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stevevanhooserstevevanhooser
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Merge pull request #78 from MATLAB-Community-Toolboxes-at-INCF/wds_2024_wrap
readability improvements and bug fixes
2 parents b32cbf2 + 4be336b commit 667f836

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+240
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lines changed

‎+deepinterp/+internal/+test/neuropixelsPlay.m‎

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% this script was made to explore the input/output requirements of the
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% pretrained neuropixels network
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E = [[1:192]' [1:192]'+0.5]; % number electrodes by Y (whole number) and X 2*(mod 1)
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NP = repmat(E,1,1,500); % 500 frames of data
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% now transpose to be the same as the expected neuropixels data
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NP = permute(NP, [3 1 2]);
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nb_probes = 384; % Number of probes
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pre_post_omission = 3; % Number of frames omitted before and after the inferred frame
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pre_frame = 30; % Number of frames provided before the inferred frame
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post_frame = 30; % Number of frames provided after the inferred frame
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batch_size = 100;
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start_frame = 100;
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end_frame = 200;
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input_full = single(zeros(batch_size, nb_probes, 2, pre_frame + post_frame));
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for frame_index = start_frame:end_frame
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input_index = (frame_index - pre_frame - pre_post_omission) : (frame_index + post_frame + pre_post_omission );
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input_index = input_index(input_index ~= frame_index); % drop the predicted frame
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for index_padding = 1: pre_post_omission % drop pre_post_omission number of frames surrounding the predicted frame
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input_index = input_index(input_index ~= frame_index - index_padding);
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input_index = input_index(input_index ~= frame_index + index_padding);
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end
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data_img_input = ephys(input_index, :, :);
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data_img_input = permute(data_img_input,[2,3,1]);
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data_img_input = (single(data_img_input) - local_mean) / local_std;
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% alternating filling with zeros padding
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odd = 1: 2: nb_probes;
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even = odd + 1;
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input_full(frame_index-start_frame+1, odd, 1, :) = data_img_input(:, 1, :);
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input_full(frame_index-start_frame+1, even, 2, :) = data_img_input(:, 2, :);
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end
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‎+deepinterp/NPcheckerboard2frame.m‎

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function frame = checkerboard2NPframe(cb)
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% CHECKERBOARD2NPFRAME - convert geometrically realistic matrix to raw Neuropixels Phase 3 format
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%
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% FRAME = CHECKERBOARD2NPFRAME(CB)
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%
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% Convert geometrically-realistic matrix data CB (384 x 2 x NSAMPLES)
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% into a format that matches the raw data output of Neuropixels Phase 3
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% probes. CB is expected to reflect the checkerboard layout of electrodes,
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% where every even linear index is 0.
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%
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% FRAME will be a 192 x 2 x NSAMPLES matrix.
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%
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% For example, the following single-frame example input where each data point has
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% been set, for illustration purposes, to the electrode number (incremented by 0.25)
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% would be transformed as follows:
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%
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% 1.0000 0
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% 0 1.2500
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% 2.0000 0
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% 0 2.2500
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% 3.0000 0
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% 0 3.2500
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% ...
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% 190.0000 0
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% 0 190.2500
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% 191.0000 0
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% 0 191.2500
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% 192.0000 0
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% 0 192.2500
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%
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% to
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%
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% 1.0000 1.2500
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% 2.0000 2.2500
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% 3.0000 3.2500
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% ...
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% 189.0000 189.2500
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% 190.0000 190.2500
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% 191.0000 191.2500
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% 192.0000 192.2500
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% Check input dimensions
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if size(cb, 1) ~= 384 || size(cb, 2) ~= 2
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error('Input matrix CB must be 384 x 2 x NSAMPLES.');
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end
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frame = zeros(size(cb,1)/2, size(cb,2), size(cb,3));
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odd = 1:2:size(cb,1);
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even = odd + 1;
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frame(:,1,:) = cb(odd,1,:);
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frame(:,2,:) = cb(even,2,:);
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‎+deepinterp/NPframe2checkerboard.m‎

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function cb = NPframe2checkerboard(frame)
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% NPFRAME2CHECKERBOARD - convert raw Neuropixels Phase 3 to geometrically realistic matrix
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%
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% CB = NPframe2checkerboard(FRAME)
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%
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% Convert Neuropixels data frame data FRAME (192 x 2 x NSAMPLES)
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% into a geometrically-realistic matrix that reflects the checkerboad
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% layout of electrodes such as the Phase 3 version.
