I'm close to getting the map that I want. Matplotlib's Basemap is great, but the coastlines are too coarse when I zoom in. I can read the Natural Earth shapefiles and plot them, which are much better... but when I try and fill the polygons, I think it's treating all of the points as belonging to a single polygon. How can I iterate through the polygons and display the map correctly?
Thanks in advance!
Here's the code:
import numpy as np
from mpl_toolkits.basemap import Basemap
import matplotlib.pyplot as plt
from matplotlib.patches import Polygon
from matplotlib.collections import PatchCollection
%matplotlib inline
landColor, coastColor, oceanColor, popColor, countyColor = '#eedd99','#93ccfa','#93ccfa','#ffee99','#aa9955'
fig = plt.figure()
ax = fig.add_subplot(111)
s = 1900000
m = Basemap(projection='ortho',lon_0=-86.5,lat_0=30.3,resolution='l',llcrnrx=-s,llcrnry=-s,urcrnrx=s,urcrnry=s)
m.drawmapboundary(fill_color=oceanColor) # fill in the ocean
# generic function for reading polygons from file and plotting them on the map. This works with Natural Earth shapes.
def drawShapesFromFile(filename,facecolor,edgecolor,m):
m.readshapefile(filename, 'temp', drawbounds = False)
patches = []
for info, shape in zip(m.temp_info, m.temp): patches.append( Polygon(np.array(shape), True) )
ax.add_collection(PatchCollection(patches, facecolor=facecolor, edgecolor=edgecolor, linewidths=1))
# read the higher resolution Natural Earth coastline (land polygons) shapefile and display it as a series of polygons
drawShapesFromFile('\\Conda\\notebooks\\shapes\\ne_10m_coastline',landColor,coastColor,m)
drawShapesFromFile('\\Conda\\notebooks\\shapes\\ne_10m_urban_areas',popColor,'none',m)
m.drawcounties(color=countyColor)
plt.gcf().set_size_inches(10,10)
As requested, here's the updated code and resulting map. All I had to do was change ne_10m_coastline to ne_10m_land like this:
import numpy as np
from mpl_toolkits.basemap import Basemap
import matplotlib.pyplot as plt
from matplotlib.patches import Polygon
from matplotlib.collections import PatchCollection
%matplotlib inline
landColor, coastColor, oceanColor, popColor, countyColor = '#eedd99','#93ccfa','#93ccfa','#ffee99','#aa9955'
fig = plt.figure()
ax = fig.add_subplot(111)
s = 1900000
m = Basemap(projection='ortho',lon_0=-86.5,lat_0=30.3,resolution='l',llcrnrx=-s,llcrnry=-s,urcrnrx=s,urcrnry=s)
m.drawmapboundary(fill_color=oceanColor) # fill in the ocean
# generic function for reading polygons from file and plotting them on the map. This works with Natural Earth shapes.
def drawShapesFromFile(filename,facecolor,edgecolor,m):
m.readshapefile(filename, 'temp', drawbounds = False)
patches = []
for info, shape in zip(m.temp_info, m.temp): patches.append( Polygon(np.array(shape), True) )
ax.add_collection(PatchCollection(patches, facecolor=facecolor, edgecolor=edgecolor, linewidths=1))
# read the higher resolution Natural Earth coastline (land polygons) shapefile and display it as a series of polygons
drawShapesFromFile('\\Conda\\notebooks\\shapes\\ne_10m_land',landColor,coastColor,m)
drawShapesFromFile('\\Conda\\notebooks\\shapes\\ne_10m_urban_areas',popColor,'none',m)
m.drawcounties(color=countyColor)
plt.gcf().set_size_inches(10,10)
Related
According to Cartopy docs, stock_img() has only one (and default) option - a down sampled version of the Natural Earth shaded relief raster.
How do I display this image using Basemap?
