gf : new wrapper

pytriqs/gf/local/CMakeLists.txt

@@ -1,5 +1,6 @@
 
 SET(PYTHON_SOURCES 
+  ${CMAKE_CURRENT_SOURCE_DIR}/__init__.py
   ${CMAKE_CURRENT_SOURCE_DIR}/block_gf.py
   ${CMAKE_CURRENT_SOURCE_DIR}/descriptors.py
   ${CMAKE_CURRENT_SOURCE_DIR}/gf_generic.py
@@ -10,21 +11,17 @@ SET(PYTHON_SOURCES
   ${CMAKE_CURRENT_SOURCE_DIR}/gf_retime.py
   ${CMAKE_CURRENT_SOURCE_DIR}/gf_two_real_times.py
   ${CMAKE_CURRENT_SOURCE_DIR}/impl_plot.py
-  ${CMAKE_CURRENT_SOURCE_DIR}/__init__.py
   ${CMAKE_CURRENT_SOURCE_DIR}/inverse.py
   ${CMAKE_CURRENT_SOURCE_DIR}/lazy_expressions.py
-  ${CMAKE_CURRENT_SOURCE_DIR}/nothing.py
   ${CMAKE_CURRENT_SOURCE_DIR}/tools.py
 )
 
 # Install python sources
 install (FILES ${PYTHON_SOURCES} DESTINATION ${TRIQS_PYTHON_LIB_DEST}/gf/local)
 
-# Build cython module 
+# Build C extension module 
-cython_module( GF3 gf gf/local )
+triqs_python_extension(gf gf/local)
-cython_module( MS matrix_stack gf/local )
+# ?? was not needed ? triqs_set_rpath_for_target(my_module)
 
-FILE(GLOB all_pxd_files RELATIVE ${CMAKE_CURRENT_SOURCE_DIR} *.pxd )
-install (FILES ${all_pxd_files} DESTINATION "include/pytriqs/gf/local")
 install (FILES ${CMAKE_SOURCE_DIR}/pytriqs/__init__.py.template DESTINATION "include/pytriqs/gf/local" RENAME __init__.py)
 

pytriqs/gf/local/OLD/gf_generic.py

@@ -191,13 +191,13 @@ class GfGeneric:
 
     #--------  LAZY expression system -----------------------------------------
 
-    def __lazy_expr_eval_context__(self):
+    def _lazy_expr_eval_context_(self):
         return LazyCTX(self)
 
     def __eq__(self, other):
         raise RuntimeError, " Operator not defined "
 
-    def __ilshift__(self, A):
+    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

pytriqs/gf/local/__init__.py

@@ -26,17 +26,27 @@ It is imported with the command::
   >>> from pytriqs.gf.local import *
 """
 
-from gf import TailGf
+from gf import *
 
 from inverse import inverse
-from gf_imfreq import GfImFreq
+#from gf_imfreq import GfImFreq
-from gf_imtime import GfImTime
+#from gf_imtime import GfImTime
-from gf_refreq import GfReFreq
+#from gf_refreq import GfReFreq
-from gf_retime import GfReTime
+#from gf_retime import GfReTime
 #from gf_two_real_times import GfTwoRealTime
-from gf_legendre import GfLegendre
+#from gf_legendre import GfLegendre
 from block_gf import BlockGf
 from descriptors import Omega, iOmega_n, SemiCircular, Wilson, Fourier, InverseFourier, LegendreToMatsubara, MatsubaraToLegendre
 
-__all__ = ['Omega','iOmega_n','SemiCircular','Wilson','Fourier','InverseFourier','LegendreToMatsubara','MatsubaraToLegendre','lazy_expressions','TailGf','GfImFreq','GfImTime','GfReFreq','GfReTime','GfLegendre','BlockGf','inverse'] #,'GfTwoRealTime']
+#__all__ = ['TailGf','GfImFreq','MeshImFreq']
+
+__all__ = ['Omega','iOmega_n','SemiCircular','Wilson','Fourier','InverseFourier','LegendreToMatsubara','MatsubaraToLegendre','lazy_expressions','TailGf',
+           'GfImFreq','MeshImFreq',
+           'GfImTime', 'MeshImTime',
+           'GfReFreq', 'MeshReFreq',
+           'GfReTime', 'MeshReTime',
+           'make_gf_from_inverse_fourier',
+           'BlockGf','inverse'] #,'GfTwoRealTime']
+
+#__all__ = ['Omega','iOmega_n','SemiCircular','Wilson','Fourier','InverseFourier','LegendreToMatsubara','MatsubaraToLegendre','lazy_expressions','TailGf','GfImFreq','GfImTime','GfReFreq','GfReTime','GfLegendre','BlockGf','inverse'] #,'GfTwoRealTime']
 

pytriqs/gf/local/_gf_common.py

@@ -0,0 +1,156 @@
+################################################################################
+#
+# 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()
+
+#---------------------------------------------------
+
+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)')
+
+#---------------------------------------------------
+
+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())
+

