投影地图上的散点图位置不正确
Scatter Plot on Projected Map is not in Correct Location
我有飓风的轨迹。在“常规”地图CRS中，飓风的轨迹是正确的
但是，当我使用非常规投影时，飓风的位置是关闭的。它从北美东部开始，然后向西穿越这片土地。这是为什么？
这是我的尝试方法
data = {'Lat':{0:12.9,2:12.9,4:13.2,6:13.6,8:13.7,10:13.8,12:14.2,14:14.5,16:14.8,18:16.0,20:17.0,22:17.9,24:18.3,26:18.9,28:19.7,30:20.7,32:22.0,34:23.4,36:24.6,38:25.1,40:25.0,42:24.8,44:24.5,46:24.6,48:24.4,50:24.6,52:25.0,54:25.9,56:26.4,58:27.1,60:28.0,62:28.5,64:29.4,66:30.4,68:31.5,70:32.5,72:33.1,74:33.6,76:33.9,78:34.1,80:34.1,82:34.0,84:33.9,86:33.7,88:33.6,90:33.6,92:33.6,94:33.7,96:34.0,98:35.5,100:38.5,102:39.8,104:42.6},'Long':{0:-18.4,2:-19.4,4:-20.9,6:-21.4,8:-22.7,10:-24.7,12:-25.5,14:-26.7,16:-27.8,18:-30.2,20:-33.2,22:-35.9,24:-38.7,26:-41.0,28:-42.5,30:-43.9,32:-45.7,34:-47.2,36:-48.6,38:-49.8,40:-51.8,42:-53.2,44:-54.3,46:-55.2,48:-56.3,50:-57.7,52:-60.0,54:-62.4,56:-64.6,58:-66.2,60:-67.9,62:-69.5,64:-70.7,66:-71.8,68:-73.2,70:-74.3,72:-75.1,74:-76.0,76:-76.4,78:-77.2,80:-77.9,82:-78.4,84:-78.8,86:-79.3,88:-79.5,90:-79.8,92:-80.1,94:-80.8,96:-81.8,98:-82.1,100:-82.9,102:-80.2,104:-71.9}}
df = pd.DataFrame.from_dict(data)
# Invert longitude for plotting in western Hemisphere
df['Long'] = df['Long'] * -1
newCrs = ccrs.RotatedPole(pole_latitude=37.5, pole_longitude=177.5)
fig = plt.figure(figsize=(20, 10))
ax = plt.subplot(projection = newCrs)
ax.coastlines(resolution = '110m')
ax.scatter(df['Long'], df['Lat'], color = 'red', transform = newCrs)
问题是 ax.scatter 中的 transform 关键字应该是 DATA CRS。因此，假设您的 indata 与 PlateCarree crs 没问题：
df = pd.DataFrame(dict(Lat=[i for i in data['Lat'].values()], Long=[i for i in data['Long'].values()]))
newCrs = ccrs.RotatedPole(pole_latitude=37.5, pole_longitude=177.5)
dataCrs = ccrs.PlateCarree()
fig = plt.figure(figsize=(20, 10))
ax = plt.axes(projection = newCrs)
ax.set_global()
ax.coastlines()
ax.scatter(df['Long'], df['Lat'], color = 'red', transform = dataCrs)
给出：
请阅读 this page explaining transforms 了解详细信息和教程。
备选方案（推荐GeoPandas）
也许不能直接回答你的问题，但如果我通过 GeoPandas（强烈推荐），我似乎没有遇到任何问题：
import pandas as pd
import geopandas as gpd
import contextily as ctx
import cartopy.crs as ccrs
data = {'Lat':{0:12.9,2:12.9,4:13.2,6:13.6,8:13.7,10:13.8,12:14.2,14:14.5,16:14.8,18:16.0,20:17.0,22:17.9,24:18.3,26:18.9,28:19.7,30:20.7,32:22.0,34:23.4,36:24.6,38:25.1,40:25.0,42:24.8,44:24.5,46:24.6,48:24.4,50:24.6,52:25.0,54:25.9,56:26.4,58:27.1,60:28.0,62:28.5,64:29.4,66:30.4,68:31.5,70:32.5,72:33.1,74:33.6,76:33.9,78:34.1,80:34.1,82:34.0,84:33.9,86:33.7,88:33.6,90:33.6,92:33.6,94:33.7,96:34.0,98:35.5,100:38.5,102:39.8,104:42.6},'Long':{0:-18.4,2:-19.4,4:-20.9,6:-21.4,8:-22.7,10:-24.7,12:-25.5,14:-26.7,16:-27.8,18:-30.2,20:-33.2,22:-35.9,24:-38.7,26:-41.0,28:-42.5,30:-43.9,32:-45.7,34:-47.2,36:-48.6,38:-49.8,40:-51.8,42:-53.2,44:-54.3,46:-55.2,48:-56.3,50:-57.7,52:-60.0,54:-62.4,56:-64.6,58:-66.2,60:-67.9,62:-69.5,64:-70.7,66:-71.8,68:-73.2,70:-74.3,72:-75.1,74:-76.0,76:-76.4,78:-77.2,80:-77.9,82:-78.4,84:-78.8,86:-79.3,88:-79.5,90:-79.8,92:-80.1,94:-80.8,96:-81.8,98:-82.1,100:-82.9,102:-80.2,104:-71.9}}
df = pd.DataFrame.from_dict(data)
gdf = gpd.GeoDataFrame(df, geometry=gpd.points_from_xy(x=df.Long,y=df.Lat), crs='wgs84')
newCrs = ccrs.RotatedPole(pole_latitude=37.5, pole_longitude=177.5)
gdf_proj = gdf.to_crs(newCrs)
ax = gdf_proj.plot(figsize=(20,8))
minx, miny, maxx, maxy = gdf_proj.total_bounds
ax.set_xlim(minx-50, maxx+75)
ax.set_ylim(miny-50, maxy+75)
ctx.add_basemap(ax, crs=gdf_proj.crs.to_string(), source=ctx.providers.Stamen.TonerLite)
一般tips/comments
- 您根本不需要翻转经度坐标。
- 你检查过Matplotlib/Cartopy是否有任何问题吗？
- 如果你有 Proj4 定义字符串，如果使用 GeoPandas，你甚至不需要 cartopy。在这种情况下，
newCrs 变量将变为 newCrs = '+ellps=WGS84 +a=6378137.0 +proj=ob_tran +o_proj=latlon +o_lon_p=0.0 +o_lat_p=37.5 +lon_0=357.5 +to_meter=111319.4907932736 +no_defs'.
- 您可能应该清理 Pandas DataFrame 的使用，不真正推荐将字典存储在 Dataframe 的列中，这可能会让您的生活更加困难。
我有飓风的轨迹
但是，当我使用非常规投影时，飓风的位置是关闭的。它从北美东部开始，然后向西穿越这片土地。这是为什么？
这是我的尝试方法
data = {'Lat':{0:12.9,2:12.9,4:13.2,6:13.6,8:13.7,10:13.8,12:14.2,14:14.5,16:14.8,18:16.0,20:17.0,22:17.9,24:18.3,26:18.9,28:19.7,30:20.7,32:22.0,34:23.4,36:24.6,38:25.1,40:25.0,42:24.8,44:24.5,46:24.6,48:24.4,50:24.6,52:25.0,54:25.9,56:26.4,58:27.1,60:28.0,62:28.5,64:29.4,66:30.4,68:31.5,70:32.5,72:33.1,74:33.6,76:33.9,78:34.1,80:34.1,82:34.0,84:33.9,86:33.7,88:33.6,90:33.6,92:33.6,94:33.7,96:34.0,98:35.5,100:38.5,102:39.8,104:42.6},'Long':{0:-18.4,2:-19.4,4:-20.9,6:-21.4,8:-22.7,10:-24.7,12:-25.5,14:-26.7,16:-27.8,18:-30.2,20:-33.2,22:-35.9,24:-38.7,26:-41.0,28:-42.5,30:-43.9,32:-45.7,34:-47.2,36:-48.6,38:-49.8,40:-51.8,42:-53.2,44:-54.3,46:-55.2,48:-56.3,50:-57.7,52:-60.0,54:-62.4,56:-64.6,58:-66.2,60:-67.9,62:-69.5,64:-70.7,66:-71.8,68:-73.2,70:-74.3,72:-75.1,74:-76.0,76:-76.4,78:-77.2,80:-77.9,82:-78.4,84:-78.8,86:-79.3,88:-79.5,90:-79.8,92:-80.1,94:-80.8,96:-81.8,98:-82.1,100:-82.9,102:-80.2,104:-71.9}}
df = pd.DataFrame.from_dict(data)
# Invert longitude for plotting in western Hemisphere
df['Long'] = df['Long'] * -1
newCrs = ccrs.RotatedPole(pole_latitude=37.5, pole_longitude=177.5)
fig = plt.figure(figsize=(20, 10))
