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TypeError Traceback (most recent call last):
File "/Users/janezdemsar/orange3/Orange/canvas/scheme/widgetsscheme.py", line 546, in process_signals_for_widget
handler(_args)
File "/Users/janezdemsar/orange3/Orange/widgets/visualize/owboxplot.py", line 198, in data
self.openContext(self.ddataset)
File "/Users/janezdemsar/orange3/Orange/widgets/widget.py", line 548, in openContext
self.settingsHandler.open_context(self, *a)
File "/Users/janezdemsar/orange3/Orange/widgets/settings.py", line 262, in open_context
self.find_or_create_context(widget, *arg, *_argkw)
File "/Users/janezdemsar/orange3/Orange/widgets/settings.py", line 391, in find_or_create_context
super().find_or_create_context(widget, *encoded_domain)
File "/Users/janezdemsar/orange3/Orange/widgets/settings.py", line 292, in find_or_create_context
context = self.clone_context(best_context, *arg)
TypeError: clone_context() takes exactly 5 arguments (4 given)

Tests for the changes in 11f7593

Is k a keyword-only argument or not?

def __init__(self, k=10, **kwargs):
    self.k = kwargs.pop('k', 10)

Use any suitable libraries. Assume that the data is stored in numpy.

Implementation should use the general interface for getting the distributions and contingencies to ensure compatibility with SQL-based data storage. It should not assume that the data is stored in numpy and access the tables directly.

The essential functions will probably need to be written in Cython.

radioButtonsInBox is broken.

To replicate, connect File -> SelectAttributes

This is a big task, not suitable for retreat. It requires thinking about what is needed by most visualization widgets, and probably also have the SQL-based storage in mind. Probably a job for Aleš.

The code must not assume that the data is stored in numpy matrices.

This may need to be written in Cython.

The filters should support any kind of data selection (rows or columns), as they will also be used for describing data sets in proxies used for SQL-based data storage.

For the beginning, think about what is needed for widget Select Data

The code must not assume that the data is stored in numpy matrices.

See "Options" in Data Sampler

The code must not assume that the data is stored in numpy matrices.

Use any suitable library (probably sklearn) and assume that the data is stored in numpy.

Orange3 is currently missing any datasets. Copy datasets from orange2 repository, add them to default search patch and fix the FileWidget.

The code may assume (at least for the time being) that the data is stored in numpy matrices; if it is not, it is allowed to load them into numpy.

If we want to implement the ReliefF for data stored in SQL, we will probably at least partially do it on the server side.

For demonstration purposes, let this learner be written so that it does not assume a particular type of storage, e.g., let it use distributions and contingencies computed by the storage.

Sample code that reproduces this error but works without (//2 + 1).

x = np.random.random_integers(1, 3, (10, 4))
y = np.random.random_integers(1, 5, (10, 1)) // 2 + 1
table_rand = Orange.data.Table(x, y)
dist_rand = distribution.get_distribution(table_rand, table_rand.domain.class_var)

They need some updating -- it is not as easy as described there.

For instance, scipy doesn't seem pip-installable -- it complains about the missing BLAS libraries, at least on Ubuntu 13. It seems better to install numpy and scipy through apt-get, globally, not within virtual environment.

I suggest keeping them in requirements.txt, but instruct people to install it with apt-get.

This seems to approximately work on a fresh Ubuntu 13:

# This is needed for setting up virtual environments in Python 3
sudo apt-get install python3-setuptools
sudo easy_install pip
sudo pip install virtualenv

    #
sudo apt-get install git # needed for Orange
sudo apt-get install mercurial # needed for bottlechest (we'll move it to git!)
#
# Python libraries that are better installed globally
sudo apt-get install python3-dev
sudo apt-get install python3-pyqt4 # this is not pip-installable in py3
sudo apt-get install python3-numpy python3-scipy # pip complains about missing BLAS
    #
# Set up virtual environment
virtualenv --system-site-packages virtualenv/orange3
. virtualenv/orange3/bin/activate
    #
# Clone orange, get the remaining requirements and compile the Cython code
git clone https://github.com/biolab/orange3.git
cd orange3
pip install -r requirements
python setup.py develop
    #
# for widget SQL Table
sudo apt-get install postgresql libpg-dev
pip install psycopg2
    #
# orangeqt is needed for widget box plot
# -- this doesn't work, it builds orangeqt.so without init function!
cd
hg clone https://bitbucket.org/biolab/orange
cd orange/source/orangeqt
sudo apt-get install libqt4-dev python-sip-dev cmake
cmake

Setting up development version of Orange3 currently requires mercurial just to install bottlechest.

Change the requirements.txt correspondingly.

move orangeqt to a separate repository
get rid of cmake
describe how to build it for python3

The following almost works, except that it the module misses the init function

hg clone https://bitbucket.org/biolab/orange
cd orange/source/orangeqt
sudo apt-get install libqt4-dev python-sip-dev cmake
cmake

Use distributions; do not assume that the data is stored in numpy

Use any suitable library. Assume that the data is stored in numpy

This widget will probably need to be written from scratch since the original one is rather complicated.

This is big task, not really suitable for the retreat.

The current function Orange.data.io.csvSaver does not handle meta attributes and doesn't add flags like D# and C# for cases in which automated recognition of variable types would fail.

The "range" should probably fall with square of the distance, so the effect is more local. Also, rename the labels from "radius" and "density" to "range" and "effect" or something similar.

Implementation should use the general interface for getting the distributions and contingencies to ensure compatibility with SQL-based data storage. It should not assume that the data is stored in numpy and access the tables directly.