lonmin = b*math.floor(min(lon)/b)
lonmax = b*math.ceil(max(lon)/b)
latmin = b*math.floor(min(lat)/b)
latmax = b*math.ceil(max(lat)/b)
meridian = (range(lonmin, lonmax+b, b))
parallel = (range(latmin, latmax+b, b))
prj = 'cyl'
res = 'i'
map = Basemap(projection=prj,
llcrnrlon=lonmin,
llcrnrlat=latmin,
urcrnrlon=lonmax,
urcrnrlat=latmax,
resolution=res)
map.plot(lon, lat, 'r-')
map.plot(lon, lat, 'k+')
fs = 10
pylab.text(115.9,-31.9, "Perth", fontsize=fs, ha='left', va='top')
pylab.text(114.1,-21.9, "Exmouth", fontsize=fs, ha='left', va='top')
pylab.text(118.5,-20.4, "Port Hedland", fontsize=fs, ha='left', va='top')
pylab.text(130.8,-12.6, "Darwin", fontsize=fs, ha='left', va='top')
pylab.text(145.75,-16.9, "Cairns", fontsize=fs, ha='right', va='top')
pylab.text(149.2,-21.2, "Mackay", fontsize=fs, ha='right', va='top')
pylab.text(153.0,-27.5, "Brisbane", fontsize=fs, ha='right', va='top')
pylab.text(153.1,-30.25, "Coffs Harbour", fontsize=fs, ha='right', va='top')
pylab.text(151.1,-33.9, "Sydney", fontsize=fs, ha='right', va='top')
pylab.text(150.5,-35.3, "Ulladulla", fontsize=fs, ha='right', va='top')
map.fillcontinents(color='0.9')
def plot_track(rlon, rlat=None, m=None, **keywords):
show_lat = 1
if ('show_lat' in keywords):
show_lat = keywords['show_lat']
show_lon = 1
if ('show_lon' in keywords):
show_lon = keywords['show_lon']
if (m == None):
map_proj = 'cyl'
if ('map_proj' in keywords):
map_proj = keywords['map_proj']
lat_0 = 0.0
if ('lat_0' in keywords):
lat_0 = keywords['lat_0']
minlat = -90.0
maxlat = 90.0
if ('minlat' in keywords):
minlat = keywords['minlat']
if ('maxlat' in keywords):
maxlat = keywords['maxlat']
minlon = -180
maxlon = 180.0
if ('minlon' in keywords):
minlon = keywords['minlon']
if ('maxlon' in keywords):
maxlon = keywords['maxlon']
lon_0 = 0
if ('lon_0' in keywords):
lon_0 = keywords['lon_0']
boundinglat = 45
if ('boundinglat' in keywords):
boundinglat = keywords['boundinglat']
if (map_proj == 'npstere' or map_proj == 'spstere'):
m = Basemap(projection=map_proj,
lon_0=lon_0,
boundinglat=boundinglat)
elif (map_proj == 'ortho'):
m = Basemap(projection=map_proj, lon_0=lon_0, lat_0=lat_0)
else:
m=Basemap(llcrnrlon=minlon, llcrnrlat=minlat, \
urcrnrlon=maxlon, urcrnrlat=maxlat,projection=map_proj, lon_0=lon_0, lat_0=lat_0)
if (show_lat == 1):
m.drawparallels(arange(minlat, maxlat + 30.0, 30.),
labels=[1, 0, 0, 0])
if (show_lon == 1):
m.drawmeridians(arange(minlon, maxlon + 60, 60.),
labels=[0, 0, 0, 1])
sgn = '+'
if ('sgn' in keywords):
sgn = keywords['sgn']
if ('color' in keywords):
lcolor = keywords['color']
if (len(rlon) < 100):
m.plot(rlon, rlat, sgn, color=lcolor, markersize=11)
else:
m.plot(rlon, rlat, sgn, color=lcolor, markersize=6)
else:
m.plot(rlon, rlat, sgn)
m.drawcoastlines(color='w', linewidth=0.5)
m.drawmapboundary()
# m.drawcountries(color='k', linewidth=0.5)
if ('title' in keywords):
stitle = keywords['title']
title(stitle)
return m
urcrnrlon = llcrnrlon+(array.shape[1]-1)*coords[1]
urcrnrlat = coords[3]
llcrnrlat = urcrnrlat+(array.shape[0]-1)*coords[5]
