diff --git a/mlair/data_handler/input_bootstraps.py b/mlair/data_handler/input_bootstraps.py
index b8ad614f2317e804d415b23308df760f4dd8da7f..c33e90caf74389a686c3955c4072cc89d41349b6 100644
--- a/mlair/data_handler/input_bootstraps.py
+++ b/mlair/data_handler/input_bootstraps.py
@@ -75,6 +75,14 @@ class BootstrapIterator(Iterator):
else:
return self._method.apply(data)
+ def _prepare_data_for_next(self):
+ index_dimension_collection = self._collection[self._position]
+ nboot = self._data.number_of_bootstraps
+ _X, _Y = self._data.data.get_data(as_numpy=False)
+ _X = list(map(lambda x: x.expand_dims({self.boot_dim: range(nboot)}, axis=-1), _X))
+ _Y = _Y.expand_dims({self.boot_dim: range(nboot)}, axis=-1)
+ return _X, _Y, index_dimension_collection
+
class BootstrapIteratorSingleInput(BootstrapIterator):
_position: int = None
@@ -85,11 +93,12 @@ class BootstrapIteratorSingleInput(BootstrapIterator):
def __next__(self):
"""Return next element or stop iteration."""
try:
- index, dimension = self._collection[self._position]
- nboot = self._data.number_of_bootstraps
- _X, _Y = self._data.data.get_data(as_numpy=False)
- _X = list(map(lambda x: x.expand_dims({self.boot_dim: range(nboot)}, axis=-1), _X))
- _Y = _Y.expand_dims({self.boot_dim: range(nboot)}, axis=-1)
+ _X, _Y, (index, dimension) = self._prepare_data_for_next()
+ # index, dimension = self._collection[self._position]
+ # nboot = self._data.number_of_bootstraps
+ # _X, _Y = self._data.data.get_data(as_numpy=False)
+ # _X = list(map(lambda x: x.expand_dims({self.boot_dim: range(nboot)}, axis=-1), _X))
+ # _Y = _Y.expand_dims({self.boot_dim: range(nboot)}, axis=-1)
single_variable = _X[index].sel({self._dimension: [dimension]})
bootstrapped_variable = self.apply_bootstrap_method(single_variable.values)
bootstrapped_data = xr.DataArray(bootstrapped_variable, coords=single_variable.coords,
@@ -117,11 +126,7 @@ class BootstrapIteratorVariable(BootstrapIterator):
def __next__(self):
"""Return next element or stop iteration."""
try:
- dimension = self._collection[self._position]
- nboot = self._data.number_of_bootstraps
- _X, _Y = self._data.data.get_data(as_numpy=False)
- _X = list(map(lambda x: x.expand_dims({self.boot_dim: range(nboot)}, axis=-1), _X))
- _Y = _Y.expand_dims({self.boot_dim: range(nboot)}, axis=-1)
+ _X, _Y, dimension = self._prepare_data_for_next()
for index in range(len(_X)):
if dimension in _X[index].coords[self._dimension]:
single_variable = _X[index].sel({self._dimension: [dimension]})
@@ -150,11 +155,12 @@ class BootstrapIteratorBranch(BootstrapIterator):
def __next__(self):
try:
- index = self._collection[self._position]
- nboot = self._data.number_of_bootstraps
- _X, _Y = self._data.data.get_data(as_numpy=False)
- _X = list(map(lambda x: x.expand_dims({self.boot_dim: range(nboot)}, axis=-1), _X))
- _Y = _Y.expand_dims({self.boot_dim: range(nboot)}, axis=-1)
+ _X, _Y, index = self._prepare_data_for_next()
+ # index = self._collection[self._position]
+ # nboot = self._data.number_of_bootstraps
+ # _X, _Y = self._data.data.get_data(as_numpy=False)
+ # _X = list(map(lambda x: x.expand_dims({self.boot_dim: range(nboot)}, axis=-1), _X))
+ # _Y = _Y.expand_dims({self.boot_dim: range(nboot)}, axis=-1)
for dimension in _X[index].coords[self._dimension].values:
single_variable = _X[index].sel({self._dimension: [dimension]})
bootstrapped_variable = self.apply_bootstrap_method(single_variable.values)
@@ -172,6 +178,68 @@ class BootstrapIteratorBranch(BootstrapIterator):
return list(range(len(data.get_X(as_numpy=False))))
+class BootstrapIteratorVariableSets(BootstrapIterator):
+ _variable_set_splitters: list = ['Sect', 'SectLeft', 'SectRight',]
+
+ def __init__(self, *args, **kwargs):
