def calculate_reservoir_rate(var, surf_mask, surf_type=None):
"""Inputs are two maps (var and surf_mask). Whereas there may be scripts that
calculate the masked means, this calculates the volume flow rate (ie, not the
flux density, but the total flux. This is currently written to only apply to
water variables. """
#If the units are not in mm/day, convert units
target_units_prect = 'mm/day'
if var.units == 'kg m-2 s-1' or var.units == 'kg/m2/s' or var.units == 'kg/m^2/s' or var.units == 'kg m^-2 s^-1' or var.units == 'kg/s/m^2':
var.units = 'mm/s'
a_prect = udunits(1., var.units)
s_prect, i_prect = a_prect.how(target_units_prect)
var = s_prect * var + i_prect
var.units = target_units_prect
#Mask the variable according to the surf_mask, using script in the same file
var_masked = surface_maskvariable(var, surf_mask, surf_type=None)
#Check to see if the variable has the time axis
var_axislist = var_masked.getAxisList()
if 'time' in var_axislist:
scalar = genutil.averager(
var_masked,
axis='yxt') #Calculate the spatial+temporal mean over the mask
area_frac = genutil.averager(area_frac, axis='t')
area_frac = 1. - genutil.averager(
surf_mask, axis='yx'
) #Calculate the fractional area over which the numbers are calculated ie, where it's NOT masked
else:
scalar = genutil.averager(
var_masked, axis='yx') #Calculate the spatial mean over the mask
area_frac = 1. - genutil.averager(
surf_mask, axis='yx'
) #Calculate the fractional area over which the numbers are calculated ie, where it's NOT masked
#Calculate the fraction of surface area that surf_mask covers
#Here we hard-wire the coefficient necessary to move from mm/day * m^2 to km3/year
coefficient = float(365. / 1000. /
1000000000.) #to convert mm/day to km^3/yr
r_earth = metrics.packages.amwg.derivations.atmconst.AtmConst.Rad_earth #obtain radius of Earth
A_earth = 4. * numpy.math.pi * r_earth**(
2) #Calulate the approximate surface area of Earth m^2
reservoir_total = A_earth * scalar * coefficient * area_frac #Calculate the volume rate
#define the units of the reservoir total
reservoir_total.units = 'km3/year'
#reservoir_total.units=reservoir_total_units #apply units to the output
return reservoir_total
def reduce_prs_tau(mv, vid=None):
"""Input is a transient variable. Dimensions isccp_prs, isccp_tau are reduced - but not
by averaging as in most reduction functions. The unweighted sum is applied instead."""
if vid is None:
vid = mv.id
axes = mv.getAxisList()
axis_names = [
a.id for a in axes if a.id == 'isccp_prs' or a.id == 'isccp_tau'
or a.id == 'cosp_prs' or a.id == 'cosp_tau' or a.id == 'modis_prs'
or a.id == 'modis_tau' or a.id == 'cosp_tau_modis'
or a.id == 'cosp_htmisr' or a.id == 'misr_cth' or a.id == 'misr_tau'
]
if len(axis_names) <= 0:
return mv
else:
axes_string = '(' + ')('.join(axis_names) + ')'
for axis in mv.getAxisList():
if axis.getBounds() is None:
axis._bounds_ = axis.genGenericBounds()
avmv = averager(mv,
axis=axes_string,
action='sum',
weights=['unweighted', 'unweighted'])
avmv.id = vid
if hasattr(mv, 'units'):
avmv.units = mv.units
return avmv
def test_MeanValue(self):
filename = 'tas_Amon_IPSL-CM5A-LR_1pctCO2_r1i1p1_185001-198912.nc'
if not os.path.exists(filename):
r = requests.get(
"https://cdat.llnl.gov/cdat/sample_data/notebooks/{}".format(filename), stream=True)
with open(filename, "wb") as f:
for chunk in r.iter_content(chunk_size=1024):
if chunk: # filter local_filename keep-alive new chunks
f.write(chunk)
# Open data file and extract variable
f = cdms2.open(filename)
data = f("tas")
# Mask the data
datamskd = MV2.masked_greater(data, data.max()-7)
