Python 不带河流的世界地图，带matplotlib/Basemap？

有没有一种方法可以用底图（或者没有底图，如果有其他方法的话）来绘制大陆的边界，而不需要那些令人讨厌的河流？尤其是那片连大海都没有到达的Kongo河，令人不安

编辑：我打算在地图上进一步绘制数据，如图中所示（在数据上仍将大陆的边界绘制为黑线，以给出世界地图的结构），因此，尽管下面的Hooked解决方案很好，甚至很精通，但它不适用于此目的

图片制作人：

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

fig = plt.figure(figsize=(8, 4.5))
plt.subplots_adjust(left=0.02, right=0.98, top=0.98, bottom=0.00)
m = Basemap(projection='robin',lon_0=0,resolution='c')
m.fillcontinents(color='gray',lake_color='white')
m.drawcoastlines()
plt.savefig('world.png',dpi=75)

如何清除“讨厌的”河流： 如果要对图像进行后处理（而不是直接使用底图），可以删除与海洋不相连的水体：

import pylab as plt
A = plt.imread("world.png")

import numpy as np
import scipy.ndimage as nd
import collections

# Get a counter of the greyscale colors
a      = A[:,:,0]
colors = collections.Counter(a.ravel())
outside_and_water_color, land_color = colors.most_common(2)

# Find the contigous landmass
land_idx = a == land_color[0]

# Index these land masses
L = np.zeros(a.shape,dtype=int) 
L[land_idx] = 1
L,mass_count = nd.measurements.label(L)

# Loop over the land masses and fill the "holes"
# (rivers without outlays)
L2 = np.zeros(a.shape,dtype=int) 
L2[land_idx] = 1
L2 = nd.morphology.binary_fill_holes(L2)

# Remap onto original image
new_land = L2==1
A2 = A.copy()
c = [land_color[0],]*3 + [1,]
A2[new_land] = land_color[0]

# Plot results
plt.subplot(221)
plt.imshow(A)
plt.axis('off')

plt.subplot(222)
plt.axis('off')
B = A.copy()
B[land_idx] = [1,0,0,1]
plt.imshow(B)

plt.subplot(223)
L = L.astype(float)
L[L==0] = None
plt.axis('off')
plt.imshow(L)

plt.subplot(224)
plt.axis('off')
plt.imshow(A2)

plt.tight_layout()  # Only with newer matplotlib
plt.show()

---

第一个图像是原始图像，第二个图像识别地块。第三个不是必需的，而是有趣的，因为它是每个独立的连续大陆。第四张图片是您想要的，删除了“rivers”的图像。

出于这样的原因，我经常一起避免使用Basemap，并使用OGR阅读shapefile，然后将它们转换为Matplotlib艺术家。这是更多的工作，但也提供了更多的灵活性

Basemap有一些非常简洁的特性，比如将输入数据的坐标转换为“工作投影”

如果你想坚持使用Basemap，那就得到一个不包含河流的shapefile。例如，自然地球在物理部分有一个漂亮的“陆地”形状文件（下载“等级”数据并解压缩）。看

您可以使用Basemap中的m.readshapefile（）方法在中读取shapefile。这允许您在投影坐标中获取Matplotlib路径顶点和代码，然后将其转换为新路径。这有点绕道，但它为您提供了Matplotlib中的所有样式选项，其中大多数选项无法通过Basemap直接提供。这有点老土，但我现在不想在坚持基本地图的同时用另一种方式

因此：

给出：

---

好的，我想我有一个部分解决方案

其基本思想是DrawCo岸线（）使用的路径按大小/面积排序。这意味着前N条路径（在大多数应用中）是主要的陆地和湖泊，后一条路径是较小的岛屿和河流

问题是，如果应用了区域阈值，您想要的前N条路径将取决于投影（例如，全局、极性、区域），以及您想要的是湖泊还是小岛等。换句话说，您必须根据应用调整此路径

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

mp = 'cyl'
m = Basemap(resolution='c',projection=mp,lon_0=0,area_thresh=200000)

fill_color = '0.9'

