def test_tables():
ip = RInterpreter()
t = toTable("a", [1, 2])
# transfer Table tor R:
ip.t = t
# fetch Table from R
assert ip.execute("s <- t").s.rows == t.rows
# fetch pandas.DataFrame from R
df = ip.get_raw("s")
assert df.as_matrix().tolist() == [[1], [2]]
def test_native_types():
ip = RInterpreter()
assert ip.execute("x <-3").x == 3
assert ip.execute("x <-1.0").x == 1.0
assert ip.execute("x <-'abc'").x == 'abc'
ip.y = 42
assert ip.execute("x <- y").x == 42
ip.y = 1.0
assert ip.execute("x <- y").x == 1.0
ip.y = "abc"
assert ip.execute("x <- y").x == "abc"
def test_table_full(regtest):
t = toTable("names", ("uwe", "schmit"), type_=str)
t.addColumn("idx", (1, 2), type_=int)
t.addColumn("mass", (1.0, 1.11), type_=float)
t.addColumn("class", (True, False), type_=bool)
ip = RInterpreter()
ip.t = t
print >> regtest, t
print >> regtest, ip.t
print >> regtest, ip.get_df_as_table("t")
print >> regtest, ip.get_df_as_table("t", types=dict(idx=long))
print >> regtest, map(type, t._colNames)
print >> regtest, map(type, ip.t._colNames)
print >> regtest, t._colTypes
print >> regtest, ip.t._colTypes
def test_table_full(regtest):
t = toTable("names", ("uwe", "schmit"), type_=str)
t.addColumn("idx", (1, 2), type_=int)
t.addColumn("mass", (1.0, 1.11), type_=float)
t.addColumn("class", (True, False), type_=bool)
ip = RInterpreter()
ip.t = t
print >> regtest, t
print >> regtest, ip.t
print >> regtest, ip.get_df_as_table("t")
print >> regtest, ip.get_df_as_table("t", types=dict(idx=long))
print >> regtest, map(type, t._colNames)
print >> regtest, map(type, ip.t._colNames)
print >> regtest, t._colTypes
print >> regtest, ip.t._colTypes
def test_interpolation():
ip = RInterpreter()
ip.execute("x<-%(name)r", name="Uwe")
assert ip.x == "Uwe"
def test_native_types():
ip = RInterpreter()
_test_native_types(ip)
def test_tables(regtest):
ip = RInterpreter()
_test_tables(ip, regtest)
def test_interpolation():
ip = RInterpreter()
ip.execute("x<-%(name)r", name="Uwe")
assert ip.x == "Uwe"