xuan-Hieu Phan
* hieuxuan@ecei.tohoku.ac.jp or pxhieu@gmail.com
* Graduate School of Information Sciences
* Tohoku University
*
* Cam-Tu Nguyen
* ncamtu@gmail.com
* College of Technology
* Vietnam National University, Hanoi
*
* JGibbsLDA is a free software; you can redistribute it and/or modify
* it under the terms of the GNU General Public License as published
* by the Free Software Foundation; either version 2 of the License,
* or (at your option) any later version.
*
* JGibbsLDA is distributed in the hope that it will be useful, but
* WITHOUT ANY WARRANTY; without even the implied warranty of
* MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
* GNU General Public License for more details.
*
* You should have received a copy of the GNU General Public License
* along with JGibbsLDA; if not, write to the Free Software Foundation,
* Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA.
*/
package jgibblda;
import java.io.BufferedReader;
import java.io.BufferedWriter;
import java.io.File;
import java.io.FileInputStream;
import java.io.FileNotFoundException;
import java.io.FileOutputStream;
import java.io.IOException;
import java.io.InputStreamReader;
import java.io.OutputStreamWriter;
import java.util.ArrayList;
import java.util.Collections;
import java.util.StringTokenizer;
import java.util.zip.GZIPInputStream;
import java.util.zip.GZIPOutputStream;
import gnu.trove.list.array.TIntArrayList;
import gnu.trove.map.hash.TIntObjectHashMap;
public class Model {
//---------------------------------------------------------------
// Class Variables
//---------------------------------------------------------------
public static String tassignSuffix = ".tassign.gz"; // suffix for topic assignment file
public static String thetaSuffix = ".theta.gz"; // suffix for theta (topic - document distribution) file
public static String phiSuffix = ".phi.gz"; // suffix for phi file (topic - word distribution) file
public static String othersSuffix = ".others.gz"; // suffix for containing other parameters
public static String twordsSuffix = ".twords.gz"; // suffix for file containing words-per-topics
public static String wordMapSuffix = ".wordmap.gz"; // suffix for file containing word to id map
//---------------------------------------------------------------
// Model Parameters and Variables
//---------------------------------------------------------------
public String dir = "./";
public String dfile = "trndocs.dat";
public boolean unlabeled = false;
public String modelName = "model";
public LDADataset data; // link to a dataset
public int M = 0; // dataset size (i.e., number of docs)
public int V = 0; // vocabulary size
public int K = 100; // number of topics
public double alpha; // LDA hyperparameters
public double beta = 0.01; // LDA hyperparameters
public int niters = 1000; // number of Gibbs sampling iteration
public int nburnin = 500; // number of Gibbs sampling burn-in iterations
public int samplingLag = 5;// Gibbs sampling sample lag
public int numSamples = 1; // number of samples taken
public int liter = 0; // the iteration at which the model was saved
public int twords = 20; // print out top words per each topic
// Estimated/Inferenced parameters
public double[][] theta = null; // theta: document - topic distributions, size M x K
public double[][] phi = null; // phi: topic-word distributions, size K x V
// Temp variables while sampling
public TIntArrayList[] z = null; // topic assignments for words, size M x doc.size()
protected int[][] nw = null; // nw[i][j]: number of instances of word/term i assigned to topic j, size V x K
protected int[][] nd = null; // nd[i][j]: number of words in document i assigned to topic j, size M x K
protected int[] nwsum = null; // nwsum[j]: total number of words assigned to topic j, size K
