def displayClustersBonds(self,clusters, factor=0.7,ev=1.0):
colors = [ getattr(upy_colors, name) for name in upy_colors.cnames ]
centers = []
radiiG = []
radiiM = []
radii = []
if clusters is None:
return
for i,cluster in enumerate(clusters):
centers.append(cluster.centroid.coords)
radg = cluster.radiusOfGyration()
radm = cluster.encapsualtingRadius()
self.radg = radg #added by Graham 4/4/11
self.radm = radm #added by Graham 4/4/11
#rad = radg/0.7
rad = radg + factor*(radm-radg)
radiiG.append(radg)
radiiM.append(radm)
radii.append(rad)
ptCoords = [x.coords for x in cluster.points]
# Create a bhtree for the ptCoords using a granility of 10
bht = bhtreelib.BHtree( centers, radiiM, 10)
# find all pairs of atoms for which the distance is less than 1.1
# times the sum of the radii
print ("cutoff ",ev)
pairs = bht.closePointsPairsInTree(ev)
bhtreelib.freeBHtree(bht)
# pairs is list of tuple of atom indices.
nbc = len(clusters)
bonds = {}
for i,pair in enumerate(pairs):
# 1- Get the atoms corresponding of the indices of the pair
cl1 = clusters[int(pair[0])]
cl2 = clusters[int(pair[1])]
head = cl1.centroid.coords
tail = cl2.centroid.coords
rad = cl1.radiusOfGyration() + factor*(cl1.encapsualtingRadius()-cl1.radiusOfGyration())#or diameter ?
pinstance = self.helper.getObject("BC")
if pinstance is None :
pinstance=self.helper.Cylinder("BC",radius=1.,length=1.,res=10, pos = [0.,0.,0.],parent=None)[0]
cyl = self.helper.getObject("clbond"+str(i))
if cyl is None :
cyl=self.helper.oneCylinder("clbond"+str(i),head,tail,radius=rad,instance=pinstance,material=None,
parent = self.CenterSpheres,color=colors[nbc])
else :
self.helper.updateOneCylinder("clbond"+str(i),head,tail,radius=rad,color=colors[nbc])
self.clusterCenterCyl["clbond"+str(i)] = [head,tail,rad]
if len(self.clusterCenterCyl) > len(pairs):
for j in range(len(pairs),len(self.clusterCenterCyl)):
# for cy in self.clusterCenterCyl[len(pair):]:
# o=self.clusterCenterCyl[]
self.helper.deleteObject("clbond"+str(j))
def displayClustersBonds(self, clusters, factor=0.7, ev=1.0):
colors = [getattr(upy_colors, name) for name in upy_colors.cnames]
centers = []
radiiG = []
radiiM = []
radii = []
if clusters is None:
return
for i, cluster in enumerate(clusters):
centers.append(cluster.centroid.coords)
radg = cluster.radiusOfGyration()
radm = cluster.encapsualtingRadius()
self.radg = radg #added by Graham 4/4/11
self.radm = radm #added by Graham 4/4/11
#rad = radg/0.7
rad = radg + factor * (radm - radg)
radiiG.append(radg)
radiiM.append(radm)
radii.append(rad)
ptCoords = [x.coords for x in cluster.points]
# Create a bhtree for the ptCoords using a granility of 10
bht = bhtreelib.BHtree(centers, radiiM, 10)
# find all pairs of atoms for which the distance is less than 1.1
# times the sum of the radii
print("cutoff ", ev)
pairs = bht.closePointsPairsInTree(ev)
bhtreelib.freeBHtree(bht)
# pairs is list of tuple of atom indices.
nbc = len(clusters)
bonds = {}
for i, pair in enumerate(pairs):
# 1- Get the atoms corresponding of the indices of the pair
cl1 = clusters[int(pair[0])]
cl2 = clusters[int(pair[1])]
head = cl1.centroid.coords
tail = cl2.centroid.coords
rad = cl1.radiusOfGyration() + factor * (
cl1.encapsualtingRadius() - cl1.radiusOfGyration()
) #or diameter ?