pytriqs/gf/local/_gf_imfreq.py

@@ -0,0 +1,112 @@
+from scipy.optimize import leastsq
+from tools import get_indices_in_dict
+import _gf_plot 
+import numpy
+
+def init( mesh= None, shape =None, name = 'g', **d):
+    """
+    """
+    if mesh is None :
+        from gf import MeshImFreq
+        if 'beta' not in d : raise ValueError, "beta not provided"
+        beta = float(d.pop('beta'))
+        n_points = d.pop('n_points',1025)
+        stat = d.pop('statistic','Fermion')
+        positive_only = d.pop('positive_only',True)
+        mesh = MeshImFreq(beta,stat,n_points, positive_only)
+    
+    indices_pack = get_indices_in_dict(d)
+    if not shape : 
+      assert indices_pack, "No shape, no indices !"
+      indicesL, indicesR = indices_pack
+      shape = len(indicesL),len(indicesR)
+    
+    #data = d.pop('data') if 'data' in d else numpy.zeros((len(mesh),N1,N2), self.dtype )
+    #tail = d.pop('tail') if 'tail' in d else TailGf(shape = (N1,N2))
+    #symmetry = d.pop('symmetry', Nothing())
+
+    return (mesh, shape, indices_pack, name), {}
+    #return mesh, data, tail, symmetry, indices_pack, name
+
+#--------------   PLOT   ---------------------------------------
+
+def plot(self, opt_dict):
+    """ Plot protocol. opt_dict can contain :
+         * :param RIS: 'R', 'I', 'S', 'RI' [ default]
+         * :param x_window: (xmin,xmax) or None [default]
+         * :param name: a string [default ='']. If not '', it remplaces the name of the function just for this plot.
+    """
+    return _gf_plot.plot_base( self, opt_dict,  r'$\omega_n$',
+            lambda name : r'%s$(i\omega_n)$'%name, True, [x.imag for x in self.mesh] )
+
+#--------------   OTHER OPERATIONS -----------------------------------------------------
+
+def replace_by_tail(self,start) :
+    d = self.data
+    t = self.tail
+    for n, om in enumerate(self.mesh) :
+        if n >= start : d[n,:,:] = t(om)
+
+def fit_tail(self, fixed_coef, order_max, fit_start, fit_stop, replace_tail = True):
+   """
+   Fit the tail of the Green's function
+   Input:
+     - fixed_coef: a 3-dim array of known coefficients for the fit starting from the order -1
+     - order_max: highest order in the fit
+     - fit_start, fit_stop: fit the data between fit_start and fit_stop
+   Output:
+     On output all the data above fit_start is replaced by the fitted tail
+     and the new moments are included in the Green's function
+   """
+
+   # Turn known_coefs into a numpy array if ever it is not already the case
+   known_coef = fixed_coef
+
+   # Change the order_max
+   # It is assumed that any known_coef will start at order -1
+   self.tail.zero()
+   self.tail.mask.fill(order_max)
+
+   # Fill up two arrays with the frequencies and values over the range of interest
+   ninit, nstop = 0, -1
+   x = []
+   for om in self.mesh:
+     if (om.imag < fit_start): ninit = ninit+1
+     if (om.imag <= fit_stop): nstop = nstop+1
+     if (om.imag <= fit_stop and om.imag >= fit_start): x += [om]
+   omegas = numpy.array(x)
+   values = self.data[ninit:nstop+1,:,:]
+
+   # Loop over the indices of the Green's function
+   for n1,indR in enumerate(self.indicesR):
+     for n2,indL in enumerate(self.indicesL):
+
+       # Construct the part of the fitting functions which is known
+       f_known = numpy.zeros((len(omegas)),numpy.complex)
+       for order in range(len(known_coef[n1][n2])):
+         f_known += known_coef[n1][n2][order]*omegas**(1-order)
+
+       # Compute how many free parameters we have and give an initial guess
+       len_param = order_max-len(known_coef[n1][n2])+2
+       p0 = len_param*[1.0]
+
+       # This is the function to be minimized, the diff between the original
+       # data in values and the fitting function
+       def fct(p):
+         y_fct = 1.0*f_known
+         for order in range(len_param):
+           y_fct += p[order]*omegas**(1-len(known_coef[n1][n2])-order)
+         y_fct -= values[:,n1,n2]
+         return abs(y_fct)
+
+       # Now call the minimizing function
+       sol = leastsq(fct, p0, maxfev=1000*len_param)
+
+       # Put the known and the new found moments in the tail
+       for order in range(len(known_coef[n1][n2])):
+         self.tail[order-1][n1,n2] = numpy.array([[ known_coef[n1][n2][order] ]])
+       for order, moment in enumerate(sol[0]):
+         self.tail[len(known_coef[n1][n2])+order-1][n1,n2] = numpy.array([[ moment ]])
+   self.tail.mask.fill(order_max)
+   # Replace then end of the Green's function by the tail
+   if replace_tail: self.replace_by_tail(ninit);

pytriqs/gf/local/_gf_imtime.py

@@ -0,0 +1,40 @@
+from tools import get_indices_in_dict
+import _gf_plot 
+import numpy
+
+def init( mesh= None, shape =None, name = 'g', **d):
+    """
+    """
+    if mesh is None : 
+        from gf import MeshImTime
+        if 'beta' not in d : raise ValueError, "beta not provided"
+        beta = float(d.pop('beta'))
+        n_max = d.pop('n_points',10000)
+        stat = d.pop('statistic','Fermion')
+        kind = d.pop('kind','half_bins') 
+        mesh = MeshImTime(beta,stat,n_max,kind)
+    
+    indices_pack = get_indices_in_dict(d)
+    if not shape : 
+      assert indices_pack, "No shape, no indices !"
+      indicesL, indicesR = indices_pack
+      shape = len(indicesL),len(indicesR)
+    
+    #data = d.pop('data') if 'data' in d else numpy.zeros((len(mesh),N1,N2), self.dtype )
+    #tail = d.pop('tail') if 'tail' in d else TailGf(shape = (N1,N2))
+    #symmetry = d.pop('symmetry', Nothing())
+
+    return (mesh, shape, indices_pack, name), {}
+    #return mesh, data, tail, symmetry, indices_pack, name
+    
+#--------------   PLOT   ---------------------------------------
+
+def plot(self, opt_dict):
+    """ Plot protocol. opt_dict can contain : 
+         * :param RI: 'R', 'I', 'RI' [ default] 
+         * :param x_window: (xmin,xmax) or None [default]
+         * :param name: a string [default ='']. If not '', it remplaces the name of the function just for this plot.
+    """
+    has_complex_value = False
+    return _gf_plot.plot_base( self, opt_dict,  r'$\tau$', lambda name : r'%s$(\tau)$'%name, has_complex_value ,  list(self.mesh) )
+

pytriqs/gf/local/_gf_plot.py

@@ -31,8 +31,8 @@ def plot_base (self, opt_dict, xlabel, ylabel, use_ris, X):
                 'xlabel' : xlabel,
                 'ylabel' : ylabel (self.name),
                 'xdata' : X[sl],
-                'label' : Name if Name else prefix + B.name ,
+                'label' : Name if Name else prefix + "%s_%s"%(i,j), 
-                'ydata' : f( B.data[sl,0,0] ) } for (i,j,B) in self ]
+                'ydata' : f( self.data[sl,i,j] ) } for i in range(self.target_shape[0]) for j in range(self.target_shape[1])]
 
