matplotlib.scale
¶matplotlib.scale.
FuncScale
(axis, functions)[source]¶Bases: matplotlib.scale.ScaleBase
Provide an arbitrary scale with user-supplied function for the axis.
Parameters: |
|
---|
name
= 'function'¶matplotlib.scale.
FuncScaleLog
(axis, functions, base=10)[source]¶Bases: matplotlib.scale.LogScale
Provide an arbitrary scale with user-supplied function for the axis and then put on a logarithmic axes.
Parameters: |
|
---|
base
¶name
= 'functionlog'¶matplotlib.scale.
FuncTransform
(forward, inverse)[source]¶Bases: matplotlib.transforms.Transform
A simple transform that takes and arbitrary function for the forward and inverse transform.
Parameters: |
|
---|
has_inverse
= True¶input_dims
= 1¶inverted
(self)[source]¶Return the corresponding inverse transformation.
The return value of this method should be treated as temporary. An update to self does not cause a corresponding update to its inverted copy.
x === self.inverted().transform(self.transform(x))
is_separable
= True¶output_dims
= 1¶transform_non_affine
(self, values)[source]¶Performs only the non-affine part of the transformation.
transform(values)
is always equivalent to
transform_affine(transform_non_affine(values))
.
In non-affine transformations, this is generally equivalent to
transform(values)
. In affine transformations, this is
always a no-op.
Accepts a numpy array of shape (N x input_dims
) and
returns a numpy array of shape (N x output_dims
).
Alternatively, accepts a numpy array of length input_dims
and returns a numpy array of length output_dims
.
matplotlib.scale.
InvertedLog10Transform
(**kwargs)[source]¶Bases: matplotlib.scale.InvertedLogTransformBase
[Deprecated]
Notes
Deprecated since version 3.1:
base
= 10.0¶matplotlib.scale.
InvertedLog2Transform
(**kwargs)[source]¶Bases: matplotlib.scale.InvertedLogTransformBase
[Deprecated]
Notes
Deprecated since version 3.1:
base
= 2.0¶matplotlib.scale.
InvertedLogTransform
(base)[source]¶Bases: matplotlib.scale.InvertedLogTransformBase
has_inverse
= True¶input_dims
= 1¶inverted
(self)[source]¶Return the corresponding inverse transformation.
The return value of this method should be treated as temporary. An update to self does not cause a corresponding update to its inverted copy.
x === self.inverted().transform(self.transform(x))
is_separable
= True¶output_dims
= 1¶transform_non_affine
(self, a)[source]¶Performs only the non-affine part of the transformation.
transform(values)
is always equivalent to
transform_affine(transform_non_affine(values))
.
In non-affine transformations, this is generally equivalent to
transform(values)
. In affine transformations, this is
always a no-op.
Accepts a numpy array of shape (N x input_dims
) and
returns a numpy array of shape (N x output_dims
).
Alternatively, accepts a numpy array of length input_dims
and returns a numpy array of length output_dims
.
matplotlib.scale.
InvertedLogTransformBase
(**kwargs)[source]¶Bases: matplotlib.transforms.Transform
[Deprecated]
Notes
Deprecated since version 3.1:
has_inverse
= True¶input_dims
= 1¶is_separable
= True¶output_dims
= 1¶transform_non_affine
(self, a)[source]¶Performs only the non-affine part of the transformation.
transform(values)
is always equivalent to
transform_affine(transform_non_affine(values))
.
In non-affine transformations, this is generally equivalent to
transform(values)
. In affine transformations, this is
always a no-op.
Accepts a numpy array of shape (N x input_dims
) and
returns a numpy array of shape (N x output_dims
).
Alternatively, accepts a numpy array of length input_dims
and returns a numpy array of length output_dims
.
matplotlib.scale.
InvertedNaturalLogTransform
(**kwargs)[source]¶Bases: matplotlib.scale.InvertedLogTransformBase
[Deprecated]
Notes
Deprecated since version 3.1:
base
= 2.718281828459045¶matplotlib.scale.
InvertedSymmetricalLogTransform
(base, linthresh, linscale)[source]¶Bases: matplotlib.transforms.Transform
has_inverse
= True¶input_dims
= 1¶inverted
(self)[source]¶Return the corresponding inverse transformation.
