Semilog plot (y-axis has log scale)
semilogy(Y)
semilogy(X1,Y1,...)
semilogy(X1,Y1,LineSpec
,...)
semilogy(...,'PropertyName
',PropertyValue,...)
semilogy(ax,...)
h = semilogy(...)
semilogy
plots data with logarithmic scale
for the y-axis.
semilogy(Y)
creates a plot
using a base 10 logarithmic scale for the y-axis
and a linear scale for the x-axis. It plots the
columns of Y
versus their index. If Y
contains
complex values, then semilogy(Y)
is equivalent
to semilogy(real(Y),imag(Y))
. The semilogy
function
ignores the imaginary component in all other uses of this function.
semilogy(X1,Y1,...)
plots
all Yn
versus Xn
pairs. If only
one of Xn
or Yn
is a matrix, semilogy
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. The values in Xn
can be
numeric, datetime, duration, or categorical values. The values in Yn
must
be numeric.
semilogy(X1,Y1,
plots all lines defined by the LineSpec
,...)Xn,Yn,
triples. LineSpec
LineSpec
determines
line style, marker symbol, and color of the plotted lines.
semilogy(...,'
sets property values for all the charting lines created by PropertyName
',PropertyValue,...)semilogy
.
For a list of properties, see Line Properties.
semilogy(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 = semilogy(...)
returns
a vector of chart line objects.
If you do not specify a color when plotting more than one line, semilogy
automatically cycle through the colors and line styles in the order specified by the
current axes ColorOrder
and
LineStyleOrder
properties.
You can mix Xn,Yn
pairs with Xn,Yn,
triples;
for example, LineSpec
semilogy(X1,Y1,X2,Y2,LineSpec,X3,Y3)
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.