# create Basemap instance.
m = Basemap(llcrnrlon=llcrnrlon,llcrnrlat=llcrnrlat,urcrnrlon=urcrnrlon,urcrnrlat=urcrnrlat,projection='cyl')
# create a figure, add an axes
# (leaving room for a colorbar).
fig = p.figure()
ax = fig.add_axes([0.1,0.1,0.75,0.75])
# plot image from DEM over map.
im = m.imshow(array,origin='upper')
# make a colorbar.
cax = p.axes([0.875, 0.1, 0.05, 0.75]) # setup colorbar axes.
p.colorbar(cax=cax) # draw colorbar
p.axes(ax) # make the original axes current again
# draw meridians and parallels.
m.drawmeridians(p.linspace(llcrnrlon+0.1,urcrnrlon-0.1,5),labels=[0,0,0,1],fmt='%4.2f')
m.drawparallels(p.linspace(llcrnrlat+0.1,urcrnrlat-0.1,5),labels=[1,0,0,0],fmt='%4.2f')
# plot county boundaries from
# http://edcftp.cr.usgs.gov/pub/data/nationalatlas/countyp020.tar.gz
shp_info = m.readshapefile('countyp020','counties',drawbounds=True,linewidth=1.0)
# plot some cities.
lons = [-105.22,-105.513,-105.316,-105.47]; lats = [39.76,39.801,39.633,39.41]
names = ['Golden','Central City','Evergreen','Bailey']
x,y = m(lons,lats)
m.plot(x,y,'ko')
for name,xx,yy in zip(names,x,y):
p.text(xx+0.01,yy+0.01,name)
p.title(gd.GetDescription()+' USGS DEM with county boundaries')
p.show()
lonmin = b*math.floor(min(lon)/b)
lonmax = b*math.ceil(max(lon)/b)
latmin = b*math.floor(min(lat)/b)
latmax = b*math.ceil(max(lat)/b)
meridian = (range(lonmin, lonmax+b, b))
parallel = (range(latmin, latmax+b, b))
prj = 'cyl'
res = 'i'
map = Basemap(projection=prj,
llcrnrlon=lonmin,
llcrnrlat=latmin,
urcrnrlon=lonmax,
urcrnrlat=latmax,
resolution=res)
map.plot(lon, lat, 'r-')
map.plot(lon, lat, 'k+')
fs = 10
pylab.text(115.9,-31.9, "Perth", fontsize=fs, ha='left', va='top')
pylab.text(114.1,-21.9, "Exmouth", fontsize=fs, ha='left', va='top')
pylab.text(118.5,-20.4, "Port Hedland", fontsize=fs, ha='left', va='top')
pylab.text(130.8,-12.6, "Darwin", fontsize=fs, ha='left', va='top')
pylab.text(145.75,-16.9, "Cairns", fontsize=fs, ha='right', va='top')
pylab.text(149.2,-21.2, "Mackay", fontsize=fs, ha='right', va='top')
pylab.text(153.0,-27.5, "Brisbane", fontsize=fs, ha='right', va='top')
pylab.text(153.1,-30.25, "Coffs Harbour", fontsize=fs, ha='right', va='top')
pylab.text(151.1,-33.9, "Sydney", fontsize=fs, ha='right', va='top')
pylab.text(150.5,-35.3, "Ulladulla", fontsize=fs, ha='right', va='top')
map.fillcontinents(color='0.9')
urcrnrlat = coords[3]
llcrnrlat = urcrnrlat + (array.shape[0] - 1) * coords[5]
