def test_from_and_to_numpy():
# This also tests __array_interface__
for dtype in ['float32', 'float64', 'int32', 'uint32', 'uint8', 'int8']:
for data in [[1, 2, 3, 4, 5, 6, 7, 8],
[[1, 2], [3, 4], [5, 6], [7, 8]],
[[[1, 2], [3, 4]],[[5, 6], [7, 8]]],
]:
# Convert from numpy, from tinynumpy, to numpy
a1 = np.array(data, dtype)
b1 = tnp.array(a1)
b2 = tnp.array(b1)
a2 = np.array(b2)
# Check if its the same
for c in [b1, b2, a2]:
assert a1.shape == c.shape
assert a1.dtype == c.dtype
assert a1.strides == c.strides
assert (a1 == c).all()
# Also test using a numpy array as a buffer
a = np.array([[1, 2], [3, 4], [5, 6], [7, 8]], 'float32')
b = tnp.ndarray(a.shape, a.dtype, strides=a.strides, buffer=a.ravel())
assert (a==b).all()
# Test that is indeed same data
a[0, 0] = 99
assert (a==b).all()
def test_from_and_to_numpy():
# This also tests __array_interface__
for dtype in ['float32', 'float64', 'int32', 'uint32', 'uint8', 'int8']:
for data in [
[1, 2, 3, 4, 5, 6, 7, 8],
[[1, 2], [3, 4], [5, 6], [7, 8]],
[[[1, 2], [3, 4]], [[5, 6], [7, 8]]],
]:
# Convert from numpy, from tinynumpy, to numpy
a1 = np.array(data, dtype)
b1 = tnp.array(a1)
b2 = tnp.array(b1)
a2 = np.array(b2)
# Check if its the same
for c in [b1, b2, a2]:
assert a1.shape == c.shape
assert a1.dtype == c.dtype
assert a1.strides == c.strides
assert (a1 == c).all()
# Also test using a numpy array as a buffer
a = np.array([[1, 2], [3, 4], [5, 6], [7, 8]], 'float32')
b = tnp.ndarray(a.shape, a.dtype, strides=a.strides, buffer=a.ravel())
assert (a == b).all()
# Test that is indeed same data
a[0, 0] = 99
assert (a == b).all()
def setUp(self):
a0 = [[[1, [1, 1, 1, 1], [2, 2], [2, 2]], 1], [2, 2, 1, 1], [3, 3],
[3, 3]]
self.t0 = tinynumpy.array(a0)
a1 = [[1, 2], [3, 4]]
self.t1 = tinynumpy.array(a1)
self.n1 = numpy.array(a1)
def test_dtype():
for shape in [(9, ), (9, 4), (9, 4, 5)]:
for dtype in ['bool', 'int8', 'uint8', 'int16', 'uint16',
'int32', 'uint32', 'float32', 'float64']:
a = np.empty(shape, dtype=dtype)
b = tnp.empty(shape, dtype=dtype)
assert a.shape == b.shape
assert a.dtype == b.dtype
assert a.itemsize == b.itemsize
raises(TypeError, tnp.zeros, (9, ), 'blaa')
assert tnp.array([1.0, 2.0]).dtype == 'float64'
assert tnp.array([1, 2]).dtype == 'int64'
def setUp(self):
a = [[ 1.0, 2.0, 3.0, 4.0],
[ 5.0, 6.0, 7.0, 8.0],
[ 9.0,10.0,11.0,12.0],
[13.0,14.0,15.0,16.0]]
self.t0 = tinynumpy.array(a)
self.n0 = numpy.array(a)
def test_dtype():
for shape in [(9, ), (9, 4), (9, 4, 5)]:
for dtype in [
'bool', 'int8', 'uint8', 'int16', 'uint16', 'int32', 'uint32',
'float32', 'float64'
]:
a = np.empty(shape, dtype=dtype)
b = tnp.empty(shape, dtype=dtype)
assert a.shape == b.shape
assert a.dtype == b.dtype
assert a.itemsize == b.itemsize
raises(TypeError, tnp.zeros, (9, ), 'blaa')
assert tnp.array([1.0, 2.0]).dtype == 'float64'
assert tnp.array([1, 2]).dtype == 'int64'
def test_subtract():
"""test the addition function for tinynumpy"""
x = [5, -2, 1]
y = [0, 3, -1]
a = tnp.add(x, y)
assert a == tnp.array([5, -5, -2], dtype='int64')
def test_divide():
"""test the addition function for tinynumpy"""
x = [15, -12, 3]
y = 3
a = tnp.divide(x, y)
assert a == tnp.array([5, -4, 1], dtype='int64')
def test_multiply():
"""test the addition function for tinynumpy"""
x = [5, -2, 1]
y = [0, 3, -1]
a = tnp.multiply(x, y)
assert a == tnp.array([0, -6, -1], dtype='int64')
def test_subtract():
"""test the addition function for tinynumpy"""
x = [5, -2, 1]
y = [0, 3, -1]
a = tnp.add(x,y)
assert a == tnp.array([5, -5, -2], dtype='int64')
