loglog

Log-log scale plot

Syntax

loglog(Y)
loglog(X1,Y1,...)
loglog(X1,Y1,LineSpec,...)
loglog(...,'PropertyName',PropertyValue,...)
loglog(ax,...)
h = loglog(...)


Description

loglog(Y) plots the columns of Y versus their index if Y contains real numbers. If Y contains complex numbers, loglog(Y) and loglog(real(Y),imag(Y)) are equivalent. loglog ignores the imaginary component in all other uses of this function.

loglog(X1,Y1,...) plots all Yn versus Xn pairs. If only one of Xn or Yn is a matrix, loglog plots the vector argument versus the rows or columns of the matrix, along the dimension of the matrix whose length matches the length of the vector. If the matrix is square, its columns plot against the vector if their lengths match.

loglog(X1,Y1,LineSpec,...) plots all lines defined by the Xn,Yn,LineSpec triples, where LineSpec determines line type, marker symbol, and color of the plotted lines. You can mix Xn,Yn,LineSpec triples with Xn,Yn pairs, for example,

loglog(X1,Y1,X2,Y2,LineSpec,X3,Y3)

loglog(...,'PropertyName',PropertyValue,...) sets line property values for all the charting lines created. For a list of properties, see Line Properties.

loglog(ax,...) creates the line in the axes specified by ax instead of in the current axes (gca). The option ax can precede any of the input argument combinations in the previous syntaxes.

h = loglog(...) returns a column vector of chart line objects.

If you do not specify a color when plotting more than one line, loglog automatically cycles through the colors and line styles in the order specified by the current axes.

If you attempt to add a loglog, semilogx, or semilogy plot to a linear axis mode graph with hold on, the axis mode remains as it is and the new data plots as linear.

Examples

Logarithmic Scale for Both Axes

Create a plot using a logarithmic scale for both the x-axis and the y-axis. Use a line with square markers. Display the grid.

x = logspace(-1,2);
y = exp(x);
loglog(x,y,'-s')
grid on

Extended Capabilities

GPU Arrays

Accelerate code by running on a graphics processing unit (GPU) using Parallel Computing Toolbox™.

Usage notes and limitations:

• This function accepts GPU arrays, but does not run on a GPU.

For more information, see Run MATLAB Functions on a GPU (Parallel Computing Toolbox).

Distributed Arrays

Partition large arrays across the combined memory of your cluster using Parallel Computing Toolbox™.

Usage notes and limitations:

• This function operates on distributed arrays, but executes in the client MATLAB^®.

For more information, see Run MATLAB Functions with Distributed Arrays (Parallel Computing Toolbox).