使用Basemap绘制经纬度点

Question

我正在尝试使用matplotlib和Basemap绘制地图上的点，其中这些点表示特定建筑物的纬度/经度。我的地图确实绘制了这些点，但将它们放在了错误的位置。当我使用相同的数据并使用Bokeh而不是matplotlib和basemap做同样的事情时，我得到了正确的绘图。

这是Bokeh中的正确结果： Bokeh Version

而这是Basemap中的不正确结果： Basemap Version

我在StackOverflow的其他讨论中看到有人提出，这可能与plot()“移动”经度有关。我尝试了那里的建议，即包括以下行： lons，lats = m.shiftdata(long，lat) 然后使用转换后的数据。但这没有任何可见影响。

我生成Basemap和Bokeh中两个图形的完整示例代码在此处：

import matplotlib.pyplot as plt
from mpl_toolkits.basemap import Basemap
import pandas as pd

from bokeh.plotting import figure, show
from bokeh.sampledata.us_states import data as states
from bokeh.models import ColumnDataSource, Range1d

# read in data to use for plotted points
buildingdf = pd.read_csv('buildingdata.csv')
lat = buildingdf['latitude'].values
long = buildingdf['longitude'].values

# determine range to print based on min, max lat and long of the data
margin = .2 # buffer to add to the range
lat_min = min(lat) - margin
lat_max = max(lat) + margin
long_min = min(long) - margin
long_max = max(long) + margin

# create map using BASEMAP
m = Basemap(llcrnrlon=long_min,
            llcrnrlat=lat_min,
            urcrnrlon=long_max,
            urcrnrlat=lat_max,
            lat_0=(lat_max - lat_min)/2,
            lon_0=(long_max-long_min)/2,
            projection='merc',
            resolution = 'h',
            area_thresh=10000.,
            )
m.drawcoastlines()
m.drawcountries()
m.drawstates()
m.drawmapboundary(fill_color='#46bcec')
m.fillcontinents(color = 'white',lake_color='#46bcec')
# convert lat and long to map projection coordinates
lons, lats = m(long, lat)
# plot points as red dots
m.scatter(lons, lats, marker = 'o', color='r')
plt.show()


# create map using Bokeh
source = ColumnDataSource(data = dict(lat = lat,lon = long))
# get state boundaries
state_lats = [states[code]["lats"] for code in states]
state_longs = [states[code]["lons"] for code in states]

p = figure(
           toolbar_location="left",
           plot_width=1100,
           plot_height=700,
           )

# limit the view to the min and max of the building data
p.y_range = Range1d(lat_min, lat_max)
p.x_range = Range1d(long_min, long_max)
p.xaxis.visible = False
p.yaxis.visible = False
p.xgrid.grid_line_color = None
p.ygrid.grid_line_color = None

p.patches(state_longs, state_lats, fill_alpha=0.0,
      line_color="black", line_width=2, line_alpha=0.3)

p.circle(x="lon", y="lat", source = source, size=4.5,
         fill_color='red',
         line_color='grey',
         line_alpha=.25
         )
show(p)

我没有足够的声望点来发布数据的链接或将其包含在此处。

- rsgny

Answer 1

在底图绘制中，散点被填充陆地所遮挡。去除这两行。

#m.drawmapboundary(fill_color='#46bcec')
#m.fillcontinents(color = 'white',lake_color='#46bcec')

如果显示这些点可能是不需要的，最好的解决方案是使用zorder参数将散点图放置在地图的顶部。

m.scatter(lons, lats, marker = 'o', color='r', zorder=5)

这是完整的代码 (并且我希望您下次询问问题时包括这种带有硬编码数据的可运行的最小示例，因为这可以节省每个人发明数据的工作量):

import matplotlib.pyplot as plt
from mpl_toolkits.basemap import Basemap
import pandas as pd
import io

u = u"""latitude,longitude
42.357778,-71.059444
39.952222,-75.163889
25.787778,-80.224167
30.267222, -97.763889"""

# read in data to use for plotted points
buildingdf = pd.read_csv(io.StringIO(u), delimiter=",")
lat = buildingdf['latitude'].values
lon = buildingdf['longitude'].values

# determine range to print based on min, max lat and lon of the data
margin = 2 # buffer to add to the range
lat_min = min(lat) - margin
lat_max = max(lat) + margin
lon_min = min(lon) - margin
lon_max = max(lon) + margin

# create map using BASEMAP
m = Basemap(llcrnrlon=lon_min,
            llcrnrlat=lat_min,
            urcrnrlon=lon_max,
            urcrnrlat=lat_max,
            lat_0=(lat_max - lat_min)/2,
            lon_0=(lon_max-lon_min)/2,
            projection='merc',
            resolution = 'h',
            area_thresh=10000.,
            )
m.drawcoastlines()
m.drawcountries()
m.drawstates()
m.drawmapboundary(fill_color='#46bcec')
m.fillcontinents(color = 'white',lake_color='#46bcec')
# convert lat and lon to map projection coordinates
lons, lats = m(lon, lat)
# plot points as red dots
m.scatter(lons, lats, marker = 'o', color='r', zorder=5)
plt.show()

- ImportanceOfBeingErnest