The return value of this method should be treated as temporary. An update to self does not cause a corresponding update to its inverted copy.
x === self.inverted().transform(self.transform(x))
is_separable
= True¶output_dims
= 1¶transform_non_affine
(self, a)[source]¶Performs only the non-affine part of the transformation.
transform(values)
is always equivalent to
transform_affine(transform_non_affine(values))
.
In non-affine transformations, this is generally equivalent to
transform(values)
. In affine transformations, this is
always a no-op.
Accepts a numpy array of shape (N x input_dims
) and
returns a numpy array of shape (N x output_dims
).
Alternatively, accepts a numpy array of length input_dims
and returns a numpy array of length output_dims
.
matplotlib.scale.
LinearScale
(axis, **kwargs)[source]¶Bases: matplotlib.scale.ScaleBase
The default linear scale.
get_transform
(self)[source]¶The transform for linear scaling is just the
IdentityTransform
.
name
= 'linear'¶matplotlib.scale.
Log10Transform
(**kwargs)[source]¶Bases: matplotlib.scale.LogTransformBase
[Deprecated]
Notes
Deprecated since version 3.1:
base
= 10.0¶matplotlib.scale.
Log2Transform
(**kwargs)[source]¶Bases: matplotlib.scale.LogTransformBase
[Deprecated]
Notes
Deprecated since version 3.1:
base
= 2.0¶matplotlib.scale.
LogScale
(axis, **kwargs)[source]¶Bases: matplotlib.scale.ScaleBase
A standard logarithmic scale. Care is taken to only plot positive values.
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
(**kwargs)¶Bases: matplotlib.scale.InvertedLogTransformBase
[Deprecated]
Notes
Deprecated since version 3.1:
base
= 10.0¶inverted
(self)¶Return the corresponding inverse transformation.
The return value of this method should be treated as temporary. An update to self does not cause a corresponding update to its inverted copy.
x === self.inverted().transform(self.transform(x))
InvertedLog2Transform
(**kwargs)¶Bases: matplotlib.scale.InvertedLogTransformBase
[Deprecated]
Notes
Deprecated since version 3.1:
base
= 2.0¶inverted
(self)¶Return the corresponding inverse transformation.
The return value of this method should be treated as temporary. An update to self does not cause a corresponding update to its inverted copy.
x === self.inverted().transform(self.transform(x))
InvertedLogTransform
(base)¶Bases: matplotlib.scale.InvertedLogTransformBase
has_inverse
= True¶input_dims
= 1¶inverted
(self)¶Return the corresponding inverse transformation.
The return value of this method should be treated as temporary. An update to self does not cause a corresponding update to its inverted copy.
x === self.inverted().transform(self.transform(x))
is_separable
= True¶output_dims
= 1¶transform_non_affine
(self, a)¶Performs only the non-affine part of the transformation.
transform(values)
is always equivalent to
transform_affine(transform_non_affine(values))
.
In non-affine transformations, this is generally equivalent to
transform(values)
. In affine transformations, this is
always a no-op.
Accepts a numpy array of shape (N x input_dims
) and
returns a numpy array of shape (N x output_dims
).
Alternatively, accepts a numpy array of length input_dims
and returns a numpy array of length output_dims
.
InvertedNaturalLogTransform
(**kwargs)¶Bases: matplotlib.scale.InvertedLogTransformBase
[Deprecated]
Notes
Deprecated since version 3.1:
base
= 2.718281828459045¶inverted
(self)¶Return the corresponding inverse transformation.
The return value of this method should be treated as temporary. An update to self does not cause a corresponding update to its inverted copy.
x === self.inverted().transform(self.transform(x))
Log10Transform
(**kwargs)¶Bases: matplotlib.scale.LogTransformBase
[Deprecated]
Notes
Deprecated since version 3.1:
base
= 10.0¶inverted
(self)¶Return the corresponding inverse transformation.
The return value of this method should be treated as temporary. An update to self does not cause a corresponding update to its inverted copy.
x === self.inverted().transform(self.transform(x))
Log2Transform
(**kwargs)¶Bases: matplotlib.scale.LogTransformBase
[Deprecated]
Notes
Deprecated since version 3.1:
base
= 2.0¶inverted
(self)¶Return the corresponding inverse transformation.
