在 Windows 上使用 Python 3.5 Anaconda 的底图
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Basemap with Python 3.5 Anaconda on Windows
提问by Prikers
I use Python 3.5 with latest version of Anaconda on Windows (64 bit). I wanted to install Basemap using conda install basemap. Apparently there is a conflict between Python 3 and basemap. After some googling indeed I found that basemap is not supported on Python 3 for Windows users (ex: https://groups.google.com/a/continuum.io/forum/#!topic/anaconda/TjAwi3ilQaU).
我在 Windows（64 位）上使用 Python 3.5 和最新版本的 Anaconda。我想使用conda install basemap. 显然 Python 3 和底图之间存在冲突。经过一番谷歌搜索后，我发现 Windows 用户的 Python 3 不支持底图（例如：https: //groups.google.com/a/continuum.io/forum/#!topic/anaconda/ TjAwi3ilQaU）。
For obvious reasons I do not want to downgrade to Python 2. What would then be the simplest alternative solution?
出于显而易见的原因，我不想降级到 Python 2。那么最简单的替代解决方案是什么？
- Is there an alternative package similar to basemap for ploting maps, etc.?
- Should I use a second environment which uses Python 2 and basemap? I have never done that but it seems possible (http://conda.pydata.org/docs/py2or3.html). Is it "safe"? Should I install again all the other packages (matplotlib, numpy, etc.) on the second environment?
- 是否有类似于用于绘制地图等的底图的替代包？
- 我应该使用使用 Python 2 和底图的第二个环境吗？我从未这样做过，但似乎有可能（http://conda.pydata.org/docs/py2or3.html）。它“安全”吗？我是否应该在第二个环境中再次安装所有其他包（matplotlib、numpy 等）？
Thanks in advance for the help and advice.
在此先感谢您的帮助和建议。
采纳答案by Paco Lopez Dekker
I have solved this several times (last time just now) by downloading it from http://www.lfd.uci.edu/~gohlke/pythonlibsand follow the instructions to install. From the anaconda command prompt
我已经通过从http://www.lfd.uci.edu/~gohlke/pythonlibs下载 并按照说明进行安装解决了这个问题好几次（上次刚刚） 。从 anaconda 命令提示符
pip install full_path_to_package
pip install full_path_to_package
For example, if you downloaded basemap-1.1.0-cp36-cp36m-win_amd64.whl, you would run
例如，如果您下载了 basemap-1.1.0-cp36-cp36m-win_amd64.whl，您将运行
pip install C:\path\to\file\basemap-1.1.0-cp36-cp36m-win_amd64.whl
pip install C:\path\to\file\basemap-1.1.0-cp36-cp36m-win_amd64.whl
Note that the python version of the .whl file must match your python version. For example, ...-cp36-....indicates Python 3.6. You can find your python version by running the command python --version.
请注意，.whl 文件的 python 版本必须与您的 python 版本匹配。例如，...-cp36-....表示 Python 3.6。您可以通过运行命令找到您的 python 版本python --version。
回答by kalinfirst
Referring to the answer of Solly, I have Windows 10, python 3.5.3, Anaconda 64bit, in the Anaconda prompt I entered:
参考Solly的回答，我有Windows 10，python 3.5.3，Anaconda 64bit，在我输入的Anaconda提示中：
conda install -c conda-forge basemap=1.0.8.dev0
conda install -c conda-forge basemap-data-hires
then the code, taken from Python for Data Science for Dummies, page 193 (Plotting geographical data worked just fine. I wanted to add just a comment to the Solly's answer, but I don't have enough credits to do so. The code is:
然后是代码，取自Python for Data Science for Dummies，第 193 页（绘制地理数据工作得很好。我只想在 Solly 的答案中添加一条评论，但我没有足够的学分来这样做。代码是：
import numpy as np
import matplotlib.pyplot as plt
from mpl_toolkits.basemap import Basemap
austin = (-97.75, 30.25)
hawaii = (-157.8, 21.3)
washington = (-77.01, 38.90)
chicago = (-87.68, 41.83)
losangeles = (-118.25, 34.05)
m = Basemap(projection = 'merc', llcrnrlat=10, urcrnrlat=50,
llcrnrlon=-160, urcrnrlon=-60)
m.drawcoastlines()
m.fillcontinents (color='lightgray', lake_color='lightblue')
m.drawparallels(np.arange(-90.,91.,30.))
m.drawmeridians(np.arange(-180.,181.,60.))
m.drawmapboundary(fill_color='aqua')
m.drawcounties()
x, y = m(*zip(*[hawaii, austin, washington, chicago, losangeles]))
m.plot(x,y, marker ='o', markersize=6, markerfacecolor='red', linewidth=0)
plt.title('Mercator Projection')
plt.show()
回答by Solly
回答by onewhaleid
Cartopy is an alternative to Basemap, and it is being actively developed.
Cartopy 是 Basemap 的替代品，并且正在积极开发中。
There is a nice gallery here: http://scitools.org.uk/cartopy/docs/latest/gallery.html
这里有一个不错的画廊：http: //scitools.org.uk/cartopy/docs/latest/gallery.html
回答by Madhu Mohan Kommu
回答by Mat Moon
Truth be told I had the same problem and tried to fix it for waaay to long and even tried a python 2 environment with no luck.
说实话，我遇到了同样的问题，并试图修复它很长时间，甚至尝试了一个没有运气的 python 2 环境。
Personally just using a python 2 install was way easier and less time consuming. Sorry for the non answer.
就个人而言，仅使用 python 2 安装更容易且耗时更少。抱歉没有回答。
