本文整理汇总了Python中anuga.file.netcdf.NetCDFFile.mean_stage方法的典型用法代码示例。如果您正苦于以下问题:Python NetCDFFile.mean_stage方法的具体用法?Python NetCDFFile.mean_stage怎么用?Python NetCDFFile.mean_stage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anuga.file.netcdf.NetCDFFile
的用法示例。
在下文中一共展示了NetCDFFile.mean_stage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: sts2sww_mesh
# 需要导入模块: from anuga.file.netcdf import NetCDFFile [as 别名]
# 或者: from anuga.file.netcdf.NetCDFFile import mean_stage [as 别名]
def sts2sww_mesh(basename_in, basename_out=None,
spatial_thinning=1, verbose=False):
from anuga.mesh_engine.mesh_engine import NoTrianglesError
from anuga.pmesh.mesh import Mesh
if verbose:
print "Starting sts2sww_mesh"
mean_stage=0.
zscale=1.
if (basename_in[:-4]=='.sts'):
stsname = basename_in
else:
stsname = basename_in + '.sts'
if verbose: print "Reading sts NetCDF file: %s" %stsname
infile = NetCDFFile(stsname, netcdf_mode_r)
cellsize = infile.cellsize
ncols = infile.ncols
nrows = infile.nrows
no_data = infile.no_data
refzone = infile.zone
x_origin = infile.xllcorner
y_origin = infile.yllcorner
origin = num.array([x_origin, y_origin])
x = infile.variables['x'][:]
y = infile.variables['y'][:]
times = infile.variables['time'][:]
wind_speed_full = infile.variables['wind_speed'][:]
wind_angle_full = infile.variables['wind_angle'][:]
pressure_full = infile.variables['barometric_pressure'][:]
infile.close()
number_of_points = nrows*ncols
points_utm = num.zeros((number_of_points,2),num.float)
points_utm[:,0]=x+x_origin
points_utm[:,1]=y+y_origin
thinned_indices=[]
for i in range(number_of_points):
if (i/ncols==0 or i/ncols==ncols-1 or (i/ncols)%(spatial_thinning)==0):
if ( i%(spatial_thinning)==0 or i%nrows==0 or i%nrows==nrows-1 ):
thinned_indices.append(i)
#Spatial thinning
points_utm=points_utm[thinned_indices]
number_of_points = points_utm.shape[0]
number_of_timesteps = wind_speed_full.shape[0]
wind_speed = num.empty((number_of_timesteps,number_of_points),dtype=float)
wind_angle = num.empty((number_of_timesteps,number_of_points),dtype=float)
barometric_pressure = num.empty((number_of_timesteps,number_of_points),dtype=float)
if verbose:
print "Total number of points: ", nrows*ncols
print "Number of thinned points: ", number_of_points
for i in xrange(number_of_timesteps):
wind_speed[i] = wind_speed_full[i,thinned_indices]
wind_angle[i] = wind_angle_full[i,thinned_indices]
barometric_pressure[i] = pressure_full[i,thinned_indices]
#P.plot(points_utm[:,0],points_utm[:,1],'ro')
#P.show()
if verbose:
print "Generating sww triangulation of gems data"
mesh = Mesh()
mesh.add_vertices(points_utm)
mesh.auto_segment(smooth_indents=True, expand_pinch=True)
mesh.auto_segment(mesh.shape.get_alpha() * 1.1)
try:
mesh.generate_mesh(minimum_triangle_angle=0.0, verbose=False)
except NoTrianglesError:
# This is a bit of a hack, going in and changing the data structure.
mesh.holes = []
mesh.generate_mesh(minimum_triangle_angle=0.0, verbose=False)
mesh_dic = mesh.Mesh2MeshList()
points_utm=ensure_numeric(points_utm)
assert num.alltrue(ensure_numeric(mesh_dic['generatedpointlist'])
== ensure_numeric(points_utm))
volumes = mesh_dic['generatedtrianglelist']