# If you don't want lakes set lake_color to fill_color
m.fillcontinents(color=fill_color,lake_color='white')

# Draw the coastlines, with a thin line and same color as the continent fill.
coasts = m.drawcoastlines(zorder=100,color=fill_color,linewidth=0.5)

# Exact the paths from coasts
coasts_paths = coasts.get_paths()

# In order to see which paths you want to retain or discard you'll need to plot them one
# at a time noting those that you want etc. 
for ipoly in xrange(len(coasts_paths)):
    print ipoly
    r = coasts_paths[ipoly]
    # Convert into lon/lat vertices
    polygon_vertices = [(vertex[0],vertex[1]) for (vertex,code) in
                        r.iter_segments(simplify=False)]
    px = [polygon_vertices[i][0] for i in xrange(len(polygon_vertices))]
    py = [polygon_vertices[i][1] for i in xrange(len(polygon_vertices))]
    m.plot(px,py,'k-',linewidth=1)
    plt.show()

一旦你知道相关的ipoly停止绘制（poly_stop），你就可以这样做

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

mproj = ['nplaea','cyl']
mp = mproj[0]

if mp == 'nplaea':
    m = Basemap(resolution='c',projection=mp,lon_0=0,boundinglat=30,area_thresh=200000,round=1)
    poly_stop = 10
else:
    m = Basemap(resolution='c',projection=mp,lon_0=0,area_thresh=200000)
    poly_stop = 18
fill_color = '0.9'

# If you don't want lakes set lake_color to fill_color
m.fillcontinents(color=fill_color,lake_color='white')

# Draw the coastlines, with a thin line and same color as the continent fill.
coasts = m.drawcoastlines(zorder=100,color=fill_color,linewidth=0.5)

# Exact the paths from coasts
coasts_paths = coasts.get_paths()

# In order to see which paths you want to retain or discard you'll need to plot them one
# at a time noting those that you want etc. 
for ipoly in xrange(len(coasts_paths)):
    if ipoly > poly_stop: continue
    r = coasts_paths[ipoly]
    # Convert into lon/lat vertices
    polygon_vertices = [(vertex[0],vertex[1]) for (vertex,code) in
                        r.iter_segments(simplify=False)]
    px = [polygon_vertices[i][0] for i in xrange(len(polygon_vertices))]
    py = [polygon_vertices[i][1] for i in xrange(len(polygon_vertices))]
    m.plot(px,py,'k-',linewidth=1)
plt.show()

---

以用户1868739为例，我只能选择我想要的路径（对于某些湖泊）：

但这只适用于使用白色背景的大陆。如果我在下一行中将

颜色

更改为

灰色

，我们会看到其他河流和湖泊的颜色与大陆的颜色不同。（同样，玩

区域_thresh

也不会移除与海洋相连的河流。）

---

白色背景的版本足以进一步彩色绘制大陆上的各种陆地信息，但如果想要保留大陆的灰色背景，则需要更详细的解决方案。

根据我对@sampo smolander的评论

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

fig = plt.figure(figsize=(8, 4.5))
plt.subplots_adjust(left=0.02, right=0.98, top=0.98, bottom=0.00)
m = Basemap(resolution='c',projection='robin',lon_0=0)
m.fillcontinents(color='gray',lake_color='white',zorder=2)
coasts = m.drawcoastlines(zorder=1,color='white',linewidth=0)
coasts_paths = coasts.get_paths()

ipolygons = range(83) + [84]
for ipoly in xrange(len(coasts_paths)):
    r = coasts_paths[ipoly]
    # Convert into lon/lat vertices
    polygon_vertices = [(vertex[0],vertex[1]) for (vertex,code) in
                        r.iter_segments(simplify=False)]
    px = [polygon_vertices[i][0] for i in xrange(len(polygon_vertices))]
    py = [polygon_vertices[i][1] for i in xrange(len(polygon_vertices))]
    if ipoly in ipolygons:
        m.plot(px,py,linewidth=0.5,zorder=3,color='black')
    else:
        m.plot(px,py,linewidth=0.5,zorder=4,color='grey')
plt.savefig('world2.png',dpi=100)