     if use_ris :
         ris = opt_dict.pop('RI','RI')
@@ -51,3 +51,25 @@ def plot_base (self, opt_dict, xlabel, ylabel, use_ris, X):
 
     if NamePrefix: self.name = name_save
     return res
+
+#------------------
+
+def x_data_view(self, x_window = None, flatten_y = False):
+    """
+    :param x_window: the window of x variable (omega/omega_n/t/tau) for which data is requested
+                      if None, take the full window
+    :param flatten_y: If the Green function is of size (1, 1) flatten the array as a 1d array
+    :rtype: a tuple (X, data) where
+             * X is a 1d numpy of the x variable inside the window requested
+             * data is a 3d numpy array of dim (:,:, len(X)), the corresponding slice of data
+               If flatten_y is True and dim is (1, 1, *), returns a 1d numpy
+    """
+    X = [x.imag for x in self.mesh] if type(self.mesh) == MeshImFreq else [x for x in self.mesh]
+    X, data = numpy.array(X), self.data
+    if x_window:
+      sl = clip_array (X, *x_window) if x_window else slice(len(X)) # the slice due to clip option x_window
+      X, data = X[sl],  data[sl,:,:]
+    if flatten_y and data.shape[1:3]==(1, 1): data = data[:,0,0]
+    return X, data
+
+

pytriqs/gf/local/_gf_refreq.py

@@ -0,0 +1,38 @@
+from tools import get_indices_in_dict
+import _gf_plot 
+import numpy
+
+def init( mesh= None, shape =None, name = 'g', **d):
+    """
+    """
+    if mesh is None :
+        from gf import MeshReFreq
+        window = d.pop('window')
+        omega_min = window[0]
+        omega_max = window[1]
+        n_max = d.pop('n_points',10000)
+        kind = d.pop('kind','full_bins')
+        mesh = MeshReFreq(omega_min, omega_max, n_max, kind)
+
+    indices_pack = get_indices_in_dict(d)
+    if not shape : 
+      assert indices_pack, "No shape, no indices !"
+      indicesL, indicesR = indices_pack
+      shape = len(indicesL),len(indicesR)
+    
+    #data = d.pop('data') if 'data' in d else numpy.zeros((len(mesh),N1,N2), self.dtype )
+    #tail = d.pop('tail') if 'tail' in d else TailGf(shape = (N1,N2))
+    #symmetry = d.pop('symmetry', Nothing())
+
+    return (mesh, shape, indices_pack, name), {}
+
+#--------------   PLOT   ---------------------------------------
+
+def plot(self, opt_dict):
+    """ Plot protocol. opt_dict can contain :
+         * :param RI: 'R', 'I', 'RI' [ default]
+         * :param x_window: (xmin,xmax) or None [default]
+         * :param name: a string [default ='']. If not '', it remplaces the name of the function just for this plot.
+    """
+    return _gf_plot.plot_base(self, opt_dict,  r'$\omega$', lambda name : r'%s$(\omega)$'%name, True, list(self.mesh))
+

pytriqs/gf/local/_gf_retime.py

@@ -0,0 +1,38 @@
+from tools import get_indices_in_dict
+import _gf_plot 
+import numpy
+
+def init( mesh= None, shape =None, name = 'g', **d):
+    """
+    """
+    if mesh is None :
+        from gf import MeshReTime
+        window = d.pop('window')
+        t_min = window[0]
+        t_max = window[1]
+        n_max = d.pop('n_points',10000)
+        kind = d.pop('kind','full_bins')
+        mesh = MeshReTime(t_min, t_max, n_max, kind)
+
+    indices_pack = get_indices_in_dict(d)
+    if not shape : 
+      assert indices_pack, "No shape, no indices !"
+      indicesL, indicesR = indices_pack
+      shape = len(indicesL),len(indicesR)
+    
+    #data = d.pop('data') if 'data' in d else numpy.zeros((len(mesh),N1,N2), self.dtype )
+    #tail = d.pop('tail') if 'tail' in d else TailGf(shape = (N1,N2))
+    #symmetry = d.pop('symmetry', Nothing())
+
+    return (mesh, shape, indices_pack, name), {}
+
+#--------------   PLOT   ---------------------------------------
+
+def plot(self, opt_dict):
+    """ Plot protocol. opt_dict can contain :
+         * :param RI: 'R', 'I', 'RI' [ default]
+         * :param x_window: (xmin,xmax) or None [default]
+         * :param name: a string [default ='']. If not '', it remplaces the name of the function just for this plot.
+    """
+    return _gf_plot.plot_base(self, opt_dict,  r'$\t$', lambda name : r'%s$(\t)$'%name, True, list(self.mesh))
+

pytriqs/gf/local/block_gf.py

@@ -1,4 +1,3 @@
-
 ################################################################################
 #
 # TRIQS: a Toolbox for Research in Interacting Quantum Systems
@@ -22,7 +21,7 @@
 
 from itertools import izip
 import operator
-from impl_plot import PlotWrapperPartialReduce
+from _gf_plot import PlotWrapperPartialReduce
 
 def call_factory_from_dict (cl,dic) :
     """Given a class cl and a dict dic, it calls cl.__factory_from_dict__(dic)"""

