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from gudhi.tensorflow import *
import numpy as np
import tensorflow as tf
import gudhi as gd
def test_rips_diff():
Xinit = np.array([[1.,1.],[2.,2.]], dtype=np.float32)
X = tf.Variable(initial_value=Xinit, trainable=True)
rl = RipsLayer(maximum_edge_length=2., dimension=0)
with tf.GradientTape() as tape:
dgm = rl.call(X)
loss = tf.math.reduce_sum(tf.square(.5*(dgm[:,1]-dgm[:,0])))
grads = tape.gradient(loss, [X])
assert np.abs(grads[0].numpy()-np.array([[-.5,-.5],[.5,.5]])).sum() <= 1e-6
def test_cubical_diff():
Xinit = np.array([[0.,2.,2.],[2.,2.,2.],[2.,2.,1.]], dtype=np.float32)
X = tf.Variable(initial_value=Xinit, trainable=True)
cl = CubicalLayer(dimension=0)
with tf.GradientTape() as tape:
dgm = cl.call(X)
loss = tf.math.reduce_sum(tf.square(.5*(dgm[:,1]-dgm[:,0])))
grads = tape.gradient(loss, [X])
assert np.abs(grads[0].numpy()-np.array([[0.,0.,0.],[0.,.5,0.],[0.,0.,-.5]])).sum() <= 1e-6
def test_st_diff():
st = gd.SimplexTree()
st.insert([0])
st.insert([1])
st.insert([2])
st.insert([3])
st.insert([4])
st.insert([5])
st.insert([6])
st.insert([7])
st.insert([8])
st.insert([9])
st.insert([10])
st.insert([0, 1])
st.insert([1, 2])
st.insert([2, 3])
st.insert([3, 4])
st.insert([4, 5])
st.insert([5, 6])
st.insert([6, 7])
st.insert([7, 8])
st.insert([8, 9])
st.insert([9, 10])
Finit = np.array([6.,4.,3.,4.,5.,4.,3.,2.,3.,4.,5.], dtype=np.float32)
F = tf.Variable(initial_value=Finit, trainable=True)
sl = LowerStarSimplexTreeLayer(simplextree=st, dimension=0)
with tf.GradientTape() as tape:
dgm = sl.call(F)
loss = tf.math.reduce_sum(tf.square(.5*(dgm[:,1]-dgm[:,0])))
grads = tape.gradient(loss, [F])
assert np.array_equal(np.array(grads[0].indices), np.array([2,4]))
assert np.array_equal(np.array(grads[0].values), np.array([-1,1]))
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