Commit 4d3269bc authored by Clément Haëck's avatar Clément Haëck
Browse files

Rename jet_zones to SN_separation

parent 6f259004
......@@ -26,7 +26,7 @@ mod = importlib.import_module('lib.data.' + args['data'])
ds = mod.get_data(args)
if args['data'] == 'jet_zones':
if args['data'] == 'SN_separation':
ds = mod.smooth(ds, 8).to_dataset()
grp = ds.groupby("time.dayofyear")
......
......@@ -5,7 +5,7 @@ import xarray as xr
import lib
import lib.data.clouds
import lib.data.jet_zones
import lib.data.SN_separation
import lib.data.ostia
import lib.data.globcolour
import lib.zones
......@@ -19,9 +19,9 @@ def main():
zone = lib.zones.get_data(args, grid=grid)['total']
land = lib.zones.get_land(args, grid=grid)['land_large']
thr = lib.data.jet_zones.get_data(args)
thr = lib.data.SN_separation.get_data(args)
thr = lib.fix_time_daily(thr)
threshold = lib.data.jet_zones.smooth(thr)
threshold = lib.data.SN_separation.smooth(thr)
st = lib.data.ostia.get_data(args)
gc = lib.data.globcolour.get_data(args)
......
......@@ -14,7 +14,7 @@ from scipy.optimize import curve_fit
import xarray as xr
import lib
import lib.data.jet_zones
import lib.data.SN_separation
import lib.data.ostia
import lib.zones
......@@ -36,7 +36,7 @@ def main():
output_dtypes=[float])
sep.name = 'threshold'
ofile = lib.data.jet_zones.get_filename(args['fixes'])
ofile = lib.data.SN_separation.get_filename(args['fixes'])
lib.check_output_dir(ofile, file=True)
sep.to_dataset().to_netcdf(ofile)
......
......@@ -6,7 +6,7 @@ import xarray as xr
import lib
import lib.data.globcolour
import lib.data.hi
import lib.data.jet_zones
import lib.data.SN_separation
import lib.data.ostia
import lib.data.tseries
import lib.zones
......@@ -32,8 +32,8 @@ def mean_gyre(da, args, variable):
def mean_GS(da, da_mask, args, variable):
threshold = lib.data.jet_zones.get_data(args)
threshold = lib.data.jet_zones.smooth(threshold)
threshold = lib.data.SN_separation.get_data(args)
threshold = lib.data.SN_separation.smooth(threshold)
threshold = lib.fix_time_daily(threshold)
threshold, _ = xr.align(threshold, da_mask.time, join='right')
......
......@@ -10,7 +10,7 @@ import pandas as pd
import lib
import lib.data.front_probability
import lib.data.hi
import lib.data.jet_zones
import lib.data.SN_separation
import lib.data.ostia
from lib.xarray_utils import save_chunks_by_date
......@@ -31,7 +31,7 @@ def main():
ds = lib.data.hi.get_data(args)
sst = lib.data.ostia.get_data(args)
thr = lib.data.jet_zones.get_data(args)['threshold']
thr = lib.data.SN_separation.get_data(args)['threshold']
hi = lib.data.hi.apply_coef(ds, lib.data.hi.get_coef(args))
hi = hi.where(sst.analysed_sst < thr)
......
......@@ -9,7 +9,7 @@ from scipy.optimize import curve_fit
import xarray as xr
import lib
import lib.data.jet_zones
import lib.data.SN_separation
import lib.data.ostia
import lib.zones
......@@ -21,7 +21,7 @@ def main():
sst = lib.data.ostia.get_data(args)
ofile = lib.data.jet_zones.get_filename(args['fixes'])
ofile = lib.data.SN_separation.get_filename(args['fixes'])
sst['zone'] = lib.zones.get_data(args, grid=lib.data.ostia.grid)['total']
sst = sst.sel(lat=slice(32, None))
......
......@@ -6,7 +6,7 @@ import numpy as np
import xarray as xr
import lib
import lib.data.jet_zones
import lib.data.SN_separation
import lib.data.ostia
import lib.zones
......@@ -17,7 +17,7 @@ def main():
args['fixes']['Y'] = args['year']
sst = lib.data.ostia.get_data(args)
ofile = lib.data.jet_zones.get_filename(args['fixes'])
ofile = lib.data.SN_separation.get_filename(args['fixes'])
zone_obj = lib.zones.zones['GS']
sst['zone'] = lib.zones.get_data(args, grid=lib.data.ostia.grid)['GS']
......