def test_divide():
"""test the addition function for tinynumpy"""
x = [15, -12, 3]
y = 3
a = tnp.divide(x,y)
assert a == tnp.array([5, -4, 1], dtype='int64')
def test_multiply():
"""test the addition function for tinynumpy"""
x = [5, -2, 1]
y = [0, 3, -1]
a = tnp.multiply(x,y)
assert a == tnp.array([0, -6, -1], dtype='int64')
def setUp(self):
a0 = [
[
[
1,
[1, 1, 1, 1],
[2, 2],
[2, 2]
],
1
],
[2, 2, 1, 1],
[3, 3],
[3, 3]
]
self.t0 = tinynumpy.array(a0)
a1 = [[1,2],[3,4]]
self.t1 = tinynumpy.array(a1)
self.n1 = numpy.array(a1)
def test_repr():
for dtype in ['float32', 'float64', 'int32', 'int64']:
for data in [[1, 2, 3, 4, 5, 6, 7, 8],
[[1, 2], [3, 4], [5, 6], [7, 8]],
[[[1, 2], [3, 4]],[[5, 6], [7, 8]]],
]:
a = np.array(data, dtype)
b = tnp.array(data, dtype)
# Compare line by line (forget leading whitespace)
charscompared = 0
for l1, l2 in zip(repr(a).splitlines(), repr(b).splitlines()):
l1, l2 = l1.rstrip(), l2.rstrip()
l1, l2 = l1.split('dtype=')[0], l2.split('dtype=')[0]
assert l1 == l2
charscompared += len(l1)
assert charscompared > (3 * b.size)
def test_repr():
for dtype in ['float32', 'float64', 'int32', 'int64']:
for data in [
[1, 2, 3, 4, 5, 6, 7, 8],
[[1, 2], [3, 4], [5, 6], [7, 8]],
[[[1, 2], [3, 4]], [[5, 6], [7, 8]]],
]:
a = np.array(data, dtype)
b = tnp.array(data, dtype)
# Compare line by line (forget leading whitespace)
charscompared = 0
for l1, l2 in zip(repr(a).splitlines(), repr(b).splitlines()):
l1, l2 = l1.rstrip(), l2.rstrip()
l1, l2 = l1.split('dtype=')[0], l2.split('dtype=')[0]
assert l1 == l2
charscompared += len(l1)
assert charscompared > (3 * b.size)
def test_reshape():
a = np.array([1, 2, 3, 4, 5, 6, 7, 8], dtype='int32')
b = tnp.array([1, 2, 3, 4, 5, 6, 7, 8], dtype='int32')
for shape in [(2, 4), (4, 2), (2, 2, 2), (8, )]:
a.shape = shape
b.shape = shape
assert a.shape == b.shape
print(repr(a), repr(b), a.strides, b.strides)
assert a.strides == b.strides
a.shape = 2, 4
b.shape = 2, 4
# Test transpose
assert b.T.shape == (4, 2)
assert (a.T == b.T).all()
assert (b.T.T == b).all()
# Make non-contiguous versions
a2 = a[:, 2:]
b2 = b[:, 2:]
# Test contiguous flag
assert a.flags['C_CONTIGUOUS']
assert not a2.flags['C_CONTIGUOUS']
# Test base
assert a2.base is a
assert b2.base is b
assert a2[:].base is a
assert b2[:].base is b
# Fail
with raises(ValueError): # Invalid shape
a.shape = (3, 3)
with raises(ValueError):
b.shape = (3, 3)
with raises(AttributeError): # Cannot reshape non-contiguous arrays
a2.shape = 4,
with raises(AttributeError):
b2.shape = 4,
def test_reshape():
a = np.array([1, 2, 3, 4, 5, 6, 7, 8], dtype='int32')
b = tnp.array([1, 2, 3, 4, 5, 6, 7, 8], dtype='int32')
for shape in [(2, 4), (4, 2), (2, 2, 2), (8,)]:
a.shape = shape
b.shape = shape
assert a.shape == b.shape
print(repr(a), repr(b), a.strides, b.strides)
assert a.strides == b.strides
a.shape = 2, 4
b.shape = 2, 4
# Test transpose
assert b.T.shape == (4, 2)
assert (a.T == b.T).all()
assert (b.T.T == b).all()
# Make non-contiguous versions
a2 = a[:, 2:]
b2 = b[:, 2:]
# Test contiguous flag
assert a.flags['C_CONTIGUOUS']
assert not a2.flags['C_CONTIGUOUS']
# Test base
assert a2.base is a
assert b2.base is b
assert a2[:].base is a
assert b2[:].base is b
# Fail
with raises(ValueError): # Invalid shape
a.shape = (3, 3)
with raises(ValueError):
b.shape = (3, 3)
with raises(AttributeError): # Cannot reshape non-contiguous arrays
a2.shape = 4,
with raises(AttributeError):
b2.shape = 4,
def test_any(self):
