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diff --git a/patsy/highlevel.py b/patsy/highlevel.py
index 78d2942..298739d 100644
--- a/patsy/highlevel.py
+++ b/patsy/highlevel.py
@@ -178,7 +178,7 @@ def _do_highlevel_design(formula_like, data, eval_env,
else:
# subok=True is necessary here to allow DesignMatrixes to pass
# through
- (lhs, rhs) = (None, asarray_or_pandas(formula_like, subok=True))
+ (lhs, rhs) = (None, asarray_or_pandas(formula_like, subok=True, copy=None))
# some sort of explicit matrix or matrices were given. Currently we
# have them in one of these forms:
# -- an ndarray or subclass
diff --git a/patsy/state.py b/patsy/state.py
index 933c588..c489a4b 100644
--- a/patsy/state.py
+++ b/patsy/state.py
@@ -103,7 +103,7 @@ class Center(object):
pass
def transform(self, x):
- x = asarray_or_pandas(x)
+ x = asarray_or_pandas(x, copy=None)
# This doesn't copy data unless our input is a DataFrame that has
# heterogeneous types. And in that case we're going to be munging the
# types anyway, so copying isn't a big deal.
diff --git a/patsy/util.py b/patsy/util.py
index 3116e11..7ac6f79 100644
--- a/patsy/util.py
+++ b/patsy/util.py
@@ -69,7 +69,7 @@ def asarray_or_pandas(a, copy=False, dtype=None, subok=False):
def test_asarray_or_pandas():
import warnings
- assert type(asarray_or_pandas([1, 2, 3])) is np.ndarray
+ assert type(asarray_or_pandas([1, 2, 3], copy=True)) is np.ndarray
with warnings.catch_warnings() as w:
warnings.filterwarnings('ignore', 'the matrix subclass',
PendingDeprecationWarning)
@@ -83,9 +83,9 @@ def test_asarray_or_pandas():
assert np.array_equal(a, a_copy)
a_copy[0] = 100
assert not np.array_equal(a, a_copy)
- assert np.allclose(asarray_or_pandas([1, 2, 3], dtype=float),
+ assert np.allclose(asarray_or_pandas([1, 2, 3], dtype=float, copy=None),
[1.0, 2.0, 3.0])
- assert asarray_or_pandas([1, 2, 3], dtype=float).dtype == np.dtype(float)
+ assert asarray_or_pandas([1, 2, 3], dtype=float, copy=None).dtype == np.dtype(float)
a_view = asarray_or_pandas(a, dtype=a.dtype)
a_view[0] = 99
assert a[0] == 99
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