Limit frt proba to northern region

Compute/front_probability.py

-"""Compute monthly frontal presence probability."""
+"""Compute probability for a front to be present.
+
+in a given time, at a given pixel.
+"""
 
 from os import path
 
@@ -7,25 +10,33 @@ import pandas as pd
 import lib
 import lib.data.front_probability
 import lib.data.hi
+import lib.data.jet_zones
+import lib.data.ostia
 from lib.xarray_utils import save_chunks_by_date
 
 
-
 def main():
 
     def add_args(parser):
         parser.add_argument('-threshold', type=float, default=15.)
+        parser.add_argument('-period', type=str, default='monthly')
 
     args = lib.get_args(['region', 'days', 'year',
                          'scale', 'number', 'fixes'],
                         add_args=add_args)
+    if args['period'] != 'monthly':
+        raise ValueError("Script only supports monthly probability")
 
     args['fixes']['Y'] = args['year']
 
     ds = lib.data.hi.get_data(args)
+    sst = lib.data.ostia.get_data(args)
+    thr = lib.data.jet_zones.get_data(args)['threshold']
+
     hi = lib.data.hi.apply_coef(ds, lib.data.hi.get_coef(args))
-    frt = (hi > args['threshold']) * 1.
+    hi = hi.where(sst.analysed_sst < thr)
 
+    frt = (hi > args['threshold']) * 1.
     mth = frt.groupby('time.month').mean()
 
     mth = mth.rename(month='time')
@@ -36,7 +47,7 @@ def main():
 
     mth = mth.to_dataset(name='frt_p')
 
-    outdir = lib.data.front_probability.get_root(args, days='monthly')
+    outdir = lib.data.front_probability.get_root(args, period='monthly')
     lib.check_output_dir(path.join(outdir, str(args['year'])))
 
     save_chunks_by_date(mth, path.join(outdir, '%Y/%Y%m.nc'))

lib/data/front_probability.py

@@ -6,17 +6,17 @@ import lib
 import lib.data
 
 
-ARGS_DIR = {'region', 'days'}
-pregex = '%(Y)/%(Y)%(m).nc'
+ARGS_DIR = {'region', 'period'}
+pregex = '%(Y)/%(Y)%(m)%(d).nc'
 grid = '4km_EPSG4326'
-defaults = dict(days='monthly')
+defaults = dict(period='monthly')
 
 
 def get_root(args=None, **kwargs):
     args = lib.data.process_args(ARGS_DIR | {'climato'}, args,
                                  defaults, **kwargs)
     root = path.join(lib.root_data, args['region'], 'Frt_proba',
-                     lib.data.get_time_folder(args))
+                     args['period'])
     return root