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%
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% CB will be a 384 x 2 x NSAMPLES matrix where every even linear index
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% will be 0.
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%
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% For example, the following single-frame example input where each data point has
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% been set, for illustration purposes, to the electrode number (incremented by 0.5)
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% would be transformed as follows:
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%
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% 1.0000 1.5000
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% 2.0000 2.5000
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% 3.0000 3.5000
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% ...
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% 189.0000 189.5000
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% 190.0000 190.5000
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% 191.0000 191.5000
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%
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% to
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%
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% 1.0000 0
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% 0 1.5000
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% 2.0000 0
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% 0 2.5000
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% 3.0000 0
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% 0 3.5000
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%...
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% 190.0000 0
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% 0 190.5000
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% 191.0000 0
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% 0 191.5000
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% 192.0000 0
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% 0 192.5000
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cb = zeros(size(frame,1)*2,size(frame,2),size(frame,3));
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odd = 1:2:size(frame,1)*2;
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even = odd + 1;
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cb(odd,1,:) = frame(:,1,:);
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cb(even,2,:) = frame(:,2,:);
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‎+deepinterp/Net.m‎

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options.Npost (1,1) double {mustBeInteger} = 30
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options.Nomit (1,1) double {mustBeInteger} = 1
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options.modelParameters (1,1) struct = struct('none',[])
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options.varname (1,:) char = "net"
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end
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networkType = options.type;
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obj.network=deepinterp.internal.importKerasMAE(options.file);
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case 'tensorflowzip',
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obj.network=deepinterp.internal.openTensorFlowNetwork(options.file,matlab.lang.makeValidName(options.model));
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case 'matlab',
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matdata = load(options.file);
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obj.network = getfield(matdata,options.varname);
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case 'pretrained',
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[modelfilename, modelparams] = deepinterp.internal.getPretrainedModelFilename(options.model);
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obj = deepinterp.Net(modelparams.format,'file',modelfilename,...
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'N',modelparams.dim(1),'M',modelparams.dim(2),...
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'Npre',modelparams.pre,'Npost',modelparams.post,'Nomit',modelparams.omit,...
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'type',modelparams.type,...
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'modelParameters',modelparams.parameters);
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'modelParameters',modelparams.parameters,'model',options.model,...
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"varname",options.varname);
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return;
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otherwise,
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error(['Unknown command: ' command]);
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options.progbar (1,1) logical = true;
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end
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if obj.networkType=="fMRI",
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error(['fMRI not yet supported by deepinterp.Net class.']);
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end;
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output = input;
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Nomit_pre = (obj.Nomit+1)/2;
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Nomit_post = (obj.Nomit+1)/2;
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offsets = [ fliplr(-[Nomit_pre:obj.Npre+Nomit_pre-1]) Nomit_post:obj.Npost+Nomit_post-1];
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if options.progbar,
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deepinterp.internal.progressbar();
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end;
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totalWork = size(input,3)-(obj.Npost+obj.Npre);
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for t = obj.Npre+1 : size(input,3) - obj.Npost,
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totalWork = size(input,3)-(obj.Npost+obj.Npre+Nomit_pre-1+Nomit_post-1);
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for t = obj.Npre+1+Nomit_pre-1 : size(input,3) - obj.Npost-Nomit_post+1,
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if options.progbar,
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deepinterp.internal.progressbar((t-(obj.Npre+1))/totalWork);
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end;
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output(:,:,t) = predict(obj.network,input(:,:,offsets+t));
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end;
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if options.progbar,
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deepinterp.internal.progressbar(0.9999999999);
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deepinterp.internal.progressbar(1);
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end;
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end; % interp()
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inSz = obj.network.Layers(1).InputSize;
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obj.N = inSz(1);
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obj.M = inSz(2);
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assert(inSz(3)==obj.Npre+obj.Npost,...
