diff --git a/enstools/feature/identification/aew_vortices/configuration.py b/enstools/feature/identification/aew_vortices/configuration.py
index dffeab69425b4673549a2d629edb8d417132e88c..dd831233789c43f2cf4d3e1b0cac4571320900d1 100644
--- a/enstools/feature/identification/aew_vortices/configuration.py
+++ b/enstools/feature/identification/aew_vortices/configuration.py
@@ -10,16 +10,26 @@ import os
# lonW = -100
# lonE = 45
-in_data = "/home/ws/he7273/phd_all/data/coll_oper/jjaso2021.nc"
-in_wts = "/home/ws/he7273/phd_all/data/coll_oper/jjaso2021.json"
+in_data = "/project/meteo/w2w/C3/fischer/data/coll_oper/2021/jjaso2021.nc"
+in_wts = "/project/meteo/w2w/C3/fischer/belanger/out/jjaso2021.json"
-circles_file = "/home/ws/he7273/phd_all/data/aew/circles.nc"
-fig_dir = '/home/ws/he7273/phd_all/data/vortices/figs'
+# in_data = "/home/ws/he7273/phd_all/data/coll_oper/jjaso2021.nc"
+# in_wts = "/home/ws/he7273/phd_all/data/coll_oper/jjaso2021.json"
+
+circles_file = "/project/meteo/w2w/C3/fischer/data/circles.nc"
+fig_dir = '/project/meteo/w2w/C3/fischer/data/vortices/figs'
+
+# circles_file = "/home/ws/he7273/phd_all/data/aew/circles.nc"
+# fig_dir = '/home/ws/he7273/phd_all/data/vortices/figs'
+
+
+# kw_rain_cm_file = '/home/he7273/phd_all/data/tracked/colorpalette_dyamond_prec_rate.txt'
+kw_rain_cm_file = '/project/meteo/w2w/C3/fischer/belanger/colorpalette_dyamond_prec_rate.txt'
# plot_dir = '/home/ws/he7273/phd_all/data/coll_oper/' # '/project/meteo/w2w/C3/fischer/belanger/plots/' # join('/home/ws/he7273/phd_all/data/aew/plots/') # '/project/meteo/w2w/C3/fischer/belanger/plots/'
field = 'rv'
-bpf = False
+bpf = True
fig_dir = fig_dir + '_' + ('bpf' if bpf else 'no_bpf') + '_' + field + '/'
try:
@@ -36,8 +46,9 @@ base_threshold = {'cv': 3e-5, 'cva': 1e-5, 'rv': 3e-5}
# time of interest, if None all
# june-oct is AEW season
-start_date = '2021-08-27T00:00' # '2022-08-01T00:00' # None # '2008-08-01T00:00' # # '2008-08-01T00:00'
-end_date = '2021-08-28T10:00' # '2022-08-15T00:00' # None # '2008-08-15T00:00' # None # '2008-08-03T00:00'
+## TODO CHANGE DATE AND BPF 2-6D
+start_date = '2021-09-01T00:00' # '2022-08-01T00:00' # None # '2008-08-01T00:00' # # '2008-08-01T00:00'
+end_date = '2021-09-15T00:00' # '2022-08-15T00:00' # None # '2008-08-15T00:00' # None # '2008-08-03T00:00'
radius = 500000 # 500 km
prominence_radius = 400000 # 300 km
diff --git a/enstools/feature/identification/aew_vortices/identification.py b/enstools/feature/identification/aew_vortices/identification.py
index af753f46319dfbccdde70d392727ad4cebb9fb0e..33e99f3f6df906ae309ce1e9a1c4d1c56d7ce5ee 100644
--- a/enstools/feature/identification/aew_vortices/identification.py
+++ b/enstools/feature/identification/aew_vortices/identification.py
@@ -120,7 +120,8 @@ class AEWVortexIdentification(IdentificationStrategy):
dataset['foci_c'] = xr.zeros_like(dataset[self.field], dtype=int)
l2 = xr.zeros_like(dataset[u_name], dtype=float)
- # TODO compute CPs in parallel in identify()
+
+ """
for time in dataset.time.values:
for lev in dataset.level.values:
print(time)
@@ -150,7 +151,8 @@ class AEWVortexIdentification(IdentificationStrategy):
dt['saddle'] = cp
dt['foci_c'] = cp_c
dataset.loc[dict(level=lev, time=time)] = dt
-
+
+ """
dataset = create_wt_troughs_and_areas(dataset, self.json_desc, self.circles, False, d=self.config.radius)
"""
@@ -190,6 +192,33 @@ class AEWVortexIdentification(IdentificationStrategy):
def identify(self, data_chunk: xr.Dataset, **kwargs):
objs = []
+
+ cp = data_chunk.saddle
+ cp_c = data_chunk.foci_c
+ u_name = self.config.u_dim
+ v_name = self.config.v_dim
+
+ sx = ScalarField()
+ sx.import_from_arrays(data_chunk.latitude.values.tolist(), data_chunk.longitude.values.tolist(), data_chunk[u_name].data)
