/usr/lib/python3/dist-packages/rpy2/robjects/tests/testNumpyConversions.py is in python3-rpy2 2.8.5-1.
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import sys
import rpy2.robjects as robjects
import rpy2.robjects.conversion as conversion
r = robjects.r
has_numpy = True
try:
import numpy
import rpy2.robjects.numpy2ri as rpyn
except:
has_numpy = False
@unittest.skipUnless(has_numpy, 'numpy is not available in python')
class NumpyConversionsTestCase(unittest.TestCase):
def setUp(self):
#self._py2ri = robjects.conversion.py2ri
#self._ri2py = robjects.conversion.ri2py
rpyn.activate()
def tearDown(self):
rpyn.deactivate()
def testActivate(self):
rpyn.deactivate()
#FIXME: is the following still making sense ?
self.assertNotEqual(rpyn.py2ri, conversion.py2ri)
l = len(conversion.py2ri.registry)
k = set(conversion.py2ri.registry.keys())
rpyn.activate()
self.assertTrue(len(conversion.py2ri.registry) > l)
rpyn.deactivate()
self.assertEqual(l, len(conversion.py2ri.registry))
self.assertEqual(k, set(conversion.py2ri.registry.keys()))
def testActivateTwice(self):
rpyn.deactivate()
#FIXME: is the following still making sense ?
self.assertNotEqual(rpyn.py2ri, conversion.py2ri)
l = len(conversion.py2ri.registry)
k = set(conversion.py2ri.registry.keys())
rpyn.activate()
rpyn.deactivate()
rpyn.activate()
self.assertTrue(len(conversion.py2ri.registry) > l)
rpyn.deactivate()
self.assertEqual(l, len(conversion.py2ri.registry))
self.assertEqual(k, set(conversion.py2ri.registry.keys()))
def checkHomogeneous(self, obj, mode, storage_mode):
converted = conversion.py2ri(obj)
self.assertEqual(r["mode"](converted)[0], mode)
self.assertEqual(r["storage.mode"](converted)[0], storage_mode)
self.assertEqual(list(obj), list(converted))
self.assertTrue(r["is.array"](converted)[0])
return converted
def testVectorBoolean(self):
l = [True, False, True]
b = numpy.array(l, dtype=numpy.bool_)
b_r = self.checkHomogeneous(b, "logical", "logical")
self.assertTupleEqual(tuple(l), tuple(b_r))
def testVectorInteger(self):
l = [1, 2, 3]
i = numpy.array(l, dtype="i")
i_r = self.checkHomogeneous(i, "numeric", "integer")
self.assertTupleEqual(tuple(l), tuple(i_r))
def testVectorFloat(self):
l = [1.0, 2.0, 3.0]
f = numpy.array(l, dtype="f")
f_r = self.checkHomogeneous(f, "numeric", "double")
for orig, conv in zip(l, f_r):
self.assertTrue(abs(orig-conv) < 0.000001)
def testVectorComplex(self):
l = [1j, 2j, 3j]
c = numpy.array(l, dtype=numpy.complex_)
c_r = self.checkHomogeneous(c, "complex", "complex")
for orig, conv in zip(l, c_r):
self.assertTrue(abs(orig.real-conv.real) < 0.000001)
self.assertTrue(abs(orig.imag-conv.imag) < 0.000001)
@unittest.skipUnless(sys.version_info[0] < 3,
"Test only relevant if Python < 3.")
