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dft_tools/pytriqs/gf/local/_gf_common.py

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2014-05-09 10:43:55 +02:00
################################################################################
#
# TRIQS: a Toolbox for Research in Interacting Quantum Systems
#
# Copyright (C) 2011-2012 by M. Ferrero, O. Parcollet
#
# TRIQS is free software: you can redistribute it and/or modify it under the
# terms of the GNU General Public License as published by the Free Software
# Foundation, either version 3 of the License, or (at your option) any later
# version.
#
# TRIQS is distributed in the hope that it will be useful, but WITHOUT ANY
# WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS
# FOR A PARTICULAR PURPOSE. See the GNU General Public License for more
# details.
#
# You should have received a copy of the GNU General Public License along with
# TRIQS. If not, see <http://www.gnu.org/licenses/>.
#
################################################################################
import numpy
import lazy_expressions, descriptor_base
#from gf import MeshImFreq
from types import IntType, SliceType, StringType
from tools import LazyCTX #, IndicesConverter, get_indices_in_dict, py_deserialize
from _gf_plot import PlotWrapperPartialReduce
#from gf import TailGf
#--------------------- [ ] operator ------------------------------------------
def __getitem__(self, key):
"""Key is a tuple of index (n1, n2) as defined at construction"""
if len(key) !=2: raise KeyError, "[ ] must be given two arguments"
sl1, sl2 = key
if type(sl1) == StringType and type(sl2) == StringType:
# Convert the indices to integer
indices_converter = [ IndicesConverter(self.indicesL), IndicesConverter(self.indicesR)]
sl1, sl2 = [ indices_converter[i].convertToNumpyIndex(k) for i, k in enumerate(key) ]
if type (sl1) != slice: sl1 = slice (sl1, sl1+1)
if type (sl2) != slice: sl2 = slice (sl2, sl2+1)
return self.__class__(indicesL = list(self.indicesL)[sl1],
indicesR = list(self.indicesR)[sl2],
name = self.name,
mesh = self.mesh,
data = self.data[:,sl1,sl2],
tail = self.tail._make_slice(sl1, sl2))
def __setitem__(self, key, val):
g = self.__getitem__(key)
g <<= val
#-------------- PLOT ---------------------------------------
def _real_plot(self):
"""Use self.real in a plot to plot only the real part"""
return PlotWrapperPartialReduce(self, RI='R')
def _imag_plot(self):
"""Use self.imag in a plot to plot only the imag part"""
return PlotWrapperPartialReduce(self, RI='I')
#-------- LAZY expression system -----------------------------------------
def add_precall (self, y):
if descriptor_base.is_lazy(y): return lazy_expressions.make_lazy(self) + y
def sub_precall (self, y):
if descriptor_base.is_lazy(y): return lazy_expressions.make_lazy(self) - y
def mul_precall (self, y):
if descriptor_base.is_lazy(y): return lazy_expressions.make_lazy(self) * y
def div_precall (self, y):
if descriptor_base.is_lazy(y): return lazy_expressions.make_lazy(self) / y
def _ilshift_(self, A):
""" A can be two things:
* G <<= any_init will init the GFBloc with the initializer
* G <<= g2 where g2 is a GFBloc will copy g2 into self
"""
import descriptors
if isinstance(A, self.__class__):
if self is not A: self.copy_from(A) # otherwise it is useless AND does not work !!
elif isinstance(A, lazy_expressions.LazyExpr): # A is a lazy_expression made of GF, scalars, descriptors
A2= descriptors.convert_scalar_to_const(A)
def e_t (x):
if not isinstance(x, descriptors.Base): return x
tmp = self.copy()
x(tmp)
return tmp
self.copy_from (lazy_expressions.eval_expr_with_context(e_t, A2) )
elif isinstance(A, lazy_expressions.LazyExprTerminal): #e.g. g<<= SemiCircular (...)
self <<= lazy_expressions.LazyExpr(A)
elif descriptors.is_scalar(A): #in the case it is a scalar ....
self <<= lazy_expressions.LazyExpr(A)
else:
raise RuntimeError, " <<= operator: RHS not understood"
return self
#---------------------------------------------------
def from_L_G_R(self, L, G, R):
N1 = self.data.shape[1]
N2 = self.data.shape[2]
assert L.shape[0] == N1
assert L.shape[1] == G.data.shape[1]
assert R.shape[0] == G.data.shape[2]
assert R.shape[1] == N2
MatrixStack(self.data).matmul_L_R(L, G.data, R)
# this might be a bit slow
for o in range(G.tail.order_min, G.tail.order_max+1):
self.tail[o] = numpy.dot(L, numpy.dot(G.tail[o], R))
self.tail.mask.fill(G.tail.order_max)
#---------------------------------------------------
def invert(self):
"""Invert the matrix for all arguments"""
MatrixStack(self.data).invert()
self.tail.invert()
#---------------------------------------------------
# FIXME NEVER USED CLEAN UP
#def transpose(self):
# """Transposes the GF Bloc: return a new transposed view"""
# ### WARNING: this depends on the C++ layering ....
# return self.__class__(
# indices = list(self.indices),
# mesh = self.mesh,
# data = self.data.transpose( (0, 2, 1) ),
# tail = self.tail.transpose(),
# name = self.name+'(t)')
2014-05-09 10:43:55 +02:00
#---------------------------------------------------
def conjugate(self):
"""Complex conjugate of the GF Bloc. It follow the policy of numpy and
make a copy only if the Green function is complex valued"""
return self.__class__(
indices = list(self.indices),
mesh = self.mesh,
data = self.data.conjugate(),
tail = self.tail.conjugate(),
name = self.name+'*')
#------------------ Density -----------------------------------
def total_density(self):
"""Trace density"""
return numpy.trace(self.density())