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aspecd.annotation module

Annotations of data, e.g. characteristics, that cannot be automated.

Annotations of data (and plots, i.e. graphical representations of data) are eventually something that cannot be automated. Nevertheless, they can be quite important for the analysis and hence for providing new scientific insight. Furthermore, annotations of data can sometimes be added to a graphical representation. A typical example would be to mark an artefact with an asterisk or to highlight a characteristic. Therefore, dataset annotations may have graphical realisations as plot annotations.

Dataset annotations

All dataset annotations inherit from the aspecd.annotation.DatasetAnnotation base class.

Concrete dataset annotations are:

• aspecd.annotation.Comment

  The simplest form of an annotation is a comment applying to an entire dataset, such as comments stored in the metadata written during data acquisition. Hence, those comments do not belong to the metadata part of a dataset, but are stored as an annotation using this class.

Other frequent types of annotations are artefacts and characteristics, for which dedicated classes are available within the ASpecD framework:

• aspecd.annotation.Artefact

• aspecd.annotation.Characteristic.

Todo

Flesh out these additional DatasetAnnotation classes, particularly in light of the newly created PlotAnnotation classes that may eventually be a way to graphically display the dataset annotations.

For other types of annotations, simply subclass the aspecd.annotation.DatasetAnnotation base class.

Plot(ter) annotations

Similar to datasets, plots, i.e. graphical representations of the data of one or multiple datasets, can be annotated as well. Plot annotations will always result in a graphical object of some kind added to the plot created by a aspecd.plotting.Plotter. Additionally, each plotter has a list of annotations attached to it. As such, plot annotations are independent of individual datasets and can span multiple datasets in case of plotters involving the data of multiple datasets.

While generally, it should not matter whether a plot annotation gets added to the plotter object before or after the actual plotting process, adding the graphical elements annotations consist eventually of to the plot is only possible once the aspecd.plotting.Plotter.plot() method has been called and the respective aspecd.plotting.Plotter.figure and aspecd.plotting.Plotter.axes attributes are set. To this end, a plot annotation will only actually add graphical elements if the plot exists already, and the plotter will in turn add any annotations added prior to plotting when its aspecd.plotting.Plotter.plot() method is called. This avoids side effects, as annotating a plotter does not create a graphical representation that did not exist before.

All plot annotations inherit from the aspecd.annotation.PlotAnnotation base class.

Concrete plot annotations are:

• aspecd.annotation.VerticalLine

  Add vertical line(s) to a plot(ter).

• aspecd.annotation.HorizontalLine

  Add horizontal line(s) to a plot(ter).

• aspecd.annotation.VerticalSpan

  Add vertical span(s) (rectangles) to a plot(ter).

• aspecd.annotation.HorizontalSpan

  Add horizontal span(s) (rectangles) to a plot(ter).

• aspecd.annotation.Text

  Add text(s) to a plot(ter).

• aspecd.annotation.TextWithLine

  Add text(s) with a connecting line to a plot(ter).

• aspecd.annotation.Marker

  Add marker(s) to a plot(ter).

• aspecd.annotation.FillBetween

  Coloured surface under a curve or between curves.

Module documentation

class aspecd.annotation.DatasetAnnotation

Bases: ToDictMixin

Annotations are user-supplied additional information to datasets.

Whereas many processing steps of data can be fully automated, annotations are mostly the domain of human interaction, looking at the data of a dataset and providing some sort of comments, trying to make sense of the data.

Annotations can have different types, such as simple “comments”, e.g. saying that a dataset is not useful as something during measurement went wrong, they can highlight “characteristics” of the data, they can point to “artefacts”. Each of these types is represented by a class on its own that is derived from the DatasetAnnotation base class. Additionally, the type is reflected in the “type” property that gets set automatically to the class name in lower-case letters.

Each annotation has a scope (such as “point”, “slice”, “area”, “distance”, “dataset”) it belongs to, and a “contents” property (dict) containing the actual content of the annotation.

type

Textual description of the type of annotation: lowercase class name

Set automatically, don’t change

Type:

str

content

Actual content of the annotation

Generic place for more information

Type:

dict

dataset

Dataset the annotation belongs to

Type:

aspecd.dataset.Dataset

Raises:

• aspecd.annotation.NoContentError – Raised when annotation contains no content(s)

• aspecd.annotation.MissingDatasetError – Raised when no dataset exists to act on

property scope

Get or set the scope the annotation applies to.

The list of allowed scopes is stored in the private property _allowed_scopes, and if no scope is set when the annotation is finally applied to a dataset, a default scope will be used that is stored in the private property _default_scope (and is defined as one element of the list of allowed scopes)

Currently, allowed scopes are: dataset, slice, point, area, distance.

annotate(dataset=None, from_dataset=False)

Annotate a dataset with the given annotation.

If no dataset is provided at method call, but is set as property in the Annotation object, the aspecd.dataset.Dataset.annotate() method of the dataset will be called and thus the history written.

If no dataset is provided at method call nor as property in the object, the method will raise a respective exception.

If no scope is set in the aspecd.annotation.Annotation object, a default value will be used that can be set in derived classes in the private property _default_scope. A full list of scopes is contained in the private property _allowed_scopes. See the scope property for details.

The aspecd.dataset.Dataset object always calls this method with the respective dataset as argument. Therefore, in this case setting the dataset property within the Annotation object is not necessary.

Parameters:

• dataset (aspecd.dataset.Dataset) – dataset to annotate

• from_dataset (bool) –

  whether we are called from within a dataset

  Defaults to “False” and shall never be set manually.

Returns:

dataset – dataset that has been annotated

Return type:

aspecd.dataset.Dataset

create_history_record()

Create history record to be added to the dataset.

Usually, this method gets called from within the aspecd.dataset.Dataset.annotate() method of the aspecd.dataset.Dataset class and ensures the history of each annotation step to get written properly.

Returns:

history_record – history record for annotation step

Return type:

aspecd.history.AnnotationHistoryRecord

to_dict(remove_empty=False)

Create dictionary containing public attributes of an object.

Parameters:

remove_empty (bool) –

Whether to remove keys with empty values

Default: False

Returns:

public_attributes – Ordered dictionary containing the public attributes of the object

The order of attribute definition is preserved

Return type:

collections.OrderedDict

Changed in version 0.6: New parameter remove_empty

Changed in version 0.9: Settings for properties to exclude and include are not traversed

Changed in version 0.9.1: Dictionaries get copied before traversing, as otherwise, the special variables __dict__ and __0dict__ are modified, what may result in strange behaviour.

Changed in version 0.9.2: Dictionaries do not get copied by default, but there is a private method that can be overridden in derived classes to copy the dictionary.

class aspecd.annotation.Comment

Bases: DatasetAnnotation

The most basic form of annotation: a simple textual comment.

property comment

Get comment of annotation.

Returns:

comment – Actual comment string

Return type:

str

annotate(dataset=None, from_dataset=False)

Annotate a dataset with the given annotation.

If no dataset is provided at method call, but is set as property in the Annotation object, the aspecd.dataset.Dataset.annotate() method of the dataset will be called and thus the history written.

If no dataset is provided at method call nor as property in the object, the method will raise a respective exception.

If no scope is set in the aspecd.annotation.Annotation object, a default value will be used that can be set in derived classes in the private property _default_scope. A full list of scopes is contained in the private property _allowed_scopes. See the scope property for details.

The aspecd.dataset.Dataset object always calls this method with the respective dataset as argument. Therefore, in this case setting the dataset property within the Annotation object is not necessary.

Parameters:

• dataset (aspecd.dataset.Dataset) – dataset to annotate

• from_dataset (bool) –

  whether we are called from within a dataset

  Defaults to “False” and shall never be set manually.