......@@ -11,7 +11,7 @@ import lib
import lib.data.hi
import lib.data.hists
import lib.data.images
import lib.data.jet_zones
import lib.data.SN_separation
import lib.data.modis
import lib.zones
......@@ -44,9 +44,9 @@ def main():
land = lib.zones.get_land(args, grid=lib.data.modis.grid)['land_large'].persist()
# Get threshold
thr = lib.data.jet_zones.get_data(args)
thr = lib.data.SN_separation.get_data(args)
thr = lib.fix_time_daily(thr)
threshold = lib.data.jet_zones.smooth(thr, 8)
threshold = lib.data.SN_separation.smooth(thr, 8)
coef = lib.data.hi.get_coef(args)
......
......@@ -9,7 +9,7 @@ import lib.data.hists
import lib.data.hi
import lib.data.globcolour
import lib.data.ostia
import lib.data.jet_zones
import lib.data.SN_separation
import lib.zones
VAR_RANGE = {
......@@ -37,8 +37,8 @@ def main():
print('Load SST', flush=True)
st = lib.data.ostia.get_data(args)
print('Load Threshold', flush=True)
thr = lib.data.jet_zones.get_data(args)
threshold = lib.data.jet_zones.smooth(thr, 8)
thr = lib.data.SN_separation.get_data(args)
threshold = lib.data.SN_separation.smooth(thr, 8)
print('Load Zones', flush=True)
# Retrieve zones, one for each grid
zone_hi = get_zone(lib.data.ostia.grid, args)
......
......@@ -14,7 +14,7 @@ import lib.data.hists
import lib.data.hi
import lib.data.globcolour
import lib.data.ostia
import lib.data.jet_zones
import lib.data.SN_separation
import lib.data.pft
import lib.zones
......@@ -52,9 +52,9 @@ def main():
pft = lib.data.pft.get_data(args, days=8, concentration=True)
pft = lib.fix_time_daily(pft)
print('Load Threshold', flush=True)
thr = lib.data.jet_zones.get_data(args)
thr = lib.data.SN_separation.get_data(args)
thr = lib.fix_time_daily(thr)
threshold = lib.data.jet_zones.smooth(thr, 8)
threshold = lib.data.SN_separation.smooth(thr, 8)
print('Load Zones', flush=True)
zone_gc = get_zone(lib.data.globcolour.grid, args)
......
......@@ -35,7 +35,7 @@ def get_data(module):
return cli, cli_std
thr, thr_std = get_data('jet_zones')
thr, thr_std = get_data('SN_separation')
clouds, clouds_std = get_data('clouds')
ts, ts_std = get_data('tseries')
......
......@@ -13,7 +13,7 @@ import xarray as xr
import lib
import lib.data.ostia
import lib.data.globcolour
import lib.data.jet_zones
import lib.data.SN_separation
import Plots.util as plot_util
from Plots.Images.examples import examples
from Compute.gs_zones_gauss import _get_separation
......@@ -35,7 +35,7 @@ fixes = dict(
st = lib.data.ostia.get_data(args, fixes=fixes)
gc = lib.data.globcolour.get_data(args, fixes=fixes)
thr = lib.data.jet_zones.get_data(args, fixes=fixes)
thr = lib.data.SN_separation.get_data(args, fixes=fixes)
sst = st.analysed_sst.isel(time=0)
chl = gc.CHL.isel(time=0)
......
......@@ -12,7 +12,7 @@ import lib
import lib.data.globcolour
import lib.data.ostia
import lib.data.hi
import lib.data.jet_zones
import lib.data.SN_separation
import Plots.util as plot_util
......@@ -37,8 +37,8 @@ hi['HI'] = lib.data.hi.apply_coef(hi, lib.data.hi.get_coef(args))
chl = gc.CHL[0]
sst = st.analysed_sst[0]
thr = lib.data.jet_zones.get_data(fixes=fixes)
thr = lib.data.jet_zones.smooth(thr)
thr = lib.data.SN_separation.get_data(fixes=fixes)
thr = lib.data.SN_separation.smooth(thr)
thr = lib.fix_time_daily(thr)
threshold = thr.sel(time=datetime(fixes['Y'], fixes['m'], fixes['d'])).values
......
