eccpy/tools.py
def hill_eq_brentq(xvalues_for_curve, hill_constants, y_value_curve_center):
    """ Residual function for the four parameter sigmoidal Hill equation.

    For further detail on the Hill equation, see the relevant docstring for hill_eq.

    y = hill_eq(x) - y_value_curve_center

    Parameters
    ----------
    xvalues_for_curve : array
        Numpy array of >250 x-values between the lowest and highest dose.
    hill_constants : tuple
        Tuple of the four parameters : upper, lower, EC50 and hillslope
    y_value_curve_center : array
        Represents the y-value of the curve. The difference between this and the real y-value from experimental
        data (e.g. y_orig_norm) is used to optimise the fit of the curve to the data.

    Returns
    -------
    y - y_value_curve_center : array
        Array that approaches zero, when an optimum fit is found.
    """
    upper, lower, EC50, hillslope = hill_constants
    y = upper + (lower-upper)/(1+(xvalues_for_curve/EC50)**-hillslope)
    return y - y_value_curve_center
 Residual function for the four parameter sigmoidal Hill equation.

    For further detail on the Hill equation, see the relevant docstring for hill_eq.

    y = hill_eq(x) - y_value_curve_center

    Parameters
    ----------
    xvalues_for_curve : array
        Numpy array of >250 x-values between the lowest and highest dose.
    hill_constants : tuple
        Tuple of the four parameters : upper, lower, EC50 and hillslope
    y_value_curve_center : array
        Represents the y-value of the curve. The difference between this and the real y-value from experimental
        data (e.g. y_orig_norm) is used to optimise the fit of the curve to the data.

    Returns
    -------
    y - y_value_curve_center : array
        Array that approaches zero, when an optimum fit is found.
    
Residual function for the four parameter sigmoidal Hill equation.
For further detail on the Hill equation, see the relevant docstring for hill_eq.



Parameters

xvalues_for_curve : array
Numpy array of >250 x-values between the lowest and highest dose.
hill_constants : tuple
Tuple of the four parameters : upper, lower, EC50 and hillslope
y_value_curve_center : array
Represents the y-value of the curve. The difference between this and the real y-value from experimental
data  is used to optimise the fit of the curve to the data.

Returns

y_value_curve_center : array
Array that approaches zero, when an optimum fit is found.
Residual function for the four parameter sigmoidal Hill equation . For further detail on the Hill equation see the relevant docstring for hill_eq . Parameters xvalues_for_curve : array Numpy array of > 250 x - values between the lowest and highest dose . hill_constants : tuple Tuple of the four parameters : upper lower EC50 and hillslope y_value_curve_center : array Represents the y - value of the curve . The difference between this and the real y - value from experimental data is used to optimise the fit of the curve to the data . Returns y_value_curve_center : array Array that approaches zero when an optimum fit is found .
def hill_eq_brentq(xvalues_for_curve, hill_constants, y_value_curve_center):
    upper, lower, EC50, hillslope = hill_constants
    y = upper + (lower-upper)/(1+(xvalues_for_curve/EC50)**-hillslope)
    return y - y_value_curve_center
def hill_eq_brentq ( xvalues_for_curve , hill_constants , y_value_curve_center ) : upper , lower , EC50 , hillslope = hill_constants y = upper + ( lower - upper ) / ( 1 + ( xvalues_for_curve / EC50 ) ** - hillslope ) return y - y_value_curve_center
Residual function for the four parameter sigmoidal Hill equation.
Residual function for the four parameter sigmoidal Hill equation .
""" Residual function for the four parameter sigmoidal Hill equation.

    For further detail on the Hill equation, see the relevant docstring for hill_eq.

    y = hill_eq(x) - y_value_curve_center

    Parameters
    ----------
    xvalues_for_curve : array
        Numpy array of >250 x-values between the lowest and highest dose.
    hill_constants : tuple
        Tuple of the four parameters : upper, lower, EC50 and hillslope
    y_value_curve_center : array
        Represents the y-value of the curve. The difference between this and the real y-value from experimental
        data (e.g. y_orig_norm) is used to optimise the fit of the curve to the data.

    Returns
    -------
    y - y_value_curve_center : array
        Array that approaches zero, when an optimum fit is found.
    """
xvalues_for_curve
hill_constants
y_value_curve_center