Prahas,
You're example is a little strange because when I set `x0 = (-1,0,0.5)`,
your function works fine on Python 2. Are you trying to set t0?
Note, your function does not compile on Python 3. You should try to be more
explicit with that first argument in that function. For example, does the
following do what you expect:
-----------------------------
# I changed the equation -- it's not Lorenz.
import numpy as np
N_trajectories = 5
def lorentz_deriv(xyz, t0, aa=1.1, yy=0.87):
"""Compute the time-derivative of a Lorentz system."""
x, y, z = xyz[0], xyz[1], xyz[2]
vals = [y*(z-1+x*x)+yy*x, x*(3*z+1-x*x)+yy*y, -2*z*(aa+x*y)]
return np.array(vals)
# Choose random starting points, uniformly distributed from -15 to 15
np.random.seed(1)
# Here's the statement which assigns the initial conditions:
x0 = -15 + 30 * np.random.random((3, N_trajectories))
#x0 = (-1, 0, 1.5)
lorentz_deriv(x0, 1.)
----------------------------------------------------
This gives me an answer for both Python2 and Python3 with both values of
x0. Is that what you want?
Ryan
On Sun, Mar 29, 2015 at 1:07 PM, Prahas David Nafissian <
prahas.mu...@gmail.com> wrote:
>
> Hi Mat-Plotters,
>
> I'm trying to modify the below code so that I can
> set the initial conditions to (-1,0,0.5).
>
> The code below randomly sets the initial conditions:
>
> **************
>
> # I changed the equation -- it's not Lorenz.
>
> N_trajectories = 1
>
> def lorentz_deriv((x, y, z), t0, aa=1.1, yy=0.87):
> """Compute the time-derivative of a Lorentz system."""
> return [y*(z-1+x*x)+yy*x, x*(3*z+1-x*x)+yy*y, -2*z*(aa+x*y)]
>
> # Choose random starting points, uniformly distributed from -15 to 15
>
> np.random.seed(1)
>
> *# Here's the statement which assigns the initial conditions:*
>
> x0 = -15 + 30 * np.random.random((N_trajectories, 3))
>
> ******************
>
> I tried simply doing this:
>
> x0 = (-1,0,0.5)
>
> but I get this error:
>
> ValueError: need more than 1 value to unpack
>
>
> What am I missing? What is the correct way to make the assignment?
>
>
> Thanks!
>
>
> --Prahas
>
>
>
>
>
>
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