我在数组 <1x43 单元格> 中有一个大型数据集。数据量非常大，这些是一些单元格尺寸 - 5 个是 <1x327680 double>，11 个是 <1x1376256 double>
我正在尝试执行我有一个功能的重新采样操作。（功能代码如下所示）。我正在尝试从数组中取出整个单元格，执行重采样操作并将结果存储回相同的数组位置或不同的位置。
但是，我在第 19 行或 Resample 函数中收到以下错误 -
“错误使用零超出了程序允许的最大变量大小。重新采样错误（第 19 行）obj = zeros(t,1);
当我评论我们的第 19 行时，我遇到了内存不足的错误。
请问有没有更有效的方法来操作这么大的数据集？
谢谢你。
实际代码：
%% To load each ".dat" file for the 51 attributes to an array.
a = dir('*.dat');
for i = 1:length(a)
eval(['load ' a(i).name ' -ascii']);
end
attributes = length(a);
% Scan folder for number of ".dat" files
datfiles = dir('*.dat');
% Count Number of ".dat" files
numfiles = length(datfiles);
% Read files in to MATLAB
for i = 1:1:numfiles
A{i} = csvread(datfiles(i).name);
end
% Remove discarded variables
ind = [1 22 23 24 25 26 27 32]; % Variables to be removed.
A(ind) = [];
% Reshape all the data into columns - (n x 1)
for i = 1:1:length(A)
temp = A{1,i};
[x,y] = size(temp);
if x == 1 && y ~= 1
temp = temp';
A{1,i} = temp;
end
end
% Retrieves the frequency data for the attributes from Excel spreadsheet
frequency = xlsread('C:\Users\aajwgc\Documents\MATLAB\Research Work\Data\testBig\frequency');
% Removing recorded frequency for discarded variables
frequency(ind) = [];
% Upsampling all the attributes to desired frequency
prompt = {'Frequency (Hz):'};
dlg_title = 'Enter desired output frequency for all attributes';
num_lines = 1;
def = {'50'};
answer= inputdlg(prompt,dlg_title,num_lines,def);
OutFreq = str2num(answer{1});
m = 1;
n = length(frequency);
A_resampled = cell(m,n);
A_resampled(:) = {''};
for i = length(frequency);
raw = cell2mat(A(1,i));
temp= Resample(raw, frequency(i,:), OutFreq);
A_resampled{i} = temp(i);
end
重采样功能：
function obj = Resample(InputData, InFreq, OutFreq, varargin)
%% Preliminary setup
% Allow for selective down-sizing by specifying type
type = 'mean'; %default to the mean/average
if size(varargin,2) > 0
type = varargin{1};
end
% Determine the necessary resampling factor
factor = OutFreq / InFreq;
%% No refactoring required
if (factor == 1)
obj = InputData;
%% Up-Sampling required
elseif (factor > 1)
t = factor * numel(InputData(1:end));
**obj = zeros(t,1); ----------------> Line 19 where I get the error message.**
for i = 1:factor:t
y = ((i-1) / factor) + 1;
z = InputData(y);
obj(i:i+factor) = z;
end
%% Down-Sampling required
elseif (factor < 1)
t = numel(InputData(1:end));
t = floor(t * factor);
obj = zeros(t,1);
factor = int32(1/factor);
if strcmp(type,'mean') %default is mean (process first)
for i = 1:t
y = (factor * (i-1)) + 1;
obj(i) = mean(InputData(y:y+factor-1));
end
elseif strcmp(type,'min')
for i = 1:t
y = (factor * (i-1)) + 1;
obj(i) = min(InputData(y:y+factor-1));
end
elseif strcmp(type,'max')
for i = 1:t
y = (factor * (i-1)) + 1;
obj(i) = max(InputData(y:y+factor-1));
end
elseif strcmp(type,'mode')
for i = 1:t
y = (factor * (i-1)) + 1;
obj(i) = mode(InputData(y:y+factor-1));
end
elseif strcmp(type,'sum')
for i = 1:t
y = (factor * (i-1)) + 1;
obj(i) = sum(InputData(y:y+factor-1));
end
elseif strcmp(type,'single')
for i = 1:t
y = (factor * (i-1)) + 1;
obj(i) = InputData(y);
end
else
obj = NaN;
end
else
obj = NaN;
end