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# What’s new in matplotlib

For a list of all of the issues and pull requests since the last revision, see the GitHub Stats.

Table of Contents

- What’s new in matplotlib
  - New in matplotlib 2.0
    - Default style changes
    - Improved color conversion API and RGBA support
    - New Configuration (rcParams)
    - Qualitative colormaps
    - Axis offset label now responds to `labelcolor`
    - Improved offset text choice
    - Style parameter blacklist
    - Change in default font
    - Faster text rendering
    - Improvements for the Qt figure options editor
    - Improved image support
    - Support for HiDPI (Retina) displays in the NbAgg and WebAgg backends
    - Change in the default animation codec
    - Deprecated support for mencoder in animation
    - Boxplot Zorder Keyword Argument
    - Filled `+` and `x` markers
    - `rcount` and `ccount` for `plot_surface()`
    - Streamplot Zorder Keyword Argument Changes
    - Extension to `matplotlib.backend_bases.GraphicsContextBase`
  - Previous Whats New

## New in matplotlib 2.0

Note

matplotlib 2.0 supports Python 2.7, and 3.4+

### Default style changes

The major changes in v2.0 are related to overhauling the default styles.

- Changes to the default style
  - Colors, color cycles, and color maps
  - Figure size, font size, and screen dpi
  - Plotting functions
  - Hatching
  - Fonts
  - Legends
  - Image
  - Plot layout
  - mplot3d

### Improved color conversion API and RGBA support

The `colors` gained a new color conversion API with full support for the alpha channel. The main public functions are `is_color_like()`, `matplotlib.colors.to_rgba()`, `matplotlib.colors.to_rgba_array()` and `to_hex()`. RGBA quadruplets are encoded in hex format as `#rrggbbaa`.

A side benefit is that the Qt options editor now allows setting the alpha channel of the artists as well.

### New Configuration (rcParams)

New rcparams added

Parameter | Description
--- | ---
`date.autoformatter.year` | format string for ‘year’ scale dates
`date.autoformatter.month` | format string for ‘month’ scale dates
`date.autoformatter.day` | format string for ‘day’ scale dates
`date.autoformatter.hour` | format string for ‘hour’ scale times
`date.autoformatter.minute` | format string for ‘minute’ scale times
`date.autoformatter.second` | format string for ‘second’ scale times
`date.autoformatter.microsecond` | format string for ‘microsecond’ scale times
`scatter.marker` | default marker for scatter plot
`svg.hashsalt` | see note
`xtick.top`, `xtick.minor.top`, `xtick.major.top` `xtick.bottom`, `xtick.minor.bottom`, `xtick.major.bottom` `ytick.left`, `ytick.minor.left`, `ytick.major.left` `ytick.right`, `ytick.minor.right`, `ytick.major.right` | Control where major and minor ticks are drawn. The global values are `and` ed with the corresponding major/minor values.
`hist.bins` | The default number of bins to use in `hist`. This can be an `int`, a list of floats, or `'auto'` if numpy >= 1.11 is installed.
`lines.scale_dashes` | Whether the line dash patterns should scale with linewidth.
`axes.formatter.offset_threshold` | Minimum number of digits saved in tick labels that triggers using an offset.

#### Added `svg.hashsalt` key to rcParams

If `svg.hashsalt` is `None` (which it is by default), the svg backend uses `uuid4` to generate the hash salt. If it is not `None`, it must be a string that is used as the hash salt instead of `uuid4`. This allows for deterministic SVG output.

#### Removed the `svg.image_noscale` rcParam

As a result of the extensive changes to image handling, the `svg.image_noscale` rcParam has been removed. The same functionality may be achieved by setting `interpolation='none'` on individual images or globally using the `image.interpolation` rcParam.

### Qualitative colormaps

ColorBrewer’s “qualitative” colormaps (“Accent”, “Dark2”, “Paired”, “Pastel1”, “Pastel2”, “Set1”, “Set2”, “Set3”) were intended for discrete categorical data, with no implication of value, and therefore have been converted to `ListedColormap` instead of `LinearSegmentedColormap`, so the colors will no longer be interpolated and they can be used for choropleths, labeled image features, etc.

### Axis offset label now responds to `labelcolor`

Axis offset labels are now colored the same as axis tick markers when `labelcolor` is altered.

### Improved offset text choice

The default offset-text choice was changed to only use significant digits that are common to all ticks (e.g. 1231..1239 -> 1230, instead of 1231), except when they straddle a relatively large multiple of a power of ten, in which case that multiple is chosen (e.g. 1999..2001->2000).

