Plate
May 24, 2022 ยท View on GitHub
from tdw.proc_gen.arrangements.plate import Plate
A kitchen plate that may have food on it.
- The plate model is chosen randomly; see
TableSetting.MODEL_CATEGORIES["plate"]. - The plate might have food on it; see
Plate.FOOD_PROBABILITY.- The possible food categories are
Plate.FOOD_CATEGORIES. - See
Plate.MODEL_CATEGORIESfor a list of models within those categories. - The position of the food is perturbed randomly.
- The rotation of the food is random.
- The possible food categories are
Fields
-
root_object_idThe ID of the root object. -
object_idsA list of all of the object IDs in this arrangement. -
object_idsA list of all of the object IDs in this arrangement.
Class Variables
| Variable | Type | Description | Value |
|---|---|---|---|
DEFAULT_CELL_SIZE | float | The default span used for arranging objects next to each other. | 0.6096 |
ENCLOSED_BY | Dict[str, List[str]] | A dictionary of categories that can be enclosed by other categories. Key = A category. Value = A list of categories of models that can enclosed by the key category. | loads(Path(resource_filename(__name__, "data/enclosed_by.json")).read_text()) |
FOOD_CATEGORIES | List[str] | The categories of possible food models. | ["apple", "banana", "chocolate", "orange", "sandwich"] |
FOOD_PROBABILITY | float | The probability from 0 to 1 of adding a food model on top of the plate. | 0.8 |
INSIDE_OF | Dict[str, List[str]] | A dictionary of categories that can be inside of other categories. Key = A category. Value = A list of categories of models that can inside of the key category. | loads(Path(resource_filename(__name__, "data/inside_of.json")).read_text()) |
MODEL_CATEGORIES | Dict[str, List[str]] | A dictionary of all of the models that may be used for procedural generation. Key = The category. Value = A list of model names. Note that this category overlaps with, but is not the same as, model_record.wcategory; see: Arrangement.get_categories_and_wcategories(). | loads(Path(resource_filename(__name__, "data/models.json")).read_text()) |
ON_TOP_OF | Dict[str, List[str]] | A dictionary of categories that can be on top of other categories. Key = A category. Value = A list of categories of models that can be on top of the key category. | loads(Path(resource_filename(__name__, "data/on_top_of.json")).read_text()) |
Functions
__init__
__init__
Plate(position)
Plate(position, model=None, rng=None)
| Parameter | Type | Default | Description |
|---|---|---|---|
| position | Dict[str, float] | The position of the root object. This might be adjusted. | |
| model | Union[str, ModelRecord] | None | Either the name of the model (in which case the model must be in models_core.json), or a ModelRecord, or None. If None, a random model is selected. |
| rng | Union[int, np.random.RandomState] | None | Either a random seed or an numpy.random.RandomState object. If None, a new random number generator is created. |
get_categories_and_wcategories
Arrangement.get_categories_and_wcategories()
(Static)
Returns: A dictionary of the categories of every model that can be used by Arrangement and their corresponding wcategory and wnid. Key = The model name. Value = A dictionary with the following keys: "category" (the ProcGenObjects category), "wcategory" (the value of record.wcategory), and "wnid" (the value of record.wnid).
get_commands
self.get_commands()
Returns: A list of commands that will generate the arrangement.