def test_trans_mult(self):
Ta = Tx(a)
Tb = Ty(b)
Tc = Tz(c)
Td = Tx(d)
Te = Ty(e)
Tf = Tz(f)
"""
Test
"""
Tt = Ta * Tb * Tc
TT = Td * Te * Tf
TtT = Ta * Tf
def test_trans_sum(self):
Ta = Tx(a)
Tb = Ty(b)
Tc = Tz(c)
Td = Tx(d)
Te = Ty(e)
Tf = Tz(f)
"""
Test
"""
Tt = Ta + Tb - Tc
TT = Td + Te - Tf
TtT = Ta + Tf
def test_get_params(self):
Ta = Tx(a)
Tb = Ty(b)
Tc = Tz(c)
Tt = Ta * Tb * Tc
"""
Test
"""
Tt.get_params()
def test_inv(self):
Ta = Tx(a)
Tb = Ty(b)
Tc = Tz(c)
Tt = Ta * Tb * Tc
"""
Test
"""
Tt_inv = Tt.Inv()
print(Tt_inv)
def test_vector_mult(self):
Ta = Tx(a)
Tb = Ty(b)
Tc = Tz(c)
Tt = Ta * Tb * Tc
"""
Test
"""
# Position vector in c reference frame
r = np.array([1, 1, 1])
# Rotated vector wrt a reference frame
r_tr = Tt * r
# Sum of rotated vector (still a symbolic transform instance) and other vector
r_rtr = r_tr + r
def test_latex(self):
Ta = Tx(a)
Tb = Ty(b)
Tc = Tz(c)
Tt = Ta * Tb * Tc
# Position vector in c reference frame
r = np.array([1, 1, 1])
# Rotated vector wrt a reference frame
r_tr = Tt * r
"""
Test
"""
# Rotated vector: LaTeX output
r_tr.to_latex()
def test_lambd(self):
Ta = Tx(a)
Tb = Ty(b)
Tc = Tz(c)
Tt = Ta * Tb * Tc
# Position vector in c reference frame
r = np.array([1, 1, 1])
# Rotated vector wrt a reference frame
r_tr = Tt * r
"""
Test
"""
# Get lambda function of rotated vector
f = r_tr.get_lambda()
# Rotated vector wrt a reference frame, by angles alpha, beta and gamma
r_tr.suppress = False
r_tr_num = r_tr(0.2, 0.3, np.pi / 2)
import numpy as np
import sympy as sp
from transforms import Tx, Ty, Tz
# Variables
a = sp.Symbol("alpha")
b = sp.Symbol("beta")
c = sp.Symbol("gamma")
# Transforms
Ta = Tx(a)
Tb = Ty(b)
Tc = Tz(c)
Tt = Ta * Tb * Tc
TT = Ta + Tb + Tc
# Position vector in c reference frame
r = np.array([1, 1, 1])
# Rotated vector wrt a reference frame
r_tr = Tt * r
# Lambdify
r_tr_num = r_tr(0.2, 0.3, np.pi / 2)
# To LaTeX
r_tr.to_latex()
def test_init_n(self):
Td = Tx(d)
Te = Ty(e)
Tf = Tz(f)
def test_init_s(self):
Ta = Tx(a)
Tb = Ty(b)
Tc = Tz(c)