pytriqs/gf/local/descriptor_base.py

@@ -0,0 +1,150 @@
+################################################################################
+#
+# TRIQS: a Toolbox for Research in Interacting Quantum Systems
+#
+# Copyright (C) 2011 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/>.
+#
+################################################################################
+
+r""" """
+
+import numpy
+from math import *
+from lazy_expressions import LazyExprTerminal, LazyExpr, transform
+
+def is_lazy(y):
+    #return type(y) in [ Omega_, LazyExpr]
+    return  isinstance(y,(Omega_, LazyExpr, LazyExprTerminal))
+
+def is_scalar(x): 
+    return type(x) in [ type(1), type(1.0), type(1j), numpy.ndarray, numpy.int, numpy.int_, numpy.int8, numpy.int16, numpy.int32, numpy.float, numpy.float_, numpy.float32, numpy.float64, numpy.complex, numpy.complex_, numpy.complex64, numpy.complex128 ]
+
+def convert_scalar_to_const(expr): 
+
+  # if the expression is a pure scalar, replace it by Const
+  t= expr.get_terminal()
+  if is_scalar(t): return LazyExpr( Const(t) )
+
+  # otherwise: replace all scalar appearing in +/- operations by Const
+  def act (tag, childs): 
+        if tag in ["+", "-"]:
+            for n,c in enumerate(childs): 
+                t = c.get_terminal()
+                if is_scalar(t): childs[n] =  Const (t)
+        return (tag,childs)
+
+  return transform(expr, act)
+    
+class Base (LazyExprTerminal):
+    def __init__(self,**kargs):
+        self.__dict__.update(kargs)
+                
+#########################################################################
+
+class Function (Base):
+    r"""   
+       Stores a python function and a tail.
+       
+       If the Green's function is defined on an array of points :math:`x_i`, then it will be initialized to :math:`F(x_i)`.
+    """
+    def __init__ (self, function, tail=None): 
+        r"""
+        :param function: the function :math:`\omega \rightarrow function(\omega)`
+        :param tail: The tail. Use None if you do not wish to use a tail (will be put to 0)
+        """
+        Base.__init__(self, function=function, tail=tail)
+        
+    def __call__(self,G):
+        if not(callable(self.function)): raise RuntimeError, "GFInitializer.Function: f must be callable"
+        res = G.data[:,:,:]
+        try:
+            for n,om in enumerate(G.mesh): res[n,:,:] = self.function(om)
+        except:
+            print "The given function has a problem..."
+            raise
+        if self.tail: G.tail.copy_from(self.tail)
+        return G
+
+#########################################################################
+
+class Const(Base):
+    def __init__ (self, C):
+        Base.__init__(self, C=C)
+         
+    def __call__(self,G):
+        C = self.C
+        if G.mesh.__class__.__name__ not in ['MeshImFreq', 'MeshReFreq']:
+            raise TypeError, "This initializer is only correct in frequency"
+
+        if not isinstance(C,numpy.ndarray): 
+            assert G.N1==G.N2, "Const only applies to square G"
+            C = C*numpy.identity(G.N1) 
+        if C.shape !=(G.N1,G.N2): raise RuntimeError, "Size of constant incorrect"
+
+        G.tail.zero()
+        G.tail[0][:,:] = C
+        
+        Function(lambda om: C, None)(G)
+        return G
+    
+#########################################################################
+
+class Omega_(Base):
+    r"""The function:math:`\omega \rightarrow \omega` """
+    def __str__(self): return "Omega" 
+    def __call__(self,G):
+        if G.mesh.__class__.__name__ not in ['MeshImFreq', 'MeshReFreq']:
+            raise TypeError, "This initializer is only correct in frequency"
+
+        Id = numpy.identity(G.N1)
+        G.tail.zero()
+        G.tail[-1][:,:] = Id
+
+        for n,om in enumerate(G.mesh): G.data[n,:,:] = om*Id
+        return G
+
+##########################################################################
+
+Omega = Omega_()
+iOmega_n = Omega_()
+
+##########################################################################
+
+class A_Omega_Plus_B(Base):
+    "deprecated. do not use"
+    def __init__ (self, A=1, B=0, Invert= False):
+        Base.__init__(self, A=A, B=B,Invert=Invert)
+         
+    def __call__(self,G):
+        A,B = self.A, self.B
+        if G.mesh.__class__.__name__ not in ['MeshImFreq', 'MeshReFreq']:
+            raise TypeError, "This initializer is only correct in frequency"
+
+        if not isinstance(A,numpy.ndarray): A = A*numpy.identity(G.N1) 
+        if not isinstance(B,numpy.ndarray): B = B*numpy.identity(G.N1) 
+        if A.shape !=(G.N1,G.N2): raise RuntimeError, "Size of A incorrect"
+        if B.shape !=(G.N1,G.N2): raise RuntimeError, "Size of B incorrect"
+
+        G.tail.zero()
+        G.tail[-1][:,:] = A
+        G.tail[0][:,:] = B
+        
+        Function(lambda om: A*om + B, None)(G)
+
+        if self.Invert: G.invert()
+        return G
+
+

pytriqs/gf/local/descriptors.py

@@ -21,135 +21,9 @@
 
 r""" """
 
-import numpy
+from descriptor_base import *
-from math import *
 from gf import MeshImFreq, MeshReFreq
-from lazy_expressions import LazyExprTerminal, LazyExpr, transform
-
-def is_lazy(y):
-    #return type(y) in [ Omega_, LazyExpr]
-    return  isinstance(y,(Omega_, LazyExpr, LazyExprTerminal))
-
-def is_scalar(x): 
-    return type(x) in [ type(1), type(1.0), type(1j), numpy.ndarray, numpy.int, numpy.int_, numpy.int8, numpy.int16, numpy.int32, numpy.float, numpy.float_, numpy.float32, numpy.float64, numpy.complex, numpy.complex_, numpy.complex64, numpy.complex128 ]
-
-def convert_scalar_to_const(expr): 
-
-  # if the expression is a pure scalar, replace it by Const
-  t= expr.get_terminal()
-  if is_scalar(t): return LazyExpr( Const(t) )
-
-  # otherwise: replace all scalar appearing in +/- operations by Const
-  def act (tag, childs): 
-        if tag in ["+", "-"]:
-            for n,c in enumerate(childs): 
-                t = c.get_terminal()
-                if is_scalar(t): childs[n] =  Const (t)
-        return (tag,childs)
-
-  return transform(expr, act)
-    
-#########################################################################
-
-class Base (LazyExprTerminal):
-    def __init__(self,**kargs):
-        self.__dict__.update(kargs)
                 
