简单代码示例

基础应用

set(gca, 'color', backColor,'w');
set (gcf,'Position',[400,300,600,200]);
set(gca, 'XTick', [0 10 20 30 40 50 60 70 80 90]) %设置X坐标轴刻度数据点位置
set(gca,'XTickLabel',{'0','10','20','30','40','50','60','70','80','90'}) %设置X坐标轴刻度处显示的字符
set(gca, 'YTick', [-15 -10 -5 0 5 10 15]) %设置X坐标轴刻度数据点位置
set(gca,'YTickLabel',{'-15','-10','-5','0','5','10','15'}) %设置Y坐标轴刻度处显示的字符
set(gca,'TickDir','out','TickLength',[0.02 0.02],'ylim',[-2 2])
axis([0,90,-20,20]),'xminortick','on')
set(gca,’XGrid’,’on’);
set(gca,’XMinorGrid’,’off’);
%改变ylabel离坐标轴的距离
hc=findobj(allchild(gcf), 'Type', 'axes');
hc2=findobj(allchild(hc), 'Type', 'text');
set(hc2(3), 'Position', [0 0 0]);
%改变xlabel离坐标轴的距离
hc=findobj(allchild(gcf), 'Type', 'axes');
hc2=findobj(allchild(hc), 'Type', 'text');
set(hc2(4), 'Position', [0 0 0]);
axis tight %使用紧凑的坐标轴范围
axis ij % 反转坐标系
axis manual %通过将范围模式设置为手动来保留当前的坐标轴范围

get(gca,‘xlim’);是获取最大最小刻度的
如果需要获取所有在坐标轴上显示的刻度，需要使用get(gca,‘ytick’)

axes应用

% 在图窗中定位多个坐标区
figure
ax1 = axes('Position',[0.1 0.1 0.7 0.7]);
ax2 = axes('Position',[0.65 0.65 0.28 0.28]);
contour(ax1,peaks(20))
surf(ax2,peaks(20))% 将坐标区设置为当前坐标区
ax1 = axes('Position',[0.1 0.1 .6 .6],'Box','on');
ax2 = axes('Position',[.35 .35 .6 .6],'Box','on');
% 将 ax1 设置为当前坐标区。此操作将使该坐标区显示在最前面，并使其成为后续图形函数的目标。在坐标区上添加一个线图。
axes(ax1)
x = linspace(0,10);
y = sin(x);
plot(x,y)

图例设置

打开此链接了解更多

填色图绘制

%% draw
figure('Name','snowc_ano','NumberTitle','off')
m_proj('Equidistant Cylindrical', 'lon',[-180,180],'lat',[0,90]);
m_contourf(LON, LAT, snowc_ano',20,'linestyle','none');
color_select = flipud(othercolor('BuDOr_18'));
color_select_divide = color_select(floor(linspace(1,size(color_select,1),20)),:);
colormap(color_select_divide);
hold on;
m_coast('color','k');
m_grid('fontsize',16);
% m_grid('xtick',[850:10:150],'ytick',[0:10:40],'linest',':','color','k');
c = colorbar;
c.Label.String = 'Snow cover (%)';
set(c,'fontsize',14,'fontweight','bold');
set(c,'ytick',-50:5:50,'yticklabel',-50:5:50)
title('Snow cover anomaly in 2020.11-2021.01','fontsize',14);
caxis([-50 50])

关于经线处理

lon2 = cat(1,lon(find(lon>180))-360,lon(find(lon<=180)));
SST2 = cat(1,SST(find(lon>180),:,:), SST(find(lon<=180),:,:));