......@@ -8,7 +8,7 @@ import xarray as xr
import lib
import lib.data.globcolour
import lib.data.jet_zones
import lib.data.SN_separation
import lib.data.ostia
plt.switch_backend('agg')
......@@ -18,7 +18,7 @@ args['fixes']['Y'] = args['year']
gc = lib.data.globcolour.get_data(args)
st = lib.data.ostia.get_data(args)
thr = lib.data.jet_zones.get_data(args)
thr = lib.data.SN_separation.get_data(args)
gc = lib.fix_time_daily(gc)
st = lib.fix_time_daily(st)
......@@ -26,7 +26,7 @@ thr = lib.fix_time_daily(thr)
gc, st, thr = xr.align(gc, st, thr, join="inner", exclude=['lat', 'lon'])
thr['threshold'] = lib.data.jet_zones.smooth(thr)
thr['threshold'] = lib.data.SN_separation.smooth(thr)
# gc = gc.chunk(dict(time=6))
# st = st.chunk(dict(time=6))
......
......@@ -9,7 +9,7 @@ import xarray as xr
import lib
import lib.data.globcolour
import lib.data.hi
import lib.data.jet_zones
import lib.data.SN_separation
import lib.data.ostia
plt.switch_backend('agg')
......@@ -21,7 +21,7 @@ args['fixes']['Y'] = args['year']
gc = lib.data.globcolour.get_data(args)
st = lib.data.ostia.get_data(args)
hi = lib.data.hi.get_data(args)
thr = lib.data.jet_zones.get_data(args)
thr = lib.data.SN_separation.get_data(args)
gc = lib.fix_time_daily(gc)
st = lib.fix_time_daily(st)
......@@ -32,7 +32,7 @@ gc, st, hi, thr = xr.align(gc, st, hi, thr, join="inner",
exclude=['lat', 'lon'])
thr['threshold'] = lib.data.jet_zones.smooth(thr)
thr['threshold'] = lib.data.SN_separation.smooth(thr)
# gc = gc.chunk(dict(time=6))
# st = st.chunk(dict(time=6))
......
......@@ -9,7 +9,7 @@ import lib
import lib.data.ostia
import lib.data.hi
import lib.data.globcolour
import lib.data.jet_zones
import lib.data.SN_separation
fixes = dict(
......@@ -34,7 +34,7 @@ st = st.sel(lat=slice(lat_min, None))
gc = gc.sel(lat=slice(None, lat_min))
hi = hi.sel(lat=slice(None, lat_min))
th = lib.data.jet_zones.get_data(fixes=fixes)
th = lib.data.SN_separation.get_data(fixes=fixes)
th = lib.fix_time_daily(th)
th = th.sel(time=datetime(fixes['Y'], fixes['m'], fixes['d']))
st['mask'] = st.analysed_sst > th.threshold.values
......
......@@ -5,7 +5,7 @@ import matplotlib.pyplot as plt
import lib
import lib.data.ostia
import lib.data.jet_zones
import lib.data.SN_separation
plt.switch_backend('agg')
......@@ -14,11 +14,11 @@ fixes = dict(
Y=2007
)
odir = path.join(lib.root_plot, 'jet_zones')
odir = path.join(lib.root_plot, 'SN_separation')
st = lib.data.ostia.get_data(fixes=fixes)
thr = lib.data.jet_zones.get_data(fixes=fixes)
st['thr'] = lib.data.jet_zones.smooth(thr, 8)
thr = lib.data.SN_separation.get_data(fixes=fixes)
st['thr'] = lib.data.SN_separation.smooth(thr, 8)
st = st.isel(time=slice(None, None, 10))
st = st.sel(lat=slice(30, None))
st['GS_N'] = st.analysed_sst > st.thr
......
......@@ -5,13 +5,13 @@ import lib
import lib.data
ARGS_DIR = {'region', 'days'}
pregex = 'jet_zones_%(Y).nc'
pregex = 'SN_separation_%(Y).nc'
grid = '4km_EPSG4326'
def get_root(args=None, **kwargs):
args = lib.data.process_args(ARGS_DIR, args, **kwargs)
root = path.join(lib.root_data, args['region'], 'Jet_zones',
root = path.join(lib.root_data, args['region'], 'SN_separation',
lib.data.get_time_folder(args))
return root
......
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