protected int[] ndsum = null; // ndsum[i]: total number of words in document i, size M
protected ArrayList<TIntObjectHashMap<int[]>> nw_inf = null; // nw[m][i][j]: number of instances of word/term i assigned to topic j in doc m, size M x V x K
protected int[][] nwsum_inf = null; // nwsum[m][j]: total number of words assigned to topic j in doc m, size M x K
// temp variables for sampling
protected double[] p = null;
//---------------------------------------------------------------
// Constructors
//---------------------------------------------------------------
public Model(LDACmdOption option) throws FileNotFoundException, IOException
{
this(option, null);
}
public Model(LDACmdOption option, Model trnModel) throws FileNotFoundException, IOException
{
modelName = option.modelName;
K = option.K;
alpha = option.alpha;
if (alpha < 0.0)
alpha = 50.0 / K;
if (option.beta >= 0)
beta = option.beta;
niters = option.niters;
nburnin = option.nburnin;
samplingLag = option.samplingLag;
dir = option.dir;
if (dir.endsWith(File.separator))
dir = dir.substring(0, dir.length() - 1);
dfile = option.dfile;
unlabeled = option.unlabeled;
twords = option.twords;
// initialize dataset
data = new LDADataset();
// process trnModel (if given)
if (trnModel != null) {
data.setDictionary(trnModel.data.localDict);
K = trnModel.K;
// use hyperparameters from model (if not overridden in options)
if (option.alpha < 0.0)
alpha = trnModel.alpha;
if (option.beta < 0.0)
beta = trnModel.beta;
}
// read in data
data.readDataSet(dir + File.separator + dfile, unlabeled);
}
//---------------------------------------------------------------
// Init Methods
//---------------------------------------------------------------
/**
* Init parameters for estimation or inference
*/
public boolean init(boolean random)
{
if (random) {
M = data.M;
V = data.V;
z = new TIntArrayList[M];
} else {
if (!loadModel()) {
System.out.println("Fail to load word-topic assignment file of the model!");
return false;
}
// debug output
System.out.println("Model loaded:");
System.out.println("\talpha:" + alpha);
System.out.println("\tbeta:" + beta);
System.out.println("\tK:" + K);
System.out.println("\tM:" + M);
System.out.println("\tV:" + V);
}
p = new double[K];
initSS();
for (int m = 0; m < data.M; m++){
if (random) {
z[m] = new TIntArrayList();
}
// initilize for z
int N = data.docs.get(m).length;
for (int n = 0; n < N; n++){
int w = data.docs.get(m).words[n];
int topic;
// random init a topic or load existing topic from z[m]
if (random) {
topic = (int)Math.floor(Math.random() * K);
z[m].add(topic);
} else {
topic = z[m].get(n);
}
nw[w][topic]++; // number of instances of word assigned to topic j
nd[m][topic]++; // number of words in document i assigned to topic j
nwsum[topic]++; // total number of words assigned to topic j
}
ndsum[m] = N; // total number of words in document i
}
theta = new double[M][K];
phi = new double[K][V];
return true;
}
public boolean initInf()
{
nw_inf = new ArrayList<TIntObjectHashMap<int[]>>();
nwsum_inf = new int[M][K];
for (int m = 0; m < M; m++) {
for (int k = 0; k < K; k++) {
nwsum_inf[m][k] = 0;
}
}
for (int m = 0; m < data.M; m++){
nw_inf.add(m, new TIntObjectHashMap<int[]>());
// initilize for z
int N = data.docs.get(m).length;
for (int n = 0; n < N; n++){
int w = data.docs.get(m).words[n];
int topic = z[m].get(n);
if (!nw_inf.get(m).containsKey(w)) {
int[] nw_inf_m_w = new int[K];
for (int k = 0; k < K; k++) {
nw_inf_m_w[k] = 0;
}
nw_inf.get(m).put(w, nw_inf_m_w);
}
nw_inf.get(m).get(w)[topic]++; // number of instances of word assigned to topic j in doc m
//nw_inf[m][w][topic]++; // number of instances of word assigned to topic j in doc m
nwsum_inf[m][topic]++; // total number of words assigned to topic j in doc m
}
}
return true;
}
/**
* Init sufficient stats
