5

我有一组定义区域边界的经纬度点。我想根据这些点创建一个多边形并在地图上绘制多边形并填充它。目前,我的多边形似乎由许多连接所有点的补丁组成,但是点的顺序不正确,当我尝试填充多边形时,我得到一个看起来很奇怪的区域(见附件)。黑点表示边界点的位置

我根据多边形的中心对经纬度点(mypolyXY 数组)进行排序,但我的猜测是这是不正确的:

cent=(np.sum([p[0] for p in mypolyXY])/len(mypolyXY),np.sum([p[1] for p in mypolyXY])/len(mypolyXY))
# sort by polar angle
mypolyXY.sort(key=lambda p: math.atan2(p[1]-cent[1],p[0]-cent[0]))

我绘制点位置(黑色圆圈)和我的多边形(彩色补丁)使用

scatter([p[0] for p in mypolyXY],[p[1] for p in mypolyXY],2)
p = Polygon(mypolyXY,facecolor=colors,edgecolor='none')
ax.add_artist(p)

我的问题是:如何根据我的经纬度点数组关闭我的多边形?

更新: 我对如何绘制多边形进行了更多测试。我删除了排序例程,只是按照它们在文件中出现的顺序使用数据。这似乎改善了结果,但正如@tcaswell 所提到的,多边形形状仍然会削弱自身(参见新图)。我希望有一个路径/多边形例程可以解决我的问题,并在多边形边界内合并所有形状或路径。非常欢迎提出建议。

在此处输入图像描述

更新 2:

我现在有一个基于@Rutger Kassies 和 Roland Smith 建议的脚本的工作版本。我最终使用 org 阅读了 Shapefile,它的效果相对较好。它适用于标准 lmes_64.shp 文件,但是当我使用更详细的 LME 文件时,每个 LME 可能由多个多边形组成,这个脚本就崩溃了。我必须找到一种方法来合并具有相同 LME 名称的各种多边形才能使其工作。我附上了我最终得到的脚本,以防有人看它。我非常感谢有关如何改进此脚本或使其更通用的评论。该脚本在我从 netcdf 文件中读取的多边形区域内创建多边形并提取数据。输入文件的网格为 -180 到 180 和 -90 到 90。

import numpy as np
import math
from pylab import *
import matplotlib.patches as patches
import string, os, sys
import datetime, types
from netCDF4 import Dataset
import matplotlib.nxutils as nx
from mpl_toolkits.basemap import Basemap
import ogr
import matplotlib.path as mpath
import matplotlib.patches as patches


def getLMEpolygon(coordinatefile,mymap,index,first):

    ds = ogr.Open(coordinatefile)
    lyr = ds.GetLayer(0)
    numberOfPolygons=lyr.GetFeatureCount()

    if first is False:
        ft = lyr.GetFeature(index)
        print "Found polygon:",  ft.items()['LME_NAME']
        geom = ft.GetGeometryRef()

        codes = []
        all_x = []
        all_y = []
        all_XY= []

        if (geom.GetGeometryType() == ogr.wkbPolygon):
          for i in range(geom.GetGeometryCount()):

            r = geom.GetGeometryRef(i)
            x = [r.GetX(j) for j in range(r.GetPointCount())]
            y = [r.GetY(j) for j in range(r.GetPointCount())]

            codes += [mpath.Path.MOVETO] + (len(x)-1)*[mpath.Path.LINETO]
            all_x += x
            all_y += y
            all_XY +=mymap(x,y)


        if len(all_XY)==0:
            all_XY=None
            mypoly=None
        else:
            mypoly=np.empty((len(all_XY[:][0]),2))
            mypoly[:,0]=all_XY[:][0]
            mypoly[:,1]=all_XY[:][3]
    else:
        print "Will extract data for %s polygons"%(numberOfPolygons)
        mypoly=None
    first=False
    return mypoly, first, numberOfPolygons


def openCMIP5file(CMIP5name,myvar,mymap):
    if os.path.exists(CMIP5name):
        myfile=Dataset(CMIP5name)
        print "Opened CMIP5 file: %s"%(CMIP5name)
    else:
        print "Could not find CMIP5 input file %s : abort"%(CMIP5name)
        sys.exit()
    mydata=np.squeeze(myfile.variables[myvar][-1,:,:]) - 273.15
    lonCMIP5=np.squeeze(myfile.variables["lon"][:])
    latCMIP5=np.squeeze(myfile.variables["lat"][:])

