From c438ac058c541675ec673ea84ce26e3b211a3045 Mon Sep 17 00:00:00 2001
From: Andreas Kloeckner <inform@tiker.net>
Date: Fri, 21 Dec 2012 20:20:26 -0500
Subject: [PATCH] Deal with the fact that loopy is now more strict about type
 inference for complex numbers.

---
 sumpy/codegen.py  | 25 ++++++++++++++++++++++---
 sumpy/layerpot.py |  4 +++-
 sumpy/p2p.py      |  4 +++-
 sumpy/tools.py    | 17 +++++++++++++----
 4 files changed, 41 insertions(+), 9 deletions(-)

diff --git a/sumpy/codegen.py b/sumpy/codegen.py
index 51296c0c..83f7bdb8 100644
--- a/sumpy/codegen.py
+++ b/sumpy/codegen.py
@@ -310,8 +310,23 @@ class MathConstantRewriter(IdentityMapper):
 
 
 
+class ComplexConstantSizer(IdentityMapper):
+    def __init__(self, dtype):
+        self.dtype = dtype
+
+    def map_constant(self, expr):
+        if isinstance(expr, (complex, np.complexfloating)):
+            assert self.dtype.kind == "c"
+            return self.dtype.type(expr)
+        else:
+            return expr
+
+
+
 
-def to_loopy_insns(assignments, vector_names=set(), pymbolic_expr_maps=[]):
+
+def to_loopy_insns(assignments, vector_names=set(), pymbolic_expr_maps=[],
+        complex_dtype=None):
     # convert from sympy
     from pymbolic.sympy_interface import SympyToPymbolicMapper
     sympy_conv = SympyToPymbolicMapper()
@@ -330,6 +345,10 @@ def to_loopy_insns(assignments, vector_names=set(), pymbolic_expr_maps=[]):
     pwr = PowerRewriter()
     ssg = SumSignGrouper()
     fck = FractionKiller()
+    if complex_dtype is not None:
+        ccs = ComplexConstantSizer(np.dtype(complex_dtype))
+    else:
+        ccs = None
 
     def convert_expr(expr):
         expr = bdr(expr)
@@ -338,12 +357,12 @@ def to_loopy_insns(assignments, vector_names=set(), pymbolic_expr_maps=[]):
         expr = pwr(expr)
         expr = fck(expr)
         expr = ssg(expr)
+        if ccs is not None:
+            expr = ccs(expr)
         for m in pymbolic_expr_maps:
             expr = m(expr)
         return expr
 
-
-
     import loopy as lp
     return [
             lp.Instruction(id=None,
diff --git a/sumpy/layerpot.py b/sumpy/layerpot.py
index f9fd1b90..df88c21a 100644
--- a/sumpy/layerpot.py
+++ b/sumpy/layerpot.py
@@ -82,7 +82,9 @@ class LayerPotentialBase(KernelComputation):
                 vector_names=set(["a", "b"]),
                 pymbolic_expr_maps=[
                     expn.kernel.transform_to_code
-                    for expn in self.expansions])
+                    for expn in self.expansions],
+                complex_dtype=np.complex128 # FIXME
+                )
 
         isrc_sym = var("isrc")
         exprs = [
diff --git a/sumpy/p2p.py b/sumpy/p2p.py
index a30614d3..0166a4ca 100644
--- a/sumpy/p2p.py
+++ b/sumpy/p2p.py
@@ -56,7 +56,9 @@ class P2P(KernelComputation):
         from sumpy.codegen import to_loopy_insns
         loopy_insns = to_loopy_insns(sac.assignments.iteritems(),
                 vector_names=set(["d"]),
-                pymbolic_expr_maps=[knl.transform_to_code for knl in self.kernels])
+                pymbolic_expr_maps=[knl.transform_to_code for knl in self.kernels],
+                complex_dtype=np.complex128 # FIXME
+                )
 
         from pymbolic import var
         exprs = [
diff --git a/sumpy/tools.py b/sumpy/tools.py
index b29bb0df..d5c8fa55 100644
--- a/sumpy/tools.py
+++ b/sumpy/tools.py
@@ -32,6 +32,7 @@ def mi_derivative(expr, vector, mi):
 
 
 
+
 def build_matrix(op, dtype=None):
     dtype = dtype or op.dtype
     from pytools import ProgressBar
@@ -161,7 +162,15 @@ class KernelComputation:
         return result
 
     def get_kernel_scaling_assignments(self):
-        from sumpy.codegen import to_loopy_insns
-        return to_loopy_insns(
-                ("knl_%d_scaling" % i, kernel.get_scaling())
-                for i, kernel in enumerate(self.kernels))
+        from pymbolic.sympy_interface import SympyToPymbolicMapper
+        sympy_conv = SympyToPymbolicMapper()
+        from sumpy.codegen import ComplexConstantSizer
+
+        import loopy as lp
+        return [
+                lp.Instruction(id=None,
+                    assignee="knl_%d_scaling" % i,
+                    expression=ComplexConstantSizer(dtype)(
+                        sympy_conv(kernel.get_scaling())),
+                    temp_var_type=dtype)
+                for i, (kernel, dtype) in enumerate(zip(self.kernels, self.value_dtypes))]
-- 
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