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Fixed the fresh hell that is the old tests
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Signed-off-by: inakleinbottle <admin@inakleinbottle.com>
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inakleinbottle committed May 24, 2023
1 parent 0f0de9c commit 41302d9
Showing 1 changed file with 98 additions and 97 deletions.
195 changes: 98 additions & 97 deletions tests/test_package.py
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Original file line number Diff line number Diff line change
Expand Up @@ -7,70 +7,67 @@
from . import esigtests as rado
from . import recombinetests as recombine

from numpy.testing import assert_array_equal

from numpy.testing import assert_array_equal, assert_array_almost_equal

# Tree-like equivalence of paths and equivalence class signature invariance. Non-generic paths used since pruning is generically unnecessary.

a=[[0.0,0],[1,0],[1,1],[1,0],[2,0],[3,1],[2,2],[1,1],[2,2],[1,3],[2,2],[3,3],[2,2],[3,1],[4,1],[3,1],[2,0],[2,-1],[2,0],[1,0],[1,-1],[1,0],[0,0]]

b=[[0.0,0], [1,3], [0,0], [1,5], [2,5], [1,5], [0,6], [1,5], [0,0]]
a = [[0.0, 0], [1, 0], [1, 1], [1, 0], [2, 0], [3, 1], [2, 2], [1, 1], [2, 2], [1, 3], [2, 2], [3, 3], [2, 2], [3, 1],
[4, 1], [3, 1], [2, 0], [2, -1], [2, 0], [1, 0], [1, -1], [1, 0], [0, 0]]

c=[[0.0,0], [1,1], [3,1], [2,1], [1,1], [2,0]]
b = [[0.0, 0], [1, 3], [0, 0], [1, 5], [2, 5], [1, 5], [0, 6], [1, 5], [0, 0]]

aa=ax.fullprune(a)
bb=ax.fullprune(b)
cc=ax.fullprune(c)
a=np.array(a)
b=np.array(b)
c=np.array(c)
aa=np.array(aa)
bb=np.array(bb)
cc=np.array(cc)
sigdiffa= ts.stream2sig(a,3)-ts.stream2sig(aa,3)
sigdiffb = ts.stream2sig(b,3)-ts.stream2sig(bb,3)
sigdiffc = ts.stream2sig(c,3)-ts.stream2sig(cc,3)
c = [[0.0, 0], [1, 1], [3, 1], [2, 1], [1, 1], [2, 0]]

aa = ax.fullprune(a)
bb = ax.fullprune(b)
cc = ax.fullprune(c)
a = np.array(a)
b = np.array(b)
c = np.array(c)
aa = np.array(aa)
bb = np.array(bb)
cc = np.array(cc)
sigdiffa = ts.stream2sig(a, 3) - ts.stream2sig(aa, 3)
sigdiffb = ts.stream2sig(b, 3) - ts.stream2sig(bb, 3)
sigdiffc = ts.stream2sig(c, 3) - ts.stream2sig(cc, 3)

y=ax.random_path(1,range(-10,11),3)
y = ax.random_path(1, range(-10, 11), 3)

x=[[0.0,0,0]]
x = [[0.0, 0, 0]]
xx = x

xx.append(y[0])
x=np.array(xx)

path1=ax.random_path(5,range(-10,11),3)
path2=ax.random_path(5,range(-10,11),3)
#print(path1)
#print(ax.concatenate(path1,path2))
x = np.array(xx)

sig1=ax.tensoraslevels(ts.stream2sig(np.array(path1),2),3,2)
#print(sig1)
sig2=ax.tensoraslevels(ts.stream2sig(np.array(path2),2),3,2)
#print(sig2)
sig_concat=ax.tensoraslevels(ts.stream2sig(ax.concatenate(path1,path2),2),3,2)
chen=ax.chen(sig1,sig2)
#print(chen)
#print(sig_concat)
path1 = ax.random_path(5, range(-10, 11), 3)
path2 = ax.random_path(5, range(-10, 11), 3)
# print(path1)
# print(ax.concatenate(path1,path2))

sig1 = ax.tensoraslevels(ts.stream2sig(np.array(path1), 2), 3, 2)
# print(sig1)
sig2 = ax.tensoraslevels(ts.stream2sig(np.array(path2), 2), 3, 2)
# print(sig2)
sig_concat = ax.tensoraslevels(ts.stream2sig(ax.concatenate(path1, path2), 2), 3, 2)
chen = ax.chen(sig1, sig2)
# print(chen)
# print(sig_concat)

logsig=ax.exponentiateTensor( ax.tensoraslevels( ax.Logsigastensor( np.array(path1),3),3,3))

logsig = ax.exponentiateTensor(ax.tensoraslevels(ax.Logsigastensor(np.array(path1), 3), 3, 3))


#c=ax.Logsigastensor(a,3)
#b=ts.stream2sig(a,3)
#d=ax.exponentiateTensor(ax.tensoraslevels(c,2,3))
#print(b)
#print(d)
#b=np.array(b)
#sigdiff= ts.stream2sig(a,2)-ts.stream2sig(b,2)
#print(sigdiff)

#if all(sigdiff)==0:
# print("ok")
# c=ax.Logsigastensor(a,3)
# b=ts.stream2sig(a,3)
# d=ax.exponentiateTensor(ax.tensoraslevels(c,2,3))
# print(b)
# print(d)
# b=np.array(b)
# sigdiff= ts.stream2sig(a,2)-ts.stream2sig(b,2)
# print(sigdiff)

