The equation of a line on a linear–log plot, where the
abscissa axis is scaled logarithmically (with a logarithmic base of
n), would be : F(x) = m \log_{n}(x) + b. \, The equation for a line on a log–linear plot, with an
ordinate axis logarithmically scaled (with a logarithmic base of
n), would be: : \log_{n}(F(x)) = mx + b : F(x) = n^{mx + b} = (n^{mx})(n^b).
Finding the function from the semi–log plot Linear–log plot On a linear–log plot, pick some
fixed point (
x0,
F0), where
F0 is shorthand for
F(
x0), somewhere on the straight line in the above graph, and further some other
arbitrary point (
x1,
F1) on the same graph. The slope formula of the plot is: : m = \frac {F_1 - F_0}{\log_n (x_1 / x_0)} which leads to : F_1 - F_0 = m \log_n (x_1 / x_0) or : F_1 = m \log_n (x_1 / x_0) + F_0 = m \log_n (x_1) - m \log_n (x_0) + F_0 which means that F(x) = m \log_n (x) + \mathrm{constant} In other words,
F is proportional to the logarithm of
x times the slope of the straight line of its lin–log graph, plus a constant. Specifically, a straight line on a lin–log plot containing points (
F0,
x0) and (
F1,
x1) will have the function: : F(x) = (F_1 - F_0) {\left[\frac{\log_n (x / x_0)}{\log_n(x_1 / x_0)}\right]} + F_0 = (F_1 - F_0) \log_{\frac{x_1}{x_0}}{\left(\frac{x}{x_0}\right)} + F_0
log–linear plot On a log–linear plot (logarithmic scale on the y-axis), pick some
fixed point (
x0,
F0), where
F0 is shorthand for
F(
x0), somewhere on the straight line in the above graph, and further some other
arbitrary point (
x1,
F1) on the same graph. The slope formula of the plot is: : m = \frac {\log_n (F_1 / F_0)}{x_1 - x_0} which leads to : \log_n(F_1 / F_0) = m (x_1 - x_0) Notice that
nlog
n(
F1) =
F1. Therefore, the logs can be inverted to find: : \frac{F_1}{F_0} = n^{m(x_1 - x_0)} or : F_1 = F_0n^{m(x_1 - x_0)} This can be generalized for any point, instead of just
F1: : F(x) = {F_0} n^{\left(\frac {x-x_0}{x_1-x_0}\right) \log_n (F_1 / F_0)} == Real-world examples ==