Returns:

dataset – dataset that has been annotated

Return type:

aspecd.dataset.Dataset

create_history_record()

Create history record to be added to the dataset.

Usually, this method gets called from within the aspecd.dataset.Dataset.annotate() method of the aspecd.dataset.Dataset class and ensures the history of each annotation step to get written properly.

Returns:

history_record – history record for annotation step

Return type:

aspecd.history.AnnotationHistoryRecord

property scope

Get or set the scope the annotation applies to.

The list of allowed scopes is stored in the private property _allowed_scopes, and if no scope is set when the annotation is finally applied to a dataset, a default scope will be used that is stored in the private property _default_scope (and is defined as one element of the list of allowed scopes)

Currently, allowed scopes are: dataset, slice, point, area, distance.

to_dict(remove_empty=False)

Create dictionary containing public attributes of an object.

Parameters:

remove_empty (bool) –

Whether to remove keys with empty values

Default: False

Returns:

public_attributes – Ordered dictionary containing the public attributes of the object

The order of attribute definition is preserved

Return type:

collections.OrderedDict

Changed in version 0.6: New parameter remove_empty

Changed in version 0.9: Settings for properties to exclude and include are not traversed

Changed in version 0.9.1: Dictionaries get copied before traversing, as otherwise, the special variables __dict__ and __0dict__ are modified, what may result in strange behaviour.

Changed in version 0.9.2: Dictionaries do not get copied by default, but there is a private method that can be overridden in derived classes to copy the dictionary.

class aspecd.annotation.Artefact

Bases: DatasetAnnotation

Mark something as an artefact.

annotate(dataset=None, from_dataset=False)

Annotate a dataset with the given annotation.

If no dataset is provided at method call, but is set as property in the Annotation object, the aspecd.dataset.Dataset.annotate() method of the dataset will be called and thus the history written.

If no dataset is provided at method call nor as property in the object, the method will raise a respective exception.

If no scope is set in the aspecd.annotation.Annotation object, a default value will be used that can be set in derived classes in the private property _default_scope. A full list of scopes is contained in the private property _allowed_scopes. See the scope property for details.

The aspecd.dataset.Dataset object always calls this method with the respective dataset as argument. Therefore, in this case setting the dataset property within the Annotation object is not necessary.

Parameters:

• dataset (aspecd.dataset.Dataset) – dataset to annotate

• from_dataset (bool) –

  whether we are called from within a dataset

  Defaults to “False” and shall never be set manually.

Returns:

dataset – dataset that has been annotated

Return type:

aspecd.dataset.Dataset

create_history_record()

Create history record to be added to the dataset.

Usually, this method gets called from within the aspecd.dataset.Dataset.annotate() method of the aspecd.dataset.Dataset class and ensures the history of each annotation step to get written properly.

Returns:

history_record – history record for annotation step

Return type:

aspecd.history.AnnotationHistoryRecord

property scope

Get or set the scope the annotation applies to.

The list of allowed scopes is stored in the private property _allowed_scopes, and if no scope is set when the annotation is finally applied to a dataset, a default scope will be used that is stored in the private property _default_scope (and is defined as one element of the list of allowed scopes)

Currently, allowed scopes are: dataset, slice, point, area, distance.

to_dict(remove_empty=False)

Create dictionary containing public attributes of an object.

Parameters:

remove_empty (bool) –

Whether to remove keys with empty values

Default: False

Returns:

public_attributes – Ordered dictionary containing the public attributes of the object

The order of attribute definition is preserved

Return type:

collections.OrderedDict

Changed in version 0.6: New parameter remove_empty

Changed in version 0.9: Settings for properties to exclude and include are not traversed

Changed in version 0.9.1: Dictionaries get copied before traversing, as otherwise, the special variables __dict__ and __0dict__ are modified, what may result in strange behaviour.

Changed in version 0.9.2: Dictionaries do not get copied by default, but there is a private method that can be overridden in derived classes to copy the dictionary.

class aspecd.annotation.Characteristic

Bases: DatasetAnnotation

Base class for characteristics.

annotate(dataset=None, from_dataset=False)

Annotate a dataset with the given annotation.

If no dataset is provided at method call, but is set as property in the Annotation object, the aspecd.dataset.Dataset.annotate() method of the dataset will be called and thus the history written.

If no dataset is provided at method call nor as property in the object, the method will raise a respective exception.

If no scope is set in the aspecd.annotation.Annotation object, a default value will be used that can be set in derived classes in the private property _default_scope. A full list of scopes is contained in the private property _allowed_scopes. See the scope property for details.

The aspecd.dataset.Dataset object always calls this method with the respective dataset as argument. Therefore, in this case setting the dataset property within the Annotation object is not necessary.

Parameters:

• dataset (aspecd.dataset.Dataset) – dataset to annotate

• from_dataset (bool) –

  whether we are called from within a dataset

  Defaults to “False” and shall never be set manually.

Returns:

dataset – dataset that has been annotated

Return type:

aspecd.dataset.Dataset

create_history_record()

Create history record to be added to the dataset.

Usually, this method gets called from within the aspecd.dataset.Dataset.annotate() method of the aspecd.dataset.Dataset class and ensures the history of each annotation step to get written properly.

Returns:

history_record – history record for annotation step

Return type:

aspecd.history.AnnotationHistoryRecord

property scope

Get or set the scope the annotation applies to.

The list of allowed scopes is stored in the private property _allowed_scopes, and if no scope is set when the annotation is finally applied to a dataset, a default scope will be used that is stored in the private property _default_scope (and is defined as one element of the list of allowed scopes)

Currently, allowed scopes are: dataset, slice, point, area, distance.

to_dict(remove_empty=False)

Create dictionary containing public attributes of an object.

Parameters:

remove_empty (bool) –

Whether to remove keys with empty values

Default: False

Returns:

public_attributes – Ordered dictionary containing the public attributes of the object

The order of attribute definition is preserved

Return type:

collections.OrderedDict

Changed in version 0.6: New parameter remove_empty

Changed in version 0.9: Settings for properties to exclude and include are not traversed

Changed in version 0.9.1: Dictionaries get copied before traversing, as otherwise, the special variables __dict__ and __0dict__ are modified, what may result in strange behaviour.

Changed in version 0.9.2: Dictionaries do not get copied by default, but there is a private method that can be overridden in derived classes to copy the dictionary.

class aspecd.annotation.PlotAnnotation

Bases: ToDictMixin

Base class for annotations for graphical representations (plots).

Whereas many processing steps of data can be fully automated, annotations are mostly the domain of human interaction, looking at the graphical representation of the data of a dataset and providing some sort of comments, trying to make sense of the data. Often, being able to add some kind of annotation to these graphical representations is both, tremendously helpful and required for further analysis.

Annotations can have different types, such as horizontal and vertical lines added to a plot for comparing different data.

Each of these types is represented by a class on its own that is derived from the PlotAnnotation base class. Additionally, the type is reflected in the “type” property that gets set automatically to the class name in lower-case letters.