-#########################################################################
-
-class Function (Base):
-    r"""   
-       Stores a python function and a tail.
-       
-       If the Green's function is defined on an array of points :math:`x_i`, then it will be initialized to :math:`F(x_i)`.
-    """
-    def __init__ (self, function, tail=None): 
-        r"""
-        :param function: the function :math:`\omega \rightarrow function(\omega)`
-        :param tail: The tail. Use None if you do not wish to use a tail (will be put to 0)
-        """
-        Base.__init__(self, function=function, tail=tail)
-        
-    def __call__(self,G):
-        if not(callable(self.function)): raise RuntimeError, "GFInitializer.Function: f must be callable"
-        res = G.data[:,:,:]
-        try:
-            for n,om in enumerate(G.mesh): res[n,:,:] = self.function(om)
-        except:
-            print "The given function has a problem..."
-            raise
-        if self.tail: G.tail.copy_from(self.tail)
-        return G
-
-#########################################################################
-
-class Const(Base):
-    def __init__ (self, C):
-        Base.__init__(self, C=C)
-         
-    def __call__(self,G):
-        C = self.C
-        if G.mesh.__class__.__name__ not in ['MeshImFreq', 'MeshReFreq']:
-            raise TypeError, "This initializer is only correct in frequency"
-
-        if not isinstance(C,numpy.ndarray): 
-            assert G.N1==G.N2, "Const only applies to square G"
-            C = C*numpy.identity(G.N1) 
-        if C.shape !=(G.N1,G.N2): raise RuntimeError, "Size of constant incorrect"
-
-        G.tail.zero()
-        G.tail[0][:,:] = C
-        
-        Function(lambda om: C, None)(G)
-        return G
-    
-#########################################################################
-
-class Omega_(Base):
-    r"""The function:math:`\omega \rightarrow \omega` """
-    def __str__(self): return "Omega" 
-    def __call__(self,G):
-        if G.mesh.__class__.__name__ not in ['MeshImFreq', 'MeshReFreq']:
-            raise TypeError, "This initializer is only correct in frequency"
-
-        Id = numpy.identity(G.N1)
-        G.tail.zero()
-        G.tail[-1][:,:] = Id
-
-        for n,om in enumerate(G.mesh): G.data[n,:,:] = om*Id
-        return G
-
-##########################################################################
-
-Omega = Omega_()
-iOmega_n = Omega_()
-
-##########################################################################
-
-class A_Omega_Plus_B(Base):
-    "deprecated. do not use"
-    def __init__ (self, A=1, B=0, Invert= False):
-        Base.__init__(self, A=A, B=B,Invert=Invert)
-         
-    def __call__(self,G):
-        A,B = self.A, self.B
-        if G.mesh.__class__.__name__ not in ['MeshImFreq', 'MeshReFreq']:
-            raise TypeError, "This initializer is only correct in frequency"
-
-        if not isinstance(A,numpy.ndarray): A = A*numpy.identity(G.N1) 
-        if not isinstance(B,numpy.ndarray): B = B*numpy.identity(G.N1) 
-        if A.shape !=(G.N1,G.N2): raise RuntimeError, "Size of A incorrect"
-        if B.shape !=(G.N1,G.N2): raise RuntimeError, "Size of B incorrect"
-
-        G.tail.zero()
-        G.tail[-1][:,:] = A
-        G.tail[0][:,:] = B
-        
-        Function(lambda om: A*om + B, None)(G)
-
-        if self.Invert: G.invert()
-        return G
-
 #######################################
 
 class OneFermionInTime(Base):

