def setUp(self):
D = Data(None, None)
D.data = np.random.random((10, 20))
lon = np.arange(-10.,10.) # -10 ... 9
lat = np.arange(-60., 50., 2.) # -60 ... 48
D.lon, D.lat = np.meshgrid(lon, lat)
self.x = D
def setUp(self):
D = Data(None, None)
tmp = np.random.random((55, 20))
D.data = np.ma.array(tmp, mask=tmp != tmp)
lon = np.arange(-10., 10.) # -10 ... 9
lat = np.arange(-60., 50., 2.) # -60 ... 48
LON, LAT = np.meshgrid(lon, lat)
D.lon = np.ma.array(LON, mask=LON != LON)
D.lat = np.ma.array(LAT, mask=LAT != LAT)
self.x = D
def setUp(self):
D = Data(None, None)
tmp = np.random.random((55, 20))
D.data = np.ma.array(tmp, mask=tmp!=tmp)
lon = np.arange(-10.,10.) # -10 ... 9
lat = np.arange(-60., 50., 2.) # -60 ... 48
LON, LAT = np.meshgrid(lon, lat)
D.lon = np.ma.array(LON, mask=LON!=LON)
D.lat = np.ma.array(LAT, mask=LAT!=LAT)
self.x = D
def test_rasterize_init(self):
x = Data(None, None)
x._init_sample_object(ny=1, nx=272)
x.lon = np.random.random(272)*10. + 5. # 5 ... 15
x.lat = np.random.random(272)*20. + 0. # 0 ... 20
lon = np.random.random((10,20))
lat = np.random.random((30,20))
with self.assertRaises(ValueError):
x._rasterize(lon, lat, radius=0.1)
lon = np.random.random((10,20))
lat = np.random.random((10,20))
with self.assertRaises(ValueError):
x._rasterize(lon, lat, radius=None)
def test_rasterize_init(self):
x = Data(None, None)
x._init_sample_object(ny=1, nx=272)
x.lon = np.random.random(272) * 10. + 5. # 5 ... 15
x.lat = np.random.random(272) * 20. + 0. # 0 ... 20
lon = np.random.random((10, 20))
lat = np.random.random((30, 20))
with self.assertRaises(ValueError):
x._rasterize(lon, lat, radius=0.1)
lon = np.random.random((10, 20))
lat = np.random.random((10, 20))
with self.assertRaises(ValueError):
x._rasterize(lon, lat, radius=None)
def test_rasterize_data(self):
"""
testdataset
+---+---+---+
|1.2|2.3| |
+---+---+---+
| | |0.7|
+---+---+---+
| |5.2| |
+---+---+---+
"""
x = Data(None, None)
x._init_sample_object(ny=1, nx=272)
x.lon = np.asarray([2.25, 2.45, 1.8, 3.6])
x.lat = np.asarray([11.9, 10.1, 10.2, 11.3])
x.data = np.asarray([5.2, 2.3, 1.2, 0.7])
# target grid
lon = np.asarray([1.5, 2.5, 3.5])
lat = np.asarray([10., 11., 12.])
LON, LAT = np.meshgrid(lon, lat)
# rasterize data
# no valid data
res = x._rasterize(LON, LAT, radius=0.000001, return_object=True)
self.assertEqual(res.data.mask.sum(), np.prod(LON.shape))
with self.assertRaises(ValueError):
res = x._rasterize(LON, LAT, radius=0.000001, return_object=False)
# check valid results
res = x._rasterize(LON, LAT, radius=0.5, return_object=True)
self.assertEqual(res.data[0,0], 1.2)
self.assertEqual(res.data[0,1], 2.3)
self.assertEqual(res.data[1,2], 0.7)
self.assertEqual(res.ny*res.nx - res.data.mask.sum(), 4)
def test_rasterize_data(self):
"""
testdataset
+---+---+---+
|1.2|2.3| |
+---+---+---+
| | |0.7|
+---+---+---+
| |5.2| |
+---+---+---+
"""
x = Data(None, None)
x._init_sample_object(ny=1, nx=272)
x.lon = np.asarray([2.25, 2.45, 1.8, 3.6])
x.lat = np.asarray([11.9, 10.1, 10.2, 11.3])
x.data = np.asarray([5.2, 2.3, 1.2, 0.7])
# target grid
lon = np.asarray([1.5, 2.5, 3.5])
lat = np.asarray([10., 11., 12.])
