Hi all,
I have experimental data that obey mono- or biexponential behavior (without or with offset): I = I0*exp(-t/T2), I = I0*exp(-t/T2) + offset1, I = I1*exp(-t/T2_1)+I2*exp(-t/T2_2), I = I1*exp(-t/T2_1)+I2*exp(-t/T2_2) + offset2. I is intensity, t is time, T2, T2_1 and T2_2 are time constants. I1 and I2 reflect fractions of T2_1 and T2_2 components, respectively. I'd like to ask a question about plotting in semilog scale. What is the difference between plotting intensity on a log scale (and the horizontal axis is time) and plotting ln(intensity) vs time (ln - natural logarithm, or base "e" logarithm)? I don't understand the first one - plotting intensity on a log scale. I know that, for example, in Matlab there are functions loglog, semilogx, semilogy, but again, I don't understand, how they work. What mathematical formulas should I use to implement conversion from standard scale to semilogy scale (when y-axis is in log scale) if I want to do such conversion manually? Moreover, from the Matlab help for semilogy function: "semilogy(Y) creates a plot using a base 10 logarithmic scale for the
y-axis and a linear scale for the
x-axis". Why do they use base 10 logarithmic scale and not base "e" logarithmic scale? If I want to use semilogy function, but with "e" base logarithm (natural logarithm), how can I implement this, for example, in Matlab? On the other side, plotting ln(intensity) is clear, because in this case I just take natural logarithm of my original intensity values, and then plot these ln(intensity) vs time. I also found the site
http://measurebiology.org/wiki/Understanding_log_plots, where topic is "Understanding log plots". On that site, authors show examples of plotting in log scale using Matlab. In the section "Linear vs. log scale", the authors wrote the following: "There are two ways to make a log-log plot in MATLAB. The first is to use the plot command to plot log(y) vs. log(x) on a linear scale.
plot( log10(x), log10(y))
Alternatively, you can use the loglog command to make a plot with log-scale axes:
loglog( x, y)"
Then they show corresponding graphs. These two plots look the same.