diff --git a/spatio_temporal_dataset/spatio_temporal_observations/abstract_spatio_temporal_observations.py b/spatio_temporal_dataset/spatio_temporal_observations/abstract_spatio_temporal_observations.py
index a5845546afcbc809b52bdd3b748678c5623d1c83..8c1890b5a2ddf1e7e1b13b3ce25be388a6364314 100644
--- a/spatio_temporal_dataset/spatio_temporal_observations/abstract_spatio_temporal_observations.py
+++ b/spatio_temporal_dataset/spatio_temporal_observations/abstract_spatio_temporal_observations.py
@@ -19,6 +19,12 @@ class AbstractSpatioTemporalObservations(object):
Main attribute of the class is the DataFrame df_maxima
Index are coordinates index
Columns are independent observations from the same coordinates index
+
+ For example, if we have spatial coordinates,
+ then all the columns might correspond to annual maxima observations for different years
+
+ If we have a spatio-temporal coordinates,
+ then all the columns might correspond to observations that were made at some spatial coodinate, and for some given year
"""
assert df_maxima_gev is not None or df_maxima_frech is not None
assert isinstance(df_maxima_gev, pd.DataFrame) or isinstance(df_maxima_frech, pd.DataFrame)
@@ -27,13 +33,6 @@ class AbstractSpatioTemporalObservations(object):
self.df_maxima_gev = df_maxima_gev # type: pd.DataFrame
self.df_maxima_frech = df_maxima_frech # type: pd.DataFrame
- @classmethod
- def from_csv(cls, csv_path: str = None):
- assert csv_path is not None
- assert op.exists(csv_path)
- df = pd.read_csv(csv_path, index_col=0)
- return cls.from_df(df)
-
@property
def _df_maxima(self) -> pd.DataFrame:
if self.df_maxima_frech is not None:
@@ -70,22 +69,6 @@ class AbstractSpatioTemporalObservations(object):
def nb_obs(self) -> int:
return len(self.columns)
- @classmethod
- def from_df(cls, df):
- df_maxima_list = []
- for suffix in [cls.OBSERVATIONS_GEV, cls.OBSERVATIONS_FRECH]:
- columns_with_suffix = [c for c in df.columns if str(c).endswith(suffix)]
- if columns_with_suffix:
- df_maxima = df[columns_with_suffix] if columns_with_suffix else None
- df_maxima.columns = [c.replace(' ' + suffix, '') for c in df_maxima.columns]
- else:
- df_maxima = None
- df_maxima_list.append(df_maxima)
- df_maxima_gev, df_maxima_frech = df_maxima_list
- if df_maxima_gev is not None and df_maxima_frech is not None:
- assert pd.Index.equals(df_maxima_gev.columns, df_maxima_frech.columns)
- return cls(df_maxima_gev=df_maxima_gev, df_maxima_frech=df_maxima_frech)
-
def convert_to_spatio_temporal_index(self, coordinates: AbstractCoordinates):
assert coordinates.has_spatio_temporal_coordinates
assert len(coordinates.index) == len(self.index) * self.nb_obs
@@ -130,9 +113,6 @@ class AbstractSpatioTemporalObservations(object):
def __str__(self) -> str:
return self._df_maxima.__str__()
- def __len__(self):
- return self._df_maxima.__len__()
-
def print_summary(self):
# Write a summary of observations
df = self.df_maxima_gev
diff --git a/spatio_temporal_dataset/spatio_temporal_observations/alps_precipitation_observations.py b/spatio_temporal_dataset/spatio_temporal_observations/alps_precipitation_observations.py
deleted file mode 100644
index 83ead9544aba119a5d350bf4af807c8bfc350aa4..0000000000000000000000000000000000000000
--- a/spatio_temporal_dataset/spatio_temporal_observations/alps_precipitation_observations.py
+++ /dev/null
@@ -1,36 +0,0 @@
-import os.path as op
-
-from spatio_temporal_dataset.spatio_temporal_observations.abstract_spatio_temporal_observations import \
- AbstractSpatioTemporalObservations
-from root_utils import get_full_path
-
-
-class AlpsPrecipitationObservations(AbstractSpatioTemporalObservations):
- RELATIVE_PATH = r'local/spatio_temporal_datasets/Gilles - precipitations'
- FULL_PATH = get_full_path(relative_path=RELATIVE_PATH)
-
- @classmethod
- def from_csv(cls, csv_file='max_precip_3j'):
- csv_path = op.join(cls.FULL_PATH, csv_file + '.csv')
- return super().from_csv(csv_path)
-
- @classmethod
- def transform_gilles_txt_into_csv(cls):
- filepath = op.join(cls.FULL_PATH, 'original data', 'max_precip_3j.txt')
- station_to_coordinates = {}
- # todo: be absolutely sure of the mapping, in the txt file of Gilles we do not have the coordinate
- # this seems rather dangerous, especially if he loaded
- # todo: re-do the whole analysis, and extraction myself about the snow
- with open(filepath, 'r') as f:
- for l in f:
- _, station_name, coordinates = l.split('"')
- coordinates = coordinates.split()
- print(len(coordinates))
- assert len(coordinates) == 55
- station_to_coordinates[station_name] = coordinates
- # df = pd.DataFrame.from_dict(data=station_to_coordinates, orient='index',
- # columns=[cls.COORDINATE_X, cls.COORDINATE_Y, cls.COORDINATE_Z])
- # print(df.head())
- # filepath = op.join(cls.FULL_PATH, 'max_precip_3j.csv')
- # assert not op.exists(filepath)
- # df.to_csv(filepath)