def lei_heat_balance(ztri=[0, .4, .7], quiet=True, blist=None):
import my_fluxes
import buoys
import numpy as np
buoy_list = buoys.buoylist()
writedir = '/data/cr1/hadax/PhD/Buoys/'
filenames = ['my_conductive_flux.dat','my_heat_uptake.dat',\
'my_basal_change.dat',\
'my_ocean_heat_flux.dat']
labels = [
'Conductive flux', 'Heat uptake', 'Basal change', 'Ocean heat flux'
]
files = [writedir + filename for filename in filenames]
filehandles = [open(ffile, 'w') for ffile in files]
if not blist is None:
buoy_list = [bb for bb in buoy_list if bb in blist]
for (label, fileh) in zip(labels, filehandles):
fileh.write(label + '\n')
fileh.write('{:6s},{:4s},{:6s},{:12s},{:12s},{:12s},{:4s}\n'.\
format('Buoy','Mon','Year','Value','Prec','Sal','RC'))
fileh.write('-----------------------------\n')
for buoy_name in buoy_list:
if not quiet:
print 'Calculating Lei heat balance for buoy ' + buoy_name
cf = my_fluxes.f_conductive_flux(buoy_name, ztri[1:])
hu = my_fluxes.f_heat_uptake(buoy_name, ztri[:2])
bc = my_fluxes.f_basal_change(buoy_name)
ohf = hu + bc - cf
ohf.label = 'Ocean heat flux'
list_all_my = list(set.union(*[set(item.my_list()) for item in\
(cf,hu,bc,ohf)]))
if len(list_all_my) > 0:
list_all_my = my_fluxes.my_sort(np.array(list_all_my))
list_all_my = [tuple(list_all_my[ii,:]) for ii in \
range(list_all_my.shape[0])]
for my_point in list_all_my:
for (iss, series) in enumerate((cf, hu, bc, ohf)):
try:
index = series.my_list().index(my_point)
except ValueError:
index = None
if not index is None:
ce = series.central_estimates[index]
pe = series.precision_error[index]
se = series.salinity_error[index]
out_str = '{:6s},{:4d},{:6d},{:12.3f},{:12.3f},{:12.3f}\n'.\
format(buoy_name,my_point[0],\
my_point[1],ce,pe,se)
filehandles[iss].write(out_str)
for fileh in filehandles:
fileh.close()
def sfc_temp_series(quiet=True, blist=None, force_new=False):
import buoys
required_distances = [-.5, -.3, -.2, -.1, 0., .1]
buoy_list = buoys.buoylist()
if not blist is None:
buoy_list = [bb for bb in buoy_list if bb in blist]
for buoy_name in buoy_list:
if not quiet:
print ' '
print 'Calculating Lei temperature series for buoy ' + buoy_name
print '----------------------------'
buoy = buoys.buoy(buoy_name)
buoy.update_series()
for distance in required_distances:
series_name = 'sftemp_{:4.3f}'.format(distance)
if (not buoy.is_series(series_name)) or force_new:
buoy.new_sfc_temp_series(distance)
if len(buoy.data[series_name].data_list) > 0:
result = 1
else:
result = 0
buoy.save_series()
else:
result = 2
if not quiet:
print '{:5.2f}{:2d}'.format(distance, result)
def calculate_ice_snow_thickness(quiet=True, blist=None, force_new=False):
import buoys
import numpy as np
import data_series as ds
buoy_list = buoys.buoylist()
ice_series_label = 'Ice_thickness'
snow_series_label = 'Snow_thickness'
if not blist is None:
buoy_list = [bb for bb in buoy_list if bb in blist]
for buoy_name in buoy_list:
buoy = buoys.buoy(buoy_name)
buoy.update_series()
if (not buoy.is_series(ice_series_label)) or force_new:
if 'interface_rt' in buoy.data.keys() and \
'bottom_rt' in buoy.data.keys():
ice_thickness = buoy.data['interface_rt'] - buoy.data[
'bottom_rt']
ice_thickness.label = ice_series_label
buoy.data[ice_thickness.label] = ice_thickness
buoy.save_series()
ice_result = 1
else:
