Changeset 805 for codes/icosagcm/devel/Python/dynamico/dev/numba.py

Timestamp:

02/08/19 08:10:04 (6 years ago)

Author:

dubos

Message:

devel/Python : moving Fortran-based features to dynamico.dev module (TBC)

File:

• codes/icosagcm/devel/Python/dynamico/dev/numba.py (modified) (1 diff)

codes/icosagcm/devel/Python/dynamico/dev/numba.py

@@ -6 +6 @@
 import numba
 
-def store_data(obj,*args):
-    """Returns a jitclass instance containing attributes copied from obj. *args is of the form type,names,type,names ... where names is a string 'attr1 attr2 attr3' containing space-separated names of attributes of obj. Those attributes are declared to numba with the type preceding them. The result of store_data can be used as argument to a @jit function."""
-    spec = []
-    for item in args:
-        if isinstance(item,str): 
-            spec = spec + [(name,thetype) for name in item.split(' ')]
-        else:
-            thetype=item
-    @numba.jitclass(spec)
-    class JitClass(object):
-        def __init__(self): pass
-    data=JitClass()
-    for name,thetype in spec: setattr(data, name, getattr(obj,name))
-    return data
+class NumbaData(object):
+    """A base class to extract data from derived class instances and use it as argument to @jit functions. Derived classes must set the 'signature' attribute."""
+    def data(self):
+        """Returns a jitclass instance containing attributes copied from self, using self.signature which is of the form type,names,type,names ... where names is a string 'attr1 attr2 attr3' containing space-separated names of attributes of self. Those attributes are declared to numba with the type preceding them. The result of data() can be used as argument to a @jit function."""
+        spec = []
+        for item in self.signature:
+            if isinstance(item,str): 
+                spec = spec + [(name,thetype) for name in item.split(' ')]
+            else:
+                thetype=item
+        @numba.jitclass(spec)
+        class JitClass(object):
+            def __init__(self): pass
+        data=JitClass()
+        for name,thetype in spec: setattr(data, name, getattr(self,name))
+        return data
 
 jit=numba.jit(nopython=True, nogil=True, error_model='numpy', fastmath=True)