From d5870c4e4ba660edc87abaae6f0ff0a6bb6ee1d7 Mon Sep 17 00:00:00 2001
From: Ray Speth <speth@mit.edu>
Date: Fri, 20 Jun 2014 18:45:22 +0000
Subject: [PATCH] [Python] Allow Func1 to accept nearly-scalar types

This includes lists, tuples, and numpy arrays with a single element
---
 interfaces/cython/cantera/func1.pyx          | 17 ++++++++++++-----
 interfaces/cython/cantera/test/test_func1.py | 18 ++++++++++++++++++
 2 files changed, 30 insertions(+), 5 deletions(-)

diff --git a/interfaces/cython/cantera/func1.pyx b/interfaces/cython/cantera/func1.pyx
index 832a4d2ce..945bbe3cc 100644
--- a/interfaces/cython/cantera/func1.pyx
+++ b/interfaces/cython/cantera/func1.pyx
@@ -56,13 +56,20 @@ cdef class Func1:
     """
     def __cinit__(self, c):
         self.exception = None
-        if isinstance(c, (float, int)):
-            self.callable = lambda t: c
-        elif hasattr(c, '__call__'):
+        if hasattr(c, '__call__'):
             self.callable = c
         else:
-            raise TypeError('Func1 must be constructed from a number or a '
-                            'callable object')
+            try:
+                # calling float() converts numpy arrays of size 1 to scalars
+                k = float(c)
+            except TypeError:
+                if hasattr(c, '__len__') and len(c) == 1:
+                    # Handle lists or tuples with a single element
+                    k = float(c[0])
+                else:
+                    raise TypeError('Func1 must be constructed from a number or'
+                                    ' a callable object')
+            self.callable = lambda t: k
 
         self.func = new CxxFunc1(func_callback, <void*>self)
 
diff --git a/interfaces/cython/cantera/test/test_func1.py b/interfaces/cython/cantera/test/test_func1.py
index b16632d9d..d1d53d762 100644
--- a/interfaces/cython/cantera/test/test_func1.py
+++ b/interfaces/cython/cantera/test/test_func1.py
@@ -33,6 +33,24 @@ class TestFunc1(utilities.CanteraTest):
         for t in [0.1, 0.7, 4.5]:
             self.assertNear(f(t), 5)
 
+    def test_sequence(self):
+        f = ct.Func1([5])
+        for t in [0.1, 0.7, 4.5]:
+            self.assertNear(f(t), 5)
+
+        with self.assertRaises(TypeError):
+            ct.Func1([3,4])
+
+    def test_numpy(self):
+        f = ct.Func1(np.array(5))
+        g = ct.Func1(np.array([[5]]))
+        for t in [0.1, 0.7, 4.5]:
+            self.assertNear(f(t), 5)
+            self.assertNear(g(t), 5)
+
+        with self.assertRaises(TypeError):
+            ct.Func1(np.array([3,4]))
+
     def test_failure(self):
         def fails(t):
             raise ValueError('bad')