pytriqs/gf/local/gf_desc.py

@@ -0,0 +1,395 @@
+from wrap_generator import *
+
+module = module_(full_name = "pytriqs.gf.local.gf", doc = "Local Green functions ...")
+module.add_include("<triqs/gfs.hpp>")
+module.add_include("<triqs/gfs/local/functions.hpp>")
+module.add_include("<triqs/gfs/local/pade.hpp>")
+module.add_using("namespace triqs::arrays")
+module.add_using("namespace triqs::gfs")
+module.add_using("namespace triqs::gfs::local")
+module.add_using("triqs::utility::mini_vector")
+
+########################
+##   TailGf
+########################
+
+t = class_( py_type = "TailGf",
+        c_type = "local::tail_view",
+        serializable= "tuple",
+        is_printable= True,
+        arithmetic = ("algebra","double")
+       )
+  
+t.add_constructor(signature = "(int N1, int N2, int size=10, int order_min=-1)",
+                  doc = "DOC of constructor")
+#t.add_constructor(doc = "DOC of constructor", signature = "(array_view<dcomplex,3> d, array_view<long,2> m, long i)", python_precall = "tail_aux.tail_construct")
+
+t.add_property(name = "data",
+               getter = cfunction(c_name="data", signature = "array_view<dcomplex,3>()"),
+               doc = "Access to the data array")
+
+##tail.add_property(name = "shape", getter = cfunction(c_name="shape", signature = "int()", doc = "Shape"))
+t.add_property(getter = cfunction(c_name="size", signature = "int()"),
+               doc = "size")
+
+t.add_property(getter = cfunction(c_name="order_min", signature = "int()"),
+               doc = "Min order of the expansion")
+
+t.add_property(getter = cfunction(c_name="order_max", signature = "int()"),
+               doc = "Max order of the expansion")
+
+t.add_property(name = "mask",
+               getter = cfunction(c_name="mask_view", signature = "array_view<long,2>()"),
+               doc = "Access to the mask")
+
+t.add_method(py_name = "has_coef",
+             calling_pattern = "bool result = (i >=self_c.order_min()) && (i<=self_c.order_max())",
+             signature = "bool(int i)",
+             doc = "A method which did not exist in C++")
+
+# strange, I should not quality : ADL ??
+t.add_method(py_name = "invert",
+             calling_pattern = "self_c = local::inverse(self_c)",
+             signature = "void()",
+             doc = "Invert")
+
+t.add_method(py_name = "zero",
+             calling_pattern = "self_c = 0",
+             signature = "void()",
+             doc = "Sets the expansion to 0")
+
+t.add_method_copy()
+t.add_method_copy_from()
+
+t.add_call(calling_pattern = "auto result = self_c.evaluate(u)",
+           signature = "dcomplex(dcomplex u)",
+           doc = "")
+
+t.number_protocol['multiply'].add_overload(calling_pattern = "*", signature = "tail(matrix<dcomplex> x,tail_view y)") #'x'), (self.c_type,'y')], rtype = self.c_type)
+t.number_protocol['multiply'].add_overload(calling_pattern = "*", signature = "tail(tail_view x,matrix<dcomplex> y)") #'x'), (self.c_type,'y')], rtype = self.c_type)
+ 
+# ok, but MISSING CHECK SIZE
+t.add_getitem(c_name = "operator()",
+              signature = "matrix_view<dcomplex>(int i)",
+              doc = "Returns the i-th coefficient of the expansion, or order Om^i")
+
+t.add_setitem(calling_pattern = "self_c(i) = m",
+              signature = "void(int i, matrix<dcomplex> m)", # I use matrix, not view. It makes a copy, but ensure I can pass double, int, and numpy will convert.
+              doc = "Sets the i-th coefficient of the expansion, or order Om^i")
+
+module.add_class(t)
+
+########################
+##   enums
+########################
+
+module.add_enum(c_name = "statistic_enum",
+                values = ["Fermion","Boson"])
+
+module.add_enum(c_name = "mesh_kind",
+                values = ["half_bins","full_bins","without_last"])
+
+########################
+##   Mesh generic
+########################
+
+def make_mesh( py_type, c_tag, has_kind=True, is_im=False) :
+    m = class_( py_type = py_type,
+            c_type = "gf_mesh<%s>"%c_tag,
+            serializable= "tuple",
+            is_printable= True,
+           )
+
+    if is_im :
+        m.add_property(name = "beta",
+                       getter = cfunction(calling_pattern="double result = self_c.domain().beta",
+                       signature = "double()",
+                       doc = "Inverse temperature"))
+
+        m.add_property(name = "statistic",
+                       getter = cfunction(calling_pattern="statistic_enum result = self_c.domain().statistic", signature = "statistic_enum()"),
+                       doc = "Statistic")
+
+    m.add_len(calling_pattern = "int result = self_c.size()", doc = "Size of the mesh")
+    m.add_iterator(c_cast_type = "dcomplex")
+
+    if has_kind :
+        m.add_property(name = "kind",
+               getter = cfunction(calling_pattern="mesh_kind result = self_c.kind()", signature = "mesh_kind()"),
+               doc = "")
+
+
+    #def __richcmp__(MeshImFreq self, MeshImFreq other,int op) :
+    #    if op ==2 : # ==
+    #        return self._c == other._c
+
+    #def __reduce__(self):
+    #    return self.__class__, (self.beta, self.statistic, len(self))
+
+    return m
+
+########################
+##   MeshImFreq
+########################
+
+m = make_mesh( py_type = "MeshImFreq", c_tag = "imfreq", has_kind = False, is_im = True)
+m.add_constructor(signature = "(double beta, statistic_enum S, int n_max=1025, bool positive_only=true)")
+
+module.add_class(m)
+
+########################
+##   MeshImTime
+########################
+
+m = make_mesh(py_type = "MeshImTime", c_tag = "imtime", is_im = True)
+m.add_constructor(signature = "(double beta, statistic_enum S, int n_max, mesh_kind kind)")
+
+module.add_class(m)
+
+########################
+##   MeshReFreq
+########################
+
+m = make_mesh(py_type = "MeshReFreq", c_tag = "refreq")
+m.add_constructor(signature = "(double omega_min, double omega_max, int n_max, mesh_kind kind)")
+
+m.add_property(name = "omega_min",
+               getter = cfunction(calling_pattern="double result = self_c.x_min()",
+               signature = "double()",
+               doc = "Inverse temperature"))
+
+m.add_property(name = "omega_max",
+               getter = cfunction(calling_pattern="double result = self_c.x_max()",
+               signature = "double()",
+               doc = "Inverse temperature"))
+
+module.add_class(m)
+
+########################
+##   MeshReTime
+########################
+
+m = make_mesh(py_type = "MeshReTime", c_tag = "retime")
+m.add_constructor(signature = "(double t_min, double t_max, int n_max, mesh_kind kind)")
+
+m.add_property(name = "t_min",
+               getter = cfunction(calling_pattern="double result = self_c.x_min()",
+               signature = "double()",
+               doc = "Inverse temperature"))
+
+m.add_property(name = "t_max",
+               getter = cfunction(calling_pattern="double result = self_c.x_max()",
+               signature = "double()",
+               doc = "Inverse temperature"))
+
+module.add_class(m)
+
+########################
+##   Gf Generic : common to all 5 one variable gf
+########################
+
+def make_gf( py_type, c_tag, is_complex_data = True, is_im = False) :
+
+    data_type = "std::complex<double>" if is_complex_data else "double"
+
+    g = class_(
+            py_type = py_type,
+            c_type = "gf_view<%s>"%c_tag,
+            #serializable= "boost",
+            serializable= "tuple",
+            is_printable= True,
+            hdf5 = True,
+            arithmetic = ("algebra",data_type)
+            )
+
+    g.add_constructor(signature = "(gf_mesh<%s> mesh, mini_vector<size_t,2> shape, std::vector<std::vector<std::string>> indices = {}, std::string name = "")"%c_tag,
+                      python_precall = "pytriqs.gf.local._gf_%s.init"%c_tag)
+
+    g.add_method_copy()
+    g.add_method_copy_from()
+
+    # properties
+    g.add_member(c_name = "name", c_type  ="std::string",  doc = "Name of the Green function (used for plotting only)")
+
+    if is_im :
+        g.add_property(name = "beta",