# if all(sigdiff)==0:
# print("ok")


# Test Chen's theorem using tensor multiplication
Expand All @@ -79,81 +76,85 @@
# Exponentiate logsig as a tensor and see it matches esig


#a=[1,2]
#sig1=ax.linsig(a,3)
#b=[[0.0,0], [1,2]]
#b=np.array(b)
#sig2=ts.stream2sig(np.array(b),3)
#print(sig1-sig2)

# a=[1,2]
# sig1=ax.linsig(a,3)
# b=[[0.0,0], [1,2]]
# b=np.array(b)
# sig2=ts.stream2sig(np.array(b),3)
# print(sig1-sig2)

#print(ax.fullunbracket(string))
#a=ax.Lietotensor(string)
#print(a)

# print(ax.fullunbracket(string))
# a=ax.Lietotensor(string)
# print(a)


#print(expand)
# print(expand)

#L=ax.Lietotensor(string)
#print(L)
#print(ax.Lietotensor('1'))
# L=ax.Lietotensor(string)
# print(L)
# print(ax.Lietotensor('1'))

#print(ax.changeofbasis(2,3))
# print(ax.changeofbasis(2,3))


#print(ax.Lietotensor(string))
#tensor_product=ax.fullunbracket(string)
#copy= tensor_product[1:-1]
#print(copy)
# print(ax.Lietotensor(string))
# tensor_product=ax.fullunbracket(string)
# copy= tensor_product[1:-1]
# print(copy)

#term=ax.spotfirstterm(copy)
#print(type(term))
#print(term)
#d=ax.distribute(term)
#print(d)
#print(type(d))
# term=ax.spotfirstterm(copy)
# print(type(term))
# print(term)
# d=ax.distribute(term)
# print(d)
# print(type(d))
##print(copy.replace(term,d))
#copy=copy.replace(term,ax.distribute(term))
#print(copy)
#term=ax.spotfirstterm(copy)
#print(term)
#print(type(term))
#a=ax.fullunbracket(string)

#print(a)
#print(len(a))
#b=a[1:-1]
#c=ax.spotterm(b)[1][1]
#print(c)

#term='1x2x(2x1-1x2)x3'
#print(ax.distribute(term))
# copy=copy.replace(term,ax.distribute(term))
# print(copy)
# term=ax.spotfirstterm(copy)
# print(term)
# print(type(term))
# a=ax.fullunbracket(string)

# print(a)
# print(len(a))
# b=a[1:-1]
# c=ax.spotterm(b)[1][1]
# print(c)

# term='1x2x(2x1-1x2)x3'
# print(ax.distribute(term))

class TestESIG(TestCase):

def test_equivalence(self):
self.assertEqual(all(sigdiffa),0)
self.assertEqual(all(sigdiffb),0)
self.assertEqual(all(sigdiffc),0)
self.assertEqual(all(sigdiffa), 0)
self.assertEqual(all(sigdiffb), 0)
self.assertEqual(all(sigdiffc), 0)

def test_linsig(self):
self.assertEqual(all(ax.linsig(y[0],4) - ts.stream2sig(x,4)),0)
# self.assertEqual(all(ax.linsig(y[0],4) - ts.stream2sig(x,4)),0)
assert_array_almost_equal(ax.linsig(y[0], 4), ts.stream2sig(x, 4))

def test_logsig(self):
self.assertEqual(all(ts.stream2sig(np.array(path1),3)[1:]- logsig),0)
# self.assertEqual(all(ts.stream2sig(np.array(path1),3)[1:]- logsig),0)
assert_array_almost_equal(ts.stream2sig(np.array(path1), 3)[1:], logsig)

def test_chen(self):
self.assertEqual(all(np.concatenate((np.array(chen)-np.array(sig_concat)).flatten())),0)
# self.assertEqual(all(np.concatenate((np.array(chen)-np.array(sig_concat)).flatten())),0)
for chen_sig, concat_sig in zip(chen, sig_concat):
assert_array_equal(chen_sig, concat_sig)

def test_compare_reverse(self):
self.assertEqual(rado.compare_reverse_test(100,[-1,0,1],2,4),1)
self.assertEqual(rado.compare_reverse_test(100, [-1, 0, 1], 2, 4), 1)

def test_shuffle_test(self):
self.assertEqual(rado.shuffle_test(100,[-1,0,1],3,3),1)
self.assertEqual(rado.shuffle_test(100, [-1, 0, 1], 3, 3), 1)

def test_reparametrizing(self):
self.assertEqual(rado.reparametrizing_test(10,[-1,0,1],2,3,3),1)
self.assertEqual(rado.reparametrizing_test(10, [-1, 0, 1], 2, 3, 3), 1)


class TestRecombine(TestCase):

Expand All @@ -166,10 +167,10 @@ class TestEsigFunctions(TestCase):

def test_sig_from_transpose_data(self):
# https://github.com/datasig-ac-uk/esig/issues/124
two_dim_stream1 = np.array([[0.11212,1.1212], [0.11, 0.22]])
two_dim_stream1 = np.array([[0.11212, 1.1212], [0.11, 0.22]])
sig1 = esig.stream2sig(two_dim_stream1, 2)

two_dim_stream2 = np.transpose(np.array([[0.11212,0.11], [1.1212,0.22]]))
two_dim_stream2 = np.transpose(np.array([[0.11212, 0.11], [1.1212, 0.22]]))
sig2 = esig.stream2sig(two_dim_stream2, 2)

assert_array_equal(sig1, sig2)

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