def find_vis_cycles(testname):
"""Parses the output of the run to collect the cycles that were written."""
try:
keys, t, d = parse_ats.readATS(dirname(testname))
except IOError:
try:
keys, t, d = parse_ats.readATS(dirname(testname),
"visdump_surface_data.h5")
except IOError:
raise IOError(
"Unable to open {0}/visdump_data.h5 (or the surface equivalent)"
.format(testname))
d.close()
return [int(k) for k in keys]
def ats_to_pflotran_bcs_h5(directory=".", output_filename="pflotran_bcs.h5"):
ixy = mesh.meshCentroidsStructuredOrdering_3D(
order=[
"x",
], filename="visdump_surface_mesh.h5", directory=directory)
keys, times, dat = parse_ats.readATS(directory,
"visdump_surface_data.h5",
timeunits='s')
with h5py.File(os.path.join(directory, output_filename), 'w') as fout:
fout.create_dataset("time [s]", data=np.array(times))
T = fout.create_group("surface temperature [K]")
for i, k in enumerate(keys):
T.create_dataset(
"%d" % i,
data=dat['surface-temperature.cell.0'][k][:][ixy['id']])
flx = fout.create_group("outward molar flux [mol m^-2 s^-1]")
# need the face area
face_areas = mesh.meshElemVolume(filename="visdump_surface_mesh.h5",
directory=directory)
for i, k in enumerate(keys):
flux_dat = dat['surface_subsurface_flux.cell.0'][k][:]
flux_dat = flux_dat / face_areas
flx.create_dataset("%d" % i, data=flux_dat[ixy['id']])
def water_table(dirname, datum=None, v86=False, patm=101325.):
prefix = "" if v86 else "surface-"
# get the ponded depth
keys, times, dats = parse_ats.readATS(dirname, "visdump_surface_data.h5")
pd = parse_ats.getSurfaceData(keys, dats, prefix + "ponded_depth")
elev_surf = dats[prefix + "elevation.cell.0"][keys[0]][0]
dats.close()
if datum is None:
datum = elev_surf
datum_offset = elev_surf - datum
# get the columnar pressure
wt = np.zeros((len(keys), ), 'd')
col_dat = column_data.column_data([
'pressure',
], directory=dirname)
for k in range(col_dat.shape[1]):
if pd[k] > 0:
wt[k] = pd[k] + datum_offset
else:
wt_index = np.where(col_dat[1, k, :] >= patm)[0]
if len(wt_index) is 0:
wt_index = 0
else:
wt_index = wt_index[-1]
wt[k] = col_dat[0, k, wt_index] - datum
return times, wt
def thaw_depth(dirname, datum=None, v86=False, T0=273.15):
prefix = "" if v86 else "surface-"
# get the unfrozen fraction, ponded depth
keys,times,dats = parse_ats.readATS(dirname, "visdump_surface_data.h5")
pd = parse_ats.getSurfaceData(keys, dats, prefix+"ponded_depth")
uf = parse_ats.getSurfaceData(keys, dats, prefix+"unfrozen_fraction")
elev_surf = dats[prefix+"elevation.cell.0"][keys[0]][0]
dats.close()
if datum is None:
datum = elev_surf
datum_offset = elev_surf - datum
td = np.zeros((len(keys),),'d')
# get the columnar temperature
col_dat = column_data.column_data(['temperature',], directory=dirname)
for k in range(col_dat.shape[1]):
if uf[k] == 0.:
td[k] = pd[k] + datum_offset
else:
td[k] = pd[k] * (1 - uf[k]) + datum_offset
still_unfrozen = True
c = col_dat.shape[2]-1
while still_unfrozen and c >= 0:
if col_dat[1,k,c] > T0:
td[k] = col_dat[0,k,c] - datum
c = c - 1
else:
still_unfrozen = False
return times, td
def water_table(dirname, datum=None, v86=False, patm=101325.):
prefix = "" if v86 else "surface-"
# get the ponded depth
keys,times,dats = parse_ats.readATS(dirname, "visdump_surface_data.h5")
pd = parse_ats.getSurfaceData(keys, dats, prefix+"ponded_depth")
elev_surf = dats[prefix+"elevation.cell.0"][keys[0]][0]
dats.close()
if datum is None:
datum = elev_surf
datum_offset = elev_surf - datum
# get the columnar pressure
wt = np.zeros((len(keys),),'d')
col_dat = column_data.column_data(['pressure',], directory=dirname)
for k in range(col_dat.shape[1]):
if pd[k] > 0:
wt[k] = pd[k] + datum_offset
else:
wt_index = np.where(col_dat[1,k,:] >= patm)[0]
if len(wt_index) is 0:
wt_index = 0
else:
wt_index = wt_index[-1]
wt[k] = col_dat[0,k,wt_index] - datum
return times, wt
def load_area_rain(args):
k, t, d = parse_ats.readATS(args.directory, args.filename)
cv = d[args.area_key][k[0]][:]
area = cv.sum()
rain = np.array([(d[args.rainfall_rate_key][key][:] * cv).sum()
for key in k]) * 86400
return area, t * 365.25, rain # units m^2, days, m^3/s
def __init__(self,
dirname,
names=None,
gravity=9.80665,
typical_density=55000.):
"""Create a simulation class.
