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fso42 merged 1 commit into from
Jan 29, 2026
Merged

refactor(core): Adjust MacOS related imports and pixi setup #1231

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2 changes: 0 additions & 2 deletions avaframe/com1DFA/com1DFA.py
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Original file line number Diff line number Diff line change
Expand Up @@ -24,8 +24,6 @@

if os.name == "nt":
from multiprocessing.pool import ThreadPool as Pool
elif platform.system() == "Darwin":
from multiprocessing.pool import ThreadPool as Pool
else:
from multiprocessing import Pool

Expand Down
157 changes: 96 additions & 61 deletions avaframe/com4FlowPy/flowCore.py
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Original file line number Diff line number Diff line change
Expand Up @@ -2,7 +2,7 @@
# -*- coding: utf-8 -*-

"""
Calculation functions (raster level)
Calculation functions (raster level)
"""

import sys
Expand All @@ -16,8 +16,6 @@

if os.name == "nt":
from multiprocessing.pool import Pool as Pool
elif platform.system() == "Darwin":
from multiprocessing.pool import ThreadPool as Pool
else:
from multiprocessing import Pool

Expand Down Expand Up @@ -47,7 +45,9 @@ def get_start_idx(dem, release):
altitude_list = []
for i in range(len(row_list)):
altitude_list.append(dem[row_list[i], col_list[i]])
altitude_list, row_list, col_list = list(zip(*sorted(zip(altitude_list, row_list, col_list), reverse=True)))
altitude_list, row_list, col_list = list(
zip(*sorted(zip(altitude_list, row_list, col_list), reverse=True))
)
# Sort this lists by altitude
return row_list, col_list

Expand Down Expand Up @@ -182,9 +182,9 @@ def run(optTuple):

if varUmaxBool:
varUmaxArray = np.load(tempDir / ("varUmax_%s_%s.npy" % (optTuple[0], optTuple[1])))
if optTuple[2]["varUmaxType"].lower() == 'umax':
if optTuple[2]["varUmaxType"].lower() == "umax":
varUmaxArray[varUmaxArray > 0] = varUmaxArray[varUmaxArray > 0] ** 2 / 2 / 9.81
elif optTuple[2]["varUmaxType"].lower() != 'zdeltalim':
elif optTuple[2]["varUmaxType"].lower() != "zdeltalim":
log.error("PLease provide the type of the uMax Limit: 'uMax' (in m/s) or zDeltaMax (in m)!")
else:
varUmaxArray = None
Expand All @@ -200,18 +200,18 @@ def run(optTuple):
varExponentArray = None

varParams = {
'varUmaxBool': varUmaxBool,
'varUmaxArray': varUmaxArray,
'varAlphaBool': varAlphaBool,
'varAlphaArray': varAlphaArray,
'varExponentBool': varExponentBool,
'varExponentArray': varExponentArray,
"varUmaxBool": varUmaxBool,
"varUmaxArray": varUmaxArray,
"varAlphaBool": varAlphaBool,
"varAlphaArray": varAlphaArray,
"varExponentBool": varExponentBool,
"varExponentArray": varExponentArray,
}

# convert release areas to binary (0: no release areas, 1: release areas)
# every positive value >0 is interpreted as release area
release[release < 0] = 0
release[release == nodata] = 0 # added in case nodata is non-negative
release[release == nodata] = 0 # added in case nodata is non-negative
release[release > 0] = 1

nRel = np.sum(release)
Expand All @@ -226,7 +226,10 @@ def run(optTuple):
)

release_list = split_release(release, nChunks)
log.info("Multiprocessing starts, used Cores/Processes/Chunks: %i/%i/%i" % (MPOptions["nCPU"], nProcesses, nChunks))
log.info(
"Multiprocessing starts, used Cores/Processes/Chunks: %i/%i/%i"
% (MPOptions["nCPU"], nProcesses, nChunks)
)

with Pool(processes=nProcesses) as pool:
results = pool.map(
Expand Down Expand Up @@ -339,9 +342,11 @@ def run(optTuple):
np.maximum(travelLengthMinArray, travelLengthMinList[i]),
)
if forestInteraction:
forestIntArray = np.where((forestIntArray >= 0) & (forestIntList[i] >= 0),
np.minimum(forestIntArray, forestIntList[i]),
np.maximum(forestIntArray, forestIntList[i]))
forestIntArray = np.where(
(forestIntArray >= 0) & (forestIntList[i] >= 0),
np.minimum(forestIntArray, forestIntList[i]),
np.maximum(forestIntArray, forestIntList[i]),
)