While generally, it should not matter whether a plot annotation gets added to the plotter object before or after the actual plotting process, adding the graphical elements annotations consist eventually of to the plot is only possible once the aspecd.plotting.Plotter.plot() method has been called and the respective aspecd.plotting.Plotter.figure and aspecd.plotting.Plotter.axes attributes are set. To this end, a plot annotation will only actually add graphical elements if the plot exists already, and the plotter will in turn add any annotations added prior to plotting when its aspecd.plotting.Plotter.plot() method is called. This avoids side effects, as annotating a plotter does not create a graphical representation that did not exist before.

plotter

Plotter the annotation belongs to

Type:

aspecd.plotting.Plotter

type

Textual description of the type of annotation: lowercase class name

Set automatically, don’t change

Type:

str

parameters

All parameters necessary for the annotation, implicit and explicit

Type:

dict

properties

Properties of the annotation, defining its appearance

Type:

None

drawings

Actual graphical representations of the annotation within the plot

Type:

list

Examples

For examples of how such a report task may be included into a recipe, see below:

- kind: multiplot
  type: MultiPlotter1DStacked
  properties:
    filename: plot1Dstacked.pdf
  result: plot1Dstacked

- kind: plotannotation
  type: VerticalLine
  properties:
    parameters:
      positions: [35, 42]
    properties:
      color: green
      linewidth: 1
      linestyle: dotted
  plotter: plot1Dstacked

In this case, the plotter is defined first, and the annotation second. To refer to the plotter from within the plotannotation task, you need to set the result attribute in the plotting task and refer to it within the plotter attribute of the plotannotation task. Although defining the plotter before the annotation, the user still expects the annotation to be included in the file containing the actual plot, despite the fact that the figure has been saved (for the first time) before the annotation has been added.

Sometimes, it might be convenient to go the other way round and first define an annotation and afterwards add it to a plot(ter). This can be done as well:

- kind: plotannotation
  type: VerticalLine
  properties:
    parameters:
      positions:
        - 21
        - 42
    properties:
      color: green
      linewidth: 1
      linestyle: dotted
  result: vlines

- kind: multiplot
  type: MultiPlotter1DStacked
  properties:
    filename: plot1Dstacked.pdf
  annotations:
    - vlines

In this way, you can add the same annotation to several plots, and be sure that each annotation is handled as a separate object.

Suppose you have more than one plotter you want to apply an annotation to. In this case, the plotter property of the plotannotation task is a list rather than a string:

- kind: multiplot
  type: MultiPlotter1DStacked
  result: plot1

- kind: multiplot
  type: MultiPlotter1DStacked
  result: plot2

- kind: plotannotation
  type: VerticalLine
  properties:
    parameters:
      positions: [35, 42]
  plotter:
    - plot1
    - plot2

In this case, the annotation will be applied to both plots independently. Note that the example has been reduced to the key aspects. In a real situation, the two plotters will differ much more.

New in version 0.9.

annotate(plotter=None, from_plotter=False)

Annotate a plot(ter) with the given annotation.

If no plotter is provided at method call, but is set as property in the Annotation object, the aspecd.plotting.Plotter.annotate() method of the plotter will be called and thus the history written.

If no plotter is provided at method call nor as property in the object, the method will raise a respective exception.

Parameters:

• plotter (aspecd.plotting.Plotter) – Plot(ter) to annotate

• from_plotter (bool) –

  whether we are called from within a plotter

  Defaults to “False” and shall never be set manually.

Returns:

plotter – Plotter that has been annotated

Return type:

aspecd.plotting.Plotter

to_dict(remove_empty=False)

Create dictionary containing public attributes of an object.

Parameters:

remove_empty (bool) –

Whether to remove keys with empty values

Default: False

Returns:

public_attributes – Ordered dictionary containing the public attributes of the object

The order of attribute definition is preserved

Return type:

collections.OrderedDict

Changed in version 0.6: New parameter remove_empty

Changed in version 0.9: Settings for properties to exclude and include are not traversed

Changed in version 0.9.1: Dictionaries get copied before traversing, as otherwise, the special variables __dict__ and __0dict__ are modified, what may result in strange behaviour.

Changed in version 0.9.2: Dictionaries do not get copied by default, but there is a private method that can be overridden in derived classes to copy the dictionary.

class aspecd.annotation.VerticalLine

Bases: PlotAnnotation

Vertical line(s) added to a plot.

Vertical lines are often useful to compare peak positions or as a general guide to the eye of the observer.

The properties of the lines can be controlled in quite some detail using the properties property. Note that all lines will share the same properties. If you need to add lines with different properties to the same plot, use several VerticalLine objects and annotate separately.

parameters

All parameters necessary for the annotation, implicit and explicit

The following keys exist:

positionslist

List of the positions vertical lines should appear at

Values are in axis (data) units.

limitslist

Limits of the vertical lines

If not given, the vertical lines will span the entire range of the current axes.

Values are in relative units, within a range of [0, 1].

Type:

dict

properties

Properties of the line(s) within a plot

For the properties that can be set this way, see the documentation of the aspecd.plotting.LineProperties class.

Type:

aspecd.plotting.LineProperties

Examples

For convenience, a series of examples in recipe style (for details of the recipe-driven data analysis, see aspecd.tasks) is given below for how to make use of this class. The examples focus each on a single aspect.

Generally and for obvious reasons, you need to have both, a plot task and a plotannotation task. It does not really matter which task you define first, the plot or the plot annotation. There are only marginal differences, and both ways are shown below.

- kind: multiplot
  type: MultiPlotter1DStacked
  properties:
    filename: plot1Dstacked.pdf
  result: plot1Dstacked

- kind: plotannotation
  type: VerticalLine
  properties:
    parameters:
      positions: [35, 42]
    properties:
      color: green
      linewidth: 1
      linestyle: dotted
  plotter: plot1Dstacked

In this case, the plotter is defined first, and the annotation second. To refer to the plotter from within the plotannotation task, you need to set the result attribute in the plotting task and refer to it within the plotter attribute of the plotannotation task. Although defining the plotter before the annotation, the user still expects the annotation to be included in the file containing the actual plot, despite the fact that the figure has been saved (for the first time) before the annotation has been added.

Sometimes, it might be convenient to go the other way round and first define an annotation and afterwards add it to a plot(ter). This can be done as well:

- kind: plotannotation
  type: VerticalLine
  properties:
    parameters:
      positions:
        - 21
        - 42
    properties:
      color: green
      linewidth: 1
      linestyle: dotted
  result: vlines

- kind: multiplot
  type: MultiPlotter1DStacked
  properties:
    filename: plot1Dstacked.pdf
  annotations:
    - vlines

In this way, you can add the same annotation to several plots, and be sure that each annotation is handled as a separate object.

Suppose you have more than one plotter you want to apply an annotation to. In this case, the plotter property of the plotannotation task is a list rather than a string:

- kind: multiplot
  type: MultiPlotter1DStacked
  result: plot1

- kind: multiplot
  type: MultiPlotter1DStacked
  result: plot2

- kind: plotannotation
  type: VerticalLine
  properties:
    parameters:
      positions: [35, 42]
  plotter:
    - plot1
    - plot2

In this case, the annotation will be applied to both plots independently. Note that the example has been reduced to the key aspects. In a real situation, the two plotters will differ much more.

New in version 0.9.

annotate(plotter=None, from_plotter=False)

Annotate a plot(ter) with the given annotation.

If no plotter is provided at method call, but is set as property in the Annotation object, the aspecd.plotting.Plotter.annotate() method of the plotter will be called and thus the history written.

If no plotter is provided at method call nor as property in the object, the method will raise a respective exception.

Parameters:

• plotter (aspecd.plotting.Plotter) – Plot(ter) to annotate

• from_plotter (bool) –

  whether we are called from within a plotter

  Defaults to “False” and shall never be set manually.

Returns:

plotter – Plotter that has been annotated

Return type:

aspecd.plotting.Plotter

to_dict(remove_empty=False)

Create dictionary containing public attributes of an object.

