Skip to content
GitLab
Commit a4f03d04 authored by Le Roux Erwan's avatar Le Roux Erwan
Browse files

[MARGIN MODEL] add 3D fitspatgev. add test

parent 12229f6f
master
No related merge requests found
Hide whitespace changes
Inline Side-by-side
Showing
with 214 additions and 195 deletions
+214 -195
extreme_estimator/estimator/margin_estimator/abstract_margin_estimator.py
+ 2
− 3
View file @ a4f03d04
......@@ -35,9 +35,8 @@ class SmoothMarginEstimator(AbstractMarginEstimator):
def _fit(self):
maxima_gev = self.dataset.maxima_gev(split=self.train_split)
df_coordinates = self.dataset.df_coordinates(self.train_split)
df_coordinates_spatial = df_coordinates.loc[:, self.dataset.coordinates.coordinates_spatial_names]
df_coordinates_temporal = df_coordinates.loc[:, self.dataset.coordinates.coordinates_temporal_names]
df_coordinates_spatial = self.dataset.coordinates.df_spatial_coordinates(self.train_split)
df_coordinates_temporal = self.dataset.coordinates.df_temporal_coordinates(self.train_split)
self._params_fitted = self.margin_model.fitmargin_from_maxima_gev(maxima_gev=maxima_gev,
df_coordinates_spatial=df_coordinates_spatial,
df_coordinates_temporal=df_coordinates_temporal)
......
extreme_estimator/extreme_models/margin_model/fitspatgev.R
+ 124
− 168
View file @ a4f03d04
......@@ -26,7 +26,7 @@ fitspatgev_2D_test <- function (n.obs){
}
# fitspatgev_test with 3D data
fitspatgev_3D_test <- function (n.obs){
fitspatgev_3D_test_ok <- function (n.obs){
n.site = 2
covariables <- matrix(rnorm(2*n.site, sd = sqrt(.2)), ncol = 2)
colnames(covariables) = c("E", "N")
......@@ -47,183 +47,139 @@ fitspatgev_3D_test <- function (n.obs){
temp.cov = matrix(1:n.obs, ncol=1)
colnames(temp.cov) = c("T")
# namedlist = list(locCoeff1=0.0, locCoeff2=1.0, scaleCoeff1=0.1, shapeCoeff1=1.0,
# tempCoeffLoc1=0.0, tempCoeffLoc2=1.0, tempCoeffScale1=0.1, tempCoeffShape1=1.0)
start = list(locCoeff1=0.0, locCoeff2=1.0, scaleCoeff1=0.1, shapeCoeff1=1.0,
tempCoeffLoc1=0.0, tempCoeffLoc2=1.0, tempCoeffScale1=0.1, tempCoeffShape1=1.0)
# res = fitspatgev(data=data, covariables=covariables, start=namedlist, loc.form=loc.form, scale.form=scale.form,shape.form=shape.form,
# temp.cov=temp.cov, temp.loc.form = temp_loc.form, temp.scale.form = temp_scale.form, temp.shape.form = temp_shape.form)
start = list(locCoeff1=0.0, locCoeff2=1.0, scaleCoeff1=0.1, shapeCoeff1=1.0,
tempCoeffLoc1=0.0, tempCoeffScale1=0.1, tempCoeffShape1=1.0)
res = fitspatgev(data=data, covariables=covariables, start=start, loc.form=loc.form, scale.form=scale.form,shape.form=shape.form,
temp.cov=temp.cov, temp.form.loc=temp.form.loc, temp.form.scale=temp.form.scale, temp.form.shape=temp.form.shape)
