Python distribute_thickness_per_altitude 예제들

예제 #1

파일: test_benchmarks.py 프로젝트: bearecinos/oggm

 def to_optimize(x):
     tasks.mass_conservation_inversion(gdir,
                                       glen_a=glen_a * x[0],
                                       fs=fs * x[1])
     tasks.distribute_thickness_per_altitude(gdir)
     with xr.open_dataset(gdir.get_filepath('gridded_data')) as ds:
         thick = ds.distributed_thickness.isel(x=('z', df['i']),
                                               y=('z', df['j']))
         out = (np.abs(thick - df.thick)).mean()
     return out

예제 #2

 def to_optimize(x):
     tasks.mass_conservation_inversion(gdir,
                                       glen_a=glen_a * x[0],
                                       fs=fs * x[1])
     tasks.distribute_thickness_per_altitude(gdir)
     with xr.open_dataset(gdir.get_filepath('gridded_data')) as ds:
         thick = ds.distributed_thickness.isel(x=('z', df['i']),
                                               y=('z', df['j']))
         out = (np.abs(thick - df.thick)).mean()
     return out

예제 #3

파일: prepare_climate.py 프로젝트: ShafeequeIGSNRR/oggm

pdf[r'$\mu (t)$'] = mu_yr_clim
pdf['bias'] = diff
res = t_star_from_refmb(gdir, mbdf=mbdf.ANNUAL_BALANCE)

# For the mass flux
cl = gdir.read_pickle('inversion_input')[-1]
mbmod = ConstantMassBalance(gdir)
mbx = (mbmod.get_annual_mb(cl['hgt']) * cfg.SEC_IN_YEAR *
       cfg.PARAMS['ice_density'])
fdf = pd.DataFrame(index=np.arange(len(mbx)) * cl['dx'])
fdf['Flux'] = cl['flux']
fdf['Mass balance'] = mbx

# For the distributed thickness
tasks.mass_conservation_inversion(gdir, glen_a=2.4e-24 * 3, fs=0)
tasks.distribute_thickness_per_altitude(gdir)


# plot functions
def example_plot_temp_ts():
    d = xr.open_dataset(gdir.get_filepath('climate_historical'))
    temp = d.temp.resample(time='12MS').mean('time').to_series()
    temp.index = temp.index.year
    try:
        temp = temp.rename_axis(None)
    except AttributeError:
        del temp.index.name
    temp.plot(figsize=(8, 4), label='Annual temp')
    tsm = temp.rolling(31, center=True, min_periods=15).mean()
    tsm.plot(label='31-yr avg')
    plt.legend(loc='best')

예제 #4

파일: prepare_climate.py 프로젝트: bearecinos/oggm

pdf[r'$\mu (t)$'] = mu_yr_clim
pdf['bias'] = diff
res = t_star_from_refmb(gdir, mbdf=mbdf.ANNUAL_BALANCE)

# For the mass flux
cl = gdir.read_pickle('inversion_input')[-1]
mbmod = ConstantMassBalance(gdir)
mbx = (mbmod.get_annual_mb(cl['hgt']) * cfg.SEC_IN_YEAR *
       cfg.PARAMS['ice_density'])
fdf = pd.DataFrame(index=np.arange(len(mbx))*cl['dx'])
fdf['Flux'] = cl['flux']
fdf['Mass balance'] = mbx

# For the distributed thickness
tasks.mass_conservation_inversion(gdir, glen_a=2.4e-24 * 3, fs=0)
tasks.distribute_thickness_per_altitude(gdir)


# plot functions
def example_plot_temp_ts():
    d = xr.open_dataset(gdir.get_filepath('climate_monthly'))
    temp = d.temp.resample(time='12MS').mean('time').to_series()
    del temp.index.name
    temp.plot(figsize=(8, 4), label='Annual temp')
    tsm = temp.rolling(31, center=True, min_periods=15).mean()
    tsm.plot(label='31-yr avg')
    plt.legend(loc='best')
    plt.title('HISTALP annual temperature, Hintereisferner')
    plt.ylabel(r'degC')
    plt.tight_layout()
    plt.show()