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['Npre + Npost must add up to the total ' ...
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'number of image inputs to ' ...
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'deepinterp.net.ImageTimeSeries.']);
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if numel(inSz)<4,
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assert(inSz(end)==obj.Npre+obj.Npost,...
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['Npre + Npost must add up to the total ' ...
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'number of image inputs to ' ...
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'deepinterp.net.ImageTimeSeries.']);
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end;
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end;
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end; % SetInputSize
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end;

‎+deepinterp/setup.m‎

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function setup()
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function tbd = setup()
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% SETUP - add DeepInterpolation Toolbox folders to the MATLAB path
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%
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% SETUP()
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% TBD = SETUP()
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%
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% Adds DeepInterpolation Toolobx folders to the MATLAB path.
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%
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% Returns the toolbox directory TBD.
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%
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tbd = deepinterp.toolboxpath();
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‎README.md‎

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| Data Type | Pretrained<br />Model| Sample<br />Data | View <br />:eyes: | Run <br /> ▶️
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| :--- | :---: | :---: | --- | --- |
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|🔬"Ophys"<br /> (optical physiology<sup>2</sup>)| [🤖](https://github.com/MATLAB-Community-Toolboxes-at-INCF/DeepInterpolation-MATLAB/blob/main/pretrainedModels/pretrained.json)<br /> (AWS, 120 MB) | [💾](sampleData/ophys_tiny_761605196.tif) | [![View Deep-Interpolation-MATLAB on File Exchange](https://www.mathworks.com/matlabcentral/images/matlab-file-exchange.svg)](https://viewer.mathworks.com/?viewer=live_code&url=https%3A%2F%2Fwww.mathworks.com%2Fmatlabcentral%2Fmlc-downloads%2Fdownloads%2F84c22101-bffc-435a-910c-b0c7dcd5b386%2F29e7e92d-4639-4178-8e19-739580981e60%2Ffiles%2Fexamples%2Ftiny_ophys_inference.mlx&embed=web) | [![Open in MATLAB Online](https://www.mathworks.com/images/responsive/global/open-in-matlab-online.svg)](https://matlab.mathworks.com/open/github/v1?repo=INCF/DeepInterpolation-MATLAB&file=examples/tiny_ophys_inference.mlx)
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|⚡"Ephys" (electrophysiology<sup>1</sup>)| [:robot:](https://github.com/MATLAB-Community-Toolboxes-at-INCF/DeepInterpolation-MATLAB/blob/main/pretrainedModels/pretrained.json) | [💾](sampleData/ephys_tiny_continuous.dat2) | [![View Deep-Interpolation-MATLAB on File Exchange](https://www.mathworks.com/matlabcentral/images/matlab-file-exchange.svg)](https://viewer.mathworks.com/?viewer=live_code&url=https%3A%2F%2Fwww.mathworks.com%2Fmatlabcentral%2Fmlc-downloads%2Fdownloads%2F84c22101-bffc-435a-910c-b0c7dcd5b386%2F29e7e92d-4639-4178-8e19-739580981e60%2Ffiles%2Fexamples%2Ftiny_ephys_inference.mlx&embed=web) | [![Open in MATLAB Online](https://www.mathworks.com/images/responsive/global/open-in-matlab-online.svg)](https://matlab.mathworks.com/open/github/v1?repo=INCF/DeepInterpolation-MATLAB&file=examples/tiny_ephys_inference.mlx)