# Save Calculated tiles
np.save(tempDir / ("res_z_delta_%s_%s" % (optTuple[0], optTuple[1])), zDeltaArray)
Expand Down Expand Up @@ -446,12 +451,12 @@ def updateInfraDirGraph(row, col, parentRow=None, parentCol=None):
cellsize = args[8]
infraBool = args[9]
forestBool = args[10]
varUmaxBool = args[11]['varUmaxBool']
varUmaxArray = args[11]['varUmaxArray']
varAlphaBool = args[11]['varAlphaBool']
varAlphaArray = args[11]['varAlphaArray']
varExponentBool = args[11]['varExponentBool']
varExponentArray = args[11]['varExponentArray']
varUmaxBool = args[11]["varUmaxBool"]
varUmaxArray = args[11]["varUmaxArray"]
varAlphaBool = args[11]["varAlphaBool"]
varAlphaArray = args[11]["varAlphaArray"]
varExponentBool = args[11]["varExponentBool"]
varExponentArray = args[11]["varExponentArray"]
fluxDistOldVersionBool = args[12]
previewMode = args[13]
outputs = args[16]
Expand Down Expand Up @@ -502,15 +507,15 @@ def updateInfraDirGraph(row, col, parentRow=None, parentCol=None):

if infraBool:
# if infraBool - here we initialize a directed graph structure
pathTopology = {} # topology of path as directed graph
infraValues = {} # values
pathTopology = {} # topology of path as directed graph
infraValues = {} # values

processedCells = {} # dictionary of cells that have been processed already
zDeltaPathArray = np.zeros_like(dem, dtype=np.float32)
cell_list = []
row_idx = row_list[startcell_idx]
col_idx = col_list[startcell_idx]
dem_ng = dem[row_idx - 1: row_idx + 2, col_idx - 1: col_idx + 2] # neighbourhood DEM
dem_ng = dem[row_idx - 1 : row_idx + 2, col_idx - 1 : col_idx + 2] # neighbourhood DEM
if varUmaxBool and varUmaxArray is not None:
if varUmaxArray[row_idx, col_idx] > 0 and varUmaxArray[row_idx, col_idx] <= 8848:
max_z_delta = varUmaxArray[row_idx, col_idx]
Expand All @@ -526,11 +531,19 @@ def updateInfraDirGraph(row, col, parentRow=None, parentCol=None):
continue

startcell = Cell(
row_idx, col_idx,
dem_ng, cellsize,
1, 0, None,
alpha, exp, flux_threshold, max_z_delta,
startcell=True, fluxDistOldVersionBool=fluxDistOldVersionBool,
row_idx,
col_idx,
dem_ng,
cellsize,
1,
0,
None,
alpha,
exp,
flux_threshold,
max_z_delta,
startcell=True,
fluxDistOldVersionBool=fluxDistOldVersionBool,
FSI=forestArray[row_idx, col_idx] if isinstance(forestArray, np.ndarray) else None,
forestParams=forestParams,
)
Expand All @@ -551,13 +564,13 @@ def updateInfraDirGraph(row, col, parentRow=None, parentCol=None):
# number of child cells (successors) to currently processed cell
row, col, flux, z_delta = cell.calc_distribution()

if len(flux) > 0: #i.e. if there are child cells
if len(flux) > 0: # i.e. if there are child cells
# Sort this lists by z_delta, to start with the highest cell
z_delta, flux, row, col = list(zip(*sorted(zip(z_delta, flux, row, col), reverse=False)))

if infraBool:
# if the current cell is not already in the dir-graph, then we add it here
updateInfraDirGraph(cell.rowindex, cell.colindex)
updateInfraDirGraph(cell.rowindex, cell.colindex)