+ super().__init__(*args, **kwargs)
+ #self.variable_set_splitters = ['Sect', 'SectLeft', 'SectRight']
+
+ def __next__(self):
+ try:
+ _X, _Y, (_index, _dimension) = self._prepare_data_for_next()
+
+ for index, dimensions in self._collection:
+ print(index, dimensions)
+ for dimension in dimensions:
+ print(index, dimension)
+ single_variable = _X[index].sel({self._dimension: [dimension]})
+ bootstrapped_variable = self.apply_bootstrap_method(single_variable.values)
+ bootstrapped_data = xr.DataArray(bootstrapped_variable, coords=single_variable.coords,
+ dims=single_variable.dims)
+ _X[index] = bootstrapped_data.combine_first(_X[index]).transpose(*_X[index].dims)
+
+ # for dimension in _X[index].coords[self._dimension].values:
+ # single_variable = _X[index].sel({self._dimension: [dimension]})
+ # bootstrapped_variable = self.apply_bootstrap_method(single_variable.values)
+ # bootstrapped_data = xr.DataArray(bootstrapped_variable, coords=single_variable.coords,
+ # dims=single_variable.dims)
+ # _X[index] = bootstrapped_data.combine_first(_X[index]).transpose(*_X[index].dims)
+ self._position += 1
+ except IndexError:
+ StopIteration()
+ _X, _Y = self._to_numpy(_X), self._to_numpy(_Y)
+ return self._reshape(_X), self._reshape(_Y), (index, dimension)
+ # return self._reshape(_X), self._reshape(_Y), (None, index)
+
+ @classmethod
+ def create_collection(cls, data, dim):
+ # l = set()
+ # for i, x in enumerate(data.get_X(as_numpy=False)):
+ # l.update(x.indexes[dim].to_list())
+ # # l.update(['O3Sect', 'O3SectLeft', 'O3SectRight']) # ToDo Remove : just for testing
+ # return [[var for var in to_list(l) if var.endswith(collection_name)] for collection_name in cls._variable_set_splitters]
+
+ l = []
+ for i, x in enumerate(data.get_X(as_numpy=False)):
+ l.append(x.indexes[dim].to_list())
+ l[0] = l[0] + ['o3Sect', 'o3SectLeft', 'o3SectRight', 'no2Sect', 'no2SectLeft', 'no2SectRight']
+
+ res = [[var for var in l[i] if var.endswith(collection_name)] for collection_name in cls._variable_set_splitters]
+ res = [(i, dimensions) for i, _ in enumerate(data.get_X(as_numpy=False)) for dimensions in res]
+ return res
+ # return list(chain(*res))
+ # [[(0, 'o3'), (0, 'relhum'), (0, 'temp'), (0, 'u'), (0, 'v'), (0, 'no'), (0, 'no2'), (0, 'cloudcover'),
+ # (0, 'pblheight')]]
+
+
+
+ # l = []
+ # for i, x in enumerate(data.get_X(as_numpy=False)):
+ # l.append(list(map(lambda y: (i, y), x.indexes[dim])))
+ # return list(chain(*l))
+
+
class ShuffleBootstraps:
@staticmethod
@@ -225,10 +293,12 @@ class Bootstraps(Iterable):
self.bootstrap_method = {"shuffle": ShuffleBootstraps(),
"zero_mean": MeanBootstraps(mean=0)}.get(
bootstrap_method) # todo adjust number of bootstraps if mean bootstrapping
+ self.bootstrap_type = bootstrap_type
self.BootstrapIterator = {"singleinput": BootstrapIteratorSingleInput,
"branch": BootstrapIteratorBranch,
- "variable": BootstrapIteratorVariable}.get(bootstrap_type,
- BootstrapIteratorSingleInput)
+ "variable": BootstrapIteratorVariable,
+ "group_of_variables": BootstrapIteratorVariableSets,
+ }.get(bootstrap_type, BootstrapIteratorSingleInput)
def __iter__(self):
return self.BootstrapIterator(self, self.bootstrap_method)
@@ -236,6 +306,11 @@ class Bootstraps(Iterable):
def __len__(self):
return len(self.BootstrapIterator.create_collection(self.data, self.bootstrap_dimension))
+ def __repr__(self):
+ return f"Bootstraps(data={self.data}, number_of_bootstraps={self.number_of_bootstraps}, " \
+ f"bootstrap_dimension='{self.bootstrap_dimension}', bootstrap_type='{self.bootstrap_type}', " \
+ f"bootstrap_method='{self.bootstrap_method}')"
+
def bootstraps(self):
return self.BootstrapIterator.create_collection(self.data, self.bootstrap_dimension)