% Open old figures. gu = open('gugu.fig'); gu_ax = gca; lu = open('lulu.fig'); lu_ax = gca; F = figure; % New figure P1 = subplot(1,2,1); % Plot a subplot. P1_pos = get(P1,'position'); % get its position. delete
This function is useful when generating 3D or transparent figures that require Matlab's OpenGL renderer and high-quality results are desired. This renderer will not output vector axes or text labels. The EXPORTFIG function can be used to output separate EPS files of the graphic and the axes ...
closeall;% Close all figures (except those of imtool.) clearvars; workspace;% Make sure the workspace panel is showing. formatlong g; formatcompact; fontSize = 16; fprintf('Beginning to run %s.m ...\n', mfilename); %--- % Read in image. folder = []; baseFileName ='image.png'...
I am not being able to produce the two graphs in the same function so I cannot use hold on. Hence I have created two seperate functions to plot the two graphs and I am calling them from a main function. For better presentation and to make comparisons, I want to plot ...
Maps from all imaging regions are presented in the main and supplementary Figures. (Figs. 2,3 and Supplementary Fig. 1). Here, we call attention to representative examples from two imaging regions in Fig. 2i, j and Fig. 3f–i. In all imaging regions, neurons with significant STAs ...
According to the dynamic model of the rice combine harvester established above, a simulation model was established using MATLAB/Simulink. The structure of the simulation model is shown in Fig. 14. The surface excitation and dynamic model were included in the simulation model. Using the combination...
Ratio analysis by SHORE confirmed that stimulated cells from T2D subjects preferentially used glycolysis, as measured by the post-stimulation OCR:ECAR ratio, ΔOCR, and ΔECAR (Figures 2G–2I). Lower ATP generation by cells from T2D subjects (Figures 2J and 2K) was consistent with a ...
The chassis leveled with the transverse inclin- ation angle shifting from −15.2 to 0, and the height adjustment decreased from 243 to 0 mm (Figures 19–21). 3.5. Comparison between mathematical and ADAMS model The ADAMS Model data for transverse tilt adjust- ment and height adjustment ...
The FASTMCD algorithm27, as implemented in the Libra toolbox for Matlab28, was used to estimate these values robustly, with the assumption of 1% aberrant (outlier) values (i.e. a value of 0.99 for the alpha parameter). The sum of the variance in x and y directions was used to obtain...
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