+                       getter = cfunction(calling_pattern="double result = self_c.domain().beta", signature = "double()"),
+                       doc = "Inverse temperature")
+
+        g.add_property(name = "statistic",
+                       getter = cfunction(calling_pattern="statistic_enum result = self_c.domain().statistic", signature = "statistic_enum()"),
+                       doc = "Statistic")
+
+    g.add_property(name = "mesh",
+                   getter = cfunction(c_name="mesh", signature = "gf_mesh<%s>()"%c_tag),
+                   doc ="The mesh")
+
+    g.add_property(name = "data",
+                   getter = cfunction(calling_pattern="auto result = self_c.data()", signature = "array_view<%s,3>()"%data_type),
+                   doc ="The data ")
+
+    g.add_property(name = "target_shape",
+                   getter = cfunction(calling_pattern="auto result = get_target_shape(self_c)", signature = "shape_type()"),
+                   doc = "")
+
+    g.add_property(name = "tail",
+                   getter = cfunction(c_name="singularity", signature = "local::tail_view()"),
+                   doc ="The high frequency tail")
+
+    g.add_property(name = "indices",
+                   getter = cfunction(calling_pattern="auto result = self_c.indices()[0]", signature = "std::vector<std::string>()"),
+                   doc ="The indices(L)")
+
+    # backward compatibility
+    g.add_property(name = "N1",
+                   getter = cfunction(calling_pattern="int result = get_target_shape(self_c)[0]", signature = "int()"),
+                   doc = "")
+    g.add_property(name = "N2",
+                   getter = cfunction(calling_pattern="int result = get_target_shape(self_c)[1]", signature = "int()"),
+                   doc = "")
+
+    # []
+    g.add_getitem(signature = "gf_view<%s>(range r1, range r2)"%c_tag,
+                  calling_pattern= "auto result = slice_target(self_c,r1,r2)",
+                  doc = " DOC to be written ")
+
+    g.add_getitem(signature = "gf_view<%s>(std::string i1, std::string i2)"%c_tag,
+                  calling_pattern= "auto result = slice_target(self_c,self_c.indices().convert_index(i1,0),self_c.indices().convert_index(i2,1))",
+                  doc = " DOC to be written ")
+
+    g.add_setitem(signature = "void(PyObject* r1, PyObject* r2, PyObject* val)",
+                  calling_pattern=
+                  """
+                   pyref gs_py = PyObject_GetItem(self,Py_BuildValue("(NN)", r1,r2));  // gs = self[r1,r2]
+                   pyref res = PyNumber_InPlaceLshift(gs_py,val);                      // gs <<= val
+                  """,
+                  no_self_c = True, # avoid a warning
+                  doc = " doc [] set ")
+
+    # Plot
+    g.add_property(name = "real",
+                   getter = "pytriqs.gf.local._gf_common._real_plot",
+                   doc ="real option for plotting")
+
+    g.add_property(name = "imag",
+                   getter = "pytriqs.gf.local._gf_common._imag_plot",
+                   doc ="imag option for plotting")
+
+    # Lazy system
+    g.add_pure_python_method("pytriqs.gf.local._gf_common.LazyCTX", py_name = "__lazy_expr_eval_context__")
+
+    g.number_protocol['add'].python_precall      = "pytriqs.gf.local._gf_common.add_precall"
+    g.number_protocol['subtract'].python_precall = "pytriqs.gf.local._gf_common.sub_precall"
+    g.number_protocol['multiply'].python_precall = "pytriqs.gf.local._gf_common.mul_precall"
+    g.number_protocol['divide'].python_precall   = "pytriqs.gf.local._gf_common.div_precall"
+
+    g.number_protocol['inplace_lshift'] = pyfunction(py_name ="__inplace_lshift__", python_precall = "pytriqs.gf.local._gf_common._ilshift_", arity = 2)
+
+    g.add_method(py_name = "invert", calling_pattern = "invert_in_place(self_c)" , signature = "void()", doc = "Invert (in place)")
+    
+    if c_tag != "imtime" : 
+        g.add_method(py_name = "conjugate", calling_pattern = "auto result = conj(self_c)" , signature = "gf<%s>()"%c_tag, doc = "Return a new function, conjugate of self.")
+
+    g.number_protocol['multiply'].add_overload(calling_pattern = "*", signature = "gf<%s>(matrix<%s> x,gf<%s> y)"%(c_tag,data_type,c_tag)) #'x'), (self.c_type,'y')], rtype = self.c_type)
+    g.number_protocol['multiply'].add_overload(calling_pattern = "*", signature = "gf<%s>(gf<%s> x,matrix<%s> y)"%(c_tag,c_tag,data_type)) #'x'), (self.c_type,'y')], rtype = self.c_type)
+   
+    g.add_method(py_name = "from_L_G_R", 
+                 calling_pattern = "self_c = L_G_R(l,g,r)", 
+                 signature = "void(matrix<%s> l,gf<%s> g,matrix<%s> r)"%(data_type,c_tag,data_type), 
+                 doc = "self <<= l * g * r")
+   
+    g.add_method(py_name = "zero",
+                 calling_pattern = "self_c = 0",
+                 signature = "void()",
+                 doc = "Put the Green function to 0")
+
+   # Pure python methods
+    g.add_pure_python_method("pytriqs.gf.local._gf_%s.plot"%c_tag, py_name = "_plot_")
+
+    return g
+
+########################
+##   GfImFreq
+########################
+
+g = make_gf(py_type = "GfImFreq", c_tag = "imfreq", is_im = True)
+
+#g.add_method(py_name = "set_from_fourier", c_name = "fourier", signature = "void()", doc = "Fills self with the Fourier transform of gt")
+#g.add_method(py_name = "set_from_legendre", c_name = "fourier", signature = "void()", doc = "Fills self with the Legendre transform of gl")
+
+g.add_method(py_name = "density",
+             calling_pattern = "auto result = density(self_c)",
+             signature = "matrix_view<double>()",
+             doc = "Density, as a matrix, computed from a Matsubara sum")
+
+g.add_method(py_name = "total_density",
+             calling_pattern = "auto result = trace(density(self_c))",
+             signature = "double()",
+             doc = "Trace of density")
+
+g.add_method(py_name = "set_from_fourier",
+             signature = "void(gf_view<imtime> gt)",
+             calling_pattern = "self_c = fourier(*gt)",
+             doc = """Fills self with the Fourier transform of gt""")
+
+# Pure python methods
+g.add_pure_python_method("pytriqs.gf.local._gf_imfreq.replace_by_tail")
+g.add_pure_python_method("pytriqs.gf.local._gf_imfreq.fit_tail")
+
+module.add_class(g)
+
+########################
+##   GfImTime
+########################
+
+g = make_gf(py_type = "GfImTime", c_tag = "imtime", is_complex_data = False, is_im = True)
+
+g.add_method(py_name = "set_from_inverse_fourier",
+             signature = "void(gf_view<imfreq> gw)",
+             calling_pattern = "self_c = inverse_fourier(*gw)",
+             doc = """Fills self with the Inverse Fourier transform of gw""")
+
+module.add_class(g)
+
+########################
+##   GfReFreq
+########################
+
+g = make_gf(py_type = "GfReFreq", c_tag = "refreq")
+
+g.add_method(py_name = "set_from_fourier",
+             signature = "void(gf_view<retime> gt)",
+             calling_pattern = "self_c = fourier(*gt)",
+             doc = """Fills self with the Fourier transform of gt""")
+
+g.add_method(py_name = "set_from_pade",
+             signature = "void(gf_view<imfreq> gw, int n_points = 100, double freq_offset = 0.0)",
+             calling_pattern = "pade(self_c,*gw,n_points, freq_offset)",
+             doc = """ TO BE WRITTEN""")
+
+module.add_class(g)
+
+########################
+##   GfReTime
+########################
+
+g = make_gf(py_type = "GfReTime", c_tag = "retime")
+
+g.add_method(py_name = "set_from_inverse_fourier",
+             signature = "void(gf_view<refreq> gw)",
+             calling_pattern = "self_c = inverse_fourier(*gw)",
+             doc = """Fills self with the Inverse Fourier transform of gw""")
+
+module.add_class(g)
+
+# EXPERIMENTAL : global fourier functions....
+
+module.add_function(name = "make_gf_from_inverse_fourier", signature="gf_view<retime>(gf_view<refreq> gw)", doc ="")
+
+########################
+##   Code generation
+########################
+
+if __name__ == '__main__' :
+   module.generate_code(mako_template = sys.argv[1], wrap_file = sys.argv[2])
+