调整子图间距与省界图绘制

clear all; clc; close all;
%% draw wind
load('data_saving_matrix.mat');
load('location.mat');
fpni='F:\china-shapefiles\china.shp';
china_map=shaperead(fpni);%读取底图heilongjiang_map = china_map(1);%在china_map 找到黑空龙江底图
sichuan_map= china_map(266);%在china_map 找到四川底图
jiangsu_map= china_map(258);%在china_map 找到江苏底图
%%%%%%%%%%%%%%1-3
%1heilongjiang
boux1=[heilongjiang_map(:).X];%获取shp经度
bouy1=[heilongjiang_map(:).Y];%获取shp纬度
%2sichuan
boux2=[sichuan_map(:).X];%获取shp经度
bouy2=[sichuan_map(:).Y];%获取shp纬度
%3jiangsu
boux3=[jiangsu_map(:).X];%获取shp经度
bouy3=[jiangsu_map(:).Y];%获取shp纬度
%%%%%%%%finish
set(gcf,'position',[0 0 1440 780]);
wind_direction = squeeze(data_saving_matrix(1,1,:,10));%最大风速对应风向
wind_speed = squeeze(data_saving_matrix(1,1,:,11));%读取最大风速
wind_direction(wind_direction==999999  ) = nan;%缺省值为nan
wind_direction(wind_direction==999998) = nan;%缺省值为nan
wind_speed(wind_speed==999999  ) = nan;%缺省值为nan
wind_speed(wind_speed==999998) = nan;%缺省值为nanu = wind_speed.*sin(wind_direction*pi/180);%风速风向与UV互换
v = wind_speed.*cos(wind_direction*pi/180);%风速风向与UV互换
%%%%%%%%figure
subplot(1,3,1)
plot(boux1,bouy1,'k');%画出省边界图
hold on;
WindBarb(location(:,2),location(:,1),u,v,0.03);%画出风速
set(gca,'xlim',[120 136],'ylim',[42 54]);%xlim省界经纬范围
%set(gca,'xlim',[116 122],'ylim',[30 36]);%xlim省界经纬范围
%set(gca,'xlim',[97 109],'ylim',[26 35]);%xlim省界经纬范围
title('黑龙江省7月1日0时最大风速');
subplot(1,3,2)
plot(boux2,bouy2,'k');%画出省边界图
hold on;
WindBarb(location(:,2),location(:,1),u,v,0.03);%画出风速
set(gca,'xlim',[97 109],'ylim',[26 35]);%xlim省界经纬范围
title('四川省7月1日0时最大风速');subplot(1,3,3)
plot(boux3,bouy3,'k');%画出省边界图
hold on;
WindBarb(location(:,2),location(:,1),u,v,0.03);%画出风速
set(gca,'xlim',[116 122],'ylim',[30 36]);%xlim省界经纬范围
title('江苏省7月1日0时最大风速');
%%%%%%调整图像
clear all;
margin_distance = 0.05; %第一个图和左边框的距离
figure_distance = 0.05;%图和图之间的距离
figure_num = 3;%子图的数目
figure_width = (1-2*margin_distance-(figure_num-1)*figure_distance)/figure_num;
subplot(1,3,1);
set(gca,'position',[0.05 0.2 figure_width 0.6]);
subplot(1,3,2);
set(gca,'position',[0.1+figure_width 0.2 figure_width 0.6]);
subplot(1,3,3);
set(gca,'position',[0.15+2*figure_width 0.2 figure_width 0.6]);%%%%%保存图像
print('-dpng','E:\毕业论文\pic\new\3S_v070100.png','-r600');