Usage:
with MassBalanceFromVis(dirname) as sim:
...
Arguments:
dirname | The directory where output is.
names | A dictionary mapping common names to variable names in the
| visualization files. Defaults are provided, and most
| simulations need not override them. (default=None)
gravity | Magnitude of gravity (default=9.80665 is the standard ATS value used)
typical_density| A typical molar density of liquid, used to print things in [m] instead of [mol]
Note that this should typically be used in 'with ... as' context, as this opens file
resources which should be closed on exit. Alternatively, close() can be called directly
by the user.
"""
self.dirname = dirname
if names is not None:
self._names.update(names)
self.gravity = gravity
self.p_atm = 101325.0
# load the vis files
self._keys, self.times, self._dat = parse_ats.readATS(dirname,
timeunits='d')
self._keys_s, self.times_s, self._dat_s = parse_ats.readATS(
dirname, 'visdump_surface_data.h5', timeunits='d')
if len(self._keys) != len(self._keys_s):
print "Warning: surface and subsurface visualization files are of different lengths! (%d, %d)" % (
len(self._keys), len(self._keys_s))
self.length = min(len(self._keys), len(self._keys_s))
# save cell volume instead of loading it repeatedly
self.volumes = self["cell volume", 0]
self.volume = self.volumes.sum()
self.areas = self["surface cell volume", 0]
self.surface_area = self.areas.sum()
self.typical_density = typical_density
def __init__(self, dirname, names=None, gravity=9.80665, typical_density=55000.):
"""Create a simulation class.
Usage:
with MassBalanceFromVis(dirname) as sim:
...
Arguments:
dirname | The directory where output is.
names | A dictionary mapping common names to variable names in the
| visualization files. Defaults are provided, and most
| simulations need not override them. (default=None)
gravity | Magnitude of gravity (default=9.80665 is the standard ATS value used)
typical_density| A typical molar density of liquid, used to print things in [m] instead of [mol]
Note that this should typically be used in 'with ... as' context, as this opens file
resources which should be closed on exit. Alternatively, close() can be called directly
by the user.
"""
self.dirname = dirname
if names is not None:
self._names.update(names)
self.gravity = gravity
self.p_atm = 101325.0
# load the vis files
self._keys, self.times, self._dat = parse_ats.readATS(dirname, timeunits='d')
self._keys_s, self.times_s, self._dat_s = parse_ats.readATS(dirname, 'visdump_surface_data.h5', timeunits='d')
if len(self._keys) != len(self._keys_s):
print "Warning: surface and subsurface visualization files are of different lengths! (%d, %d)"%(len(self._keys),len(self._keys_s))
self.length = min(len(self._keys), len(self._keys_s))
# save cell volume instead of loading it repeatedly
self.volumes = self["cell volume",0]
self.volume = self.volumes.sum()
self.areas = self["surface cell volume",0]
self.surface_area = self.areas.sum()
self.typical_density = typical_density
def model(pars,hostname,processor):
# Modify base ats xml input file with pars dictionary and run ats
m = atsxml.get_root('../test7-v_fwd.xml')
atsxml.replace_by_path(m,['base_porosity','rest domain','value'],pars['poro_m'])
atsxml.replace_by_path(m,['base_porosity','peat','value'],pars['poro_p'])
atsxml.replace_by_path(m,['permeability','rest domain','value'],10**pars['perm_m'])
atsxml.replace_by_path(m,['permeability','peat','value'],10**pars['perm_p'])
atsxml.run(m,nproc=4,stdout='stdout.out',stderr='stdout.err',cpuset=processor)
# Read results from ats visualization files
#keys,times,file handle
