given an array of points my program should in theory, Find the two furthest points from each other. Then calculate the angle that those two points make with the x axis. Then in rotate all the points in the array around the averaged center of all the points by that angle. For some reason my translation function to rotate all the points around the center is not working it is giving me unexpected values. I am fairly sure the math I am using to do this is accurate since I tested the formula I am using using wolfram alpha and plotted the points on desmos. I am not sure what's wrong with my code because it keeps giving me unexpected output. Any help would greatly be appreciated.
This is the code to translate the array:
def translation(array,centerArray):
array1=array
maxDistance=0
point1=[]
point2=[]
global angle
for i in range(len(array1)):
for idx in range(len(array1)):
if(maxDistance<math.sqrt(((array1[i][0]-array1[idx][0])**2)+((array1[i][1]-array1[idx][1])**2)+((array1[i][2]-array1[idx][2])**2))):
maxDistance=math.sqrt(((array1[i][0]-array1[idx][0])**2)+((array1[i][1]-array1[idx][1])**2)+((array1[i][2]-array1[idx][2])**2))
point1 = array1[i]
point2 = array1[idx]
angle=math.atan2(point1[1]-point2[1],point1[0]-point2[0]) #gets the angle between two furthest points and xaxis
for i in range(len(array1)): #this is the problem here
array1[i][0]=((array[i][0]-centerArray[0])*math.cos(angle)-(array[i][1]-centerArray[1])*math.sin(angle))+centerArray[0] #rotate x cordiate around center of all points
array1[i][1]=((array[i][1]-centerArray[1])*math.cos(angle)+(array[i][0]-centerArray[0])*math.sin(angle))+centerArray[1] #rotate y cordiate around center of all points
return array1
This is the code I am using to test it. tortose is what I set turtle graphics name as
tortose.color("violet")
testarray=[[200,400,9],[200,-100,9]] #array of 2 3d points but don't worry about z axis it will not be used for in function translation
print("testsarray",testarray)
for i in range(len(testarray)): #graph points in testarray
tortose.setposition(testarray[i][0],testarray[i][1])
tortose.dot()
testcenter=findCenter(testarray) # array of 1 point in the center of all the points format center=[x,y,z] but again don't worry about z
print("center",testcenter)
translatedTest=translation(testarray,testcenter) # array of points after they have been translated same format and size of testarray
print("translatedarray",translatedTest) #should give the output [[-50,150,9]] as first point but instead give output of [-50,-99.999999997,9] not sure why
tortose.color("green")
for i in range(len(testarray)): #graphs rotated points
tortose.setposition(translatedTest[i][0],translatedTest[i][1])
tortose.dot()
print(angle*180/3.14) #checks to make sure angle is 90 degrees because it should be in this case this is working fine
tortose.color("red")
tortose.setposition(testcenter[0],testcenter[1])
tortose.dot()
find center code finds the center of all points in array don't worry about z axis since it is not used in translation:
def findCenter(array):
sumX = 0
sumY = 0
sumZ = 0
for i in range(len(array)):
sumX += array[i][0]
sumY += array[i][1]
sumZ += array[i][2]
centerX= sumX/len(array)
centerY= sumY/len(array)
centerZ= sumZ/len(array)
#print(centerX)
#print(centerY)
#print(centerZ)
centerArray=[centerX,centerY,centerZ]
return centerArray
import math
import turtle
tortose = turtle.Turtle()
tortose.penup()
my expected output should be a point at (-50,150) but it is giving me a point at (-50,-99.99999999999997)
This is a common mistake when doing in-place rotations:
array1[i][0]= ...
array1[i][1]= ... array[i][0] ...
