def test_double(self):
from dcgpy import expression_double as expression
from dcgpy import kernel_set_double as kernel_set
# Construction
ex = expression(inputs=1,
outputs=1,
rows=1,
cols=6,
levels_back=6,
arity=2,
kernels=kernel_set(["sum", "mul", "div", "diff"])(),
n_eph=0,
seed=33)
ex = expression(inputs=1,
outputs=1,
rows=1,
cols=6,
levels_back=6,
arity=2,
kernels=kernel_set(["sum", "mul", "div", "diff"])(),
n_eph=2,
seed=33)
# Ephemeral value attributes tests
self.assertEqual(ex.eph_val, [1, 2])
self.assertEqual(ex.eph_symb, ["c1", "c2"])
ex.eph_val = [-0.2, 0.3]
self.assertEqual(ex.eph_val, [-0.2, 0.3])
ex.eph_symb = ["d1", "d2"]
self.assertEqual(ex.eph_symb, ["d1", "d2"])
def test_serialization_gdual_double(self):
import cloudpickle as cpk
from dcgpy import kernel_set_gdual_double as kernel_set
from dcgpy import kernel_gdual_double as kernel
from pyaudi import gdual_double as gdual
# cpp kernels
cpp_kv = kernel_set([
"sum", "diff", "mul", "div", "tanh", "sig", "cos", "sin", "log",
"exp", "gaussian", "sqrt", "ReLu", "ELU", "ISRU"
])()
x1 = gdual(1.2, "x1", 2)
x2 = gdual(-1.2, "x2", 2)
x3 = gdual(3.2, "x3", 2)
for cpp_k in cpp_kv:
cpp_k2 = cpk.loads(cpk.dumps(cpp_k))
self.assertEqual(cpp_k([x1, x2, x3]), cpp_k2([x1, x2, x3]))
self.assertEqual(cpp_k(["a", "b", "c"]), cpp_k2(["a", "b", "c"]))
# pythonic kernels
my_py_kernel = kernel(my_py_fun, my_py_fun_print, "my_py_fun")
my_py_kernel2 = cpk.loads(cpk.dumps(my_py_kernel))
self.assertEqual(my_py_kernel([x1, x2, x3]),
my_py_kernel2([x1, x2, x3]))
self.assertEqual(my_py_kernel(["a", "b", "c"]),
my_py_kernel2(["a", "b", "c"]))
def test_gdual_vdouble(self):
from dcgpy import expression_gdual_vdouble as expression
from dcgpy import kernel_set_gdual_vdouble as kernel_set
from pyaudi import gdual_vdouble as gdual
ex = expression(1,1,1,6,6,2,kernel_set(["sum","mul", "div", "diff"])(), 32)
self.assertEqual(ex([gdual([1, 2, -1, 2], "x", 2)]), [gdual([1, 1, 1, 1])])
def test_gdual_vdouble(self):
from dcgpy import expression_gdual_vdouble as expression
from dcgpy import kernel_set_gdual_vdouble as kernel_set
from pyaudi import gdual_vdouble as gdual
ex = expression(1, 1, 1, 6, 6, 2,
kernel_set(["sum", "mul", "div", "diff"])(), 32)
self.assertEqual(ex([gdual([1, 2, -1, 2], "x", 2)]),
[gdual([1, 1, 1, 1])])
def test_double(self):
from dcgpy import expression_double as expression
from dcgpy import kernel_set_double as kernel_set
ex = expression(1,1,1,6,6,2,kernel_set(["sum","mul", "div", "diff"])(), 32)
self.assertEqual(ex([1.]), [1])
self.assertEqual(ex([2.]), [1])
self.assertEqual(ex([-1.]), [1])
self.assertEqual(ex([-2.]), [1])
def test_double(self):
from dcgpy import expression_double as expression
from dcgpy import kernel_set_double as kernel_set
ex = expression(1, 1, 1, 6, 6, 2,
kernel_set(["sum", "mul", "div", "diff"])(), 32)
self.assertEqual(ex([1.]), [1])
self.assertEqual(ex([2.]), [1])
self.assertEqual(ex([-1.]), [1])
self.assertEqual(ex([-2.]), [1])
def test_loss_double(self):
from dcgpy import expression_double as expression
from dcgpy import kernel_set_double as kernel_set
import numpy as np
ex = expression(1, 1, 1, 6, 6, 2,
kernel_set(["sum", "mul", "div", "diff"])(), 32)
x = 1.
