[Orange Datascience] - Tutorials, Overview and Plugins

[Orange3 AI Explain] - Explainable AI add-on for Orange3

Orange3 Explain
Orange3 Explain is an add-on for the Orange3 data mining suite. It provides extensions for explanatory AI.

Installation
Install from Orange add-on installer through Options - Add-ons.

To install the add-on from source run

pip install .
To register this add-on with Orange, but keep the code in the development directory (do not copy it to Python's site-packages directory), run

pip install -e .
Usage
After the installation, the widget from this add-on is registered with Orange. To run Orange from the terminal, use

orange-canvas
or

python -m Orange.canvas
The new widget appears in the toolbox bar under the section Example.

[Orange3 Bioinframatics Addon] - Bioinformatics add-on for Orange3

Orange3-bioinformatics
Documentation Status  PyPI Conda PyPI - License
Orange Bioinformatics extends Orange, a data mining software package, with common functionality for bioinformatics. The provided functionality can be accessed as a Python library or through a visual programming interface (Orange Canvas). The latter is also suitable for non-programmers.

In Orange Canvas the analyst connects basic computational units, called widgets, into data flow analytics schemas. Two units-widgets can be connected if they share a data type. Compared to other popular tools like Taverna, Orange widgets are high-level, integrated potentially complex tasks, but are specific enough to be used independently. Even elaborate analyses rarely consist of more than ten widgets; while tasks such as clustering and enrichment analysis could be executed with up to five widgets. While building the schema each widget is independently controlled with settings, the settings do not conceptually burden the analyst.

Orange Bioinformatics provides access to publicly available data, like GEO data sets, GO and KEGG. All features can be combined with powerful visualization, network exploration and data mining techniques from the Orange data mining framework.

Installation
To install the add-on with pip use

pip install Orange3-bioinformatics
To register this add-on with Orange, but keep the code in the development directory (do not copy it to Python's site-packages directory), run

pip install -e .
Documentation / widget help can be built by running

make html htmlhelp
from the doc directory.

Usage
After the installation, the widgets from this add-on are registered with Orange. To run Orange from the terminal, use

python3 -m Orange.canvas
or

orange-canvas
The new widgets are in the toolbox bar under Bioinformatics section.

[Orange3 Education ML Addon] - Educational widgets for machine learning and data mining in Orange 3

Orange3-Educational
Educational widgets for machine learning and data mining in Orange.

Widgets in Educational Add-on demonstrate several key data mining and machine learning procedures. The widgets are useful for beginners to understand the inner working of key algorithms in the data mining and for teachers to be able to visually explain various methods in a classroom.

Installation
To install the add-on with pip use

pip install Orange3-Educational
To install the add-on from source, run

python setup.py install
To register this add-on with Orange, but keep the code in the development directory (do not copy it to Python's site-packages directory), run

python setup.py develop
Usage
After the installation, the widgets from this add-on are registered with Orange. To run Orange from the terminal, use

python3 -m Orange.canvas
new widgets are in the toolbox bar under Educational section.

[Orange3 Geo Addon] - Orange add-on for dealing with geography and geo-location

Orange3-Geo
Discord Chat build: passing codecov

Orange add-on for dealing with geography and geo-location. It provides widgets for visualizing maps and regions, and encoding and decoding geographical data.

Installation
Install from Orange add-on installer through Options - Add-ons.

To install the add-on with pip use

pip install Orange3-Geo
To install the add-on from source, run

python setup.py install
To register this add-on with Orange, but keep the code in the development directory (do not copy it to Python's site-packages directory), run

python setup.py develop
You can also run

pip install -e .
which is sometimes preferable as you can pip uninstall packages later. You may also want to read CONTRIBUTING.md

Usage
After the installation the widgets from this add-on are registered with Orange. To run Orange from the terminal use

orange-canvas
or

python3 -m Orange.canvas
New widgets are in the toolbox bar under the Geo section.

[Orange3 Time Series] - Orange add-on for analyzing, visualizing, manipulating, and forecasting time series data.

Orange3-Timeseries
Discord Chat Build Status codecov Documentation Status

Orange add-on for analyzing, visualizing, manipulating, and forecasting time series data.

License: CC-BY-NC-3.0

In order to use this package commercially, please obtain a Highcharts license.

Package documentation: http://orange3-timeseries.readthedocs.io/

Installing
Via Add-on Dialogue
Go to Options - Add-ons in Orange, select Timeseries from the list of add-on and install. Restart Orange for the add-on to appear.

With Anaconda
The easiest way to install Orange3-Timeseries on a non-GNU/Linux system is with Anaconda distribution for your OS (Python version 3.5). In your Anaconda Prompt, first add conda-forge to your channels:

conda config --add channels conda-forge
Then install Orange3:

conda install orange3
This will install the latest release of Orange. Then install Orange3-Timeseries:

conda install Orange3-Timeseries
Run:

orange-canvas
to open Orange and check if everything is installed properly.