LON, LAT = np.meshgrid(lon, lat)
# rasterize data
# no valid data
res = x._rasterize(LON, LAT, radius=0.000001, return_object=True)
self.assertEqual(res.data.mask.sum(), np.prod(LON.shape))
with self.assertRaises(ValueError):
res = x._rasterize(LON, LAT, radius=0.000001, return_object=False)
# check valid results
res = x._rasterize(LON, LAT, radius=0.5, return_object=True)
self.assertEqual(res.data[0, 0], 1.2)
self.assertEqual(res.data[0, 1], 2.3)
self.assertEqual(res.data[1, 2], 0.7)
self.assertEqual(res.ny * res.nx - res.data.mask.sum(), 4)
#~ AMZ 7 (20.000S, 66.377W) (1.239S, 79.729W) (11.439N, 68.800W) (11.439N, 50.000W) (20.000S, 50.000W)
#~ CAM 6 (11.439N, 68.800W) (1.239S, 79.729W) (28.566N, 118.323W) (28.566N, 90.315W)
tmp = np.ones((180, 360))
d = Data(None, None)
d.data = np.ma.array(tmp, mask=tmp!=tmp)
d.cell_area = np.ones_like(tmp)
lon = np.arange(-180., 180.) + 0.5
lat = np.arange(-90., 90.) + 0.5
d.lon, d.lat = np.meshgrid(lon, lat)
# Basemap plots
m = SingleMap(d) # this is supposed to make a baemap plot with stripes
m.backend = 'basemap' # overwrite default
m._draw = m._draw_basemap
m.plot(polygons=[P1, P2], proj_prop={'projection':'robin', 'lon_0':0.}, vmin_polygons=0., vmax_polygons=250.)
plt.title('Basemap')
# cartopy plots
m1 = SingleMap(d, backend='cartopy')
m1.plot(polygons=[P1, P2], proj_prop={'projection':'robin', 'lon_0':0.}, vmin_polygons=0., vmax_polygons=250.)
plt.title('Cartopy')
plt.show()
def _import_regional_file(self,
region_file,
varname,
targetgrid=None,
logfile=None):
"""
check if the regional file can be either imported or if
regions are provided as vector data. In the latter case
the regions are rasterized and results are stored in a netCDF
file
Parameters
----------
region_file : str
name of file defining the region. This is either a netCDF
file which contains the mask as different integer values
or it is a *.reg file which contains the regions as
vector data.
varname : str
name of variable in netCDF file
targetgrid : str
name of targetgrid; either 't63grid' or the name of a file
with a valid geometry
Returns
-------
region_filename, region_file_varname
"""
if not os.path.exists(region_file):
raise ValueError('ERROR: region file is not existing: ' +
region_file)
ext = os.path.splitext(region_file)[1]
if ext == '.nc':
# netCDF file was given. Try to read variable
if varname is None:
raise ValueError('ERROR: no variable name given!')
try:
tmp = Data(region_file, varname, read=True)
except:
raise ValueError(
'ERROR: the regional masking file can not be read!')
del tmp
# everything is fine
return region_file, varname
elif ext == '.reg':
# regions were given as vector files. Read it and
# rasterize the data and store results in a temporary
# file
import tempfile
if targetgrid is None:
raise ValueError(
'ERROR: targetgrid needs to be specified for vectorization of regions!'