    lons,lats=np.meshgrid(lonCMIP5,latCMIP5)

    lons=lons.flatten()
    lats=lats.flatten()
    mygrid=np.empty((len(lats),2))
    mymapgrid=np.empty((len(lats),2))

    for i in xrange(len(lats)):
        mygrid[i,0]=lons[i]
        mygrid[i,1]=lats[i]
        X,Y=mymap(lons[i],lats[i])
        mymapgrid[i,0]=X
        mymapgrid[i,1]=Y

    return mydata, mygrid, mymapgrid

def drawMap(NUM_COLORS):

    ax = plt.subplot(111)
    cm = plt.get_cmap('RdBu')
    ax.set_color_cycle([cm(1.*j/NUM_COLORS) for j in range(NUM_COLORS)])
    mymap = Basemap(resolution='l',projection='robin',lon_0=0)

    mymap.drawcountries()

    mymap.drawcoastlines()
    mymap.fillcontinents(color='grey',lake_color='white')
    mymap.drawparallels(np.arange(-90.,120.,30.))
    mymap.drawmeridians(np.arange(0.,360.,60.))
    mymap.drawmapboundary(fill_color='white')

    return ax, mymap, cm

"""Edit the correct names below:"""

LMEcoordinatefile='ShapefileBoundaries/lmes_64.shp'
CMIP5file='tos_Omon_CCSM4_rcp85_r1i1p1_200601-210012_regrid.nc'

mydebug=False
doPoints=False
first=True


"""initialize the map:"""
mymap=None
mypolyXY, first, numberOfPolygons = getLMEpolygon(LMEcoordinatefile, mymap, 0,first)
NUM_COLORS=numberOfPolygons
ax, mymap, cm = drawMap(NUM_COLORS)


"""Get the CMIP5 data together with the grid"""
SST,mygrid, mymapgrid = openCMIP5file(CMIP5file,"tos",mymap)

"""For each LME of interest create a polygon of coordinates defining the boundaries"""
for counter in xrange(numberOfPolygons-1):

    mypolyXY,first,numberOfPolygons = getLMEpolygon(LMEcoordinatefile, mymap,counter,first)

    if mypolyXY != None:
        """Find the indices inside the grid that are within the polygon"""
        insideBoolean = plt.mlab.inside_poly(np.c_[mymapgrid[:,0],mymapgrid[:,1]],np.c_[mypolyXY[:,0],mypolyXY[:,1]])
        SST=SST.flatten()
        SST=np.ma.masked_where(SST>50,SST)

        mymapgrid=np.c_[mymapgrid[:,0],mymapgrid[:,1]]
        myaverageSST=np.mean(SST[insideBoolean])

        mycolor=cm(myaverageSST/SST.max())
        scaled_z = (myaverageSST - SST.min()) / SST.ptp()
        colors = plt.cm.coolwarm(scaled_z)

        scatter([p[0] for p in mypolyXY],[p[1] for p in mypolyXY],2)

        p = Polygon(mypolyXY,facecolor=colors,edgecolor='none')
        ax.add_artist(p)

        if doPoints is True:

            for point in xrange(len(insideBoolean)):
                pointX=mymapgrid[insideBoolean[point],0]
                pointY=mymapgrid[insideBoolean[point],1]
                ax.scatter(pointX,pointY,8,color=colors)
                ax.hold(True)


if doPoints is True:
    colorbar()
print "Extracted average values for %s LMEs"%(numberOfPolygons)
plt.savefig('LMEs.png',dpi=300)
plt.show()

附上最终图像。感谢所有帮助。

在此处输入图像描述 干杯,特隆德

4

3 回答 3

3

拥有一系列点是不够的。您需要知道点的顺序。通常,多边形的点是按顺序给出的。所以你从第一个点到第二个点画一条线,然后从第二个点到第三个点等等。

如果您的列表不是按顺序排列的,您需要额外的信息才能制作一个按顺序排列的列表。

shapefile(请参阅文档)包含形状列表,例如 Null 形状、Point、PolyLine、Polygon,其变体还包含 Z 和 M(测量)坐标。因此,仅倾倒积分是行不通的。您必须将它们分成不同的形状并渲染您感兴趣的形状。在这种情况下,可能是折线或多边形。有关这些形状的数据格式,请参见上面的链接。请记住,文件的某些部分是 big-endian,而其他部分是 little-endian。真是一团糟。