pinstance = self.helper.getObject("BC")
if pinstance is None:
pinstance = self.helper.Cylinder("BC",
radius=1.,
length=1.,
res=10,
pos=[0., 0., 0.],
parent=None)[0]
cyl = self.helper.getObject("clbond" + str(i))
if cyl is None:
cyl = self.helper.oneCylinder("clbond" + str(i),
head,
tail,
radius=rad,
instance=pinstance,
material=None,
parent=self.CenterSpheres,
color=colors[nbc])
else:
self.helper.updateOneCylinder("clbond" + str(i),
head,
tail,
radius=rad,
color=colors[nbc])
self.clusterCenterCyl["clbond" + str(i)] = [head, tail, rad]
if len(self.clusterCenterCyl) > len(pairs):
for j in range(len(pairs), len(self.clusterCenterCyl)):
# for cy in self.clusterCenterCyl[len(pair):]:
# o=self.clusterCenterCyl[]
self.helper.deleteObject("clbond" + str(j))
def pack_multi(env, ncpus=1,seedNum=14, stepByStep=False, verbose=False, sphGeom=None,
labDistGeom=None, debugFunc=None,name = None, vTestid = 3,vAnalysis = 0,**kw):
## Fill the grid by picking an ingredient first and then
## this filling should be able to continue from a previous one
## find a suitable point suing hte ingredient's placer object
self=env
import time
import pp
nparts = 2
job_server = pp.Server(ncpus=ncpus)
t1=time.time()
self.timeUpDistLoopTotal = 0 #Graham added to try to make universal "global variable Verbose" on Aug 28
self.static=[]
if self.grid is None:
print("no grid setup")
return
# create a list of active ingredients indices in all recipes to allow
# removing inactive ingredients when molarity is reached
allIngredients = self.callFunction(self.getActiveIng)
nbIngredients = len(allIngredients)
self.cFill = self.nFill
if name == None :
name = "F"+str(self.nFill)
self.FillName.append(name)
self.nFill+=1
# seed random number generator
SEED=seedNum
numpy.random.seed(SEED)#for gradient
seed(seedNum)
self.randomRot.setSeed(seed=seedNum)
# create copies of the distance array as they change when molecules
# are added, theses array can be restored/saved before feeling
freePoints = self.grid.freePoints[:]
nbFreePoints = len(freePoints)#-1
grab_callback = GrabResult(nbFreePoints,self)
grab_callback.freePoints=freePoints
# self.freePointMask = numpy.ones(nbFreePoints,dtype="int32")
if "fbox" in kw : # Oct 20, 2012 This is part of the code that is breaking the grids for all meshless organelle fills
self.fbox = kw["fbox"]
if self.fbox is not None and not self.EnviroOnly :
self.freePointMask = numpy.ones(nbFreePoints,dtype="int32")
bb_insidepoint = self.grid.getPointsInCube(self.fbox, [0,0,0], 1.0)[:]#center and radius ?3,runTime=self.runTimeDisplay
self.freePointMask[bb_insidepoint]=0
bb_outside = numpy.nonzero(self.freePointMask)
self.grid.gridPtId[bb_outside] = 99999
compId = self.grid.gridPtId
#why a copy? --> can we split ?
distance = self.grid.distToClosestSurf[:]
grab_callback.distance = distance
spacing = self.smallestProteinSize
# DEBUG stuff, should be removed later
self.jitterVectors = []
self.jitterLength = 0.0
self.totnbJitter = 0
self.maxColl = 0.0
self.successfullJitter = []
self.failedJitter = []
#this function also depend on the ingr.completiion that can be restored ?
self.activeIngr0, self.activeIngr12 = self.callFunction(self.getSortedActiveIngredients, (allIngredients,verbose))
print('len(allIngredients', len(allIngredients))
print('len(self.activeIngr0)', len(self.activeIngr0))
print('len(self.activeIngr12)', len(self.activeIngr12))
self.activeIngre_saved = self.activeIngr[:]
self.totalPriorities = 0 # 0.00001
for priors in self.activeIngr12:
pp = priors.packingPriority
self.totalPriorities = self.totalPriorities + pp
print('totalPriorities = ', self.totalPriorities)
previousThresh = 0
self.normalizedPriorities = []
self.thresholdPriorities = []
# Graham- Once negatives are used, if picked random#
# is below a number in this list, that item becomes
# the active ingredient in the while loop below
for priors in self.activeIngr0:
self.normalizedPriorities.append(0)
if self.pickWeightedIngr :#why ?