Here is an example:
import matplotlib.pyplot as plt
from mpl_toolkits.basemap import Basemap
ax = plt.gca()
bmap = Basemap( projection='ortho', lat_0=45, lon_0=-100, resolution='l', ax=ax )
bmap.shadedrelief(scale=0.25)
plt.show()
I am at a loss to get the following code to work. For whatever reason, the GeoPandas *.plot() doesn't work, but I want to use both Pandas and GeoPandas for some simple plots.
I have been trying to take the Shapely objects from GeoPandas and plot them on a Basemap. The problem is that the polygons won't plot. I iterate through them from the GeoPandas.geometry, add them to the axes collection, and then use plot() - to no avail. Basemap seems to work fine, the code doesn't give any errors, but the polygons - counties - don't appear...
Thank you for the help!
import geopandas as gpd
from descartes import PolygonPatch
import matplotlib as mpl
import mpl_toolkits.basemap as base
import matplotlib.pyplot as plt
counties_file = r'C:\Users\...\UScounties\UScounties.shp'
counties = gpd.read_file(counties_file)
#new plot
fig = plt.figure(figsize=(5,5),dpi=300)
#ax = fig.add_subplot(111)
ax = ax = plt.gca()
minx, miny, maxx, maxy = counties.total_bounds
#map
m = base.Basemap(llcrnrlon=minx, llcrnrlat=miny,
urcrnrlon=maxx, urcrnrlat=maxy,
resolution='h', area_thresh=100000,
projection='merc')
patches = []
#add polygons
for poly in counties.geometry:
#deal with single polygons and multipolygons
if poly.geom_type == 'Polygon':
p = PolygonPatch(poly, facecolor='blue', alpha=1)
#plt.gca().add_patch(p)
#ax.add_patch(p)
patches.append(p)
elif poly.geom_type == 'MultiPolygon':
for single in poly:
q = PolygonPatch(single,facecolor='red', alpha=1)
#ax.add_patch(p)
patches.append(q)
m.drawcoastlines(linewidth=.1)
m.fillcontinents()
m.drawcountries(linewidth=.25,linestyle='solid')
m.drawstates(linewidth=.25,linestyle='dotted')
m.drawmapboundary(fill_color='white')
ax.add_collection(mpl.collections.PatchCollection(patches, match_original=True))
ax.plot()
plt.show()
Check if your shapefile is in the right projection system. Basemap is currently set to Mercator Projection. After that it worked for me.
I want to plot a graph on a map where the nodes would be defined by coordinates (lat, long) and have some value associated.
I have been able to plot points as a scatterplot on a basemap but can't seem to find how to plot a graph on the map.
Thanks.
EDIT: I have added code on how I plotted the points on a basemap. Most of it has been adapted from code in this article.
from mpl_toolkits.basemap import Basemap
from shapely.geometry import Point, MultiPoint
import pandas as pd
import matplotlib.pyplot as plt
m = Basemap(
projection='merc',
ellps = 'WGS84',
llcrnrlon=-130,
llcrnrlat=25,
urcrnrlon=-60,
urcrnrlat=50,
lat_ts=0,
resolution='i',
suppress_ticks=True)
# Create Point objects in map coordinates from dataframe lon
# and lat values
# I have a dataframe of coordinates
map_points = pd.Series(
[Point(m(mapped_x, mapped_y))
for mapped_x, mapped_y in zip(df['lon'],
df['lat'])])
amre_points = MultiPoint(list(map_points.values))
plt.clf()
fig = plt.figure()
ax = fig.add_subplot(111, axisbg='w', frame_on=False)
fig.set_size_inches(18.5, 10.5)
# Create a scatterplot on the map
dev = m.scatter(
[geom.x for geom in map_points],
[geom.y for geom in map_points],
20, marker='o', lw=.25,
facecolor='#33ccff', edgecolor='w',
alpha=0.9,antialiased=True,
zorder=3)
m.fillcontinents(color='#555555')
I get this image:
Here is one way to do it:
import networkx as nx
import matplotlib.pyplot as plt
from mpl_toolkits.basemap import Basemap as Basemap
m = Basemap(
projection='merc',
llcrnrlon=-130,
llcrnrlat=25,
urcrnrlon=-60,
urcrnrlat=50,
lat_ts=0,
resolution='i',
suppress_ticks=True)
# position in decimal lat/lon
lats=[37.96,42.82]
lons=[-121.29,-73.95]
# convert lat and lon to map projection
mx,my=m(lons,lats)
# The NetworkX part
# put map projection coordinates in pos dictionary
G=nx.Graph()
G.add_edge('a','b')
pos={}
pos['a']=(mx[0],my[0])
pos['b']=(mx[1],my[1])
# draw
nx.draw_networkx(G,pos,node_size=200,node_color='blue')
# Now draw the map
m.drawcountries()
m.drawstates()
m.bluemarble()
plt.title('How to get from point a to point b')
plt.show()
As of today there is a nice alternative to basemap. Mplleaflet is a library inspired by mpld3. It plots faster than basemap, is more easy to use and allows to visualizing geographic data on beautiful interactive openstreetmap. The input can be longitude and latitude the library automatically projects the data properly.