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|🔬"Ophys"<br /> (optical physiology<sup>2</sup>)| [🤖](https://github.com/MATLAB-Community-Toolboxes-at-INCF/DeepInterpolation-MATLAB/blob/main/pretrainedModels/pretrained.json#L3)<br /> (AWS, 120 MB) | [💾](sampleData/ophys_tiny_761605196.tif) | [![View Deep-Interpolation-MATLAB on File Exchange](https://www.mathworks.com/matlabcentral/images/matlab-file-exchange.svg)](https://viewer.mathworks.com/?viewer=live_code&url=https%3A%2F%2Fwww.mathworks.com%2Fmatlabcentral%2Fmlc-downloads%2Fdownloads%2F84c22101-bffc-435a-910c-b0c7dcd5b386%2F29e7e92d-4639-4178-8e19-739580981e60%2Ffiles%2Fexamples%2Ftiny_ophys_inference.mlx&embed=web) | [![Open in MATLAB Online](https://www.mathworks.com/images/responsive/global/open-in-matlab-online.svg)](https://matlab.mathworks.com/open/github/v1?repo=INCF/DeepInterpolation-MATLAB&file=examples/tiny_ophys_inference.mlx)
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|⚡"Ephys" (electrophysiology<sup>1</sup>)| [:robot:](https://github.com/MATLAB-Community-Toolboxes-at-INCF/DeepInterpolation-MATLAB/blob/main/pretrainedModels/pretrained#L54.json) | [💾](sampleData/ephys_tiny_continuous.dat2) | [![View Deep-Interpolation-MATLAB on File Exchange](https://www.mathworks.com/matlabcentral/images/matlab-file-exchange.svg)](https://viewer.mathworks.com/?viewer=live_code&url=https%3A%2F%2Fwww.mathworks.com%2Fmatlabcentral%2Fmlc-downloads%2Fdownloads%2F84c22101-bffc-435a-910c-b0c7dcd5b386%2F29e7e92d-4639-4178-8e19-739580981e60%2Ffiles%2Fexamples%2Ftiny_ephys_inference.mlx&embed=web) | [![Open in MATLAB Online](https://www.mathworks.com/images/responsive/global/open-in-matlab-online.svg)](https://matlab.mathworks.com/open/github/v1?repo=INCF/DeepInterpolation-MATLAB&file=examples/tiny_ephys_inference.mlx)
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<sub><sup>1</sup> via Neuropixels neural probes <sup>2</sup> via two-photon (2P) calcium imaging<sub>
@@ -28,9 +28,9 @@ First-time users on MATLAB Online will be prompted to install the [Deep Learning
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Expected use cases involve training on a user's representative or actual dataset. The following examples illustrate the transfer learning workflow for (re)training DeepInterpolation pretrained models along with subsequent inference. Notably the DeepInterpolation principle **does not require separate ground truth data**; thus training and inference can be run using the same dataset.
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| Data Type | Pretrained Model | Sample Data | View :eyes:| Run ▶️
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|---|---|---|---|---|
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| 🔬"Ophys" (optical physiology<sup>1</sup>)| [TODO](sample_data/pretrainedNetwork.mat) | [sample data](sampleData/ophys_tiny_761605196.tif) | [![View Deep-Interpolation-MATLAB on File Exchange](https://www.mathworks.com/matlabcentral/images/matlab-file-exchange.svg)](https://viewer.mathworks.com/?viewer=live_code&url=https%3A%2F%2Fwww.mathworks.com%2Fmatlabcentral%2Fmlc-downloads%2Fdownloads%2F84c22101-bffc-435a-910c-b0c7dcd5b386%2Fbfd58de9-1242-48ba-81bc-dfe9c37fae6b%2Ffiles%2Fexamples%2Fcustomdatastore_example.mlx&embed=web) | [![Open in MATLAB Online](https://www.mathworks.com/images/responsive/global/open-in-matlab-online.svg)](https://matlab.mathworks.com/open/github/v1?repo=INCF/DeepInterpolation-MATLAB&file=examples/tiny_ophys_training.mlx)