self.thresholdPriorities.append(2)
for priors in self.activeIngr12:
#pp1 = 0
pp = priors.packingPriority
if self.totalPriorities != 0:
np = float(pp)/float(self.totalPriorities)
else:
np=0.
self.normalizedPriorities.append(np)
print('np is ', np, ' pp is ', pp, ' tp is ', np + previousThresh)
self.thresholdPriorities.append(np + previousThresh)
previousThresh = np + float(previousThresh)
self.activeIngr = self.activeIngr0 + self.activeIngr12
nls=0
totalNumMols = 0
self.totalNbIngr = self.getTotalNbObject(allIngredients)
if len(self.thresholdPriorities ) == 0:
for ingr in allIngredients:
totalNumMols += ingr.nbMol
print('totalNumMols Fill5if = ', totalNumMols)
else :
for threshProb in self.thresholdPriorities:
nameMe = self.activeIngr[nls]
print('threshprop Fill5else is %f for ingredient: %s %s %d'%(threshProb, nameMe,nameMe.name,nameMe.nbMol))
totalNumMols += nameMe.nbMol
print('totalNumMols Fill5else = ', totalNumMols)
nls+=1
print ("tobj = ",self.totalNbIngr)
a=numpy.ones((self.totalNbIngr,3))*999999999.9#*100.0#max ingredient excepted.
vRangeStart = 0.0
tCancelPrev=time.time()
test = True
kk=0
ptInd = 0
PlacedMols = 0
vThreshStart = 0.0 # Added back by Graham on July 5, 2012 from Sept 25, 2011 thesis version
#if bullet build the organel rbnode
if self.placeMethod == "pandaBullet":
self.setupPanda()
for o in self.organelles:
if o.rbnode is None :
o.rbnode = self.addMeshRBOrganelle(o)
#==============================================================================
# #the big loop
#==============================================================================
#self.largestProteinSize = 0 #before starting reset largest size
self.grabedvalue=[]
while nbFreePoints:
#breakin test
print ("nbFreePoints",nbFreePoints,len(self.activeIngr),vRangeStart)
if len(self.activeIngr)==0:
print('broken by len****')
break
if vRangeStart>1:
print('broken by vRange and hence Done!!!****')
break
#we do two pass by dividing the grid on Y by 2*ncpus
for p in range(nparts):
print ("pass n ",p)
grab_callback.reset(grab_callback.nbFreePoints)
picked_ingredients=[]
for n in range(ncpus):
print ("prepare job",n)
ingr = self.callFunction(self.pickIngredient,(vThreshStart,))
picked_ingredients.append(ingr)
compNum = ingr.compNum
radius = ingr.minRadius
jitter = self.callFunction(ingr.getMaxJitter,(spacing,))
# compute dpad which is the distance at which we need to update
# distances after the drop is successfull
mr = self.get_dpad(compNum)
dpad = ingr.minRadius + mr + jitter
## find the points that can be used for this ingredients
## in the slice ?
res=self.callFunction(self.getPointToDrop,(ingr,radius,jitter,
freePoints,nbFreePoints,
distance,compId,compNum,vRangeStart,vThreshStart))
# distance,compId,compNum,vRangeStart)) # Replaced this with Sept 25, 2011 thesis version on July 5, 2012
print ("pick",ingr,res)
if res[0] :
ptInd = res[1]
if ptInd > len(distance):
print ("problem ",ptInd)
continue
else :
print ("vRangeStart coninue ",res)
vRangeStart = res[1]
continue
# continue
# print ("picked ",ptInd)
#place the ingrediant
if self.overwritePlaceMethod :
ingr.placeType = self.placeMethod
#check the largestProteinSize
#worker ?
