return vectors instead of structured arrays when 1d and no names

IPython/extensions/rmagic.py

@@ -72,11 +72,19 b' def Rconverter(Robj):'
     Robj: an R object returned from rpy2
     """
     if is_data_frame(Robj):
-        names = np.array(Robj.do_slot('names'))
-        Robj = np.rec.fromarrays(Robj, names = tuple(names))
+        dimRobj = dimR(Robj)
+        if dimRobj != ri.NULL:
+            dimRobj = list(np.array(dimRobj))
+            if len(dimRobj) > 1:
+                try:
+                    names = np.array(Robj.do_slot('names'))
+                    Robj = np.rec.fromarrays(Robj, names = tuple(names))
+                except LookupError:
+                    pass
     return np.asarray(Robj)
 
 is_data_frame = None
+dimR = None
 
 @magics_class
 class RMagics(Magics):
@@ -105,8 +113,9 b' class RMagics(Magics):'
         self.cache_display_data = cache_display_data
 
         self.r = ro.R()
-        global is_data_frame
+        global is_data_frame, dimR
         is_data_frame = self.r('is.data.frame')
+        dimR = self.r('dim')
 
         self.Rstdout_cache = []
         self.pyconverter = pyconverter

IPython/extensions/tests/test_rmagic.py

@@ -1,6 +1,7 b''
 import numpy as np
 from IPython.core.interactiveshell import InteractiveShell
 from IPython.extensions import rmagic
+import nose.tools as nt
 
 ip = get_ipython()
 ip.magic('load_ext rmagic')
@@ -20,19 +21,39 b' def test_pull():'
     np.testing.assert_almost_equal(np.asarray(rm.r('Z')), ip.user_ns['Z'])
     np.testing.assert_almost_equal(ip.user_ns['Z'], np.arange(11,21))
 
-# def test_inline():
-#     rm = rmagic.RMagics(ip)
-#     c = ip.run_line_magic('Rinline', 'lm(Y~X)$coef')
-#     np.testing.assert_almost_equal(c, [3.2, 0.9])
+def test_Rconverter():
+    datapy= np.array([(1, 2.9, 'a'), (2, 3.5, 'b'), (3, 2.1, 'c')], 
+          dtype=[('x', '<i4'), ('y', '<f8'), ('z', '|S1')])
+    ip.user_ns['datapy'] = datapy
+    ip.run_line_magic('Rpush', 'datapy')
+
+    # test to see if a copy is being made
+    v = ip.run_line_magic('R', 'datapy')
+    w = ip.run_line_magic('R', 'datapy')
+    np.testing.assert_almost_equal(w['x'], v['x'])
+    np.testing.assert_almost_equal(w['y'], v['y'])
+    nt.assert_true(np.all(w['z'] == v['z']))
+    np.testing.assert_equal(id(w.data), id(v.data))
+    nt.assert_equal(w.dtype, v.dtype)
+
+    ip.run_cell_magic('R', ' -o datar datar=datapy', '')
+
+    u = ip.run_line_magic('R', 'datar')
+    np.testing.assert_almost_equal(u['x'], v['x'])
+    np.testing.assert_almost_equal(u['y'], v['y'])
+    nt.assert_true(np.all(u['z'] == v['z']))
+    np.testing.assert_equal(id(u.data), id(v.data))
+    nt.assert_equal(u.dtype, v.dtype)
+
 
 def test_cell_magic():
 
     ip.push({'x':np.arange(5), 'y':np.array([3,5,4,6,7])})
     snippet = '''
     print(summary(a))
-    plot(X, Y, pch=23, bg='orange', cex=2)
-    plot(Y, X)
-    print(summary(X))
+    plot(x, y, pch=23, bg='orange', cex=2)
+    plot(x, x)
+    print(summary(x))
     r = resid(a)
     xc = coef(a)
     '''