def example(ncNameFile):
#Input file is a list of each output file on its own line.
#Paraview has a hard time animating the 0 time step .nc files. Maybe it's an issue with the MPAS reader?
#We can get around it by creating vtk files of the fields of interest named fnameN.vtk where N is an integer that indicates time.
#store the names of the files we want in order in a file
#ncNameFile = 'ncNames.txt'
fp = open(ncNameFile,'r')
#output the files to
outNameBase = 'june'
#
i = 0
for line in fp:
ncfname = line.rstrip('\n') #do we have to strip off any characters like \n?
if (i==0):
#reference field for orientation
vtkfname = outNameBase+'_ref'+'.vtk'
data = output_data.open_netcdf_data(ncfname)
#header and mesh info
fvtk = output_data.write_vtk_header_polydata(vtkfname, ncfname)
nNodes = output_data.write_vtk_xyzNodes(fvtk, data)
nCells = output_data.write_vtk_polygons(fvtk, data)
fvtk.write('\nCELL_DATA '+str(nCells)+'\n')
output_data.write_vtk_staticGeoFields(f,data,nCells)
fvtk.close()
data.close()
#
vtkfname = outNameBase+str(i)+'.vtk'
data = output_data.open_netcdf_data(ncfname)
#header and mesh info
fvtk = output_data.write_vtk_header_polydata(vtkfname, ncfname)
nNodes = output_data.write_vtk_xyzNodes(fvtk, data)
nCells = output_data.write_vtk_polygons(fvtk, data)
#write cell data
fvtk.write('\nCELL_DATA '+str(nCells)+'\n')
time = 0
vLevel = 18
output_data.write_vtk_cellCenterVelocity(fvtk, data, time, vLevel, nCells)
output_data.write_vtk_var_timeLevelCells(fvtk, 'pv_cell', data, vLevel, time, nCells)
i = i+1
#close files
data.close()
fvtk.close()
fp.close()
def example():
# file properties
ncfname = "/arctic1/nick/cases/cfsr/output.2006-08-07_12.00.00.nc"
# ncfname = '/home/nickszap/research/mpas/output.2010-10-23_00:00:00.nc' #input file
vtkfname = "plotTest.vtk" # output file
data = output_data.open_netcdf_data(ncfname)
# open the output vtk file and write header. -------------------
fvtk = output_data.write_vtk_header_polydata(vtkfname, ncfname)
# write nodes and cells
nNodes = output_data.write_vtk_xyzNodes(fvtk, data)
nCells = output_data.write_vtk_polygons(fvtk, data)
nLevels = len(data.dimensions["nVertLevels"])
# write some cell data --------------------
fvtk.write("\nCELL_DATA " + str(nCells) + "\n")
output_data.write_vtk_staticGeoFields(fvtk, data, nCells)
# time dependent stuff goes in different files
time = 0
output_data.write_vtk_pressureHeights(fvtk, data, nCells, time, nLevels, 50000) # 500mb = 50,000Pa
# write some node data
# close the .nc and vtk files
data.close()
fvtk.close()
def driver_ncGeo2vtk(ncfname):
'''
given .nc (MPAS NETCDF) file, output the surface geography data into classic vtk format.
The MPAS NetCDF reader in Paraview loads only the "critical" netcdf variables, ie with time and vertLevels.
Rather than edit that reader, we can create a file of the vars we care about on the scvt mesh rather than the dual.
I think they have to use the dual for the volume mesh since the elements need to be of supported VTK type (eg prism, hex,...)
'''
#file properties
#ncfname = '/home/nickszap/research/mpas/output.2010-10-23_00:00:00.nc' #input file
vtkfname = 'geoTest.vtk' #output file
data = output_data.open_netcdf_data(ncfname)
#open the output vtk file and write header.
fvtk = output_data.write_vtk_header_polydata(vtkfname, ncfname)
#write nodes and cells
nNodes = output_data.write_vtk_xyzNodes(fvtk, data)
nCells = output_data.write_vtk_polygons(fvtk, data)
vLevels = len(data.dimensions['nVertLevels'])
nTimes = len(data.dimensions['Time'])
#write some geographic cell data
fvtk.write('\nCELL_DATA '+str(nCells)+'\n')
write_vtk_staticGeoFields(fvtk,data,nCells)
write_vtk_timeGeoFields(fvtk,data,nCells, nTimes)
#write node data (none for geog)
#close the .nc and vtk files
data.close()
fvtk.close()
def example_2pvu():
# fpath = '/arctic1/nick/cases/v1.0/x4/august/kf/v1.1/x4.kf.output.2006-08-01_00.00.00.nc'
fpath = "/arctic1/nick/cases/v1.0/x4/august/tiedtke/v1.1/x4.t.output.2006-08-08_00.00.00.nc"
# fpath = '/arctic1/nick/cases/v1.0/x4/august/kf/v1.1/x4.kf.output.2006-08-08_00.00.00.nc'
# fnames = searchFiles()
# for iFile, fpath in enumerate(fnames):
data = output_data.open_netcdf_data(fpath)
for timeInd in xrange(0, 28, 4):
# for timeInd in [0]:
# open the output vtk file and write header, nodes, and cells
vtkfname = "x4_t_2006-08-01_1day." + str(28 + timeInd) + ".vtk"
# vtkfname = 'x4_cfsr_2006-07-25_1day.'+str(iFile)+'.vtk'
fvtk = output_data.write_vtk_header_polydata(vtkfname, fpath)
# fvtk = open(vtkfname,'w'); nCells = 163842
nNodes = output_data.write_vtk_xyzNodes(fvtk, data)
nCells = output_data.write_vtk_polygons(fvtk, data)
# write some cell dataa
fvtk.write("\nCELL_DATA " + str(nCells) + "\n")
# calc values
# timeInd = 0
epv_ht, theta_trop = calc_height_theta_2PVU(data, timeInd)
output_data.write_levelData_float("ht_2pvu", fvtk, epv_ht, nCells)
output_data.write_levelData_float("theta_2pvu", fvtk, theta_trop, nCells)
fvtk.close()
data.close()
def derivedSfcs(ncfname, vtkfname):
#write some derived surfaces to file
data = output_data.open_netcdf_data(ncfname)
#header info
fvtk = output_data.write_vtk_header_polydata(vtkfname, ncfname)
nNodes = output_data.write_vtk_xyzNodes(fvtk, data)
nCells = output_data.write_vtk_polygons(fvtk, data)
nLevels = len(data.dimensions['nVertLevels'])
#cell data
fvtk.write('\nCELL_DATA '+str(nCells)+'\n')
#geo for reference
output_data.write_vtk_staticGeoFields(f,data,nCells)
time = 0
#500 mb
output_data.write_vtk_pressureHeights(fvtk, data, nCells, time, vLevels, 50000.)
