udelal upravu calc_distance, a napsal funkce spatial_points a pytest …#3
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IvaNodyanosh wants to merge 3 commits intomainfrom
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udelal upravu calc_distance, a napsal funkce spatial_points a pytest …#3IvaNodyanosh wants to merge 3 commits intomainfrom
IvaNodyanosh wants to merge 3 commits intomainfrom
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jbrezmorf
reviewed
Mar 10, 2026
| def spatial_points(points_k, points_m, min_distance): | ||
| tree = cKDTree(points_m) | ||
| result = [] | ||
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| import numpy as np | ||
| from scipy.spatial import cKDTree | ||
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| def spatial_points(points_k, points_m, min_distance): |
Contributor
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points_k -> target_points
points_m -> mixing_points
... i jinde
| tree = cKDTree(points_m) | ||
| result = [] | ||
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| __, idx = tree.query(points_k, k=5) |
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Comment shape : (len(points_k), max_neighbours)
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| __, idx = tree.query(points_k, k=5) | ||
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| for i in range(len(points_k)): |
Contributor
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Vectorize the loops:
point_k shape = ( K, dim); idx.shape = (5, K)
diff = point_k[None, :, :] - points_m[idx[:, :], :]
dist = np.linalg.norm(diff, axis = -1)
| import numpy as np | ||
| from field_synthesis.functions.spatial_points import spatial_points | ||
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Contributor
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Zkusit změřit před a po vektorizaci.
jbrezmorf
reviewed
Mar 24, 2026
| class FieldSynthesis(): | ||
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| def __init__(self, area_size: float, count_points: int, num_source: int, dimension: int = 2, seed: int = 42): | ||
| self.area_size = area_size |
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| def generate_points(self): |
Contributor
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Refactor as @cached_property:
@cached_property
def anchor_points(self):
...
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