在具有相同值

时间:2017-08-30 16:54:51

标签: matlab plot grouping visualization matlab-figure

考虑以下7x5矩阵的可视化,该矩阵由3个不同的区域/值组成:

bL = toeplitz( [zeros(1,5) -2*ones(1,2)], [0 -ones(1,4)] ); 
hF = figure(); hA = axes(hF);    
imagesc(hA,bL); axis(hA,'image'); set(hA,'XTick',[],'YTick',[]);
N = 4; cmap = parula(N); colormap(cmap(1:end-1,:));

Unselected

现在让我们说我"选择"每列中有0个或更多像素,以便:

  • 只能在绿色区域中选择所选像素。
  • 所选像素始终是连续的。
  • 通过指定一个恒定的新值来执行选择,该值与3个初始区域不同。

几个选择示例(使用值1):

%Example 1:
cSF = toeplitz([ones(1,1) zeros(1,4) -2*ones(1,2)],[1 -ones(1,4)]);
%Example 2:
oSF = toeplitz( [zeros(1,5) -2*ones(1,2)], [0 -ones(1,4)] );
oSF(end-2:end,find(any(oSF==-2,1),1,'last')+1:end) = 1; 
%Example 3:
iSF = toeplitz([ones(1,3) zeros(1,2) -2*ones(1,2)],[1 -ones(1,4)]);
% Plot:
hF = figure();
hP(1) = subplot(1,3,1); imagesc(cSF);
hP(2) = subplot(1,3,2); imagesc(oSF);
hP(3) = subplot(1,3,3); imagesc(iSF);
axis(hP,'image'); set(hP,'XTick',[],'YTick',[]);

Possible selections

我的目标是绘制一组包含"选择"的矩形。 (黄色)属于同一列的像素。对于上面的示例,结果应该如下(分别):

Desired result

我看到它的方式,因为代码是通用的,它应该接受:(1)一个轴处理应该绘制imagesc的位置; (2)一个data数组; (3)在data数组中找到的值,代表"选择"像素;以及可选的封闭像素的颜色。

我找到了一些使用patchrectangle执行此操作的方法(请参阅own answer),但我想知道这是否可以通过更少的函数调用或其他函数来实现我没有想过的方法。

2 个答案:

答案 0 :(得分:4)

使用patch的无环路解决方案:

这是一个为patch生成坐标而无需循环的解决方案:

function column_highlight(hA, data, selectionVal)

  assert(nargin >= 2);
  if (nargin < 3) || isempty(selectionVal)
    selectionVal = 1;
  end

  nCol = size(data, 2);
  data = diff([false(1, nCol); (data == selectionVal); false(1, nCol)]);
  [r, c] = find(data);
  r = reshape(r-0.5, 2, []);
  c = c(1:2:end);
  X = [c-0.5 c+0.5 c+0.5 c-0.5].';
  Y = r([1 1 2 2], :);
  patch(hA, 'XData', X, 'YData', Y, 'FaceColor', 'none');

end


使用regionprops的解决方案:

如果您拥有Image Processing Toolbox,则可以通过标记每个蒙版列部分并使用'BoundingBox'获取regionprops形状度量来解决此问题:

function column_highlight(hA, data, selectionVal)

  assert(nargin >= 2);
  if (nargin < 3) || isempty(selectionVal)
    selectionVal = 1;
  end

  labelMat = bsxfun(@times, (data == selectionVal), 1:size(data, 2));
  coords = regionprops(labelMat, 'BoundingBox');
  coords = vertcat(coords.BoundingBox);
  coords(:, 3:4) = coords(:, 1:2)+coords(:, 3:4);
  X = coords(:, [1 3 3 1]).';
  Y = coords(:, [4 4 2 2]).';
  patch(hA, 'XData', X, 'YData', Y, 'FaceColor', 'none');

end

答案 1 :(得分:3)

使用rectangle的解决方案:

function markStreaksRect(hA, data, selectionVal)
% Check inputs:
assert(nargin >= 2); if nargin < 3 || isempty(selectionVal), selectionVal = 1; end
% Create a mask for "selected" values:
oneMask = data == selectionVal;
% Find the first encountered "selected" element from both the top and the bottom:
[~,I1] = max(oneMask,[],1); [~,I2] = max(flipud(oneMask),[],1);
% Express the "selected" extent as a 2 row vector:
firstLast = [I1; size(oneMask,1)-I2+1].*any(oneMask,1);
% For nonzero extents, plot shifted rectangles:
for ind1 = find(all(firstLast,1))  
  rectangle(hA,'Position',[ind1-0.5, firstLast(1,ind1)-0.5, 1, diff(firstLast(:,ind1))+1 ]);
end

使用patch的解决方案:

function markStreaksPatch(hA, data, selectionVal)
% Check inputs:
assert(nargin >= 2); if nargin < 3 || isempty(selectionVal), selectionVal = 1; end
% Create a mask for "selected" values:
oneMask = data == selectionVal;
% Find the first encountered "selected" element from both the top and the bottom:
[~,I1] = max(oneMask,[],1); [~,I2] = max(flipud(oneMask),[],1);
% Express the "selected" extent as a 2 row vector:
firstLast = [I1; size(oneMask,1)-I2+1].*any(oneMask,1);
% For nonzero extents, plot shifted patches:
for ind1 = find(all(firstLast,1))  
  [XX,YY] = meshgrid(ind1-0.5 + [0 1], firstLast(1,ind1)-0.5+[0 diff(firstLast(:,ind1))+1]);
  patch(hA, XX(:), [YY(1:2) YY(4:-1:3)], 'y', 'FaceAlpha', 0);
end

上述解决方案可以使用以下方法进行测试:

function q45965920
iSF = toeplitz([ones(1,3) zeros(1,2) -2*ones(1,2)],[1 -ones(1,4)]);
hF = figure(); hA = axes(hF); imagesc(hA,iSF); 
axis(hA,'image'); set(hA,'XTick',[],'YTick',[]);

...然后运行markStreaksRect(hA, iSF, 1);markStreaksPatch(hA, iSF, 1);会产生所需的结果。