#
# # START PASTING CODE FROM THE FUNCTION
# n.site <- ncol(data)
# n.obs <- nrow(data)
# if (n.site != nrow(covariables))
# stop("'data' and 'covariates' doesn't match")
# use.temp.cov <- c(!is.null(temp.form.loc), !is.null(temp.form.scale),
# !is.null(temp.form.shape))
# if (any(use.temp.cov) && (n.obs != nrow(temp.cov)))
# stop("'data' and 'temp.cov' doesn't match")
# if (any(use.temp.cov) && is.null(temp.cov))
# stop("'temp.cov' must be supplied if at least one temporal formula is given")
# loc.form <- update(loc.form, y ~ .)
# scale.form <- update(scale.form, y ~ .)
# shape.form <- update(shape.form, y ~ .)
# if (use.temp.cov[1])
# temp.form.loc <- update(temp.form.loc, y ~ . + 0)
# if (use.temp.cov[2])
# temp.form.scale <- update(temp.form.scale, y ~ . + 0)
# if (use.temp.cov[3])
# temp.form.shape <- update(temp.form.shape, y ~ . + 0)
# loc.model <- modeldef(covariables, loc.form)
# scale.model <- modeldef(covariables, scale.form)
# shape.model <- modeldef(covariables, shape.form)
# loc.dsgn.mat <- loc.model$dsgn.mat
# scale.dsgn.mat <- scale.model$dsgn.mat
# shape.dsgn.mat <- shape.model$dsgn.mat
# loc.pen.mat <- loc.model$pen.mat
# scale.pen.mat <- scale.model$pen.mat
# shape.pen.mat <- shape.model$pen.mat
# loc.penalty <- loc.model$penalty.tot
# scale.penalty <- scale.model$penalty.tot
# shape.penalty <- shape.model$penalty.tot
# n.loccoeff <- ncol(loc.dsgn.mat)
# n.scalecoeff <- ncol(scale.dsgn.mat)
# n.shapecoeff <- ncol(shape.dsgn.mat)
# n.pparloc <- loc.model$n.ppar
# n.pparscale <- scale.model$n.ppar
# n.pparshape <- shape.model$n.ppar
# loc.names <- paste("locCoeff", 1:n.loccoeff, sep = "")
# scale.names <- paste("scaleCoeff", 1:n.scalecoeff, sep = "")
# shape.names <- paste("shapeCoeff", 1:n.shapecoeff, sep = "")
# if (use.temp.cov[1]) {
# temp.model.loc <- modeldef(temp.cov, temp.form.loc)
# temp.dsgn.mat.loc <- temp.model.loc$dsgn.mat
# temp.pen.mat.loc <- temp.model.loc$pen.mat
# temp.penalty.loc <- temp.model.loc$penalty.tot
# n.tempcoeff.loc <- ncol(temp.dsgn.mat.loc)
# n.ppartemp.loc <- temp.model.loc$n.ppar
# temp.names.loc <- paste("tempCoeffLoc", 1:n.tempcoeff.loc,
# sep = "")
# }
# else {
# temp.model.loc <- temp.dsgn.mat.loc <- temp.pen.mat.loc <- temp.names.loc <- NULL
# n.tempcoeff.loc <- n.ppartemp.loc <- temp.penalty.loc <- 0
# }
# if (use.temp.cov[2]) {
# temp.model.scale <- modeldef(temp.cov, temp.form.scale)
# temp.dsgn.mat.scale <- temp.model.scale$dsgn.mat
# temp.pen.mat.scale <- temp.model.scale$pen.mat
# temp.penalty.scale <- temp.model.scale$penalty.tot
# n.tempcoeff.scale <- ncol(temp.dsgn.mat.scale)
# n.ppartemp.scale <- temp.model.scale$n.ppar
# temp.names.scale <- paste("tempCoeffScale", 1:n.tempcoeff.scale,
# sep = "")
# }
# else {
# temp.model.scale <- temp.dsgn.mat.scale <- temp.pen.mat.scale <- temp.names.scale <- NULL
# n.tempcoeff.scale <- n.ppartemp.scale <- temp.penalty.scale <- 0
# }
# if (use.temp.cov[3]) {
# temp.model.shape <- modeldef(temp.cov, temp.form.shape)
# temp.dsgn.mat.shape <- temp.model.shape$dsgn.mat
# temp.pen.mat.shape <- temp.model.shape$pen.mat
# temp.penalty.shape <- temp.model.shape$penalty.tot
# n.tempcoeff.shape <- ncol(temp.dsgn.mat.shape)
# n.ppartemp.shape <- temp.model.shape$n.ppar
# temp.names.shape <- paste("tempCoeffShape", 1:n.tempcoeff.shape,
# sep = "")
# }
# else {
# temp.model.shape <- temp.dsgn.mat.shape <- temp.pen.mat.shape <- temp.names.shape <- NULL
# n.tempcoeff.shape <- n.ppartemp.shape <- temp.penalty.shape <- 0
# }
# param <- c(loc.names, scale.names, shape.names, temp.names.loc,
# temp.names.scale, temp.names.shape)
# nllik <- function(x) x
# body(nllik) <- parse(text = paste("-.C(C_spatgevlik, as.double(data), as.double(covariables),\n as.integer(n.site), as.integer(n.obs), as.double(loc.dsgn.mat), as.double(loc.pen.mat),\n as.integer(n.loccoeff), as.integer(n.pparloc), as.double(loc.penalty),\n as.double(scale.dsgn.mat), as.double(scale.pen.mat), as.integer(n.scalecoeff),\n as.integer(n.pparscale), as.double(scale.penalty), as.double(shape.dsgn.mat),\n as.double(shape.pen.mat), as.integer(n.shapecoeff), as.integer(n.pparshape),\n as.double(shape.penalty), as.integer(use.temp.cov), as.double(temp.dsgn.mat.loc),\n as.double(temp.pen.mat.loc), as.integer(n.tempcoeff.loc), as.integer(n.ppartemp.loc),\n as.double(temp.penalty.loc), as.double(temp.dsgn.mat.scale), as.double(temp.pen.mat.scale),\n as.integer(n.tempcoeff.scale), as.integer(n.ppartemp.scale), as.double(temp.penalty.scale),\n as.double(temp.dsgn.mat.shape), as.double(temp.pen.mat.shape), as.integer(n.tempcoeff.shape),\n as.integer(n.ppartemp.shape), as.double(temp.penalty.shape),",
