def testSetFieldStats(self):
"""Test setting the min and max using setFieldStats"""
def _dumpParams(enc):
return (enc.n, enc.w, enc.minval, enc.maxval, enc.resolution,
enc.windowSize, enc._learningEnabled, enc.recordNum,
enc.radius, enc.rangeInternal, enc.padding, enc.nInternal)
sfs = AdaptiveScalarEncoder(name='scalar',
n=14,
w=5,
minval=1,
maxval=10,
periodic=False)
reg = AdaptiveScalarEncoder(name='scalar',
n=14,
w=5,
minval=1,
maxval=100,
periodic=False)
self.assertTrue(_dumpParams(sfs) != _dumpParams(reg), "Params should not be equal, "\
"since the two encoders were instantiated with different values.")
# set the min and the max using sFS to 1,100 respectively.
sfs.setFieldStats('this', {"this": {"min": 1, "max": 100}})
#Now the parameters for both should be the same
self.assertEqual(_dumpParams(sfs), _dumpParams(reg), "Params should now be equal, "\
"but they are not. sFS should be equivalent to initialization.")
def testSetFieldStats(self):
"""Test setting the min and max using setFieldStats"""
def _dumpParams(enc):
return (enc.n, enc.w, enc.minval, enc.maxval, enc.resolution,
enc._learningEnabled, enc.recordNum,
enc.radius, enc.rangeInternal, enc.padding, enc.nInternal)
sfs = AdaptiveScalarEncoder(name='scalar', n=14, w=5, minval=1, maxval=10,
periodic=False, forced=True)
reg = AdaptiveScalarEncoder(name='scalar', n=14, w=5, minval=1, maxval=100,
periodic=False, forced=True)
self.assertTrue(_dumpParams(sfs) != _dumpParams(reg), "Params should not be equal, "\
"since the two encoders were instantiated with different values.")
# set the min and the max using sFS to 1,100 respectively.
sfs.setFieldStats('this',{"this":{"min":1,"max":100}})
#Now the parameters for both should be the same
self.assertEqual(_dumpParams(sfs), _dumpParams(reg), "Params should now be equal, "\
"but they are not. sFS should be equivalent to initialization.")
