本文整理汇总了Python中nansat.Nansat.write_kml_image方法的典型用法代码示例。如果您正苦于以下问题：Python Nansat.write_kml_image方法的具体用法？Python Nansat.write_kml_image怎么用？Python Nansat.write_kml_image使用的例子？那么恭喜您, 这里精选的方法代码示例或许可以为您提供帮助。您也可以进一步了解该方法所在类nansat.Nansat的用法示例。
在下文中一共展示了Nansat.write_kml_image方法的2个代码示例，这些例子默认根据受欢迎程度排序。您可以为喜欢或者感觉有用的代码点赞，您的评价将有助于系统推荐出更棒的Python代码示例。
示例1: main
# 需要导入模块: from nansat import Nansat [as 别名]
# 或者: from nansat.Nansat import write_kml_image [as 别名]
#.........这里部分代码省略.........
# try to create Nansat object
try:
n = Nansat(iPath + dirName + '/' + fileName, mapperName='asar', logLevel=27)
except Exception as e:
print "Failed to create Nansat object:"
print str(e)
os.rmdir(oPath + fileName[0:27] + '/' )
continue
#~ Get the bands
raw_counts = n[1]
inc_angle = n[2]
#~ NICE image (roughness)
pol = n.bands()[3]['polarization']
if pol == 'HH':
ph = (2.20495, -14.3561e-2, 11.28e-4)
sigma0_hh_ref = exp( ( ph[0]+inc_angle*ph[1]+inc_angle**2*ph[2])*log(10) )
roughness = n[3]/sigma0_hh_ref
elif pol == 'VV':
pv = (2.29373, -15.393e-2, 15.1762e-4)
sigma0_vv_ref = exp( ( pv[0]+inc_angle*pv[1]+inc_angle**2*pv[2])*log(10) )
roughness = n[3]/sigma0_vv_ref
#~ Create new band
n.add_band(bandID=4, array=roughness, \
parameters={'name':'roughness', \
'wkv': 'surface_backwards_scattering_coefficient_of_radar_wave', \
'dataType': 6})
# Reproject image into Lat/Lon WGS84 (Simple Cylindrical) projection
# 1. Cancel previous reprojection
# 2. Get corners of the image and the pixel resolution
# 3. Create Domain with stereographic projection, corner coordinates 1000m
# 4. Reproject
# 5. Write image
n.reproject() # 1.
lons, lats = n.get_corners() # 2.
# Pixel resolution
#~ pxlRes = distancelib.getPixelResolution(array(lats), array(lons), n.shape())
#~ pxlRes = array(pxlRes)*360/40000 # great circle distance
pxlRes = array(distancelib.getPixelResolution(array(lats), array(lons), n.shape(), 'deg'))
ipdb.set_trace()
if min(lats) >= 65 and max(lats) >= 75 and max(lats)-min(lats) >= 13:
pxlRes = array([0.00065, 0.00065])*2 # make the resolution 150x150m
#~ pxlRes = pxlRes*7 # make the resolution worser
srsString = "+proj=latlong +datum=WGS84 +ellps=WGS84 +no_defs"
#~ extentString = '-lle %f %f %f %f -ts 3000 3000' % (min(lons), min(lats), max(lons), max(lats))
extentString = '-lle %f %f %f %f -tr %f %f' % (min(lons), min(lats), \
max(lons), max(lats), pxlRes[1], pxlRes[0])
d = Domain(srs=srsString, ext=extentString) # 3.
n.reproject(d) # 4.
if useMask:
# get array with watermask (landmask) b
# it must be done after reprojection!
# 1. Get Nansat object with watermask
# 2. Get array from Nansat object. 0 - land, 1 - water
#wm = n.watermask(mod44path='/media/magDesk/media/SOLabNFS/store/auxdata/coastline/mod44w/')
wm = n.watermask(mod44path='/media/data/data/auxdata/coastline/mod44w/')
wmArray = wm[1]
#~ ОШИБКА numOfColor=255 не маскирует, потому что в figure.apply_mask: availIndeces = range(self.d['numOfColor'], 255 - 1)
#~ n.write_figure(fileName=figureName, bands=[3], \
#~ numOfColor=255, mask_array=wmArray, mask_lut={0: 0},
#~ clim=[0,0.15], cmapName='gray', transparency=0) # 5.
n.write_figure(fileName=figureName, bands=[4], \
mask_array=wmArray, mask_lut={0: [0,0,0]},
clim=[0,2], cmapName='gray', transparency=[0,0,0]) # 5.
else:
n.write_figure(fileName=figureName, bands=[1], \
clim=[0,2], cmapName='gray', transparency=[0,0,0]) # 5.
# open the input image and convert to RGBA for further tiling with slbtiles
input_img = Image.open(figureName)
output_img = input_img.convert("RGBA")
output_img.save(figureName)
# make KML image
n.write_kml_image(kmlFileName=kmlName, kmlFigureName=figureName)
#~ Change the file permissions
os.chmod(oPath, 0777)
os.chmod(oPath + fileName[0:27] + '/', 0777)
os.chmod(kmlName, 0777)
os.chmod(figureName, 0777)
#~ Change the owner and group
#~ os.chown(oPath, 1111, 1111)
#~ os.chown(oPath + fileName[0:27] + '/', 1111, 1111)
#~ os.chown(kmlName, 1111, 1111)
#~ os.chown(figureName, 1111, 1111)
#~ garbage collection
gc.collect()示例2: array
# 需要导入模块: from nansat import Nansat [as 别名]
# 或者: from nansat.Nansat import write_kml_image [as 别名]
# 4. Reproject
# 5. Write image
n.reproject() # 1.
lons, lats = n.get_corners() # 2.
pxlRes = distancelib.getPixelResolution(array(lats), array(lons), n.shape(), units="deg")
srsString = "+proj=latlong +datum=WGS84 +ellps=WGS84 +no_defs"
#~ extentString = '-lle %f %f %f %f -ts 3000 3000' % (min(lons), min(lats), max(lons), max(lats))
extentString = '-lle %f %f %f %f -tr %f %f' % (min(lons), min(lats), \
max(lons), max(lats), pxlRes[1], pxlRes[0])
d = Domain(srs=srsString, ext=extentString) # 3.
print d
n.reproject(d) # 4.
# get array with watermask (landmask) b
# it must be done after reprojection!
# 1. Get Nansat object with watermask
# 2. Get array from Nansat object. 0 - land, 1 - water
#wm = n.watermask(mod44path='/media/magDesk/media/SOLabNFS/store/auxdata/coastline/mod44w/')
wm = n.watermask(mod44path='/media/data/data/auxdata/coastline/mod44w/')
wmArray = wm[1]
figureName = oPath + fileName + '_proj.png'
n.write_figure(fileName=figureName, clim=[3,133], bands=[2], \
mask_array=wmArray, mask_lut={0: [204, 153, 25]}) # 5.
#~ # make KML file with image borders (to be opened in Googe Earth)
#~ n.write_kml(kmlFileName=oPath + fileName + '_preview.kml')
# make KML image file with image borders (to be opened in Googe Earth)
n.write_kml_image(kmlFileName=oPath + fileName + '.kml', kmlFigureName=figureName)