Interpolation of a scatter plot

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Yannick Tabot Njami
评论： Yannick Tabot Njami 2019-6-18
Hello ;I would be most grateful if someone could give me a helping hand. i have a scatter plot where the the third variable is velocity color coded for each pair of (x,y)I woud like to interpolate this plot to have more points.below is a figure of what i have and my code as well . thanks in advance.
the interpolated points are the red piont of the second figure is having just 9 pionts. i would like to apply that to the first figure which is what i have .
plotTypes = {'mean_velocity','std_velocity','mean_pd', 'std_pd'};
for i = 1: length(plotTypes)
figure
plotType = plotTypes{i};
%subplot(1,length(plotTypes), i);
hold all ;
legendLabels = cell(1,length(plotData));
for j = 1:length(plotData)
xPlot= plotData{j}.data(:, idx.x);
yPlot= plotData{j}.data(:, idx.(plotTypes{i}));
plot(xPlot,yPlot, '-o','color',k(j,:));
legendLabels{j} = ['Y = ', num2str(plotData{j}.y)];
end
legend(legendLabels);
title(plotTypes{i}, 'Interpreter', 'none');
xlabel('x position')
ylabel(plotTypes{i}, 'Interpreter', 'none')
end
%% Generating the 3D color plot
% figure
for i = 1: length(plotTypes)
figure
legendLabels = cell(1,length(plotData));
% subplot(1,length(plotTypes), i);
hold all
for N=1:size(plotData,2)
pz =150;
plotData{1,N}.data();
x=plotData{1,N}.data(:,1);
y= plotData{1,N}.data(:,2);
%if i ==3
% z= plotData{1,N}.data(:,(i+2));
%end% Z(:,N) =plotData{1,N}.data(:,(i+2));
scatter(x,y,pz,plotData{1,N}.data(:,(i+2)),'filled')
legendLabels{N} = ['Y = ', num2str(plotData{N}.y)];
end
%%Interpolation into a gridded data
%F =scatteredInterpolant(x,y,Z);
%[xq,yq]=meshgrid(linspace(20,230,100));
%cq =F(xq,yq);
%h=pcolor(xq,yq,cq)
%legendLabels{N} = ['Y = ', num2str(plotData{N}.y)];
legend(legendLabels);
title(['3D plot of position against ',plotTypes{i}], 'Interpreter', 'none')
xlabel('X(mm)')
ylabel('Y(mm)')
H = colorbar;
ylabel(H, plotTypes{i});
end

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采纳的回答

Akira Agata
Akira Agata 2019-6-18
Seems that scatteredInterpolant function would be better. Here is an example.
% Read data file
T = readtable('data.xlsx');
% Make interpolation function F = f(x,y)
F = scatteredInterpolant(T.xcoordinate,T.ycoordinate,T.mean_velocity);
% Make a grid points (20-by-20, for example)
[xmin,xmax] = bounds(T.xcoordinate);
[ymin,ymax] = bounds(T.ycoordinate);
[xGrid,yGrid] = meshgrid(linspace(xmin,xmax,20),linspace(ymin,ymax,20));
% Calculate interpolated value for each grid point
zGrid = F(xGrid,yGrid);
% Visualize the result
figure
scatter(xGrid(:),yGrid(:),[],zGrid(:),'filled')
colorbar
scatter.png
  1 个评论
Yannick Tabot Njami
Yannick Tabot Njami 2019-6-18
Thank you very much Mr Agata, you solve my problem .i appreciate you !

