Skip to content
Snippets Groups Projects
Commit df8b8c13 authored by Eric Wait's avatar Eric Wait
Browse files

Forgot to check-in Matlab files after building

parent 90f66229
No related branches found
No related tags found
No related merge requests found
function valueOut = Sum(arrayIn,device,suppressWarning)
if (~exist('suppressWarning','var') || isempty(suppressWarning) || ~suppressWarning)
warning('Falling back to matlab.');
end
valueOut = sum(arrayIn(:));
end
......@@ -15,9 +15,12 @@ methods (Static)
arrayOut = MeanFilter(arrayIn,kernel,numIterations,device)
arrayOut = MedianFilter(arrayIn,kernel,numIterations,device)
arrayOut = MinFilter(arrayIn,kernel,numIterations,device)
[minOut,maxOut] = MinMax(arrayIn,device)
arrayOut = MultiplySum(arrayIn,kernel,numIterations,device)
arrayOut = Opener(arrayIn,kernel,numIterations,device)
arrayOut = StdFilter(arrayIn,kernel,numIterations,device)
valueOut = Sum(arrayIn,device)
arrayOut = WienerFilter(arrayIn,kernel,noiseVariance,device)
shapeElement = ImProc.MakeBallMask(radius)
end
methods (Static, Access = private)
......
% Sum - This sums up the entire array in.
% valueOut = ImProc.Cuda.Sum(arrayIn,[device])
% imageIn = This is a one to five dimensional array. The first three dimensions are treated as spatial.
% The spatial dimensions will have the kernel applied. The last two dimensions will determine
% how to stride or jump to the next spatial block.
%
% device (optional) = Use this if you have multiple devices and want to select one explicitly.
% Setting this to [] allows the algorithm to either pick the best device and/or will try to split
% the data across multiple devices.
%
% valueOut = This is the summation of the entire array.
function valueOut = Sum(arrayIn,device)
[valueOut] = ImProc.Cuda.Mex('Sum',arrayIn,device);
end
% MinMax - This returns the global min and max values.
% [minOut,maxOut] = ImProc.MinMax(arrayIn,[device])
% imageIn = This is a one to five dimensional array. The first three dimensions are treated as spatial.
% The spatial dimensions will have the kernel applied. The last two dimensions will determine
% how to stride or jump to the next spatial block.
%
% device (optional) = Use this if you have multiple devices and want to select one explicitly.
% Setting this to [] allows the algorithm to either pick the best device and/or will try to split
% the data across multiple devices.
%
% minOut = This is the minimum value found in the input.
% maxOut = This is the maximum value found in the input.
function [minOut,maxOut] = MinMax(arrayIn,device)
try
[minOut,maxOut] = ImProc.Cuda.MinMax(arrayIn,device);
catch errMsg
warning(errMsg.message);
[minOut,maxOut] = ImProc.Local.MinMax(arrayIn,device);
end
end
% Sum - This sums up the entire array in.
% valueOut = ImProc.Sum(arrayIn,[device])
% imageIn = This is a one to five dimensional array. The first three dimensions are treated as spatial.
% The spatial dimensions will have the kernel applied. The last two dimensions will determine
% how to stride or jump to the next spatial block.
%
% device (optional) = Use this if you have multiple devices and want to select one explicitly.
% Setting this to [] allows the algorithm to either pick the best device and/or will try to split
% the data across multiple devices.
%
% valueOut = This is the summation of the entire array.
function valueOut = Sum(arrayIn,device)
try
valueOut = ImProc.Cuda.Sum(arrayIn,device);
catch errMsg
warning(errMsg.message);
valueOut = ImProc.Local.Sum(arrayIn,device);
end
end
0% Loading or .
You are about to add 0 people to the discussion. Proceed with caution.
Finish editing this message first!
Please register or to comment