#theta on dynamic tropopause
pv = np.empty((nCells,nLevels), dtype=float)
for hcell in range(nCells):
for l in range(nLevels):
pv[hcell,l] = vars.calc_ertelPV(data, 'theta', time, hcell, l, nLevels)
#
pvuVal = 2.
thetaVal = np.empty(nCells)
for hcell in range(nCells):
(l,dl) = output_data.calcIndexOfValue(pvuVal,pv[hcell,:], nLevels)
thetaVal[hcell] = output_data.calcValueOfIndex(l,dl,data.variables['theta'][time,hcell,:])
output_data.write_levelData_float('theta_pv', fvtk, thetaVal, nCells)
#slp
slp = np.empty(nCells)
for hcell in range(nCells):
slp[hcell] = vars.calc_slp(data, hcell, nLevels, time)
output_data.write_levelData_float('slp', fvtk, slp, nCells)
#close da files
fvtk.close()
data.close()
def example_vars():
# for every 6 hours of the IC CFSR data,
# write a vtk file with slp, 500mb heights, and theta on 2 pv surface
t0 = dt.datetime(2006, 6, 1, 0)
# tf = dt.datetime(2006,9,29,18)
tf = dt.datetime(2006, 6, 1, 13)
h6 = dt.timedelta(hours=6)
cfsrPath = "/arctic1/nick/cases/cfsr/"
vtkBase = "cfsrIC."
i = 1
t = t0
while t <= tf: # since increment t after check, don't do
# open the .nc data file for this datetime
tString = cfsr.form_cfsrTimeString(t)
ncName = "vert_sfc." + tString + ".nc" # initial condition netcdf file
ncName = cfsrPath + ncName
data = output_data.open_netcdf_data(ncName)
# open the output vtk file and write header. -------------------
vtkfname = vtkBase + str(i - 1) + ".vtk"
fvtk = output_data.write_vtk_header_polydata(vtkfname, ncName)
# write nodes and cells
nNodes = output_data.write_vtk_xyzNodes(fvtk, data)
nCells = output_data.write_vtk_polygons(fvtk, data)
nLevels = len(data.dimensions["nVertLevels"])
# write some cell data --------------------
fvtk.write("\nCELL_DATA " + str(nCells) + "\n")
timeInd = 0
#
data.close()
fvtk.close()
# increment day
t = t0 + i * h6
i = i + 1
def example_difference_vtk():
# For this, we have mpas outputs and CFSR ICs every 6 hours.
# The files are on the same horizontal and vertical mesh
t0 = dt.datetime(2006, 7, 15, 0)
mpasFile = mpasOutputName(t0)
mpasData = netCDF4.Dataset(mpasFile, "r")
# fields: config_frames_per_outfile tells us when we need to get new file
# config_output_interval time separation between values
nTimeInds = 28
h6 = dt.timedelta(hours=6)
s = cfsr.form_cfsrTimeString(t0)
diffFile = "diff." + s + ".6hr.vtk"
fvtk = output_data.write_vtk_header_polydata(diffFile, s)
# write nodes and cells
nNodes = output_data.write_vtk_xyzNodes(fvtk, mpasData)
nCells = output_data.write_vtk_polygons(fvtk, mpasData)
nLevels = len(mpasData.dimensions["nVertLevels"])
fieldKeys = [
"uReconstructX",
"uReconstructY",
"uReconstructZ",
"uReconstructZonal",
"uReconstructMeridional",
"w",
"theta",
] # ,'qv','qc','qr']
for i in xrange(nTimeInds):
# for i in xrange(4,5,1):
t = t0 + i * h6
initFile = loc_initFile(t)
initData = netCDF4.Dataset(initFile, "r")
for key in fieldKeys:
varInit = initData.variables[key][0, :, :]
varMPAS = mpasData.variables[key][i, :, :]
varMPAS -= varInit
s = "Statistics for MPAS-Init for variable {0} at timInd {1}\n".format(key, i)
m = np.mean(varMPAS)
dev = np.std(varMPAS)
maxd = np.max(np.abs(varMPAS))
s += "{0},\t{1},\t{2}\n".format(m, dev, maxd)
print s
s = ""
# diffData.variables[key][i,:,:] = varMPAS[:,:]
# histograms
varMPAS.flatten() # else each column is separate dataset
nBins = 100
plt2.hist(varMPAS, bins=nBins, normed=False)
# save instead of displaying
figName = key + ".t" + str(i)
plt2.title(figName)
# plt2.savefig(figName+'.png')
plt2.autoscale(enable=True, axis="x", tight=True)
plt2.savefig(figName + ".png")
plt2.clf()
initData.close()
mpasData.close()
