Pass an array in python odeint

Question

I am quite new to Python, so do excuse me if the following question has a 'duh' answer.

So, I'm trying to solve an ODE using odeint and wish to pass an array. But, the TypeError: can't multiply sequence by non-int of type 'float' keeps cropping up, in the line:

CA0 = (-kd-kn*Cv)*CAi/(1+(CAi/ks))

So, the code is:

from scipy.integrate import odeint
import numpy as np

Ap_data = [2, 7, 91, 1.6, 0.4, 5]
tdata= [0, 1, 4, 5, 4, 20]
Cv_data = [43, 580, 250, 34, 30, 3]

#Define parameters
kn = 1E-5 #change 
ks = 1E+5 #change
kd = 0.058  

def deriv (CAi,t, Cv):
    CA0 = (-kd-kn*Cv)*CAi/(1+(CAi/ks))
    return CA0

#Initial conditions
CA_init = 21.6

#Solve the ODE
(CAb_soln) = odeint (derivCAb, CA_init, tdata, (Cv_data,))

print CAb_soln

Some help, please?

In your example, `deriv` isn't actually called. Can you please change your example code? — Carsten, Feb 06 '15 at 23:01

xnx · Accepted Answer · 2015-02-11T20:39:38.017

Your immediate problem is that your deriv function is trying to multiply the ordinary Python list, Cv_data (passed in as Cv) by float values. If you want to vectorize this operation, use NumPy arrays:

Ap_data = np.array([2, 7, 91, 1.6, 0.4, 5])
tdata= np.array([0, 1, 4, 5, 4, 20])
Cv_data = np.array([43, 580, 250, 34, 30, 3])

to solve this. You now have the problem that odeint fails for the input you give it...

 intdy--  t (=r1) illegal      
      in above message,  r1 =  0.4000000000000D+01
      t not in interval tcur - hu (= r1) to tcur (=r2)       
      in above,  r1 =  0.4287484688360D+01   r2 =  0.5551311182627D+01
 lsoda--  trouble from intdy. itask = i1, tout = r1ls
      in above message,  i1 =         1
      in above message,  r1 =  0.4000000000000D+01
Illegal input detected (internal error).
Run with full_output = 1 to get quantitative information.
[[ 21.6       ]
 [ 20.37432613]
 [ 17.09897165]
 [ 16.12866355]
 [ 16.12866355]
 [ -0.90614016]]

Perhaps you can give more information about what your equation is and how it relates to Cv_data. In particular, your derivative doesn't depend on t, but you have a range of values for this parameter, Cv.

UPDATE: It fails because of your funny time series. odeint works properly if it is monotonic, for example:

from scipy.integrate import odeint
import numpy as np

Ap_data = [2, 7, 91, 1.6, 0.4, 5]
tdata= np.array([0, 1, 4, 5, 10, 20])
Cv_data = np.array([43, 580, 250, 34, 30, 3])

#Define parameters
kn = 1E-5 #change 
ks = 1E+5 #change
kd = 0.058  

def deriv (CAi,t, Cv):
    CA0 = (-kd-kn*Cv)*CAi/(1+(CAi/ks))
    return CA0

#Initial conditions
CA_init = 21.6

#Solve the ODE
(CAb_soln) = odeint (deriv, CA_init, tdata, (Cv_data,))
print CAb_soln

The result:

[[ 21.6       ]
 [ 20.37432613]
 [ 17.09897165]
 [ 16.12866355]
 [ 12.04306424]
 [  6.71431758]]

Hello. Essentially there is a Cv value and an Ap value for every given time point, and I wish for odeint to solve for Ap at every time point using an initial Ap value and the corresponding Cv and t values. Also, thank you trying to help. I appreciate it. I tried taking your suggestion into account, and got an error (the picture of which I shall be posting as answer). — MacGuffin, Feb 08 '15 at 23:45
I'm a bit confused: you don't seem to be using `Ap_data` anywhere in your code? How does it relate to the problem you're trying to solve? Do you want to solve the same equation 6 times for each value of Cv and Ap using the same time points in each case? — xnx, Feb 09 '15 at 02:44
Hello. The Ap_data is for comparing the calculated CA values with the experimental ones (which is given in Ap_data). I shall use it to calculate the variance and then get better parameter estimates (where it says change in the code). And yes, I do wish to solve six times for CA, like a normal ODE solver, with time points that mentioned in tdata (and Cv for each from Cv_data). — MacGuffin, Feb 11 '15 at 15:35
See the update? I think the problem was with your time series. — xnx, Feb 11 '15 at 20:39
Woao. That's brilliant! Thanks a gazillion. Shall not delve in funny time arrays from now on. — MacGuffin, Feb 12 '15 at 20:58

score 0 · Answer 2 · answered Feb 08 '15 at 23:50

Well, as it turns out I cannot post an image yet (being new to stackoverflow). So, the code that I used was-

from scipy.integrate import odeint
import numpy as np

Ap_data = np.array([2, 7, 91, 1.6, 0.4, 5])
tdata= [0, 1, 4, 5, 4, 20]
Cv_data = np.array([43, 580, 250, 34, 30, 3])

#Define parameters
kn = 1E-5 #change 
ks = 1E+5 #change
kd = 0.058  

def deriv (CAi,t, Cv):
    CA0 = (-kd-kn*Cv)*CAi/(1+(CAi/ks))
    return CA0

#Initial conditions
CA_init = 21.6

#Solve the ODE
(CAb_soln) = odeint (deriv, CA_init, tdata, (Cv_data,), full_output=True)

print CAb_soln

Pass an array in python odeint

2 Answers2