+ sy = ScalarField()
+ sy.import_from_arrays(data_chunk.latitude.values.tolist(), data_chunk.longitude.values.tolist(), data_chunk[v_name].data)
+
+ v = VectorField()
+ v.import_from_sfs(sx, sy)
+
+ cpp = IMTreatment.vortex_detection.vortex_detection.get_critical_points(v)
+ foci = cpp.sadd[0].xy
+ foci_c = cpp.foc_c[0].xy
+
+ for i in range(foci.shape[0]):
+ cp.loc[dict(longitude=round_off_rating(foci[i][1]), latitude=round_off_rating(foci[i][0]))] = 1
+
+ for i in range(foci_c.shape[0]):
+ cp_c.loc[dict(longitude=round_off_rating(foci_c[i][1]), latitude=round_off_rating(foci_c[i][0]))] = 1
+
+ data_chunk['saddle'] = cp
+ data_chunk['foci_c'] = cp_c
+
# v = data_chunk.vortices
cp = data_chunk.saddle
diff --git a/enstools/feature/identification/aew_vortices/plotting.py b/enstools/feature/identification/aew_vortices/plotting.py
index 5313f1ebfffcd6c89e06dc7b6cd15bfa0c525387..e2c9b5d66de219a3d69fe4d970645131ea3b2b09 100644
--- a/enstools/feature/identification/aew_vortices/plotting.py
+++ b/enstools/feature/identification/aew_vortices/plotting.py
@@ -10,12 +10,10 @@ from cartopy.mpl.gridliner import LONGITUDE_FORMATTER, LATITUDE_FORMATTER
from PIL import Image
from datetime import datetime
-def get_kitweather_rain_cm():
+def get_kitweather_rain_cm(rain_cm_file):
rgb_colors = []
- pathtotxtfile = '/home/he7273/phd_all/data/tracked/'
- filename_colorpalette = 'colorpalette_dyamond_prec_rate.txt'
- with open(pathtotxtfile + filename_colorpalette, 'r') as f:
+ with open(rain_cm_file, 'r') as f:
lines = f.readlines()
for i, line in enumerate(lines):
rgb_colors.append([float(line[0:3])/255, float(line[4:7])/255, float(line[8:11])/255, 1])
@@ -79,8 +77,8 @@ def plot_kw_style(dataset, dataset_desc, config, lev=700):
subplot_kw=dict(projection=ccrs.PlateCarree()))
extent = [-75, 45, -10, 40]
-
- levels_rain, rain_cm, norm = get_kitweather_rain_cm()
+
+ levels_rain, rain_cm, norm = get_kitweather_rain_cm(config.kw_rain_cm_file)
distance_plot_to_cbar = 0.010
axins = ax.inset_axes([1 + distance_plot_to_cbar, 0.05, 0.015, 0.93],
transform=ax.transAxes)
@@ -131,9 +129,9 @@ def plot_kw_style(dataset, dataset_desc, config, lev=700):
# plot vortices
# ds_t.sel(level=700).vortices.plot.contourf(levels=[-0.5,0.5,99], colors=('#00000000', 'blue'), subplot_kws={'transform_first': True}, add_colorbar=False)
- ds_t.sel(level=lv).saddle.plot.contourf(levels=[-0.5,0.5,99], colors=('#00000000', 'green'), subplot_kws={'transform_first': True}, add_colorbar=False)
- ds_t.sel(level=lv).foci_c.plot.contourf(levels=[-0.5, 0.5, 99], colors=('#00000000', 'grey'),
- subplot_kws={'transform_first': True}, add_colorbar=False)
+ ds_t.sel(level=lv).saddle.plot.contourf(levels=[-0.5,0.5,99], colors=('#00000000', 'orange'), subplot_kws={'transform_first': True}, add_colorbar=False)
+ ds_t.sel(level=lv).foci_c.plot.contourf(levels=[-0.5, 0.5, 99], colors=('#00000000', 'orange'),
+ subplot_kws={'transform_first': True}, add_colorbar=False) #### TODO all points seem to end up here!!
# ds_t.prec_rate_rea.plot.contourf(levels=levels_rain, extend='max', subplot_kws={'transform_first': True},
# cmap=rain_cm, norm=norm, add_colorbar=False)
diff --git a/enstools/feature/identification/aew_vortices/util.py b/enstools/feature/identification/aew_vortices/util.py
index f0be833d46abe001d4250e4b54b52fddadd0ccd3..f1644b4fd306c5e9904ef06b046957abaf4fdc77 100644
--- a/enstools/feature/identification/aew_vortices/util.py
+++ b/enstools/feature/identification/aew_vortices/util.py
@@ -255,8 +255,8 @@ def bpf(dataset, u_str, v_str, min_days=2, max_days=6): # 2-6day bpf as default
time_res_days = time_res_hrs / 24.0 # 6/24 = 1/4
print("Execute bpf for " + str(min_days) + " to " + str(max_days) + " days.")