First you update array1[i][0]. Then you update array1[i][1], but you use the new value when you should use the old value. Instead, temporarily store the old value:
x = array1[i][0]
array1[i][0]=((array[i][0]-centerArray[0])*math.cos(angle)-(array[i][1]-centerArray[1])*math.sin(angle))+centerArray[0] #rotate x cordiate around center of all points
array1[i][1]=((array[i][1]-centerArray[1])*math.cos(angle)+(x-centerArray[0])*math.sin(angle))+centerArray[1] #rotate y cordiate around center of all points
I am trying to use vtkImageReSlicer to extract a 2d slice from a 3d
vtkImageData object. But I can't seem to get the recipe right. Am I doing it right?
I am also a bit confused about ResliceAxes Matrix. Does it represent a cutting plane? If
I move the ReSliceAxes origin will it also move the cutting plane? When I
call Update on the vtkImageReSlicer, the program crashes. But when I don't
call it, the output is empty.
Here's what I have so far.
#my input is any vtkactor that contains a closed curve of type vtkPolyData
ShapePolyData = actor.GetMapper().GetInput()
boundingBox = ShapePolyData.GetBounds()
for i in range(0,6,2):
delta = boundingBox[i+1]-boundingBox[i]
newBoundingBox.append(boundingBox[i]-0.5*delta)
newBoundingBox.append(boundingBox[i+1]+0.5*delta)
voxelizer = vtk.vtkVoxelModeller()
voxelizer.SetInputData(ShapePolyData)
voxelizer.SetModelBounds(newBoundingBox)
voxelizer.SetScalarTypeToBit()
voxelizer.SetForegroundValue(1)
voxelizer.SetBackgroundValue(0)
voxelizer.Update()
VoxelModel =voxelizer.GetOutput()
ImageOrigin = VoxelModel.GetOrigin()
slicer = vtk.vtkImageReslice()
#Am I setting the cutting axis here. x axis set at 1,0,0 , y axis at 0,1,0 and z axis at 0,0,1
slicer.SetResliceAxesDirectionCosines(1,0,0,0,1,0,0,0,1)
#if I increase the z value, will the cutting plane move up?
slicer.SetResliceAxesOrigin(ImageOrigin[0],ImageOrigin[1],ImageOrigin[2])
slicer.SetInputData(VoxelModel)
slicer.SetInterpolationModeToLinear()
slicer.SetOutputDimensionality(2)
slicer.Update() #this makes the code crash
voxelSurface = vtk.vtkContourFilter()
voxelSurface.SetInputConnection(slicer.GetOutputPort())
voxelSurface.SetValue(0, .999)
voxelMapper = vtk.vtkPolyDataMapper()
voxelMapper.SetInputConnection(voxelSurface.GetOutputPort())
voxelActor = vtk.vtkActor()
voxelActor.SetMapper(voxelMapper)
Renderer.AddActor(voxelActor)
I have never used vtkImageReslice, but I have used vtkExtractVOI for vtkImageData, which allows you to achieve a similar result, I think. Here is your example modified with the latter, instead:
ImageOrigin = VoxelModel.GetOrigin()
slicer = vtk.vtkExtractVOI()
slicer.SetInputData(VoxelModel)
#With the setVOI method you can define which slice you want to extract
slicer.SetVOI(xmin, xmax, ymin, ymax, zslice, zslice)
slicer.SetSampleRate(1, 1, 1)
slicer.Update()
voxelSurface = vtk.vtkContourFilter()
voxelSurface.SetInputConnection(slicer.GetOutputPort())
voxelSurface.SetValue(0, .999)
voxelMapper = vtk.vtkPolyDataMapper()
voxelMapper.SetInputConnection(voxelSurface.GetOutputPort())
voxelActor = vtk.vtkActor()
voxelActor.SetMapper(voxelMapper)
Renderer.AddActor(voxelActor)
With xticks automatically generated by gnuplot we find too often that the labels are too tight / cramped together as shown in this snapshot.
How can we fix this issue?
This is a very crude workaround. The idea is telling how many (approximate) number of tick labels one wants, and have gnuplot "translate" that into a suitable tick spacing according to the whole plotting range.
I am posting what I am using now, and it works reasonably well.
It takes xmin=0.
You could guess the way it works and tune it.