Input dictionary pos, where the node (country) is the key and long lat are saved as value.
pos = {u'Afghanistan': [66.00473365578554, 33.83523072784668],
u'Aland': [19.944009818523348, 60.23133494165451],
u'Albania': [20.04983396108883, 41.14244989474517],
u'Algeria': [2.617323009197829, 28.158938494487625],
.....
Plotting is as easy as:
import mplleaflet
fig, ax = plt.subplots()
nx.draw_networkx_nodes(GG,pos=pos,node_size=10,node_color='red',edge_color='k',alpha=.5, with_labels=True)
nx.draw_networkx_edges(GG,pos=pos,edge_color='gray', alpha=.1)
nx.draw_networkx_labels(GG,pos, label_pos =10.3)
mplleaflet.display(fig=ax.figure)
I have difficulties in plotting e.g. polygons across the boundaries of a map generated using matplotlib-basemap. In the example below, the map boundary is specified by the dateline. I try to plot a triangle across the dateline by specifying the coordinates of vertices of a triangle. This works fine when all coordinates are within the map, but if they go across the map boundary, basemap performs strange extrapolation, as it seems not to know how to draw the rectangles in the right way.
Right way would mean in my sense that the triangle is drawn until the map boundary and would then continue at the other side of the map.
Below is a minimum code example and a figure illustrating the general problem.
Any ideas how to solve this problem in a general way are highly welcome.
from mpl_toolkits.basemap import Basemap
import matplotlib.pylab as plt
import numpy as np
import matplotlib.path as mpath
import matplotlib.patches as mpatches
import matplotlib as mpl
from matplotlib.collections import PatchCollection
![plt.close('all')
Path = mpath.Path
fig=plt.figure(); ax=fig.add_subplot(121); ax1=fig.add_subplot(122)
def do_plot(ax,lons,lats,title):
patches=\[\]
m = Basemap(projection='robin', resolution='c',lon_0=0.,ax=ax) #todo: how to make it properly work for other projections ???
m.drawmapboundary(fill_color='grey')
m.drawcoastlines()
#--- generate first sample with no problem
x,y=m(lons,lats)
verts = np.asarray(\[x,y\]).T
codes = \[Path.MOVETO,Path.LINETO,Path.LINETO\]
patches.append(mpatches.PathPatch(mpath.Path(verts, codes,closed=True)))
#--- generate collection
cmap = plt.cm.get_cmap('jet', 50); norm = mpl.colors.Normalize(vmin=None, vmax=None) #colorbar mapping
collection = PatchCollection(patches, cmap=cmap,norm=norm, alpha=1.,match_original=False) #construct library of all objects
colors = np.asarray(np.random.random(len(patches)))
collection.set_array(np.array(colors)) #assign data values here
#--- do actual plotting
im=m.ax.add_collection(collection)
ax.set_title(title)
do_plot(ax,\[-10.,0.,20.\],\[30.,50.,20.\],'This works')
do_plot(ax1,\[170,180,-175\],\[30.,50.,20.\],'... and here is the boundary problem')
plt.show()][1]
You cannot get around this problem with Basemap in a simple way. In your line x,y=m(lons,lats) you have transformed the points to map coordinates, and drawing the polygon just draws between those projected points.