# Write sww intro and grid stuff.
if (basename_out is not None and basename_out[:-4]=='.sww'):
swwname = basename_out
else:
swwname = basename_in + '.sww'
if verbose: 'Output to %s' % swwname
if verbose:
print "Writing sww wind and pressure field file"
outfile = NetCDFFile(swwname, netcdf_mode_w)
sww = Write_sww([], ['wind_speed','wind_angle','barometric_pressure'])
sww.store_header(outfile, times, len(volumes), len(points_utm),
verbose=verbose, sww_precision='d')
outfile.mean_stage = mean_stage
#.........这里部分代码省略.........
示例2: urs_ungridded2sww
# 需要导入模块: from anuga.file.netcdf import NetCDFFile [as 别名]
# 或者: from anuga.file.netcdf.NetCDFFile import mean_stage [as 别名]
def urs_ungridded2sww(basename_in='o', basename_out=None, verbose=False,
mint=None, maxt=None,
mean_stage=0,
origin=None,
hole_points_UTM=None,
zscale=1):
"""
Convert URS C binary format for wave propagation to
sww format native to abstract_2d_finite_volumes.
Specify only basename_in and read files of the form
basefilename-z-mux, basefilename-e-mux and
basefilename-n-mux containing relative height,
x-velocity and y-velocity, respectively.
Also convert latitude and longitude to UTM. All coordinates are
assumed to be given in the GDA94 datum. The latitude and longitude
information is assumed ungridded grid.
min's and max's: If omitted - full extend is used.
To include a value min ans max may equal it.
Lat and lon are assumed to be in decimal degrees.
origin is a 3-tuple with geo referenced
UTM coordinates (zone, easting, northing)
It will be the origin of the sww file. This shouldn't be used,
since all of anuga should be able to handle an arbitary origin.
The mux point info is NOT relative to this origin.
URS C binary format has data organised as TIME, LONGITUDE, LATITUDE
which means that latitude is the fastest
varying dimension (row major order, so to speak)
In URS C binary the latitudes and longitudes are in assending order.
Note, interpolations of the resulting sww file will be different
from results of urs2sww. This is due to the interpolation
function used, and the different grid structure between urs2sww
and this function.
Interpolating data that has an underlying gridded source can
easily end up with different values, depending on the underlying
mesh.
consider these 4 points
50 -50
0 0
The grid can be
-
|\| A
-
or;
-
|/| B
-
If a point is just below the center of the midpoint, it will have a
+ve value in grid A and a -ve value in grid B.
"""
from anuga.mesh_engine.mesh_engine import NoTrianglesError
from anuga.pmesh.mesh import Mesh
files_in = [basename_in + WAVEHEIGHT_MUX_LABEL,
basename_in + EAST_VELOCITY_LABEL,
basename_in + NORTH_VELOCITY_LABEL]
quantities = ['HA','UA','VA']
# instantiate urs_points of the three mux files.
mux = {}
for quantity, file in map(None, quantities, files_in):
mux[quantity] = Read_urs(file)
# Could check that the depth is the same. (hashing)
# handle to a mux file to do depth stuff
a_mux = mux[quantities[0]]
# Convert to utm
lat = a_mux.lonlatdep[:,1]
long = a_mux.lonlatdep[:,0]
points_utm, zone = convert_from_latlon_to_utm(latitudes=lat,
longitudes=long)
elevation = a_mux.lonlatdep[:,2] * -1
# grid (create a mesh from the selected points)
# This mesh has a problem. Triangles are streched over ungridded areas.
# If these areas could be described as holes in pmesh, that would be great.
# I can't just get the user to selection a point in the middle.
# A boundary is needed around these points.
# But if the zone of points is obvious enough auto-segment should do
# a good boundary.
mesh = Mesh()
mesh.add_vertices(points_utm)
mesh.auto_segment(smooth_indents=True, expand_pinch=True)
#.........这里部分代码省略.........