function visualizeTableMask(data,idx) figure imagesc(idx) xticklabels(erase(data.Properties.VariableNames,"_")) xticks(1:width(data)) xtickangle(-45) ys = yticks; yticklabels(cellstr(data.Time(ys))) colormap gray end function plotEventCostsMap(data,threshold) ev = ["Flood","Lightning","Tropical Storm","Hurricane",... "Waterspout","Tornado"]; idx = ismember(string(data.event_type),ev) & ... data.damage_total > threshold; x = data(idx ,:); x.weathercats = removecats(x.weathercats); x = FillMissingLatLon(x); figure gb = geobubble(x,"begin_lat","begin_lon",... "SizeVariable","damage_total","ColorVariable","weathercats"); gb.Title = "Storm Event Damage"; gb.SizeLegendTitle = "Damage Cost ($1000)"; gb.ColorLegendTitle = "Event Type"; gb.Basemap = "colorterrain"; end function data = FillMissingLatLon(data) stateLatLon = struct2table(shaperead("usastatehi")); idx = find(ismissing(data.begin_lat) & ismissing(data.begin_lon) & ~ismissing(data.state) & ... ismember(string(data.weathercats),["Tropical Storm","Hurricane",... "Waterspout"])); for ii = 1:length(idx) sidx = lower(stateLatLon.Name) == lower(string(data.state(idx(ii)))); data.begin_lat(idx(ii)) = stateLatLon.LabelLat(sidx); data.begin_lon(idx(ii)) = stateLatLon.LabelLon(sidx); end end function plotEventCosts(data) ev = ["Flood","Lightning","Tropical Storm","Hurricane",... "Waterspout","Tornado"]; idx = ismember(string(data.event_type),ev) & ... data.damage_total > 0; x = data(idx ,:); x.weathercats = removecats(x.weathercats); warning("off","MATLAB:handle_graphics:Layout:NoPositionSetInTiledChartLayout") % Create figure t = tiledlayout(4,2,"TileSpacing","compact","Padding","compact"); %#ok nexttile([1 2]) boxplot(x.damage_total,x.event_type) ylabel("Damge Total ($)") nexttile(3,[3 1]) gb = geobubble(x,"begin_lat","begin_lon",... "SizeVariable","damage_total","ColorVariable","weathercats"); gb.Title = "Storm Event Damage Total"; gb.SizeLegendTitle = "Damage Cost ($1000)"; gb.ColorLegendTitle = "Event Type"; gb.Basemap = "colorterrain"; nexttile histogram(x.damage_property) title("Property Damage ($)") nexttile histogram(x.damage_crops) title("Crop Damage ($)") nexttile scatter(x.damage_property,x.damage_crops,"."); xlabel("Property Damage ($)"); ylabel("Crop Damage ($)") sgtitle("Damage by Event") warning("on","MATLAB:handle_graphics:Layout:NoPositionSetInTiledChartLayout") end

这段代码包含了多个函数，用于可视化数据和绘制图表。以下是每个函数的功能说明：

1. `visualizeTableMask(data,idx)`: 绘制一个图表，其中使用热图显示`idx`数据，并将`data`表的变量名作为x轴标签，并将`data.Time`作为y轴标签。

2. `plotEventCostsMap(data,threshold)`: 基于给定的阈值`threshold`，绘制一个地理气泡图，显示符合特定事件类型和损失阈值的数据。地理气泡图使用经度（begin_lon）和纬度（begin_lat）来定位气泡的位置，气泡的大小表示损失总额（damage_total），气泡的颜色表示天气类别（weathercats）。

3. `FillMissingLatLon(data)`: 填充缺失的经纬度信息。根据缺失的州信息（state）和特定的天气类别，从"usastatehi"数据中查找对应州的经纬度，并将其填充到data表中对应的记录中。

4. `plotEventCosts(data)`: 绘制一个包含多个子图的图表。其中，第一个子图是箱线图，显示不同事件类型的损失总额。第二个子图是地理气泡图，显示符合特定事件类型和损失阈值的数据。第三个和第四个子图分别是直方图，显示财产损失（damage_property）和农作物损失（damage_crops）的分布情况。最后一个子图是散点图，显示财产损失和农作物损失之间的关系。

请确保在运行这些函数之前已经加载了相应的数据，并且需要提供正确的参数。