### Style parameter blacklist

In order to prevent unexpected consequences from using a style, style files are no longer able to set parameters that affect things unrelated to style. These parameters include:

    'interactive', 'backend', 'backend.qt4', 'webagg.port',
    'webagg.port_retries', 'webagg.open_in_browser', 'backend_fallback',
    'toolbar', 'timezone', 'datapath', 'figure.max_open_warning',
    'savefig.directory', 'tk.window_focus', 'docstring.hardcopy'

### Change in default font

The default font used by matplotlib in text has been changed to DejaVu Sans and DejaVu Serif for the sans-serif and serif families, respectively. The DejaVu font family is based on the previous matplotlib default –Bitstream Vera– but includes a much wider range of characters.

The default mathtext font has been changed from Computer Modern to the DejaVu family to maintain consistency with regular text. Two new options for the `mathtext.fontset` configuration parameter have been added: `dejavusans` (default) and `dejavuserif`. Both of these options use DejaVu glyphs whenever possible and fall back to STIX symbols when a glyph is not found in DejaVu. To return to the previous behavior, set the rcParam `mathtext.fontset` to `cm`.

### Faster text rendering

Rendering text in the Agg backend is now less fuzzy and about 20% faster to draw.

### Improvements for the Qt figure options editor

Various usability improvements were implemented for the Qt figure options editor, among which:

- Line style entries are now sorted without duplicates.
- The colormap and normalization limits can now be set for images.
- Line edits for floating values now display only as many digits as necessary to avoid precision loss. An important bug was also fixed regarding input validation using Qt5 and a locale where the decimal separator is “,”.
- The axes selector now uses shorter, more user-friendly names for axes, and does not crash if there are no axes.
- Line and image entries using the default labels (“_lineX”, “_imageX”) are now sorted numerically even when there are more than 10 entries.

### Improved image support

Prior to version 2.0, matplotlib resampled images by first applying the color map and then resizing the result. Since the resampling was performed on the colored image, this introduced colors in the output image that didn’t actually exist in the color map. Now, images are resampled first (and entirely in floating-point, if the input image is floating-point), and then the color map is applied.

In order to make this important change, the image handling code was almost entirely rewritten. As a side effect, image resampling uses less memory and fewer datatype conversions than before.

The experimental private feature where one could “skew” an image by setting the private member `_image_skew_coordinate` has been removed. Instead, images will obey the transform of the axes on which they are drawn.

#### Non-linear scales on image plots

`imshow()` now draws data at the requested points in data space after the application of non-linear scales.

The image on the left demonstrates the new, correct behavior. The old behavior can be recreated using `pcolormesh()` as demonstrated on the right.

(Source code, png, pdf)

This can be understood by analogy to plotting a histogram with linearly spaced bins with a logarithmic x-axis. Equal sized bins will be displayed as wider for small x and narrower for large x.

### Support for HiDPI (Retina) displays in the NbAgg and WebAgg backends

The NbAgg and WebAgg backends will now use the full resolution of your high-pixel-density display.

### Change in the default animation codec

The default animation codec has been changed from `mpeg4` to `h264`, which is more efficient. It can be set via the `animation.codec` rcParam.

### Deprecated support for mencoder in animation

The use of mencoder for writing video files with mpl is problematic; switching to ffmpeg is strongly advised. All support for mencoder will be removed in version 2.2.

### Boxplot Zorder Keyword Argument

The `zorder` parameter now exists for `boxplot()`. This allows the zorder of a boxplot to be set in the plotting function call.

    boxplot(np.arange(10), zorder=10)

### Filled `+` and `x` markers

New fillable plus and x markers have been added. See the `markers` module and marker reference examples.

### `rcount` and `ccount` for `plot_surface()`

As of v2.0, mplot3d’s `plot_surface()` now accepts `rcount` and `ccount` arguments for controlling the sampling of the input data for plotting. These arguments specify the maximum number of evenly spaced samples to take from the input data. These arguments are also the new default sampling method for the function, and is considered a style change.

The old `rstride` and `cstride` arguments, which specified the size of the evenly spaced samples, become the default when ‘classic’ mode is invoked, and are still available for use. There are no plans for deprecating these arguments.

### Streamplot Zorder Keyword Argument Changes

The `zorder` parameter for `streamplot()` now has default value of `None` instead of `2`. If `None` is given as `zorder`, `streamplot()` has a default `zorder` of `matplotlib.lines.Line2D.zorder`.

### Extension to `matplotlib.backend_bases.GraphicsContextBase`

To support standardizing hatch behavior across the backends we ship the `matplotlib.backend_bases.GraphicsContextBase.get_hatch_color` method as added to `matplotlib.backend_bases.GraphicsContextBase`. This is only used during the render process in the backends we ship so will not break any third-party backends.

If you maintain a third-party backend which extends `GraphicsContextBase` this method is now available to you and should be used to color hatch patterns.

## Previous Whats New

- New in matplotlib 0.98.4
- New in matplotlib 0.99
- New in matplotlib 1.0
- New in matplotlib 1.1
- New in matplotlib 1.2
- New in matplotlib 1.2.2
- New in matplotlib 1.3
- New in matplotlib 1.4
- New in matplotlib 1.5
- List of changes to Matplotlib prior to 2015