def test_generate_predictor_dt_func():
symbs = [Sdts[0], Sdts[1], Sdts[2], Sdts[0] + Sdts[1],
Sdts[0]/2 + Sdts[1]/2]
t = sympy.symbols('t')
fake_ts = utils.dts2ts(t, Sdts[::-1])
for symb in symbs:
print fake_ts
yield utils.assert_sym_eq, symb, generate_p_dt_func(symb)(fake_ts)
def test_generate_predictor_dt_func():
symbs = [
Sdts[0], Sdts[1], Sdts[2], Sdts[0] + Sdts[1], Sdts[0] / 2 + Sdts[1] / 2
]
t = sympy.symbols('t')
fake_ts = utils.dts2ts(t, Sdts[::-1])
for symb in symbs:
print fake_ts
yield utils.assert_sym_eq, symb, generate_p_dt_func(symb)(fake_ts)
def test_symbolic_compare_step_time_residual():
# Define the symbols we need
St = sympy.symbols('t')
Sdts = sympy.symbols('Delta0:9')
Sys = sympy.symbols('y0:9')
Sdys = sympy.symbols('dy0:9')
# Generate the stuff needed to run the residual
def fake_eqn_residual(ts, ys, dy):
return Sdys[0] - dy
fake_ts = utils.dts2ts(St, Sdts[::-1])
fake_ys = Sys[::-1]
# Check bdf2
step_result_bdf2 = ibdf2_step(Sdts[0], Sys[1], Sdys[0], Sdts[1], Sys[2])
res_result_bdf2 = bdf2_residual(fake_eqn_residual, fake_ts, fake_ys)
res_bdf2_step = sympy.solve(res_result_bdf2, Sys[0])
assert len(res_bdf2_step) == 1
utils.assert_sym_eq(res_bdf2_step[0], step_result_bdf2)
def test_symbolic_compare_step_time_residual():
# Define the symbols we need
St = sympy.symbols('t')
Sdts = sympy.symbols('Delta0:9')
Sys = sympy.symbols('y0:9')
Sdys = sympy.symbols('dy0:9')
# Generate the stuff needed to run the residual
def fake_eqn_residual(ts, ys, dy):
return Sdys[0] - dy
fake_ts = utils.dts2ts(St, Sdts[::-1])
fake_ys = Sys[::-1]
# Check bdf2
step_result_bdf2 = ibdf2_step(Sdts[0], Sys[1], Sdys[0], Sdts[1], Sys[2])
res_result_bdf2 = bdf2_residual(fake_eqn_residual, fake_ts, fake_ys)
res_bdf2_step = sympy.solve(res_result_bdf2, Sys[0])
assert len(res_bdf2_step) == 1
utils.assert_sym_eq(res_bdf2_step[0], step_result_bdf2)