buoy.data[ice_series_label] = ds.data_series(buoy_name,' ',\
ice_series_label)
buoy.save_series()
ice_result = 0
else:
ice_result = 2
if (not buoy.is_series(snow_series_label)) or force_new:
if 'interface_rt' in buoy.data.keys() and \
'surface_rt' in buoy.data.keys():
snow_thickness = buoy.data['surface_rt'] - \
buoy.data['interface_rt']
snow_thickness.label = snow_series_label
buoy.data[snow_thickness.label] = snow_thickness
buoy.save_series()
snow_result = 1
else:
buoy.data[snow_series_label] = ds.data_series(buoy_name,' ',\
snow_series_label)
buoy.save_series()
snow_result = 0
else:
snow_result = 2
if not quiet:
print '{:6s}{:4d}{:4d}'.format(buoy_name, ice_result, snow_result)
def buoynumber(input_value):
import buoys
bl = buoys.buoylist()
try:
return bl[input_value]
except (TypeError, IndexError) as e:
try:
return bl.index(input_value.strip())
except ValueError:
print('Invalid buoy number/identifier')
return None
def zgrad_top_snow_adjusted(blist=None,force_new=False,quiet=True,\
int_length = 0.5, mean_salinity = 1):
import buoys
import numpy as np
import data_series as ds
import tprof
buoy_list = buoys.buoylist()
if not blist is None:
buoy_list = [bb for bb in buoy_list if bb in blist]
for buoy_name in buoy_list:
if not quiet:
print 'Calculating top gradient for buoy ' + buoy_name
buoy = buoys.buoy(buoy_name)
buoy.update_series()
buoy.process_temp()
series_names = [
'sftemp_' + '{:6.3f}'.format(0. - int_length), 'sftemp_0.000'
]
if set(series_names) & set(buoy.data.keys()) == set(series_names):
boundary_vars = series_names
else:
boundary_vars = None
tdates = buoy.temp.dates()
varname = 'zgrad_top_snow_adjusted_' + '{:6.3f}'.format(0. -
int_length)
zgrad_adjust_series = ds.data_series(buoy.name, '', varname)
for tdate in tdates:
snowpos = buoy.snowpos_rt(tdate)
if snowpos is not None:
zint = [snowpos[1] - int_length, snowpos[1]]
complete_zprof = tprof.complete_zprof(buoy,tdate,zint,\
boundary_vars = boundary_vars, adjust_for_snow=True,\
salinity = mean_salinity)
if complete_zprof is not None:
zgrad_adjust = np.polyfit(complete_zprof[0],
complete_zprof[1], 1)[0]
zgrad_adjust_series.data_list[tdate] = zgrad_adjust
buoy.data[varname] = zgrad_adjust_series
buoy.data[varname].type = 'regular_temp'
buoy.save_series()
def buoynumber(input_value):
import sys
sys.path.insert(0, '../reading_interpolating_qc/')
import buoys
bl = buoys.buoylist()
try:
return bl[input_value]
except (TypeError, IndexError) as e:
try:
return bl.index(input_value.strip())
except ValueError:
print('Invalid buoy number/identifier')
return None
def write_all_my_series(filename,
funcname,
quiet=True,
blist=None,
label='',
**kwargs):
import buoys
ddir = '/data/cr1/hadax/PhD/Buoys/'
ffile = ddir + filename
fileh = open(ffile, 'w')
fileh.write(label + '\n')
fileh.write('{:6s},{:4s},{:6s},{:12s},{:12s},{:12s},{:4s}\n'.\
format('Buoy','Mon','Year','Value','Prec','Sal','RC'))
fileh.write('-----------------------------\n')
buoy_list = buoys.buoylist()
if not blist is None:
buoy_list = [bb for bb in buoy_list if bb in blist]
for buoy_name in buoy_list:
buoy = buoys.buoy(buoy_name)
buoy.update_series()
if not quiet:
print 'Calculating series '+\
'for buoy '+buoy_name
my_series = funcname(buoy_name, **kwargs)
my_points = my_series.my_list()
for (ii, my_point) in enumerate(my_points):
