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 testReshape(self):
# Convert SDR dimensions from (4 x 4) to (8 x 2)
A = SDR([4, 4])
A.coordinates = ([1, 1, 2], [0, 1, 2])
B = A.reshape([8, 2])
assert ((np.array(B.coordinates) == ([2, 2, 5], [0, 1, 0])).all())
assert (A is B)
def testCoordinates(self):
A = SDR((103, ))
B = SDR((100, 100, 1))
C = SDR((2, 4, 5, 1, 1, 1, 1, 3))
A.coordinates
B.coordinates = [[0, 55, 99], [0, 11, 99], [0, 0, 0]]
assert (B.dense[0, 0, 0] == 1)
assert (B.dense[55, 11, 0] == 1)
assert (B.dense[99, 99, 0] == 1)
C.randomize(.5)
assert (len(C.coordinates) == len(C.dimensions))
# Test wrong dimensions assigned
C = SDR((2, 4, 5, 1, 1, 1, 1, 3))
C.randomize(.5)
try:
A.coordinates = C.coordinates
except RuntimeError:
pass
else:
self.fail()