)
if targetgrid == 't63grid':
ls_mask = get_T63_landseamask(True,
area='global',
mask_antarctica=False)
else:
ls_mask = get_generic_landseamask(True,
area='global',
target_grid=targetgrid,
mask_antarctica=False)
# temporary netCDF filename
region_file1 = tempfile.mktemp(prefix='region_mask_', suffix='.nc')
R = RegionParser(region_file) # read region vector data
M = Raster(ls_mask.lon, ls_mask.lat)
polylist = []
if logfile is not None:
logf = open(logfile, 'w')
else:
logf = None
id = 1
for k in R.regions.keys():
reg = R.regions[k]
polylist.append(pycmbsPolygon(id, zip(reg.lon, reg.lat)))
if logf is not None: # store mapping table
logf.write(k + '\t' + str(id) + '\n')
id += 1
M.rasterize_polygons(polylist)
if logf is not None:
logf.close()
# generate dummy output file
O = Data(None, None)
O.data = M.mask
O.lat = ls_mask.lat
O.lon = ls_mask.lon
varname = 'regions'
O.save(region_file1, varname=varname, format='nc', delete=True)
print('Regionfile was store in file: %s' % region_file1)
# check again that file is readable
try:
tmp = Data(region_file1, varname, read=True)
except:
print region_file1, varname
raise ValueError(
'ERROR: the generated region file is not readable!')
del tmp
return region_file1, varname
else:
raise ValueError('ERROR: unsupported file type')
def _import_regional_file(self, region_file, varname, targetgrid=None, logfile=None):
"""
check if the regional file can be either imported or if
regions are provided as vector data. In the latter case
the regions are rasterized and results are stored in a netCDF
file
Parameters
----------
region_file : str
name of file defining the region. This is either a netCDF
file which contains the mask as different integer values
or it is a *.reg file which contains the regions as
vector data.
varname : str
name of variable in netCDF file
targetgrid : str
name of targetgrid; either 't63grid' or the name of a file
with a valid geometry
Returns
-------
region_filename, region_file_varname
"""
if not os.path.exists(region_file):
raise ValueError('ERROR: region file is not existing: ' + region_file)
ext = os.path.splitext(region_file)[1]
if ext == '.nc':
# netCDF file was given. Try to read variable
if varname is None:
raise ValueError('ERROR: no variable name given!')
try:
tmp = Data(region_file, varname, read=True)
except:
raise ValueError('ERROR: the regional masking file can not be read!')
del tmp
# everything is fine
return region_file, varname
elif ext == '.reg':
# regions were given as vector files. Read it and
# rasterize the data and store results in a temporary
# file
import tempfile
if targetgrid is None:
raise ValueError('ERROR: targetgrid needs to be specified for vectorization of regions!')
if targetgrid == 't63grid':
ls_mask = get_T63_landseamask(True, area='global', mask_antarctica=False)
else:
ls_mask = get_generic_landseamask(True, area='global', target_grid=targetgrid,
mask_antarctica=False)
# temporary netCDF filename
region_file1 = tempfile.mktemp(prefix='region_mask_', suffix='.nc')
R = RegionParser(region_file) # read region vector data
M = Raster(ls_mask.lon, ls_mask.lat)
polylist = []
if logfile is not None:
logf = open(logfile, 'w')
else:
logf = None
id = 1
for k in R.regions.keys():
reg = R.regions[k]
polylist.append(pycmbsPolygon(id, zip(reg.lon, reg.lat)))
if logf is not None: # store mapping table
logf.write(k + '\t' + str(id) + '\n')
id += 1
M.rasterize_polygons(polylist)
if logf is not None:
logf.close()
# generate dummy output file
O = Data(None, None)
O.data = M.mask
O.lat = ls_mask.lat
O.lon = ls_mask.lon
varname = 'regions'
O.save(region_file1, varname=varname, format='nc', delete=True)
print('Regionfile was store in file: %s' % region_file1)
# check again that file is readable
try:
tmp = Data(region_file1, varname, read=True)
except:
print region_file1, varname
raise ValueError('ERROR: the generated region file is not readable!')
del tmp
return region_file1, varname
else:
raise ValueError('ERROR: unsupported file type')
