From 1ebf5239ac01c63295bad58fdaec150dd9d39b09 Mon Sep 17 00:00:00 2001
From: "v.gramlich1" <v.gramlichfz-juelich.de>
Date: Tue, 22 Jun 2021 11:08:27 +0200
Subject: [PATCH] Todo: l.209
---
mlair/data_handler/default_data_handler.py | 37 +++++++++++++++-------
1 file changed, 25 insertions(+), 12 deletions(-)
diff --git a/mlair/data_handler/default_data_handler.py b/mlair/data_handler/default_data_handler.py
index 0c6d2ddc..d0ee9d0a 100644
--- a/mlair/data_handler/default_data_handler.py
+++ b/mlair/data_handler/default_data_handler.py
@@ -166,13 +166,15 @@ class DefaultDataHandler(AbstractDataHandler):
def apply_transformation(self, data, base="target", dim=0, inverse=False):
return self.id_class.apply_transformation(data, dim=dim, base=base, inverse=inverse)
- def apply_oversampling(self, bin_edges, oversampling_rates):
+ def apply_oversampling(self, bin_edges, oversampling_rates, timedelta: Tuple[int, str] = (1, 's'), timedelta2: Tuple[int, str] = (1, 'ms')):
self._load()
if (self._X is None) or (self._Y is None):
logging.debug(f"{str(self.id_class)} has no data for X or Y, skip multiply extremes")
return
Y = self._Y
X = self._X
+ complete_extremes_X_list = []
+ complete_extremes_Y_list = []
for i_bin in range(len(bin_edges)-1):
bin_start = bin_edges[i_bin]
if i_bin == len(bin_edges) - 1:
@@ -186,16 +188,27 @@ class DefaultDataHandler(AbstractDataHandler):
extreme_idx = xr.concat([(Y >= bin_start).any(dim=other_dims[0]),
(Y < bin_end).any(dim=other_dims[0])],
dim=other_dims[0]).all(dim=other_dims[0])
-
- extremes_X = list(map(lambda x: x.sel(**{self.time_dim: extreme_idx}), X))
- self._add_timedelta(extremes_X, dim, timedelta)
- # extremes_X = list(map(lambda x: x.coords[dim].values + np.timedelta64(*timedelta), extremes_X))
-
- extremes_Y = Y.sel(**{dim: extreme_idx})
- extremes_Y.coords[dim].values += np.timedelta64(*timedelta)
-
- self._Y_extreme = xr.concat([Y, extremes_Y], dim=dim)
- self._X_extreme = list(map(lambda x1, x2: xr.concat([x1, x2], dim=dim), X, extremes_X))
+ extremes_X_list =[]
+ extremes_Y_list = []
+ for i in range(np.ceil(rate).astype(int)):
+ sel = extreme_idx.coords[self.time_dim].values
+ if rate-i < 1:
+ rest = int(len(sel)*(rate-i))
+ sel = np.random.choice(sel, rest, replace=False)
+ extremes_X = list(map(lambda x: x.sel(**{self.time_dim: sel}), X))
+ self._add_timedelta(extremes_X, self.time_dim, (i,timedelta[1]))
+ self._add_timedelta(extremes_X, self.time_dim, (i_bin, timedelta2[1]))
+ extremes_Y = Y.sel(**{self.time_dim: sel})
+ extremes_Y.coords[self.time_dim] = extremes_Y.coords[self.time_dim].values + i*np.timedelta64(*timedelta) + i_bin*np.timedelta64(*timedelta2)
+ extremes_X_list.append(extremes_X)
+ extremes_Y_list.append(extremes_Y)
+
+ complete_extremes_X_list.append(extremes_X_list)
+ complete_extremes_Y_list.append(extremes_Y_list)
+
+ #Convert complete_extremes_X_list (list of lists of xarrays) into xarray and give it to self._X_extreme
+ #self._X_extreme = [[xr.concat(X_list, dim=self.time_dim) for X_list in complete_X_list] for complete_X_list in complete_extremes_X_list]
+ #self._Y_extreme = [[xr.concat(Y_list, dim=self.time_dim) for Y_list in complete_Y_list] for complete_Y_list in complete_extremes_Y_list]
def multiply_extremes(self, extreme_values: num_or_list = 1., extremes_on_right_tail_only: bool = False,
@@ -264,7 +277,7 @@ class DefaultDataHandler(AbstractDataHandler):
@staticmethod
def _add_timedelta(data, dim, timedelta):
for d in data:
- d.coords[dim].values += np.timedelta64(*timedelta)
+ d.coords[dim] = d.coords[dim].values + np.timedelta64(*timedelta)
@classmethod
def transformation(cls, set_stations, **kwargs):
--
GitLab