---

如果您对绘制轮廓线而不是形状文件没有意见，那么绘制从任何地方都可以得到的海岸线都非常容易。我从NOAA海岸线提取程序中以MATLAB格式获取了我的海岸线：

为了编辑海岸线，我转换成SVG，然后用Inkscape编辑它们，然后转换回lat/lon文本文件（“MATLAB”格式）

下面包含了所有Python代码

# ---------------------------------------------------------------
def plot_lines(mymap, lons, lats, **kwargs) :
    """Plots a custom coastline.  This plots simple lines, not
    ArcInfo-style SHAPE files.

    Args:
        lons: Longitude coordinates for line segments (degrees E)
        lats: Latitude coordinates for line segments (degrees N)

    Type Info:
        len(lons) == len(lats)
        A NaN in lons and lats signifies a new line segment.

    See:
        giss.noaa.drawcoastline_file()
    """

    # Project onto the map
    x, y = mymap(lons, lats)

    # BUG workaround: Basemap projects our NaN's to 1e30.
    x[x==1e30] = np.nan
    y[y==1e30] = np.nan

    # Plot projected line segments.
    mymap.plot(x, y, **kwargs)


# Read "Matlab" format files from NOAA Coastline Extractor.
# See: http://www.ngdc.noaa.gov/mgg/coast/

lineRE=re.compile('(.*?)\s+(.*)')
def read_coastline(fname, take_every=1) :
    nlines = 0
    xdata = array.array('d')
    ydata = array.array('d')
    for line in file(fname) :
#        if (nlines % 10000 == 0) :
#            print 'nlines = %d' % (nlines,)
        if (nlines % take_every == 0 or line[0:3] == 'nan') :
            match = lineRE.match(line)
            lon = float(match.group(1))
            lat = float(match.group(2))

            xdata.append(lon)
            ydata.append(lat)
        nlines = nlines + 1


    return (np.array(xdata),np.array(ydata))

def drawcoastline_file(mymap, fname, **kwargs) :
    """Reads and plots a coastline file.
    See:
        giss.basemap.drawcoastline()
        giss.basemap.read_coastline()
    """

    lons, lats = read_coastline(fname, take_every=1)
    return drawcoastline(mymap, lons, lats, **kwargs)
# =========================================================
# coastline2svg.py
#
import giss.io.noaa
import os
import numpy as np
import sys

svg_header = """<?xml version="1.0" encoding="UTF-8" standalone="no"?>
<!-- Created with Inkscape (http://www.inkscape.org/) -->

<svg
   xmlns:dc="http://purl.org/dc/elements/1.1/"
   xmlns:cc="http://creativecommons.org/ns#"
   xmlns:rdf="http://www.w3.org/1999/02/22-rdf-syntax-ns#"
   xmlns:svg="http://www.w3.org/2000/svg"
   xmlns="http://www.w3.org/2000/svg"
   version="1.1"
   width="360"
   height="180"
   id="svg2">
  <defs
     id="defs4" />
  <metadata
     id="metadata7">
    <rdf:RDF>
      <cc:Work
         rdf:about="">
        <dc:format>image/svg+xml</dc:format>
        <dc:type
           rdf:resource="http://purl.org/dc/dcmitype/StillImage" />
        <dc:title></dc:title>
      </cc:Work>
    </rdf:RDF>
  </metadata>
  <g
     id="layer1">
"""

path_tpl = """
    <path
       d="%PATH%"
       id="%PATH_ID%"
       style="fill:none;stroke:#000000;stroke-width:1px;stroke-linecap:butt;stroke-linejoin:miter;stroke-opacity:1"
"""

svg_footer = "</g></svg>"




