Hello community, here is the log from the commit of package python-seaborn for openSUSE:Factory checked in at 2017-01-25 23:18:35 ++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++ Comparing /work/SRC/openSUSE:Factory/python-seaborn (Old) and /work/SRC/openSUSE:Factory/.python-seaborn.new (New) ++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++ Package is "python-seaborn" Changes: -------- New Changes file: --- /dev/null 2016-12-08 12:47:06.134691974 +0100 +++ /work/SRC/openSUSE:Factory/.python-seaborn.new/python-seaborn.changes 2017-01-25 23:18:35.809656585 +0100 @@ -0,0 +1,243 @@ +------------------------------------------------------------------- +Mon Sep 19 18:12:42 UTC 2016 - toddrme2178@gmail.com + +- update to version 0.7.1: + * Added the ability to put "caps" on the error bars that are drawn + by :func:`barplot` or :func:`pointplot` (and, by extension, + :func:`factorplot`). Additionally, the line width of the error + bars can now be controlled. These changes involve the new + parameters "capsize" and "errwidth". See the `github pull request + https://github.com/mwaskom/seaborn/pull/898`_ for examples of + usage. + * Improved the row and column colors display in + :func:`clustermap`. It is now possible to pass Pandas objects for + these elements and, when possible, the semantic information in the + Pandas objects will be used to add labels to the plot. When Pandas + objects are used, the color data is matched against the main + heatmap based on the index, not on position. This is more + accurate, but it may lead to different results if current code + assumed positional matching. + * Improved the luminance calculation that determines the annotation + color in :func:`heatmap`. + * The "annot" parameter of :func:`heatmap` now accepts a rectangular + dataset in addition to a boolean value. If a dataset is passed, + its values will be used for the annotations, while the main + dataset will be used for the heatmap cell colors. + * Fixed a bug in :class:`FacetGrid` that appeared when using + "col_wrap" with missing "col" levels. + * Made it possible to pass a tick locator object to the + :func:`heatmap` colorbar. + * Made it possible to use different styles (e.g., step) for + :class:`PairGrid` histograms when there are multiple hue levels. + * Fixed a bug in scipy-based univariate kernel density bandwidth + calculation. + * The :func:`reset_orig` function (and, by extension, importing + "seaborn.apionly") resets matplotlib rcParams to their values at + the time seaborn itself was imported, which should work better + with rcParams changed by the jupyter notebook backend. + * Removed some objects from the top-level "seaborn" namespace. + * Improved unicode compatibility in :class:`FacetGrid`. +- Update to 0.7.0 + - Added the :func:`swarmplot` function, which draws beeswarm + plots. These are categorical scatterplots, similar to those + produced by :func:`stripplot`, but position of the points on + the categorical axis is chosen to avoid overlapping points. + - Changed some of the :func:`stripplot` defaults to be closer + to :func:`swarmplot`. Points are now somewhat smaller, have + no outlines, and are not split by default when using ``hue``. + These settings remain customizable through function + parameters. + - Added an additional rule when determining category order in + categorical plots. Now, when numeric variables are used in a + categorical role, the default behavior is to sort the unique + levels of the variable (i.e they will be in proper numerical + order). This can still be overridden by the appropriate + ``{*_}order`` parameter, and variables with a ``category`` + datatype will still follow the category order even if the + levels are strictly numerical. + - Changed how :func:`stripplot` draws points when using + ``hue`` nesting with ``split=False`` so that the different + ``hue`` levels are not drawn strictly on top of each other. + - Improve performance for large dendrograms in + :func:`clustermap`. + - Added ``font.size`` to the plotting context definition so + that the default output from ``plt.text`` will be scaled + appropriately. + - Fixed a bug in :func:`clustermap` when ``fastcluster`` is + not installed. + - Fixed a bug in the zscore calculation in + :func:`clustermap`. + - Fixed a bug in :func:`distplot` where sometimes the default + number of bins would not be an integer. + - Fixed a bug in :func:`stripplot` where a legend item would + not appear for a ``hue`` level if there were no observations + in the first group of points. + - Heatmap colorbars are now rasterized for better performance + in vector plots. + - Added workarounds for some matplotlib boxplot issues, such as + strange colors of outlier points. + - Added workarounds for an issue where violinplot edges would be + missing or have random colors. + - Added a workaround for an issue where only one :func:`heatmap` + cell would be annotated on some matplotlib backends. + - Fixed a bug on newer versions of matplotlib where a colormap + would be erroneously applied to scatterplots with only three + observations. + - Updated seaborn for compatibility with matplotlib 1.5. + - Added compatibility for various IPython (and Jupyter) versions + in functions