From 4fabc891b9ca8a907372b20e9b144a1358e9bde2 Mon Sep 17 00:00:00 2001
From: leufen1 <l.leufen@fz-juelich.de>
Date: Wed, 20 Jan 2021 15:53:51 +0100
Subject: [PATCH] skill score statistics require now more explicitly named
indicators for forecast, observation and reference to prevent error arising
from auto-filling
---
mlair/helpers/statistics.py | 10 ++++++----
1 file changed, 6 insertions(+), 4 deletions(-)
diff --git a/mlair/helpers/statistics.py b/mlair/helpers/statistics.py
index 0251f3ea..546a4636 100644
--- a/mlair/helpers/statistics.py
+++ b/mlair/helpers/statistics.py
@@ -209,7 +209,7 @@ class SkillScores:
def skill_scores(self, window_lead_time: int) -> pd.DataFrame:
"""
- Calculate skill scores for all combinations of CNN, persistence and OLS.
+ Calculate skill scores for all combinations of model names.
:param window_lead_time: length of forecast steps
@@ -228,7 +228,7 @@ class SkillScores:
return skill_score
def climatological_skill_scores(self, external_data: Data, window_lead_time: int,
- forecast_name: str = "cnn") -> xr.DataArray:
+ forecast_name: str) -> xr.DataArray:
"""
Calculate climatological skill scores according to Murphy (1988).
@@ -273,8 +273,8 @@ class SkillScores:
kwargs = {"external_data": external_data} if external_data is not None else {}
return self.__getattribute__(f"skill_score_mu_case_{mu_type}")(data, observation_name, forecast_name, **kwargs)
- @staticmethod
- def general_skill_score(data: Data, observation_name: str, forecast_name: str, reference_name: str) -> np.ndarray:
+ def general_skill_score(self, data: Data, forecast_name: str, reference_name: str,
+ observation_name: str = None) -> np.ndarray:
r"""
Calculate general skill score based on mean squared error.
@@ -285,6 +285,8 @@ class SkillScores:
:return: skill score of forecast
"""
+ if observation_name is None:
+ observation_name = self.observation_name
data = data.dropna("index")
observation = data.sel(type=observation_name)
forecast = data.sel(type=forecast_name)
--
GitLab