代码搜索：Plot

找到约 10,000 项符合「Plot」的源代码

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m plot_gaussian.m

function plot_gaussian(number_clusters, power, AOA_deg, sigma_deg, ... delta_phi_deg, plot_number) % plot_gaussian(number_clusters, power, AOA_deg, sigma_deg, % delta_phi_deg,
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m plot_laplacian.m

function plot_laplacian(number_clusters, power, AOA_deg, sigma_deg, ... delta_phi_deg, plot_number) % plot_laplacian(number_clusters, power, AOA_deg, sigma_deg, % delta_phi_d
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m plot_uniform.m

function plot_uniform(number_clusters, amplitude, AOA, AS, ... plot_number) % plot_uniform(number_clusters, amplitude, AOA, AS, plot_number) % % Plots the multi-cluster uniform PAS % %
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m sample_plot.m

function figh = sample_plot(hist) % Customized plot function for approximate RL. % FIGH = SAMPLE_PLOT(HIST) % This function will be called if its name is specified in the 'plotfun' field % of the m
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m nav_plot.m

function figh = nav_plot(cfg) % Plot various information regarding the navigation problem % FIGH = NAV_PLOT(CFG) % Parameters: % CFG - history for a simple trajectory plot; %
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m example_plot.m

% example_plot.m % plot函数绘图示例 % 生成一维数组及其参数数组 a=0:0.1:1; t=0:0.01:1; % 生成二维数组 y=sin(3*t').*exp(-t')*a; % 不同的绘制参数比较 % figure1: 二维数组绘制曲线 subplot(2,2,1); plot(y); axis([0 100 0 1]); xlabel('in
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asv plot_complex.asv

% plot_complex.m % plot函数绘制复数曲线示例 % 产生一维自变量向量 t=[0:0.1:5]'; % 产生需要绘制的复数矩阵 y=t+exp(1/3*t).*sin(2*t+3)*i; real_y=real(); imag_y=exp(1/3*t).*sin(2*t+3); % 绘制曲线 subplot(1,2,1); plot(y); axis([0
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m plot_complex.m

% plot_complex.m % plot函数绘制复数曲线示例 % 产生一维自变量向量 t=[0:0.1:5]'; % 产生需要绘制的复数矩阵 y=t+exp(1/3*t).*sin(2*t+3)*i; real_y=real(y); imag_y=imag(y); % 绘制曲线 subplot(1,2,1); plot(y); axis([0 5 -4 3]); xl
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m plot_params.m

% plot_params.m % plot函数参数的示例 % 产生一维自变量向量 t=[0:pi/20:3*pi]'; % 产生需要绘制的复数矩阵 y=exp(-1/3*t).*sin(2*t+3); y1=exp(-1/3*t); % 绘制曲线 plot(t,y,'b:*'); xlabel('t');ylabel('y'); hold on; plot(t,y1,'r-
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m plot_gm.m

function Plot_GM(W,M,V,flag,X) % Plot_GM(W,M,V,X) % % Plots a 1D or 2D Gaussian mixture. % % Inputs: % W(1,k) - weights of each GM component, k is the number of component % M(d,k) - m
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