mask 降水

clc; close all; clear all;
filename = 'Z_3IMERG_all_2001_2021_apr_sub.nc';
lat = ncread(filename,'lat');
lon = ncread(filename,'lon');
rain = ncread(filename,'rain');
time = ncread(filename,'time');
hours = 24;
[LON, LAT] = meshgrid(lat, lon);
lon_fine = lon(1):0.5:lon(end);
lat_fine = lat(1):0.5:lat(end);
[LON_FINE, LAT_FINE] = meshgrid(lat_fine, lon_fine);
%% date index
start_index = datenum('2020-06-01')-datenum('2000-06-01')+1;
end_index = datenum('2020-07-20')-datenum('2000-06-01')+1;
rain_2020 = rain(start_index:end_index, :, :);
rain_2020_sum = squeeze(sum(rain_2020,1)); % 获得每个格点的累计降水
rain_2020_sum_interp = interp2(LON, LAT, rain_2020_sum, LON_FINE, LAT_FINE, 'cubic');
%% draw the contour map
m_proj('Mercator','lon',[70,140],'lat',[15,55]);
m_contourf(lon_fine,lat_fine,rain_2020_sum_interp'*hours,'linecolor','none');
hold on;
data_3=shaperead('D:\AA_Senior2\科研\曹地冯\province\province.shp');
boux=[data_3(:).X];bouy=[data_3(:).Y];%分别是获取经度X信息和纬度Y信息
m_plot(boux,bouy,'k');%最关键的一句，绘制地图
lon2 = [70 140];
lat2 = [15 55];
m_maskmap('D:\AA_Senior2\科研\曹地冯\province\province.shp', true,'lon', lon2,'lat', lat2,'m_map',true);
color = [255,255,255
204,236,230
153,216,201
102,194,164
65,174,118
35,139,69
0,88,36]/255;
colormap(color);
%m_grid('xticklabels',["80°E";"100°E";"120°E";"140°E"],'xtick',[80:20:140],...
%      'ytick',[10:10:60],'yticklabels',["10°N";"20°N";"30°N";"40°N";"50°N";"60°N"],'linest',':','color','k');
m_grid('xtick',[80:20:140],'ytick',[10:10:60],'linest',':','color','k');
colorbar;
caxis([0 700]);

mask降水+动图

%% subsequent plotting
filegifname = "D:\AA_Senior2\科研\曹地冯\图汇总\movie.gif";
for i = 1:size(rain_2020,1)figure(i);m_proj('Mercator','lon',[70,140],'lat',[15,55]);rain_2020_interp = interp2(LON, LAT, squeeze(rain_2020(i, :, :)), LON_FINE, LAT_FINE, 'cubic');m_contourf(lon_fine,lat_fine, rain_2020_interp'*hours,'linecolor','none');hold on;data_3=shaperead('D:\AA_Senior2\科研\曹地冯\province\province.shp');boux=[data_3(:).X];bouy=[data_3(:).Y];%分别是获取经度X信息和纬度Y信息m_plot(boux,bouy,'k');%最关键的一句，绘制地图lon2 = [70 140];lat2 = [15 55];m_maskmap('D:\AA_Senior2\科研\曹地冯\province\province.shp', true,'lon', lon2,'lat', lat2,'m_map',true,'facecolor',[1 1 1]);color = [255,255,255204,236,230153,216,201102,194,16465,174,11835,139,690,88,36]/255;colormap(color);m_grid('xtick',[80:20:140],'ytick',[10:10:60],'linest',':','color','k');colorbar;caxis([0 35]);title("Precipitation on "+datestr(i-1+datenum('2020-06-01'),'yyyy-mm-dd'),'fontsize',14); drawnow; % 刷新屏幕pause(0.1)f = getframe(gcf);imind = frame2im(f);[imind,cm] = rgb2ind(imind,256);if i == 1imwrite(imind,cm,filegifname,'gif', 'Loopcount',inf,'DelayTime',0.25);elseimwrite(imind,cm,filegifname,'gif','WriteMode','append','DelayTime',0.25);endendclose all;