# Get/print stats about input data, ...
stats "output.csv" using 2:5 nooutput
# ... and use them for setting the number of tick labels for x axes, to avoid overlap
#tmin = STATS_min_x
tmin = 0
tmax = STATS_max_x
nxtics = 5 # Tune this
# Do not count 0 as a tick
nxtics = nxtics - 1
# Shift numbers to the range [1,10)
ttic1 = tmax / nxtics
nshift_digits = -floor(log10(ttic1))
shift = 10.0**nshift_digits
tmax_shift = tmax * shift
ttic1_shift = ttic1 * shift
# ttic1_shift should be between [1,10)
# Use (arbitrary) specified tick spacing (here at 1, 2, 5 in the first significant digit, but one could use others, including 2.5, e.g.), which better matches the data range and selected number of tick labels. Note that the number of tick labels would not be strictly maintained.
# Tune these numbers
ttic_shift = 1.0
if (ttic1_shift < 1.3) {
ttic_shift = 1.0
} else { if (ttic1_shift < 3.0) {
ttic_shift = 2.0
} else { if (ttic1_shift < 7.0) {
ttic_shift = 5.0
} else {
ttic_shift = 10.0
} } }
ttic = ttic_shift / shift
print "ttic=", ttic
PS: I could not have this working, although I did not try "hard". I guess that solution might work for a single plotted dataset, but not sure it would work for more than one.
If they aren't too cramped, you can rotate them 90 degrees i.e.
set xtics rotate by 90
This is quite a tough challenge I have with my code. First of all the code I am putting here is not runnable because I am using an Excel sheet (but I am happy to email it if people want to try using my code).
What I have is an Excel sheet with data on cross-sectional fibres in a microscopic image I took. The information is basically: location of the section, area, angle of rotation.
From that I calculate the angle of orientation Phi, and Gamma. After that I use the scatter function to plot a dot of different colors for each Phi angle value. I use a constant color for a range of 10 degrees. Which gives me a picture like this:
Now my aim to is calculate the area of each homogeneous region. So I look for a way to plot let's say all the dots within the -10 +10 region (I'm doing 20 degrees for now, but will do 10 after). I used a look and I get a picture like this:
The white corresponds where the dots are within the range I selected. After that I use the toolbox in MATLAB to convert each dot into a pixel. So I'll get a black background with loads of white pixels, then I use imdilate to make circles, fill holes and isolate each region with a specific color. Finally I use the functions boundary and patch, to create each boundary and fill them with a color. And I get a picture like this:
Which is what I want and I can get the area of each region and the total area (I used a threshold to discard the small areas). Then I run the code several time for each region, and I use imfuse to put them back together and see what it looks like.
THE PROBLEM is, they overlap quite a lot, and that is because there are some errors in my data, and therefore some blue dots will be in the red and so on.
So I want to run the code once, then when I rerun it with another range, it does the same thing but doesn't take into account value when there's already something plotted before.
I tried to do that by, after running once, saving the matrix bw4 and adding a condition when plotting the black and white pic, by saying if Phi is in my range AND there no white here then you can put white, otherwise it's black. But it doesn't seem to work.
I understand this is quite a complicated thing to explain, but I would appreciate any ideas, and open to chat via email or otherwise. I am putting the full code now, and I can send you my Excel sheet if you want to run it on your computer and see for yourself.
clearvars -except data colheaders bw4
close all
clc
%%
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%%% CHANGE DATA FOR EACH SAMPLE %%%
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
cd 'C:\Users\dkarta\Desktop\Sample 12\12.6'
data=xlsread('Sample12_6res.xlsx');
cd 'C:\Users\dkarta\Documents\MATLAB'
%data=Sample121res; % Data name
imax=length(data); % Numbers of rows in data sheet
y=11900; % Number of pixels in the y on image j
%%
data(:,15)=data(:,9)*pi/180; % Convers Column 9 (angle of rotation) in rads
data(:,16)=y-data(:,6); % Reset the Y coordinate axis to bottom left
delta = 0 : 0.01 : 2*pi; % Angle in paramteric equations
theta=45*pi/180; % Sample cutting angle in rads
%AA=[data(:,5)' data(:,16)' phi']
% Define colors
beta=acos(data(1:imax,8)./data(1:imax,7));%./acos(0);
phi=atan(sin(beta).*cos(data(1:imax,15))./(sin(theta)*sin(beta).*sin(data(1:imax,15))+cos(theta)*cos(beta)))/(pi/2);
phi2=phi/2+1/2; % Scales in plane angle phi between 0 and 1
gamma=atan((cos(theta)*sin(beta).*sin(data(1:imax,15))-sin(theta)*cos(beta))./...