# Set up paths
data_root = os.path.join(os.environ['HOME'], 'data')
#modelerc = giss.modele.read_modelerc()
#cmrun = modelerc['CMRUNDIR']
#savedisk = modelerc['SAVEDISK']

ifname = sys.argv[1]
ofname = ifname.replace('.dat', '.svg')

lons, lats = giss.io.noaa.read_coastline(ifname, 1)

out = open(ofname, 'w')
out.write(svg_header)

path_id = 1
points = []
for lon, lat in zip(lons, lats) :
    if np.isnan(lon) or np.isnan(lat) :
        # Process what we have
        if len(points) > 2 :
            out.write('\n<path d="')
            out.write('m %f,%f L' % (points[0][0], points[0][1]))
            for pt in points[1:] :
                out.write(' %f,%f' % pt)
            out.write('"\n   id="path%d"\n' % (path_id))
#            out.write('style="fill:none;stroke:#000000;stroke-width:1px;stroke-linecap:butt;stroke-linejoin:miter;stroke-opacity:1"')
            out.write(' />\n')
            path_id += 1
        points = []
    else :
        lon += 180
        lat = 180 - (lat + 90)
        points.append((lon, lat))


out.write(svg_footer)
out.close()

# =============================================================
# svg2coastline.py

import os
import sys
import re

# Reads the output of Inkscape's "Plain SVG" format, outputs in NOAA MATLAB coastline format

mainRE = re.compile(r'\s*d=".*"')
lineRE = re.compile(r'\s*d="(m|M)\s*(.*?)"')

fname = sys.argv[1]


lons = []
lats = []
for line in open(fname, 'r') :
    # Weed out extraneous lines in the SVG file
    match = mainRE.match(line)
    if match is None :
        continue

    match = lineRE.match(line)

    # Stop if something is wrong
    if match is None :
        sys.stderr.write(line)
        sys.exit(-1)

    type = match.group(1)[0]
    spairs = match.group(2).split(' ')
    x = 0
    y = 0
    for spair in spairs :
        if spair == 'L' :
            type = 'M'
            continue

        (sdelx, sdely) = spair.split(',')
        delx = float(sdelx)
        dely = float(sdely)
        if type == 'm' :
            x += delx
            y += dely
        else :
            x = delx
            y = dely
        lon = x - 180
        lat = 90 - y
        print '%f\t%f' % (lon, lat)
    print 'nan\tnan'

#---------------------------------------------------------------
def绘图线（mymap、lons、lats、**kwargs）：
“”“绘制自定义海岸线。这将绘制简单的线，而不是
ArcInfo样式形状文件。
Args：
lons：线段的经度坐标（E度）
lats：线段的纬度坐标（N度）
类型信息：
len（lons）=len（lats）
lons和lats中的NaN表示新线段。
见：
giss.noaa.drawCoasines_文件（）
"""
#投射到地图上
x、 y=我的地图（lons，lats）
#BUG解决方法：Basemap将我们的NaN投影到1e30。
x[x==1e30]=np.nan
y[y==1e30]=np.nan
#绘制投影线段。
mymap.绘图（x，y，**kwargs）
#从NOAA海岸线提取程序读取“Matlab”格式文件。
#见：http://www.ngdc.noaa.gov/mgg/coast/
lineRE=re.compile（'（.*）\s+（.*））
def read_海岸线（fname，take_every=1）：
nlines=0
扩展数据=数组。数组（'d'）
ydata=array.array（'d'）
对于文件中的行（fname）：
#如果（行%10000==0）：
#打印“nlines=%d%”（nlines，）
如果（行%take_every==0或行[0:3]==nan'）：
match=lineRE.match（行）
lon=浮动（匹配组（1））
lat=浮动（匹配组（2））
扩展数据追加（lon）
ydata.append（lat）
nlines=nlines+1
返回（np.array（扩展数据），np.array（ydata））
def DrawCoasines_文件（mymap、fname、**kwargs）：
“”“读取并绘制海岸线文件。
见：
giss.basemap.drawcoastline（）
giss.basemap.read_coastline（）
"""
lons，lats=读取海岸线（fname，take\u every=1）
返回绘制海岸线（mymap、lons、lats、**kwargs）
# =========================================================
#2svg.py
#
进口giss.io.noaa
导入操作系统
将numpy作为np导入
导入系统
svg_header=“”
image/svg+xml
"""
路径_tpl=“”
我经常修改Basemap的DrawCo岸线（）以避免那些“破碎”的河流。为了数据源的一致性，我还修改了drawcountries（）