if ingr.encapsulatingRadius > self.largestProteinSize :
self.largestProteinSize = ingr.encapsulatingRadius
print ("submit job",n)
p=job_server.submit(ingr.place_mp,(self, ptInd,
freePoints, nbFreePoints, distance, dpad,True,
stepByStep, verbose), modules=("AutoFill",),
callback=grab_callback.add)
# success, nbFreePoints = self.callFunction(ingr.place,(self, ptInd,
# freePoints, nbFreePoints, distance, dpad,
# stepByStep, verbose),
# {"debugFunc":debugFunc})
print ("after place nbFreePoints",nbFreePoints)
job_server.wait()
#grab result
results=grab_callback.queue[:]#success, nbFreePoints
# print ("results",results)
nbFreePoints=grab_callback.nbFreePoints
print ("cumul freePts",grab_callback.nbFreePoints)
#need to cumul freepoints and distance
distance = grab_callback.distance[:]
freePoints = grab_callback.freePoints[:]
# self.molecules = grab_callback.molecules[:]
# self.grabedvalue.append(grab_callback.queue[:])
for n in range(ncpus):
# print("nbFreePoints after PLACE ",nbFreePoints)
ingr = picked_ingredients[n]
success = results[n][0]
# nbFreePoints = results[n][1]
if success:
if ingr.encapsulatingRadius > self.largestProteinSize :
self.largestProteinSize = ingr.encapsulatingRadius
PlacedMols+=1
print ("ingr",ingr.completion,ingr.name)
if ingr.completion >= 1.0 :
ind = self.activeIngr.index(ingr)
if ind > 0:
#j = 0
for j in range(ind):
if j >= len(self.thresholdPriorities) or j >= len(self.normalizedPriorities):
continue
self.thresholdPriorities[j] = self.thresholdPriorities[j] + self.normalizedPriorities[ind]
self.activeIngr.pop(ind)
self.activeIngr0, self.activeIngr12 = self.callFunction(self.getSortedActiveIngredients, (self.activeIngr,verbose))
self.activeIngre_saved = self.activeIngr[:]
self.totalPriorities = 0 # 0.00001
for priors in self.activeIngr12:
pp = priors.packingPriority
self.totalPriorities = self.totalPriorities + pp
previousThresh = 0
self.normalizedPriorities = []
self.thresholdPriorities = []
# Graham- Once negatives are used, if picked random#
# is below a number in this list, that item becomes
#the active ingredient in the while loop below
for priors in self.activeIngr0:
self.normalizedPriorities.append(0)
if self.pickWeightedIngr :
self.thresholdPriorities.append(2)
for priors in self.activeIngr12:
#pp1 = 0
pp = priors.packingPriority
if self.totalPriorities != 0:
np = float(pp)/float(self.totalPriorities)
else:
np=0.
self.normalizedPriorities.append(np)
self.thresholdPriorities.append(np + previousThresh)
previousThresh = np + float(previousThresh)
self.activeIngr = self.activeIngr0 + self.activeIngr12
#end for part
# break
self.distancesAfterFill = distance
self.freePointsAfterFill = freePoints
self.nbFreePointsAfterFill = nbFreePoints
self.distanceAfterFill = distance
t2 = time.time()
print('time to fill', t2-t1)
if self.saveResult:
self.grid.freePoints = freePoints[:]
self.grid.distToClosestSurf = distance[:]
#shoul check extension filename for type of saved file
self.saveGridToFile(self.resultfile+"grid")
self.grid.result_filename = self.resultfile+"grid"
self.store()
self.store_asTxt()
self.store_asJson()
print('time to save end', time.time()-t2)
ingredients ={}
for pos, rot, ingr, ptInd in self.molecules:
if ingr.name not in ingredients :
ingredients[ingr.name]=[ingr,[],[],[]]
mat = rot.copy()
mat[:3, 3] = pos
ingredients[ingr.name][1].append(pos)
ingredients[ingr.name][2].append(rot)
ingredients[ingr.name][3].append(numpy.array(mat))
for o in self.organelles:
for pos, rot, ingr, ptInd in o.molecules:
if ingr.name not in ingredients :
