Article Outline
Python matplotlib example 'plot basemap'
Functions in program:
def np2pd(data,lat,lon,slat,slon,svar):def pd2np(DF,slat,slon,svar):def plot_streamlines(u,v,speed,lat,lon,clevs,units,title,ismask_continent,density_lines=2):def plot_wind(u,v,speed,lat,lon,clevs,units,title,ismask_continent):def plot_slpwind(slp,u,v,lat,lon,clevs,units,title,ismask_continent):def plot_data(data,lat,lon,clevs,units,title,ismask_continent):
python plot basemap
Python matplotlib example: plot basemap
"""
Plot any meteorological variable on Geographical Map
"""
def plot_data(data,lat,lon,clevs,units,title,ismask_continent):
from mpl_toolkits.basemap import Basemap
import matplotlib.cm as cm
import numpy as np
import matplotlib.pyplot as plt
import sys
"""
PARAMETERS
resolution: c, l, i, h, f
area_thresh: 10000,1000,100,10,1
"""
resolution = 'h'
details_resolution = 10000
figsize = (12,12)
parallels = np.arange(20.,40,1.)
meridians = np.arange(110.,140.,1.)
try:
# create figure and axes instances
fig = plt.figure(figsize=figsize)
ax = fig.add_axes([0.1,0.1,0.8,0.8])
# prepare geographical data
latcorners = [np.min(lat),np.min(lat),np.max(lat),np.max(lat)]
loncorners = [np.min(lon),np.max(lon),np.max(lon),np.min(lon)]
lon_0 = np.mean(lon)
lat_0 = np.mean(lat)
# create Basemap instance.
m = Basemap(projection='mill',lon_0=lon_0,lat_0=lat_0,\
llcrnrlat=latcorners[0],urcrnrlat=latcorners[-1],\
llcrnrlon=loncorners[0],urcrnrlon=loncorners[1],\
resolution=resolution,area_thresh=details_resolution)
# draw coastlines, edge of map.
m.drawcoastlines(linewidth=1.5)
m.drawcountries()
if ismask_continent: m.fillcontinents(color='grey',lake_color='aqua')
# draw parallels.
m.drawparallels(parallels,labels=[1,0,0,0],fontsize=10)
# draw meridians
m.drawmeridians(meridians,labels=[0,0,0,1],fontsize=10)
# prepare data
#data = data[::-1,:]
ny = data.shape[0]; nx = data.shape[1]
lons, lats = m.makegrid(nx, ny) # get lat/lons of ny by nx evenly space grid.
x, y = m(lons, lats) # compute map proj coordinates.
# draw filled contours.
cs = m.contourf(x,y,data,clevs,cmap=cm.jet)
# add colorbar.
cbar = m.colorbar(cs,location='bottom',pad="5%")
cbar.set_label("%s"%(units),fontsize=12)
# add title
plt.title("%s"%(title),fontsize=12)
# plot by screen
plt.show()
except Exception as e:
print("ERROR: There are any problem plotting %s"%title)
print(str(e))
sys.stop("Stop!")
return None
"""
Plot slp + wind (using arrows) on Geographical Map
"""
def plot_slpwind(slp,u,v,lat,lon,clevs,units,title,ismask_continent):
from mpl_toolkits.basemap import Basemap, shiftgrid
import matplotlib.cm as cm
import numpy as np
import matplotlib.pyplot as plt
import sys
"""
PARAMETERS:
resolution: c, l, i, h, f
area_thresh: 10000,1000,100,10,1
"""
resolution = 'h'
details_resolution = 10000
figsize = (12,12)
parallels = np.arange(20.,40,1.)
meridians = np.arange(110.,140.,1.)
