def fpt (self, node_origin, node_sink, num_runs=200, option='mean', bins=20, segment=None, delta_x=None,norm=None):
"""option=['mean','distribution','both','raw']"""
if self.Ts==False :
self.build_Ts()
scratch=[]
for ii in range(num_runs):
iseed=numpy.random.random_integers(0,4094,4)
iseed[3]=(iseed[3]/2)*2+1
aa=f_net.brownian_run_fpt(self.T_start,self.T_ind,self.T_wl,iseed,node_origin,node_sink,self.num_nodes,self.k_total)
scratch.append(aa)
if option in ['distribution','both']:
xx,yy=pyn_math.histogram(scratch,bins,segment,delta_x,None,norm,plot=False)
if option in ['mean','both']:
yy_av,yy_sigma=pyn_math.average(scratch)
if option=='distribution': return xx,yy
if option=='mean': return yy_av, yy_sigma
if option=='both': return yy_av, yy_sigma, xx,yy
if option=='raw': return scratch
pass
def k_distribution (self, option='out', bins=20, segment=None, delta_x=None,norm=None):
""" option=['total','in','out']"""
for ii in self.node:
ii.k_out=len(ii.link)
scratch=[]
if option=='out':
for ii in self.node:
scratch.append(ii.k_out)
xx,yy=pyn_math.histogram(scratch,bins,segment,delta_x,None,norm,plot=False)
return xx, yy
def histogram(self,dimension=None,node=None,cluster=None,bins=20,segment=None,delta=None,select_dim=0,norm=False,cumul=False):
if cluster==None and node==None:
return pyn_math.histogram(self.traj,bins=bins,segment=segment,delta=delta,select_dim=select_dim,norm=norm,cumul=cumul)
if cluster!=None:
xx,yy=pyn_math.histogram_mask(self.traj,bins=bins,segment=segment,delta=delta,select_dim=select_dim,\
traj_mask=self.traj_clusters,select_mask=cluster,offset_mask=self.__offset__,\
norm=norm,cumul=cumul)
return xx,yy
if node!=None:
xx,yy=pyn_math.histogram_mask(self.traj,bins=bins,segment=segment,delta=delta,select_dim=select_dim,\
traj_mask=self.traj_nodes,select_mask=node,offset_mask=self.__offset__,\
norm=norm,cumul=cumul)
return xx,yy
def weight_distribution (self, option='all', bins=20, segment=None, delta_x=None,norm=None):
"""option=['all','self_links','all-self_links','links'] (I have to do the same for the links of a node)"""
scratch=[]
if option=='all':
for ii in self.node:
scratch.append(ii.weight)
if option=='self_links':
for ii in range(self.num_nodes):
scratch.append(self.node[ii].link[ii])
if option=='all-self_links':
for ii in range(self.num_nodes):
scratch.append(self.node[ii].weight-self.node[ii].link[ii])
xx,yy=pyn_math.histogram(scratch,bins,segment,delta_x,None,norm,plot=False)
return xx, yy
def histogram(
self,
dimension=None,
node=None,
cluster=None,
bins=20,
segment=None,
delta=None,
select_dim=0,
norm=False,
cumul=False,
):
if cluster == None and node == None:
if self.__tr_mode_in_file__:
return pyn_math.histogram(
self.traj,
bins=bins,
segment=segment,
delta=delta,
select_dim=select_dim,
norm=norm,
cumul=cumul,
in_file=self.file_traj,
by_frame=self.__tr_mode_by_frame__,
)
else:
return pyn_math.histogram(
self.traj,
bins=bins,
segment=segment,
delta=delta,
select_dim=select_dim,
norm=norm,
cumul=cumul,
in_file=False,
by_frame=self.__tr_mode_by_frame__,
)
if cluster != None:
return pyn_math.histogram_mask(
self.traj,
bins=bins,
segment=segment,
delta=delta,
select_dim=select_dim,
traj_mask=self.traj_clusters,
select_mask=cluster,
offset_mask=self.__offset__,
norm=norm,
cumul=cumul,
)
if node != None:
return pyn_math.histogram_mask(
self.traj,
bins=bins,
segment=segment,
delta=delta,
select_dim=select_dim,
traj_mask=self.traj_nodes,
select_mask=node,
offset_mask=self.__offset__,
norm=norm,
cumul=cumul,
)