*/
protected void initSS()
{
nw = new int[V][K];
for (int w = 0; w < V; w++){
for (int k = 0; k < K; k++){
nw[w][k] = 0;
}
}
nd = new int[M][K];
for (int m = 0; m < M; m++){
for (int k = 0; k < K; k++){
nd[m][k] = 0;
}
}
nwsum = new int[K];
for (int k = 0; k < K; k++){
nwsum[k] = 0;
}
ndsum = new int[M];
for (int m = 0; m < M; m++){
ndsum[m] = 0;
}
}
//---------------------------------------------------------------
// Update Methods
//---------------------------------------------------------------
public void updateParams()
{
updateTheta();
updatePhi();
numSamples++;
}
public void updateParams(Model trnModel)
{
updateTheta();
updatePhi(trnModel);
numSamples++;
}
public void updateTheta()
{
double Kalpha = K * alpha;
for (int m = 0; m < M; m++) {
for (int k = 0; k < K; k++) {
if (numSamples > 1) theta[m][k] *= numSamples - 1; // convert from mean to sum
theta[m][k] += (nd[m][k] + alpha) / (ndsum[m] + Kalpha);
if (numSamples > 1) theta[m][k] /= numSamples; // convert from sum to mean
}
}
}
public void updatePhi()
{
double Vbeta = V * beta;
for (int k = 0; k < K; k++) {
for (int w = 0; w < V; w++) {
if (numSamples > 1) phi[k][w] *= numSamples - 1; // convert from mean to sum
phi[k][w] += (nw[w][k] + beta) / (nwsum[k] + Vbeta);
if (numSamples > 1) phi[k][w] /= numSamples; // convert from sum to mean
}
}
}
// for inference
public void updatePhi(Model trnModel)
{
double Vbeta = trnModel.V * beta;
for (int k = 0; k < K; k++) {
for (int _w = 0; _w < V; _w++) {
if (data.lid2gid.containsKey(_w)) {
int id = data.lid2gid.get(_w);
if (numSamples > 1) phi[k][_w] *= numSamples - 1; // convert from mean to sum
phi[k][_w] += (trnModel.nw[id][k] + nw[_w][k] + beta) / (trnModel.nwsum[k] + nwsum[k] + Vbeta);
if (numSamples > 1) phi[k][_w] /= numSamples; // convert from sum to mean
} // else ignore words that don't appear in training
} //end foreach word
} // end foreach topic
}
//---------------------------------------------------------------
// I/O Methods
//---------------------------------------------------------------
/**
* Save model
*/
public boolean saveModel()
{
return saveModel("");
}
public boolean saveModel(String modelPrefix)
{
if (!saveModelTAssign(dir + File.separator + modelPrefix + modelName + tassignSuffix)) {
return false;
}
if (!saveModelOthers(dir + File.separator + modelPrefix + modelName + othersSuffix)) {
return false;
}
if (!saveModelTheta(dir + File.separator + modelPrefix + modelName + thetaSuffix)) {
return false;
}
//if (!saveModelPhi(dir + File.separator + modelPrefix + modelName + phiSuffix)) {
// return false;
//}
if (twords > 0) {
if (!saveModelTwords(dir + File.separator + modelPrefix + modelName + twordsSuffix)) {
return false;
}
}
if (!data.localDict.writeWordMap(dir + File.separator + modelPrefix + modelName + wordMapSuffix)) {
return false;
}
return true;
}
/**
* Save word-topic assignments for this model
*/
public boolean saveModelTAssign(String filename) {
int i, j;
try{
BufferedWriter writer = new BufferedWriter(new OutputStreamWriter(
new GZIPOutputStream(
new FileOutputStream(filename)), "UTF-8"));
//write docs with topic assignments for words
for (i = 0; i < data.M; i++) {
for (j = 0; j < data.docs.get(i).length; ++j) {
writer.write(data.docs.get(i).words[j] + ":" + z[i].get(j) + " ");
}
writer.write("\n");
}
writer.close();
}
catch (Exception e) {
System.out.println("Error while saving model tassign: " + e.getMessage());
e.printStackTrace();
return false;
}
return true;
}
/**
* Save theta (topic distribution) for this model
*/
public boolean saveModelTheta(String filename) {
try{
BufferedWriter writer = new BufferedWriter(new OutputStreamWriter(
new GZIPOutputStream(
new FileOutputStream(filename)), "UTF-8"));
for (int i = 0; i < M; i++) {
for (int j = 0; j < K; j++) {
if (theta[i][j] > 0) {