try:
# create figure, add axes
fig = plt.figure(figsize=figsize)
ax = fig.add_axes([0.1,0.1,0.8,0.8])
# prepare geographical data
latcorners = [np.min(lat),np.min(lat),np.max(lat),np.max(lat)]
loncorners = [np.min(lon),np.max(lon),np.max(lon),np.min(lon)]
lon_0 = np.mean(lon)
lat_0 = np.mean(lat)
lons, lats = np.meshgrid(lon,lat)
# create Basemap instance.
m = Basemap(projection='mill',lon_0=lon_0,lat_0=lat_0,\
llcrnrlat=latcorners[0],urcrnrlat=latcorners[-1],\
llcrnrlon=loncorners[0],urcrnrlon=loncorners[1],\
resolution=resolution,area_thresh=details_resolution)
# draw coastlines, edge of map.
m.drawcoastlines(linewidth=1.5)
m.drawcountries()
if ismask_continent: m.fillcontinents(color='grey',lake_color='aqua')
# draw parallels.
m.drawparallels(parallels,labels=[1,0,0,0],fontsize=10)
# draw meridians
m.drawmeridians(meridians,labels=[0,0,0,1],fontsize=10)
# compute native x,y coordinates of grid.
x, y = m(lons, lats)
# plot SLP contours.
CS1 = m.contour(x,y,slp,clevs,linewidths=0.5,colors='k',animated=True)
CS2 = m.contourf(x,y,slp,clevs,cmap=plt.cm.RdBu_r,animated=True)
# filter points to be showed
yy=np.arange(0,len(lat),filter_points)
xx=np.arange(0,len(lon),filter_points)
points=np.meshgrid(yy,xx)
# plot wind arrows
Q = m.quiver(lons[points],lats[points],u[points],v[points],latlon=True)
# add colorbar
cb = m.colorbar(CS2,"bottom", size="5%", pad="4%")
cb.set_label(units,fontsize=12)
# set plot title
ax.set_title(title,fontsize=12)
plt.show()
except Exception as e:
print("ERROR: There are any problem plotting %s"%title)
print(str(e))
sys.stop("Stop!")
return None
"""
Plot Wind (using arrows) on Geographical Map
"""
def plot_wind(u,v,speed,lat,lon,clevs,units,title,ismask_continent):
from mpl_toolkits.basemap import Basemap, shiftgrid
import matplotlib.cm as cm
import numpy as np
import matplotlib.pyplot as plt
"""
PARAMETERS:
resolution: c, l, i, h, f
area_thresh: 10000,1000,100,10,1
"""
resolution = 'h'
details_resolution = 10000
figsize = (12,12)
parallels = np.arange(20.,40,1.)
meridians = np.arange(110.,140.,1.)
try:
# create figure, add axes
fig = plt.figure(figsize=figsize)
ax = fig.add_axes([0.1,0.1,0.8,0.8])
# prepare geographical data
latcorners = [np.min(lat),np.min(lat),np.max(lat),np.max(lat)]
loncorners = [np.min(lon),np.max(lon),np.max(lon),np.min(lon)]
lon_0 = np.mean(lon)
lat_0 = np.mean(lat)
lons, lats = np.meshgrid(lon,lat)
# create Basemap instance.
m = Basemap(projection='mill',lon_0=lon_0,lat_0=lat_0,\
llcrnrlat=latcorners[0],urcrnrlat=latcorners[-1],\
llcrnrlon=loncorners[0],urcrnrlon=loncorners[1],\
resolution=resolution,area_thresh=details_resolution)
# draw coastlines, edge of map.
m.drawcoastlines(linewidth=1.5)
m.drawcountries()
if ismask_continent: m.fillcontinents(color='grey',lake_color='aqua')
# draw parallels.
m.drawparallels(parallels,labels=[1,0,0,0],fontsize=10)
# draw meridians
m.drawmeridians(meridians,labels=[0,0,0,1],fontsize=10)
# filter points to be showed
yy=np.arange(0,len(lat),filter_points)
xx=np.arange(0,len(lon),filter_points)
points=np.meshgrid(yy,xx)
# plot wind arrows
Q = m.quiver(lons[points],lats[points],u[points],v[points],speed[points],cmap=cm.jet ,latlon=True)
# add colorbar
cb = m.colorbar(Q,"bottom", size="5%", pad="4%")
cb.set_label(units,fontsize=12)
# set plot title
ax.set_title(title,fontsize=12)
plt.show()
except Exception as e:
print("ERROR: There are any problem plotting %s"%title)
print(str(e))
sys.stop("Stop!")
