def test_Ma_1():
"""Check inversion for values near Ma = 1."""
dMa = 0.0001
Ma_fw = np.array([-dMa, 0., dMa]) + 1.
for v in var_test_sup:
Y_fw = cf.from_Ma( v, Ma_fw, ga)
Ma_bk = cf.to_Ma( v, Y_fw, ga)
if v in ['mcpTo_APo','A_Acrit']:
Ma_bk[-1] = cf.to_Ma( v, Y_fw[-1], ga, True)
err = Ma_fw-Ma_bk
print(v, err)
assert np.all(np.abs(err[~np.isnan(Ma_bk)])<1e-5)
def test_inverse_sub():
"""Compare Ma lookup values to CUED Data Book, subsonic."""
for v in var_test_sub:
for _ in range(Nrep):
X = cf.to_Ma(v, dat_sub[v], ga)
err_sub = np.abs(X - dat_sub['Ma'])
imax = np.argmax(err_sub)
assert err_sub[imax] <= 0.01, \
"{0}={1} => Ma={2} with error={3}".format(
v, dat_sub[v][imax], X[imax], err_sub[imax])
def test_Ma_0():
"""Check expected values for Ma = 0."""
val0 = np.array([1., 1., 1., 0., 0., 0., np.nan, np.nan])
Y0 = {var_test_sup[i]: val0[i] for i in range(len(var_test_sup))}
for v in var_test_sup:
print(v, Y0[v], cf.from_Ma( v, np.atleast_1d(0.), ga))
assert np.isclose( cf.from_Ma( v, np.atleast_1d(0.), ga), Y0[v],
atol=1e-7, equal_nan=True)
if np.isfinite(Y0[v]):
assert np.isclose( cf.to_Ma( v, np.atleast_1d(Y0[v]), ga), 0.0,
atol=1e-7, equal_nan=True)
a.set_title('Benchmark evaluation of $\dot{m}\sqrt{c_pT_0}/Ap_0$')
a.legend()
a.set_xlim((1, 1e5))
a.set_ylim((1e-7, 1e-2))
a.set_xticks(tick_marks)
f.tight_layout(pad=0.1)
plt.savefig('bench_forward.png', dpi=250)
speedup = np.array(dt_fort) / np.array(dt_native)
print('Fortran speedup: ', 1. / speedup[(0, -1), ])
# FORWARD EVALUATION
print('Benchmarking inversion...')
# Initialise lookup table
cf.to_Ma('mcpTo_APo', 0.4, ga, use_lookup=True)
# Loop over array sizes
dt_native = []
dt_fort = []
dt_lookup = []
for Ni in N:
X = np.random.rand(Ni) * (Xmax - Xmin) + Xmin
# Set up timers
T_fort = timeit.Timer('cf.Ma_from_mcpTo_APo(X,ga)',
'from __main__ import X,ga,cf')
T_native = timeit.Timer('cf.native.Ma_from_mcpTo_APo(X,ga)',
'from __main__ import X,ga,cf')
T_lookup = timeit.Timer('cf.to_Ma("mcpTo_APo",X,ga,use_lookup=True)',