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| ⚡ Ephys" (electrophysiology<sup>2</sup>) | ["Ephys-Neuropixels_Phase_3a_1050"](pretrainedModels/pretrained.json) | [sample data](sampleData/ephys_tiny_continuous.dat2) | [![View Deep-Interpolation-MATLAB on File Exchange](https://www.mathworks.com/matlabcentral/images/matlab-file-exchange.svg)](https://viewer.mathworks.com/?viewer=live_code&url=https%3A%2F%2Fwww.mathworks.com%2Fmatlabcentral%2Fmlc-downloads%2Fdownloads%2F84c22101-bffc-435a-910c-b0c7dcd5b386%2F29e7e92d-4639-4178-8e19-739580981e60%2Ffiles%2Fexamples%2Ftiny_ephys_training.mlx&embed=web) | [![Open in MATLAB Online](https://www.mathworks.com/images/responsive/global/open-in-matlab-online.svg)](https://matlab.mathworks.com/open/github/v1?repo=INCF/DeepInterpolation-MATLAB&file=examples/tiny_ephys_training.mlx)
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|---| :---: |---|---|---|
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| 🔬"Ophys" (optical physiology<sup>1</sup>)| [:robot:](https://github.com/MATLAB-Community-Toolboxes-at-INCF/DeepInterpolation-MATLAB/blob/main/pretrainedModels/pretrained#L3.json) | [sample data](sampleData/ophys_tiny_761605196.tif) | [![View Deep-Interpolation-MATLAB on File Exchange](https://www.mathworks.com/matlabcentral/images/matlab-file-exchange.svg)](https://viewer.mathworks.com/?viewer=live_code&url=https%3A%2F%2Fwww.mathworks.com%2Fmatlabcentral%2Fmlc-downloads%2Fdownloads%2F84c22101-bffc-435a-910c-b0c7dcd5b386%2Fbfd58de9-1242-48ba-81bc-dfe9c37fae6b%2Ffiles%2Fexamples%2Fcustomdatastore_example.mlx&embed=web) | [![Open in MATLAB Online](https://www.mathworks.com/images/responsive/global/open-in-matlab-online.svg)](https://matlab.mathworks.com/open/github/v1?repo=INCF/DeepInterpolation-MATLAB&file=examples/tiny_ophys_training.mlx)
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| ⚡ Ephys" (electrophysiology<sup>2</sup>) | [:robot:](https://github.com/MATLAB-Community-Toolboxes-at-INCF/DeepInterpolation-MATLAB/blob/main/pretrainedModels/pretrained#L54.json) | [sample data](sampleData/ephys_tiny_continuous.dat2) | [![View Deep-Interpolation-MATLAB on File Exchange](https://www.mathworks.com/matlabcentral/images/matlab-file-exchange.svg)](https://viewer.mathworks.com/?viewer=live_code&url=https%3A%2F%2Fwww.mathworks.com%2Fmatlabcentral%2Fmlc-downloads%2Fdownloads%2F84c22101-bffc-435a-910c-b0c7dcd5b386%2F29e7e92d-4639-4178-8e19-739580981e60%2Ffiles%2Fexamples%2Ftiny_ephys_training.mlx&embed=web) | [![Open in MATLAB Online](https://www.mathworks.com/images/responsive/global/open-in-matlab-online.svg)](https://matlab.mathworks.com/open/github/v1?repo=INCF/DeepInterpolation-MATLAB&file=examples/tiny_ephys_training.mlx)
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<sub><sup>1</sup> via two-photon (2P) calcium imaging <sup>2</sup> via Neuropixels neural probes<sub>
3636

@@ -40,9 +40,9 @@ Expected use cases involve training on a user's representative or actual dataset
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Expected use cases will involve larger data sizes, for which remote data locations and/or big data handling become important considerations. The following examples utilize larger datasets from cloud-hosted public scientific data archives to illustrate these data acccess & handling workflows.
