def test_pickle_1(self): # Issue #1529 a = np.array([(1, [])], dtype=[('a', np.int32), ('b', np.int32, 0)]) for proto in range(2, pickle.HIGHEST_PROTOCOL + 1): assert_equal(a, pickle.loads(pickle.dumps(a, protocol=proto))) assert_equal(a[0], pickle.loads(pickle.dumps(a[0], protocol=proto)))
def test_novalue(): import numpy as np for proto in range(2, pickle.HIGHEST_PROTOCOL + 1): assert_equal(repr(np._NoValue), '<no value>') assert_( pickle.loads(pickle.dumps(np._NoValue, protocol=proto)) is np._NoValue)
def test_pickling_subbaseclass(self): # Test pickling w/ a subclass of ndarray a = masked_array(np.matrix(list(range(10))), mask=[1, 0, 1, 0, 0] * 2) for proto in range(2, pickle.HIGHEST_PROTOCOL + 1): a_pickled = pickle.loads(pickle.dumps(a, protocol=proto)) assert_equal(a_pickled._mask, a._mask) assert_equal(a_pickled, a) assert_(isinstance(a_pickled._data, np.matrix))
def test_pickle_3(self): # Issue #7140 a = self.data for proto in range(2, pickle.HIGHEST_PROTOCOL + 1): pa = pickle.loads(pickle.dumps(a[0], protocol=proto)) assert_(pa.flags.c_contiguous) assert_(pa.flags.f_contiguous) assert_(pa.flags.writeable) assert_(pa.flags.aligned)
def test_testPickle(self): # Test of pickling x = arange(12) x[4:10:2] = masked x = x.reshape(4, 3) for proto in range(2, pickle.HIGHEST_PROTOCOL + 1): s = pickle.dumps(x, protocol=proto) y = pickle.loads(s) assert_(eq(x, y))
def test_pickling(self): # Test pickling base = self.base.copy() mrec = base.view(mrecarray) for proto in range(2, pickle.HIGHEST_PROTOCOL + 1): _ = pickle.dumps(mrec, protocol=proto) mrec_ = pickle.loads(_) assert_equal(mrec_.dtype, mrec.dtype) assert_equal_records(mrec_._data, mrec._data) assert_equal(mrec_._mask, mrec._mask) assert_equal_records(mrec_._mask, mrec._mask)
def check_pickling(self, dtype): for proto in range(pickle.HIGHEST_PROTOCOL + 1): pickled = pickle.loads(pickle.dumps(dtype, proto)) assert_equal(pickled, dtype) assert_equal(pickled.descr, dtype.descr) if dtype.metadata is not None: assert_equal(pickled.metadata, dtype.metadata) # Check the reconstructed dtype is functional x = np.zeros(3, dtype=dtype) y = np.zeros(3, dtype=pickled) assert_equal(x, y) assert_equal(x[0], y[0])
def test_novalue(): import numpy as np for proto in range(2, pickle.HIGHEST_PROTOCOL + 1): assert_equal(repr(np._NoValue), '<no value>') assert_(pickle.loads(pickle.dumps(np._NoValue, protocol=proto)) is np._NoValue)
def test_pickle(self): for proto in range(2, pickle.HIGHEST_PROTOCOL + 1): roundtripped = pickle.loads( pickle.dumps(dispatched_one_arg, protocol=proto)) assert_(roundtripped is dispatched_one_arg)
def test_pickle_2(self): a = self.data for proto in range(2, pickle.HIGHEST_PROTOCOL + 1): assert_equal(a, pickle.loads(pickle.dumps(a, protocol=proto))) assert_equal(a[0], pickle.loads(pickle.dumps(a[0], protocol=proto)))