# check if child cells already exist
for i in range(idx, len(cell_list)):
Expand All @@ -580,7 +593,7 @@ def updateInfraDirGraph(row, col, parentRow=None, parentCol=None):
k += 1

for k in range(len(row)):
dem_ng = dem[row[k] - 1: row[k] + 2, col[k] - 1: col[k] + 2] # neighbourhood DEM
dem_ng = dem[row[k] - 1 : row[k] + 2, col[k] - 1 : col[k] + 2] # neighbourhood DEM

# This bit handles edge cases and noData-values in the DEM!! this is an important piece of code, since
# no-data handling is expected (by some users/applications) to behave like here:
Expand All @@ -599,22 +612,35 @@ def updateInfraDirGraph(row, col, parentRow=None, parentCol=None):
else:
processedCells[(row[k], col[k])] = 1

cell_list.append(Cell(
row[k], col[k],
dem_ng, cellsize,
flux[k], z_delta[k],
cell,
alpha, exp, flux_threshold, max_z_delta,
startcell, fluxDistOldVersionBool=fluxDistOldVersionBool,
FSI=forestArray[row[k], col[k]] if isinstance(forestArray, np.ndarray) else None,
forestParams=forestParams,
))

zDeltaArray[cell.rowindex, cell.colindex] = max(zDeltaArray[cell.rowindex, cell.colindex], cell.z_delta)
cell_list.append(
Cell(
row[k],
col[k],
dem_ng,
cellsize,
flux[k],
z_delta[k],
cell,
alpha,
exp,
flux_threshold,
max_z_delta,
startcell,
fluxDistOldVersionBool=fluxDistOldVersionBool,
FSI=forestArray[row[k], col[k]] if isinstance(forestArray, np.ndarray) else None,
forestParams=forestParams,
)
)

zDeltaArray[cell.rowindex, cell.colindex] = max(
zDeltaArray[cell.rowindex, cell.colindex], cell.z_delta
)
fluxArray[cell.rowindex, cell.colindex] = max(fluxArray[cell.rowindex, cell.colindex], cell.flux)
routFluxSumArray[cell.rowindex, cell.colindex] += cell.flux
depFluxSumArray[cell.rowindex, cell.colindex] += cell.fluxDep
zDeltaPathArray[cell.rowindex, cell.colindex] = max(zDeltaPathArray[cell.rowindex, cell.colindex], cell.z_delta)
zDeltaPathArray[cell.rowindex, cell.colindex] = max(
zDeltaPathArray[cell.rowindex, cell.colindex], cell.z_delta
)
if "fpTravelAngleMax" in outputs or "fpTravelAngle" in outputs:
fpTravelAngleMaxArray[cell.rowindex, cell.colindex] = max(
fpTravelAngleMaxArray[cell.rowindex, cell.colindex], cell.max_gamma
Expand All @@ -628,8 +654,9 @@ def updateInfraDirGraph(row, col, parentRow=None, parentCol=None):
fpTravelAngleMinArray[cell.rowindex, cell.colindex] = max(
fpTravelAngleMinArray[cell.rowindex, cell.colindex], cell.max_gamma
)
slTravelAngleArray[cell.rowindex, cell.colindex] = max(slTravelAngleArray[cell.rowindex, cell.colindex],
cell.sl_gamma)
slTravelAngleArray[cell.rowindex, cell.colindex] = max(
slTravelAngleArray[cell.rowindex, cell.colindex], cell.sl_gamma
)
if "travelLengthMax" in outputs or "travelLength" in outputs:
travelLengthMaxArray[cell.rowindex, cell.colindex] = max(
travelLengthMaxArray[cell.rowindex, cell.colindex], cell.min_distance
Expand All @@ -648,20 +675,26 @@ def updateInfraDirGraph(row, col, parentRow=None, parentCol=None):

if forestInteraction:
if forestIntArray[cell.rowindex, cell.colindex] >= 0 and cell.forestIntCount >= 0:
forestIntArray[cell.rowindex, cell.colindex] = min(forestIntArray[cell.rowindex, cell.colindex],
cell.forestIntCount)
forestIntArray[cell.rowindex, cell.colindex] = min(
forestIntArray[cell.rowindex, cell.colindex], cell.forestIntCount
)
else:
forestIntArray[cell.rowindex, cell.colindex] = max(forestIntArray[cell.rowindex, cell.colindex],
cell.forestIntCount)
forestIntArray[cell.rowindex, cell.colindex] = max(
forestIntArray[cell.rowindex, cell.colindex], cell.forestIntCount
)

