matplotlib.scale
¶matplotlib.scale.
InvertedLog10Transform
(shorthand_name=None)[source]¶Bases: matplotlib.scale.InvertedLogTransformBase
Creates a new TransformNode
.
Parameters: | shorthand_name : str
|
---|
base
= 10.0¶matplotlib.scale.
InvertedLog2Transform
(shorthand_name=None)[source]¶Bases: matplotlib.scale.InvertedLogTransformBase
Creates a new TransformNode
.
Parameters: | shorthand_name : str
|
---|
base
= 2.0¶matplotlib.scale.
InvertedLogTransformBase
(shorthand_name=None)[source]¶Bases: matplotlib.transforms.Transform
Creates a new TransformNode
.
Parameters: | shorthand_name : str
|
---|
has_inverse
= True¶input_dims
= 1¶is_separable
= True¶output_dims
= 1¶matplotlib.scale.
InvertedNaturalLogTransform
(shorthand_name=None)[source]¶Bases: matplotlib.scale.InvertedLogTransformBase
Creates a new TransformNode
.
Parameters: | shorthand_name : str
|
---|
base
= 2.718281828459045¶matplotlib.scale.
InvertedSymmetricalLogTransform
(base, linthresh, linscale)[source]¶Bases: matplotlib.transforms.Transform
has_inverse
= True¶input_dims
= 1¶is_separable
= True¶output_dims
= 1¶matplotlib.scale.
LinearScale
(axis, **kwargs)[source]¶Bases: matplotlib.scale.ScaleBase
The default linear scale.
get_transform
()[source]¶The transform for linear scaling is just the
IdentityTransform
.
name
= u'linear'¶matplotlib.scale.
Log10Transform
(nonpos=u'clip')[source]¶Bases: matplotlib.scale.LogTransformBase
base
= 10.0¶matplotlib.scale.
Log2Transform
(nonpos=u'clip')[source]¶Bases: matplotlib.scale.LogTransformBase
base
= 2.0¶matplotlib.scale.
LogScale
(axis, **kwargs)[source]¶Bases: matplotlib.scale.ScaleBase
A standard logarithmic scale. Care is taken so non-positive values are not plotted.
For computational efficiency (to push as much as possible to Numpy C code in the common cases), this scale provides different transforms depending on the base of the logarithm:
- base 10 (
Log10Transform
)- base 2 (
Log2Transform
)- base e (
NaturalLogTransform
)- arbitrary base (
LogTransform
)
Where to place the subticks between each major tick.
Should be a sequence of integers. For example, in a log10
scale: [2, 3, 4, 5, 6, 7, 8, 9]
will place 8 logarithmically spaced minor ticks between each major tick.
InvertedLog10Transform
(shorthand_name=None)¶Bases: matplotlib.scale.InvertedLogTransformBase
Creates a new TransformNode
.
Parameters: | shorthand_name : str
|
---|
base
= 10.0¶inverted
()¶InvertedLog2Transform
(shorthand_name=None)¶Bases: matplotlib.scale.InvertedLogTransformBase
Creates a new TransformNode
.
Parameters: | shorthand_name : str
|
---|
base
= 2.0¶inverted
()¶InvertedLogTransform
(base)¶Bases: matplotlib.scale.InvertedLogTransformBase
inverted
()¶InvertedNaturalLogTransform
(shorthand_name=None)¶Bases: matplotlib.scale.InvertedLogTransformBase
Creates a new TransformNode
.
Parameters: | shorthand_name : str
|
---|
base
= 2.718281828459045¶inverted
()¶Log10Transform
(nonpos=u'clip')¶Bases: matplotlib.scale.LogTransformBase
base
= 10.0¶inverted
()¶Log2Transform
(nonpos=u'clip')¶Bases: matplotlib.scale.LogTransformBase
base
= 2.0¶inverted
()¶LogTransform
(base, nonpos=u'clip')¶Bases: matplotlib.scale.LogTransformBase
inverted
()¶LogTransformBase
(nonpos=u'clip')¶Bases: matplotlib.transforms.Transform
has_inverse
= True¶input_dims
= 1¶is_separable
= True¶output_dims
= 1¶transform_non_affine
(a)¶NaturalLogTransform
(nonpos=u'clip')¶Bases: matplotlib.scale.LogTransformBase
base
= 2.718281828459045¶inverted
()¶name
= u'log'¶matplotlib.scale.
LogTransformBase
(nonpos=u'clip')[source]¶Bases: matplotlib.transforms.Transform
has_inverse
= True¶input_dims
= 1¶is_separable
= True¶output_dims
= 1¶matplotlib.scale.
LogisticTransform
(nonpos=u'mask')[source]¶Bases: matplotlib.transforms.Transform
has_inverse
= True¶input_dims
= 1¶is_separable
= True¶output_dims
= 1¶matplotlib.scale.
LogitScale
(axis, nonpos=u'mask')[source]¶Bases: matplotlib.scale.ScaleBase
Logit scale for data between zero and one, both excluded.
This scale is similar to a log scale close to zero and to one, and almost linear around 0.5. It maps the interval ]0, 1[ onto ]-infty, +infty[.
get_transform
()[source]¶Return a LogitTransform
instance.
limit_range_for_scale
(vmin, vmax, minpos)[source]¶Limit the domain to values between 0 and 1 (excluded).
name
= u'logit'¶matplotlib.scale.
LogitTransform
(nonpos=u'mask')[source]¶Bases: matplotlib.transforms.Transform
has_inverse
= True¶input_dims
= 1¶is_separable
= True¶output_dims
= 1¶matplotlib.scale.
NaturalLogTransform
(nonpos=u'clip')[source]¶Bases: matplotlib.scale.LogTransformBase
base
= 2.718281828459045¶matplotlib.scale.
ScaleBase
[source]¶Bases: object
The base class for all scales.
Scales are separable transformations, working on a single dimension.
Any subclasses will want to override:
matplotlib.scale.
SymmetricalLogScale
(axis, **kwargs)[source]¶Bases: matplotlib.scale.ScaleBase
The symmetrical logarithmic scale is logarithmic in both the positive and negative directions from the origin.
Since the values close to zero tend toward infinity, there is a need to have a range around zero that is linear. The parameter linthresh allows the user to specify the size of this range (-linthresh, linthresh).
Where to place the subticks between each major tick.
Should be a sequence of integers. For example, in a log10
scale: [2, 3, 4, 5, 6, 7, 8, 9]
will place 8 logarithmically spaced minor ticks between each major tick.
InvertedSymmetricalLogTransform
(base, linthresh, linscale)¶Bases: matplotlib.transforms.Transform
has_inverse
= True¶input_dims
= 1¶inverted
()¶is_separable
= True¶output_dims
= 1¶transform_non_affine
(a)¶SymmetricalLogTransform
(base, linthresh, linscale)¶Bases: matplotlib.transforms.Transform
has_inverse
= True¶input_dims
= 1¶inverted
()¶is_separable
= True¶output_dims
= 1¶transform_non_affine
(a)¶get_transform
()[source]¶Return a SymmetricalLogTransform
instance.
name
= u'symlog'¶matplotlib.scale.
SymmetricalLogTransform
(base, linthresh, linscale)[source]¶Bases: matplotlib.transforms.Transform
has_inverse
= True¶input_dims
= 1¶is_separable
= True¶output_dims
= 1¶matplotlib.scale.
get_scale_docs
()[source]¶Helper function for generating docstrings related to scales.