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Equal distribution of particles to MPI processors #1231

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Equal distribution of particles to MPI processors #1231

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be039cb
Update collectionsoa.py
JakeNewmanUEA Aug 31, 2022
8b21bc9
Equal distribution of particles to MPI processors
JakeNewmanUEA Aug 31, 2022
e3b100d
Equal distribution of particles to MPI processors
JakeNewmanUEA Aug 31, 2022
b44e59c
Equal distribution of particles to MPI processors
JakeNewmanUEA Sep 1, 2022
11fdf50
Equal distribution of particles to MPI processors
JakeNewmanUEA Sep 1, 2022
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13 changes: 12 additions & 1 deletion parcels/collection/collectionaos.py
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Original file line number Diff line number Diff line change
Expand Up @@ -3,6 +3,7 @@

from ctypes import c_void_p

import copy
import numpy as np

from parcels.collection.collections import ParticleCollection
Expand Down Expand Up @@ -103,7 +104,17 @@ def __init__(self, pclass, lon, lat, depth, time, lonlatdepth_dtype, pid_orig, p
if mpi_rank == 0:
coords = np.vstack((lon, lat)).transpose()
kmeans = KMeans(n_clusters=mpi_size, random_state=0).fit(coords)
self._pu_indicators = kmeans.labels_
labels = np.linspace(0, mpi_size, lon.size, endpoint=False)
labels = np.floor(labels)
reorderedCoords = copy.copy(labels)
for i in range(0, len(kmeans.cluster_centers_)):
clusterCentre = kmeans.cluster_centers_[i]
distances = map(lambda point: ((point[0]-clusterCentre[0])**2 + (point[1]-clusterCentre[1])**2), coords)
sortedDistanceIdxs = np.argsort(list(distances))
numberToChoose = sum(labels == i)
reorderedCoords[sortedDistanceIdxs[0:numberToChoose]] = i
coords[sortedDistanceIdxs[0:numberToChoose],:] = float('inf')
self._pu_indicators = reorderedCoords
else:
self._pu_indicators = None
self._pu_indicators = mpi_comm.bcast(self._pu_indicators, root=0)
Expand Down
16 changes: 13 additions & 3 deletions parcels/collection/collectionsoa.py
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Original file line number Diff line number Diff line change
Expand Up @@ -3,7 +3,7 @@
from ctypes import Structure, POINTER
from bisect import bisect_left
from math import floor

import copy
import numpy as np

from parcels.collection.collections import ParticleCollection
Expand Down Expand Up @@ -101,10 +101,20 @@ def __init__(self, pclass, lon, lat, depth, time, lonlatdepth_dtype, pid_orig, p
if mpi_size > 1:
if partitions is not False:
if (self._pu_indicators is None) or (len(self._pu_indicators) != len(lon)):
if mpi_rank == 0:
if mpi_rank == 0:
coords = np.vstack((lon, lat)).transpose()
kmeans = KMeans(n_clusters=mpi_size, random_state=0).fit(coords)
self._pu_indicators = kmeans.labels_
labels = np.linspace(0, mpi_size, lon.size, endpoint=False)
labels = np.floor(labels)
reorderedCoords = copy.copy(labels)
for i in range(0, len(kmeans.cluster_centers_)):
clusterCentre = kmeans.cluster_centers_[i]
distances = map(lambda point: ((point[0]-clusterCentre[0])**2 + (point[1]-clusterCentre[1])**2), coords)
sortedDistanceIdxs = np.argsort(list(distances))
numberToChoose = sum(labels == i)
reorderedCoords[sortedDistanceIdxs[0:numberToChoose]] = i
coords[sortedDistanceIdxs[0:numberToChoose],:] = float('inf')
self._pu_indicators = reorderedCoords
else:
self._pu_indicators = None
self._pu_indicators = mpi_comm.bcast(self._pu_indicators, root=0)
Expand Down