I draw a correlation plot from iris data for explanation.
p <- iris %>%
dplyr::select(Sepal.Length, Petal.Length, Species) %>%
ggpairs(mapping = aes(color = Species),
lower = list(continuous = "smooth"),
diag = list(continuous = wrap("densityDiag", alpha = 0.5))
) +
theme_classic()
p
I have two questions.
See the following figure. The y-axis surrounded by the red rectangle is the axis for the density plot. That scale does not work for the right bar plot. Then, I want the axis for the bar plot around either of blue rectangles. Is it possible?
click for my image
Is it possible that the size of each row/column is changed specifically? The following image shows an example of change of the width of the 3rd column.
click for my image
Thank you very much.
im trying to understand what tools i need to use as im new to d3 and didnt find any thing related...
i need a area chart that is like bars but can float and be on multiple values both on the x and y axis.
in this example the values are days but it might be hours/months etc...
need to know the direction i need to go.. / the right term to search...
There's no significant difference between drawing this chart and a normal bar chart.
And you need to define some scales that will map the values in your data to co-ordinates on your chart.
You need to draw some rect shapes.
So, in the above example you would define a time scale that, given an input date, will map that to a certain x co-ordinate on your chart. You can then use that to determine both the x co-ordinate for where the left-hand-side of a rectangle will be, and to work out how wide the rectangle needs to be.
const xScale = d3.scaleTime()
.domain([d3.min(dateValuesInMyDataset, d => d.date), d3.max(dateValuesInMyDataset, d => d.date)])
.range([0, widthOfMyChart]);
The above xScale if given the earliest date in your dataset would return the value 0, because this is the x co-ordinate representing that date.
Similarly, you would want to construct a linear scale which defines how to map the numerical range of values in your dataset, to the y co-ordinates in your chart. Then you can use the scale to determine the y value and height of all of the rectangles in your chart.
There are lots of good examples of this on ObservableHQ.com that you can browse and see the code for.
I have data that is only accessible as a 2D point plot saved as pdf-file and need the raw data (the x and associated y values) out of it.
Is there any way I can do this with Mathematica, so that I am able to use the data internally for evaluation?
An example plot to Import would be (ListPlot of x^2; x=0-10)
Here is an approach you could take with Mathematica
img = First#Import[
"https://drive.google.com/uc?export=download&id=1Kgny29eM8q2oIj7BopP-dx0HQ4E449P_"];
mb = MorphologicalBinarize[img];
cn = ColorNegate[Closing[mb, DiskMatrix[0.5]]];
coords = Flatten[Last /# ComponentMeasurements[cn, {"Centroid"}], 1];
ListPlot[coords]
You will have to appropriately scale the coordinates if you want them to exactly match y = x^2.
I am trying to feature extraction from an image for some certain points. First time I am using HogFeatureextraction. When I plot the features and valid points, I am getting result not on the certain points. I will use these features for training later on. For example, I have points on the straight line. Should not my features on where my certain points on the line. I am a little bit confused about concept of it. I used [features,validPoints] = extractHOGFeatures(I,points). x and y are my 10 positions in the image. In this case how is feature extraction working?
[features,validPoints] = extractHOGFeatures(I,[x,y]);
figure;
imshow(I);
hold on;
plot(features, 'ro');
plot(validPoints,'go');
Thank you
The function's documentation explains it all clearly.
validPoints is a nX2 matrix of xy coordinates so you should use plot(x,y) instead of plot(x) to plot it.
features is a matrix of the HoG features of each point, and simply plot it using plot(features, 'ro') will not produce any reasonable output.
However, you can simply obtain the third output (visualization) from extractHOGFeatures and then use plot to plot it:
I = im2double(imread('cameraman.tif'));
% desired points
n = 20;
x = randi(size(I,2), [n 1]);
y = randi(size(I,1), [n 1]);
% extract features + visualization object
[features,validPoints,visualization] = extractHOGFeatures(I,[x,y]);
% show image and features
figure;
imshow(I);
hold on;
plot(visualization,'Color','r');
% plot valid points
plot(validPoints(:,1),validPoints(:,2),'go');
I have an image in MATLAB:
im = rgb2gray(imread('some_image.jpg');
% normalize the image to be between 0 and 1
im = im/max(max(im));
And I've done some processing that resulted in a number of points that I want to highlight:
points = some_processing(im);
Where points is a matrix the same size as im with ones in the interesting points.
Now I want to draw a circle on the image in all the places where points is 1.
Is there any function in MATLAB that does this? The best I can come up with is:
[x_p, y_p] = find (points);
[x, y] = meshgrid(1:size(im,1), 1:size(im,2))
r = 5;
circles = zeros(size(im));
for k = 1:length(x_p)
circles = circles + (floor((x - x_p(k)).^2 + (y - y_p(k)).^2) == r);
end
% normalize circles
circles = circles/max(max(circles));
output = im + circles;
imshow(output)
This seems more than somewhat inelegant. Is there a way to draw circles similar to the line function?
You could use the normal PLOT command with a circular marker point:
[x_p,y_p] = find(points);
imshow(im); %# Display your image
hold on; %# Add subsequent plots to the image
plot(y_p,x_p,'o'); %# NOTE: x_p and y_p are switched (see note below)!
hold off; %# Any subsequent plotting will overwrite the image!