Parameters:

remove_empty (bool) –

Whether to remove keys with empty values

Default: False

Returns:

public_attributes – Ordered dictionary containing the public attributes of the object

The order of attribute definition is preserved

Return type:

collections.OrderedDict

Changed in version 0.6: New parameter remove_empty

Changed in version 0.9: Settings for properties to exclude and include are not traversed

Changed in version 0.9.1: Dictionaries get copied before traversing, as otherwise, the special variables __dict__ and __0dict__ are modified, what may result in strange behaviour.

Changed in version 0.9.2: Dictionaries do not get copied by default, but there is a private method that can be overridden in derived classes to copy the dictionary.

class aspecd.annotation.HorizontalLine

Bases: PlotAnnotation

Horizontal line(s) added to a plot.

Horizontal lines are often useful to compare peak positions or as a general guide to the eye of the observer.

The properties of the lines can be controlled in quite some detail using the properties property. Note that all lines will share the same properties. If you need to add lines with different properties to the same plot, use several HorizontalLine objects and annotate separately.

parameters

All parameters necessary for the annotation, implicit and explicit

The following keys exist:

positionslist

List of the positions horizontal lines should appear at

Values are in axis (data) units.

limitslist

Limits of the horizontal lines

If not given, the horizontal lines will span the entire range of the current axes.

Values are in relative units, within a range of [0, 1].

Type:

dict

properties

Properties of the line(s) within a plot

For the properties that can be set this way, see the documentation of the aspecd.plotting.LineProperties class.

Type:

aspecd.plotting.LineProperties

Examples

For convenience, a series of examples in recipe style (for details of the recipe-driven data analysis, see aspecd.tasks) is given below for how to make use of this class. The examples focus each on a single aspect.

Generally and for obvious reasons, you need to have both, a plot task and a plotannotation task. It does not really matter which task you define first, the plot or the plot annotation. There are only marginal differences, and both ways are shown below.

- kind: multiplot
  type: MultiPlotter1DStacked
  properties:
    filename: plot1Dstacked.pdf
  result: plot1Dstacked

- kind: plotannotation
  type: HorizontalLine
  properties:
    parameters:
      positions: [35, 42]
    properties:
      color: green
      linewidth: 1
      linestyle: dotted
  plotter: plot1Dstacked

In this case, the plotter is defined first, and the annotation second. To refer to the plotter from within the plotannotation task, you need to set the result attribute in the plotting task and refer to it within the plotter attribute of the plotannotation task. Although defining the plotter before the annotation, the user still expects the annotation to be included in the file containing the actual plot, despite the fact that the figure has been saved (for the first time) before the annotation has been added.

Sometimes, it might be convenient to go the other way round and first define an annotation and afterwards add it to a plot(ter). This can be done as well:

- kind: plotannotation
  type: HorizontalLine
  properties:
    parameters:
      positions:
        - 21
        - 42
    properties:
      color: green
      linewidth: 1
      linestyle: dotted
  result: hlines

- kind: multiplot
  type: MultiPlotter1DStacked
  properties:
    filename: plot1Dstacked.pdf
  annotations:
    - hlines

In this way, you can add the same annotation to several plots, and be sure that each annotation is handled as a separate object.

Suppose you have more than one plotter you want to apply an annotation to. In this case, the plotter property of the plotannotation task is a list rather than a string:

- kind: multiplot
  type: MultiPlotter1DStacked
  result: plot1

- kind: multiplot
  type: MultiPlotter1DStacked
  result: plot2

- kind: plotannotation
  type: HorizontalLine
  properties:
    parameters:
      positions: [35, 42]
  plotter:
    - plot1
    - plot2

In this case, the annotation will be applied to both plots independently. Note that the example has been reduced to the key aspects. In a real situation, the two plotters will differ much more.

New in version 0.9.

annotate(plotter=None, from_plotter=False)

Annotate a plot(ter) with the given annotation.

If no plotter is provided at method call, but is set as property in the Annotation object, the aspecd.plotting.Plotter.annotate() method of the plotter will be called and thus the history written.

If no plotter is provided at method call nor as property in the object, the method will raise a respective exception.

Parameters:

• plotter (aspecd.plotting.Plotter) – Plot(ter) to annotate

• from_plotter (bool) –

  whether we are called from within a plotter

  Defaults to “False” and shall never be set manually.

Returns:

plotter – Plotter that has been annotated

Return type:

aspecd.plotting.Plotter

to_dict(remove_empty=False)

Create dictionary containing public attributes of an object.

Parameters:

remove_empty (bool) –

Whether to remove keys with empty values

Default: False

Returns:

public_attributes – Ordered dictionary containing the public attributes of the object

The order of attribute definition is preserved

Return type:

collections.OrderedDict

Changed in version 0.6: New parameter remove_empty

Changed in version 0.9: Settings for properties to exclude and include are not traversed

Changed in version 0.9.1: Dictionaries get copied before traversing, as otherwise, the special variables __dict__ and __0dict__ are modified, what may result in strange behaviour.

Changed in version 0.9.2: Dictionaries do not get copied by default, but there is a private method that can be overridden in derived classes to copy the dictionary.

class aspecd.annotation.Text

Bases: PlotAnnotation

Text added to a plot.

One of the most versatile ways to annotate a plot is adding text labels at defined positions. Basically, this class is the ASpecD wrapper to matplotlib.axes.Axes.text(). In short, you provide coordinates (x, y) for the location and a text label. By default, coordinates are data coordinates and specify the bottom left corner of the text.

The properties of the texts can be controlled in quite some detail using the properties property. Note that all texts will share the same properties. If you need to add texts with different properties to the same plot, use several Text objects and annotate separately.

parameters

All parameters necessary for the annotation, implicit and explicit

The following keys exist:

positionslist

List of the positions texts should appear at.

Note that each position is itself a list: [x, y]

Values are in axis (data) units.

xpositionslist

List of the x positions texts should appear at.

This allows to set x positions from the result of other tasks, e.g. a peak finding analysis step.

If xpositions is set, you need to set ypositions as well. However, you can set either a single element or even a scalar (not a list). In this case, the single y position is expanded to match the number of x positions, i.e., all texts will appear with the same y position.

If you provide both, positions and xpositions/ypositions, the latter couple wins.

Values are in axis (data) units.

ypositionslist or float

List of the y positions texts should appear at.

If xpositions is set, you need to set ypositions as well. However, you can set either a single element or even a scalar (not a list). In this case, the single y position is expanded to match the number of x positions, i.e., all texts will appear with the same y position.

If you provide both, positions and xpositions/ypositions, the latter couple wins.

Values are in axis (data) units.

textslist

Texts that should appear at the individual positions.

Each text is a str, obviously.

Type:

dict

properties

Properties of the text(s) within a plot

For the properties that can be set this way, see the documentation of the aspecd.plotting.TextProperties class.

Type:

aspecd.plotting.TextProperties

Examples

For convenience, a series of examples in recipe style (for details of the recipe-driven data analysis, see aspecd.tasks) is given below for how to make use of this class. The examples focus each on a single aspect.

Generally and for obvious reasons, you need to have both, a plot task and a plotannotation task. It does not really matter which task you define first, the plot or the plot annotation. There are only marginal differences, and both ways are shown below.

- kind: singleplot
  type: SinglePlotter1D
  properties:
    filename: plot1D.pdf
  result: plot1D

- kind: plotannotation
  type: Text
  properties:
    parameters:
      positions:
        - [0.5, 0.5]
        - [1.0, 0.5]
      texts:
        - "Lorem ipsum"
        - "dolor sit amet"
    properties:
      color: green
      fontsize: large
      fontstyle: oblique
      rotation: 30
  plotter: plot1D

In this case, the plotter is defined first, and the annotation second. To refer to the plotter from within the plotannotation task, you need to set the result attribute in the plotting task and refer to it within the plotter attribute of the plotannotation task. Although defining the plotter before the annotation, the user still expects the annotation to be included in the file containing the actual plot, despite the fact that the figure has been saved (for the first time) before the annotation has been added.