self.assertEqual(tinynumpy.array([1, 0, 1]).any(), True)
def test_getitem():
a = np.array([[1, 2, 3, 4], [5, 6, 7, 8]])
b = tnp.array([[1, 2, 3, 4], [5, 6, 7, 8]])
def test_ptp(self):
self.assertEqual(tinynumpy.array([-1, 2, 3]).ptp(), 4)
def test_sum(self):
self.assertEqual(tinynumpy.array([1, 2, -3]).sum(), 0)
def test_any(self):
self.assertEqual(tinynumpy.array([1, 0, 1]).any(), True)
def test_cumprod(self):
self.assertEqual(_clean_repr(tinynumpy.array([1, 2, 3]).cumprod()),
_clean_repr(tinynumpy.array([1, 2, 6])))
def setUp(self):
a = [[1.0, 2.0, 3.0, 4.0], [5.0, 6.0, 7.0, 8.0],
[9.0, 10.0, 11.0, 12.0], [13.0, 14.0, 15.0, 16.0]]
self.t0 = tinynumpy.array(a)
self.n0 = numpy.array(a)
def test_ptp(self):
self.assertEqual(tinynumpy.array([-1, 2, 3]).ptp(), 4)
def test_flatten(self):
self.assertEqual(_clean_repr(self.t1.flatten()), _clean_repr(tinynumpy.array([1, 2, 3, 4])))
def test_var(self):
self.assertEqual(tinynumpy.array([1, 1, 1, 1]).var(), 0)
self.assertEqual(_clean_repr(self.t1.var()),
_clean_repr(self.n1.var()))
def test_var(self):
self.assertEqual(tinynumpy.array([1,1,1,1]).var(), 0)
self.assertEqual(_clean_repr(self.t1.var()), _clean_repr(self.n1.var()))
def test_std(self):
self.assertEqual(tinynumpy.array([1,1,1,1]).std(), 0)
self.assertEqual(int(self.t1.std()*1000000), int(self.n1.std()*1000000))
def setUp(self):
self.t0 = tinynumpy.array([[1.0,2.0],[3.0,4.0]])
self.n0 = numpy.array([[1.0,2.0],[3.0,4.0]])
def test_all(self):
self.assertEqual(tinynumpy.array([1, 0, 1]).all(), False)
def test_argmax(self):
self.assertEqual(tinynumpy.array([1, 2, 3]).argmax(), 2)
def test_cumprod(self):
self.assertEqual(_clean_repr(tinynumpy.array([1, 2, 3]).cumprod()), _clean_repr(tinynumpy.array([1, 2, 6])))
def test_prod(self):
self.assertEqual(tinynumpy.array([1, 2, 3, 10]).prod(), 60)
def test_argmax(self):
self.assertEqual(tinynumpy.array([1, 2, 3]).argmax(), 2)
def test_creating_functions():
# Test array
b1 = tnp.array([[1, 2, 3], [4, 5, 6]])
assert b1.shape == (2, 3)
def test_all(self):
self.assertEqual(tinynumpy.array([1, 0, 1]).all(), False)
def test_getitem():
a = np.array([[1, 2, 3, 4], [5, 6, 7, 8]])
b = tnp.array([[1, 2, 3, 4], [5, 6, 7, 8]])
def test_argmin(self):
self.assertEqual(tinynumpy.array([1, 2, -3]).argmin(), 2)
def test_sum(self):
self.assertEqual(tinynumpy.array([1, 2, -3]).sum(), 0)
def test_prod(self):
self.assertEqual(tinynumpy.array([1, 2, 3, 10]).prod(), 60)
def test_argmin(self):
self.assertEqual(tinynumpy.array([1, 2, -3]).argmin(), 2)
def test_flatten(self):
self.assertEqual(_clean_repr(self.t1.flatten()),
_clean_repr(tinynumpy.array([1, 2, 3, 4])))
def test_creating_functions():
# Test array
b1 = tnp.array([[1, 2, 3], [4, 5, 6]])
assert b1.shape == (2, 3)
def test_std(self):
self.assertEqual(tinynumpy.array([1, 1, 1, 1]).std(), 0)
self.assertEqual(int(self.t1.std() * 1000000),
int(self.n1.std() * 1000000))
def avg(data):
data = remove_all(data, [None, ""])
if len(data) > 0:
if is_number(data[0]): return normalize(tinynumpy.array(data).mean())
else: return __builtin__.max(set(data), key=data.count)
else: return None
def setUp(self):
self.t0 = tinynumpy.array([[1.0, 2.0], [3.0, 4.0]])
self.n0 = numpy.array([[1.0, 2.0], [3.0, 4.0]])
def sum(data):
data = remove_all(data, [None, ""])
if len(data) > 0:
if is_number(data[0]): return normalize(tinynumpy.array(data).sum())
else: return 0
else: return 0
def test_mean(self):
self.assertEqual(tinynumpy.array([-5, 5]).mean(), 0)
def test_mean(self):
self.assertEqual(tinynumpy.array([-5, 5]).mean(), 0)