that use widgets. +- Add python3-seaborn-0.7.0-remove_color_list _from_dendrogram_call_in_tests.patch + to fix compatibility with python3-scipy 0.17.0 + +------------------------------------------------------------------- +Wed Jul 1 12:15:21 UTC 2015 - toddrme2178@gmail.com + +- Update to 0.6.0 + * Changed plotting functions + - In version 0.6, the "categorical" plots have been unified with a common + API + - Changes to :func:`boxplot` and :func:`violinplot` will probably be the + most disruptive. Both functions maintain backwards-compatibility in + terms of the kind of data they can accept, but the syntax has changed to + be more similar to other seaborn functions. These functions are now + invoked with ``x`` and/or ``y`` parameters that are either vectors of + data or names of variables in a long-form DataFrame passed to the new + ``data`` parameter. You can still pass wide-form DataFrames or arrays to + ``data``, but it is no longer the first positional argument. See the + `github pull request https://github.com/mwaskom/seaborn/pull/410`_ for + more information on these changes and the logic behind them. + - As :func:`pointplot` and :func:`barplot` can now plot with the major + categorical variable on the y axis, the ``x_order`` parameter has been + renamed to ``order``. + - Added a ``hue`` argument to :func:`boxplot` and :func:`violinplot`, + which allows for nested grouping the plot elements by a third + categorical variable. For :func:`violinplot`, this nesting can also be + accomplished by splitting the violins when there are two levels of the + ``hue`` variable (using ``split=True``). To make this functionality + feasible, the ability to specify where the plots will be draw in data + coordinates has been removed. These plots now are drawn at set + positions, like (and identical to) :func:`barplot` and :func:`pointplot`. + - Added a ``palette`` parameter to :func:`boxplot`/:func:`violinplot`. The + ``color`` parameter still exists, but no longer does double-duty in + accepting the name of a seaborn palette. ``palette`` supersedes + ``color`` so that it can be used with a :class:`FacetGrid`. + - The default rules for ordering the categories has changed. Instead of + automatically sorting the category levels, the plots now show the levels + in the order they appear in the input data (i.e., the order given by + ``Series.unique()``). Order can be specified when plotting with the + ``order`` and ``hue_order`` parameters. Additionally, when variables are + pandas objects with a "categorical" dtype, the category order is + inferred from the data object. This change also affects + :class:`FacetGrid` and :class:`PairGrid`. + - Added the ``scale`` and ``scale_hue`` parameters to :func:`violinplot`. + These control how the width of the violins are scaled. The default is + ``area``, which is different from how the violins used to be drawn. Use + ``scale='width'`` to get the old behavior. + - Used a different style for the ``box`` kind of interior plot in + :func:`violinplot`, which shows the whisker range in addition to the + quartiles. Use ``inner='quartile'`` to get the old style. + * New plotting functions + - Added the :func:`stripplot` function, which draws a scatterplot where + one of the variables is categorical. This plot has the same API as + :func:`boxplot` and :func:`violinplot`. It is useful both on its own and + when composed with one of these other plot kinds to show both the + observations and underlying distribution. + - Added the :func:`countplot` function, which uses a bar plot + representation to show counts of variables in one or more categorical + bins. This replaces the old approach of calling :func:`barplot` without + a numeric variable. + * Other additions and changes + - The :func:`corrplot` and underlying :func:`symmatplot` functions have + been deprecated in favor of :func:`heatmap`, which is much more flexible + and robust. These two functions are still available in version 0.6, but + they will be removed in a future version. + - Added the :func:`set_color_codes` function and the ``color_codes`` + argument to :func:`set` and :func:`set_palette`. This changes the + interpretation of shorthand color codes (i.e. "b", "g", k", etc.) within + matplotlib to use the values from one of the named seaborn palettes + (i.e. "deep", "muted", etc.). That makes it easier to have a more + uniform look when using matplotlib functions directly with seaborn + imported. This could be disruptive to existing plots, so it does not + happen by default. It is possible this could change in the future. + - The :func:`color_palette` function no longer trims palettes that are + longer than 6 colors when passed into it. + - Added the ``as_hex`` method to color palette objects, to return a list + of hex codes rather than rgb tuples. + - :func:`jointplot` now passes additional keyword arguments to the + function used to draw the plot on the joint axes. + - Changed the default ``linewidths`` in :func:`heatmap` and + :func:`clustermap` to 0 so that larger matrices plot correctly. This + parameter still exists and can be used to get the old effect of lines + demarcating each cell in the heatmap (the old default ``linewidths`` was + 0.5). + - :func:`heatmap` and :func:`clustermap` now automatically use a mask for + missing values, which previously were shown with the "under" value of + the colormap per default `plt.pcolormesh` behavior. + - Added the ``seaborn.crayons`` dictionary and the :func:`crayon_palette` + function to define colors from the 120 box (!) of `Crayola crayons + http://en.wikipedia.org/wiki/List_of_Crayola_crayon_colors`_. + - Added the ``line_kws`` parameter to :func:`residplot` to change the + style of the lowess line, when used. + - Added open-ended ``**kwargs`` to the ``add_legend`` method on + :class:`FacetGrid` and :class:`PairGrid`, which will pass additional + keyword arguments through when calling the legend function on the + ``Figure`` or ``Axes``. + - Added the ``gridspec_kws`` parameter to :class:`FacetGrid`, which allows + for control over the size of individual facets in the grid to emphasize + certain plots or account for differences in variable ranges. + - The interactive palette widgets now show a continuous colorbar, rather + than a discrete palette, when `as_cmap` is True. + - The default Axes size for :func:`pairplot` and :class:`PairGrid` is now + slightly smaller. + - Added the ``shade_lowest`` parameter to :func:`kdeplot` which will set + the alpha for the lowest contour level to 0, making it easier to plot + multiple bivariate distributions on the same axes. + - The ``height`` parameter of :func:`rugplot` is now interpreted as a + function of the axis size and is invariant to changes in the data scale + on that axis. The rug lines are also slightly narrower by default. ++++ 46 more lines (skipped) ++++ between /dev/null ++++ and /work/SRC/openSUSE:Factory/.python-seaborn.new/python-seaborn.changes New: ---- python-seaborn.changes python-seaborn.spec seaborn-0.7.1.tar.gz ++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++ Other differences: ------------------ ++++++ python-seaborn.spec ++++++ # # spec file for package python-seaborn # # Copyright (c) 2016 SUSE LINUX Products GmbH, Nuernberg, Germany. # # All modifications and additions to the file contributed by third parties # remain the property of their copyright owners, unless otherwise agreed # upon. The license for this file, and modifications and additions to the # file, is the same license as for the pristine package itself (unless the # license for the pristine package is not an Open Source License, in which # case the license is the MIT License). An "Open Source License" is a # license that conforms to the Open Source Definition (Version 1.9) # published by the Open Source Initiative. # Please submit bugfixes or comments via http://bugs.opensuse.org/ # Name: python-seaborn Version: 0.7.1 Release: 0 Summary: Statistical data visualization for python License: BSD-3-Clause Group: Development/Languages/Python Url: https://pypi.python.org/pypi/seaborn/ Source: https://files.pythonhosted.org/packages/source/s/seaborn/seaborn-%{version}.tar.gz BuildRequires: python-devel BuildRequires: python-setuptools BuildRequires: python-Pillow BuildRequires: python-fastcluster BuildRequires: python-matplotlib BuildRequires: python-numpy-devel BuildRequires: python-pandas BuildRequires: python-patsy BuildRequires: python-scipy BuildRequires: python-six BuildRequires: python-statsmodels BuildConflicts: python-buildservice-tweak # Testing requirements BuildRequires: python-jupyter_ipython BuildRequires: python-jupyter_notebook BuildRequires: python-nose Requires: python-matplotlib Requires: python-numpy Requires: python-pandas Requires: python-scipy Requires: python-six Recommends: python-Pillow Recommends: python-fastcluster Recommends: python-patsy Recommends: python-statsmodels BuildRoot: %{_tmppath}/%{name}-%{version}-build %if 0%{?suse_version} && 0%{?suse_version} <= 1110 %{!?python_sitelib: %global python_sitelib %(python -c "from distutils.sysconfig import get_python_lib; print get_python_lib()")} %else BuildArch: noarch %endif %description Seaborn is a library for making attractive and informative statistical graphics in Python. It is built on top of matplotlib and tightly integrated with the PyData stack, including support for numpy and pandas data structures and statistical routines from scipy and statsmodels. Some of the features that seaborn offers are: - Several built-in themes that improve on the default matplotlib aesthetics - Tools for choosing color palettes to make beautiful plots that reveal patterns in your data - Functions for visualizing univariate and bivariate distributions or for comparing them between subsets of data - Tools that fit and visualize linear regression models for different kinds of independent and dependent variables - Functions that visualize matrices of data and use clustering algorithms to discover structure in those matrices - A function to plot statistical timeseries data with flexible estimation and representation of uncertainty around the estimate - High-level abstractions for structuring grids of plots that let you easily build complex visualizations %prep %setup -q -n seaborn-%{version} %build python setup.py build %install python setup.py install --prefix=%{_prefix} --root=%{buildroot} %check nosetests %files %defattr(-,root,root,-) %{python_sitelib}/* %changelog