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Copy file name to clipboardExpand all lines: CHANGELOG.md
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This project adheres to [Semantic Versioning](http://semver.org/).
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## [Unreleased]
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### Added
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- The FigureFactory can now create violin plots with `.create_violin`. Check it out with:
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```
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import plotly.tools as tls
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help(tls.FigureFactory.create_violin)
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```
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## [1.12.0] - 2016-06-06
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### Added
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- Added ability to enable/disable SSL certificate verification for streaming. Disabling SSL certification verification requires Python v2.7.9 / v3.4.3 (or above). This feature can be toggled via the `plotly_ssl_verification` configuration setting.
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## [1.11.0] - 2016-05-27
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### Updated
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- Changed the default option for `create_distplot` in the figure factory from `probability` to `probability density` and also added the `histnorm` parameter to allow the user to choose between the two options.
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Note: This is a backwards incompatible change.
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- Updated plotly.min.js so the offline mode is using plotly.js v1.12.0
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- Light position is now configurable in surface traces
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- surface and mesh3d lighting attributes are now accompanied with comprehensive descriptions
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- Allowed `create_scatterplotmatrix` and `create_trisurf` to use divergent and categorical colormaps. The parameter `palette` has been replaced by `colormap` and `use_palette` has been removed. In `create_scatterplotmatrix`, users can now:
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- Input a list of different color types (hex, tuple, rgb) to `colormap` to map colors divergently
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- Use the same list to categorically group the items in the index column
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- Pass a singlton color type to `colormap` to color all the data with one color
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- Input a dictionary to `colormap` to map index values to a specific color
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- 'cat' and 'seq' are valid options for `colormap_type`, which specify the type of colormap being used
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- In `create_trisurf`, the parameter `dist_func` has been replaced by `color_func`. Users can now:
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- Input a list of different color types (hex, tuple, rgb) to `colormap` to map colors divergently
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- Input a list|array of hex and rgb colors to `color_func` to assign each simplex to a color
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### Added
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- Added the option to load plotly.js from a CDN by setting the parameter `connected=True`
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in the `init_notebook_mode()` function call
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- The FigureFactory can now create trisurf plots with `.create_trisurf`. Check it out with:
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```
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import plotly.tools as tls
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help(tls.FigureFactory.create_trisurf)
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```
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## [1.10.0] - 2016-05-19
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### Fixed
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- Version 1.9.13 fixed an issue in offline mode where if you ran `init_notebook_mode`
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more than once the function would skip importing (because it saw that it had
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already imported the library) but then accidentally clear plotly.js from the DOM.
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This meant that if you ran `init_notebook_mode` more than once, your graphs would
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not appear when you refreshed the page.
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Version 1.9.13 solved this issue by injecting plotly.js with every iplot call.
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While this works, it also injects the library excessively, causing notebooks
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to have multiple versions of plotly.js inline in the DOM, potentially making
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notebooks with many `iplot` calls very large.
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Version 1.10.0 brings back the requirement to call `init_notebook_mode` before
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making an `iplot` call. It makes `init_notebook_mode` idempotent: you can call
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it multiple times without worrying about losing your plots on refresh.
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## [1.9.13] - 2016-05-19
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### Fixed
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- Fixed issue in offline mode related to the inability to reload plotly.js on page refresh and extra init_notebook_mode calls.
Copy file name to clipboardExpand all lines: contributing.md
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When you write a new test anywhere under the `tests` directory, if your PR gets accepted, that test will run in a virtual machine to ensure that future changes don't break your contributions!
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#### Publishing to Pip
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You'll need the credentials file `~/.pypirc`. Request access from @theengineear and @chriddyp. Then, from inside the repository:
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```
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(plotly.py) $ git checkout master
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(plotly.py) $ git stash
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(plotly.py) $ git pull origin master
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(plotly.py) $ python setup.py sdist upload # upload to pip
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```
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After it has uploaded, move to another directly and double+triple check that you are able to upgrade ok:
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```
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$ pip install plotly --upgrade
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```
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And ask one of your friends to do it too. Our tests should catch any issues, but you never know.
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