# create Basemap instance.
m = Basemap(llcrnrlon=llcrnrlon, llcrnrlat=llcrnrlat, urcrnrlon=urcrnrlon, urcrnrlat=urcrnrlat, projection="cyl")
# create a figure with the right aspect ratio, add an axes
# (leaving room for a colorbar).
fig = p.figure(figsize=(8, m.aspect * 8))
ax = fig.add_axes([0.1, 0.1, 0.75, 0.75])
# plot image from DEM over map.
im = m.imshow(array, origin="upper")
# make a colorbar.
cax = p.axes([0.875, 0.1, 0.05, 0.75]) # setup colorbar axes.
p.colorbar(tickfmt="%d", cax=cax) # draw colorbar
p.axes(ax) # make the original axes current again
# draw meridians and parallels.
m.drawmeridians(p.linspace(llcrnrlon + 0.1, urcrnrlon - 0.1, 5), labels=[0, 0, 0, 1], fmt="%4.2f")
m.drawparallels(p.linspace(llcrnrlat + 0.1, urcrnrlat - 0.1, 5), labels=[1, 0, 0, 0], fmt="%4.2f")
# plot county boundaries from
# http://edcftp.cr.usgs.gov/pub/data/nationalatlas/countyp020.tar.gz
shp_info = m.readshapefile("countyp020", "counties", drawbounds=True, linewidth=1.0)
# plot some cities.
lons = [-105.22, -105.513, -105.316, -105.47]
lats = [39.76, 39.801, 39.633, 39.41]
names = ["Golden", "Central City", "Evergreen", "Bailey"]
x, y = m(lons, lats)
m.plot(x, y, "ko")
for name, xx, yy in zip(names, x, y):
p.text(xx + 0.01, yy + 0.01, name)
p.title(gd.GetDescription() + " USGS DEM with county boundaries")
p.show()
# in which direction to depart for other points on earth and how far
# it will be to reach that destination.
# The specified point shows up as a red dot in the center of the map.
# This example shows how to use the width and height keywords
# to specify the map projection region (instead of specifying
# the lat/lon of the upper right and lower left corners).
# user enters the lon/lat of the point, and it's name
lon_0 = float(raw_input('input reference lon (degrees):'))
lat_0 = float(raw_input('input reference lat (degrees):'))
location = raw_input('name of location:')
# use these values to setup Basemap instance.
width = 28000000
m = Basemap(width=width,height=width,\
resolution='c',projection='aeqd',\
lat_0=lat_0,lon_0=lon_0)
# draw coasts and fill continents.
m.drawcoastlines(linewidth=0.5)
m.fillcontinents()
# 20 degree graticule.
m.drawparallels(arange(-80, 81, 20))
m.drawmeridians(arange(-180, 180, 20))
# draw a red dot at the center.
xpt, ypt = m(lon_0, lat_0)
m.plot([xpt], [ypt], 'ro')
# draw the title.
title('The World According to Garp in ' + location)
show()
map.drawcountries(linewidth=0.25)
map.fillcontinents(color='coral')
# draw the edge of the map projection region (the projection limb)
map.drawmapboundary()
# draw lat/lon grid lines every 30 degrees.
map.drawmeridians(p.arange(0,360,30))
map.drawparallels(p.arange(-90,90,30))
# lat/lon coordinates of five cities.
lats=[40.02,32.73,38.55,48.25,17.29]
lons=[-105.16,-117.16,-77.00,-114.21,-88.10]
cities=['Boulder, CO','San Diego, CA',
'Washington, DC','Whitefish, MT','Belize City, Belize']
# compute the native map projection coordinates for cities.
x,y = map(lons,lats)
# plot filled circles at the locations of the cities.
map.plot(x,y,'bo')
# plot the names of those five cities.
for name,xpt,ypt in zip(cities,x,y):
p.text(xpt+50000,ypt+50000,name,fontsize=9)
# make up some data on a regular lat/lon grid.
nlats = 73; nlons = 145; delta = 2.*p.pi/(nlons-1)
lats = (0.5*p.pi-delta*p.indices((nlats,nlons))[0,:,:])
lons = (delta*p.indices((nlats,nlons))[1,:,:])
wave = 0.75*(p.sin(2.*lats)**8*p.cos(4.*lons))
mean = 0.5*p.cos(2.*lats)*((p.sin(2.*lats))**2 + 2.)