# extract the departures of the masked data.
datamskd_departures = cdutil.times.ANNUALCYCLE.departures(datamskd)
# create time series of the masked data departures.
datamskd_departures_ts = genutil.averager(datamskd_departures, axis='xy', weights=[
'weighted', 'weighted'], combinewts=1)
datamskd_departures_ts_corrected = cdutil.times.ANNUALCYCLE.departures(
datamskd_departures_ts)
# Graphics and plot steps
template = vcs.createtemplate()
self.x = vcs.init(bg=True, geometry=(1200, 900))
# Plot image and check against reference
self.x.clear()
self.x.plot(datamskd_departures_ts_corrected, template)
self.checkImage("test_vcs_plot_mean_value.png")
def calculate_reservoir_rate(var, surf_mask, surf_type=None):
"""Inputs are two maps (var and surf_mask). Whereas there may be scripts that
calculate the masked means, this calculates the volume flow rate (ie, not the
flux density, but the total flux. This is currently written to only apply to
water variables. """
#If the units are not in mm/day, convert units
target_units_prect='mm/day'
if var.units=='kg m-2 s-1' or var.units=='kg/m2/s' or var.units=='kg/m^2/s' or var.units=='kg m^-2 s^-1' or var.units=='kg/s/m^2':
var.units='mm/s'
a_prect=udunits(1.,var.units)
s_prect,i_prect=a_prect.how(target_units_prect)
var=s_prect*var + i_prect
var.units=target_units_prect
#Mask the variable according to the surf_mask, using script in the same file
var_masked=surface_maskvariable(var, surf_mask, surf_type=None)
#Check to see if the variable has the time axis
var_axislist=var_masked.getAxisList()
if 'time' in var_axislist:
scalar=genutil.averager(var_masked,axis='yxt') #Calculate the spatial+temporal mean over the mask
area_frac=genutil.averager(area_frac,axis='t')
area_frac=1.-genutil.averager(surf_mask,axis='yx') #Calculate the fractional area over which the numbers are calculated ie, where it's NOT masked
else:
scalar=genutil.averager(var_masked,axis='yx') #Calculate the spatial mean over the mask
area_frac=1.-genutil.averager(surf_mask,axis='yx') #Calculate the fractional area over which the numbers are calculated ie, where it's NOT masked
#Calculate the fraction of surface area that surf_mask covers
#Here we hard-wire the coefficient necessary to move from mm/day * m^2 to km3/year
coefficient=float(365./1000./1000000000.) #to convert mm/day to km^3/yr
r_earth=metrics.packages.amwg.derivations.atmconst.AtmConst.Rad_earth #obtain radius of Earth
A_earth=4. * numpy.math.pi * r_earth ** (2) #Calulate the approximate surface area of Earth m^2
reservoir_total=A_earth * scalar * coefficient * area_frac #Calculate the volume rate
#define the units of the reservoir total
reservoir_total.units='km3/year'
#reservoir_total.units=reservoir_total_units #apply units to the output
return reservoir_total
def reduce_prs_tau( mv, vid=None ):
"""Input is a transient variable. Dimensions isccp_prs, isccp_tau are reduced - but not
by averaging as in most reduction functions. The unweighted sum is applied instead."""
if vid is None:
vid = mv.id
axes = mv.getAxisList()
axis_names = [ a.id for a in axes if a.id=='isccp_prs' or a.id=='isccp_tau' or
a.id=='cosp_prs' or a.id=='cosp_tau' or a.id=='modis_prs' or a.id=='modis_tau'
or a.id=='cosp_tau_modis' or a.id=='cosp_htmisr'
or a.id=='misr_cth' or a.id=='misr_tau']
if len(axis_names)<=0:
return mv
else:
axes_string = '('+')('.join(axis_names)+')'
for axis in mv.getAxisList():
if axis.getBounds() is None:
axis._bounds_ = axis.genGenericBounds()
avmv = averager( mv, axis=axes_string, action='sum', weights=['unweighted','unweighted'] )
avmv.id = vid
if hasattr(mv,'units'):
avmv.units = mv.units
return avmv