The return value of this method should be treated as temporary. An update to self does not cause a corresponding update to its inverted copy.
x === self.inverted().transform(self.transform(x))
LogTransform
(base, nonpos='clip')¶Bases: matplotlib.transforms.Transform
has_inverse
= True¶input_dims
= 1¶inverted
(self)¶Return the corresponding inverse transformation.
The return value of this method should be treated as temporary. An update to self does not cause a corresponding update to its inverted copy.
x === self.inverted().transform(self.transform(x))
is_separable
= True¶output_dims
= 1¶transform_non_affine
(self, a)¶Performs only the non-affine part of the transformation.
transform(values)
is always equivalent to
transform_affine(transform_non_affine(values))
.
In non-affine transformations, this is generally equivalent to
transform(values)
. In affine transformations, this is
always a no-op.
Accepts a numpy array of shape (N x input_dims
) and
returns a numpy array of shape (N x output_dims
).
Alternatively, accepts a numpy array of length input_dims
and returns a numpy array of length output_dims
.
LogTransformBase
(**kwargs)¶Bases: matplotlib.transforms.Transform
[Deprecated]
Notes
Deprecated since version 3.1:
has_inverse
= True¶input_dims
= 1¶is_separable
= True¶output_dims
= 1¶transform_non_affine
(self, a)¶Performs only the non-affine part of the transformation.
transform(values)
is always equivalent to
transform_affine(transform_non_affine(values))
.
In non-affine transformations, this is generally equivalent to
transform(values)
. In affine transformations, this is
always a no-op.
Accepts a numpy array of shape (N x input_dims
) and
returns a numpy array of shape (N x output_dims
).
Alternatively, accepts a numpy array of length input_dims
and returns a numpy array of length output_dims
.
NaturalLogTransform
(**kwargs)¶Bases: matplotlib.scale.LogTransformBase
[Deprecated]
Notes
Deprecated since version 3.1:
base
= 2.718281828459045¶inverted
(self)¶Return the corresponding inverse transformation.
The return value of this method should be treated as temporary. An update to self does not cause a corresponding update to its inverted copy.
x === self.inverted().transform(self.transform(x))
base
¶name
= 'log'¶matplotlib.scale.
LogTransform
(base, nonpos='clip')[source]¶Bases: matplotlib.transforms.Transform
has_inverse
= True¶input_dims
= 1¶inverted
(self)[source]¶Return the corresponding inverse transformation.
The return value of this method should be treated as temporary. An update to self does not cause a corresponding update to its inverted copy.
x === self.inverted().transform(self.transform(x))
is_separable
= True¶output_dims
= 1¶transform_non_affine
(self, a)[source]¶Performs only the non-affine part of the transformation.
transform(values)
is always equivalent to
transform_affine(transform_non_affine(values))
.
In non-affine transformations, this is generally equivalent to
transform(values)
. In affine transformations, this is
always a no-op.
Accepts a numpy array of shape (N x input_dims
) and
returns a numpy array of shape (N x output_dims
).
Alternatively, accepts a numpy array of length input_dims
and returns a numpy array of length output_dims
.
matplotlib.scale.
LogTransformBase
(**kwargs)[source]¶Bases: matplotlib.transforms.Transform
[Deprecated]
Notes
Deprecated since version 3.1:
has_inverse
= True¶input_dims
= 1¶is_separable
= True¶output_dims
= 1¶transform_non_affine
(self, a)[source]¶Performs only the non-affine part of the transformation.
transform(values)
is always equivalent to
transform_affine(transform_non_affine(values))
.
In non-affine transformations, this is generally equivalent to
transform(values)
. In affine transformations, this is
always a no-op.
Accepts a numpy array of shape (N x input_dims
) and
returns a numpy array of shape (N x output_dims
).
Alternatively, accepts a numpy array of length input_dims
and returns a numpy array of length output_dims
.
matplotlib.scale.
LogisticTransform
(nonpos='mask')[source]¶Bases: matplotlib.transforms.Transform
has_inverse
= True¶input_dims
= 1¶inverted
(self)[source]¶Return the corresponding inverse transformation.
The return value of this method should be treated as temporary. An update to self does not cause a corresponding update to its inverted copy.
x === self.inverted().transform(self.transform(x))
is_separable
= True¶output_dims
= 1¶matplotlib.scale.