(sin(theta)*sin(beta).*sin(data(1:imax,15))+cos(theta)*cos(beta)))/(pi/2);
gamma2=gamma+1/2; % Scales out of plane angle gamma between 0 and 1
%%
%%%%%%%%%%%%%%%%%%%%%%%%%%%
%%% MESHGRID AND COLOURMAP %%%
%%%%%%%%%%%%%%%%%%%%%%%%%%%
x1=data(1:imax,5);
y1=data(1:imax,16);
z1=phi*90;
z2=gamma*90;
n=300;
%Create regular grid across data space
[X,Y] = meshgrid(linspace(min(x1),max(x1),n), linspace(min(y1),max(y1),n));
% Creating a colormap with 10 degree constant colors
map4=[0 0 1;0 1/3 1;0 2/3 1; 0 1 1;0 1 2/3;0 1 1/3;0 1 0;1/3 1 0;2/3 1 0;1 1 0;1 0.75 0;1 0.5 0;1 0.25 0;1 0 0;0.75 0 0.25;0.5 0 0.5;0.25 0 0.75; 0 0 1];
Colormap4=colormap(map4);
h=colorbar;
caxis([-90 90])
set(h, 'YTick', [-90:10:90])
%%
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%%% PLOT USING SCATTER - ISOLATE SOME REGIONS %%%
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
a=-10; % Lower boundary for angle interval
b=10; % Upper boundary for angle interval
c=z1>a & z1 < b;
c=c.*1;
%j=1;
y1=(y1-min(y1)+1);
y2=max(y1)-y1+1;
[X1,Y1]=meshgrid(1:500,1:500);
griddata(x1,y2,c,X1,Y1);
clear c1
for i=1:imax
if z1(i)< b && z1(i)> a %&& bw4(round(y1(i)),round(x1(i))) == 0
c(i) = 1;
c1(round(y2(i)),round(x1(i)))=1;
else
c(i)= 0;
c1(round(y2(i)),round(x1(i)))=0;
end
end
C=[c c c];
%c(find(c==0)) = NaN;
%contourf(X,Y,griddata(x1,y1,c,X,Y),100,'EdgeColor', 'None')
figure(1), scatter(x1,y1,3,z1,'filled');
axis equal
axis ([0 8000 0 12000])
axis off
figure(2), scatter(x1,y1,3,C,'filled');
axis equal
axis ([0 8000 0 12000])
axis off
se=strel('disk',50,8);
bw2=imdilate(c1,se);
bw4=bwlabel(bw2);
bw3=imfill(bw4,'holes');
max(bw4(:));
figure(3),imshow(c1,'InitialMagnification', 10);
figure(4), imshow(bw2,'InitialMagnification', 10);
figure(5), imshow(bw3,'InitialMagnification', 10);
figure(6),imshow(label2rgb(bw4),'InitialMagnification', 10);
k=ones(max(bw4(:)),1);
clear bw5
for i=1:length(x1)
if bw3(round(y2(i)),round(x1(i))) ~= 0
m=bw3(round(y2(i)),round(x1(i)));
bw5{m}(k(m),1)=x1(i); bw5{m}(k(m),2)=y2(i);
k(m)=k(m)+1;
end
end
figure(7), imshow(~c1,'InitialMagnification', 10);
hold on
for i=1:max(bw4(:))
%scatter(bw5{i}(:,1),bw5{i}(:,2))
j = boundary(bw5{i}(:,1),bw5{i}(:,2),0.5);
%poly=convhull(bw5{i}(:,1),bw5{i}(:,2));
%plot(bw5{i}(poly,1),bw5{i}(poly,2)), title('convhull')
if polyarea(bw5{i}(j,1),bw5{i}(j,2))> 10^5;
patch(bw5{i}(j,1),bw5{i}(j,2),'r'), title('boundary')
indexminy(i)=find(min(bw5{i}(:,2)) == bw5{i}(:,2));
indexminx(i)=find(min(bw5{i}(:,1)) == bw5{i}(:,1));
indexmaxy(i)=find(max(bw5{i}(:,2)) == bw5{i}(:,2));
indexmaxx(i)=find(max(bw5{i}(:,1)) == bw5{i}(:,1));
%xmin = bw5{i}(indexminx); xmax = bw5{i}(indexmaxx);
%ymin = bw5{i}(indexminy); ymax = bw5{i}(indexmaxy);
str=[(indexminx(i)+indexmaxx(i))/2,(indexminy(i)+indexmaxy(i))/2,'Region no.',num2str(i)];
text((min(x1(i))+max(x1(i)))/2,(min(y1(i))+max(y1(i)))/2,str)
polya(i)=polyarea(bw5{i}(j,1),bw5{i}(j,2));
