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#This file is part of QuTIP.
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# QuTIP is free software: you can redistribute it and/or modify
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# it under the terms of the GNU General Public License as published by
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# the Free Software Foundation, either version 3 of the License, or
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# (at your option) any later version.
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# QuTIP is distributed in the hope that it will be useful,
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# but WITHOUT ANY WARRANTY; without even the implied warranty of
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# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
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# GNU General Public License for more details.
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# You should have received a copy of the GNU General Public License
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# along with QuTIP. If not, see <http://www.gnu.org/licenses/>.
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# Copyright (C) 2011, Paul D. Nation & Robert J. Johansson
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###########################################################################
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__array_priority__=101
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def __init__(self,q=array([]),s=array([])):
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if (not any(q)) and (not any(s)):
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if any(q) and (not any(s)):
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if isinstance(q,eseries):
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elif isinstance(q,(ndarray,list)):
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num=ind[0] #number of elements in q
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#sh=array([qobj(x).shape for x in range(0,num)])
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sh=array([qobj(x).shape for x in q])
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raise TypeError('All amplitudes must have same dimension.')
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#self.ampl=array([qobj(x) for x in q])
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self.ampl=array([x for x in q])
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self.dims=self.ampl[0].dims
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self.shape=self.ampl[0].shape
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elif isinstance(q,qobj):
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self.ampl = array([q])
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self.rates = array([0])
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if isinstance(q,(ndarray,list)):
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sh=array([qobj(q[x]).shape for x in range(0,num)])
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raise TypeError('All amplitudes must have same dimension.')
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self.ampl=array([qobj(q[x]) for x in range(0,num)])
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self.dims=self.ampl[0].dims
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self.shape=self.ampl[0].shape
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self.ampl=array([qobj(q)])
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self.dims=self.ampl[0].dims
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self.shape=self.ampl[0].shape
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if isinstance(s,(int,complex,float)):
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raise TypeError('Number of rates must match number of members in object array.')
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elif isinstance(s,(ndarray,list)):
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raise TypeError('Number of rates must match number of members in object array.')
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zipped=zip(self.rates,self.ampl)#combine arrays so that they can be sorted together
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zipped.sort() #sort rates from lowest to highest
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rates,ampl=zip(*zipped) #get back rates and ampl
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self.rates=array(rates)
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######___END_INIT___######################
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##########################################
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def __str__(self):#string of ESERIES information
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print "ESERIES object: "+str(len(self.ampl))+" terms"
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print "Hilbert space dimensions: "+str(self.dims)
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for k in range(0,len(self.ampl)):
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print "Exponent #"+str(k)+" = "+str(self.rates[k])
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if isinstance(self.ampl[k], sp.spmatrix):
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print self.ampl[k].full()
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def __add__(self,other):#Addition with ESERIES on left (ex. ESERIES+5)
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if self.dims!=right.dims:
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raise TypeError("Incompatible operands for ESERIES addition")
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out.ampl=append(self.ampl,right.ampl)
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out.rates=append(self.rates,right.rates)
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def __radd__(self,other):#Addition with ESERIES on right (ex. 5+ESERIES)
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def __neg__(self):#define negation of ESERIES
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def __sub__(self,other):#Subtraction with ESERIES on left (ex. ESERIES-5)
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def __rsub__(self,other):#Subtraction with ESERIES on right (ex. 5-ESERIES)
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def __mul__(self,other):#Multiplication with ESERIES on left (ex. ESERIES*other)
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if isinstance(other,eseries):
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for i in range(len(self.rates)):
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for j in range(len(other.rates)):
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out += eseries(self.ampl[i] * other.ampl[j], self.rates[i] + other.rates[j])
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out.ampl=self.ampl * other
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def __rmul__(self,other): #Multiplication with ESERIES on right (ex. other*ESERIES)
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out.ampl=other * self.ampl
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# select_ampl, select_rate: functions to select some terms given the ampl
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# or rate. This is done with {ampl} or (rate) in qotoolbox. we should use
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# functions with descriptive names for this.
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def esval(es, tlist):
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Evaluate an exponential series at the times listed in tlist.
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#val_list = [] #zeros(size(tlist))
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val_list = zeros(size(tlist))
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for j in range(len(tlist)):
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exp_factors = exp(array(es.rates) * tlist[j])
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#for i in range(len(es.ampl)):
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# val += es.ampl[i] * exp_factors[i]
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val_list[j] = sum(dot(es.ampl, exp_factors))
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#val_list.append(val)
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def esspec(es, wlist):
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Evaluate the spectrum of an exponential series at frequencies in wlist.
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val_list = zeros(size(wlist))
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for i in range(len(wlist)):
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#print "data =", es.ampl
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#print "demon =", 1/(1j*wlist[i] - es.rates)
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val_list[i] = 2 * real( dot(es.ampl, 1/(1j*wlist[i] - es.rates)) )
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##########---ESERIES TIDY---#############################
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def estidy(es,*args):
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#zipped=zip(es.rates,es.ampl)#combine arrays so that they can be sorted together
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#zipped.sort() #sort rates from lowest to highest
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out.dims = es.ampl[0].dims
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out.shape = es.ampl[0].shape
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# determine the tolerance
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tol1=array([1e-6,1e-6])
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tol2=array([1e-6,1e-6])
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tol2=array([1e-6,1e-6])
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rmax=max(abs(array(rates)))
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tol=max(tol1[0]*rmax,tol1[1])
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# find unique rates (todo: allow deviations within tolerance)
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rates_unique = sort(list(set(rates)))
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# collect terms that have the same rates (within the tolerance)
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for r in rates_unique:
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for idx,rate in enumerate(rates):
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if abs(rate - r) < tol:
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terms += es.ampl[idx]
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if terms.norm() > tol:
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out.ampl.append(terms)
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###########---Find Groups---####################
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def findgroups(values,index,tol):
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zipped=zip(values,index)#combine arrays so that they can be sorted together
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zipped.sort() #sort rates from lowest to highest
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vs,vperm=zip(*zipped)
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big=where(diff(vs)>tol,1,0)
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sgroup=append(array([1]),big)
added
removed
qutip/eseries.py
