def testSig(self):
#test that sigjacobian and sigbackprop compatible with sig
numpy.random.seed(291)
d = 3
m = 5
pathLength = 10
path = numpy.random.uniform(size=(pathLength,d))
path = numpy.cumsum(2 * (path - 0.5),0)#makes it more random-walk-ish, less like a scribble
increment = 0.01 * numpy.random.uniform(size=(pathLength,d))
base_sig = iisignature.sig(path,m)
target = fdDeriv(lambda x:iisignature.sig(x,m),path,increment,2, nosum=True)
gradient = iisignature.sigjacobian(path,m)
calculated = numpy.tensordot(increment,gradient)
diffs = numpy.max(numpy.abs(calculated - target))
niceOnes = numpy.abs(calculated) > 1.e-4
niceOnes2 = numpy.abs(calculated) < numpy.abs(base_sig)
diffs1 = numpy.max(numpy.abs((calculated[niceOnes2] - target[niceOnes2]) / base_sig[niceOnes2]))
diffs2 = numpy.max(numpy.abs(calculated[1 - niceOnes2] - target[1 - niceOnes2]))
ratioDiffs = numpy.max(numpy.abs(calculated[niceOnes] / target[niceOnes] - 1))
#numpy.set_printoptions(suppress=True,linewidth=os.popen('stty size',
#'r').read().split()[1] #LINUX
#numpy.set_printoptions(suppress=True,linewidth=150)
#print ("")
#print (path)
#print
#(numpy.vstack([range(len(base_sig)),base_sig,calculated,target,(calculated-target)/base_sig,calculated/target-1]).transpose())
#print (diffs, ratioDiffs, diffs1, diffs2)
#print(numpy.argmax(numpy.abs(calculated[niceOnes]/target[niceOnes]-1)),numpy.argmax(numpy.abs((calculated-target)/base_sig)))
self.assertLess(diffs,0.00001)
self.assertLess(ratioDiffs,0.01)
self.assertLess(diffs1,0.001)
self.assertLess(diffs2,0.00001)
#compatibility between sigbackprop and sigjacobian is strong
dFdSig = numpy.random.uniform(size=(iisignature.siglength(d,m),))
backProp = iisignature.sigbackprop(dFdSig,path,m)
manualCalcBackProp = numpy.dot(gradient,dFdSig)
backDiffs = numpy.max(numpy.abs(backProp - manualCalcBackProp))
if 0: # to investigate the compile logic problem I used this and
# (d,m,pathLength)=(1,2,2)
print("")
print(dFdSig)
print(path)
print(backProp)
print(manualCalcBackProp)
self.assertLess(backDiffs,0.000001)
def testSig(self):
#test that sigjacobian and sigbackprop compatible with sig
numpy.random.seed(291)
d = 3
m = 5
pathLength = 10
path = numpy.random.uniform(size=(pathLength,d))
path = numpy.cumsum(2 * (path - 0.5),0)#makes it more random-walk-ish, less like a scribble
increment = 0.01 * numpy.random.uniform(size=(pathLength,d))
base_sig = iisignature.sig(path,m)
target = fdDeriv(lambda x:iisignature.sig(x,m),path,increment,2, nosum=True)
gradient = iisignature.sigjacobian(path,m)
calculated = numpy.tensordot(increment,gradient)
diffs = numpy.max(numpy.abs(calculated - target))
niceOnes = numpy.abs(calculated) > 1.e-4
niceOnes2 = numpy.abs(calculated) < numpy.abs(base_sig)
diffs1 = numpy.max(numpy.abs((calculated[niceOnes2] - target[niceOnes2]) / base_sig[niceOnes2]))
diffs2 = numpy.max(numpy.abs(calculated[1 - niceOnes2] - target[1 - niceOnes2]))
ratioDiffs = numpy.max(numpy.abs(calculated[niceOnes] / target[niceOnes] - 1))
#numpy.set_printoptions(suppress=True,linewidth=os.popen('stty size',
#'r').read().split()[1] #LINUX
#numpy.set_printoptions(suppress=True,linewidth=150)
#print ("")
#print (path)
#print
#(numpy.vstack([range(len(base_sig)),base_sig,calculated,target,(calculated-target)/base_sig,calculated/target-1]).transpose())
#print (diffs, ratioDiffs, diffs1, diffs2)
#print(numpy.argmax(numpy.abs(calculated[niceOnes]/target[niceOnes]-1)),numpy.argmax(numpy.abs((calculated-target)/base_sig)))
self.assertLess(diffs,0.00001)
self.assertLess(ratioDiffs,0.01)
self.assertLess(diffs1,0.001)
self.assertLess(diffs2,0.00001)
#compatibility between sigbackprop and sigjacobian is strong
dFdSig = numpy.random.uniform(size=(iisignature.siglength(d,m),))
backProp = iisignature.sigbackprop(dFdSig,path,m)
manualCalcBackProp = numpy.dot(gradient,dFdSig)
backDiffs = numpy.max(numpy.abs(backProp - manualCalcBackProp))
if 0: # to investigate the compile logic problem I used this and
# (d,m,pathLength)=(1,2,2)
print("")
print(dFdSig)
print(path)
print(backProp)
print(manualCalcBackProp)
self.assertLess(backDiffs,0.000001)