def test_warnings():
# ticket 1334
with np.errstate(all='raise'):
# these should raise no fp warnings
orth.eval_legendre(1, 0)
orth.eval_laguerre(1, 1)
orth.eval_gegenbauer(1, 1, 0)
def test_warnings():
# ticket 1334
olderr = np.seterr(all='raise')
try:
# these should raise no fp warnings
orth.eval_legendre(1, 0)
orth.eval_laguerre(1, 1)
orth.eval_gegenbauer(1, 1, 0)
finally:
np.seterr(**olderr)
def test_warnings():
# ticket 1334
olderr = np.seterr(all='raise')
try:
# these should raise no fp warnings
orth.eval_legendre(1, 0)
orth.eval_laguerre(1, 1)
orth.eval_gegenbauer(1, 1, 0)
finally:
np.seterr(**olderr)
def param(V, T, P, aerosols=[], accom=0.1,
mus=[], sigmas=[], Ns=[], kappas=[],
pcm=RUNS.keys()[0], level="expansion_order_4", pcm_N=False):
if aerosols:
d = _unpack_aerosols(aerosols)
mu = d['mus'][0]
sigma = d['sigmas'][0]
kappa = d['kappas'][0]
N = d['Ns'][0]
else:
## Assert that the aerosol was already decomposed into component vars
assert mus
mu = mus[0]
assert sigmas
sigma = sigmas[0]
assert Ns
N = Ns[0]
assert kappas
kappa = kappas[0]
logN = np.log10(N)
logmu = np.log10(mu)
logV = np.log10(V)
## Project into orthogonal polynomial space
z = project([logN, logmu, sigma, kappa, logV, T, P, accom])
coeffs = RUNS_SAVE[pcm][level]['coeffs']
orders = RUNS_SAVE[pcm][level]['orders']
max_orders = RUNS_SAVE[pcm][level]['max_orders']
#nterms = len(coeffs)
#nvars = len(z)
## Step 1) Evaluate the necessary polynomial orders
poly_evals = []
for zi, order in zip(z, max_orders):
poly_evals.append([op.eval_legendre(n, zi) for n in xrange(order+1)])
poly_evals = np.array(poly_evals)
evaluation = poly_eval(orders, coeffs, poly_evals)
## Step 3) This gives us log10(Smax), so now we return Smax
Smax = 10.**(evaluation)
n_act, act_frac = lognormal_activation(Smax, mu*1e-6, sigma, N, kappa, T=T)
return Smax, n_act, act_frac
from scipy.special.orthogonal import eval_legendre
import matplotlib.pyplot as plt
import numpy as np
psi = lambda n,x: eval_legendre(n, x)
x = np.linspace(-5, 5, 500)
for n in xrange(6):
plt.plot(x, psi(n,x), label=r"$P_"+str(n)+r"(x)$")
plt.grid(True)
plt.xlim(-1,1)
plt.ylim(-1.5,1.5)
plt.xlabel(r"$x$")
plt.ylabel(r"$P_n(x)$")
plt.legend(loc="lower center", ncol=6, prop={'size': 10})
plt.title(r"Legendre polynomials $P_n$")
#plt.show()
plt.savefig('legendre.pdf')
