mhjensen
28 lines
727 B
Python
28 lines
727 B
Python
import numpy as np
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# Estimate r
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data = np.loadtxt('ecoli.csv', delimiter=',')
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t_e = data[:,0]
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N_e = data[:,1]
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i = 2 # Data point (i,i+1) used to estimate r
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r = (N_e[i+1] - N_e[i])/(N_e[i]*(t_e[i+1] - t_e[i]))
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print 'Estimated r=%.5f' % r
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# Can experiment with r values and see if the model can
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# match the data better
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T = 1200 # cell can divide after T sec
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t_max = 5*T # 5 generations in experiment
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t = np.linspace(0, t_max, 1000)
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dt = t[1] - t[0]
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N = np.zeros(t.size)
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N[0] = 100
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for n in range(0, len(t)-1, 1):
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N[n+1] = N[n] + r*dt*N[n]
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import matplotlib.pyplot as plt
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plt.plot(t, N, 'r-', t_e, N_e, 'bo')
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plt.xlabel('time [s]'); plt.ylabel('N')
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plt.legend(['model', 'experiment'], loc='upper left')
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plt.show()
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