# compute native map projection coordinates of lat/lon grid.
x, y = map(lons*180./p.pi, lats*180./p.pi)
# contour data over the map.
cs = map.contour(x,y,wave+mean,15,linewidths=1.5)
p.show()
#p.savefig('wiki_example.ps')
# in which direction to depart for other points on earth and how far
# it will be to reach that destination.
# The specified point shows up as a red dot in the center of the map.
# This example shows how to use the width and height keywords
# to specify the map projection region (instead of specifying
# the lat/lon of the upper right and lower left corners).
# user enters the lon/lat of the point, and it's name
lon_0 = float(raw_input('input reference lon (degrees):'))
lat_0 = float(raw_input('input reference lat (degrees):'))
location = raw_input('name of location:')
# use these values to setup Basemap instance.
width = 28000000
m = Basemap(width=width,height=width,\
resolution='c',projection='aeqd',\
lat_0=lat_0,lon_0=lon_0)
# draw coasts and fill continents.
m.drawcoastlines(linewidth=0.5)
m.fillcontinents()
# 20 degree graticule.
m.drawparallels(arange(-80,81,20))
m.drawmeridians(arange(-180,180,20))
# draw a red dot at the center.
xpt, ypt = m(lon_0, lat_0)
m.plot([xpt],[ypt],'ro')
# draw the title.
title('The World According to Garp in '+location)
show()
nx = int((m.xmax-m.xmin)/40000.)+1; ny = int((m.ymax-m.ymin)/40000.)+1
topodat,x,y = m.transform_scalar(topoin,lons,lats,nx,ny,returnxy=True)
# create the figure.
fig=figure(figsize=(8,8))
# add an axes, leaving room for colorbar on the right.
ax = fig.add_axes([0.1,0.1,0.7,0.7])
# plot image over map with imshow.
im = m.imshow(topodat,cm.jet)
# setup colorbar axes instance.
l,b,w,h = ax.get_position()
cax = axes([l+w+0.075, b, 0.05, h])
colorbar(tickfmt='%d', cax=cax) # draw colorbar
axes(ax) # make the original axes current again
# plot blue dot on boulder, colorado and label it as such.
xpt,ypt = m(-104.237,40.125)
m.plot([xpt],[ypt],'bo')
text(xpt+100000,ypt+100000,'Boulder')
# draw coastlines and political boundaries.
m.drawcoastlines()
m.drawcountries()
m.drawstates()
# draw parallels and meridians.
# label on left, right and bottom of map.
parallels = arange(0.,80,20.)
m.drawparallels(parallels,labels=[1,1,0,1])
meridians = arange(10.,360.,30.)
m.drawmeridians(meridians,labels=[1,1,0,1])
# set title.
title('ETOPO Topography - Lambert Conformal Conic')
show()
ax = fig.add_axes([0.1, 0.1, 0.7, 0.7])
# plot image over map with imshow.
im = m.imshow(topodat, cm.jet)
