def readVar(fn, vstr, cl=1):
xDict = read3dDataFromNetCDF(fn, vstr, cl)
v = xDict['v']
x = xDict['x']
y = xDict['y']
z = xDict['z']
xDict = None
return v, x, y, z
varname = args.varname
writeAscii = args.writeAscii
#==========================================================#
# Obtain a list of files to include.
fileNos, fileList = filesFromList( fileKey+'*' )
fig = plt.figure(num=1, figsize=(12,10))
for fn in fileNos:
VNU = varname.upper()
if('MAG' in VNU or 'U1' in VNU or 'U2' in VNU or 'DIR' in VNU):
dataDict = read3dDataFromNetCDF( fileList[fn] , 'u', cl )
u = dataDict['v']
dataDict = read3dDataFromNetCDF( fileList[fn] , 'v', cl )
v = dataDict['v']
if('MAG' in VNU ): # vr := Umag
vr = np.sqrt( u**2 + v**2 ); u = None; v = None
else:
um = np.mean( u, axis=(0) ); vm = np.mean( v, axis=(0) )
a = np.arctan( vm/(um+1.e-5) ); um = None; vm = None
if( 'U1' in VNU ):
vr = u * np.cos(a) + v * np.sin(a)
elif('U2' in VNU): # U2
vr =-u * np.sin(a) + v * np.cos(a)
else:# direction
vr = np.arctan( v/(u+1.e-5) ) * (180./np.pi)
#==========================================================#
'''
Establish two boolean variables which indicate whether the created variable is an
independent or dependent variable in function createNetcdfVariable().
'''
parameter = True
variable = False
strKey = inputIfNone(strKey, " Enter search string: ")
fileNos, fileList = filesFromList(strKey + "*")
for fn in fileNos:
# - - - - - - - - - - - - - - - - - - - - - - - - - - #
# First fluctuation component
cl = 1
ncDict = read3dDataFromNetCDF(fileList[fn], varnames[0], cl)
v1 = ncDict['v'] # 'v' is a generic name for a variable in ncDict
# Second fluctuation component
ncDict = read3dDataFromNetCDF(fileList[fn], varnames[1], cl)
v2 = ncDict['v']
# Dims
nt, nz, ny, nx = np.shape(v1)
# - - - - - - - - - - - - - - - - - - - - - - - - - - #
# Spatial coords and time
x = ncDict['x']
y = ncDict['y']
z = ncDict['z']
time = ncDict['time']
normalize = args.normalize
Nbins = args.nbins
mode = args.mode
cl = abs(args.coarse)
varname = args.varname
#==========================================================#
# Obtain a list of files to include.
fileNos, fileList = filesFromList(fileKey + '*')
first = True
fig = None
for fn in fileNos:
dataDict = read3dDataFromNetCDF(fileList[fn], varname, cl)
v = dataDict['v']
x = dataDict['x']
y = dataDict['y']
z = dataDict['z']
time = dataDict['time']
if (first):
infoStr = '''
Coord. range:
min(x)={0} ... max(x)={1}, nx = {2}
min(y)={3} ... max(y)={4}, ny = {5}
min(z)={6} ... max(z)={7}, nz = {8}
'''.format(\
np.min(x), np.max(x), len(x),\
np.min(y), np.max(y), len(y),\
'''
Establish two boolean variables which indicate whether the created variable is an
independent or dependent variable in function createNetcdfVariable().
'''
parameter = True; variable = False
# Create a dict that is passed into the function read3dDataFromNetCDF
nameDict = dict()
nameDict['xname'] = args.xname
nameDict['yname'] = args.yname
nameDict['zname'] = args.zname
# First fluctuation component
nameDict['varname'] = varname[0]
cl = 1
ncDict = read3dDataFromNetCDF( filename , nameDict, cl )
v = ncDict['v'] # 'v' is a generic name for a variable in ncDict
# Spatial coords and time
x = ncDict['x']; y = ncDict['y']; z = ncDict['z']
time = ncDict['time']
# Now check whether the given indices make sense
# Here we set i = 0 and j = 0.
ijk1 = sensibleIds( np.array([0,0,kIds[0]]), x, y, z )
ijk2 = sensibleIds( np.array([0,0,kIds[1]]), x, y, z )
print(' Check (1): i, j, k = {}'.format(ijk1))
print(' Check (2): i, j, k = {}'.format(ijk2))
# = = = = = = = = = = = = =
# Mean and variance
if (mode == 'mean'): sfunc = bs_stats.mean
if (mode == 'std'): sfunc = bs_stats.std
if (mode == 'var'): sfunc = bs_stats.var
# Obtain a list of files to include.
fileNos, fileList = filesFromList(fileKey + '*', allfiles)
fig = plt.figure(num=1, figsize=(12, 10))
ax = fig.add_axes([0.1, 0.075, 0.875, 0.81]) #[left, top, width, height]
for fn in fileNos:
vr = None
for i in range(len(varnames)):
if (varnames[i].upper() == 'U1' or varnames[i].upper() == 'U2'):
dataDict = read3dDataFromNetCDF(fileList[fn], 'u', 1)
u = dataDict['v']
dataDict = read3dDataFromNetCDF(fileList[fn], 'v', 1)
v = dataDict['v']
um = np.mean(u, axis=(0))
vm = np.mean(v, axis=(0))
a = np.arctan(vm / (um + 1.e-5))
um = None
vm = None
# Carry the data within dataDict.
if (varnames[i].upper() == 'U1'):
dataDict['v'] = u * np.cos(a) + v * np.sin(a)
else:
dataDict['v'] = -u * np.sin(a) + v * np.cos(a)
# Free memory
u = None
ijk1 = args.ijk1 ijk2 = args.ijk2 axisLim = args.axisLim nkpoints = args.nkpoints ustar = args.ustar holewidth = args.holewidth weighted = args.weighted npixels = args.npixels ofile = args.outputToFile printOn = args.printOn #==========================================================# first = True fig = None # First fluctuation component ncDict = read3dDataFromNetCDF(filename, varnames[0], cl) v1 = ncDict['v'] # 'v' is a generic name for a variable in ncDict # Second fluctuation component ncDict = read3dDataFromNetCDF(filename, varnames[1], cl) v2 = ncDict['v'] # Spatial coords and time x = ncDict['x'] y = ncDict['y'] z = ncDict['z'] time = ncDict['time'] # Plot coord. information. This aids the user in the beginning. infoStr = ''' Coord. range:
complexOn = args.complex
ofile = args.outputToFile
saveFig = args.save
gridOn = args.gridOn
limsOn = args.limsOn
#==========================================================#
'''
Establish two boolean variables which indicate whether the created variable is an
independent or dependent variable in function createNetcdfVariable().
'''
parameter = True; variable = False
# Read data from NETCDF file
cl = 1
ncDict = read3dDataFromNetCDF( filename , varname, cl )
v = ncDict['v'] # 'v' is a generic name for a variable in ncDict
# Spatial coords and time
x = ncDict['x']
y = ncDict['y']
z = ncDict['z']
time = ncDict['time']
# Plot coord. information. This aids the user in the beginning.
infoStr = '''
Coord. range:
min(x)={0} ... max(x)={1}, nx = {2}
min(y)={3} ... max(y)={4}, ny = {5}
min(z)={6} ... max(z)={7}, nz = {8}
'''.format(\
