Data Visualization (astropy.visualization
)¶
Introduction¶
astropy.visualization
provides functionality that can be helpful when
visualizing data. This includes a framework for plotting Astronomical images
with coordinates with Matplotlib (previously the standalone wcsaxes
package), functionality related to image normaliation (including both scaling
and stretching), smart histogram plotting, RGB color image creation from
separate images, and custom plotting styles for Matplotlib.
Using astropy.visualization
¶
Astropy matplotlib style¶
The visualization package contains two dictionaries that can be used to set the Matplotlib plotting style:
-
astropy_mpl_style
¶ Improves some settings over the matplotlib default style.
-
astropy_mpl_docs_style
¶ Matplotlib style used by the Astropy documentation.
To apply the custom style on top of your existing matplotlib style, perform the following:
Using matplotlib version >= 1.5:
>>> import matplotlib.pyplot as plt
>>> from astropy.visualization import astropy_mpl_style
>>> plt.style.use(astropy_mpl_style)
For older versions of matplotlib:
>>> import matplotlib as mpl
>>> from astropy.visualization import astropy_mpl_style
>>> mpl.rcParams.update(astropy_mpl_style)
Note that these styles are applied on top your existing matplotlib style. If you want an exactly reproducible plot (i.e. if you want the plot to come out exactly the same independent of the user configuration), you should reset the matplotlib settings to the defaults before applying the astropy style.
Using matplotlib version >= 1.5:
>>> import matplotlib.pyplot as plt
>>> from astropy.visualization import astropy_mpl_style
>>> plt.style.use('default')
>>> plt.style.use(astropy_mpl_style)
For older versions of matplotlib:
>>> import matplotlib as mpl
>>> from astropy.visualization import astropy_mpl_style
>>> mpl.rcdefaults()
>>> mpl.rcParams.update(astropy_mpl_style)
Scripts¶
This module includes a command-line script, fits2bitmap
to convert FITS
images to bitmaps, including scaling and stretching of the image. To find out
more about the available options and how to use it, type:
$ fits2bitmap --help
Reference/API¶
astropy.visualization.mpl_style Module¶
This module contains dictionaries that can be used to set a matplotlib plotting style. It is mostly here to allow a consistent plotting style in tutorials, but can be used to prepare any matplotlib figure.
astropy.visualization Package¶
Functions¶
hist (x[, bins, ax]) |
Enhanced histogram function |
make_lupton_rgb (image_r, image_g, image_b[, ...]) |
Return a Red/Green/Blue color image from up to 3 images using an asinh stretch. |
quantity_support ([format]) |
Enable support for plotting astropy.units.Quantity instances in matplotlib. |
simple_norm (data[, stretch, power, asinh_a, ...]) |
Return a Normalization class that can be used for displaying images with Matplotlib. |
Classes¶
AsinhStretch ([a]) |
An asinh stretch. |
AsymmetricPercentileInterval (...[, n_samples]) |
Interval based on a keeping a specified fraction of pixels (can be asymmetric). |
BaseInterval |
Base class for the interval classes, which, when called with an array of values, return an interval computed following different algorithms. |
BaseStretch |
Base class for the stretch classes, which, when called with an array of values in the range [0:1], return an transformed array of values, also in the range [0:1]. |
BaseTransform |
A transformation object. |
CompositeTransform (transform_1, transform_2) |
A combination of two transforms. |
ContrastBiasStretch (contrast, bias) |
A stretch that takes into account contrast and bias. |
HistEqStretch (data[, values]) |
A histogram equalization stretch. |
ImageNormalize ([data, interval, vmin, vmax, ...]) |
Normalization class to be used with Matplotlib. |
LinearStretch |
A linear stretch. |
LogStretch ([a]) |
A log stretch. |
ManualInterval ([vmin, vmax]) |
Interval based on user-specified values. |
MinMaxInterval |
Interval based on the minimum and maximum values in the data. |
PercentileInterval (percentile[, n_samples]) |
Interval based on a keeping a specified fraction of pixels. |
PowerDistStretch ([a]) |
An alternative power stretch. |
PowerStretch (a) |
A power stretch. |
SinhStretch ([a]) |
A sinh stretch. |
SqrtStretch |
A square root stretch. |
SquaredStretch () |
A convenience class for a power stretch of 2. |
ZScaleInterval ([nsamples, contrast, ...]) |
Interval based on IRAF’s zscale. |
Class Inheritance Diagram¶
astropy.visualization.mpl_normalize Module¶
Normalization class for Matplotlib that can be used to produce colorbars.
Functions¶
simple_norm (data[, stretch, power, asinh_a, ...]) |
Return a Normalization class that can be used for displaying images with Matplotlib. |
Classes¶
ImageNormalize ([data, interval, vmin, vmax, ...]) |
Normalization class to be used with Matplotlib. |