- u_filtered = butter_bandpass_filter(dataset[u_str].data, time_res_days / 6, time_res_days / 2, 1, axis=0) # time is dim0
- v_filtered = butter_bandpass_filter(dataset[v_str].data, time_res_days / 6, time_res_days / 2, 1, axis=0) # time is dim0
+ u_filtered = butter_bandpass_filter(dataset[u_str].data, time_res_days / max_days, time_res_days / min_days, 1, axis=0) # time is dim0
+ v_filtered = butter_bandpass_filter(dataset[v_str].data, time_res_days / max_days, time_res_days / min_days, 1, axis=0) # time is dim0
u_bpf = xr.zeros_like(dataset[u_str])
v_bpf = xr.zeros_like(dataset[v_str])
diff --git a/enstools/feature/identification/african_easterly_waves/configuration.py b/enstools/feature/identification/african_easterly_waves/configuration.py
index a5c01a65c71a4f4263b0b19f5bb10cdd4e67d619..dbf9b187353387616c8b2f49bf274bdf85ed5251 100644
--- a/enstools/feature/identification/african_easterly_waves/configuration.py
+++ b/enstools/feature/identification/african_easterly_waves/configuration.py
@@ -13,11 +13,13 @@ data_lat = (3, 35)
data_lon = (-100, 45)
aew_clim_dir = '/project/meteo/w2w/C3/fischer/belanger/aew_clim/cv_clim_era5.nc' # '/home/ws/he7273/phd_all/data/aew/clim/cv_clim_era5.nc' # # '/lsdf/MOD/Gruppe_Transregio/Gruppe_Knippertz/kitweather/data/era5/cv_clim_era5.nc' 'C:\\Users\\Christoph\\phd\\data\\enstools-feature\\cv_clim_era5.nc' # '/home/christoph/phd/data/aew/clim/cv_clim_era5.nc' # '/home/christoph/phd/data/framework_example_ds/aew/' # '/project/meteo/w2w/C3/fischer/belanger/aew_clim/' #
-in_files = '/project/meteo/w2w/C3/fischer/data/coll_oper/2021/jjaso2021.nc' # '/home/ws/he7273/phd_all/data/coll_oper/jja2021/jja2021.nc' # 'C:\\Users\\Christoph\\phd\\data\\enstools-feature\\2008_sum_uv.nc' # '/home/christoph/phd/data/framework_example_ds/aew/cv_aug_08.nc'
-out_dir = '/project/meteo/w2w/C3/fischer/belanger/out/' # join('/home/ws/he7273/phd_all/data/aew/out/') # '/project/meteo/w2w/C3/fischer/belanger/out/'
+in_files = '/project/meteo/w2w/C3/fischer/data/aew_new/2009/jjaso2009_uv_05.nc' #
+'/home/ws/he7273/phd_all/data/coll_oper/jja2021/jja2021.nc' # 'C:\\Users\\Christoph\\phd\\data\\enstools-feature\\2008_sum_uv.nc' # '/home/christoph/phd/data/framework_example_ds/aew/cv_aug_08.nc'
+out_dir = '/project/meteo/w2w/C3/fischer/data/aew_new/2009/' #
+join('/home/ws/he7273/phd_all/data/aew/out/') # '/project/meteo/w2w/C3/fischer/belanger/out/'
-out_json_path = out_dir + 'jjaso2021.json'
-out_data_path = out_dir + 'jjaso2021_wts.nc'
+out_json_path = out_dir + 'jjaso2009.json'
+out_data_path = out_dir + 'jjaso2009_wts.nc'
generate_output = True
plot_dir = '/home/ws/he7273/phd_all/data/coll_oper/' # '/project/meteo/w2w/C3/fischer/belanger/plots/' # join('/home/ws/he7273/phd_all/data/aew/plots/') # '/project/meteo/w2w/C3/fischer/belanger/plots/'
diff --git a/enstools/feature/identification/african_easterly_waves/run_identify.py b/enstools/feature/identification/african_easterly_waves/run_identify.py
index 33ce487f8721fcfa789cd0d4b1b5b549383073d6..6120a98b420e5f5d2d2ae079c5d38319feb08018 100644
--- a/enstools/feature/identification/african_easterly_waves/run_identify.py
+++ b/enstools/feature/identification/african_easterly_waves/run_identify.py
@@ -176,6 +176,12 @@ if enable_out:
### add WTs to orig DS. field tracks and field WTs
ds = add_wts_to_ds(ds, ob)
print(ds)
+ if 'u' in ds.data_vars:
+ ds = ds.drop_vars(['u'])
+ if 'v' in ds.data_vars:
+ ds = ds.drop_vars(['v'])
+ if 'cv' in ds.data_vars:
+ ds = ds.drop_vars(['cv'])
pipeline.set_data(ds)