matplotlib.colors.LogNorm
-
class
matplotlib.colors.
LogNorm
( vmin=None, vmax=None, clip=False ) [source] -
Bases:
matplotlib.colors.LogNorm
Normalize a given value to the 0-1 range on a log scale.
-
__call__
( value, clip=None ) -
Normalize value data in the
[vmin, vmax]
interval into the[0.0, 1.0]
interval and return it.Parameters: - value
-
Data to normalize.
- clip bool
-
If
None
, defaults toself.clip
(which defaults toFalse
).
Notes
If not already initialized,
self.vmin
andself.vmax
are initialized usingself.autoscale_None(value)
.
-
__init__
( vmin=None, vmax=None, clip=False ) -
Parameters: - vmin, vmax float 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)
. - clip bool, 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
.
-
__module__
= 'matplotlib.colors'
-
__slotnames__
= []
-
inverse
( value )
-
Examples using matplotlib.colors.LogNorm
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Licensed under the Matplotlib License Agreement.
https://matplotlib.org/3.4.3/api/_as_gen/matplotlib.colors.LogNorm.html