You might try using Cartopy, which can do this. This example may help.
I use orthographic projection to plot maps.
I use this programm:
from mpl_toolkits.basemap import Basemap
import numpy as np
import matplotlib.pyplot as plt
import os, sys
from sys import argv
import pylab
from mpl_toolkits.basemap import Basemap, shiftgrid
from matplotlib import mpl
from matplotlib import rcParams
import matplotlib.pyplot as plt
import matplotlib.mlab as mlab
import matplotlib.patches as patches
import matplotlib.path as path
import matplotlib.dates as dt
from numpy import linalg
import netCDF4
import time
import datetime as d
import sys
import math
from mpl_toolkits.axes_grid1 import make_axes_locatable
from pylab import *
nc = netCDF4.Dataset ('tt.nc')
latvar = nc.variables['lat']
lat = latvar[:]
lon = nc.variables['lon'][:]
lat_0=30;lon_0=-25
m1 = Basemap(projection='ortho',lon_0=-25,lat_0=30,resolution='l')
m = Basemap(projection='ortho',lon_0=lon_0,lat_0=lat_0,resolution='l',\
llcrnrx=0.,llcrnry=0.,urcrnrx=m1.urcrnrx/2.,urcrnry=m1.urcrnry/2.)
X, Y = m(lon, lat)
O_x_1=nc.variables['O3']
h=9
lev=0
minOzone=0
maxOzone=40
plotOzone = m.pcolor(X,Y,O_x_1[h,lev,:,:],vmin=minOzone,vmax=maxOzone)
ax=colorbar(plotOzone, shrink=0.8,norm=(0,40))
m.drawcoastlines()
m.drawparallels(np.arange(-90.,120.,30.))
m.drawmeridians(np.arange(0.,420.,60.))
plt.show()
What do I have to do to center my map
on Europe ?
I have already played with lat_0 and lon_0 but that doesn't
give what I want...
I can't add figures to show what I obtained and
what I would like...
Thank you!
The lat_0 and lon_0 are for setting the origin of the projection, not the extent of the map. Usually the place with the least distortions so you dont want the origin to deviate too much from the center of your area of interest. Basemap will automatically center the map around the origin if you dont specify an extent.
Centering the map (different from its origin) can be done if you know what extent (or boundingbox) you want to use. If you know the corner coordinates in your 'ortho' projection you could use the keywords from your example (llcrnrx etc.). I have had no luck with the 'llcrnrlon' keywords in Basemap 1.0.6, they seem to suggest that you can input the coordinates of your extent in geographic (lat/lon).
An alternative is to grab the axes and manually set an x- and y limit. A benefit is that you can do it after declaring the Basemap object which you can then use for coordinate transformation. An example:
from mpl_toolkits.basemap import Basemap
fig = plt.figure(figsize=(5,5))
m = Basemap(projection='ortho',lon_0=5,lat_0=35,resolution='l')
m.drawcoastlines()
m.drawparallels(np.arange(-90.,120.,15.))
m.drawmeridians(np.arange(0.,420.,30.))
# your extent in lat/lon (dec degrees)
ulx = -10
uly = 65
lrx = 65
lry = 35
# transform coordinates to map projection
xmin, ymin = m(ulx, lry)
xmax, ymax = m(lrx, uly)
# set the axes limits
ax = plt.gca()
ax.set_xlim(xmin, xmax)
ax.set_ylim(ymin, ymax)
Make sure the projection in the map declaration suites your needs, i have just picked an origin which falls within Europe.