# use pcolor (looks very similar to imshow, but slower).
# p = m.pcolor(x,y,topodat,shading='flat')
# plot contour lines over map (colors is a list so neg contours will
# not be dashed).
# levels, colls = m.contour(x,y,topodat,15,linewidths=0.5,colors=['k','k'])
# fill the contours.
# levels, colls = m.contourf(x,y,topodat,15,cmap=cm.jet,colors=None)
cax = axes([0.875, 0.1, 0.05, 0.7]) # setup colorbar axes
colorbar(tickfmt="%d", cax=cax) # draw colorbar
axes(ax) # make the original axes current again
# plot blue dot on boulder, colorado and label it as such.
xpt, ypt = m(-104.237, 40.125)
m.plot([xpt], [ypt], "bo")
text(xpt + 100000, ypt + 100000, "Boulder")
# draw coastlines and political boundaries.
m.drawcoastlines()
m.drawcountries()
m.drawstates()
# draw parallels and meridians.
# label on left, right and bottom of map.
parallels = arange(0.0, 80, 20.0)
m.drawparallels(parallels, labels=[1, 1, 0, 1])
meridians = arange(10.0, 360.0, 30.0)
m.drawmeridians(meridians, labels=[1, 1, 0, 1])
title("ETOPO Topography - Lambert Conformal Conic")
show()
# draw the edge of the map projection region (the projection limb)
map.drawmapboundary()
# draw lat/lon grid lines every 30 degrees.
map.drawmeridians(p.arange(0, 360, 30))
map.drawparallels(p.arange(-90, 90, 30))
# lat/lon coordinates of five cities.
lats = [40.02, 32.73, 38.55, 48.25, 17.29]
lons = [-105.16, -117.16, -77.00, -114.21, -88.10]
cities = [
'Boulder, CO', 'San Diego, CA', 'Washington, DC', 'Whitefish, MT',
'Belize City, Belize'
]
# compute the native map projection coordinates for cities.
x, y = map(lons, lats)
# plot filled circles at the locations of the cities.
map.plot(x, y, 'bo')
# plot the names of those five cities.
for name, xpt, ypt in zip(cities, x, y):
p.text(xpt + 50000, ypt + 50000, name, fontsize=9)
# make up some data on a regular lat/lon grid.
nlats = 73
nlons = 145
delta = 2. * p.pi / (nlons - 1)
lats = (0.5 * p.pi - delta * p.indices((nlats, nlons))[0, :, :])
lons = (delta * p.indices((nlats, nlons))[1, :, :])
wave = 0.75 * (p.sin(2. * lats)**8 * p.cos(4. * lons))
mean = 0.5 * p.cos(2. * lats) * ((p.sin(2. * lats))**2 + 2.)
# compute native map projection coordinates of lat/lon grid.
x, y = map(lons * 180. / p.pi, lats * 180. / p.pi)
# contour data over the map.
cs = map.contour(x, y, wave + mean, 15, linewidths=1.5)
mapobj= Basemap(projection='merc',lat_0=(box[2]+box[3])/2.0, lon_0=(box[0]+box[1])/2.0,llcrnrlat=box[2], llcrnrlon=box[0], urcrnrlat=box[3] , urcrnrlon=box[1], resolution='l',area_thresh=1., lat_ts=(box[2]+box[3])/2.0)
longr, latgr=meshgrid(lons,lats)
xx, yy = mapobj(longr, latgr)
mapobj.drawmapboundary()
mapobj.readshapefile('/flurry/home/scollis/shapes/cstntcd_r','coast',drawbounds=True,linewidth=0.5,color='k',antialiased=1,ax=None)
mapobj.contour(xx,yy,angs, levels=[150,30], colors=['r'])
mapobj.drawmeridians(array([130.2, 130.4, 130.6, 130.8,131.0,131.2, 131.4]), labels=[1,0,0,1])
mapobj.drawparallels(array([--12.8, -12.6, -12.4, -12.2, -12.0, -11.8, -11.6, -11.4]), labels=[1,0,0,1])