end
end
spolya=sum(polya(:))
print -dpng -r500 B
Just to show you more pictures of when I fuse several of them:
And when I fuse:
As you can see they overlap, which I don't want, so I want each image that I create to 'know' what I'm doing on the previous runs so that it doesn't overlap. I want to get the percentage area of each region and if they overlap I cannot use the actual total area of my sample and the results are wrong.
I dont have my matlab working but here is what you need to do.
For the first run make an array of zeros equal to your image size
already_taken = zeros(size(bw3));
Then on each run, you can fill up the regions taken by this iteration. So at the end of your code, where you save the output to a png, read it back into something like
this_png = rgb2gray(imread(current_png_path))>threshold;
Convert this into a logical array by doing some thresholding and add these values into already taken. So at the end of the code, do a
already_taken = already_taken | this_png; % You might need to check if you need a single | or a double ||
So now you have an image of already taken pixels, ill bake sure I don't allow bw2 to take these values at first place
bw2(already_taken) = 0;
And at the end of the code when I want to write my png, my smart boundary creation might again have entered into already_taken area so there again I'll have to put some check. As far as I understand, this boundary is being created based upon your bw5. So where ever you fill this matrix, try putting a similar check as I did above for bw2.
I hope this helps.
I am trying to get a y-tick at "zero" for a multi-series d3 plot. My x-axis is a time scale and y-axis is some random data-scale. Here is my plunkr
http://plnkr.co/edit/emOKcxrHP7gU1U1l0Mff?p=preview
If I just add zero to the y-tick values, it does not work (i.e. in the following function if I say var yTickValues=[0] ) and it messes up my plot (draws another x-axis below the existing one)
function getYTickValues(){
var deltaY = Math.round((maxY - minY)/(yTickCount-1));
var yTickValues = [];
for(var i=0;i<yTickCount;i++){
yTickValues.push(((minY + i * deltaY) * 100) / 100);
};
return yTickValues;
}
I am unable to figure out how to fix this so I can always get a y-tick at zero. I would like to not touch my minX, maxX, minY and maxY because the domain range scale will change for the sake of accommodating the zero y-tick.
Any help is appreciated.
Change the y domain to start at 0:
y.domain([0, maxY]);
and then also including 0 in the yTickValues array as you suggest above:
var yTickValues = [0];
The data values still remain between minY and maxY, but the y-axis runs to 0. I think that's what the question was getting at?
I also made a couple of changes to the getYTickValues() function to evenly space the rest of the y tick values. See http://plnkr.co/edit/q6XnujIyB8JdzN8AA88j?p=preview