ingredients[ingr.name]=[ingr,[],[],[]]
mat = rot.copy()
mat[:3, 3] = pos
ingredients[ingr.name][1].append(pos)
ingredients[ingr.name][2].append(rot)
ingredients[ingr.name][3].append(numpy.array(mat))
self.ingr_result = ingredients
if self.treemode == "bhtree" :
from bhtree import bhtreelib
bhtreelib.freeBHtree(self.close_ingr_bhtree)
def pack_multi(env,
ncpus=1,
seedNum=14,
stepByStep=False,
verbose=False,
sphGeom=None,
labDistGeom=None,
debugFunc=None,
name=None,
vTestid=3,
vAnalysis=0,
**kw):
## Fill the grid by picking an ingredient first and then
## this filling should be able to continue from a previous one
## find a suitable point suing hte ingredient's placer object
self = env
import time
import pp
nparts = 2
job_server = pp.Server(ncpus=ncpus)
t1 = time.time()
self.timeUpDistLoopTotal = 0 #Graham added to try to make universal "global variable Verbose" on Aug 28
self.static = []
if self.grid is None:
print("no grid setup")
return
# create a list of active ingredients indices in all recipes to allow
# removing inactive ingredients when molarity is reached
allIngredients = self.callFunction(self.getActiveIng)
nbIngredients = len(allIngredients)
self.cFill = self.nFill
if name == None:
name = "F" + str(self.nFill)
self.FillName.append(name)
self.nFill += 1
# seed random number generator
SEED = seedNum
numpy.random.seed(SEED) #for gradient
seed(seedNum)
self.randomRot.setSeed(seed=seedNum)
# create copies of the distance array as they change when molecules
# are added, theses array can be restored/saved before feeling
freePoints = self.grid.freePoints[:]
nbFreePoints = len(freePoints) #-1
grab_callback = GrabResult(nbFreePoints, self)
grab_callback.freePoints = freePoints
# self.freePointMask = numpy.ones(nbFreePoints,dtype="int32")
if "fbox" in kw: # Oct 20, 2012 This is part of the code that is breaking the grids for all meshless organelle fills
self.fbox = kw["fbox"]
if self.fbox is not None and not self.EnviroOnly:
self.freePointMask = numpy.ones(nbFreePoints, dtype="int32")
bb_insidepoint = self.grid.getPointsInCube(
self.fbox, [0, 0, 0],
1.0)[:] #center and radius ?3,runTime=self.runTimeDisplay
self.freePointMask[bb_insidepoint] = 0
bb_outside = numpy.nonzero(self.freePointMask)
self.grid.gridPtId[bb_outside] = 99999
compId = self.grid.gridPtId
#why a copy? --> can we split ?
distance = self.grid.distToClosestSurf[:]
grab_callback.distance = distance
spacing = self.smallestProteinSize
# DEBUG stuff, should be removed later
self.jitterVectors = []
self.jitterLength = 0.0
self.totnbJitter = 0
self.maxColl = 0.0
self.successfullJitter = []
self.failedJitter = []
#this function also depend on the ingr.completiion that can be restored ?
self.activeIngr0, self.activeIngr12 = self.callFunction(
self.getSortedActiveIngredients, (allIngredients, verbose))
print('len(allIngredients', len(allIngredients))
print('len(self.activeIngr0)', len(self.activeIngr0))
print('len(self.activeIngr12)', len(self.activeIngr12))
self.activeIngre_saved = self.activeIngr[:]
self.totalPriorities = 0 # 0.00001
for priors in self.activeIngr12:
pp = priors.packingPriority
self.totalPriorities = self.totalPriorities + pp
print('totalPriorities = ', self.totalPriorities)
previousThresh = 0
self.normalizedPriorities = []
self.thresholdPriorities = []
# Graham- Once negatives are used, if picked random#
# is below a number in this list, that item becomes
# the active ingredient in the while loop below
for priors in self.activeIngr0:
self.normalizedPriorities.append(0)
if self.pickWeightedIngr: #why ?