dd_box_xx, dd_box_yy=mapobj(array([dd_box[0], dd_box[1]]),array([dd_box[2], dd_box[3]]))
xy=dd_box_xx[0], dd_box_yy[0]
width, height= dd_box_xx[1]-dd_box_xx[0], dd_box_yy[1]-dd_box_yy[0]
my_patch=matplotlib.patches.Rectangle(xy, width, height, edgecolor='blue', facecolor='white')
ax=gca()
ax.add_patch(my_patch)
radar_xx, radar_yy=mapobj(array([ber_loc[1], gp_loc[1]]), array([ber_loc[0], gp_loc[0]]))
mapobj.plot(radar_xx, radar_yy, 'bo')
ax.text(radar_xx[0]+1000.0, radar_yy[0]-3000.0, 'Berrimah')
ax.text(radar_xx[1]+1000.0, radar_yy[1]-3000.0, 'Gunn Point')
savefig('/flurry/home/scollis/results/area_vis.png')
close(f)
|
| ================= ==============================================
| Property Description
| ================= ==============================================
| alpha float
| animated [True | False]
| antialiased or aa [True | False]
| clip_box a matplotlib.transform.Bbox instance
def wrf_grid(
# WPS -> map_proj
projection,
# WPS -> truelat1
lat_1,
# WPS -> truelat2
lat_2,
# WPS -> stand_lon
lon_0,
# WPS -> ref_lat
grid_centre_lat,
# WPS -> ref_lon
grid_centre_lon,
delta_x,
delta_y,
# WPS -> e_we
nx,
# WPS -> e_sn
ny,
show_mass_grid = False,
show_stag_grids = False,
):
if lon_0 != grid_centre_lon:
print 'not implemented yet -> see the source'
print "\tbut let's try it anyways..."
#return
width = nx * delta_x
height = ny * delta_y
frame_x = 10 * delta_x
frame_y = 10 * delta_y
m = Basemap(
lat_0 = grid_centre_lat,
# this could be a bad assumption... because lon_0 and grid_centre_lon
# need not be aligned, but at the same time I need to give this to
# basemap for the grid to be centred... I could probably fix it
# assigning lon_0 and then imposing a grid shift in native coordinates
# if ref_lon and lon_0 were not the same
lon_0 = lon_0,
lat_1 = lat_1,
lat_2 = lat_2,
width = width + 2*frame_x,
height = height + 2*frame_y,
resolution = 'l',
area_thresh=1000.
)
grid_centre_x, grid_centre_y = m(grid_centre_lon, grid_centre_lat)
min_x = grid_centre_x - width/2.
min_y = grid_centre_y - height/2.
max_x = min_x + width
max_y = min_y + height
x = n.arange(min_x, max_x + a_small_number, delta_x)
y = n.arange(min_y, max_y + a_small_number, delta_y)
x = x[1:-1]
y = y[1:-1]
x_u = n.arange(min_x, max_x + delta_x + a_small_number, delta_x)
x_u -= delta_x/2.
x_u = x_u[1:-1]
y_v = n.arange(min_y, max_y + delta_y + a_small_number, delta_y)
y_v -= delta_y/2.
y_v = y_v[1:-1]
X, Y = p.meshgrid(x,y)
lon, lat = m(X, Y, inverse=True)
X_u, Y_u = p.meshgrid(x_u,y)
lon_u, lat_u = m(X_u, Y_u, inverse=True)
X_v, Y_v = p.meshgrid(x,y_v)
lon_v, lat_v = m(X_v, Y_v, inverse=True)
if show_mass_grid:
m.plot(X, Y, 'b+')
m.plot([grid_centre_x], [grid_centre_y], 'r+')
if show_stag_grids:
m.plot(X_u, Y_u, 'g+')
m.plot(X_v, Y_v, 'r+')
m.drawcoastlines()
p.show()
output = {
'map' : m,
'mass_stag': {
'lon_2d' : lon,
'lat_2d' : lat,
'x' : x,
'y' : y,
'x_2d' : X,
'y_2d' : Y,
},
'u_stag': {
'lon_2d' : lon_u,
'lat_2d' : lat_u,
'x' : x_u,
'y' : y,
'x_2d' : X_u,
'y_2d' : Y_u,
},
'v_stag': {
'lon_2d' : lon_v,
'lat_2d' : lat_v,
'x' : x,
'y' : y_v,
'x_2d' : X_v,
'y_2d' : Y_v,
}
}
return output