** 不等间距的colorbar绘制+风速的quiver绘制**

figure(1)
m_proj('Equidistant Cylindrical', 'lon',[begin_lon, end_lon],'lat',[begin_lat, end_lat]);
m_contourf(LON, LAT,quv1',15,'linestyle','none');
color =[255,255,255255,241,118255,238,0253,216,53167,242,134167,242,134167,242,134167,242,13452,172,252,172,252,172,252,172,2103,185,250103,185,250103,185,250103,185,2500,0,2550,0,2550,0,2550,0,255253,1,253253,1,253253,1,253253,1,253]/255;
level =  [0:0.002:0.006 0.008:0.008:0.048];
color_select = othercolor('PuBuGn8');
color_select_divide = color_select(floor(linspace(1,size(color_select,1),15)),:);
color_select_divide2 = [color_select_divide(7,:); color_select_divide(13:end,:)];
colormap(color);
hold on;
m_grid('fontsize',16);
color_border = [0.4 0.4 0.4];
m_gshhs('hc1','linewidth',.8,'color',color_border);
data_3=shaperead('G:\ERA5-mon\china\china.shp');
boux=[data_3(:).X];bouy=[data_3(:).Y];%分别是获取经度X信息和纬度Y信息
m_plot(boux,bouy,'color',color_border,'linewidth',1);%最关键的一句，绘制地图caxis([0 0.048])
h = colorbar;
h.Label.String = "Specific humidity transportation (m/s*kg/kg)";
%set(h,'Ticks',0:length(level)-1,'Ticklabels',level,'yticklabel',string(level));
set(h,'ytick',level,'yticklabel',level)
set(h,'fontsize',14,'fontweight','bold');
set(h,'TickLength',0);
title('Specific humidity transportation from 1979/1980 to 1996/1997 at 850hPa','fontsize',18,'fontweight','bold');
d = 5; dd = 100*10^-4;
[LON_WIND, LAT_WIND] = meshgrid(lon_need(1:d:end-d), lat_need(1:d:end-d));
% m_quiver(LON_WIND, LAT_WIND, qu_1(1:d:end,1:d:end)'./dd.*cosd(lat_need(1:d:end)),qv_1(1:d:end,1:d:end)'./dd, 0,'k','linewidth',1.5);
m_quiver(LON_WIND, LAT_WIND, qu_1(1:d:end-d,1:d:end-d)'./dd.*cosd(lat_need(1:d:end-d)),qv_1(1:d:end-d,1:d:end-d)'./dd, 0,'k','linewidth',1.5);
axis equal

加入地图细节

m_gshhs('hr1','linewidth',.8,'color','k');
m_gshhs('hc1','linewidth',1,'color','k');
m_gshhs('hb1','linewidth',1,'color','k');

** 颠倒colorbar，**


figure(3)
color_select = flipud(othercolor('RdYlBu9'));
color_select_divide = color_select(floor(linspace(1,size(color_select,1),20)),:);
m_proj('Equidistant Cylindrical', 'lon',[40,160],'lat',[0,80]);
m_contourf(LON, LAT,z500_1_ano',20,'linestyle','none');
colormap(color_select_divide);
hold on;
text_contour = 480:8:600;
z_mean_smooth1 = zeros(size(z_mean));
z_mean_smooth2 = zeros(size(z_mean));
for i = 1:size(z_mean,1)z_mean_smooth1(i,:) = smooth(z_mean(i,:),20);for j = 1:size(z_mean,2)z_mean_smooth2(:,j) = smooth(z_mean_smooth1(:,j),20);endend
m_contour(LON, LAT,z_mean_smooth2',text_contour,'linewidth',1.5,'color','k','showtext','on');
color_border = [0.4 0.4 0.4];
m_gshhs('hc1','linewidth',.8,'color',color_border);
data_3=shaperead('G:\ERA5-mon\china\china.shp');
boux=[data_3(:).X];bouy=[data_3(:).Y];%分别是获取经度X信息和纬度Y信息
m_plot(boux,bouy,'color',color_border,'linewidth',1);%最关键的一句，绘制地图
% m_contour(LON, LAT,z1000_1_ano_neg',text_contour,'--','linewidth',1.8,'color','k','showtext','on');
m_grid('fontsize',16);
caxis([-2.5 2.5])
h = colorbar;
h.Label.String = "Geopotential (dagpm)";
%set(h,'ytick',500:100:2000,'yticklabel',500:100:2000)
set(h,'fontsize',14,'fontweight','bold');
title('Geopotential mean and anomaly from 1979/1980 to 1996/1997 at 500hPa','fontsize',16,'fontweight','bold');