ax = plt.subplot(projection = newCrs)
ax.coastlines(resolution = '110m')
ax.scatter(df['Long'], df['Lat'], color = 'red', transform = newCrs)
问题是 ax.scatter 中的 transform 关键字应该是 DATA CRS。因此，假设您的 indata 与 PlateCarree crs 没问题：
df = pd.DataFrame(dict(Lat=[i for i in data['Lat'].values()], Long=[i for i in data['Long'].values()]))
newCrs = ccrs.RotatedPole(pole_latitude=37.5, pole_longitude=177.5)
dataCrs = ccrs.PlateCarree()
fig = plt.figure(figsize=(20, 10))
ax = plt.axes(projection = newCrs)
ax.set_global()
ax.coastlines()
ax.scatter(df['Long'], df['Lat'], color = 'red', transform = dataCrs)
给出：
请阅读 this page explaining transforms 了解详细信息和教程。
备选方案（推荐GeoPandas）
也许不能直接回答你的问题，但如果我通过 GeoPandas（强烈推荐），我似乎没有遇到任何问题：
import pandas as pd
import geopandas as gpd
import contextily as ctx
import cartopy.crs as ccrs
data = {'Lat':{0:12.9,2:12.9,4:13.2,6:13.6,8:13.7,10:13.8,12:14.2,14:14.5,16:14.8,18:16.0,20:17.0,22:17.9,24:18.3,26:18.9,28:19.7,30:20.7,32:22.0,34:23.4,36:24.6,38:25.1,40:25.0,42:24.8,44:24.5,46:24.6,48:24.4,50:24.6,52:25.0,54:25.9,56:26.4,58:27.1,60:28.0,62:28.5,64:29.4,66:30.4,68:31.5,70:32.5,72:33.1,74:33.6,76:33.9,78:34.1,80:34.1,82:34.0,84:33.9,86:33.7,88:33.6,90:33.6,92:33.6,94:33.7,96:34.0,98:35.5,100:38.5,102:39.8,104:42.6},'Long':{0:-18.4,2:-19.4,4:-20.9,6:-21.4,8:-22.7,10:-24.7,12:-25.5,14:-26.7,16:-27.8,18:-30.2,20:-33.2,22:-35.9,24:-38.7,26:-41.0,28:-42.5,30:-43.9,32:-45.7,34:-47.2,36:-48.6,38:-49.8,40:-51.8,42:-53.2,44:-54.3,46:-55.2,48:-56.3,50:-57.7,52:-60.0,54:-62.4,56:-64.6,58:-66.2,60:-67.9,62:-69.5,64:-70.7,66:-71.8,68:-73.2,70:-74.3,72:-75.1,74:-76.0,76:-76.4,78:-77.2,80:-77.9,82:-78.4,84:-78.8,86:-79.3,88:-79.5,90:-79.8,92:-80.1,94:-80.8,96:-81.8,98:-82.1,100:-82.9,102:-80.2,104:-71.9}}
df = pd.DataFrame.from_dict(data)
gdf = gpd.GeoDataFrame(df, geometry=gpd.points_from_xy(x=df.Long,y=df.Lat), crs='wgs84')
newCrs = ccrs.RotatedPole(pole_latitude=37.5, pole_longitude=177.5)
gdf_proj = gdf.to_crs(newCrs)
ax = gdf_proj.plot(figsize=(20,8))
minx, miny, maxx, maxy = gdf_proj.total_bounds
ax.set_xlim(minx-50, maxx+75)
ax.set_ylim(miny-50, maxy+75)
ctx.add_basemap(ax, crs=gdf_proj.crs.to_string(), source=ctx.providers.Stamen.TonerLite)
一般tips/comments
- 您根本不需要翻转经度坐标。
- 你检查过Matplotlib/Cartopy是否有任何问题吗？
- 如果你有 Proj4 定义字符串，如果使用 GeoPandas，你甚至不需要 cartopy。在这种情况下，
newCrs变量将变为newCrs = '+ellps=WGS84 +a=6378137.0 +proj=ob_tran +o_proj=latlon +o_lon_p=0.0 +o_lat_p=37.5 +lon_0=357.5 +to_meter=111319.4907932736 +no_defs'. - 您可能应该清理 Pandas DataFrame 的使用，不真正推荐将字典存储在 Dataframe 的列中，这可能会让您的生活更加困难。