MATLAB: Theorical Question About Making Matlab Read Graphic

graphic

Let's say we have a graphic which consinst of x axis and y axis, but the shown lines in graphic are gathered from many experimental data's and we can't reach to those informations. So we are left with only graphic. To make situation worse we just have pdf version of the graphic.

In this case, how can we make a program which will read values from this graphic?

Graphic Example

The question might be awkward. Im die-hard newbie in programming. I just wanted to ask and see what you guys would think about this.

Best Answer

Click on this link to launch a File Exchange search for functions that scan and import data from a printed plot. One popular file appears to be GRABIT.

Related Solutions

MATLAB: How to remove outliers from a linear fit

My idea:

x = 1:100;                                                      % Create Data

y = randi(99, 1, 100);                                          % Create Data
nr_pts_to_remove = fix(length(x)/2);
for k1 = 1:nr_pts_to_remove
    dm = [ones(size(x(:))) x(:)];                               % Design Matrix
    b = dm\y(:);                                                % Estimate Parameters
    yfit = dm*b;                                                % Fit Data
    [~,idx] = max(abs(y(:) - yfit));                            % Index Of Maximum Residual
    x(idx) = [];                                                % Remove Maximum ‘x’
    y(idx) = [];                                                % Remove Maximum ‘y’
end
xv = linspace(min(x), max(x));                                  % Create Vectors For Plot

yv = [ones(size(xv(:))) xv(:)]*b;                               % Create Vectors For Plot
figure(1)
plot(x, y, 'pg', 'MarkerFaceColor','g')
hold on
plot(xv, yv, '-r')
hold off
grid

The ‘(:)’ creates column vectors for all data and other variables.

MATLAB: Help with curve fitting

If you don't have an equation of your dataset, then it will be simpler to use the following methods

spline()

rng(0)
x = 1:10; % x-values


y = rand(size(x)); % random y-values


xv = linspace(min(x), max(x), 100); % more points on x-axis to make a smooth curve


yv = spline(x, y, xv); % interpolation using spline
plot(x, y, 'ro-', xv, yv, 'b-')

pchip()

rng(0)
x = 1:10; % x-values
y = rand(size(x)); % random y-values
xv = linspace(min(x), max(x), 100); % more points on x-axis to make a smooth curve
yv = pchip(x, y, xv); % interpolation using pchip
plot(x, y, 'ro-', xv, yv, 'b-')

makima()

rng(0)
x = 1:10; % x-values
y = rand(size(x)); % random y-values
xv = linspace(min(x), max(x), 100); % more points on x-axis to make a smooth curve
yv = makima(x, y, xv); % interpolation using makima
plot(x, y, 'ro-', xv, yv, 'b-')

Best Answer

Related Solutions

MATLAB: How to remove outliers from a linear fit

MATLAB: Help with curve fitting

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