ce = my_series.central_estimates[ii]
pe = my_series.precision_error[ii]
se = my_series.salinity_error[ii]
out_str='{:6s},{:4d},{:6d},{:12.3f},{:12.3f},{:12.3f}\n'.\
format(buoy_name,my_point[0],\
my_point[1],ce,pe,se)
fileh.write(out_str)
fileh.close()
def write_spatial_codes(quiet=True, blist=None):
import buoys
import spatial
import my_fluxes
import numpy as np
outfile = '/data/cr1/hadax/PhD/Buoys/spatial_codes.dat'
outfileh = open(outfile, 'w')
outfileh.write(
'Codes to denote regions occupied by buoys during particular months\n')
outfileh.write('1 = North Pole\n')
outfileh.write('2 = Beaufort Sea\n')
outfileh.write('0 = neither\n')
outfileh.write('-1 = no lat or lon data available\n')
outfileh.write('\n')
outfileh.write(
'------------------------------------------------------------------\n')
outfileh.write('{:6s},{:4s},{:6s},{:6s}\n'.format('Buoy', 'Mon', 'Year',
'Code'))
buoy_list = buoys.buoylist()
if not blist is None:
buoy_list = [bb for bb in buoy_list if bb in blist]
for buoy_name in buoy_list:
if not quiet:
print 'Calculating spatial codes for buoy ' + buoy_name
buoy = buoys.buoy(buoy_name)
buoy.update_series()
if np.sum(np.array([name not in buoy.data.keys() for \
name in ['longitude','latitude']])) == 0:
my_points = my_fluxes.valid_month_points([buoy.data[name] for \
name in ['longitude','latitude']])
for my_point in my_points:
code = spatial.region_my(buoy, my_point)
outfileh.write('{:6s},{:4d},{:6d},{:6d}\n'.format(\
buoy_name, my_point[0], my_point[1], code))
outfileh.close()
def full_tgrads(quiet=True, blist=None, tperiod=1., force_new=False):
import tprof
import buoys
buoy_list = buoys.buoylist()
if not blist is None:
buoy_list = [bb for bb in buoy_list if bb in blist]
for buoy_name in buoy_list:
if not quiet:
print 'Calculating full depth tgrad in ice for buoy ' + buoy_name
buoy = buoys.buoy(buoy_name)
buoy.update_series()
buoy.process_temp()
varname = 'weighted_total_ice_tgrad_tperiod_{:3.1f}'.format(tperiod)
if force_new or not buoy.is_series(varname):
total_tgrad_series = tprof.weighted_total_ice_tgrad(buoy, tperiod)
buoy.data[total_tgrad_series.varname] = total_tgrad_series
buoy.data[total_tgrad_series.varname].type = 'regular_temp'
buoy.save_series()
def effective_thickness(quiet=True, blist=None, snow_conductivity=0.33):
import buoys
ice_conductivity = 2.03
buoy_list = buoys.buoylist()
if not blist is None:
buoy_list = [bb for bb in buoy_list if bb in blist]
for buoy_name in buoy_list:
if not quiet:
print 'Calculating effective thickness for buoy ' + buoy_name
buoy = buoys.buoy(buoy_name)
buoy.update_series()
series_label = 'effective_thickness.' + snow_conductivity.__str__()
buoy.data[series_label] = \
buoy.data['ice_thickness'] / ice_conductivity + \
buoy.data['snow_thickness'] / snow_conductivity
buoy.data[series_label].label = series_label
buoy.save_series()
'''Main driver program for processing IMB data'''
import buoys
import numpy as np
temp_series_base_positions = np.arange(0, 1, .1)
temp_series_sfc_positions = np.arange(-.5, .5, .1)
base_layers_calc = [[0,.1],[0,.2],[0,.3],[0,.4],[0,.5],[0,.6],\
[.1,.2],[.2,.3],[.3,.4],[.4,.5],[.5,.6],[.6,.7],\
[.1,.3],[.2,.4],[.3,.5],[.4,.6],[.5,.7],[.6,.8],\
[.1,.4],[.2,.5],[.3,.6],[.4,.7],[.5,.8],[.6,.9],\
[.1,.5],[.2,.6],[.3,.7],[.4,.8],[.5,.9],[.6,1.]]