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| Data Type | Pretrained Model | Public Data Archive | View :eyes: | Run ▶️
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|---|---|---|---|---|
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|🔬"Ophys" (optical physiology) | [model](pretrainedModels/pretrained.json) | [Allen Brain Observatory](http://allen-brain-observatory.s3.amazonaws.com/visual-coding-2p/ophys_movies/ophys_experiment_496908818.h5) (55.6 GB) | [![View Deep-Interpolation-MATLAB on File Exchange](https://www.mathworks.com/matlabcentral/images/matlab-file-exchange.svg)](https://viewer.mathworks.com/?viewer=live_code&url=https%3A%2F%2Fwww.mathworks.com%2Fmatlabcentral%2Fmlc-downloads%2Fdownloads%2F84c22101-bffc-435a-910c-b0c7dcd5b386%2F29e7e92d-4639-4178-8e19-739580981e60%2Ffiles%2Fexamples%2Fophys_AllenBrainObservatory.mlx&embed=web) | (\*) |
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|🧠 fMRI (functional magnetic resonance imaging) | [TODO](pretrainedModels/pretrained.json) (AWS)| [Open Neuro](https://openneuro.org/datasets/ds001246/versions/1.2.1) (18.3 GB)| [![View Deep-Interpolation-MATLAB on File Exchange](https://www.mathworks.com/matlabcentral/images/matlab-file-exchange.svg)](https://viewer.mathworks.com/?viewer=live_code&url=https%3A%2F%2Fwww.mathworks.com%2Fmatlabcentral%2Fmlc-downloads%2Fdownloads%2F84c22101-bffc-435a-910c-b0c7dcd5b386%2F29e7e92d-4639-4178-8e19-739580981e60%2Ffiles%2Fexamples%2Ftiny_fMRI_inference.mlx&embed=web) | [![Open in MATLAB Online](https://www.mathworks.com/images/responsive/global/open-in-matlab-online.svg)](https://matlab.mathworks.com/open/github/v1?repo=INCF/DeepInterpolation-MATLAB&file=examples/other/fMRI_OpenNeuro.mlx)
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|---|:---:|---|---|---|
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|🔬"Ophys" (optical physiology) | [:robot:](https://github.com/MATLAB-Community-Toolboxes-at-INCF/DeepInterpolation-MATLAB/blob/main/pretrainedModels/pretrained#L92.json) | [Allen Brain Observatory](http://allen-brain-observatory.s3.amazonaws.com/visual-coding-2p/ophys_movies/ophys_experiment_496908818.h5) (55.6 GB) | [![View Deep-Interpolation-MATLAB on File Exchange](https://www.mathworks.com/matlabcentral/images/matlab-file-exchange.svg)](https://viewer.mathworks.com/?viewer=live_code&url=https%3A%2F%2Fwww.mathworks.com%2Fmatlabcentral%2Fmlc-downloads%2Fdownloads%2F84c22101-bffc-435a-910c-b0c7dcd5b386%2F29e7e92d-4639-4178-8e19-739580981e60%2Ffiles%2Fexamples%2Fophys_AllenBrainObservatory.mlx&embed=web) | (\*) |
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|🧠 fMRI (functional magnetic resonance imaging) | [:robot:](https://github.com/MATLAB-Community-Toolboxes-at-INCF/DeepInterpolation-MATLAB/blob/main/pretrainedModels/pretrained#L74.json) | [Open Neuro](https://openneuro.org/datasets/ds001246/versions/1.2.1) (18.3 GB)| [![View Deep-Interpolation-MATLAB on File Exchange](https://www.mathworks.com/matlabcentral/images/matlab-file-exchange.svg)](https://viewer.mathworks.com/?viewer=live_code&url=https%3A%2F%2Fwww.mathworks.com%2Fmatlabcentral%2Fmlc-downloads%2Fdownloads%2F84c22101-bffc-435a-910c-b0c7dcd5b386%2F29e7e92d-4639-4178-8e19-739580981e60%2Ffiles%2Fexamples%2Ftiny_fMRI_inference.mlx&embed=web) | [![Open in MATLAB Online](https://www.mathworks.com/images/responsive/global/open-in-matlab-online.svg)](https://matlab.mathworks.com/open/github/v1?repo=INCF/DeepInterpolation-MATLAB&file=examples/other/fMRI_OpenNeuro.mlx)
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<sub>(\*) This data-intensive example is recommended for use on a local machine, not for MATLAB online.</sub>
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