def test_dataframe_as_gpu_matrix_null_values():
df = DataFrame()
nelem = 123
na = -10000
refvalues = {}
for k in 'abcd':
df[k] = data = np.random.random(nelem)
bitmask = utils.random_bitmask(nelem)
df[k] = df[k].set_mask(bitmask)
boolmask = np.asarray(utils.expand_bits_to_bytes(bitmask)[:nelem],
dtype=np.bool_)
data[~boolmask] = na
refvalues[k] = data
# Check null value causes error
with pytest.raises(ValueError) as raises:
df.as_gpu_matrix()
raises.match("column 'a' has null values")
for k in df.columns:
df[k] = df[k].fillna(na)
mat = df.as_gpu_matrix().copy_to_host()
for i, k in enumerate(df.columns):
np.testing.assert_array_equal(refvalues[k], mat[:, i])
def test_dataframe_as_gpu_matrix(order):
df = DataFrame()
nelem = 123
for k in 'abcd':
df[k] = np.random.random(nelem)
# Check all columns
mat = df.as_gpu_matrix(order=order).copy_to_host()
assert mat.shape == (nelem, 4)
for i, k in enumerate(df.columns):
np.testing.assert_array_equal(df[k].to_array(), mat[:, i])
# Check column subset
mat = df.as_gpu_matrix(order=order, columns=['a', 'c']).copy_to_host()
assert mat.shape == (nelem, 2)
for i, k in enumerate('ac'):
np.testing.assert_array_equal(df[k].to_array(), mat[:, i])