# paste("as.double(c(", paste(loc.names, collapse = ","),
# ")), "), paste("as.double(c(", paste(scale.names,
# collapse = ","), ")), "), paste("as.double(c(", paste(shape.names,
# collapse = ","), ")), "), paste("as.double(c(", paste(temp.names.loc,
# collapse = ","), ")), "), paste("as.double(c(", paste(temp.names.scale,
# collapse = ","), ")), "), paste("as.double(c(", paste(temp.names.shape,
# collapse = ","), ")), "), "dns = double(1), NAOK = TRUE)$dns"))
# form.nllik <- NULL
# for (i in 1:length(param)) form.nllik <- c(form.nllik, alist(a = ))
# names(form.nllik) <- param
# formals(nllik) <- form.nllik
# if (missing(start)) {
# loc <- scale <- shape <- rep(0, n.site)
# for (i in 1:n.site) {
# gev.param <- gevmle(data[, i])
# loc[i] <- gev.param["loc"]
# scale[i] <- gev.param["scale"]
# shape[i] <- gev.param["shape"]
# }
# locCoeff <- loc.model$init.fun(loc)
# scaleCoeff <- scale.model$init.fun(scale)
# shapeCoeff <- shape.model$init.fun(shape)
# locCoeff[is.na(locCoeff)] <- 0
# scaleCoeff[is.na(scaleCoeff)] <- 0
# shapeCoeff[is.na(shapeCoeff)] <- 0
# scales.hat <- scale.model$dsgn.mat %*% scaleCoeff
# if (any(scales.hat <= 0))
# scaleCoeff[1] <- scaleCoeff[1] - 1.001 * min(scales.hat)
# names(locCoeff) <- loc.names
# names(scaleCoeff) <- scale.names
# names(shapeCoeff) <- shape.names
# if (use.temp.cov[1]) {
# tempCoeff.loc <- rep(0, n.tempcoeff.loc)
# names(tempCoeff.loc) <- temp.names.loc
# }
# else tempCoeff.loc <- NULL
# if (use.temp.cov[2]) {
# tempCoeff.scale <- rep(0, n.tempcoeff.scale)
# names(tempCoeff.scale) <- temp.names.scale
# }
# else tempCoeff.scale <- NULL
# if (use.temp.cov[3]) {
# tempCoeff.shape <- rep(0, n.tempcoeff.shape)
# names(tempCoeff.shape) <- temp.names.shape
# }
# else tempCoeff.shape <- NULL
# start <- as.list(c(locCoeff, scaleCoeff, shapeCoeff,
# tempCoeff.loc, tempCoeff.scale, tempCoeff.shape))
# # start <- start[!(param %in% names(list(...)))]
# }
# if (!length(start))
# stop("there are no parameters left to maximize over")
# nm <- names(start)
# l <- length(nm)
# f <- formals(nllik)
# names(f) <- param
# m <- match(nm, param)
# if (any(is.na(m)))
# stop("'start' specifies unknown arguments")
# formals(nllik) <- c(f[m], f[-m])
# nllh <- function(p, ...) nllik(p, ...)
# stop(param)
# if (l > 1)
# body(nllh) <- parse(text = paste("nllik(", paste("p[",
# 1:l, "]", collapse = ", "), ", ...)"))
# fixed.param <- list(...)[names(list(...)) %in% param]
# if (any(!(param %in% c(nm, names(fixed.param)))))
# stop("unspecified parameters")
# start.arg <- c(list(p = unlist(start)), fixed.param)
print(res['fitted.values'])
}
# fitspatgev_test with 3D data
fitspatgev_3D_test <- function (n.obs){
n.site = 2
covariables <- matrix(rnorm(2*n.site, sd = sqrt(.2)), ncol = 2)
colnames(covariables) = c("E", "N")
# Generate the data
data <- rmaxstab(n.obs, covariables, "gauss", cov11 = 100, cov12 = 25, cov22 = 220)
print(data)
loc.form = loc ~ N
scale.form = scale ~ N
shape.form = shape ~ N
# Add the temporal covariates
temp.form.loc = loc ~ T
temp.form.scale = scale ~ T
temp.form.shape = shape ~ T
# temp.form.shape = NULL
temp.cov = matrix(1:n.obs, ncol=1)
colnames(temp.cov) = c("T")
# namedlist = list(locCoeff1=0.0, locCoeff2=1.0, scaleCoeff1=0.1, shapeCoeff1=1.0,
# tempCoeffLoc1=0.0, tempCoeffLoc2=1.0, tempCoeffScale1=0.1, tempCoeffShape1=1.0)
start = list(locCoeff1=0.0, locCoeff2=1.0, scaleCoeff1=0.1, shapeCoeff1=1.0,
tempCoeffLoc1=0.0, tempCoeffLoc2=1.0, tempCoeffScale1=0.1, tempCoeffShape1=1.0)
start = list(locCoeff1=0.0, locCoeff2=1.0, scaleCoeff1=0.1, shapeCoeff1=1.0, scaleCoeff2=0.1, shapeCoeff2=1.0,
tempCoeffLoc1=0.0, tempCoeffScale1=0.1, tempCoeffShape1=0.1)
res = fitspatgev(data=data, covariables=covariables, start=start, loc.form=loc.form, scale.form=scale.form,shape.form=shape.form,
temp.cov=temp.cov, temp.form.loc=temp.form.loc, temp.form.scale=temp.form.scale, temp.form.shape = temp.form.shape)
n.site <- ncol(data)
n.obs <- nrow(data)
if (n.site != nrow(covariables))
stop("'data' and 'covariates' doesn't match")
use.temp.cov <- c(!is.null(temp.form.loc), !is.null(temp.form.scale),
!is.null(temp.form.shape))
if (any(use.temp.cov) && (n.obs != nrow(temp.cov)))
stop("'data' and 'temp.cov' doesn't match")
if (any(use.temp.cov) && is.null(temp.cov))
stop("'temp.cov' must be supplied if at least one temporal formula is given")
loc.form <- update(loc.form, y ~ .)
