所以我试图使用散景来绘制一组地理点(确切地说是学校位置)。我可以使用lats和longs绘制它们,但是如何在实际地图上叠加这些点呢?有没有办法将散景与谷歌地图或其他东西整合?
由于
答案 0 :(得分:9)
我认识到这个帖子已经老了,但我还没有在其他任何地方找到一个超级明确的答案,所以希望这会有所帮助。
from bokeh.sampledata import us_states
from bokeh.plotting import *
us_states = us_states.data.copy()
del us_states["HI"]
del us_states["AK"]
# separate latitude and longitude points for the borders
# of the states.
state_xs = [us_states[code]["lons"] for code in us_states]
state_ys = [us_states[code]["lats"] for code in us_states]
# init figure
p = figure(title="Plotting Points Example: The 5 Largest Cities in Texas",
toolbar_location="left", plot_width=1100, plot_height=700)
# Draw state lines
p.patches(state_xs, state_ys, fill_alpha=0.0,
line_color="#884444", line_width=1.5)
# Latitude and Longitude of 5 Cities
# ------------------------------------
# Austin, TX -------30.26° N, 97.74° W
# Dallas, TX -------32.77° N, 96.79° W
# Fort Worth, TX ---32.75° N, 97.33° W
# Houston, TX ------29.76° N, 95.36° W
# San Antonio, TX --29.42° N, 98.49° W
# Now group these values together into a lists of x (longitude) and y (latitude)
x = [-97.7431, -96.79, -97.33, -95.36, -98.49]
y = [30.26, 32.77, 32.75, 29.76, 29.42]
# The scatter markers
p.circle(x, y, size=8, color='navy', alpha=1)
# output to static HTML file
output_file("texas.html")
# show results
show(p)
这些绘图点被称为" Scatter Markers"在散景。有关详细信息,请参阅http://bokeh.pydata.org/en/latest/docs/user_guide/plotting.html#scatter-markers
答案 1 :(得分:3)
这里有一个将Bokeh与谷歌地图集成的例子:
http://bokeh.pydata.org/en/latest/docs/user_guide/geo.html#google-maps-support
现在(从0.7开始)你必须使用较低级别的界面,但很快就会将GMap选项添加到更高级别的API中。
答案 2 :(得分:2)
以下是您可能想要检查的链接:
http://bokeh.pydata.org/en/latest/docs/gallery/choropleth.html
from bokeh.sampledata import us_states, us_counties, unemployment
from bokeh.plotting import *
us_states = us_states.data.copy()
us_counties = us_counties.data.copy()
unemployment = unemployment.data
del us_states["HI"]
del us_states["AK"]
state_xs = [us_states[code]["lons"] for code in us_states]
state_ys = [us_states[code]["lats"] for code in us_states]
county_xs=[us_counties[code]["lons"] for code in us_counties if us_counties[code]["state"] not in ["ak", "hi", "pr", "gu", "vi", "mp", "as"]]
county_ys=[us_counties[code]["lats"] for code in us_counties if us_counties[code]["state"] not in ["ak", "hi", "pr", "gu", "vi", "mp", "as"]]
colors = ["#F1EEF6", "#D4B9DA", "#C994C7", "#DF65B0", "#DD1C77", "#980043"]
county_colors = []
for county_id in us_counties:
if us_counties[county_id]["state"] in ["ak", "hi", "pr", "gu", "vi", "mp", "as"]:
continue
try:
rate = unemployment[county_id]
idx = min(int(rate/2), 5)
county_colors.append(colors[idx])
except KeyError:
county_colors.append("black")
output_file("choropleth.html", title="choropleth.py example")
p = figure(title="US Unemployment 2009", toolbar_location="left",
plot_width=1100, plot_height=700)
p.patches(county_xs, county_ys, fill_color=county_colors, fill_alpha=0.7,
line_color="white", line_width=0.5)
p.patches(state_xs, state_ys, fill_alpha=0.0,
line_color="#884444", line_width=2)
show(p)
我还没有尝试过,但我想你可以使用形状文件来获得更准确的地图。
我之前尝试过的是底图模块..