def create_rvector(self, vals):
'''
Return rScalar object(s) with user defined value(s).
INPUTS
======
vals: list of lists of floats, compulsory
Value of the list of Vector variables
RETURNS
========
A list of Vector variables
NOTES
=====
POST:
returns a list of vector variables with value defined in vals
'''
try:
rvectors = [None] * len(vals)
for i in range(len(vals)):
rvectors[i] = rVector(vals[i])
rvectors[i]._init_roots()
return rvectors
except TypeError:
rvector = rVector(vals)
rvector._init_roots()
return rvector
def test_arccosh():
# Test rScalar
x = generate(1)
f = op.arccosh(x)
assert f.eval() == np.arccosh(x._val)
f._grad_val = 1
f.gradient(x)
assert x._grad_val == -np.arccosh(x._val) * np.tanh(x._val)
# Test constant
assert op.arccosh(c2) == np.arccosh(c2)
# Test vector
y = rVector([2, 4])
y._init_roots()
g = op.arccosh(y)
g._grad_val = 1
g.gradient(y)
assert (y._grad_val == np.array(-np.arccosh(y._val) *
np.tanh(y._val))).all()
def generate():
vars = rVector([10, 10, 15]), rVector([20, 20, 25]), rVector([30, 30, 1])
for var in vars:
var._init_roots()
return tuple(vars)
def test_get_item():
x = rVector([10, 20])
assert x[0].eval() == 10
assert x[1].eval() == 20
def generate_vec():
var = rVector([0.2, 0.3])
var._init_roots()
return var