H
m.fillcontinents(color='gray',lake_color='white',zorder=2)

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

fig = plt.figure(figsize=(8, 4.5))
plt.subplots_adjust(left=0.02, right=0.98, top=0.98, bottom=0.00)
m = Basemap(resolution='c',projection='robin',lon_0=0)
m.fillcontinents(color='gray',lake_color='white',zorder=2)
coasts = m.drawcoastlines(zorder=1,color='white',linewidth=0)
coasts_paths = coasts.get_paths()

ipolygons = range(83) + [84]
for ipoly in xrange(len(coasts_paths)):
    r = coasts_paths[ipoly]
    # Convert into lon/lat vertices
    polygon_vertices = [(vertex[0],vertex[1]) for (vertex,code) in
                        r.iter_segments(simplify=False)]
    px = [polygon_vertices[i][0] for i in xrange(len(polygon_vertices))]
    py = [polygon_vertices[i][1] for i in xrange(len(polygon_vertices))]
    if ipoly in ipolygons:
        m.plot(px,py,linewidth=0.5,zorder=3,color='black')
    else:
        m.plot(px,py,linewidth=0.5,zorder=4,color='grey')
plt.savefig('world2.png',dpi=100)

# ---------------------------------------------------------------
def plot_lines(mymap, lons, lats, **kwargs) :
    """Plots a custom coastline.  This plots simple lines, not
    ArcInfo-style SHAPE files.

    Args:
        lons: Longitude coordinates for line segments (degrees E)
        lats: Latitude coordinates for line segments (degrees N)

    Type Info:
        len(lons) == len(lats)
        A NaN in lons and lats signifies a new line segment.

    See:
        giss.noaa.drawcoastline_file()
    """

    # Project onto the map
    x, y = mymap(lons, lats)

    # BUG workaround: Basemap projects our NaN's to 1e30.
    x[x==1e30] = np.nan
    y[y==1e30] = np.nan

    # Plot projected line segments.
    mymap.plot(x, y, **kwargs)


# Read "Matlab" format files from NOAA Coastline Extractor.
# See: http://www.ngdc.noaa.gov/mgg/coast/

lineRE=re.compile('(.*?)\s+(.*)')
def read_coastline(fname, take_every=1) :
    nlines = 0
    xdata = array.array('d')
    ydata = array.array('d')
    for line in file(fname) :
#        if (nlines % 10000 == 0) :
#            print 'nlines = %d' % (nlines,)
        if (nlines % take_every == 0 or line[0:3] == 'nan') :
            match = lineRE.match(line)
            lon = float(match.group(1))
            lat = float(match.group(2))

            xdata.append(lon)
            ydata.append(lat)
        nlines = nlines + 1


    return (np.array(xdata),np.array(ydata))

def drawcoastline_file(mymap, fname, **kwargs) :
    """Reads and plots a coastline file.
    See:
        giss.basemap.drawcoastline()
        giss.basemap.read_coastline()
    """

    lons, lats = read_coastline(fname, take_every=1)
    return drawcoastline(mymap, lons, lats, **kwargs)
# =========================================================
# coastline2svg.py
#
import giss.io.noaa
import os
import numpy as np
import sys

svg_header = """<?xml version="1.0" encoding="UTF-8" standalone="no"?>
<!-- Created with Inkscape (http://www.inkscape.org/) -->

