INNER CODE UNIT · Python

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mszell/geospatialdatascience · unit11_mobilityindividual/stats_utils.py:235

        def f(x): return x[0] *  x[1] / mu()

        # Gaussian
            np.exp( -(x-mu())**2.0/sigma()**2.0/2.0)/(2.0*sigma()**2.0*np.pi)**0.5
        # Lognormal
            np.exp( -(np.log(x)-mu())**2.0/sigma()**2.0/2.0)/(2.0*sigma()**2.0*np.pi)**0.5/x

    Example:
        x=[np.random.normal() for i in range(1000)]
        variables,data = map(np.array,zip(*pdf(0.4,x)))

        # giving INITIAL _PARAMETERS_:
        mu     = Parameter(7)
        sigma  = Parameter(3)

        # define your _FUNCTION_:
        def function(x): return np.exp( -(x-mu())**2.0/sigma()**2.0/2.0)/(2.0*sigma()**2.0*np.pi)**0.5

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