k,t,f = parse_ats.readATS()
# Collect point at middle of polygon 1 m deep
# x,z = 7.17946807, 4.65764252
# index for this location is 1733, see below how to find this
# Create output dictionary that matches MATK observations
out = {}
out['Sl'] = f[u'saturation_liquid.cell.0/'+k[-1]][1733]
out['T'] = f[u'temperature.cell.0/'+k[-1]][1733]
# Return simulated values of interest
return out
hackfactor = None
if dirname == "run-transient4":
hackfactor = 2.0
if args.colors is None:
if len(dirnames) > 1:
c = cm(float(i) / (len(dirnames) - 1))
else:
c = 'b'
else:
if type(args.colors[i]) is float:
c = cm(args.colors[i])
else:
c = args.colors[i]
ktd = parse_ats.readATS(dirname,
get_filename_base('surface', domain_suffix))
if version == 'dev-new':
ktds = parse_ats.readATS(dirname,
get_filename_base('snow',
domain_suffix))[2]
else:
ktds = None
plot_surface_balance((ktd[0], ktd[1], (ktd[2], ktds)),
axs,
c,
label=dirname,
hackfactor=hackfactor,
version=version,
marker=marker,
domain_suffix=domain_suffix)
if ktds is not None:
fig, axes = plt.subplots(4, 2, sharex=True)
#fname = 'ThawData_Yr10_All.csv'
#with open(fname, 'wb') as csvFile:
# writer = csv.writer(csvFile, delimiter=',')
for i in range(len(runPrefixList)):
y = np.nan * np.ones([nruns, len(trange)], 'd')
for j in range(nruns):
directory = runPrefixList[i] + '_' + runDate + '.' + str(j + 1)
isDir = os.path.isdir(os.getcwd() + '/' + directory)
if not isDir:
continue
keys, times, dat = parse_ats.readATS(directory,
"visdump_data.h5",
timeunits='yr')
col_dat = transect_data.transect_data(['saturation_ice'],
keys=np.s_[trange],
directory=directory)
times_subset = times[trange]
#col_dat structure:
#col 1 = variable
#col 2 = time
#col 3 = x position
#col 4 = z position
z_surf = col_dat[1, 0, :, -1] + (
col_dat[1, 0, :, -1] - col_dat[1, 0, :, -2]
) / 2. # average of the uppermost and second-to-uppermost rows, shifted up to the top row
z_bott = col_dat[1, 0, :, 0] - (
col_dat[1, 0, :, 1] - col_dat[1, 0, :, 0]
def water_table(dirname, datum=None, v86=False, patm=101325.):
prefix = "" if v86 else "surface-"
# get the ponded depth
keys,times,dats = parse_ats.readATS(dirname, "visdump_surface_data.h5")
pd = parse_ats.get2DSurfaceData(keys, dats, prefix+"ponded_depth")
center = len(dats[prefix+"elevation.cell.0"][keys[0]])
print ('Center location: ', center)
elev_surf = dats[prefix+"elevation.cell.0"][keys[0]][center-1]
dats.close()
print ('Datum (surface elevation)', elev_surf)
if datum is None:
datum = elev_surf
datum_offset = elev_surf - datum
# get the columnar pressure
wt = np.zeros((len(keys),),'d')
wt_ss = np.zeros((len(keys),),'d')
wt_surf = np.zeros((len(keys),),'d')
thaw_depth = np.zeros((len(keys),),'d')
wt_bottom = np.zeros((len(keys),),'d')
col_dat = transect_data.transect_data(['pressure', 'temperature'], directory=dirname)
vars = 2
nvar, cycles, xnum, znum = col_dat.shape
for k in range(col_dat.shape[1]):
if pd[k, xnum-1] > 0:
wt[k] = pd[k, xnum-1] + datum_offset
wt_surf[k] = pd[k, xnum-1] + datum_offset
else:
wt_index = np.where(col_dat[vars ,k,xnum-1, :] >= patm)[0] #var 1
temp_index = np.where(col_dat[vars+1 ,k,xnum-1, :] >= 273.25)[0] ##
temp_data = col_dat[vars + 1,k,xnum-1, :] #var 2
wt_index0 = wt_index
if len(wt_index) is 0:
wt_index = 0
wt_index0 = 0
else:
wt_index = wt_index[-1]
if (len(wt_index0) > 2):
wt_index0 = wt_index0[-2]
if (len(temp_index) is 0):
temp_index =0
else:
temp_index = temp_index[0]
if (temp_data[wt_index] > 273.25):
wt[k] = col_dat[1,k,xnum-1, wt_index] - datum
else:
wt_ss[k] = col_dat[1,k,xnum-1, temp_index] - datum