Sometimes, it might be convenient to go the other way round and first define an annotation and afterwards add it to a plot(ter). This can be done as well:

- kind: plotannotation
  type: Text
  properties:
    parameters:
      positions:
        - [0.5, 0.5]
        - [1.0, 0.5]
      texts:
        - "Lorem ipsum"
        - "dolor sit amet"
    properties:
      color: green
      fontsize: large
      fontstyle: oblique
      rotation: 30
  result: text

- kind: singleplot
  type: SinglePlotter1D
  properties:
    filename: plot1D.pdf
  annotations:
    - text

In this way, you can add the same annotation to several plots, and be sure that each annotation is handled as a separate object.

Suppose you have more than one plotter you want to apply an annotation to. In this case, the plotter property of the plotannotation task is a list rather than a string:

- kind: singleplot
  type: SinglePlotter1D
  result: plot1

- kind: singleplot
  type: SinglePlotter1D
  result: plot2

- kind: plotannotation
  type: Text
  properties:
    parameters:
      positions:
        - [0.5, 0.5]
        - [1.0, 0.5]
      texts:
        - "Lorem ipsum"
        - "dolor sit amet"
  plotter:
    - plot1
    - plot2

In this case, the annotation will be applied to both plots independently. Note that the example has been reduced to the key aspects. In a real situation, the two plotters will differ much more.

New in version 0.10.

annotate(plotter=None, from_plotter=False)

Annotate a plot(ter) with the given annotation.

If no plotter is provided at method call, but is set as property in the Annotation object, the aspecd.plotting.Plotter.annotate() method of the plotter will be called and thus the history written.

If no plotter is provided at method call nor as property in the object, the method will raise a respective exception.

Parameters:

• plotter (aspecd.plotting.Plotter) – Plot(ter) to annotate

• from_plotter (bool) –

  whether we are called from within a plotter

  Defaults to “False” and shall never be set manually.

Returns:

plotter – Plotter that has been annotated

Return type:

aspecd.plotting.Plotter

to_dict(remove_empty=False)

Create dictionary containing public attributes of an object.

Parameters:

remove_empty (bool) –

Whether to remove keys with empty values

Default: False

Returns:

public_attributes – Ordered dictionary containing the public attributes of the object

The order of attribute definition is preserved

Return type:

collections.OrderedDict

Changed in version 0.6: New parameter remove_empty

Changed in version 0.9: Settings for properties to exclude and include are not traversed

Changed in version 0.9.1: Dictionaries get copied before traversing, as otherwise, the special variables __dict__ and __0dict__ are modified, what may result in strange behaviour.

Changed in version 0.9.2: Dictionaries do not get copied by default, but there is a private method that can be overridden in derived classes to copy the dictionary.

class aspecd.annotation.VerticalSpan

Bases: PlotAnnotation

Vertical span(s) (rectangle) added to a plot.

Vertical spans are often useful to highlight areas of a plot, such as peaks.

The properties of the spans can be controlled in quite some detail using the properties property. Note that all spans will share the same properties. If you need to add spans with different properties to the same plot, use several VerticalSpan objects and annotate separately.

parameters

All parameters necessary for the annotation, implicit and explicit

The following keys exist:

positionslist

List of the positions vertical spans should appear at.

Each span needs two coordinates: [xmin, xmax].

If you want to have more than one span, provide a list of lists.

Values are in axis (data) units.

limitslist

Limits of the vertical spans

If not given, the vertical spans will span the entire range of the current axes.

Values are in relative units, within a range of [0, 1].

Type:

dict

properties

Properties of the span(s) within a plot

For the properties that can be set this way, see the documentation of the aspecd.plotting.PatchProperties class.

Type:

aspecd.plotting.PatchProperties

Examples

For convenience, a series of examples in recipe style (for details of the recipe-driven data analysis, see aspecd.tasks) is given below for how to make use of this class. The examples focus each on a single aspect.

Generally and for obvious reasons, you need to have both, a plot task and a plotannotation task. It does not really matter which task you define first, the plot or the plot annotation. There are only marginal differences, and both ways are shown below.

- kind: singleplot
  type: SinglePlotter1D
  properties:
    filename: plot1D.pdf
  result: plot1D

- kind: plotannotation
  type: VerticalSpan
  properties:
    parameters:
      positions: [[35, 42]]
    properties:
      edgecolor: Null
      facecolor: green
      alpha: 0.5
  plotter: plot1D

In this case, the plotter is defined first, and the annotation second. To refer to the plotter from within the plotannotation task, you need to set the result attribute in the plotting task and refer to it within the plotter attribute of the plotannotation task. Although defining the plotter before the annotation, the user still expects the annotation to be included in the file containing the actual plot, despite the fact that the figure has been saved (for the first time) before the annotation has been added.

Sometimes, it might be convenient to go the other way round and first define an annotation and afterwards add it to a plot(ter). This can be done as well:

- kind: plotannotation
  type: VerticalSpan
  properties:
    parameters:
      positions:
        - [35, 42]
        - [21, 24]
    properties:
      edgecolor: Null
      facecolor: green
      alpha: 0.5
  result: vspans

- kind: singleplot
  type: SinglePlotter1D
  properties:
    filename: plot1D.pdf
  annotations:
    - vspans

In this way, you can add the same annotation to several plots, and be sure that each annotation is handled as a separate object.

Suppose you have more than one plotter you want to apply an annotation to. In this case, the plotter property of the plotannotation task is a list rather than a string:

- kind: singleplot
  type: SinglePlotter1D
  result: plot1

- kind: singleplot
  type: SinglePlotter1D
  result: plot2

- kind: plotannotation
  type: VerticalSpan
  properties:
    parameters:
      positions:
        - [35, 42]
  plotter:
    - plot1
    - plot2

In this case, the annotation will be applied to both plots independently. Note that the example has been reduced to the key aspects. In a real situation, the two plotters will differ much more.

New in version 0.11.

annotate(plotter=None, from_plotter=False)

Annotate a plot(ter) with the given annotation.

If no plotter is provided at method call, but is set as property in the Annotation object, the aspecd.plotting.Plotter.annotate() method of the plotter will be called and thus the history written.

If no plotter is provided at method call nor as property in the object, the method will raise a respective exception.

Parameters:

• plotter (aspecd.plotting.Plotter) – Plot(ter) to annotate

• from_plotter (bool) –

  whether we are called from within a plotter

  Defaults to “False” and shall never be set manually.

Returns:

plotter – Plotter that has been annotated

Return type:

aspecd.plotting.Plotter

to_dict(remove_empty=False)

Create dictionary containing public attributes of an object.

Parameters:

remove_empty (bool) –

Whether to remove keys with empty values

Default: False

Returns:

public_attributes – Ordered dictionary containing the public attributes of the object

The order of attribute definition is preserved

Return type:

collections.OrderedDict

Changed in version 0.6: New parameter remove_empty

Changed in version 0.9: Settings for properties to exclude and include are not traversed

Changed in version 0.9.1: Dictionaries get copied before traversing, as otherwise, the special variables __dict__ and __0dict__ are modified, what may result in strange behaviour.

Changed in version 0.9.2: Dictionaries do not get copied by default, but there is a private method that can be overridden in derived classes to copy the dictionary.

class aspecd.annotation.HorizontalSpan

Bases: PlotAnnotation

Horizontal span(s) (rectangle) added to a plot.