loss_list = ex.loss([[x]], [ex([x])], "MSE")
loss_array = ex.loss(np.array([[x]]), np.array([ex([x])]), "MSE")
self.assertEqual(loss_list, loss_array)
def test_gdual_double(self):
from dcgpy import expression_gdual_double as expression
from dcgpy import kernel_set_gdual_double as kernel_set
from pyaudi import gdual_double as gdual
ex = expression(1, 1, 1, 6, 6, 2,
kernel_set(["sum", "mul", "div", "diff"])(), 0, 20)
self.assertEqual(ex([gdual(1, "x", 2)]), [gdual(0.)])
self.assertEqual(ex([gdual(2, "x", 2)]), [gdual(0.)])
self.assertEqual(ex([gdual(-1, "x", 2)]), [gdual(0.)])
self.assertEqual(ex([gdual(-2, "x", 2)]), [gdual(0.)])
def test_double(self):
from dcgpy import expression_double as expression
from dcgpy import kernel_set_double as kernel_set
# Construction
ex = expression(1, 1, 1, 6, 6, 2,
kernel_set(["sum", "mul", "div", "diff"])(), 0, 33)
self.assertEqual(ex([1.]), [0.5])
self.assertEqual(ex([2.]), [1.])
self.assertEqual(ex([-1.]), [-0.5])
self.assertEqual(ex([-2.]), [-1.])
ex = expression(1, 1, 1, 6, 6, 2,
kernel_set(["sum", "mul", "div", "diff"])(), 2, 33)
# Ephemeral value attributes tests
self.assertEqual(ex.eph_val, [1, 2])
self.assertEqual(ex.eph_symb, ["c1", "c2"])
ex.eph_val = [-0.2, 0.3]
self.assertEqual(ex.eph_val, [-0.2, 0.3])
ex.eph_symb = ["d1", "d2"]
self.assertEqual(ex.eph_symb, ["d1", "d2"])
def test_loss_gdual_vdouble(self):
from dcgpy import expression_gdual_vdouble as expression
from dcgpy import kernel_set_gdual_vdouble as kernel_set
from pyaudi import gdual_vdouble as gdual
import numpy as np
ex = expression(1, 1, 1, 6, 6, 2,
kernel_set(["sum", "mul", "div", "diff"])(), 0, 33)
x = gdual([1., 2.], "x", 3)
loss_list = ex.loss([[x]], [ex([x])], "MSE")
loss_array = ex.loss(np.array([[x]]), np.array([ex([x])]), "MSE")
self.assertEqual(loss_list, loss_array)
def test_double(self):
from dcgpy import kernel_set_double as kernel_set
from dcgpy import kernel_double as kernel
a = kernel_set(["diff"])
a.push_back("mul")
my_kernel = kernel(self.my_sum, self.print_my_sum, "my_sum_kernel")
a.push_back(my_kernel)
self.assertEqual(a.__repr__(), "[diff, mul, my_sum_kernel]")
x = 1
y = 2
z = 3
self.assertEqual(a[0]([x,y,z]), x-y-z)
self.assertEqual(a[1]([x,y,z]), x*y*z)
self.assertEqual(a[2]([x,y,z]), x+y+z)
def test_double(self):
from dcgpy import kernel_set_double as kernel_set
from dcgpy import kernel_double as kernel
a = kernel_set(["diff"])
a.push_back("mul")
my_kernel = kernel(self.my_sum, self.print_my_sum, "my_sum_kernel")
a.push_back(my_kernel)
self.assertEqual(a.__repr__(), "[diff, mul, my_sum_kernel]")
x = 1
y = 2
z = 3
self.assertEqual(a[0]([x, y, z]), x - y - z)
self.assertEqual(a[1]([x, y, z]), x * y * z)
self.assertEqual(a[2]([x, y, z]), x + y + z)
def test_gdual_vdouble(self):
from dcgpy import expression_gdual_vdouble as expression
from dcgpy import kernel_set_gdual_vdouble as kernel_set
from pyaudi import gdual_vdouble as gdual
expression(inputs=1,
outputs=1,
rows=1,
cols=6,
levels_back=6,
arity=2,
kernels=kernel_set(["sum", "mul", "div", "diff"])(),
n_eph=0,
seed=20)
def test_gdual_vdouble(self):
from dcgpy import kernel_set_gdual_vdouble as kernel_set
from dcgpy import kernel_gdual_vdouble as kernel
from pyaudi import gdual_vdouble as gdual
a = kernel_set(["diff"])
a.push_back("mul")
my_kernel = kernel(self.my_sum, self.print_my_sum, "my_sum_kernel")
a.push_back(my_kernel)
self.assertEqual(a.__repr__(), "[diff, mul, my_sum_kernel]")
x = gdual([1,-1], "x", 2)
y = gdual([2,-2], "y", 2)
z = gdual([-2,1], "z", 2)
self.assertEqual(a[0]([x,y,z]), x-y-z)
self.assertEqual(a[1]([x,y,z]), x*y*z)