temp_index = np.where(col_dat[vars+1 ,k,xnum-1, :] >= 273.25)[0] ##
if len(temp_index) > 0:
thaw_depth[k] = col_dat[1,k,xnum-1, temp_index[0]] - datum
return times, wt, wt_ss, wt_bottom, thaw_depth
def water_table2D(dirname, datum=None, location='center', v86=False, patm=101325.):
prefix = "" if v86 else "surface-"
# get the ponded depth
keys,times,dats = parse_ats.readATS(dirname, "visdump_surface_data.h5")
pd = parse_ats.get2DSurfaceData(keys, dats, prefix+"ponded_depth")
if location == 'center':
center = len(dats[prefix+"elevation.cell.0"][keys[0]])
elif location == 'trough':
center = 1
print ('Location: ', location, center)
elev_cell = dats[prefix+"elevation.cell.0"][keys[0]][center-1]
dats.close()
print ('Datum (surface elevation)', elev_cell)
if datum is None:
datum = elev_cell
datum_offset = elev_cell - datum
# get the columnar pressure
water_table = np.zeros((len(keys),),'d')
thaw_depth = np.zeros((len(keys),),'d')
col_dat = transect_data.transect_data(['pressure', 'temperature'], directory=dirname)
vars = 2
nvar, cycles, xnum, znum = col_dat.shape
#print xnum
xnum = center
#print xnum
for k in range(col_dat.shape[1]):
if pd[k, xnum-1] > 0:
water_table[k] = pd[k, xnum-1] + datum_offset
#wt_surf[k] = pd[k, xnum-1] + datum_offset
#print 'surface:: ',k, pd[k, xnum-1]
else:
#print 'subsurface: ', k, pd[k, xnum-1]
wt_index = np.where(col_dat[vars ,k,xnum-1, :] >= patm)[0] #var 1
temp_index = np.where(col_dat[vars+1 ,k,xnum-1, :] >= 273.25)[0] ##
temp_data = col_dat[vars + 1,k,xnum-1, :] #var 2
if len(wt_index) is 0:
wt_index = 0
else:
wt_index = wt_index[-1]
if (len(temp_index) is 0):
temp_index =0
else:
temp_index = temp_index[0]
if (temp_data[wt_index] > 273.25):
water_table[k] = col_dat[1,k,xnum-1, wt_index] - datum
temp_index = np.where(col_dat[vars+1 ,k,xnum-1, :] >= 273.2)[0] ##
#print col_dat[vars+1 ,k,xnum-1, :], round(times[k]*365.25,2), k
if len(temp_index) > 0:
#print 'ALT: ', len(temp_index), temp_index[0], col_dat[vars+1 ,k,xnum-1, temp_index[0]]
thaw_depth[k] = col_dat[1,k,xnum-1, temp_index[0]] - datum
return times, water_table, thaw_depth, elev_cell
fig, axs = get_axs()
fnames = args.INPUT_DIRECTORIES
for i, fname in enumerate(fnames):
hackfactor = None
if fname == "run-transient4":
hackfactor = 2.0
if args.colors is None:
if len(fnames) > 1:
c = cm(float(i) / (len(fnames) - 1))
else:
c = 'b'
else:
if type(args.colors[i]) is float:
c = cm(args.colors[i])
else:
c = args.colors[i]
ktd = parse_ats.readATS(fname, "visdump_surface_data.h5")
plot_surface_balance(ktd, axs, c, label=fname, hackfactor=hackfactor)
ktd[2].close()
plt.tight_layout()
axs[0].legend(bbox_to_anchor=(0., 1., 3.6, .05),
loc=3,
ncol=len(fnames),
mode="expand",
borderaxespad=0.)
plt.show()
print("Directory %s got version: %s and domain_suffix: %r"%(dirname,version, domain_suffix))
hackfactor = None
if dirname == "run-transient4":
hackfactor = 2.0
if args.colors is None:
if len(dirnames) > 1:
c = cm(float(i)/(len(dirnames)-1))
else:
c = 'b'
else:
if type(args.colors[i]) is float:
c = cm(args.colors[i])
else:
c = args.colors[i]
ktd = parse_ats.readATS(dirname, get_filename_base('surface', domain_suffix))
if version == 'dev-new':
ktds = parse_ats.readATS(dirname, get_filename_base('snow', domain_suffix))[2]
else:
ktds = None
plot_surface_balance((ktd[0], ktd[1], (ktd[2],ktds)), axs, c, label=dirname, hackfactor=hackfactor, version=version, marker=marker, domain_suffix=domain_suffix)
if ktds is not None:
ktds.close()
ktd[2].close()
plt.tight_layout()
axs[0].legend(bbox_to_anchor=(0., 1., 3.6, .05), loc=3,
ncol=len(dirnames), mode="expand", borderaxespad=0.)
plt.show()