writer.write(j + ":" + theta[i][j] + " ");
}
}
writer.write("\n");
}
writer.close();
}
catch (Exception e){
System.out.println("Error while saving topic distribution file for this model: " + e.getMessage());
e.printStackTrace();
return false;
}
return true;
}
/**
* Save word-topic distribution
*/
public boolean saveModelPhi(String filename)
{
try {
BufferedWriter writer = new BufferedWriter(new OutputStreamWriter(
new GZIPOutputStream(
new FileOutputStream(filename)), "UTF-8"));
for (int i = 0; i < K; i++) {
for (int j = 0; j < V; j++) {
if (phi[i][j] > 0) {
writer.write(j + ":" + phi[i][j] + " ");
}
}
writer.write("\n");
}
writer.close();
}
catch (Exception e) {
System.out.println("Error while saving word-topic distribution:" + e.getMessage());
e.printStackTrace();
return false;
}
return true;
}
/**
* Save other information of this model
*/
public boolean saveModelOthers(String filename){
try{
BufferedWriter writer = new BufferedWriter(new OutputStreamWriter(
new GZIPOutputStream(
new FileOutputStream(filename)), "UTF-8"));
writer.write("alpha=" + alpha + "\n");
writer.write("beta=" + beta + "\n");
writer.write("ntopics=" + K + "\n");
writer.write("ndocs=" + M + "\n");
writer.write("nwords=" + V + "\n");
writer.write("liters=" + liter + "\n");
writer.close();
}
catch(Exception e){
System.out.println("Error while saving model others:" + e.getMessage());
e.printStackTrace();
return false;
}
return true;
}
/**
* Save model the most likely words for each topic
*/
public boolean saveModelTwords(String filename){
try{
BufferedWriter writer = new BufferedWriter(new OutputStreamWriter(
new GZIPOutputStream(
new FileOutputStream(filename)), "UTF-8"));
if (twords > V){
twords = V;
}
for (int k = 0; k < K; k++){
ArrayList<Pair> wordsProbsList = new ArrayList<Pair>();
for (int w = 0; w < V; w++){
Pair p = new Pair(w, phi[k][w], false);
wordsProbsList.add(p);
}//end foreach word
//print topic
writer.write("Topic " + k + ":\n");
Collections.sort(wordsProbsList);
for (int i = 0; i < twords; i++){
if (data.localDict.contains((Integer)wordsProbsList.get(i).first)){
String word = data.localDict.getWord((Integer)wordsProbsList.get(i).first);
writer.write("\t" + word + "\t" + wordsProbsList.get(i).second + "\n");
}
}
} //end foreach topic
writer.close();
}
catch(Exception e){
System.out.println("Error while saving model twords: " + e.getMessage());
e.printStackTrace();
return false;
}
return true;
}
/**
* Load saved model
*/
public boolean loadModel(){
if (!readOthersFile(dir + File.separator + modelName + othersSuffix))
return false;
if (!readTAssignFile(dir + File.separator + modelName + tassignSuffix))
return false;
// read dictionary
Dictionary dict = new Dictionary();
if (!dict.readWordMap(dir + File.separator + modelName + wordMapSuffix))
return false;
data.localDict = dict;
return true;
}
/**
* Load "others" file to get parameters
*/
protected boolean readOthersFile(String otherFile){
try {
BufferedReader reader = new BufferedReader(new InputStreamReader(
new GZIPInputStream(
new FileInputStream(otherFile)), "UTF-8"));
String line;
while((line = reader.readLine()) != null){
StringTokenizer tknr = new StringTokenizer(line,"= \t\r\n");
int count = tknr.countTokens();
if (count != 2)
continue;
String optstr = tknr.nextToken();
String optval = tknr.nextToken();
if (optstr.equalsIgnoreCase("alpha")){
alpha = Double.parseDouble(optval);
}
else if (optstr.equalsIgnoreCase("beta")){
beta = Double.parseDouble(optval);
}
else if (optstr.equalsIgnoreCase("ntopics")){
K = Integer.parseInt(optval);
}
else if (optstr.equalsIgnoreCase("liter")){
liter = Integer.parseInt(optval);
}
else if (optstr.equalsIgnoreCase("nwords")){
V = Integer.parseInt(optval);
}
else if (optstr.equalsIgnoreCase("ndocs")){
M = Integer.parseInt(optval);
}
else {
// any more?
