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Clean up _gf_common.py -- removed duplicated python functions
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@ -100,61 +100,3 @@ def _ilshift_(self, A):
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else:
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raise RuntimeError, " <<= operator: RHS not understood"
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return self
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#---------------------------------------------------
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def from_L_G_R(self, L, G, R):
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N1 = self.data.shape[1]
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N2 = self.data.shape[2]
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assert L.shape[0] == N1
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assert L.shape[1] == G.data.shape[1]
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assert R.shape[0] == G.data.shape[2]
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assert R.shape[1] == N2
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MatrixStack(self.data).matmul_L_R(L, G.data, R)
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# this might be a bit slow
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for o in range(G.tail.order_min, G.tail.order_max+1):
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self.tail[o] = numpy.dot(L, numpy.dot(G.tail[o], R))
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self.tail.mask.fill(G.tail.order_max)
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#---------------------------------------------------
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def invert(self):
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"""Invert the matrix for all arguments"""
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MatrixStack(self.data).invert()
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self.tail.invert()
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#---------------------------------------------------
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# FIXME NEVER USED CLEAN UP
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#def transpose(self):
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# """Transposes the GF Bloc: return a new transposed view"""
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# ### WARNING: this depends on the C++ layering ....
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# return self.__class__(
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# indices = list(self.indices),
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# mesh = self.mesh,
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# data = self.data.transpose( (0, 2, 1) ),
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# tail = self.tail.transpose(),
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# name = self.name+'(t)')
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#---------------------------------------------------
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def conjugate(self):
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"""Complex conjugate of the GF Bloc. It follow the policy of numpy and
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make a copy only if the Green function is complex valued"""
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return self.__class__(
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indices = list(self.indices),
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mesh = self.mesh,
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data = self.data.conjugate(),
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tail = self.tail.conjugate(),
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name = self.name+'*')
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#------------------ Density -----------------------------------
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def total_density(self):
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"""Trace density"""
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return numpy.trace(self.density())
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