在MATLAB中,可以使用以下方法处理缺失数据或NaN值: 删除包含NaN值的行或列: data = [1 2 NaN 4; 5 NaN 7 8; 9 10 11 12]; data_cleaned = data(~any(isnan(data), 2), :); % 删除包含NaN值的行 data_cleaned = data(:, ~any(isnan(data), 1)); % 删除包含NaN值的列 复制代码 替换...
mustBeNonNan(value)throws an error ifvalueisNaN. This function does not return a value. mustBeNonNancalls the following function to determine if the input is notNaN: isnan Class support: All numeric classes,logical, and MATLAB®classes that overloadisnan. ...
因此,MATLAB的系统文件、Toolboxes工具箱函数、用户自己编写的M文件等都应该保存在搜索路径中。当用户输入一个标识符(例如Value)时,MATLAB按下列步骤处理: (1)检查 Value 是否为变量 (2)检查 Value 是否为内部函数 (3)在当前的工作目录下是否存在 Value.m 文件 (4)在MATLAB搜索路径中是否存在 Value.m 文件 如果...
Check IDSeverityMessageMessage ReleaseCan Be Disabled?Related Documentation ATAS Error The attribute value is unexpected. Use a single meta-class object or a cell array of meta-class objects. true ATLAB Error Attribute 'Input' and 'Output' must not be assigned a value or negated. true ATNA...
(POS);ifsize(POS,1) ~= size(POS_fit,1)warning(['The objective function is badly programmed. It is not returning'...'a value for each particle, please check it.']);endPBEST = POS;PBEST_fit= POS_fit;DOMINATED= checkDomination(POS_fit);REP.pos = POS(~DOMINATED,:);REP.pos_fit ...
elseif ~islogical(varargin{1}); error 'C must be logical (TRUE||FALSE)' else c = varargin{1}; end % Compare inputs if ~all(size(y)==size(f)); error 'Y and F must be the same size'; end % Check for NaN tmp = ~or(isnan(y),isnan(f)); ...
% places to store movement cost value and position cost = Inf*ones(4,1); heuristic = Inf*ones(4,1); pos = ones(4,2); % if we can look left, we move from the right newx = currentpos(2) - 1; newy = currentpos(1);
ft_artifact_nan.m cleaned up whitespace Nov 10, 2022 ft_artifact_threshold.m print a notice about preprocessing, but only once Oct 13, 2021 ft_artifact_tms.m FIX - resolved small regression error with missing cfg.headerformat Aug 10, 2020 ft_artifact_zvalue.m ENH - pass on optional mont...
(i.e. the ability to re-use code for many different situations). Let me know if you have comments. Some of the code uses random-number generation, so it is recommended that you have something like rand('state',sum(100*clock)); randn('state',sum(100*clock)); in your MATLAB start...
if ~isempty(ekf.sensor) ekf.landmarks = NaN*zeros(2, ekf.sensor.map.nlandmarks); end end function run(ekf, n, varargin) %EKF.run Run the filter % % E.run(N, OPTIONS) runs the filter for N time steps and shows an animation % of the vehicle moving. % % Options...