mirror of https://github.com/pyodide/pyodide.git
13 lines
589 B
Python
13 lines
589 B
Python
#from: http://wiki.scipy.org/Cookbook/Theoretical_Ecology/Hastings_and_Powell
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#setup: import numpy as np ; y = np.random.rand(3) ; args = np.random.rand(7)
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#run: hasting(y, *args)
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#pythran export hasting(float [], float, float, float, float, float, float, float)
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import numpy as np
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def hasting(y, t, a1, a2, b1, b2, d1, d2):
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yprime = np.empty((3,))
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yprime[0] = y[0] * (1. - y[0]) - a1*y[0]*y[1]/(1. + b1 * y[0])
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yprime[1] = a1*y[0]*y[1] / (1. + b1 * y[0]) - a2 * y[1]*y[2] / (1. + b2 * y[1]) - d1 * y[1]
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yprime[2] = a2*y[1]*y[2]/(1. + b2*y[1]) - d2*y[2]
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return yprime
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