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更多回答（1 个）

KSSV
KSSV 2019-6-17
Read about interp2, griddata. If not working attach your data.
  1 个评论
Yannick Tabot Njami
Yannick Tabot Njami 2019-6-17
%
Bellow is my entire code And attached you would fine my data as well .plotData{1,4}. has 7 rows due to error that why at the centere of the color plot there is a missing point there . The rest are all 8 rows. just a hint.
%%This Script selects file of of specific format(.txt) and
%% mport them each for data analysis.
%% the Analyzed data are then plotted as per requirement
clear all ;cla;
%% processing the parent folder
myfolder ='C:\Users\TABOT\Desktop\Windkanal_Data\Yannick\Yannick_2019_01_03';
%% checking to snsure that folder actually exist
if~isdir(myfolder)
Error_message =sprintf('Error,Folder not found:\n %s',myfolder);
end
%% getting list of all files with File pattern .txt
filepattern =fullfile(myfolder,'*.txt');
txtfiles=dir(filepattern);
%% sorting out the zero measurement and calculating Time sequence ,samples and mean voltage
zerofile =fullfile(myfolder,'20190301_00_20_20.txt');
offsetdata =importdata(zerofile);
zerovoltage =offsetdata.data(:,2);
mean_Uo =mean(zerovoltage);
%% ignoring the off set file after being used
txtfiles(1)=[];
%% preallocating memeory
mean_pd = zeros(length(txtfiles),1);
mean_velocity =zeros(length(txtfiles),1);
std_pd=zeros(length(txtfiles),1);
std_velocity =zeros(length(txtfiles),1);
velocity =zeros(length(txtfiles),1);
mean_voltage =zeros(length(txtfiles),1);
pd =zeros(length(zerovoltage),1);
Non_Avg_table = zeros(length(zerovoltage),5);
velocities =zeros(length(zerovoltage),1);
all_nonaveragetable(1,64) =struct('table',[],'x_position',[],'y_position',[]);
%% looping over each file in the directory txtfiles
for k =1 : length(txtfiles)
% getting the name of each file base on its x and y coordinates
% and importing the content of the file current file
fn_parts =split(txtfiles(k).name,{'_','.'});
coor_x =str2double(fn_parts{3});
coor_y =str2double(fn_parts{4});
filecontents =importdata(fullfile(txtfiles(k).folder,txtfiles(k).name));
%% referring to voltage and samples of each file consisting of a struture and sample value
voltage =filecontents.data(:,2);
samples =filecontents.data(:,1);
time_sequence =samples/1000;
for ii=1: length(voltage)
%% Looping over the voltage and calculating pd and velocities respectively
pd(ii)=abs( 474.6*(voltage(ii)-mean_Uo));
velocities(ii)=sqrt(2*pd(ii)/1.2);
end
%% calculating the various mean and standard deviation of the respective parameters
mean_pd(k) = mean(pd);
velocity(k) = sqrt(2*mean_pd(k)/1.2);
mean_voltage(k) = mean(voltage);
mean_velocity(k) = mean(velocities);
std_velocity(k) =std(velocities);
std_pd(k)=std(pd);
%% Generating table of non-average values and forming a structure of 1x 64
%% of 3 fields
Non_Avg_table= table(samples,time_sequence,voltage ,velocities,pd);
all_nonaveragetable(k).table= Non_Avg_table;
%%getting the coordinate of each point
all_nonaveragetable(k).x_position=coor_x;
all_nonaveragetable(k).y_position=coor_y;
end
%% Extracting the x and y Coordinate and transposing
xcoordinate =(extractfield(all_nonaveragetable,'x_position'))';
ycoordinate =(extractfield(all_nonaveragetable,'y_position'))';
%% Generating the table of average values
Average_Table = table(xcoordinate,ycoordinate,mean_velocity,std_velocity, mean_pd ,std_pd);
[data,txt] =xlsread('data.xlsx');
idx = struct('x',1, 'y',2, 'mean_velocity', 3, 'std_velocity', 4, 'mean_pd', 5, 'std_pd', 6);
%% Gathering and sorting data
plotTypes = {'mean_velocity','std_velocity','mean_pd', 'std_pd'};
% stepval = 30;
yValues = [20 50 80 110 140 170 200 230];
indextoFind =cell(1,length(yValues));
plotData = cell(1,length(yValues));
for i= 1:length(yValues)
foundIndex = find(data(:, idx.y) == yValues(i));
tempData = sortrows(data(foundIndex,:)); %% Get all data and sort row-wise for each yValues
plotData{i} = struct('y', yValues(i), 'data',tempData) ;%% here store data to be plotted
end
%% Plot Data
k =[1 ,0 ,0 ;0, 1, 0 ;0 ,1 ,.5;.5 .5 .5 ;.1 ,.1, .25; 1 ,1, 0; 0, 0,1;0 ,0.5 ,1];
% figure
for i = 1: length(plotTypes)
figure
plotType = plotTypes{i};
% subplot(1,length(plotTypes), i);
hold all ;
legendLabels = cell(1,length(plotData));
for j = 1:length(plotData)
xPlot= plotData{j}.data(:, idx.x);
yPlot= plotData{j}.data(:, idx.(plotTypes{i}));
plot(xPlot,yPlot, '-o','color',k(j,:));
legendLabels{j} = ['Y = ', num2str(plotData{j}.y)];
end
legend(legendLabels);
title(plotTypes{i}, 'Interpreter', 'none');
xlabel('x position')
ylabel(plotTypes{i}, 'Interpreter', 'none')
end
%% Generating the 3D color plot
% figure
for i = 1: length(plotTypes)
figure
legendLabels = cell(1,length(plotData));
% subplot(1,length(plotTypes), i);
hold all
for N=1:size(plotData,2)
pz =150;
plotData{1,N}.data();
x=plotData{1,N}.data(:,1);
y= plotData{1,N}.data(:,2);
% if i ==3
% z= plotData{1,N}.data(:,(i+2));
%
% end% Z(:,N) =plotData{1,N}.data(:,(i+2));
% %
scatter(x,y,pz,plotData{1,N}.data(:,(i+2)),'filled')
legendLabels{N} = ['Y = ', num2str(plotData{N}.y)];
end
%%Interpolation into a gridded data
% F =scatteredInterpolant(x,y,Z);
%
% [xq,yq]=meshgrid(linspace(20,230,100));
% cq =F(xq,yq);
% % h=pcolor(xq,yq,cq)
%
% legendLabels{N} = ['Y = ', num2str(plotData{N}.y)];
legend(legendLabels);
title(['3D plot of position against ',plotTypes{i}], 'Interpreter', 'none')
xlabel('X(mm)')
ylabel('Y(mm)')
H = colorbar;
ylabel(H, plotTypes{i});
end

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