buoy_list = buoys.buoylist()
for buoy_name in buoy_list:
buoy_str = buoys.buoy(buoy_name)
buoy_str.process_temp()
buoy_str.calculate_elevation_series()
buoy_str.position_rt()
buoy_str.temp_series_base(temp_series_base_positions)
for base_layer_calc in base_layers_calc:
buoy_str.temp_statistics(layer_calc=base_layer_calc, mode='base')
buoy_str.temp_series_sfc(temp_series_sfc_positions)
#for sfc_layer_calc in sfc_layers_calc:
# buoy_str.temp_statistics(sfc_layer_calc,mode='interface')
buoy_str.effective_thickness(ice_cond=2.03, snow_cond=0.33)
buoy_str.adjusted_zgrad_snow(int_length=0.5,ice_cond=2.03,snow_cond=0.33,\
def lei_statistics(zint=None,quiet=True,blist=None,force_new=False,\
relative_position = 'bottom'):
import buoys
import tprof
import data_series as ds
import numpy as np
if relative_position == 'bottom':
icepos_index = 0
prefix = ''
boundary_vars = ['temp_{:4.3f}'.format(zpos) for zpos in zint]
elif relative_position == 'interface':
icepos_index = 1
prefix = 'int_'
boundary_vars = None
statistics = ['zmean', 'zgrad', 'z_recip_mean', 'z_recip_sq_mean']
if zint is None:
print 'Please specify z-interval'
layer_label = '{:4.3f}_{:4.3f}'.format(*zint)
varnames = [prefix + layer_label + '_' + stat for stat in statistics]
buoy_list = buoys.buoylist()
if not blist is None:
buoy_list = [bb for bb in buoy_list if bb in blist]
for buoy_name in buoy_list:
if not quiet:
print ' '
print 'Calculating Lei statistics of '+\
str(zint[0])+'-'+str(zint[1])+' heat storage series '+\
'for buoy '+buoy_name
print '----------------------------'
buoy = buoys.buoy(buoy_name)
not_there_log = np.array([(not buoy.is_series(varname)) \
for varname in varnames])
if np.sum(not_there_log) > 0 or force_new:
buoy.update_series()
buoy.process_temp()
for varname in varnames:
buoy.data[varname] = ds.data_series(buoy.name, '', varname)
buoy.data[varname].type = 'regular_temp'
tdates = buoy.temp.dates()
for tdate in tdates:
if tdate.day == 1 and tdate.hour == 1:
print tdate
icepos = buoy.icepos_rt(tdate)
if not icepos is None:
zint_transform = [zi + icepos[icepos_index] for zi in zint]
zprof = tprof.complete_zprof(buoy,tdate,zint_transform,\
boundary_vars=boundary_vars)
if not zprof is None:
zweights = tprof.zpt_weights(zprof[0])
zgrad = np.polyfit(zprof[0], zprof[1], 1)[0]
zmean = np.sum(zweights * zprof[1])
z_recip_mean = np.sum(zweights * 1. / zprof[1])
z_recip_sq_mean = np.sum(zweights * 1. /
(zprof[1])**2.)
data_series = [zmean,zgrad,z_recip_mean,\
z_recip_sq_mean]
for (ii, varname) in enumerate(varnames):
buoy.data[varname].data_list[tdate] = \
data_series[ii]
result = 1
buoy.save_series()
else:
result = 2
if not quiet:
print result
def calculate_elevation_series(quiet=True, blist=None):
import numpy as np
import buoys
import data_series as ds
buoy_list = buoys.buoylist()
if not blist is None:
buoy_list = [bb for bb in buoy_list if bb in blist]
basic_variable_names = ['interface', 'snow depth', 'surface', 'bottom']
if not quiet:
print('{:3s} ' * 4).format('sfc', 'snd', 'int', 'bot')
for buoy_name in buoy_list:
buoy = buoys.buoy(buoy_name)
buoy.extract_temp()
results = np.zeros(4, dtype='int32')
for (ii, varname) in enumerate(basic_variable_names):
buoy.extract_data(varname)
if len(buoy.data[varname].data_list) != 0:
if varname == 'surface' and len(
buoy.data['interface'].data_list) > 0:
use_series = buoy.data['surface'].snap(
buoy.data['interface_r'])
else:
use_series = buoy.data[varname]
buoy.data[varname + '_r'] = use_series.regularise()
buoy.data[varname + '_rt'] = use_series.regularise_temp(
buoy.temp.dates())
results.itemset(ii, 1)
else:
buoy.data[varname + '_r'] = ds.data_series(
buoy_name, '', varname + '_r')
buoy.data[varname + '_rt'] = ds.data_series(
buoy_name, '', varname + '_rt')
if len(buoy.data['interface'].data_list) == 0 and len(
buoy.data['surface'].data_list) > 0:
buoy.interface_from_surface()
buoy.data['interface_rt'] = buoy.data[
'interface_r'].regularise_temp(buoy.temp.dates())
results.itemset(0, 2)
if len(buoy.data['surface'].data_list)==0 and len(buoy.data['interface'].data_list) > 0 \
and len(buoy.data['snow depth'].data_list) > 0:
buoy.surface_from_interface_and_snow()
buoy.data['surface_rt'] = buoy.data['surface_r'].regularise_temp(
buoy.temp.dates())
results.itemset(2, 2)
buoy.data['ice_thickness'] = buoy.data['interface_rt'] - \
buoy.data['bottom_rt']
buoy.data['ice_thickness'].label = 'ice_thickness'
buoy.data['snow_thickness'] = buoy.data['surface_rt'] - \
buoy.data['interface_rt']
buoy.data['snow_thickness'].label = 'snow_thickness'
buoy.save_series()
if not quiet:
print('{:6s}' + '{:3d} ' * 4).format(buoy_name, *results)