You can also adjust these other properties of the plot marker: MarkerEdgeColor, MarkerFaceColor, MarkerSize.
If you then want to save the new image with the markers plotted on it, you can look at this answer I gave to a question about maintaining image dimensions when saving images from figures.
NOTE: When plotting image data with IMSHOW (or IMAGE, etc.), the normal interpretation of rows and columns essentially becomes flipped. Normally the first dimension of data (i.e. rows) is thought of as the data that would lie on the x-axis, and is probably why you use x_p as the first set of values returned by the FIND function. However, IMSHOW displays the first dimension of the image data along the y-axis, so the first value returned by FIND ends up being the y-coordinate value in this case.
This file by Zhenhai Wang from Matlab Central's File Exchange does the trick.
%----------------------------------------------------------------
% H=CIRCLE(CENTER,RADIUS,NOP,STYLE)
% This routine draws a circle with center defined as
% a vector CENTER, radius as a scaler RADIS. NOP is
% the number of points on the circle. As to STYLE,
% use it the same way as you use the rountine PLOT.
% Since the handle of the object is returned, you
% use routine SET to get the best result.
%
% Usage Examples,
%
% circle([1,3],3,1000,':');
% circle([2,4],2,1000,'--');
%
% Zhenhai Wang <zhenhai#ieee.org>
% Version 1.00
% December, 2002
%----------------------------------------------------------------
Funny! There are 6 answers here, none give the obvious solution: the rectangle function.
From the documentation:
Draw a circle by setting the Curvature property to [1 1]. Draw the circle so that it fills the rectangular area between the points (2,4) and (4,6). The Position property defines the smallest rectangle that contains the circle.
pos = [2 4 2 2];
rectangle('Position',pos,'Curvature',[1 1])
axis equal
So in your case:
imshow(im)
hold on
[y, x] = find(points);
for ii=1:length(x)
pos = [x(ii),y(ii)];
pos = [pos-0.5,1,1];
rectangle('position',pos,'curvature',[1 1])
end
As opposed to the accepted answer, these circles will scale with the image, you can zoom in an they will always mark the whole pixel.
Hmm I had to re-switch them in this call:
k = convhull(x,y);
figure;
imshow(image); %# Display your image
hold on; %# Add subsequent plots to the image
plot(x,y,'o'); %# NOTE: x_p and y_p are switched (see note below)!
hold off; %# Any subsequent plotting will overwrite the image!
In reply to the comments:
x and y are created using the following code:
temp_hull = stats_single_object(k).ConvexHull;
for k2 = 1:length(temp_hull)
i = i+1;
[x(i,1)] = temp_hull(k2,1);
[y(i,1)] = temp_hull(k2,2);
end;
it might be that the ConvexHull is the other way around and therefore the plot is different. Or that I made a mistake and it should be
[x(i,1)] = temp_hull(k2,2);
[y(i,1)] = temp_hull(k2,1);
However the documentation is not clear about which colum = x OR y:
Quote: "Each row of the matrix contains the x- and y-coordinates of one vertex of the polygon. "
I read this as x is the first column and y is the second colum.
In newer versions of MATLAB (I have 2013b) the Computer Vision System Toolbox contains the vision.ShapeInserter System object which can be used to draw shapes on images. Here is an example of drawing yellow circles from the documentation:
yellow = uint8([255 255 0]); %// [R G B]; class of yellow must match class of I
shapeInserter = vision.ShapeInserter('Shape','Circles','BorderColor','Custom','CustomBorderColor',yellow);
I = imread('cameraman.tif');
circles = int32([30 30 20; 80 80 25]); %// [x1 y1 radius1;x2 y2 radius2]
RGB = repmat(I,[1,1,3]); %// convert I to an RGB image
J = step(shapeInserter, RGB, circles);
imshow(J);
With MATLAB and Image Processing Toolbox R2012a or newer, you can use the viscircles function to easily overlay circles over an image. Here is an example:
% Plot 5 circles at random locations
X = rand(5,1);
Y = rand(5,1);
% Keep the radius 0.1 for all of them
R = 0.1*ones(5,1);
% Make them blue
viscircles([X,Y],R,'EdgeColor','b');
Also, check out the imfindcircles function which implements the Hough circular transform. The online documentation for both functions (links above) have examples that show how to find circles in an image and how to display the detected circles over the image.
For example:
% Read the image into the workspace and display it.
A = imread('coins.png');
imshow(A)
% Find all the circles with radius r such that 15 ≤ r ≤ 30.
[centers, radii, metric] = imfindcircles(A,[15 30]);
% Retain the five strongest circles according to the metric values.
centersStrong5 = centers(1:5,:);
radiiStrong5 = radii(1:5);
metricStrong5 = metric(1:5);
% Draw the five strongest circle perimeters.
viscircles(centersStrong5, radiiStrong5,'EdgeColor','b');
Here's the method I think you need:
[x_p, y_p] = find (points);
% convert the subscripts to indicies, but transposed into a row vector
a = sub2ind(size(im), x_p, y_p)';
% assign all the values in the image that correspond to the points to a value of zero
im([a]) = 0;
% show the new image
imshow(im)