Horizontal spans are often useful to highlight areas of a plot.

The properties of the spans can be controlled in quite some detail using the properties property. Note that all spans will share the same properties. If you need to add spans with different properties to the same plot, use several HorizontalSpan objects and annotate separately.

parameters

All parameters necessary for the annotation, implicit and explicit

The following keys exist:

positionslist

List of the positions hoizontal spans should appear at.

Each span needs two coordinates: [ymin, ymax].

If you want to have more than one span, provide a list of lists.

Values are in axis (data) units.

limitslist

Limits of the hoizontal spans

If not given, the hoizontal spans will span the entire range of the current axes.

Values are in relative units, within a range of [0, 1].

Type:

dict

properties

Properties of the span(s) within a plot

For the properties that can be set this way, see the documentation of the aspecd.plotting.PatchProperties class.

Type:

aspecd.plotting.PatchProperties

Examples

For convenience, a series of examples in recipe style (for details of the recipe-driven data analysis, see aspecd.tasks) is given below for how to make use of this class. The examples focus each on a single aspect.

Generally and for obvious reasons, you need to have both, a plot task and a plotannotation task. It does not really matter which task you define first, the plot or the plot annotation. There are only marginal differences, and both ways are shown below.

- kind: singleplot
  type: SinglePlotter1D
  properties:
    filename: plot1D.pdf
  result: plot1D

- kind: plotannotation
  type: HorizontalSpan
  properties:
    parameters:
      positions: [[35, 42]]
    properties:
      edgecolor: Null
      facecolor: green
      alpha: 0.5
  plotter: plot1D

In this case, the plotter is defined first, and the annotation second. To refer to the plotter from within the plotannotation task, you need to set the result attribute in the plotting task and refer to it within the plotter attribute of the plotannotation task. Although defining the plotter before the annotation, the user still expects the annotation to be included in the file containing the actual plot, despite the fact that the figure has been saved (for the first time) before the annotation has been added.

Sometimes, it might be convenient to go the other way round and first define an annotation and afterwards add it to a plot(ter). This can be done as well:

- kind: plotannotation
  type: HorizontalSpan
  properties:
    parameters:
      positions:
        - [35, 42]
        - [21, 24]
    properties:
      edgecolor: Null
      facecolor: green
      alpha: 0.5
  result: vspans

- kind: singleplot
  type: SinglePlotter1D
  properties:
    filename: plot1D.pdf
  annotations:
    - vspans

In this way, you can add the same annotation to several plots, and be sure that each annotation is handled as a separate object.

Suppose you have more than one plotter you want to apply an annotation to. In this case, the plotter property of the plotannotation task is a list rather than a string:

- kind: singleplot
  type: SinglePlotter1D
  result: plot1

- kind: singleplot
  type: SinglePlotter1D
  result: plot2

- kind: plotannotation
  type: HorizontalSpan
  properties:
    parameters:
      positions:
        - [35, 42]
  plotter:
    - plot1
    - plot2

In this case, the annotation will be applied to both plots independently. Note that the example has been reduced to the key aspects. In a real situation, the two plotters will differ much more.

New in version 0.11.

annotate(plotter=None, from_plotter=False)

Annotate a plot(ter) with the given annotation.

If no plotter is provided at method call, but is set as property in the Annotation object, the aspecd.plotting.Plotter.annotate() method of the plotter will be called and thus the history written.

If no plotter is provided at method call nor as property in the object, the method will raise a respective exception.

Parameters:

• plotter (aspecd.plotting.Plotter) – Plot(ter) to annotate

• from_plotter (bool) –

  whether we are called from within a plotter

  Defaults to “False” and shall never be set manually.

Returns:

plotter – Plotter that has been annotated

Return type:

aspecd.plotting.Plotter

to_dict(remove_empty=False)

Create dictionary containing public attributes of an object.

Parameters:

remove_empty (bool) –

Whether to remove keys with empty values

Default: False

Returns:

public_attributes – Ordered dictionary containing the public attributes of the object

The order of attribute definition is preserved

Return type:

collections.OrderedDict

Changed in version 0.6: New parameter remove_empty

Changed in version 0.9: Settings for properties to exclude and include are not traversed

Changed in version 0.9.1: Dictionaries get copied before traversing, as otherwise, the special variables __dict__ and __0dict__ are modified, what may result in strange behaviour.

Changed in version 0.9.2: Dictionaries do not get copied by default, but there is a private method that can be overridden in derived classes to copy the dictionary.

class aspecd.annotation.TextWithLine

Bases: PlotAnnotation

Text with connecting line added to a plot.

One of the most versatile ways to annotate a plot is adding text labels at defined positions. However, if you intend to annotate data points, sometimes it is helpful to have a connecting line between data point and text. This class uses matplotlib.axes.Axes.annotate() under the hood. Basically, you provide coordinates (x, y) for the location, an offset (dx, dy), and a text label. By default, coordinates are data coordinates.

Depending on the horizontal offset dx, the connecting line is either a straight line (dx = 0), or it has a 45° hook in the upper part to the left (dx < 0) or to the right (dx > 0). Similarly, if you set a negative vertical offset, the hook is obviously in the lower part.

In ASCII art, this may look like this:

foo  foo  foo            | | |
  \   |   /              | | |
   \  |  /               | | |
    | | |               /  |  \
    | | |              /   |   \
    | | |            foo  foo  foo

The properties of the texts and the connecting line can be controlled in quite some detail using the properties property. Note that all texts will share the same properties. If you need to add texts with different properties to the same plot, use several TextWithLine objects and annotate separately.

parameters

All parameters necessary for the annotation, implicit and explicit

The following keys exist:

positionslist

List of the positions the lines should point to.

Note that each position is itself a list: [x, y]

Values are in axis (data) units.

offsetslist

List of the offsets texts should appear at.

Note that each position is itself a list: [dx, dy]

Depending on the horizontal offset dx, the connecting line is either a straight line (dx = 0), or it has a 45° hook in the upper part to the left (dx < 0) or to the right (dx > 0). Similarly, if you set a negative vertical offset, the hook is obviously in the lower part.

Values are in axis (data) units.

xpositionslist

List of the x positions texts should appear at.

This allows to set x positions from the result of other tasks, e.g. a peak finding analysis step.

If xpositions is set, you need to set ypositions as well. However, you can set either a single element or even a scalar (not a list). In this case, the single y position is expanded to match the number of x positions, i.e., all texts will appear with the same y position.

If you provide both, positions and xpositions/ypositions, the latter couple wins.

Values are in axis (data) units.

ypositionslist or float

List of the y positions texts should appear at.

If xpositions is set, you need to set ypositions as well. However, you can set either a single element or even a scalar (not a list). In this case, the single y position is expanded to match the number of x positions, i.e., all texts will appear with the same y position.

If you provide both, positions and xpositions/ypositions, the latter couple wins.

Values are in axis (data) units.

textslist

Texts that should appear at the individual positions.

Each text is a str, obviously.

Type:

dict

properties

Properties of the text(s) and line(s) within a plot

For the properties that can be set this way, see the documentation of the aspecd.plotting.AnnotationProperties class.

Type:

aspecd.plotting.AnnotationProperties

Examples

For convenience, a series of examples in recipe style (for details of the recipe-driven data analysis, see aspecd.tasks) is given below for how to make use of this class. The examples focus each on a single aspect.

Generally and for obvious reasons, you need to have both, a plot task and a plotannotation task. It does not really matter which task you define first, the plot or the plot annotation. There are only marginal differences, and both ways are shown below.

