pytransform3d.transform_manager.TransformManager¶

class pytransform3d.transform_manager.TransformManager(strict_check=True, check=True)[source]¶

Bases: TransformGraphBase

Manage transformations between frames.

This is a simplified version of ROS tf that ignores the temporal aspect. A user can register transformations. The shortest path between all frames will be computed internally which enables us to provide transforms for any connected frames.

Suppose we know the transformations A2B, D2C, and B2C. The transform manager can compute any transformation between the frames A, B, C and D. For example, you can request the transformation that represents frame D in frame A. The transformation manager will automatically concatenate the transformations D2C, C2B, and B2A, where C2B and B2A are obtained by inverting B2C and A2B respectively.

Warning

It is possible to introduce inconsistencies in the transformation manager. Adding A2B and B2A with inconsistent values will result in an invalid state because inconsistencies will not be checked. It seems to be trivial in this simple case but can be computationally complex for large graphs. You can check the consistency explicitly with TransformManager.check_consistency().

The TransformManager does not directly support serialization because we don’t want to decide for a specific format. However, it allows conversion to a dict with only primitive types that is serializable, for instance, as JSON. If a more compact format is required, binary formats like msgpack can be used. Use TransformManager.to_dict() and TransformManager.from_dict() for this purpose.

Parameters:

strict_checkbool, optional (default: True): Raise a ValueError if the transformation matrix is not numerically close enough to a real transformation matrix. Otherwise we print a warning.
checkbool, optional (default: True): Check if transformation matrices are valid and requested nodes exist, which might significantly slow down some operations.

__init__(strict_check=True, check=True)[source]¶

Methods

`__init__`([strict_check, check])
`add_transform`(from_frame, to_frame, A2B)	Register a transformation.
`check_consistency`()	Check consistency of the known transformations.
`connected_components`()	Get number of connected components.
`from_dict`(tm_dict)	Create transform manager from dict.
`get_transform`(from_frame, to_frame)	Request a transformation.
`has_frame`(frame)	Check if frame has been registered.
`plot_connections_in`(frame[, ax, ax_s, whitelist])	Plot direct frame connections in a given reference frame.
`plot_frames_in`(frame[, ax, s, ax_s, ...])	Plot all frames in a given reference frame.
`remove_transform`(from_frame, to_frame)	Remove a transformation.
`set_transform_manager_state`(tm_dict)	Set state of transform manager from dict.
`to_dict`()	Convert the transform manager to a dict that is serializable.
`write_png`(filename[, prog])	Create PNG from dot graph of the transformations.

Attributes

transforms

Rigid transformations between nodes.

property transforms¶: Rigid transformations between nodes.

plot_frames_in(frame, ax=None, s=1.0, ax_s=1, show_name=True, whitelist=None, **kwargs)[source]¶

Plot all frames in a given reference frame.

Note that frames that cannot be connected to the reference frame are omitted.

Parameters:

frameHashable: Reference frame
axMatplotlib 3d axis, optional (default: None): If the axis is None, a new 3d axis will be created
sfloat, optional (default: 1): Scaling of the frame that will be drawn
ax_sfloat, optional (default: 1): Scaling of the new matplotlib 3d axis
show_namebool, optional (default: True): Print node names
whitelistlist, optional (default: None): Frames that must be plotted
kwargsdict, optional (default: {}): Additional arguments for the plotting functions, e.g. alpha

Returns:

axMatplotlib 3d axis: New or old axis

Raises:

KeyError: If the frame is unknown

plot_connections_in(frame, ax=None, ax_s=1, whitelist=None, **kwargs)[source]¶

Plot direct frame connections in a given reference frame.

A line between each pair of frames for which a direct transformation is known will be plotted. Direct means that either A2B or B2A has been added to the transformation manager.

Note that frames that cannot be connected to the reference frame are omitted.

Parameters:

frameHashable: Reference frame
axMatplotlib 3d axis, optional (default: None): If the axis is None, a new 3d axis will be created
ax_sfloat, optional (default: 1): Scaling of the new matplotlib 3d axis
whitelistlist, optional (default: None): Both frames of a connection must be in the whitelist to plot the connection
kwargsdict, optional (default: {}): Additional arguments for the plotting functions, e.g. alpha

Returns:

axMatplotlib 3d axis: New or old axis

Raises:

KeyError: If the frame is unknown

write_png(filename, prog=None)[source]¶

Create PNG from dot graph of the transformations.

Warning

Note that this method requires the Python package pydot and an existing installation of graphviz on your system.

Parameters:

filenamestr: Name of the output file. Should end with ‘.png’.
progstr, optional (default: dot): Name of GraphViz executable that can be found in the $PATH or absolute path to GraphViz executable. Possible options are, for example, ‘dot’, ‘twopi’, ‘neato’, ‘circo’, ‘fdp’, ‘sfdp’.

Raises:

ImportError: If pydot is not available

to_dict()[source]¶

Convert the transform manager to a dict that is serializable.

Returns:

tm_dictdict: Serializable dict.

static from_dict(tm_dict)[source]¶

Create transform manager from dict.

Parameters:

tm_dictdict: Serializable dict.

Returns:

tmTransformManager: Deserialized transform manager.

set_transform_manager_state(tm_dict)[source]¶

Set state of transform manager from dict.

Parameters:

tm_dictdict: Serializable dict.

add_transform(from_frame, to_frame, A2B)¶

Parameters:

from_frameHashable: Name of the frame for which the transformation is added in the to_frame coordinate system
to_frameHashable: Name of the frame in which the transformation is defined
A2BAny: Transformation from ‘from_frame’ to ‘to_frame’

Returns:

selfTransformManager: This object for chaining

check_consistency()¶

Check consistency of the known transformations.

The complexity of this is between $O(n^2)$ and $O(n^3)$ , where $n$ is the number of nodes. In graphs where each pair of nodes is directly connected the complexity is $O(n^2)$ . In graphs that are actually paths, the complexity is $O(n^3)$ .

Returns:

consistentbool: Is the graph consistent, i.e. is A2B always the same as the inverse of B2A?

connected_components()¶

Get number of connected components.

If the number is larger than 1 there will be frames without connections.

Returns:

n_connected_componentsint: Number of connected components.

get_transform(from_frame, to_frame)¶

Request a transformation.

Parameters:

from_frameHashable: Name of the frame for which the transformation is requested in the to_frame coordinate system
to_frameHashable: Name of the frame in which the transformation is defined

Returns:

A2BAny: Transformation from ‘from_frame’ to ‘to_frame’

Raises:

KeyError: If one of the frames is unknown or there is no connection between them

has_frame(frame)¶

Check if frame has been registered.

Parameters:

frameHashable: Frame name

Returns:

has_framebool: Frame is registered

remove_transform(from_frame, to_frame)¶

Remove a transformation.

Nothing happens if there is no such transformation.

Parameters:

from_frameHashable: Name of the frame for which the transformation is added in the to_frame coordinate system
to_frameHashable: Name of the frame in which the transformation is defined

Returns:

selfTransformManager: This object for chaining

Examples using `pytransform3d.transform_manager.TransformManager`¶

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pytransform3d.transform_manager.TransformManager¶

Examples using pytransform3d.transform_manager.TransformManager¶

Examples using `pytransform3d.transform_manager.TransformManager`¶