From f29ad0db6d26b2bdad2a7036602d5940170a24f5 Mon Sep 17 00:00:00 2001
From: Le Roux Erwan <erwan.le-roux@irstea.fr>
Date: Tue, 7 May 2019 09:10:24 +0200
Subject: [PATCH] [EXTREME ESTIMATOR][MARGIN MODEL] add temporal linear margin
model
---
.../margin_function/linear_margin_function.py | 7 ++-
.../temporal_linear_margin_model.py | 52 +++++++++++++++++++
.../extreme_models/result_from_fit.py | 30 +++++++++--
extreme_estimator/extreme_models/utils.py | 2 -
.../coordinates/abstract_coordinates.py | 4 ++
.../abstract_spatio_temporal_observations.py | 2 +-
6 files changed, 86 insertions(+), 11 deletions(-)
create mode 100644 extreme_estimator/extreme_models/margin_model/temporal_linear_margin_model.py
diff --git a/extreme_estimator/extreme_models/margin_model/margin_function/linear_margin_function.py b/extreme_estimator/extreme_models/margin_model/margin_function/linear_margin_function.py
index 7545bc06..db54afeb 100644
--- a/extreme_estimator/extreme_models/margin_model/margin_function/linear_margin_function.py
+++ b/extreme_estimator/extreme_models/margin_model/margin_function/linear_margin_function.py
@@ -50,10 +50,9 @@ class LinearMarginFunction(ParametricMarginFunction):
if self.starting_point is not None:
# Shift temporal coordinate to enable to model temporal trend with starting point
assert self.coordinates.has_temporal_coordinates
- idx_coordinate_t = self.coordinates.coordinates_names.index(self.coordinates.COORDINATE_T)
- assert 0 <= idx_coordinate_t < len(coordinate)
- if coordinate[idx_coordinate_t] < self.starting_point:
- coordinate[idx_coordinate_t] = self.starting_point
+ assert 0 <= self.coordinates.idx_temporal_coordinates < len(coordinate)
+ if coordinate[self.coordinates.idx_temporal_coordinates] < self.starting_point:
+ coordinate[self.coordinates.idx_temporal_coordinates] = self.starting_point
return super().get_gev_params(coordinate)
@classmethod
diff --git a/extreme_estimator/extreme_models/margin_model/temporal_linear_margin_model.py b/extreme_estimator/extreme_models/margin_model/temporal_linear_margin_model.py
new file mode 100644
index 00000000..42574333
--- /dev/null
+++ b/extreme_estimator/extreme_models/margin_model/temporal_linear_margin_model.py
@@ -0,0 +1,52 @@
+import numpy as np
+import pandas as pd
+
+from extreme_estimator.extreme_models.margin_model.linear_margin_model import LinearMarginModel
+from extreme_estimator.extreme_models.result_from_fit import ResultFromFit, ResultFromIsmev
+from extreme_estimator.extreme_models.utils import r, ro, get_null
+from extreme_estimator.extreme_models.utils import safe_run_r_estimator
+from extreme_estimator.margin_fits.gev.gev_params import GevParams
+from spatio_temporal_dataset.coordinates.abstract_coordinates import AbstractCoordinates
+
+
+class TemporalLinearMarginModel(LinearMarginModel):
+ # Linearity only with respect to the temporal coordinates
+
+ def __init__(self, coordinates: AbstractCoordinates, use_start_value=False, params_start_fit=None,
+ params_sample=None, starting_point=None):
+ super().__init__(coordinates, use_start_value, params_start_fit, params_sample, starting_point)
+
+ def fitmargin_from_maxima_gev(self, data: np.ndarray, df_coordinates_spat: pd.DataFrame,
+ df_coordinates_temp: pd.DataFrame) -> ResultFromFit:
+ # Modify df_coordinates_temp
+ df_coordinates_temp = self.add_starting_temporal_point(df_coordinates_temp)
+ # Gev Fit
+ res = safe_run_r_estimator(function=r('gev.fit'), use_start=self.use_start_value,
+ xdat=ro.FloatVector(data[0]), y=df_coordinates_temp.values, mul=self.mul)
+ return ResultFromIsmev(res, self.margin_function_start_fit.gev_param_name_to_dims)
+
+ @property
+ def mul(self):
+ return NotImplementedError
+
+
+class StationaryStationModel(TemporalLinearMarginModel):
+
+ def load_margin_functions(self, gev_param_name_to_dims=None):
+ super().load_margin_functions({})
+
+ @property
+ def mul(self):
+ return get_null()
+
+
+class NonStationaryStationModel(TemporalLinearMarginModel):
+
+ def load_margin_functions(self, gev_param_name_to_dims=None):
