def testGetOverlap(self):
A = SDR((103, ))
B = SDR((103, ))
assert (A.getOverlap(B) == 0)
A.dense[:10] = 1
B.dense[:20] = 1
A.dense = A.dense
B.dense = B.dense
assert (A.getOverlap(B) == 10)
A.dense[:20] = 1
A.dense = A.dense
assert (A.getOverlap(B) == 20)
A.dense[50:60] = 1
B.dense[0] = 0
A.dense = A.dense
B.dense = B.dense
assert (A.getOverlap(B) == 19)
# Test wrong dimensions
C = SDR((1, 1, 1, 1, 103))
C.randomize(.5)
try:
A.getOverlap(C)
except RuntimeError:
pass
else:
self.fail()
def testExampleUsage(self):
# Make an SDR with 9 values, arranged in a (3 x 3) grid.
X = SDR(dimensions=(3, 3))
# These three statements are equivalent.
X.dense = [[0, 1, 0], [0, 1, 0], [0, 0, 1]]
assert (X.dense.tolist() == [[0, 1, 0], [0, 1, 0], [0, 0, 1]])
assert ([list(v) for v in X.coordinates] == [[0, 1, 2], [1, 1, 2]])
assert (list(X.sparse) == [1, 4, 8])
X.coordinates = [[0, 1, 2], [1, 1, 2]]
assert (X.dense.tolist() == [[0, 1, 0], [0, 1, 0], [0, 0, 1]])
assert ([list(v) for v in X.coordinates] == [[0, 1, 2], [1, 1, 2]])
assert (list(X.sparse) == [1, 4, 8])
X.sparse = [1, 4, 8]
# Access data in any format, SDR will automatically convert data formats,
# even if it was not the format used by the most recent assignment to the
# SDR.
assert (X.dense.tolist() == [[0, 1, 0], [0, 1, 0], [0, 0, 1]])
assert ([list(v) for v in X.coordinates] == [[0, 1, 2], [1, 1, 2]])
assert (list(X.sparse) == [1, 4, 8])
# Data format conversions are cached, and when an SDR value changes the
# cache is cleared.
X.sparse = [1, 2, 3] # Assign new data to the SDR, clearing the cache.
X.dense # This line will convert formats.
X.dense # This line will resuse the result of the previous line
X = SDR((1000, 1000))
data = X.dense
data[0, 4] = 1
data[444, 444] = 1
X.dense = data
assert (list(X.sparse) == [4, 444444])
def testStr(self):
A = SDR((103, ))
B = SDR((100, 100, 1))
A.dense[0] = 1
A.dense[9] = 1
A.dense[102] = 1
A.dense = A.dense
assert (str(A) == "SDR( 103 ) 0, 9, 102")
A.zero()
assert (str(A) == "SDR( 103 )")
B.dense[0, 0, 0] = 1
B.dense[99, 99, 0] = 1
B.dense = B.dense
assert (str(B) == "SDR( 100, 100, 1 ) 0, 9999")
def testChaining(self):
A = SDR([10, 10])
B = Reshape(A, [100])
C = Reshape(B, [4, 25])
D = B.reshape([1, 100]) # Test convenience method.
A.dense.fill(1)
A.dense = A.dense
assert (len(C.sparse) == A.size)
assert (len(D.sparse) == A.size)
del B
def testDenseInplace(self):
# Check that assigning dense data to itself (ie: sdr.dense = sdr.dense)
# is significantly faster than copying the data on assignment.
# Also, it should not be *too* much faster because this test-case is
# tuned to very fast in both situations.
A = SDR(100 * 1000)
B = np.copy(A.dense)
copy_time = time.clock()
for i in range(100):
A.dense = B
copy_time = time.clock() - copy_time
inplace_time = time.clock()
for i in range(100):
A.dense = A.dense
inplace_time = time.clock() - inplace_time
assert (inplace_time < copy_time / 3)
def testChaining(self):
A = SDR([10, 10])
B = Reshape(A, [100])
C = Reshape(B, [4, 25])
D = Reshape(B, [1, 100])
A.dense.fill(1)
A.dense = A.dense
assert (len(C.sparse) == A.size)
assert (len(D.sparse) == A.size)
del B
def testSetSDR(self):
A = SDR((103, ))
B = SDR((103, ))
A.sparse = [66]
B.setSDR(A)
assert (B.dense[66] == 1)
assert (B.getSum() == 1)
B.dense[77] = 1
B.dense = B.dense
A.setSDR(B)
assert (set(A.sparse) == set((66, 77)))
# Test wrong dimensions assigned
C = SDR((2, 4, 5, 1, 1, 1, 1, 3))
C.randomize(.5)
try:
A.setSDR(C)
except RuntimeError:
pass
else:
self.fail()
def testDense(self):
A = SDR((103, ))
B = SDR((100, 100, 1))
A.dense
# Test is the same buffer every time
A.dense[0] = 1
A.dense[99] = 1
assert (A.dense[0] + A.dense[99] == 2)
# Test modify in-place
A.dense = A.dense
assert (set(A.sparse) == set((0, 99)))
# Test dense dimensions
assert (B.dense.shape == (100, 100, 1))
# No crash with dimensions
B.dense[0, 0, 0] += 1
B.dense[66, 2, 0] += 1
B.dense[99, 99, 0] += 1
B.dense = B.dense
# Test wrong dimensions assigned
C = SDR((A.size + 1))
C.randomize(.5)
test_cases = [
(SDR(1), SDR(2)),
(SDR(100), SDR((100, 1))),
(SDR((1, 100)), SDR((100, 1))),
]
for left, right in test_cases:
try:
left.dense = right.dense
except RuntimeError:
pass
else:
self.fail()
# Test assign data.
A.dense = np.zeros(A.size, dtype=np.int16)
A.dense = np.ones(A.size, dtype=np.uint64)
A.dense = np.zeros(A.size, dtype=np.int8)
A.dense = [1] * A.size
B.dense = [[[1]] * 100 for _ in range(100)]
def testGetSparsity(self):
A = SDR((103, ))
assert (A.getSparsity() == 0)
A.dense = np.ones(A.size)
assert (A.getSparsity() == 1)
def testGetSum(self):
A = SDR((103, ))
assert (A.getSum() == 0)
A.dense = np.ones(A.size)
assert (A.getSum() == 103)