}
}
reader.close();
}
catch (Exception e){
System.out.println("Error while reading other file:" + e.getMessage());
e.printStackTrace();
return false;
}
return true;
}
/**
* Load word-topic assignments for this model
*/
protected boolean readTAssignFile(String tassignFile)
{
try {
int i,j;
BufferedReader reader = new BufferedReader(new InputStreamReader(
new GZIPInputStream(
new FileInputStream(tassignFile)), "UTF-8"));
String line;
z = new TIntArrayList[M];
data = new LDADataset();
data.setM(M);
data.V = V;
for (i = 0; i < M; i++){
line = reader.readLine();
StringTokenizer tknr = new StringTokenizer(line, " \t\r\n");
int length = tknr.countTokens();
TIntArrayList words = new TIntArrayList();
TIntArrayList topics = new TIntArrayList();
for (j = 0; j < length; j++){
String token = tknr.nextToken();
StringTokenizer tknr2 = new StringTokenizer(token, ":");
if (tknr2.countTokens() != 2){
System.out.println("Invalid word-topic assignment line\n");
return false;
}
words.add(Integer.parseInt(tknr2.nextToken()));
topics.add(Integer.parseInt(tknr2.nextToken()));
}//end for each topic assignment
//allocate and add new document to the corpus
Document doc = new Document(words);
data.setDoc(doc, i);
//assign values for z
z[i] = new TIntArrayList();
for (j = 0; j < topics.size(); j++){
z[i].add(topics.get(j));
}
}//end for each doc
reader.close();
}
catch (Exception e){
System.out.println("Error while loading model: " + e.getMessage());
e.printStackTrace();
return false;
}
return true;
}
}

54
java_LabledLDA/src/jgibblda/Pair.java Normal file
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@ -0,0 +1,54 @@
/*
* Copyright (C) 2007 by
*
* Xuan-Hieu Phan
* hieuxuan@ecei.tohoku.ac.jp or pxhieu@gmail.com
* Graduate School of Information Sciences
* Tohoku University
*
* Cam-Tu Nguyen
* ncamtu@gmail.com
* College of Technology
* Vietnam National University, Hanoi
*
* JGibbsLDA is a free software; you can redistribute it and/or modify
* it under the terms of the GNU General Public License as published
* by the Free Software Foundation; either version 2 of the License,
* or (at your option) any later version.
*
* JGibbsLDA is distributed in the hope that it will be useful, but
* WITHOUT ANY WARRANTY; without even the implied warranty of
* MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
* GNU General Public License for more details.
*
* You should have received a copy of the GNU General Public License
* along with JGibbsLDA; if not, write to the Free Software Foundation,
* Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA.
*/
package jgibblda;
import java.util.Comparator;
public class Pair implements Comparable<Pair> {
public Object first;
public Comparable second;
public static boolean naturalOrder = false;
public Pair(Object k, Comparable v){
first = k;
second = v;
}
public Pair(Object k, Comparable v, boolean naturalOrder){
first = k;
second = v;
Pair.naturalOrder = naturalOrder;
}
public int compareTo(Pair p){
if (naturalOrder)
return this.second.compareTo(p.second);
else return -this.second.compareTo(p.second);
}
}

199
old/testo.py Normal file
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# -*- coding: utf-8 -*-
import functools
import re
import spacy
import textacy
from spacy.tokens import Doc
from spacy.tagger import Tagger
import xml.etree.ElementTree as ET
PARSER = spacy.load('de')
stop_words = list(__import__("spacy." + PARSER.lang, globals(), locals(), ['object']).STOP_WORDS)
def compose(*functions):
def compose2(f, g):
return lambda x: f(g(x))
return functools.reduce(compose2, functions, lambda x: x)
def cleanTexts(textstream, parser, attr):
#input str-stream output str-stream
pipe = parser.pipe(textstream)
for doc in pipe:
tokens = [tok.text for tok in doc
if tok.pos_ not in attr
and tok.tag_ not in attr
and tok.ent_ not in attr
and tok.text not in attr
and tok.lower_ not in attr]
yield " ".join(tokens)
"""
def cleanDoc_lemmatize(doc,parser=PARSER):