+ super().load_margin_functions({GevParams.LOC: [self.coordinates.idx_temporal_coordinates]})
+
+ @property
+ def mul(self):
+ return 1
+
+
diff --git a/extreme_estimator/extreme_models/result_from_fit.py b/extreme_estimator/extreme_models/result_from_fit.py
index 9ddcf476..bc01dd8b 100644
--- a/extreme_estimator/extreme_models/result_from_fit.py
+++ b/extreme_estimator/extreme_models/result_from_fit.py
@@ -3,6 +3,8 @@ from typing import Dict
from rpy2 import robjects
from extreme_estimator.extreme_models.margin_model.param_function.linear_coef import LinearCoef
+from extreme_estimator.margin_fits.gev.gev_params import GevParams
+from spatio_temporal_dataset.coordinates.abstract_coordinates import AbstractCoordinates
class ResultFromFit(object):
@@ -27,17 +29,38 @@ class ResultFromFit(object):
class ResultFromIsmev(ResultFromFit):
- pass
+
+ def __init__(self, result_from_fit: robjects.ListVector, gev_param_name_to_dim) -> None:
+ super().__init__(result_from_fit)
+ self.gev_param_name_to_dim = gev_param_name_to_dim
@property
- def mle(self):
- return self.res['mle']
+ def margin_coef_dict(self):
+ # Build the Coeff dict from gev_param_name_to_dim
+ coef_dict = {}
+ i = 0
+ mle_values = self.name_to_value['mle']
+ for gev_param_name in GevParams.PARAM_NAMES:
+ # Add intercept
+ intercept_coef_name = LinearCoef.coef_template_str(gev_param_name, LinearCoef.INTERCEPT_NAME).format(1)
+ coef_dict[intercept_coef_name] = mle_values[i]
+ i += 1
+ # Add a potential linear temporal trend
+ if gev_param_name in self.gev_param_name_to_dim:
+ temporal_coef_name = LinearCoef.coef_template_str(gev_param_name, AbstractCoordinates.COORDINATE_T).format(1)
+ coef_dict[temporal_coef_name] = mle_values[i]
+ i += 1
+ return coef_dict
+ @property
+ def all_parameters(self):
+ return self.margin_coef_dict
@property
def nllh(self):
return self.res['nllh']
+
class ResultFromSpatialExtreme(ResultFromFit):
"""
Handler from any result with the result of a fit functions from the package Spatial Extreme
@@ -45,7 +68,6 @@ class ResultFromSpatialExtreme(ResultFromFit):
FITTED_VALUES_NAME = 'fitted.values'
CONVERGENCE_NAME = 'convergence'
-
@property
def convergence(self) -> str:
convergence_value = self.name_to_value[self.CONVERGENCE_NAME]
diff --git a/extreme_estimator/extreme_models/utils.py b/extreme_estimator/extreme_models/utils.py
index afeaf6fb..581723ad 100644
--- a/extreme_estimator/extreme_models/utils.py
+++ b/extreme_estimator/extreme_models/utils.py
@@ -16,8 +16,6 @@ from rpy2.rinterface._rinterface import RRuntimeError
from rpy2.robjects import numpy2ri
from rpy2.robjects import pandas2ri
-from extreme_estimator.extreme_models.result_from_fit import ResultFromFit, ResultFromSpatialExtreme
-
r = ro.R()
numpy2ri.activate()
pandas2ri.activate()
diff --git a/spatio_temporal_dataset/coordinates/abstract_coordinates.py b/spatio_temporal_dataset/coordinates/abstract_coordinates.py
index f4653bd4..95229f9f 100644
--- a/spatio_temporal_dataset/coordinates/abstract_coordinates.py
+++ b/spatio_temporal_dataset/coordinates/abstract_coordinates.py
@@ -202,6 +202,10 @@ class AbstractCoordinates(object):
df_temporal_coordinates = self.df_temporal_coordinates(split)
return int(df_temporal_coordinates.min()), int(df_temporal_coordinates.max()),
+ @property
+ def idx_temporal_coordinates(self):
+ return self.coordinates_names.index(self.COORDINATE_T)
+
# Spatio temporal attributes
@property
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 8b7076d0..483db946 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
@@ -12,7 +12,7 @@ class AbstractSpatioTemporalObservations(object):
OBSERVATIONS_GEV = 'obs_gev'
OBSERVATIONS_FRECH = 'obs_frech'
- def __init__(self, df_maxima_frech: pd.DataFrame = None, df_maxima_gev: pd.DataFrame = None):
+ def __init__(self, df_maxima_gev: pd.DataFrame = None, df_maxima_frech: pd.DataFrame = None):
"""
Main attribute of the class is the DataFrame df_maxima
Index are coordinates index
--
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