# Scatter Plots in MATLAB®

How to make Scatter Plots plots in MATLAB® with Plotly.

## Create Scatter Plot

Create x as 200 equally spaced values between 0 and 3π. Create y as cosine values with random noise. Then, create a scatter plot.

x = linspace(0,3*pi,200);
y = cos(x) + rand(1,200);
scatter(x,y)

fig2plotly(gcf);


## Vary Circle Size

Create a scatter plot using circles with different sizes. Specify the size in points squared

x = linspace(0,3*pi,200);
y = cos(x) + rand(1,200);
sz = linspace(1,100,200);
scatter(x,y,sz)

fig2plotly(gcf);


Corresponding elements in x, y, and sz determine the location and size of each circle. To plot all circles with the equal area, specify sz as a numeric scalar.

## Vary Circle Color

Create a scatter plot and vary the circle color.

x = linspace(0,3*pi,200);
y = cos(x) + rand(1,200);
c = linspace(1,10,length(x));
scatter(x,y,[],c)

fig2plotly(gcf);


Corresponding elements in x, y, and c determine the location and color of each circle. The scatter function maps the elements in c to colors in the current colormap.

## Fill the Markers

Create a scatter plot and fill in the markers. scatter fills each marker using the color of the marker edge.

x = linspace(0,3*pi,200);
y = cos(x) + rand(1,200);
sz = 25;
c = linspace(1,10,length(x));
scatter(x,y,sz,c,'filled')

fig2plotly(gcf);


## Specify Marker Symbol

Create vectors x and y as sine and cosine values with random noise. Then, create a scatter plot and use diamond markers with an area of 140 points squared.

theta = linspace(0,2*pi,150);
x = sin(theta) + 0.75*rand(1,150);
y = cos(theta) + 0.75*rand(1,150);
sz = 140;
scatter(x,y,sz,'d')

fig2plotly(gcf);


## Change Marker Color and Line Width

Create vectors x and y as sine and cosine values with random noise. Create a scatter plot and set the marker edge color, marker face color, and line width.

theta = linspace(0,2*pi,300);
x = sin(theta) + 0.75*rand(1,300);
y = cos(theta) + 0.75*rand(1,300);
sz = 40;
scatter(x,y,sz,'MarkerEdgeColor',[0 .5 .5],...
'MarkerFaceColor',[0 .7 .7],...
'LineWidth',1.5)

fig2plotly(gcf);


## Vary Transparency Across Data Points

You can vary the transparency of scattered points by setting the AlphaData property to a vector of different opacity values. To ensure the scatter plot uses the AlphaData values, set the MarkerFaceAlpha property to 'flat'.

Create a set of normally distributed random numbers. Then create a scatter plot of the data with filled markers.

x = randn(1000,1);
y = randn(1000,1);
s = scatter(x,y,'filled');

fig2plotly(gcf);


Set the opacity of each point according to its distance from zero.

x = randn(1000,1);
y = randn(1000,1);
s = scatter(x,y,'filled');

distfromzero = sqrt(x.^2 + y.^2);
s.MarkerFaceAlpha = 'flat';

fig2plotly(gcf);


## Specify Target Axes and Marker Type

Starting in R2019b, you can display a tiling of plots using the tiledlayout and nexttile functions. Call the tiledlayout function to create a 2-by-1 tiled chart layout. Call the nexttile function to create the axes objects ax1 and ax2. Plot scattered data into each axes. In the bottom scatter plot, specify diamond filled diamond markers.

x = linspace(0,3*pi,200);
y = cos(x) + rand(1,200);
tiledlayout(2,1)

% Top plot
ax1 = nexttile;
scatter(ax1,x,y)

% Bottom plot
ax2 = nexttile;
scatter(ax2,x,y,'filled','d')

fig2plotly(gcf);


## Modify Scatter Series After Creation

Create a scatter plot and return the scatter series object, s.

theta = linspace(0,1,500);
x = exp(theta).*sin(100*theta);
y = exp(theta).*cos(100*theta);
s = scatter(x,y);

fig2plotly(gcf);


Use s to query and set properties of the scatter series after it has been created. Set the line width to 0.6 point. Set the marker edge color to blue. Set the marker face color using an RGB triplet color.

theta = linspace(0,1,500);
x = exp(theta).*sin(100*theta);
y = exp(theta).*cos(100*theta);
s = scatter(x,y);

s.LineWidth = 0.6;
s.MarkerEdgeColor = 'b';
s.MarkerFaceColor = [0 0.5 0.5];

fig2plotly(gcf);


## Simple Scatter Plot

load seamount x y z;

fig = figure;
scatter(x, y, 10, z);

title('Undersea Elevation');
xlabel('Longitude');
ylabel('Latitude');

fig2plotly(gcf);


## Plotting Complex Data (Real and Imaginary Parts)

x = -2:0.25:2;
z1 = x.^exp(-x.^2);
z2 = 2*x.^exp(-x.^2);
real_z1 = real(z1);
imag_z1 = imag(z1);

real_z2 = real(z2);
imag_z2 = imag(z2);

plot(real_z1,imag_z1,'g*',real_z2,imag_z2,'bo');
title('Plotting Complex Data');

fig2plotly(gcf);


## Thick line on top of points

fs = 500;

dur = 1;

t = 1 + linspace(-dur,dur,fs);

sig = [t(1:length(t)/2) t(1:length(t)/2)];

sign = sig + 0.1*randn(1,length(sig));

fig = figure;
sp = plot(t,sig,'LineWidth',8);
hold on
sn = plot(t,sign,'ro');

title('Singal Noise');
xlabel('Time (s.)');
ylabel('Amplitude');

fig2plotly(gcf);