pytriqs/gf/local/tools.py

@@ -1,5 +1,5 @@
 from types import SliceType
-import descriptors
+import descriptor_base
 
 class LazyCTX:
     def __init__ (self, G): 
@@ -10,60 +10,16 @@ class LazyCTX:
     def __eq__ (self, y):
         return isinstance(y, self.__class__) and self._is_compatible_for_ops(y.G)
     def __call__ (self, x): 
-        if not isinstance(x, descriptors.Base): return x
+        if not isinstance(x, descriptor_base.Base): return x
         tmp = self.G.copy()
         x(tmp)
         return tmp
 
-class IndicesConverter: 
-    def __init__(self, indices): 
-        if indices == None: # none is a trivial converter
-            self.indices=None
-            return
-
-        try: 
-            self.indices = list(indices)[:] # make a copy
-        except:
-            raise RuntimeError, "Indices must be a list or transformable into a list %s"(indices,)
-        assert len(set(repr(x) for x in self.indices)) == len(self.indices), "Error: indices are not unique !!!"
-        assert self.indices != [], "Error: indices are empty!!!"
-        try:
-            # a continuous list of ordered integers
-            self.__indices_are_sliceable = (self.indices== range(min(self.indices),max(self.indices)+1)) 
-            self.__indexmin = min(self.indices)
-            self.__indexmax = max(self.indices)
-            #self.__indexlen = self.__indexmax - self.__indexmin +1
-        except:
-            self.__indices_are_sliceable =False
-        self.Length = len(self.indices)
-    
-    def convertToNumpyIndex(self,a,noslice=False):
-        """
-        Transcription of one Python index/slice into the index/slice of the numpy
-        """
-        if self.indices==None: 
-            if type(a)==SliceType: return a
-            return a if noslice else slice(a,a+1,1)
-
-        if type(a)==SliceType:
-            if not self.__indices_are_sliceable: raise IndexError, "Indices %s can't be sliced"%self.indices
-            # put the slice to start at 0, and clip it
-            sta,sto,ste = slice(a.start, a.stop , a.step).indices(self.__indexmax+1)
-            return slice( max(0,sta-self.__indexmin), sto - self.__indexmin, ste)
-                    
-        try:
-            s1 = self.indices.index(a) 
-        except:
-            raise IndexError, "Index %s out of range %s"%(a,self.indices)
-        return s1 if noslice else slice(s1,s1+1,1)
-
 def get_indices_in_dict( d): 
-    # exclusive: size = (n1,n2) or IndicesL/R
+    if not ( ('indicesL' in d and 'indicesR' in d) or 'indices' in d) : return ()
-    if 'indices_pack' in d: 
+
-        indicesL, indicesR = d.pop('indices_pack')
+    indicesL = list ( d.pop('indicesL',()) or d.pop('indices',()) )
-    else:
+    indicesR = list ( d.pop('indicesR',()) or indicesL  )
-        indicesL = list ( d.pop('indicesL',()) or d.pop('indices',()) )
-        indicesR = list ( d.pop('indicesR',()) or indicesL  )
 
     # Now check the indices
     ty = set([type(x) for x in indicesL]+[type(x) for x in indicesR])
@@ -76,7 +32,5 @@ def get_indices_in_dict( d):
 
     return indicesL, indicesR
 
-def py_deserialize( cls, s): 
-    return cls(boost_serialization_string = s)
 
 

test/pytriqs/base/gf_base_op.py

@@ -61,17 +61,11 @@ h['ga2'] = ga2
 Gc = G.conjugate()
 h['Gc'] = Gc
 
-# Some tail stuff:
-tailtempl={}
-for sig,g in G: 
-    tailtempl[sig] = copy.deepcopy(g.tail)
-h['tt'] = tailtempl
-
-
 # tranpose
 g = G['a']
-gt = G['a'].transpose()
+if 0 : 
-gt.data[3,0,1] = 100
+    gt = G['a'].transpose()
-assert g.data[3,1,0] == 100
+    gt.data[3,0,1] = 100
+    assert g.data[3,1,0] == 100
 
 del h

triqs/gfs/gf.hpp

@@ -19,6 +19,7 @@
  *
  ******************************************************************************/
 #pragma once
+#define TRIQS_GF_INCLUDED
 #include <triqs/utility/first_include.hpp>
 #include <triqs/utility/std_vector_expr_template.hpp>
 #include <triqs/utility/factory.hpp>

triqs/gfs/meshes/matsubara_freq.hpp

@@ -148,7 +148,9 @@ namespace gfs {
   friend class boost::serialization::access;
   ///  BOOST Serialization
   template <class Archive> void serialize(Archive &ar, const unsigned int version) {
-   ar &TRIQS_MAKE_NVP("domain", _dom);
+   ar &TRIQS_MAKE_NVP("beta", _dom.beta);
+   ar &TRIQS_MAKE_NVP("statistic", _dom.statistic);
+   //ar &TRIQS_MAKE_NVP("domain", _dom);
    ar &TRIQS_MAKE_NVP("size", _n_pts);
    ar &TRIQS_MAKE_NVP("kind", _positive_only);
   }