用全息图绘制动态图但冻结

Question

基本需求:绘制一张地图，并根据编码更新为变量。挑战：

• 必须使用栅格化、数据聚合(大数据)。
• 全息视图.DynamicMap似乎不支持光栅化。

import holoviews as hv, datashader as ds, geoviews as gv, geoviews.tile_sources as gvts
from holoviews.operation.datashader import datashade, rasterize, dynspread
import panel as pn

hv.extension('bokeh')
opts = dict(width=700, height=500, tools=['hover'], 
            colorbar=True,symmetric=True,clim=(-5,5),
            cmap='Spectral')
tiles = gvts.OSM.options(alpha=0.6)

def load_dh(var=None):
    points = gv.Points(df, kdims=['longitude','latitude'])
    return rasterize(points, x_sampling=0.01, y_sampling=0.01, aggregator=ds.mean(var)).options(**opts)* tiles

def on_var_select(event):
    var = event.obj.value
    col[-1] = load_dh(var=var)

var_select = pn.widgets.Select(name='var:', options=['dh_after_dtm10', '2', '3'])

var_select.param.watch(on_var_select, parameter_names=['value'])

col = pn.Column(var_select, load_dh(var_select.value))
col

情节确实显示了，但没有随变量的变化而更新：

图片

我还尝试了DynamicMap，它与rasterize不兼容](变量变化时面板/图形交互)：

Exception: Nesting a DynamicMap inside a DynamicMap is not supported.

Answer 1

原始代码不是可运行的(尝试显示一个完全可复制的示例！)，但当我使其可运行并删除GeoViews (不在我当前的envt中)时，它似乎有效：

import holoviews as hv, datashader as ds, panel as pn, pandas as pd
from holoviews.operation.datashader import datashade, rasterize, dynspread

df = pd.DataFrame(dict(longitude=[70,80,90,100], latitude=[10,30,20,5],
                       c1=[1,0,9,7], c2=[5,2,0,1], c3=[3,1,3,8]))

hv.extension('bokeh')
opts = dict(width=700, height=500, tools=['hover'], 
            colorbar=True,symmetric=True,clim=(-5,5),
            cmap='Spectral')

def load_dh(var=None):
    points = hv.Points(df, kdims=['longitude','latitude'])
    return dynspread(rasterize(points, x_sampling=0.01, y_sampling=0.01, aggregator=ds.mean(var))).options(**opts)

def on_var_select(event):
    var = event.obj.value
    col[-1] = load_dh(var=var)

var_select = pn.widgets.Select(name='var:', options=['c1', 'c2', 'c3'])

var_select.param.watch(on_var_select, parameter_names=['value'])

col = pn.Column(var_select, load_dh(var_select.value))
col

​

​

尽管如此，这似乎是一个过于复杂的解决方案，当pn.bind可以非常直接地用于此时：

import holoviews as hv, datashader as ds, panel as pn, pandas as pd
from holoviews.operation.datashader import datashade, rasterize, dynspread

df = pd.DataFrame(dict(longitude=[70,80,90,100], latitude=[10,30,20,5],
                       c1=[1,0,9,7], c2=[5,2,0,1], c3=[3,1,3,8]))

hv.extension('bokeh')
opts = dict(width=700, height=500, tools=['hover'], 
            colorbar=True,symmetric=True,clim=(-5,5),
            cmap='Spectral')

def load_dh(var=None):
    points = hv.Points(df, kdims=['longitude','latitude'])
    return dynspread(rasterize(points, x_sampling=0.01, y_sampling=0.01, aggregator=ds.mean(var))).options(**opts)

var_select = pn.widgets.Select(name='var:', options=['c1', 'c2', 'c3'])

col = pn.Column(var_select, pn.bind(load_dh, var=var_select))
col

​

​

而且，与其说DynamicMap不支持rasterize，不如说rasterize的结果已经是DynamicMap，并且只支持单一级别的DynamicMap。总是可以制作一个单级别的DynamicMap来实现您想做的事情，但是由于HoloViews操作(与DynamicMaps不同)确实接受DynamicMap作为参数，所以您通常需要做的就是调用DynamicMap上的rasterize。因此，如果您想要制作一个DynamicMap，只需这样做，然后rasterize它。