** 绘制要相关的图**

clear all; clc; close all;
filelist=dir(['*.mat']);%指定批量数据的类型
for i = 1:length(filelist)load(filelist(i).name);
end
load('get_location_corr.mat')
indice_name = ["AAO","AMM","AMO","EA","east_IOD","IOD","NAO","nino_12","nino_34","nino_3","nino_4","nino_A","nino_CP","nino_EP","nino_Z","NP","NTA","ONI","PDO","PNA","SOI","TNA","TSA","west_IOD","WHWP","WP"];
place_name = ["australia","california","north_africa","siberia","south_africa","south_america"];
for i = 1:length(indice_name)for j = 1:length(place_name)command_str = indice_name(i)+"_"+place_name(j)+"  = [get_"+indice_name(i)+"_corr_"+place_name(j)+"_spring_array; get_"+indice_name(i)+"_corr_"+place_name(j)+"_summer_array; get_"+indice_name(i)+"_corr_"+place_name(j)+"_fall_array; get_"+indice_name(i)+"_corr_"+place_name(j)+"_winter_array];";eval(command_str)end
end
% combine indices
for j = 1:length(place_name)initial_fuzhi = place_name(j)+"_indice = []";eval(initial_fuzhi);for i = 1:length(indice_name)command_str_indice = place_name(j)+"_indice = cat(3,"+place_name(j)+"_indice,"+indice_name(i)+"_"+place_name(j)+");";eval(command_str_indice);end
endtotal_indice = cat(2,australia_indice,california_indice, north_africa_indice, siberia_indice, south_africa_indice, south_america_indice);
festival = [ 'sprinig','summer','autumn','winter'];color_matrix2 = flipud([103,0,31
178,24,43
214,96,77
253,219,199
247,247,247
247,247,247
247,247,247
247,247,247
209,229,240
67,147,195
33,102,172
5,48,97]/255);indice_new = ["AAO","AMM","AMO","EA","east IOD","IOD","NAO","nino 12","nino 34","nino 3","nino 4","nino A","nino CP","nino EP","nino Z","NP","NTA","ONI","PDO","PNA","SOI","TNA","TSA","west IOD","WHWP","WP"];
for i = 1:9aus_pla(i) = "au"+num2str(i);
end
for i=1:3cal_pla(i) = "ca"+num2str(i);
end
for i = 1:10nor_pla(i) = "no"+num2str(i);
end
for i =1:8sib_pla(i) = "si"+num2str(i);  sof_pla(i) = "sf"+num2str(i);
end
for i =1:7som_pla(i) = "sm"+num2str(i);
endplace_new = [aus_pla cal_pla nor_pla sib_pla sof_pla som_pla "au" "ca" "no" "si" "sf" "sm"];
season= ["spring","summer","autumn","winter"];
total_indice = cat(2,total_indice,get_location_corr);
for i = 1:size(total_indice,1)subplot(2,2,i)h = heatmap(place_new,indice_new,squeeze(total_indice(i,:,:))');set(h,'fontsize',8)caxis([-0.7 0.7])colorbar()title(season(i));colormap(color_matrix2);end'''**物理量的时间序列多模式比较**```python
clear all; clc; close all;
var_126_f = load('var_matrix_126.mat');
var_585_f = load('var_matrix_585.mat');
var_126 = var_126_f.var_matrix_reshape;
var_585 = var_585_f.var_matrix_reshape;
[time, domain, model, var] = size(var_126);
%% smooth
for i =1:domainfor j = 1:varfor k = 1:modelvar_smooth_126(:,i,k,j) = smoothdata(var_126(:,i,k,j),1,'movmean',60);var_smooth_585(:,i,k,j) = smoothdata(var_585(:,i,k,j),1,'movmean',60);endend
end
maxtemp126 = zeros(time, domain);
mintemp126= zeros(time, domain);
maxtemp585= zeros(time, domain);
mintemp585= zeros(time, domain);
domain_name = ["Australia","California","North Africa","Siberia","South Africa","South America"];
for i =1:domainj  = 6;maxtemp126(:,i) = max(var_smooth_126(:,i,:,j),[],3);maxtemp585(:,i) = max(var_smooth_585(:,i,:,j),[],3);mintemp126(:,i) = min(var_smooth_126(:,i,:,j),[],3);mintemp585(:,i) = min(var_smooth_585(:,i,:,j),[],3);
end
tempFill126 = [mintemp126; flipud(maxtemp126)]';
tempFill585 = [mintemp585; flipud(maxtemp585)]';
x = 1:time;
xFill = [x fliplr(x)];
% %% draw
% for i =1:domain
%     for j = 1:var