<svg
   xmlns:dc="http://purl.org/dc/elements/1.1/"
   xmlns:cc="http://creativecommons.org/ns#"
   xmlns:rdf="http://www.w3.org/1999/02/22-rdf-syntax-ns#"
   xmlns:svg="http://www.w3.org/2000/svg"
   xmlns="http://www.w3.org/2000/svg"
   version="1.1"
   width="360"
   height="180"
   id="svg2">
  <defs
     id="defs4" />
  <metadata
     id="metadata7">
    <rdf:RDF>
      <cc:Work
         rdf:about="">
        <dc:format>image/svg+xml</dc:format>
        <dc:type
           rdf:resource="http://purl.org/dc/dcmitype/StillImage" />
        <dc:title></dc:title>
      </cc:Work>
    </rdf:RDF>
  </metadata>
  <g
     id="layer1">
"""

path_tpl = """
    <path
       d="%PATH%"
       id="%PATH_ID%"
       style="fill:none;stroke:#000000;stroke-width:1px;stroke-linecap:butt;stroke-linejoin:miter;stroke-opacity:1"
"""

svg_footer = "</g></svg>"




# Set up paths
data_root = os.path.join(os.environ['HOME'], 'data')
#modelerc = giss.modele.read_modelerc()
#cmrun = modelerc['CMRUNDIR']
#savedisk = modelerc['SAVEDISK']

ifname = sys.argv[1]
ofname = ifname.replace('.dat', '.svg')

lons, lats = giss.io.noaa.read_coastline(ifname, 1)

out = open(ofname, 'w')
out.write(svg_header)

path_id = 1
points = []
for lon, lat in zip(lons, lats) :
    if np.isnan(lon) or np.isnan(lat) :
        # Process what we have
        if len(points) > 2 :
            out.write('\n<path d="')
            out.write('m %f,%f L' % (points[0][0], points[0][1]))
            for pt in points[1:] :
                out.write(' %f,%f' % pt)
            out.write('"\n   id="path%d"\n' % (path_id))
#            out.write('style="fill:none;stroke:#000000;stroke-width:1px;stroke-linecap:butt;stroke-linejoin:miter;stroke-opacity:1"')
            out.write(' />\n')
            path_id += 1
        points = []
    else :
        lon += 180
        lat = 180 - (lat + 90)
        points.append((lon, lat))


out.write(svg_footer)
out.close()

# =============================================================
# svg2coastline.py

import os
import sys
import re

# Reads the output of Inkscape's "Plain SVG" format, outputs in NOAA MATLAB coastline format

mainRE = re.compile(r'\s*d=".*"')
lineRE = re.compile(r'\s*d="(m|M)\s*(.*?)"')

fname = sys.argv[1]


lons = []
lats = []
for line in open(fname, 'r') :
    # Weed out extraneous lines in the SVG file
    match = mainRE.match(line)
    if match is None :
        continue

    match = lineRE.match(line)

    # Stop if something is wrong
    if match is None :
        sys.stderr.write(line)
        sys.exit(-1)

    type = match.group(1)[0]
    spairs = match.group(2).split(' ')
    x = 0
    y = 0
    for spair in spairs :
        if spair == 'L' :
            type = 'M'
            continue

        (sdelx, sdely) = spair.split(',')
        delx = float(sdelx)
        dely = float(sdely)
        if type == 'm' :
            x += delx
            y += dely
        else :
            x = delx
            y = dely
        lon = x - 180
        lat = 90 - y
        print '%f\t%f' % (lon, lat)
    print 'nan\tnan'

from mpl_toolkits.basemap import Basemap


class Basemap(Basemap):
    """ Modify Basemap to use Natural Earth data instead of GSHHG data """
    def drawcoastlines(self):
        shapefile = 'data/naturalearth/coastline/ne_%sm_coastline' % \
                    {'l':110, 'm':50, 'h':10}[self.resolution]
        self.readshapefile(shapefile, 'coastline', linewidth=1.)
    def drawcountries(self):
        shapefile = 'data/naturalearth/countries/ne_%sm_admin_0_countries' % \
                    {'l':110, 'm':50, 'h':10}[self.resolution]
        self.readshapefile(shapefile, 'countries', linewidth=0.5)


m = Basemap(llcrnrlon=-90, llcrnrlat=-40, urcrnrlon=-30, urcrnrlat=+20,
            resolution='l')  # resolution = (l)ow | (m)edium | (h)igh
m.drawcoastlines()
m.drawcountries()