def _runGetPermanenceTrial(self, float_type):
"""
Check that getPermanence() returns values for a given float_type.
These tests are sensitive to the data type. This because if you pass a
numpy array of the type matching the C++ argument then PyBind11 does not
convert the data, and the C++ code can modify the data in-place
If you pass the wrong data type, then PyBind11 does a conversion so
your C++ function only gets a converted copy of a numpy array, and any changes
are lost after returning
"""
inputs = SDR(100).randomize(.05)
active = SDR(100)
sp = SP(inputs.dimensions, active.dimensions, stimulusThreshold=1)
# Make sure that the perms start off zero.
perms_in = np.zeros(sp.getNumInputs(), dtype=float_type)
sp.setPermanence(0, perms_in)
perms = np.zeros(sp.getNumInputs(), dtype=float_type)
sp.getPermanence(0, perms)
assert (perms.sum() == 0.0)
for i in range(10):
sp.compute(inputs, True, active)
# There should be at least one perm none zero
total = np.zeros(sp.getNumInputs(), dtype=float_type)
for i in range(100):
perms = np.zeros(sp.getNumInputs(), dtype=float_type)
sp.getPermanence(i, perms)
total = total + perms
assert (total.sum() > 0.0)
def _runGetConnectedSynapses(self, float_type):
""" Check that getConnectedSynapses() returns values. """
inputs = SDR(100).randomize(.05)
active = SDR(100)
sp = SP(inputs.dimensions, active.dimensions, stimulusThreshold=1)
for i in range(10):
sp.compute(inputs, True, active)
# There should be at least one connected none zero
total = np.zeros(sp.getNumInputs(), dtype=float_type)
for i in range(100):
connected = np.zeros(sp.getNumInputs(), dtype=float_type)
sp.getPermanence(i, connected, sp.connections.connectedThreshold)
total = total + connected
assert (total.sum() > 0)