def testVectorCharacter(self):
l = ["a", "b", "c"]
s = numpy.array(l, dtype="S")
s_r = self.checkHomogeneous(s, "character", "character")
self.assertTupleEqual(tuple(l), tuple(s_r))
def testVectorUnicodeCharacter(self):
l = [u"a", u"b", u"c"]
u = numpy.array(l, dtype="U")
u_r = self.checkHomogeneous(u, "character", "character")
self.assertTupleEqual(tuple(l), tuple(u_r))
def testArray(self):
i2d = numpy.array([[1, 2, 3], [4, 5, 6]], dtype="i")
i2d_r = conversion.py2ri(i2d)
self.assertEqual(r["storage.mode"](i2d_r)[0], "integer")
self.assertEqual(tuple(r["dim"](i2d_r)), (2, 3))
# Make sure we got the row/column swap right:
self.assertEqual(r["["](i2d_r, 1, 2)[0], i2d[0, 1])
f3d = numpy.arange(24, dtype="f").reshape((2, 3, 4))
f3d_r = conversion.py2ri(f3d)
self.assertEqual(r["storage.mode"](f3d_r)[0], "double")
self.assertEqual(tuple(r["dim"](f3d_r)), (2, 3, 4))
# Make sure we got the row/column swap right:
self.assertEqual(r["["](f3d_r, 1, 2, 3)[0], f3d[0, 1, 2])
def testScalar(self):
i32 = numpy.int32(100)
i32_r = conversion.py2ri(i32)
i32_test = numpy.array(i32_r)[0]
self.assertEqual(i32, i32_test)
i64 = numpy.int64(100)
i64_r = conversion.py2ri(i64)
i64_test = numpy.array(i64_r)[0]
self.assertEqual(i64, i64_test)
f128 = numpy.float128(100.000000003)
f128_r = conversion.py2ri(f128)
f128_test = numpy.array(f128_r)[0]
self.assertEqual(f128, f128_test)
def testObjectArray(self):
o = numpy.array([1, "a", 3.2], dtype=numpy.object_)
o_r = conversion.py2ri(o)
self.assertEqual(r["mode"](o_r)[0], "list")
self.assertEqual(r["[["](o_r, 1)[0], 1)
self.assertEqual(r["[["](o_r, 2)[0], "a")
self.assertEqual(r["[["](o_r, 3)[0], 3.2)
def testRecordArray(self):
rec = numpy.array([(1, 2.3), (2, -0.7), (3, 12.1)],
dtype=[("count", "i"), ("value", numpy.double)])
rec_r = conversion.py2ri(rec)
self.assertTrue(r["is.data.frame"](rec_r)[0])
self.assertEqual(tuple(r["names"](rec_r)), ("count", "value"))
count_r = r["$"](rec_r, "count")
value_r = r["$"](rec_r, "value")
self.assertEqual(r["storage.mode"](count_r)[0], "integer")
self.assertEqual(r["storage.mode"](value_r)[0], "double")
self.assertEqual(count_r[1], 2)
self.assertEqual(value_r[2], 12.1)
def testBadArray(self):
u = numpy.array([1, 2, 3], dtype=numpy.uint32)
self.assertRaises(ValueError, conversion.py2ri, u)
def testAssignNumpyObject(self):
x = numpy.arange(-10., 10., 1)
env = robjects.Environment()
env["x"] = x
self.assertEqual(1, len(env))
# do have an R object of the right type ?
x_r = env["x"]
self.assertEqual(robjects.rinterface.REALSXP, x_r.typeof)
#
self.assertEqual((20,), tuple(x_r.dim))
def testDataFrameToNumpy(self):
df = robjects.vectors.DataFrame(dict((('a', 1), ('b', 2))))
rec = conversion.ri2py(df)
self.assertEqual(numpy.recarray, type(rec))
self.assertEqual(1, rec.a[0])
self.assertEqual(2, rec.b[0])
def testAtomicVectorToNumpy(self):
v = robjects.vectors.IntVector((1,2,3))
a = rpyn.ri2py(v)
self.assertTrue(isinstance(a, numpy.ndarray))
self.assertEqual(1, v[0])
def testRx2(self):
df = robjects.vectors.DataFrame({
"A": robjects.vectors.IntVector([1,2,3]),
"B": robjects.vectors.IntVector([1,2,3])})
b = df.rx2('B')
self.assertEquals(tuple((1,2,3)), tuple(b))
def suite():
if has_numpy:
return unittest.TestLoader().loadTestsFromTestCase(NumpyConversionsTestCase)
else:
return unittest.TestLoader().loadTestsFromTestCase(MissingNumpyDummyTestCase)
if __name__ == '__main__':
unittest.main()
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