return None
"""
Plot Wind (using streamlines) on Geographical Map
"""
def plot_streamlines(u,v,speed,lat,lon,clevs,units,title,ismask_continent,density_lines=2):
from mpl_toolkits.basemap import Basemap, shiftgrid
import matplotlib.cm as cm
import numpy as np
import matplotlib.pyplot as plt
"""
PARAMETERS:
resolution: c, l, i, h, f
area_thresh: 10000,1000,100,10,1
"""
resolution = 'f'
details_resolution = 0
figsize = (16,16)
parallels = np.arange(20.,40,1.)
meridians = np.arange(110.,140.,1.)
width_lines = 2
try:
# create figure, add axes
fig = plt.figure(figsize=figsize)
ax = fig.add_axes([0.1,0.1,0.8,0.8])
# prepare geographical data
latcorners = [np.min(lat),np.min(lat),np.max(lat),np.max(lat)]
loncorners = [np.min(lon),np.max(lon),np.max(lon),np.min(lon)]
lon_0 = np.mean(lon)
lat_0 = np.mean(lat)
lons, lats = np.meshgrid(lon,lat)
# create Basemap instance.
m = Basemap(projection='cyl',
llcrnrlat=latcorners[0],urcrnrlat=latcorners[-1],\
llcrnrlon=loncorners[0],urcrnrlon=loncorners[1],\
resolution=resolution,area_thresh=details_resolution)
# draw coastlines, edge of map.
m.drawcoastlines(linewidth=1.5)
m.drawcountries()
if ismask_continent: m.fillcontinents(color='grey',lake_color='aqua')
# draw parallels.
m.drawparallels(parallels,labels=[1,0,0,0],fontsize=10)
# draw meridians
m.drawmeridians(meridians,labels=[0,0,0,1],fontsize=10)
# plot
x, y = np.meshgrid(lon, lat)
Q = m.streamplot(x,y,u,v,color=speed,linewidth=width_lines,density=density_lines,cmap=plt.cm.spectral)
# add colorbar
cb = m.colorbar(location="bottom", size="5%", pad="4%")
cb.set_label(units,fontsize=12)
# set plot title
ax.set_title(title,fontsize=22)
plt.show()
except Exception as e:
print("ERROR: There are any problem plotting %s"%title)
print(str(e))
sys.stop("Stop!")
return None
"""
Lat/Lon/Variable Pandas Dataframe to numpy arrays: lat inverse(1D), lon(1D), variable (2D)
"""
def pd2np(DF,slat,slon,svar):
# get arrays of lat inverse / lon
lat = np.array(sorted(set(DF[slat].tolist()),reverse=True))
lon = np.array(sorted(set(DF[slon].tolist()),reverse=False))
# get array matrix of data (lat inverse)
data = np.reshape(DF[svar].as_matrix(),(len(lat),len(lon)))
# return
return [data,lat,lon]
"""
Numpy arrays: lat inverse(1D), lon(1D), variable (2D) to Lat/Lon/Variable Pandas Dataframe
"""
def np2pd(data,lat,lon,slat,slon,svar):
import pandas as pd
import numpy as np
# inverse sort latitude
lat = np.sort(lat)[::-1]
# create numpy arrays
fdata = np.reshape(data,(len(lat)*len(lon),))
flat = np.repeat(lat,len(lon))
flon = np.reshape(np.repeat(np.reshape(lon, (1,len(lon))),len(lat),axis=0),(len(lon)*len(lat),))
# return dataframe
return pd.DataFrame({slat:flat,slon:flon,svar:fdata})
Python links
- Learn Python: https://pythonbasics.org/
- Python Tutorial: https://pythonprogramminglanguage.com