if infraBool:
# if 'infraBool' is True - i.e. calculation is performed with infrastructure information
# then we perform the back-tracking of the stored directed graph (topology and node values)

updatedInfraValues = backTracking(pathTopology, infraValues) # actual "back-tracking" for current process-path
updatedInfraValues = backTracking(
pathTopology, infraValues
) # actual "back-tracking" for current process-path

for key, val in updatedInfraValues.items():
backcalc[key[0], key[1]] = max(backcalc[key[0], key[1]], val) # writing max-values to back-tracking array
backcalc[key[0], key[1]] = max(
backcalc[key[0], key[1]], val
) # writing max-values to back-tracking array

del pathTopology, infraValues, updatedInfraValues
gc.collect()
Expand Down Expand Up @@ -822,6 +855,7 @@ def handleMemoryAvailability(recheckInterval=30):
while not enoughMemoryAvailable():
time.sleep(recheckInterval)


def backTracking(topologyDict, infraValDict):
"""
peform the back-tracking of infrastructure values across the dir-graph
Expand All @@ -834,9 +868,9 @@ def backTracking(topologyDict, infraValDict):
where parent nodes (colindex, rowindex) serve as keys and children of the
respective parent node are stored as list items for the respective key
infraValDict : dict
dictionay containing information if a node is an infrastructure cell
dictionay containing information if a node is an infrastructure cell
(value at key 'node' > 0) or not (value at key 'node' == 0)

Returns
-----------
infraValDict : dict
Expand All @@ -845,7 +879,7 @@ def backTracking(topologyDict, infraValDict):
"""
# sort valDict (so we start traversing from highest infrastructure cells first)
# this makes the algorithm more efficient
valDictSorted = {k: v for k, v in sorted(infraValDict.items(), key= lambda item: item[1], reverse=True)}
valDictSorted = {k: v for k, v in sorted(infraValDict.items(), key=lambda item: item[1], reverse=True)}
# reverse the graph topology, so "parents" become "children"
reverseGraph = reverseTopology(topologyDict)

Expand Down Expand Up @@ -873,8 +907,9 @@ def propagateInfraVal(node, infraValToPropagate, visited):

return infraValDict


def reverseTopology(topologyDict):
'''
"""
reverse graph topology
i.e. directions of graph edges connecting the nodes in the dir graph

Expand All @@ -884,12 +919,12 @@ def reverseTopology(topologyDict):
dictionary containing the topology of the modeled process path
where parent nodes (colindex, rowindex) serve as keys and children of the
respective parent node are stored as list items for the respective key

Returns
-----------
reverseGraph : dict
dir-graph with reversed edges in same dictionary format as orignial input
'''
"""
reverseGraph = {}

for parentNode, childNodes in topologyDict.items():
Expand Down
2 changes: 0 additions & 2 deletions avaframe/com8MoTPSA/com8MoTPSA.py
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Original file line number Diff line number Diff line change
Expand Up @@ -11,8 +11,6 @@

if os.name == "nt":
from multiprocessing.pool import ThreadPool as Pool
elif platform.system() == "Darwin":
from multiprocessing.pool import ThreadPool as Pool
else:
from multiprocessing import Pool

Expand Down
2 changes: 0 additions & 2 deletions avaframe/com9MoTVoellmy/com9MoTVoellmy.py
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Original file line number Diff line number Diff line change
Expand Up @@ -7,8 +7,6 @@

if os.name == "nt":
from multiprocessing.pool import ThreadPool as Pool
elif platform.system() == "Darwin":
from multiprocessing.pool import ThreadPool as Pool
else:
from multiprocessing import Pool

Expand Down
2 changes: 1 addition & 1 deletion pyproject.toml
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Original file line number Diff line number Diff line change
Expand Up @@ -83,7 +83,7 @@ line-length = 109
# PIXI setup
[tool.pixi.workspace]
channels = ["https://prefix.dev/conda-forge"]
platforms = ["linux-64", "win-64", "osx-64"]
platforms = ["linux-64", "win-64", "osx-64", "osx-arm64"]

[tool.pixi.dependencies]
python = ">=3.9,<3.14"
Expand Down
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