def binning(traj=None,bins=20,segment=None,delta_x=None,prec=None):
if segment==None:
opt_range=0
mmx=0.0
mmn=0.0
else:
opt_range=1
mmn=segment[0]
mmx=segment[1]
if delta_x==None:
opt_delta_x=0
delta_x=1.0
else:
opt_delta_x=1
if traj==None:
o_delta_x=fort_math.binning_x(opt_range,opt,bins,mmn,mmx,delta_x)
h_x=copy.deepcopy(fort_math.histo_x)
fort_math.free_mem()
return h_x
else:
tray_bins=fort_math.binning(opt_range,opt_delta_x,traj,bins,mmn,mmx,delta_x,len(traj))
h_x=copy.deepcopy(fort_math.histo_x)
fort_math.free_mem()
return h_x,tray_bins
def histogram_mask(traj,bins=20,segment=None,delta=None,select_dim=0,traj_mask=None,select_mask=None,offset_mask=None,norm=False,cumul=False):
traj=standard_traj(traj)
traj_mask=standard_traj(traj_mask)
opt_norm=0
if norm:
opt_norm=1
opt_cumul=0
if cumul:
opt_cumul=1
bins,mmx,mmn,delta=parameters_bins(traj,bins,segment,delta)
if type(select_mask) in [int]:
select_mask=[select_mask]
select_mask=numpy.array(select_mask,dtype=int,order='F')
select_dim+=1
fort_math.histogram1d_mask(opt_norm,opt_cumul,traj,bins,mmn,mmx,delta,select_dim,\
traj_mask,select_mask,offset_mask,traj_mask.shape[0],select_mask.shape[0],\
traj.shape[0],traj.shape[1],traj.shape[2])
h_x=copy.deepcopy(fort_math.histo_x)
h_y=copy.deepcopy(fort_math.histo_y)
fort_math.free_mem()
return h_x,h_y
def histogram(traj,bins=20,segment=None,delta=None,select_dim=0,norm=False,cumul=False,in_file=False,by_frame=False):
infile=in_file
opt_norm=0
if norm:
opt_norm=1
opt_cumul=0
if cumul:
opt_cumul=1
if by_frame:
print '# Not implemented yet.'
return
else:
if infile:
infile.unit=len(pyn_f90units)+100
pyn_f90units.append(infile.unit)
select_dim+=1
bins,mmx,mmn,delta=parameters_bins(False,bins,segment,delta)
fort_math.histogram1d_infile(infile.name,infile.binary,infile.unit,opt_norm,opt_cumul,bins,mmn,mmx,delta,select_dim,\
in_file.frames,in_file.particles,in_file.dimensions)
h_x=copy.deepcopy(fort_math.histo_x)
h_y=copy.deepcopy(fort_math.histo_y)
fort_math.free_mem()
pyn_f90units.remove(infile.unit)
infile.unit=None
return h_x,h_y
else:
traj=standard_traj(traj)
bins,mmx,mmn,delta=parameters_bins(traj,bins,segment,delta)
select_dim+=1
fort_math.histogram1d(opt_norm,opt_cumul,traj,bins,mmn,mmx,delta,select_dim,\
traj.shape[0],traj.shape[1],traj.shape[2])
h_x=copy.deepcopy(fort_math.histo_x)
h_y=copy.deepcopy(fort_math.histo_y)
fort_math.free_mem()
return h_x,h_y
def histogram2D(traj,bins=[20,20],segment=None,delta_x=None,prec=None,norm=False,plot=False):
leng=len(traj)
if norm==False:
opt_norm=0
else:
opt_norm=1
if prec==None:
opt_prec=0
prec=1.0
else:
opt_prec=1
if segment==None:
opt_range=0
mmx0=max(traj[:,0])
mmx1=max(traj[:,1])
mmn0=min(traj[:,0])
mmn1=min(traj[:,1])
else:
opt_range=1
mmn0=segment[0][0]
mmn1=segment[1][0]
mmx0=segment[0][1]
mmx1=segment[1][1]
if delta_x!=None:
opt=1
else:
delta_x=[1.0,1.0]
opt=2
fort_math.histograma_2d(opt_norm,opt_prec,opt_range,opt,traj,bins,[mmn0,mmn1],[mmx0,mmx1],delta_x,prec,leng)
h_x=copy.deepcopy(fort_math.histo_x)
h_y=copy.deepcopy(fort_math.histo_y)
h_z=copy.deepcopy(fort_math.histo_z)
fort_math.free_mem()
if plot and wpylab:
pylab.plot(h_x,h_y,'ro-')
return h_x,h_y,h_z
