def plot_coordinate_systems(
cs_data: Tuple[str, Dict],
axes: Axes = None,
title: str = None,
limits: types_limits = None,
time_index: int = None,
legend_pos: str = "lower left",
) -> Axes:
"""Plot multiple coordinate systems.
Parameters
----------
cs_data :
A tuple containing the coordinate system that should be plotted and a dictionary
with the key word arguments that should be passed to its plot function.
axes :
The target axes object that should be drawn to. If `None` is provided, a new
one will be created.
title :
The title of the plot
limits :
Each tuple marks lower and upper boundary of the x, y and z axis. If only a
single tuple is passed, the boundaries are used for all axis. If `None`
is provided, the axis are adjusted to be of equal length.
time_index :
Index of a specific time step that should be plotted if the corresponding
coordinate system is time dependent
legend_pos :
A string that specifies the position of the legend. See the matplotlib
documentation for further details
Returns
-------
matplotlib.axes.Axes :
The axes object that was used as canvas for the plot
"""
if axes is None:
_, axes = new_3d_figure_and_axes()
for lcs, kwargs in cs_data:
if "time_index" not in kwargs:
kwargs["time_index"] = time_index
lcs.plot(axes, **kwargs)
_set_limits_matplotlib(axes, limits)
if title is not None:
axes.set_title(title)
axes.legend(loc=legend_pos)
return axes
def plot_coordinate_system_manager_matplotlib(
csm: CoordinateSystemManager,
axes: Axes = None,
reference_system: str = None,
coordinate_systems: List[str] = None,
data_sets: List[str] = None,
colors: Dict[str, int] = None,
time: types_timeindex = None,
time_ref: pd.Timestamp = None,
title: str = None,
limits: types_limits = None,
scale_vectors: Union[float, List, np.ndarray] = None,
set_axes_equal: bool = False,
show_origins: bool = True,
show_trace: bool = True,
show_vectors: bool = True,
show_wireframe: bool = True,
) -> Axes:
"""Plot the coordinate systems of a `weldx.transformations.CoordinateSystemManager`.
Parameters
----------
csm :
The coordinate system manager instance that should be plotted.
axes :
The target axes object that should be drawn to. If `None` is provided, a new
one will be created.
reference_system :
The name of the reference system for the plotted coordinate systems
coordinate_systems :
Names of the coordinate systems that should be drawn. If `None` is provided,
all systems are plotted.
data_sets :
Names of the data sets that should be drawn. If `None` is provided, all data
is plotted.
colors :
A mapping between a coordinate system name or a data set name and a color.
The colors must be provided as 24 bit integer values that are divided into
three 8 bit sections for the rgb values. For example `0xFF0000` for pure
red.
Each coordinate system or data set that does not have a mapping in this
dictionary will get a default color assigned to it.
time :
The time steps that should be plotted
time_ref :
A reference timestamp that can be provided if the ``time`` parameter is a
`pandas.TimedeltaIndex`
title :
The title of the plot
limits :
Each tuple marks lower and upper boundary of the x, y and z axis. If only a
single tuple is passed, the boundaries are used for all axis. If `None`
is provided, the axis are adjusted to be of equal length.
scale_vectors :
A scaling factor or array to adjust the length of the coordinate system vectors
set_axes_equal :
(matplotlib only) If `True`, all axes are adjusted to cover an equally large
range of value. That doesn't mean, that the limits are identical
show_origins :
If `True`, the origins of the coordinate system are visualized in the color
assigned to the coordinate system.
show_trace :
If `True`, the trace of time dependent coordinate systems is plotted.
show_vectors :
If `True`, the coordinate cross of time dependent coordinate systems is plotted.
show_wireframe :
If `True`, the mesh is visualized as wireframe. Otherwise, it is not shown.
Returns
-------
matplotlib.axes.Axes :
The axes object that was used as canvas for the plot.
"""
if time is not None:
return plot_coordinate_system_manager_matplotlib(
csm.interp_time(time=time, time_ref=time_ref),
axes=axes,
reference_system=reference_system,
coordinate_systems=coordinate_systems,
title=title,
show_origins=show_origins,
show_trace=show_trace,
show_vectors=show_vectors,
)
if axes is None:
_, axes = new_3d_figure_and_axes()
axes.set_xlabel("x")
axes.set_ylabel("y")
axes.set_zlabel("z")
if reference_system is None:
reference_system = csm.root_system_name
if coordinate_systems is None:
coordinate_systems = csm.coordinate_system_names
if data_sets is None:
data_sets = csm.data_names
if title is not None:
axes.set_title(title)
# plot coordinate systems
color_gen = color_generator_function()
for lcs_name in coordinate_systems:
color = color_int_to_rgb_normalized(
get_color(lcs_name, colors, color_gen))
lcs = csm.get_cs(lcs_name, reference_system)
lcs.plot(
axes=axes,
color=color,
label=lcs_name,
scale_vectors=scale_vectors,
show_origin=show_origins,
show_trace=show_trace,
show_vectors=show_vectors,
)
# plot data
for data_name in data_sets:
color = color_int_to_rgb_normalized(
get_color(data_name, colors, color_gen))
data = csm.get_data(data_name, reference_system)
plot_spatial_data_matplotlib(
data=data,
axes=axes,
color=color,
label=data_name,
show_wireframe=show_wireframe,
)
_set_limits_matplotlib(axes, limits, set_axes_equal)
axes.legend()
return axes