Hello community, here is the log from the commit of package python-seaborn for openSUSE:Factory checked in at 2017-08-18 15:05:56 ++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++ Comparing /work/SRC/openSUSE:Factory/python-seaborn (Old) and /work/SRC/openSUSE:Factory/.python-seaborn.new (New) ++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++
Package is "python-seaborn" Fri Aug 18 15:05:56 2017 rev:3 rq:517403 version:0.8 Changes: -------- --- /work/SRC/openSUSE:Factory/python-seaborn/python-seaborn.changes 2017-05-08 19:03:54.184608797 +0200 +++ /work/SRC/openSUSE:Factory/.python-seaborn.new/python-seaborn.changes 2017-08-18 15:05:57.589007132 +0200 @@ -1,0 +2,76 @@ +Thu Aug 17 14:44:57 UTC 2017 - [email protected] + +- Update to version 0.8.0 + * The default style is no longer applied when seaborn is + imported. It is now necessary to explicitly call set() or one + or more of set_style(), set_context(), and set_palette(). + Correspondingly, the seaborn.apionly module has been + deprecated. + * Changed the behavior of heatmap() (and by extension + clustermap()) when plotting divergent dataesets (i.e. when + the center parameter is used). Instead of extending the lower + and upper limits of the colormap to be symettrical around the + center value, the colormap is modified so that its middle color + corresponds to center. This means that the full range of the + colormap will not be used (unless the data or specified vmin + and vmax are symettric), but the upper and lower limits of + the colorbar will correspond to the range of the data. See the + Github pull request (#1184) for examples of the behavior. + * Removed automatic detection of diverging data in heatmap() + (and by extension clustermap()). If you want the colormap to + be treated as diverging (see above), it is now necessary to + specify the center value. When no colormap is specified, + specifying center will still change the default to be one that + is more appropriate for displaying diverging data. + * Added four new colormaps, created using viscm for perceptual + uniformity. The new colormaps include two sequential colormaps + (“rocket” and “mako”) and two diverging colormaps (“icefire” + and “vlag”). These colormaps are registered with matplotlib on + seaborn input and the colormap objects can be accessed in the + seaborn.cm namespace. + * Changed the default heatmap() colormaps to be “rocket” (in the + case of sequential data) or “icefire” (in the case of diverging + data). Note that this change reverses the direction of the + luminance ramp from the previous defaults. While potentially + confusing and disruptive, this change better aligns the seaborn + defaults with the new matplotlib default colormap (“viridis”) + and arguably better aligns the semantics of a “heat” map with + the appearance of the colormap. + * Added "auto" as a (default) option for tick labels in heatmap() + and clustermap(). This will try to estimate how many ticks can + be labeled without the text objects overlapping, which should + improve performance for larger matrices. + * Added the dodge parameter to boxplot(), violinplot(), and + barplot() to allow use of hue without changing the position or + width of the plot elements, as when the hue varible is not + nested within the main categorical variable. + * Correspondingly, the split parameter for stripplot() and + swarmplot() has been renamed to dodge for consistency with the + other categorical functions (and for differentiation from the + meaning of split in violinplot()). + * Added the ability to draw a colorbar for a bivariate kdeplot() + with the cbar parameter (and related cbar_ax and cbar_kws + parameters). + * Added the ability to use error bars to show standard deviations + rather than bootstrap confidence intervals in most statistical + functions by putting ci="sd". + * Allow side-specific offsets in despine(). + * Figure size is no longer part of the seaborn plotting context + parameters. + * Put a cap on the number of bins used in jointplot() for + type=="hex" to avoid hanging when the reference rule prescribes + too many. + * Turn off dendrogram axes in clustermap() rather than setting + the background color to white. + * New matplotlib qualitative palettes (e.g. “tab10”) are now + handled correctly. + * Some modules and functions have been internally reorganized; + there should be no effect on code that uses the seaborn + namespace. + * Added a deprecation warning to tsplot() function to indicate + that it will be removed or replaced with a substantially + altered version in a future release. + * The interactplot and coefplot functions are officially + deprecated and will be removed in a future release. + +------------------------------------------------------------------- Old: ---- seaborn-0.7.1.tar.gz New: ---- seaborn-0.8.tar.gz ++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++ Other differences: ------------------ ++++++ python-seaborn.spec ++++++ --- /var/tmp/diff_new_pack.SKq7zf/_old 2017-08-18 15:05:59.116791959 +0200 +++ /var/tmp/diff_new_pack.SKq7zf/_new 2017-08-18 15:05:59.116791959 +0200 @@ -21,7 +21,7 @@ %{?!python_module:%define python_module() python-%{**} python3-%{**}} Name: python-seaborn -Version: 0.7.1 +Version: 0.8 Release: 0 Summary: Statistical data visualization for python License: BSD-3-Clause ++++++ seaborn-0.7.1.tar.gz -> seaborn-0.8.tar.gz ++++++ ++++ 10295 lines of diff (skipped)
