ImageNormalize¶
-
class
astropy.visualization.mpl_normalize.
ImageNormalize
(data=None, interval=None, vmin=None, vmax=None, stretch=<astropy.visualization.stretch.LinearStretch object>, clip=True)[source] [edit on github]¶ Bases:
matplotlib.colors.Normalize
Normalization class to be used with Matplotlib.
Parameters: - data :
ndarray
, optional The image array. This input is used only if
interval
is also input.data
andinterval
are used to compute the vmin and/or vmax values only ifvmin
orvmax
are not input.- interval :
BaseInterval
subclass instance, optional The interval object to apply to the input
data
to determine thevmin
andvmax
values. This input is used only ifdata
is also input.data
andinterval
are used to compute the vmin and/or vmax values only ifvmin
orvmax
are not input.- vmin, vmax : float
The minimum and maximum levels to show for the data. The
vmin
andvmax
inputs override any calculated values from theinterval
anddata
inputs.- stretch :
BaseStretch
subclass instance, optional The stretch object to apply to the data. The default is
LinearStretch
.- clip : bool, optional
If
True
(default), data values outside the [0:1] range are clipped to the [0:1] range.
Methods Summary
__call__
(values[, clip])Normalize value data in the [vmin, vmax]
interval into the[0.0, 1.0]
interval and return it.inverse
(values)Methods Documentation
-
__call__
(values, clip=None)[source] [edit on github]¶ Normalize value data in the
[vmin, vmax]
interval into the[0.0, 1.0]
interval and return it. clip defaults to self.clip (which defaults to False). If not already initialized, vmin and vmax are initialized using autoscale_None(value).
-
inverse
(values)[source] [edit on github]¶
- data :