ImageNormalize¶
-
class
astropy.visualization.
ImageNormalize
(data=None, interval=None, vmin=None, vmax=None, stretch=<astropy.visualization.stretch.LinearStretch object>, clip=False)[source]¶ 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, vmaxfloat, optional
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 The stretch object to apply to the data. The default is
LinearStretch
.- clipbool, optional
If
True
, data values outside the [0:1] range are clipped to the [0:1] range.
- data
- Parameters
- vmin, vmaxfloat or None
If vmin and/or vmax is not given, they are initialized from the minimum and maximum value, respectively, of the first input processed; i.e.,
__call__(A)
callsautoscale_None(A)
.- clipbool, default: False
If
True
values falling outside the range[vmin, vmax]
, are mapped to 0 or 1, whichever is closer, and masked values are set to 1. IfFalse
masked values remain masked.Clipping silently defeats the purpose of setting the over, under, and masked colors in a colormap, so it is likely to lead to surprises; therefore the default is
clip=False
.
Notes
Returns 0 if
vmin == vmax
.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]¶ Normalize value data in the
[vmin, vmax]
interval into the[0.0, 1.0]
interval and return it.- Parameters
- value
Data to normalize.
- clipbool
If
None
, defaults toself.clip
(which defaults toFalse
).
Notes
If not already initialized,
self.vmin
andself.vmax
are initialized usingself.autoscale_None(value)
.