我建议使用struct模块来解析二进制.shp文件,因为再次根据文档,单个 Polygon 的点有序的,它们形成一个闭合链(最后一个点与第一个相同)。

您可以使用当前坐标列表尝试的另一件事是从一个点开始,然后在列表中进一步查找相同的点。这些相同点之间的一切都应该是一个多边形。这可能不是万无一失的,但看看它能让你走多远。

于 2013-05-01T20:48:22.213 回答
2

这里有一篇关于 shapefile 和底图的博客文章:http ://www.geophysique.be/2013/02/12/matplotlib-basemap-tutorial-10-shapefiles-unleached-continued/

如果您热衷于尝试,cartopy也可能是一种选择。从 shapefile 绘制数据被设计得相当容易:

import matplotlib.pyplot as plt

import cartopy.crs as ccrs
import cartopy.io.shapereader as shpreader

# pick a shapefile - Cartopy makes it easy to access Natural Earth
# shapefiles, but it could be anything
shapename = 'admin_1_states_provinces_lakes_shp'
states_shp = shpreader.natural_earth(resolution='110m',
                                      category='cultural', name=shapename)

.

# states_shp is just a filename to a shapefile
>>> print states_shp
/Users/pelson/.local/share/cartopy/shapefiles/natural_earth/cultural/110m_admin_1_states_provinces_lakes_shp.shp

.

# Create the mpl axes of a PlateCarree map
ax = plt.axes(projection=ccrs.PlateCarree())

# Read the shapes from the shapefile into a list of shapely geometries.
geoms = shpreader.Reader(states_shp).geometries()

# Add the shapes in the shapefile to the axes
ax.add_geometries(geoms, ccrs.PlateCarree(),
                  facecolor='coral', edgecolor='black')

plt.show()

输出

于 2013-05-03T21:11:27.620 回答
2

我建议使用原始的 Shapefile,它的格式适合存储多边形。作为 OGR 的替代方案,您可以使用 Shapely,或将多边形导出到 Wkt 等。

import ogr
import matplotlib.path as mpath
import matplotlib.patches as patches
import matplotlib.pyplot as plt

ds = ogr.Open('lmes_64.shp')
lyr = ds.GetLayer(0)
ft = lyr.GetFeature(38)
geom = ft.GetGeometryRef()
ds = None

codes = []
all_x = []
all_y = []

if (geom.GetGeometryType() == ogr.wkbPolygon):
  for i in range(geom.GetGeometryCount()):

    r = geom.GetGeometryRef(i)
    x = [r.GetX(j) for j in range(r.GetPointCount())]
    y = [r.GetY(j) for j in range(r.GetPointCount())]

    codes += [mpath.Path.MOVETO] + (len(x)-1)*[mpath.Path.LINETO]
    all_x += x
    all_y += y

if (geom.GetGeometryType() == ogr.wkbMultiPolygon):
  codes = []
  for i in range(geom.GetGeometryCount()):
    # Read ring geometry and create path
    r = geom.GetGeometryRef(i)
    for part in r:
      x = [part.GetX(j) for j in range(part.GetPointCount())]
      y = [part.GetY(j) for j in range(part.GetPointCount())]
      # skip boundary between individual rings
      codes += [mpath.Path.MOVETO] + (len(x)-1)*[mpath.Path.LINETO]
      all_x += x
      all_y += y

carib_path = mpath.Path(np.column_stack((all_x,all_y)), codes)    
carib_patch = patches.PathPatch(carib_path, facecolor='orange', lw=2)

poly1 = patches.Polygon([[-80,20],[-75,20],[-75,15],[-80,15],[-80,20]], zorder=5, fc='none', lw=3)
poly2 = patches.Polygon([[-65,25],[-60,25],[-60,20],[-65,20],[-65,25]], zorder=5, fc='none', lw=3)


fig, ax = plt.subplots(1,1)

for poly in [poly1, poly2]:
    if carib_path.intersects_path(poly.get_path()):
        poly.set_edgecolor('g')
    else:
        poly.set_edgecolor('r')

    ax.add_patch(poly)

ax.add_patch(carib_patch)
ax.autoscale_view()

在此处输入图像描述

如果您想要非常简单的 Shapefile 处理,还可以查看Fiona(OGR 的包装器)。

于 2013-05-02T13:59:53.303 回答