return parser(" ".join([tok.lemma_ for tok in doc ]))
def cleanDoc_STOPS(doc,parser=PARSER, stop_words=None, keep=None):
if stop_words is None:
stop_words = list(__import__("spacy." + parser.lang, globals(), locals(), ['object']).STOP_WORDS)
if hasattr(keep, '__iter__'):
for k in keep:
try:
stop_words.remove(k)
except ValueError:
pass
return parser(" ".join([tok.text for tok in doc if tok.text not in stop_words]))
def cleanDoc_ENT(doc,parser=PARSER, keeponly=False, attr=["WORK_OF_ART", "ORG", "PRODUCT", "LOC"]):
if keeponly:
return parser(" ".join([tok.text for tok in doc if tok.ent_ in attr]))
else:
return parser(" ".join([tok.text for tok in doc if tok.ent_ not in attr]))
def cleanDoc_POS(doc,parser=PARSER, keeponly=False, attr=["SPACE", "PUNCT"]):
if keeponly:
return parser(" ".join([tok.text for tok in doc if tok.pos_ in attr]))
else:
return parser(" ".join([tok.text for tok in doc if tok.pos_ not in attr]))
"""
def cleanTexts_POS(spacypipe, keeponly=False, attr=["SPACE", "PUNCT"]):
"""
:param spacypipe: spacypipe
:param keeponly: bool . If True, only attr will be kept. If false, all attr will be deleted
:param attr: [str] pos_ or ent_type_
:yields: stream of strings: full-length cleaned text
"""
if keeponly:
for doc in spacypipe:
yield " ".join([tok.text for tok in doc if tok.pos_ in attr])
else:
for doc in spacypipe:
yield " ".join([tok.text for tok in doc if tok.pos_ not in attr])
def cleanText_POS(text,parser=PARSER, keeponly=False, attr=["SPACE", "PUNCT"]):
"""
:param txt: str
:param keeponly: bool . If True, only attr will be kept. If false, all attr will be deleted
:param attr: [str] pos_ or ent_type_
:return: str
"""
doc = parser(text)
if keeponly:
return " ".join([tok.text for tok in doc if tok.pos_ in attr])
else:
return " ".join([tok.text for tok in doc if tok.pos_ not in attr])
def removeWhitespace(string):
return re.sub(r'(\r\n|\r|\n|(\s)+)', ' ', string)
def removeWords(string, words):
big_regex = re.compile('|'.join(map(re.escape, words)))
return big_regex.sub("", string)
def generateMainTextfromTicketXML(path2xml, main_textfield='Beschreibung', cleaning_function=None):
"""
generates strings from XML
:param path2xml:
:param main_textfield:
:param cleaning_function:
:yields strings
"""
import xml.etree.ElementTree as ET
tree = ET.parse(path2xml, ET.XMLParser(encoding="utf-8"))
root = tree.getroot()
for ticket in root:
text = "ERROR"
for field in ticket:
if field.tag == main_textfield:
if cleaning_function:
text = cleaning_function(field.text)
else:
text = field.text
yield text
def generateMetadatafromTicketXML(path2xml, key_function_pairs_to_clean, leave_out=['Beschreibung']):
import xml.etree.ElementTree as ET
tree = ET.parse(path2xml, ET.XMLParser(encoding="utf-8"))
root = tree.getroot()
for ticket in root:
metadata = {}
for field in ticket:
if field.tag not in leave_out:
if field.tag in key_function_pairs_to_clean:
metadata[field.tag] = key_function_pairs_to_clean[field.tag](field.text)
else:
metadata[field.tag] = field.text
yield metadata
string = "Frau Hinrichs überdenkt die tu Situation a@bc.de und 545453 macht ' dann neue Anträge. \n Dieses Ticket wird geschlossen \n \n test"
#print(removeWords(string,["die", "neue"]))
# in:str out:str
cleanString = compose(
cleanText_POS,
functools.partial(textacy.preprocess.replace_emails, replace_with=u'EMAIL')
)
key_function_pairs_to_clean = {
"Loesung":removeWhitespace,
"Zusammenfassung":cleanText_POS
}
"""
# in:str-gen out:str-gen
cleanStream = compose(
removeSTOP,
lemmatize,
cleanEnt
)
"""
# content: xml -> stringCleaning -> pipe -> docCleaning -> corpus
# metadata:xml -> -> stringCleaning -> corpus
corpus = textacy.Corpus(PARSER)
corpus.add_texts(
cleanTexts(generateMainTextfromTicketXML("ticketSamples.xml"),PARSER,["PUNCT","SPACE","PERSON"])#,
#generateMetadatafromTicketXML("ticketSamples.xml",key_function_pairs_to_clean=key_function_pairs_to_clean)
)
print(corpus[0].text)