%         subplot(8,6,i+6*(j-1));
%         for k = 1:model
%         plot(squeeze(var_126(:,i,k,j)),'color',ssp126_color(k,:));
%         hold on;
%         plot(squeeze(var_585(:,i,k,j)),'color',ssp585_color(k,:));
%         end
%         set(gca,'xtick',1:120:1020,'xticklabel',["2015","2025","2035","2045","2055","2065","2075","2085","2095"]);
%         if j == 1
%             ylabel('Cloud Fraction')
%         else if j == 2
%                 %ylim([20 100]);
%                 ylabel('RH');
%             else if j ==3
%                     %ylim([0 1*10^-4])
%                     ylabel('Precip');
%                 else if j == 4
%                        % ylim([9.5*10^4 10*10^4])
%                         ylabel('Surface Pressure');
%                     else if j ==5
%                             ylabel('Radiation');
%                         else if j==6
%                               %  ylim([250 310])
%                                 ylabel('Surface Temp');
%                             else if j == 7
%                                  %   ylim([-4 4])
%                                     ylabel('Uwnd');
%                                 else if j ==8
%                                      %   ylim([-4 4])
%                                         ylabel('Vwnd');
%                                     end
%                                 end
%                             end
%                         end
%                     end
%                 end
%             end
%         end
%     end
% end
ssp126_color = [27,158,119
217,95,2
117,112,179
231,41,138
102,166,30
230,171,2
166,118,29]/255;
ssp585_color = [27,158,119
217,95,2
117,112,179
231,41,138
102,166,30
230,171,2
166,118,29]/255;
figure('units','normalized','position',[0.1,0.1,0.7,0.6])for i =1:domainfor k = 1:modelsubplot(2,3,i)j = 6;     plot(squeeze(var_smooth_126(:,i,k,j)),'color',ssp126_color(k,:));hold on;plot(squeeze(var_smooth_585(:,i,k,j)),'color',ssp585_color(k,:));set(gca,'xlim',[60 1020-60]);end% shadeyFill126 = tempFill126(i,:);yFill585 = tempFill585(i,:);f_585 = fill(xFill,yFill585,[228 95 81]/255);%'edgecolor',[0.5 0.5 0.5],'linewidth',2,'facealpha',0.3)f_585.EdgeColor = [0 0 0];f_585.LineWidth = 1;f_585.FaceAlpha = 0.3;f_126 = fill(xFill,yFill126,[39 128 194]/255);%,'facecolor', [39 128 194]/255,'edgecolor',[0 0 0],'linewidth',2,'facealpha',0.3);f_126.EdgeColor = [0.3 0.3 0.3];f_126.LineWidth = 1;f_126.FaceAlpha = 0.3;h126 = plot(squeeze(mean(var_smooth_126(1:end,i,:,j),3)),'color',[11 22 82]/255,'linewidth',3);h585 = plot(squeeze(mean(var_smooth_585(1:end,i,:,j),3)),'color',[142 0 0]/255,'linewidth',3);legend([h126 h585],'ssp126','ssp585','location','northwest');title("2m temperature of "+ domain_name(i),'fontsize',14);xlabel('Year')ylabel('2m temperature (K)');set(gca,'xtick',60:120:961,'xticklabel',["2020","2030","2040","2050","2060","2070","2080","2090"]);
endvar_126_mean = squeeze(mean(var_126,3));
var_585_mean = squeeze(mean(var_585,3));
save var_126_mean.mat var_126_mean
save var_585_mean.mat var_585_mean![在这里插入图片描述](https://img-blog.csdnimg.cn/20210719085133526.jpg?x-oss-process=image/watermark,type_ZmFuZ3poZW5naGVpdGk,shadow_10,text_aHR0cHM6Ly9ibG9nLmNzZG4ubmV0L3lpd2VpeGlhb21pYW5kdWk=,size_16,color_FFFFFF,t_70)

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MATLAB代码细节整理

MATLAB代码细节

简单代码示例

基础应用

axes应用

图例设置

填色图绘制

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