From source
To install the add-on from source

# Clone the repository and move into it
git clone https://github.com/biolab/orange3-timeseries.git
cd orange3-timeseries

# Install corresponding wheels for your OS:
pip install some-wheel.whl

# Install Orange3-Timeseries in editable/development mode.
pip install -e .
numpy+mkl
scipy
statsmodels
To register this add-on with Orange, run

python setup.py install

[Orange3-Text Addon]orange_ds_addon_text

Orange3 Text extends Orange3, a data mining software package, with common functionality for text mining. It provides access to publicly available data, like NY Times, Twitter, Wikipedia and PubMed. Furthermore, it provides tools for preprocessing, constructing vector spaces (like bag-of-words, topic modeling, and similarity hashing) and visualizations like word cloud end geo map. All features can be combined with powerful data mining techniques from the Orange data mining framework.

Please note that Text add-on won't work on 32-bit Windows systems. The add-on depends on conda-forge and they have removed support for Windows 32 in April 2018.

Anaconda installation
The easiest way to install Orange3-Text is with Anaconda distribution. Download Anaconda for your OS (Python version 3.5). In your Anaconda Prompt first add conda-forge to your channels:

conda config --add channels conda-forge
Then install Orange3-Text

conda install orange3-text
Run

python -m Orange.canvas
to open Orange and check if everything is installed properly.

Installation from source
To install the add-on from source

# Clone the repository and move into it
git clone https://github.com/biolab/orange3-text.git
cd orange3-text

# Install the dependencies:
pip install -r requirements.txt

# Finally install Orange3-Text in editable/development mode.
pip install -e .
To register this add-on with Orange, but keep the code in the development directory (do not copy it to Python's site-packages directory), run

python setup.py develop
Windows setup for biopython library
If you're not using Anaconda distribution, you can manually install biopython library before installing the add-on. First, download the compiler Visual Studio and run the setup with:

python setup.py build_ext --inplace --compiler=msvc install
Usage
After the installation, the widgets from this add-on are registered with Orange. To run Orange from the terminal, use

python3 -m Orange.canvas
or

orange-canvas
The new widgets are in the toolbox bar under Text Mining section.

orange_ds

Want to write a widget? Use the Orange3 example add-on template.

Want to get involved? Join us on Discord, introduce yourself in #general!

Take a look at our contributing guide and style guidelines.

Check out our widget development docs for a comprehensive guide on writing Orange widgets.

The Orange ecosystem
The development of core Orange is primarily split into three repositories:

biolab/orange-canvas-core implements the canvas,
biolab/orange-widget-base is a handy widget GUI library,
biolab/orange3 brings it all together and implements the base data mining toolbox.

Additionally, add-ons implement additional widgets for more specific use cases. Anyone can write an add-on. Some of our first-party add-ons:

biolab/orange3-text
biolab/orange3-bioinformatics
biolab/orange3-timeseries
biolab/orange3-single-cell
biolab/orange3-imageanalytics
biolab/orange3-educational
biolab/orange3-geo
biolab/orange3-associate
biolab/orange3-network
biolab/orange3-explain
Setting up for core Orange development
First, fork the repository by pressing the fork button in the top-right corner of this page.

Set your GitHub username,

export MY_GITHUB_USERNAME=replaceme
create a conda environment, clone your fork, and install it:

conda create python=3 --yes --name orange3
conda activate orange3

git clone ssh://git@github.com/$MY_GITHUB_USERNAME/orange3

pip install -e orange3
Now you're ready to work with git. See GitHub's guides on pull requests, forks if you're unfamiliar. If you're having trouble, get in touch on Discord.

Running
Run Orange with python -m Orange.canvas (after activating the conda environment).

python -m Orange.canvas -l 2 --no-splash --no-welcome will skip the splash screen and welcome window, and output more debug info. Use -l 4 for more.

Add --clear-widget-settings to clear the widget settings before start.

To explore the dark side of the Orange, try --style=fusion:breeze-dark

Argument --help lists all available options.

To run tests, use unittest Orange.tests Orange.widgets.tests

Setting up for development of all components
Should you wish to contribute Orange's base components (the widget base and the canvas), you must also clone these two repositories from Github instead of installing them as dependencies of Orange3.

First, fork all the repositories to which you want to contribute.

Set your GitHub username,

export MY_GITHUB_USERNAME=replaceme
create a conda environment, clone your forks, and install them:

conda create python=3 --yes --name orange3
conda activate orange3

git clone ssh://git@github.com/$MY_GITHUB_USERNAME/orange-widget-base
pip install -e orange-widget-base

git clone ssh://git@github.com/$MY_GITHUB_USERNAME/orange-canvas-core
pip install -e orange-canvas-core

git clone ssh://git@github.com/$MY_GITHUB_USERNAME/orange3
pip install -e orange3

# Repeat for any add-on repositories
It's crucial to install orange-base-widget and orange-canvas-core before orange3 to ensure that orange3 will use your local versions.