def eval_Taylor(P, R, mbar, alpha_x, x):
"""My function description here."""
if (P % 2 == 0):
T0 = 2 * np.pi
else:
T0 = 1 * np.pi
A = pl.dist(1, P + 1, R, dist_type_x='Taylor', mbar=mbar, alpha_x=alpha_x)
x, result = IFS(A,
T0,
m_start=-P / 2,
m_stop=P / 2,
x_min=x,
x_max=x,
x_num=1)
# if(P%2==0):
# A = pl.dist(1, P + 1, R, dist_type_x='Taylor', mbar=mbar, alpha_x=alpha_x)
# x, result = IFS(A, T0=2*np.pi, m_start= -P / 2, m_stop=P / 2, x_min=x, x_max=x, x_num=1)
# else:
# A = pl.dist(1, 2*P + 1, R, dist_type_x='Taylor', mbar=mbar, alpha_x=alpha_x)
# x, result = IFS(A, T0=1*np.pi, m_start= -P, m_stop=P, x_min=x, x_max=x, x_num=1)
result = result[0, 0].real
return result
def eval_Bayliss(P, R, mbar, alpha_x, x):
"""My function description here."""
if(P%2==0):
print "Order needs to be an ODD number for null patterns"
else:
T0=1*np.pi
A = pl.dist(1, P + 1, R, dist_type_x='Bayliss', mbar=mbar, alpha_x=alpha_x)
x, result = IFS(A, T0, m_start= -P / 2, m_stop=P / 2, x_min=x, x_max=x, x_num=1)
result = result[0,0].imag
return result
def eval_Bayliss(P, R, mbar, alpha_x, x):
"""My function description here."""
if (P % 2 == 0):
print("Order needs to be an ODD number for null patterns")
else:
T0 = 1 * np.pi
A = pl.dist(1, P + 1, R, dist_type_x='Bayliss', mbar=mbar, alpha_x=alpha_x)
x, result = IFS(A,
T0,
m_start=-P / 2,
m_stop=P / 2,
x_min=x,
x_max=x,
x_num=1)
result = result[0, 0].imag
return result
def eval_Taylor(P, R, mbar, alpha_x, x):
"""My function description here."""
if(P%2==0):
T0 = 2*np.pi
else:
T0=1*np.pi
A = pl.dist(1, P + 1, R, dist_type_x='Taylor', mbar=mbar, alpha_x=alpha_x)
x, result = IFS(A, T0, m_start= -P / 2, m_stop=P / 2, x_min=x, x_max=x, x_num=1)
# if(P%2==0):
# A = pl.dist(1, P + 1, R, dist_type_x='Taylor', mbar=mbar, alpha_x=alpha_x)
# x, result = IFS(A, T0=2*np.pi, m_start= -P / 2, m_stop=P / 2, x_min=x, x_max=x, x_num=1)
# else:
# A = pl.dist(1, 2*P + 1, R, dist_type_x='Taylor', mbar=mbar, alpha_x=alpha_x)
# x, result = IFS(A, T0=1*np.pi, m_start= -P, m_stop=P, x_min=x, x_max=x, x_num=1)
result = result[0,0].real
return result