- kind: singleplot
  type: SinglePlotter1D
  properties:
    filename: plot1D.pdf
  result: plot1D

- kind: plotannotation
  type: TextWithLine
  properties:
    parameters:
      positions:
        - [0.5, 0.5]
        - [0.55, 0.5]
      offsets:
        - [0.5, 2]
        - [0.8, 2]
      texts:
        - "Lorem ipsum"
        - "dolor sit amet"
    properties:
      text:
        color: green
        fontsize: large
        fontstyle: oblique
      line:
        linestyle: ":"
  plotter: plot1D

In this case, the plotter is defined first, and the annotation second. To refer to the plotter from within the plotannotation task, you need to set the result attribute in the plotting task and refer to it within the plotter attribute of the plotannotation task. Although defining the plotter before the annotation, the user still expects the annotation to be included in the file containing the actual plot, despite the fact that the figure has been saved (for the first time) before the annotation has been added.

Sometimes, it might be convenient to go the other way round and first define an annotation and afterwards add it to a plot(ter). This can be done as well:

- kind: plotannotation
  type: TextWithLine
  properties:
    parameters:
      positions:
        - [0.5, 0.5]
        - [0.55, 0.5]
      offsets:
        - [0.5, 2]
        - [0.8, 2]
      texts:
        - "Lorem ipsum"
        - "dolor sit amet"
    properties:
      text:
        color: green
        fontsize: large
        fontstyle: oblique
      line:
        linestyle: ":"
  result: text

- kind: singleplot
  type: SinglePlotter1D
  properties:
    filename: plot1D.pdf
  annotations:
    - text

In this way, you can add the same annotation to several plots, and be sure that each annotation is handled as a separate object.

Suppose you have more than one plotter you want to apply an annotation to. In this case, the plotter property of the plotannotation task is a list rather than a string:

- kind: singleplot
  type: SinglePlotter1D
  result: plot1

- kind: singleplot
  type: SinglePlotter1D
  result: plot2

- kind: plotannotation
  type: TextWithLine
  properties:
    parameters:
      positions:
        - [0.5, 0.5]
        - [0.55, 0.5]
      offsets:
        - [0.5, 2]
        - [0.8, 2]
      texts:
        - "Lorem ipsum"
        - "dolor sit amet"
  plotter:
    - plot1
    - plot2

In this case, the annotation will be applied to both plots independently. Note that the example has been reduced to the key aspects. In a real situation, the two plotters will differ much more.

New in version 0.11.

annotate(plotter=None, from_plotter=False)

Annotate a plot(ter) with the given annotation.

If no plotter is provided at method call, but is set as property in the Annotation object, the aspecd.plotting.Plotter.annotate() method of the plotter will be called and thus the history written.

If no plotter is provided at method call nor as property in the object, the method will raise a respective exception.

Parameters:

• plotter (aspecd.plotting.Plotter) – Plot(ter) to annotate

• from_plotter (bool) –

  whether we are called from within a plotter

  Defaults to “False” and shall never be set manually.

Returns:

plotter – Plotter that has been annotated

Return type:

aspecd.plotting.Plotter

to_dict(remove_empty=False)

Create dictionary containing public attributes of an object.

Parameters:

remove_empty (bool) –

Whether to remove keys with empty values

Default: False

Returns:

public_attributes – Ordered dictionary containing the public attributes of the object

The order of attribute definition is preserved

Return type:

collections.OrderedDict

Changed in version 0.6: New parameter remove_empty

Changed in version 0.9: Settings for properties to exclude and include are not traversed

Changed in version 0.9.1: Dictionaries get copied before traversing, as otherwise, the special variables __dict__ and __0dict__ are modified, what may result in strange behaviour.

Changed in version 0.9.2: Dictionaries do not get copied by default, but there is a private method that can be overridden in derived classes to copy the dictionary.

class aspecd.annotation.Marker

Bases: PlotAnnotation

Marker added to a plot.

One very common way to annotate a plot is adding markers at defined positions. Basically, this class is the ASpecD wrapper to matplotlib.axes.Axes.plot() with only a marker used and no line drawn. Basically, you provide coordinates (x, y) for the location and a marker. By default, coordinates are data coordinates and specify the centre of the marker.

The properties of the markers can be controlled in quite some detail using the properties property. Note that all markers will share the same properties. If you need to add markers with different properties to the same plot, use several Marker objects and annotate separately.

parameters

All parameters necessary for the annotation, implicit and explicit

The following keys exist:

positionslist

List of the positions markers should appear at.

Note that each position is itself a list: [x, y]

Values are in axis (data) units.

xpositionslist

List of the x positions markers should appear at.

This allows to set x positions from the result of other tasks, e.g. a peak finding analysis step.

If xpositions is set, you need to set ypositions as well. However, you can set either a single element or even a scalar (not a list). In this case, the single y position is expanded to match the number of x positions, i.e., all markers will appear with the same y position.

If you provide both, positions and xpositions/ypositions, the latter couple wins.

Values are in axis (data) units.

ypositionslist or float

List of the y positions markers should appear at.

If xpositions is set, you need to set ypositions as well. However, you can set either a single element or even a scalar (not a list). In this case, the single y position is expanded to match the number of x positions, i.e., all markers will appear with the same y position.

If you provide both, positions and xpositions/ypositions, the latter couple wins.

Values are in axis (data) units.

yoffsetfloat

Additional offset for the y direction added to the y position.

Useful, e.g., when you want to mark peaks, but not on the line itself, but slightly above (positive offset values) or below ( negative offset values).

Default: 0

markerstr

Marker that shall be added to the plot.

There is a large list of predefined markers available. For details, see matplotlib.markers. Note that you can use both, the code and the keyword of a specific marker, as returned by the matplotlib.lines.Line2D.markers attribute:

code	keyword
"."	point
","	pixel
"o"	circle
"v"	triangle_down
"^"	triangle_up
"<"	triangle_left
">"	triangle_right
"1"	tri_down
"2"	tri_up
"3"	tri_left
"4"	tri_right
"8"	octagon
"s"	square
"p"	pentagon
"*"	star
"h"	hexagon1
"H"	hexagon2
"+"	plus
"x"	x
"D"	diamond
"d"	thin_diamond
"|"	vline
"_"	hline
"P"	plus_filled
"X"	x_filled
0	tickleft
1	tickright
2	tickup
3	tickdown
4	caretleft
5	caretright
6	caretup
7	caretdown
8	caretleftbase
9	caretrightbase
10	caretupbase
11	caretdownbase

Please note the difference between the string "1" and the number 1 that result in triangle down and tick right markers, respectively.

Furthermore, you can use markers created from TeX symbols using MathText (LaTeX needs not to be installed). Just surround your marker with $ signs, such as "$\u266B$" or "$\mathcal{A}$".

If you provide multiple positions, the same marker will be added multiple times.

Type:

dict

properties

Properties of the marker(s) within a plot

For the properties that can be set this way, see the documentation of the aspecd.plotting.MarkerProperties class.

Type:

aspecd.plotting.MarkerProperties

Examples

For convenience, a series of examples in recipe style (for details of the recipe-driven data analysis, see aspecd.tasks) is given below for how to make use of this class. The examples focus each on a single aspect.

Generally and for obvious reasons, you need to have both, a plot task and a plotannotation task. It does not really matter which task you define first, the plot or the plot annotation. There are only marginal differences, and both ways are shown below.

- kind: singleplot
  type: SinglePlotter1D
  properties:
    filename: plot1D.pdf
  result: plot1D

- kind: plotannotation
  type: Marker
  properties:
    parameters:
      positions:
        - [0.5, 0.5]
        - [1.0, 0.5]
      marker: o
    properties:
      edgecolor: green
      size: 12
  plotter: plot1D

In this case, the plotter is defined first, and the annotation second. To refer to the plotter from within the plotannotation task, you need to set the result attribute in the plotting task and refer to it within the plotter attribute of the plotannotation task. Although defining the plotter before the annotation, the user still expects the annotation to be included in the file containing the actual plot, despite the fact that the figure has been saved (for the first time) before the annotation has been added.