scale.form <- update(scale.form, y ~ .)
shape.form <- update(shape.form, y ~ .)
print(use.temp.cov)
if (use.temp.cov[1])
temp.form.loc <- update(temp.form.loc, y ~ . + 0)
if (use.temp.cov[2])
temp.form.scale <- update(temp.form.scale, y ~ . + 0)
if (use.temp.cov[3])
temp.form.shape <- update(temp.form.shape, y ~ . + 0)
loc.model <- modeldef(covariables, loc.form)
scale.model <- modeldef(covariables, scale.form)
shape.model <- modeldef(covariables, shape.form)
loc.dsgn.mat <- loc.model$dsgn.mat
scale.dsgn.mat <- scale.model$dsgn.mat
shape.dsgn.mat <- shape.model$dsgn.mat
loc.pen.mat <- loc.model$pen.mat
scale.pen.mat <- scale.model$pen.mat
shape.pen.mat <- shape.model$pen.mat
loc.penalty <- loc.model$penalty.tot
scale.penalty <- scale.model$penalty.tot
shape.penalty <- shape.model$penalty.tot
n.loccoeff <- ncol(loc.dsgn.mat)
n.scalecoeff <- ncol(scale.dsgn.mat)
n.shapecoeff <- ncol(shape.dsgn.mat)
n.pparloc <- loc.model$n.ppar
n.pparscale <- scale.model$n.ppar
n.pparshape <- shape.model$n.ppar
loc.names <- paste("locCoeff", 1:n.loccoeff, sep = "")
scale.names <- paste("scaleCoeff", 1:n.scalecoeff, sep = "")
shape.names <- paste("shapeCoeff", 1:n.shapecoeff, sep = "")
if (use.temp.cov[1]) {
temp.model.loc <- modeldef(temp.cov, temp.form.loc)
temp.dsgn.mat.loc <- temp.model.loc$dsgn.mat
temp.pen.mat.loc <- temp.model.loc$pen.mat
temp.penalty.loc <- temp.model.loc$penalty.tot
n.tempcoeff.loc <- ncol(temp.dsgn.mat.loc)
n.ppartemp.loc <- temp.model.loc$n.ppar
temp.names.loc <- paste("tempCoeffLoc", 1:n.tempcoeff.loc,
sep = "")
}
else {
temp.model.loc <- temp.dsgn.mat.loc <- temp.pen.mat.loc <- temp.names.loc <- NULL
n.tempcoeff.loc <- n.ppartemp.loc <- temp.penalty.loc <- 0
}
if (use.temp.cov[2]) {
temp.model.scale <- modeldef(temp.cov, temp.form.scale)
temp.dsgn.mat.scale <- temp.model.scale$dsgn.mat
temp.pen.mat.scale <- temp.model.scale$pen.mat
temp.penalty.scale <- temp.model.scale$penalty.tot
n.tempcoeff.scale <- ncol(temp.dsgn.mat.scale)
n.ppartemp.scale <- temp.model.scale$n.ppar
temp.names.scale <- paste("tempCoeffScale", 1:n.tempcoeff.scale,
sep = "")
}
else {
temp.model.scale <- temp.dsgn.mat.scale <- temp.pen.mat.scale <- temp.names.scale <- NULL
n.tempcoeff.scale <- n.ppartemp.scale <- temp.penalty.scale <- 0
}
if (use.temp.cov[3]) {
temp.model.shape <- modeldef(temp.cov, temp.form.shape)
temp.dsgn.mat.shape <- temp.model.shape$dsgn.mat
temp.pen.mat.shape <- temp.model.shape$pen.mat
temp.penalty.shape <- temp.model.shape$penalty.tot
n.tempcoeff.shape <- ncol(temp.dsgn.mat.shape)
n.ppartemp.shape <- temp.model.shape$n.ppar
temp.names.shape <- paste("tempCoeffShape", 1:n.tempcoeff.shape,
sep = "")
}
else {
temp.model.shape <- temp.dsgn.mat.shape <- temp.pen.mat.shape <- temp.names.shape <- NULL
n.tempcoeff.shape <- n.ppartemp.shape <- temp.penalty.shape <- 0
}
param <- c(loc.names, scale.names, shape.names, temp.names.loc,
temp.names.scale, temp.names.shape)
print(param)
}
# Boolean for python call
......