LogitScale
(axis, nonpos='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
(self)[source]¶Return a LogitTransform
instance.
limit_range_for_scale
(self, vmin, vmax, minpos)[source]¶Limit the domain to values between 0 and 1 (excluded).
name
= 'logit'¶matplotlib.scale.
LogitTransform
(nonpos='mask')[source]¶Bases: matplotlib.transforms.Transform
has_inverse
= True¶input_dims
= 1¶inverted
(self)[source]¶Return the corresponding inverse transformation.
The return value of this method should be treated as temporary. An update to self does not cause a corresponding update to its inverted copy.
x === self.inverted().transform(self.transform(x))
is_separable
= True¶output_dims
= 1¶matplotlib.scale.
NaturalLogTransform
(**kwargs)[source]¶Bases: matplotlib.scale.LogTransformBase
[Deprecated]
Notes
Deprecated since version 3.1:
base
= 2.718281828459045¶matplotlib.scale.
ScaleBase
(axis, **kwargs)[source]¶Bases: object
The base class for all scales.
Scales are separable transformations, working on a single dimension.
Any subclasses will want to override:
Construct a new scale.
Notes
The following note is for scale implementors.
For back-compatibility reasons, scales take an Axis
object as first argument. However, this argument should not
be used: a single scale object should be usable by multiple
Axis
es at the same time.
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).
Parameters: |
|
---|
InvertedSymmetricalLogTransform
(base, linthresh, linscale)¶Bases: matplotlib.transforms.Transform
has_inverse
= True¶input_dims
= 1¶inverted
(self)¶Return the corresponding inverse transformation.
The return value of this method should be treated as temporary. An update to self does not cause a corresponding update to its inverted copy.
x === self.inverted().transform(self.transform(x))
is_separable
= True¶output_dims
= 1¶transform_non_affine
(self, a)¶Performs only the non-affine part of the transformation.
transform(values)
is always equivalent to
transform_affine(transform_non_affine(values))
.
In non-affine transformations, this is generally equivalent to
transform(values)
. In affine transformations, this is
always a no-op.
Accepts a numpy array of shape (N x input_dims
) and
returns a numpy array of shape (N x output_dims
).
Alternatively, accepts a numpy array of length input_dims
and returns a numpy array of length output_dims
.
SymmetricalLogTransform
(base, linthresh, linscale)¶Bases: matplotlib.transforms.Transform
has_inverse
= True¶input_dims
= 1¶inverted
(self)¶Return the corresponding inverse transformation.
The return value of this method should be treated as temporary. An update to self does not cause a corresponding update to its inverted copy.
x === self.inverted().transform(self.transform(x))
is_separable
= True¶output_dims
= 1¶transform_non_affine
(self, a)¶Performs only the non-affine part of the transformation.
transform(values)
is always equivalent to
transform_affine(transform_non_affine(values))
.
In non-affine transformations, this is generally equivalent to
transform(values)
. In affine transformations, this is
always a no-op.
Accepts a numpy array of shape (N x input_dims
) and
returns a numpy array of shape (N x output_dims
).
Alternatively, accepts a numpy array of length input_dims
and returns a numpy array of length output_dims
.
get_transform
(self)[source]¶Return a SymmetricalLogTransform
instance.
name
= 'symlog'¶matplotlib.scale.
SymmetricalLogTransform
(base, linthresh, linscale)[source]¶Bases: matplotlib.transforms.Transform
has_inverse
= True¶input_dims
= 1¶inverted
(self)[source]¶Return the corresponding inverse transformation.
The return value of this method should be treated as temporary. An update to self does not cause a corresponding update to its inverted copy.
x === self.inverted().transform(self.transform(x))
is_separable
= True¶output_dims
= 1¶transform_non_affine
(self, a)[source]¶Performs only the non-affine part of the transformation.
transform(values)
is always equivalent to
transform_affine(transform_non_affine(values))
.
In non-affine transformations, this is generally equivalent to
transform(values)
. In affine transformations, this is
always a no-op.
Accepts a numpy array of shape (N x input_dims
) and
returns a numpy array of shape (N x output_dims
).
Alternatively, accepts a numpy array of length input_dims
and returns a numpy array of length output_dims
.
matplotlib.scale.
get_scale_docs
()[source]¶[Deprecated] Helper function for generating docstrings related to scales.
Notes
Deprecated since version 3.1: get_scale_docs() is considered private API since 3.1 and will be removed from the public API in 3.3.