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A rather confusing TypeError: cannot unpack non-iterable float object raised

February 16, 2024

I have a problem when generating two plots using solve_ivp. The problem occurs at the line that unpack concentrations from the array. What can I do to fix it? Thanks a lot for your replies in advance!

#Modules needed
import numpy as np
import matplotlib.pyplot as plt
from scipy.integrate import solve_ivp

def reaction_prime(c, t):
    # Define rate constants
    k1 = 100  # Unit: s^-1 * M^-1
    k2 = 0.5  # Unit: s^-1 * M^-1
    k3 = 0.1  # Unit: s^-1
    k4 = 0.2  # Unit: s^-1
    k5 = 0.3  # Unit: s^-1

    # Define initial concentrations
    cA, cB, cC, cD, cE, cF, cG, cH, cI = c  # Unpack concentrations from the array

    # Define reaction rates
    dcAdt = (-1) * k1 * cA * cB + k2 * cC
    dcBdt = (-1) * k1 * cA * cB + k2 * cC
    dcCdt = k1 * cA * cB - k2 * cC - k3 * cC * cD
    dcDdt = k3 * cC * cD - k4 * cE * cF - k5 * cE * cH
    dcEdt = k4 * cE * cF + k5 * cE * cH - k3 * cC * cD
    dcFdt = (-1) * k4 * cE * cF
    dcGdt = k4 * cE * cF
    dcHdt = (-1) * k5 * cE * cH
    dcIdt = k5 * cE * cH

    # Output every rates
    return [dcAdt, dcBdt, dcCdt, dcDdt, dcEdt, dcFdt, dcGdt, dcHdt, dcIdt]

# Define initial concentration of every components
c_ini = [0.1, 0.1, 0, 0.01, 0, 0.1, 0, 0.1, 0]

# Define reaction time
t_r = np.linspace(0, 100, 500)

# Modeling using solve_ivp
c_predict = solve_ivp(reaction_prime, [0, 100], y0=c_ini, t_eval=t_r)

# Plot generation
plt.plot(t_r, c_predict.y[0], label='[A]')
plt.plot(t_r, c_predict.y[1], label='[B]')
plt.plot(t_r, c_predict.y[2], label='[C]')
plt.plot(t_r, c_predict.y[3], label='[D]')
plt.plot(t_r, c_predict.y[4], label='[E]')
plt.plot(t_r, c_predict.y[5], label='[F]')
plt.plot(t_r, c_predict.y[6], label='[G]')
plt.plot(t_r, c_predict.y[7], label='[H]')
plt.plot(t_r, c_predict.y[8], label='[I]')
plt.xlabel('t, Time')
plt.ylabel('c, Concentration')
plt.legend()
plt.title('Relatively COMPLEX Situation')
plt.show()

In another simple codes I wrote, it runs smoothly, no Typeerror raised. I have no idea about why the previous one cannot work…

# Modules needed
import numpy as np
import matplotlib.pyplot as plt
from scipy.integrate import solve_ivp

def reaction(t, c):
    # Define rate constants
    k1 = 100  # Unit: s^-1 * M^-1
    k2 = 0.5  # Unit: s^-1 * M^-1
    k3 = 0.1  # Unit: s^-1

    # Define concentrations of every components
    cA, cB, cC, cD = c

    # Define reaction rates
    dcAdt = (-1) * k1 * cA * cB + k2 * cC
    dcBdt = (-1) * k1 * cA * cB + k2 * cC
    dcCdt = k1 * cA * cB - k2 * cC - k3 * cC
    dcDdt = k3 * cC

    # Return every rates as a list
    return [dcAdt, dcBdt, dcCdt, dcDdt]

# Define initial rates of every components
c_initial = [0.01, 0.02, 0, 0]

# Define reaction time
t_reaction = np.linspace(0, 100, 500)

# Modeling using solve_ivp
c_predict = solve_ivp(reaction, [0, 100], y0=c_initial, t_eval=t_reaction)

# Plot generation
plt.plot(t_reaction, c_predict.y[0], label='[A]')
plt.plot(t_reaction, c_predict.y[1], label='[B]')
plt.plot(t_reaction, c_predict.y[2], label='[C]')
plt.plot(t_reaction, c_predict.y[3], label='[D]')
plt.xlabel('t, Time')
plt.ylabel('c, Concentration')
plt.legend()
plt.title('Relatively Simple Situation')
plt.show

The error for the former codes:

---------------------------------------------------------------------------
TypeError                                 Traceback (most recent call last)
<ipython-input-50-8b328c41d85b> in <cell line: 38>()
     36 
     37 # Modeling using solve_ivp
---> 38 c_predict = solve_ivp(reaction_prime, [0, 100], y0=c_ini, t_eval=t_r)
     39 
     40 # Plot generation

4 frames
<ipython-input-50-8b328c41d85b> in reaction_prime(c, t)
     13 
     14     # Define initial concentrations
---> 15     cA, cB, cC, cD, cE, cF, cG, cH, cI = c  # Unpack concentrations from the array
     16 
     17     # Define reaction rates

TypeError: cannot unpack non-iterable float object