def test_region_from_object(self):
test_region = Region([10] * 3, [50] * 3)
objects = []
objects.append({"lower": [10] * 3, "upper": [50] * 3})
objects.append({"dimension": 3, "lower": 10, "upper": [50] * 3})
objects.append({"dimension": 3, "lower": 10, "upper": 50})
objects.append({"dimension": 3, "lower": [10] * 3, "upper": 50})
objects.append({"dimension": 3, "interval": [10, 50]})
objects.append({"dimension": 3, "interval": (10, 50)})
objects.append({
"dimension": 3,
"interval": {
"lower": 10,
"upper": 50
}
})
objects.append({"dimensions": [[10, 50]] * 3})
objects.append({"dimensions": [(10, 50)] * 3})
objects.append({"dimensions": [{"lower": 10, "upper": 50}] * 3})
objects.append([[10, 50]] * 3)
objects.append([(10, 50)] * 3)
objects.append([{"lower": 10, "upper": 50}] * 3)
objects.append((3, [10, 50]))
objects.append((3, (10, 50)))
objects.append((3, {"lower": 10, "upper": 50}))
for object in objects:
#print(f'{object}')
self.assertEqual(test_region, Region.from_object(object))
def generate(cls, output: FileIO, kind: str, nregions: int, dimension: int,
**kwargs):
"""
Randomly generate a new collection or intersection graph of Regions. \f
Args:
output:
The file to save the newly generated set
or intersection graph of Regions.
kind: The output object type.
nregions: The number of Regions to be generated.
dimension: The number of dimensions for each Region.
kwargs: Additional arguments.
Keyword Args:
id:
The unique identifier for the output.
bounds:
The minimum + maximum bounding value for
each dimension that all Region must be
enclosed within.
sizepc:
The minimum + maximum size of each Region
as a percent of the bounding Region that
all Region must be enclosed within.
precision:
The number of digits after the decimal pt
in each Region's lower + upper values.
colored:
Boolean flag for whether to color code the
connected Regions and save the associated
colors in each Region's data properties.
"""
kwargs['bounds'] = Region.from_object((dimension, kwargs['bounds']))
kwargs['sizepc'] = Region.from_object((dimension, kwargs['sizepc']))
colored = kwargs.pop('colored', False)
regions = RegionSet.from_random(nregions, **kwargs)
bundle = cls.bundle(regions)
if colored:
cls.colorize_components(bundle)
cls.write(output, cls.unbundle(bundle, kind))