extreme_estimator/extreme_models/margin_model/margin_function/linear_margin_function.py
+ 2
− 0
View file @ a4f03d04
......@@ -95,6 +95,8 @@ class LinearMarginFunction(IndependentMarginFunction):
temporal_names = [name for name in self.coordinates.coordinates_temporal_names
if self.coefficient_name_to_dim(self.coordinates)[name] in linear_dims]
temporal_form = self.gev_param_name_to_linear_coef[gev_param_name].temporal_form_dict(temporal_names)
# Specifying a formula '~ 1' creates a bug in fitspatgev of SpatialExtreme R package
assert not any(['1' in formula for formula in temporal_form.values()])
form_dict.update(temporal_form)
return form_dict
......
extreme_estimator/extreme_models/margin_model/param_function/linear_coef.py
+ 33
− 12
View file @ a4f03d04
......@@ -32,7 +32,7 @@ class LinearCoef(object):
def coef_template_str(cls, gev_param_name: str, coefficient_name: str) -> str:
"""
Example of coef that can be specified
-for the spatial covariates: locCoeff1
-for the spatial covariates: locCoeff
-for the temporal covariates: tempCoeffLoc
:param gev_param_name:
:param coefficient_name:
......@@ -44,24 +44,41 @@ class LinearCoef(object):
else:
return 'tempCoeff' + gev_param_name.title() + '{}'
@staticmethod
def has_dependence_in_spatial_coordinates(dim_to_coefficient_name):
return any([coefficient_name in AbstractCoordinates.COORDINATE_SPATIAL_NAMES
for coefficient_name in dim_to_coefficient_name.values()])
@classmethod
def add_intercept_dim(cls, dims):
return [0] + dims
@classmethod
def from_coef_dict(cls, coef_dict: Dict[str, float], gev_param_name: str, linear_dims: List[int],
dim_to_coefficient_name):
dims = [0] + linear_dims
dim_to_coefficient_name: Dict[int, str]):
dims = cls.add_intercept_dim(linear_dims)
dim_to_coef = {}
for j, dim in enumerate(dims, 1):
j = 1
for dim in dims:
coefficient_name = dim_to_coefficient_name[dim]
if coefficient_name == AbstractCoordinates.COORDINATE_T:
j = 1
coef = coef_dict[cls.coef_template_str(gev_param_name, coefficient_name).format(j)]
dim_to_coef[dim] = coef
j += 1
return cls(gev_param_name, dim_to_coef)
def coef_dict(self, linear_dims, dim_to_coefficient_name) -> Dict[str, float]:
dims = [0] + linear_dims
def coef_dict(self, linear_dims, dim_to_coefficient_name: Dict[int, str]) -> Dict[str, float]:
dims = self.add_intercept_dim(linear_dims)
coef_dict = {}
for j, dim in enumerate(dims, 1):
j = 1
for dim in dims:
coefficient_name = dim_to_coefficient_name[dim]
if coefficient_name == AbstractCoordinates.COORDINATE_T:
j = 1
coef = self.dim_to_coef[dim]
coef_dict[self.coef_template_str(self.gev_param_name, coefficient_name).format(j)] = coef
j += 1
return coef_dict
def form_dict(self, names: List[str]) -> Dict[str, str]:
......@@ -71,9 +88,10 @@ class LinearCoef(object):
def spatial_form_dict(self, coordinate_spatial_names: List[str]) -> Dict[str, str]:
"""
Example of formula that could be specified:
loc.form = loc ~ 1
loc.form = loc ~ coord_x
scale.form = scale ~ coord_y
shape.form = shape ~ coord_x+coord_y
shape.form = shape ~ coord_x + coord_y
:return:
"""
assert all([name in AbstractCoordinates.COORDINATE_SPATIAL_NAMES for name in coordinate_spatial_names])
......@@ -82,10 +100,13 @@ class LinearCoef(object):
def temporal_form_dict(self, coordinate_temporal_names: List[str]) -> Dict[str, str]:
"""
Example of formula that could be specified:
temp.loc.form = loc ~ coord_t
temp.scale.form = scale ~ coord_t
temp.shape.form = shape ~ 1
temp.form.loc = loc ~ coord_t
Example of formula that could not be specified
temp.loc.form = shape ~ 1
:return:
"""
assert all([name in [AbstractCoordinates.COORDINATE_T] for name in coordinate_temporal_names])
return {'temp.' + k: v for k, v in self.form_dict(coordinate_temporal_names).items()}
k, v = self.form_dict(coordinate_temporal_names).popitem()
k = 'temp.form.' + k.split('.')[0]
v = 'NULL' if '1' in v else v
return {k: v}
extreme_estimator/extreme_models/margin_model/smooth_margin_model.py
+ 17
− 5
View file @ a4f03d04
......@@ -58,13 +58,25 @@ class LinearMarginModel(AbstractMarginModel):
params[(gev_param_name, dim)] = coef
return cls(coordinates, params_sample=params, params_start_fit=params)
def fitmargin_from_maxima_gev(self, maxima_gev: np.ndarray,
df_coordinates: pd.DataFrame) -> Dict[str, float]:
def fitmargin_from_maxima_gev(self, maxima_gev: np.ndarray, df_coordinates_spatial: pd.DataFrame,
df_coordinates_temporal: pd.DataFrame) -> Dict[str, float]:
# The reshaping on the line below is only valid if we have a single observation per spatio-temporal point
if maxima_gev.shape[1] == 1:
maxima_gev = maxima_gev.reshape([len(df_coordinates_temporal), len(df_coordinates_spatial)])
data = np.transpose(maxima_gev)
covariables = get_coord(df_coordinates)
fit_params = get_margin_formula(self.margin_function_start_fit.form_dict)
fit_params['start'] = r.list(**self.margin_function_start_fit.coef_dict)
res = safe_run_r_estimator(function=r.fitspatgev, use_start=self.use_start_value, data=data, covariables=covariables, **fit_params)
# Covariables
covariables = get_coord(df_coordinates=df_coordinates_spatial)
fit_params['temp.cov'] = get_coord(df_coordinates=df_coordinates_temporal)
# Start parameters
coef_dict = self.margin_function_start_fit.coef_dict
fit_params['start'] = r.list(**coef_dict)
res = safe_run_r_estimator(function=r.fitspatgev, use_start=self.use_start_value, data=data,
covariables=covariables, **fit_params)
return retrieve_fitted_values(res)
......
