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Merge two points that are too close.
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import CGNS.MAP as cgm | ||
import CGNS.PAT.cgnslib as cgl | ||
import CGNS.PAT.cgnsutils as cgu | ||
import CGNS.PAT.cgnskeywords as cgk | ||
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import numpy as np | ||
import argparse | ||
import wrapper | ||
import sys | ||
from check_nodes import getUniqueZone, readPoints | ||
from scipy.spatial import KDTree | ||
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X, Y, Z = 0, 1, 2 | ||
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def multiple_to_unique(multiple_points: np.ndarray, radius: float, verbose: bool) -> tuple[np.ndarray, np.ndarray]: | ||
assert multiple_points.shape[1] == 3 | ||
n_multiple = len(multiple_points) | ||
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multiple_kdtree = KDTree(multiple_points) | ||
i_multiple_to_i_minimum = np.zeros((n_multiple,), dtype='int') - 1 | ||
i_multiple_to_i_unique = np.zeros((n_multiple,), dtype='int') - 1 | ||
i_minimum_to_i_unique = dict() | ||
i_unique = 0 | ||
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for i_multiple in range(n_multiple): | ||
point_i = multiple_points[i_multiple] | ||
neighbors = multiple_kdtree.query_ball_point(point_i, radius) | ||
i_minimum = np.min(neighbors) | ||
assert 0 <= i_minimum < n_multiple | ||
if verbose: | ||
print(f'{i_multiple} -> {i_minimum}, {neighbors}') | ||
i_multiple_to_i_minimum[i_multiple] = i_minimum | ||
if i_minimum not in i_minimum_to_i_unique: | ||
i_minimum_to_i_unique[i_minimum] = i_unique | ||
i_unique += 1 | ||
i_multiple_to_i_unique[i_multiple] = i_minimum_to_i_unique[i_minimum] | ||
n_unique = len(i_minimum_to_i_unique) | ||
assert i_unique == n_unique | ||
assert (0 <= i_multiple_to_i_unique).all() and (i_multiple_to_i_unique < n_unique).all() | ||
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unique_points = np.ndarray((n_unique, 3), dtype=multiple_points.dtype) | ||
for i_minimum, i_unique in i_minimum_to_i_unique.items(): | ||
unique_points[i_unique] = multiple_points[i_minimum] | ||
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for i_multiple in range(n_multiple): | ||
i_unique = i_multiple_to_i_unique[i_multiple] | ||
assert np.linalg.norm(multiple_points[i_multiple] - unique_points[i_unique]) < radius | ||
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np.save('i_multiple_to_i_unique.npy', i_multiple_to_i_unique) | ||
np.save('unique_points.npy', unique_points) | ||
print('in multiple_to_unique:', n_unique, n_multiple) | ||
return unique_points, i_multiple_to_i_unique | ||
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if __name__ == "__main__": | ||
parser = argparse.ArgumentParser( | ||
prog = f'python3 {sys.argv[0][:-3]}.py', | ||
description = 'Merge geometrically duplicated points in a single unstructured `Zone_t`.') | ||
parser.add_argument('--input', type=str, help='the CGNS file to be merged') | ||
parser.add_argument('--output', type=str, help='the merged CGNS file') | ||
parser.add_argument('--radius', type=float, default=1e-8, help='radius of the ball within which two points are treated as duplicated') | ||
parser.add_argument('--verbose', default=True, action='store_true') | ||
args = parser.parse_args() | ||
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if args.verbose: | ||
print(args) | ||
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# get the unique Zone_t | ||
cgns, zone, zone_size = getUniqueZone(args.input) | ||
_, multiple_points, _, _, _ = readPoints(zone, zone_size) | ||
assert zone_size[0][0] == len(multiple_points) | ||
unique_points, i_multiple_to_i_unique = multiple_to_unique(multiple_points, args.radius, args.verbose) | ||
n_unique = len(unique_points) | ||
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# update zone_size and GridCoordinates_t | ||
zone_size[0][0] = n_unique | ||
coords = wrapper.getChildrenByType( | ||
wrapper.getUniqueChildByType(zone, 'GridCoordinates_t'), 'DataArray_t') | ||
if args.verbose: | ||
print('\ncoords before merging:\n', coords) | ||
coords[X][1] = np.array(unique_points[:, X]) | ||
coords[Y][1] = np.array(unique_points[:, Y]) | ||
coords[Z][1] = np.array(unique_points[:, Z]) | ||
if args.verbose: | ||
print('\ncoords after merging:\n', coords) | ||
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# update Elements_t's | ||
sections = wrapper.getChildrenByType(zone, 'Elements_t') | ||
for section in sections: | ||
connectivity = wrapper.getNodeData( | ||
wrapper.getUniqueChildByName(section, 'ElementConnectivity')) | ||
n = len(connectivity) | ||
for i in range(n): | ||
connectivity[i] = i_multiple_to_i_unique[connectivity[i] - 1] + 1 | ||
assert (1 <= connectivity).all() and (connectivity <= n_unique).all() | ||
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# write the new mesh out | ||
output = args.output | ||
if output is None: | ||
output = f'merged_{args.input}' | ||
print('writing to', output) | ||
cgm.save(output, cgns) |