self.assertEqual(a[2]([x,y,z]), x+y+z)
def test_gdual_double(self):
from dcgpy import kernel_set_gdual_double as kernel_set
from dcgpy import kernel_gdual_double as kernel
from pyaudi import gdual_double as gdual
a = kernel_set(["diff"])
a.push_back("mul")
my_kernel = kernel(my_py_fun, my_py_fun_print, "my_sum_kernel")
a.push_back(my_kernel)
self.assertEqual(a.__repr__(), "[diff, mul, my_sum_kernel]")
x = gdual(1, "x", 2)
y = gdual(2, "y", 2)
z = gdual(3, "z", 2)
self.assertEqual(a[0]([x, y, z]), x - y - z)
self.assertEqual(a[1]([x, y, z]), x * y * z)
self.assertEqual(a[2]([x, y, z]), x + y + z)
def test_gdual_vdouble(self):
from dcgpy import kernel_set_gdual_vdouble as kernel_set
from dcgpy import kernel_gdual_vdouble as kernel
from pyaudi import gdual_vdouble as gdual
a = kernel_set(["diff"])
a.push_back("mul")
my_kernel = kernel(self.my_sum, self.print_my_sum, "my_sum_kernel")
a.push_back(my_kernel)
self.assertEqual(a.__repr__(), "[diff, mul, my_sum_kernel]")
x = gdual([1, -1], "x", 2)
y = gdual([2, -2], "y", 2)
z = gdual([-2, 1], "z", 2)
self.assertEqual(a[0]([x, y, z]), x - y - z)
self.assertEqual(a[1]([x, y, z]), x * y * z)
self.assertEqual(a[2]([x, y, z]), x + y + z)
def test_loss_double(self):
from dcgpy import expression_double as expression
from dcgpy import kernel_set_double as kernel_set
import numpy as np
ex = expression(inputs=1,
outputs=1,
rows=1,
cols=6,
levels_back=6,
arity=2,
kernels=kernel_set(["sum", "mul", "div", "diff"])(),
n_eph=0,
seed=33)
x = 1.
loss_list = ex.loss([[x]], [ex([x])], "MSE")
loss_array = ex.loss(np.array([[x]]), np.array([ex([x])]), "MSE")
self.assertEqual(loss_list, loss_array)
from dcgpy import expression_gdual_double as expression
from dcgpy import kernel_set_gdual_double as kernel_set
from pyaudi import gdual_double as gdual
# 1- Instantiate a random expression using the 4 basic arithmetic operations
ks = kernel_set(["sum", "diff", "div", "mul"])
ex = expression(inputs = 1,
outputs = 1,
rows = 1,
cols = 6,
levels_back = 6,
arity = 2,
kernels = ks(),
n_eph = 0,
seed = 4232123212)
# 2 - Define the symbol set to be used in visualizing the expression
# (in our case, 1 input variable named "x") and visualize the expressionin_sym = ["x"]
print("Expression:", ex(in_sym)[0])
# 3 - Print the simplified expression
print("Simplified expression:", ex.simplify(in_sym))
# 4 - Visualize the dCGP graph
ex.visualize(in_sym)
# 5 - Define a gdual number of value 1.2 and truncation order 2
x = gdual(1.2, "x", 2)
# 6 - Compute the output of the expression and its second derivative in x = 1.2 and print
from dcgpy import expression_gdual_double as expression
from dcgpy import kernel_set_gdual_double as kernel_set
from pyaudi import gdual_double as gdual
# 1- Instantiate a random expression using the 4 basic arithmetic operations
ks = kernel_set(["sum", "diff", "div", "mul"])
ex = expression(1, 1, 1, 6, 6, 2, ks(), 4232123212)
# 2 - Define the symbol set (in our case, 1 input variable named "x") and print the expression
in_sym = ["x"]
print("Expression:", ex(in_sym)[0])
# 3 - Print the simplified expression
print("Simplified expression:", ex.simplify(in_sym))
# 4 - Visualize the dCGP graph
ex.visualize(in_sym)
# 5 - Define a gdual number of value 1.2 and truncation order 2
x = gdual(1.2, "x", 2)
# 6 - Compute the output of the expression and its second derivative in x = 1.2 and print
print("Expression in x=1.2:", ex([x])[0])
print("Second derivative:", ex([x])[0].get_derivative([2]))
# 5 - Mutate the expression with 2 random mutations of active genes and print
ex.mutate_active(2)
print("Mutated expression:", ex(in_sym)[0])
