spateo.tdr.models.models_migration.arrow_model¶
Functions¶
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Create a 3D arrow model. |
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Create a 3D arrow model. |
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Create multiple 3D arrows model. |
Module Contents¶
- spateo.tdr.models.models_migration.arrow_model._construct_arrow(start_point: list | tuple | numpy.ndarray = (0.0, 0.0, 0.0), direction: list | tuple | numpy.ndarray = (1.0, 0.0, 0.0), tip_length: float = 0.25, tip_radius: float = 0.1, tip_resolution: int = 20, shaft_radius: float = 0.05, shaft_resolution: int = 20, scale: str | float | None = 'auto') pyvista.PolyData [source]¶
Create a 3D arrow model.
- Parameters:
- start_point
Start location in [x, y, z] of the arrow.
- direction
Direction the arrow points to in [x, y, z].
- tip_length
Length of the tip.
- tip_radius
Radius of the tip.
- tip_resolution
Number of faces around the tip.
- shaft_radius
Radius of the shaft.
- shaft_resolution
Number of faces around the shaft.
- scale
Scale factor of the entire object.
'auto'
scales to length of direction array.
- Returns:
Arrow model.
- spateo.tdr.models.models_migration.arrow_model.construct_arrow(start_point: list | tuple | numpy.ndarray, direction: list | tuple | numpy.ndarray, arrow_scale: int | float | None = None, key_added: str | None = 'arrow', label: str = 'arrow', color: str = 'gainsboro', alpha: float = 1.0, **kwargs) Tuple[pyvista.PolyData, str | None] [source]¶
Create a 3D arrow model.
- Parameters:
- start_point
Start location in [x, y, z] of the arrow.
- direction
Direction the arrow points to in [x, y, z].
- arrow_scale
Scale factor of the entire object. ‘auto’ scales to length of direction array.
- key_added
The key under which to add the labels.
- label
The label of arrow model.
- color
Color to use for plotting model.
- alpha
The opacity of the color to use for plotting model.
- **kwargs
Additional parameters that will be passed to
_construct_arrow
function.
- Returns:
Arrow model. plot_cmap: Recommended colormap parameter values for plotting.
- Return type:
model
- spateo.tdr.models.models_migration.arrow_model.construct_arrows(start_points: numpy.ndarray, direction: numpy.ndarray = None, arrows_scale: numpy.ndarray | None = None, n_sampling: int | None = None, sampling_method: str = 'trn', factor: float = 1.0, key_added: str | None = 'arrow', label: str | list | numpy.ndarray = 'arrows', color: str | list | dict | numpy.ndarray = 'gainsboro', alpha: float | int | list | dict | numpy.ndarray = 1.0, **kwargs) Tuple[pyvista.PolyData, str | None] [source]¶
Create multiple 3D arrows model.
- Parameters:
- start_points
List of Start location in [x, y, z] of the arrows.
- direction
Direction the arrows points to in [x, y, z].
- arrows_scale
Scale factor of the entire object.
- n_sampling
n_sampling is the number of coordinates to keep after sampling. If there are too many coordinates in start_points, the generated arrows model will be too complex and unsightly, so sampling is used to reduce the number of coordinates.
- sampling_method
The method to sample data points, can be one of
['trn', 'kmeans', 'random']
.- factor
Scale factor applied to scaling array.
- key_added
The key under which to add the labels.
- label
The label of arrows models.
- color
Color to use for plotting model.
- alpha
The opacity of the color to use for plotting model.
- **kwargs
Additional parameters that will be passed to
_construct_arrow
function.
- Returns:
Arrows model. plot_cmap: Recommended colormap parameter values for plotting.
- Return type:
model