Sometimes, it might be convenient to go the other way round and first define an annotation and afterwards add it to a plot(ter). This can be done as well:

- kind: plotannotation
  type: Marker
  properties:
    parameters:
      positions:
        - [0.5, 0.5]
        - [1.0, 0.5]
      marker: o
    properties:
      edgecolor: green
      size: 12
  result: text

- kind: singleplot
  type: SinglePlotter1D
  properties:
    filename: plot1D.pdf
  annotations:
    - text

In this way, you can add the same annotation to several plots, and be sure that each annotation is handled as a separate object.

Suppose you have more than one plotter you want to apply an annotation to. In this case, the plotter property of the plotannotation task is a list rather than a string:

- kind: singleplot
  type: SinglePlotter1D
  result: plot1

- kind: singleplot
  type: SinglePlotter1D
  result: plot2

- kind: plotannotation
  type: Marker
  properties:
    parameters:
      positions:
        - [0.5, 0.5]
        - [1.0, 0.5]
      marker: o
  plotter:
    - plot1
    - plot2

In this case, the annotation will be applied to both plots independently. Note that the example has been reduced to the key aspects. In a real situation, the two plotters will differ much more.

New in version 0.11.

annotate(plotter=None, from_plotter=False)

Annotate a plot(ter) with the given annotation.

If no plotter is provided at method call, but is set as property in the Annotation object, the aspecd.plotting.Plotter.annotate() method of the plotter will be called and thus the history written.

If no plotter is provided at method call nor as property in the object, the method will raise a respective exception.

Parameters:

• plotter (aspecd.plotting.Plotter) – Plot(ter) to annotate

• from_plotter (bool) –

  whether we are called from within a plotter

  Defaults to “False” and shall never be set manually.

Returns:

plotter – Plotter that has been annotated

Return type:

aspecd.plotting.Plotter

to_dict(remove_empty=False)

Create dictionary containing public attributes of an object.

Parameters:

remove_empty (bool) –

Whether to remove keys with empty values

Default: False

Returns:

public_attributes – Ordered dictionary containing the public attributes of the object

The order of attribute definition is preserved

Return type:

collections.OrderedDict

Changed in version 0.6: New parameter remove_empty

Changed in version 0.9: Settings for properties to exclude and include are not traversed

Changed in version 0.9.1: Dictionaries get copied before traversing, as otherwise, the special variables __dict__ and __0dict__ are modified, what may result in strange behaviour.

Changed in version 0.9.2: Dictionaries do not get copied by default, but there is a private method that can be overridden in derived classes to copy the dictionary.

class aspecd.annotation.FillBetween

Bases: PlotAnnotation

Coloured surface under a curve or between curves.

Particularly in signal decomposition, highlighting the individual components with coloured surfaces is a common task. But similarly, confidence intervals for a fit (between two lines or curves) can be marked this way.

Basically, this class is the ASpecD wrapper to matplotlib.axes.Axes.fill_between(), although (currently) with some restrictions.

parameters

All parameters necessary for the annotation, implicit and explicit

The following keys exist:

dataaspecd.dataset.Dataset | list

Dataset or list of datasets.

Datasets used to fill the area below. Strictly speaking, without further parameters, the area between the data points and zero is filled.

secondfloat | aspecd.dataset.Dataset | list

Scalar, dataset or list (of scalars or datasets).

Second value used to fill the area between.

If a scalar, the scalar value is broadcast to the length of the y values in data.

If a dataset, the data need to be of same shape as the data of the dataset in data.

If a list, it needs to contain at least as many elements as data. Note that you can mix scalars and datasets in the list.

Default: 0

Type:

dict

properties

Properties of the marker(s) within a plot

For the properties that can be set this way, see the documentation of the aspecd.plotting.PatchProperties class.

Type:

aspecd.plotting.PatchProperties

Examples

For convenience, a series of examples in recipe style (for details of the recipe-driven data analysis, see aspecd.tasks) is given below for how to make use of this class. The examples focus each on a single aspect.

Generally and for obvious reasons, you need to have both, a plot task and a plotannotation task. It does not really matter which task you define first, the plot or the plot annotation. There are only marginal differences, and both ways are shown below.

- kind: singleplot
  type: SinglePlotter1D
  properties:
    filename: plot1D.pdf
  result: plot1D

- kind: plotannotation
  type: FillBetween
  properties:
    parameters:
      data: component
    properties:
      facecolor: green
      alpha: 0.3
  plotter: plot1D

In this case, the plotter is defined first, and the annotation second. To refer to the plotter from within the plotannotation task, you need to set the result attribute in the plotting task and refer to it within the plotter attribute of the plotannotation task. Although defining the plotter before the annotation, the user still expects the annotation to be included in the file containing the actual plot, despite the fact that the figure has been saved (for the first time) before the annotation has been added.

Note that component refers to a dataset available within your recipe.

Sometimes, it might be convenient to go the other way round and first define an annotation and afterwards add it to a plot(ter). This can be done as well:

- kind: plotannotation
  type: FillBetween
  properties:
    parameters:
      data: component
    properties:
      facecolor: green
      alpha: 0.3
  result: fillbetween

- kind: singleplot
  type: SinglePlotter1D
  properties:
    filename: plot1D.pdf
  annotations:
    - fillbetween

In this way, you can add the same annotation to several plots, and be sure that each annotation is handled as a separate object.

Suppose you have more than one plotter you want to apply an annotation to. In this case, the plotter property of the plotannotation task is a list rather than a string:

- kind: singleplot
  type: SinglePlotter1D
  result: plot1

- kind: singleplot
  type: SinglePlotter1D
  result: plot2

- kind: plotannotation
  type: FillBetween
  properties:
    parameters:
      data: component
    properties:
      facecolor: green
      alpha: 0.3
  plotter:
    - plot1
    - plot2

In this case, the annotation will be applied to both plots independently. Note that the example has been reduced to the key aspects. In a real situation, the two plotters will differ much more.

New in version 0.11.

annotate(plotter=None, from_plotter=False)

Annotate a plot(ter) with the given annotation.

If no plotter is provided at method call, but is set as property in the Annotation object, the aspecd.plotting.Plotter.annotate() method of the plotter will be called and thus the history written.

If no plotter is provided at method call nor as property in the object, the method will raise a respective exception.

Parameters:

• plotter (aspecd.plotting.Plotter) – Plot(ter) to annotate

• from_plotter (bool) –

  whether we are called from within a plotter

  Defaults to “False” and shall never be set manually.

Returns:

plotter – Plotter that has been annotated

Return type:

aspecd.plotting.Plotter

to_dict(remove_empty=False)

Create dictionary containing public attributes of an object.

Parameters:

remove_empty (bool) –

Whether to remove keys with empty values

Default: False

Returns:

public_attributes – Ordered dictionary containing the public attributes of the object

The order of attribute definition is preserved

Return type:

collections.OrderedDict

Changed in version 0.6: New parameter remove_empty

Changed in version 0.9: Settings for properties to exclude and include are not traversed

Changed in version 0.9.1: Dictionaries get copied before traversing, as otherwise, the special variables __dict__ and __0dict__ are modified, what may result in strange behaviour.

Changed in version 0.9.2: Dictionaries do not get copied by default, but there is a private method that can be overridden in derived classes to copy the dictionary.