self.thresholdPriorities.append(2)
for priors in self.activeIngr12:
#pp1 = 0
pp = priors.packingPriority
if self.totalPriorities != 0:
np = float(pp) / float(self.totalPriorities)
else:
np = 0.
self.normalizedPriorities.append(np)
print('np is ', np, ' pp is ', pp, ' tp is ', np + previousThresh)
self.thresholdPriorities.append(np + previousThresh)
previousThresh = np + float(previousThresh)
self.activeIngr = self.activeIngr0 + self.activeIngr12
nls = 0
totalNumMols = 0
self.totalNbIngr = self.getTotalNbObject(allIngredients)
if len(self.thresholdPriorities) == 0:
for ingr in allIngredients:
totalNumMols += ingr.nbMol
print('totalNumMols Fill5if = ', totalNumMols)
else:
for threshProb in self.thresholdPriorities:
nameMe = self.activeIngr[nls]
print('threshprop Fill5else is %f for ingredient: %s %s %d' %
(threshProb, nameMe, nameMe.name, nameMe.nbMol))
totalNumMols += nameMe.nbMol
print('totalNumMols Fill5else = ', totalNumMols)
nls += 1
print("tobj = ", self.totalNbIngr)
a = numpy.ones(
(self.totalNbIngr, 3)) * 999999999.9 #*100.0#max ingredient excepted.
vRangeStart = 0.0
tCancelPrev = time.time()
test = True
kk = 0
ptInd = 0
PlacedMols = 0
vThreshStart = 0.0 # Added back by Graham on July 5, 2012 from Sept 25, 2011 thesis version
#if bullet build the organel rbnode
if self.placeMethod == "pandaBullet":
self.setupPanda()
for o in self.organelles:
if o.rbnode is None:
o.rbnode = self.addMeshRBOrganelle(o)
#==============================================================================
# #the big loop
#==============================================================================
#self.largestProteinSize = 0 #before starting reset largest size
self.grabedvalue = []
while nbFreePoints:
#breakin test
print("nbFreePoints", nbFreePoints, len(self.activeIngr), vRangeStart)
if len(self.activeIngr) == 0:
print('broken by len****')
break
if vRangeStart > 1:
print('broken by vRange and hence Done!!!****')
break
#we do two pass by dividing the grid on Y by 2*ncpus
for p in range(nparts):
print("pass n ", p)
grab_callback.reset(grab_callback.nbFreePoints)
picked_ingredients = []
for n in range(ncpus):
print("prepare job", n)
ingr = self.callFunction(self.pickIngredient, (vThreshStart, ))
picked_ingredients.append(ingr)
compNum = ingr.compNum
radius = ingr.minRadius
jitter = self.callFunction(ingr.getMaxJitter, (spacing, ))
# compute dpad which is the distance at which we need to update
# distances after the drop is successfull
mr = self.get_dpad(compNum)
dpad = ingr.minRadius + mr + jitter
## find the points that can be used for this ingredients
## in the slice ?
res = self.callFunction(
self.getPointToDrop,
(ingr, radius, jitter, freePoints, nbFreePoints, distance,
compId, compNum, vRangeStart, vThreshStart))
# distance,compId,compNum,vRangeStart)) # Replaced this with Sept 25, 2011 thesis version on July 5, 2012
print("pick", ingr, res)
if res[0]:
ptInd = res[1]
if ptInd > len(distance):
print("problem ", ptInd)
continue
else:
print("vRangeStart coninue ", res)
vRangeStart = res[1]
continue
# continue
# print ("picked ",ptInd)
#place the ingrediant
if self.overwritePlaceMethod:
ingr.placeType = self.placeMethod
#check the largestProteinSize
#worker ?