extreme_estimator/extreme_models/utils.py
+ 5
− 1
View file @ a4f03d04
......@@ -16,7 +16,11 @@ r = ro.R()
numpy2ri.activate()
pandas2ri.activate()
r.library('SpatialExtremes')
# todo: R is not reloading all the time, the SpatialExtremes, so it's quite hard to debug or print in the code...
# Notice: R is not reloading all the time, the SpatialExtremes, so it's quite hard to debug or print in the code...
# the best solution for debugging is to copy/paste the code module into a file that belongs to me, and then
# I can put print & stop in the code, and I can understand where are the problems
def set_seed_r(seed=42):
r("set.seed({})".format(seed))
......
spatio_temporal_dataset/coordinates/abstract_coordinates.py
+ 16
− 0
View file @ a4f03d04
......@@ -148,6 +148,8 @@ class AbstractCoordinates(object):
def nb_coordinates(self) -> int:
return len(self.coordinates_names)
# Spatial attributes
@property
def coordinates_spatial_names(self) -> List[str]:
return [name for name in self.COORDINATE_SPATIAL_NAMES if name in self.df_all_coordinates.columns]
......@@ -156,6 +158,14 @@ class AbstractCoordinates(object):
def nb_coordinates_spatial(self) -> int:
return len(self.coordinates_spatial_names)
def df_spatial_coordinates(self, split: Split = Split.all) -> pd.DataFrame:
if self.nb_coordinates_spatial == 0:
return pd.DataFrame()
else:
return self.df_coordinates(split).loc[:, self.coordinates_spatial_names].drop_duplicates()
# Temporal attributes
@property
def coordinates_temporal_names(self) -> List[str]:
return [self.COORDINATE_T] if self.COORDINATE_T in self.df_all_coordinates else []
......@@ -164,6 +174,12 @@ class AbstractCoordinates(object):
def nb_coordinates_temporal(self) -> int:
return len(self.coordinates_temporal_names)
def df_temporal_coordinates(self, split: Split = Split.all) -> pd.DataFrame:
if self.nb_coordinates_temporal == 0:
return pd.DataFrame()
else:
return self.df_coordinates(split).loc[:, self.coordinates_temporal_names].drop_duplicates()
# Visualization
@property
......
test/test_extreme_estimator/test_estimator/test_margin_estimators.py
+ 15
− 6
View file @ a4f03d04
......@@ -2,19 +2,25 @@ import unittest
from extreme_estimator.estimator.margin_estimator.abstract_margin_estimator import SmoothMarginEstimator
from spatio_temporal_dataset.dataset.simulation_dataset import MarginDataset
from test.test_utils import load_smooth_margin_models, load_test_1D_and_2D_spatial_coordinates
from test.test_utils import load_smooth_margin_models, load_test_1D_and_2D_spatial_coordinates, \
load_test_spatiotemporal_coordinates
class TestSmoothMarginEstimator(unittest.TestCase):
DISPLAY = False
nb_points = 2
nb_obs = 2
def setUp(self):
super().setUp()
def test_smooth_margin_estimator_spatial(self):
self.nb_points = 2
self.nb_obs = 2
self.coordinates = load_test_1D_and_2D_spatial_coordinates(nb_points=self.nb_points)
def test_smooth_margin_estimator(self):
def test_smooth_margin_estimator_spatio_temporal(self):
self.nb_points = 2
self.nb_steps = 2
self.nb_obs = 1
self.coordinates = load_test_spatiotemporal_coordinates(nb_steps=self.nb_steps, nb_points=self.nb_points)
def tearDown(self) -> None:
for coordinates in self.coordinates:
smooth_margin_models = load_smooth_margin_models(coordinates=coordinates)
for margin_model in smooth_margin_models[1:]:
......@@ -33,3 +39,6 @@ class TestSmoothMarginEstimator(unittest.TestCase):
if __name__ == '__main__':
unittest.main()
# t = TestSmoothMarginEstimator()
# t.test_smooth_margin_estimator_spatio_temporal()
# t.tearDown()
Supports Markdown
0% or .
You are about to add 0 people to the discussion. Proceed with caution.
Finish editing this message first!
Please register or to comment