if ingr.encapsulatingRadius > self.largestProteinSize:
self.largestProteinSize = ingr.encapsulatingRadius
print("submit job", n)
p = job_server.submit(
ingr.place_mp, (self, ptInd, freePoints, nbFreePoints,
distance, dpad, True, stepByStep, verbose),
modules=("AutoFill", ),
callback=grab_callback.add)
# success, nbFreePoints = self.callFunction(ingr.place,(self, ptInd,
# freePoints, nbFreePoints, distance, dpad,
# stepByStep, verbose),
# {"debugFunc":debugFunc})
print("after place nbFreePoints", nbFreePoints)
job_server.wait()
#grab result
results = grab_callback.queue[:] #success, nbFreePoints
# print ("results",results)
nbFreePoints = grab_callback.nbFreePoints
print("cumul freePts", grab_callback.nbFreePoints)
#need to cumul freepoints and distance
distance = grab_callback.distance[:]
freePoints = grab_callback.freePoints[:]
# self.molecules = grab_callback.molecules[:]
# self.grabedvalue.append(grab_callback.queue[:])
for n in range(ncpus):
# print("nbFreePoints after PLACE ",nbFreePoints)
ingr = picked_ingredients[n]
success = results[n][0]
# nbFreePoints = results[n][1]
if success:
if ingr.encapsulatingRadius > self.largestProteinSize:
self.largestProteinSize = ingr.encapsulatingRadius
PlacedMols += 1
print("ingr", ingr.completion, ingr.name)
if ingr.completion >= 1.0:
ind = self.activeIngr.index(ingr)
if ind > 0:
#j = 0
for j in range(ind):
if j >= len(self.thresholdPriorities) or j >= len(
self.normalizedPriorities):
continue
self.thresholdPriorities[
j] = self.thresholdPriorities[
j] + self.normalizedPriorities[ind]
self.activeIngr.pop(ind)
self.activeIngr0, self.activeIngr12 = self.callFunction(
self.getSortedActiveIngredients,
(self.activeIngr, verbose))
self.activeIngre_saved = self.activeIngr[:]
self.totalPriorities = 0 # 0.00001
for priors in self.activeIngr12:
pp = priors.packingPriority
self.totalPriorities = self.totalPriorities + pp
previousThresh = 0
self.normalizedPriorities = []
self.thresholdPriorities = []
# Graham- Once negatives are used, if picked random#
# is below a number in this list, that item becomes
#the active ingredient in the while loop below
for priors in self.activeIngr0:
self.normalizedPriorities.append(0)
if self.pickWeightedIngr:
self.thresholdPriorities.append(2)
for priors in self.activeIngr12:
#pp1 = 0
pp = priors.packingPriority
if self.totalPriorities != 0:
np = float(pp) / float(self.totalPriorities)
else:
np = 0.
self.normalizedPriorities.append(np)
self.thresholdPriorities.append(np + previousThresh)
previousThresh = np + float(previousThresh)
self.activeIngr = self.activeIngr0 + self.activeIngr12
#end for part
# break
self.distancesAfterFill = distance
self.freePointsAfterFill = freePoints
self.nbFreePointsAfterFill = nbFreePoints
self.distanceAfterFill = distance
t2 = time.time()
print('time to fill', t2 - t1)
if self.saveResult:
self.grid.freePoints = freePoints[:]
self.grid.distToClosestSurf = distance[:]
#shoul check extension filename for type of saved file
self.saveGridToFile(self.resultfile + "grid")
self.grid.result_filename = self.resultfile + "grid"
self.store()
self.store_asTxt()
self.store_asJson()
print('time to save end', time.time() - t2)
ingredients = {}
for pos, rot, ingr, ptInd in self.molecules:
if ingr.name not in ingredients:
ingredients[ingr.name] = [ingr, [], [], []]
mat = rot.copy()
mat[:3, 3] = pos
ingredients[ingr.name][1].append(pos)
ingredients[ingr.name][2].append(rot)
ingredients[ingr.name][3].append(numpy.array(mat))
for o in self.organelles:
for pos, rot, ingr, ptInd in o.molecules:
if ingr.name not in ingredients:
ingredients[ingr.name] = [ingr, [], [], []]
mat = rot.copy()
mat[:3, 3] = pos
ingredients[ingr.name][1].append(pos)
ingredients[ingr.name][2].append(rot)
ingredients[ingr.name][3].append(numpy.array(mat))
self.ingr_result = ingredients
if self.treemode == "bhtree":
from bhtree import bhtreelib
bhtreelib.freeBHtree(self.close_ingr_bhtree)