From 0f53dffaa0b7c8eb08fb7040b1375423732cb883 Mon Sep 17 00:00:00 2001
From: Felix Kleinert <f.kleinert@fz-juelich.de>
Date: Tue, 23 Mar 2021 17:07:17 +0100
Subject: [PATCH] update transform methods to proplery work when external
transformation parameetrs are preovided
---
mlair/data_handler/data_handler_single_station.py | 12 +++++++++++-
mlair/data_handler/default_data_handler.py | 12 ++++++++----
2 files changed, 19 insertions(+), 5 deletions(-)
diff --git a/mlair/data_handler/data_handler_single_station.py b/mlair/data_handler/data_handler_single_station.py
index 0c83e625..e9db27a9 100644
--- a/mlair/data_handler/data_handler_single_station.py
+++ b/mlair/data_handler/data_handler_single_station.py
@@ -195,7 +195,17 @@ class DataHandlerSingleStation(AbstractDataHandler):
else:
raise NotImplementedError
- def f_apply(data, method, mean=None, std=None, min=None, max=None):
+ def f_apply(data, method, **kwargs):
+ for k, v in kwargs.items():
+ if not (isinstance(v, xr.DataArray) or v is None):
+ _, opts = statistics.min_max(data, dim)
+ helper = xr.ones_like(opts['min'])
+ kwargs[k] = helper * v
+ mean = kwargs.pop('mean', None)
+ std = kwargs.pop('std', None)
+ min = kwargs.pop('min', None)
+ max = kwargs.pop('max', None)
+
if method == "standardise":
return statistics.standardise_apply(data, mean, std), {"mean": mean, "std": std, "method": method}
elif method == "centre":
diff --git a/mlair/data_handler/default_data_handler.py b/mlair/data_handler/default_data_handler.py
index 5eb6fd02..2eceff32 100644
--- a/mlair/data_handler/default_data_handler.py
+++ b/mlair/data_handler/default_data_handler.py
@@ -241,6 +241,8 @@ class DefaultDataHandler(AbstractDataHandler):
* standardise (default, if method is not given)
* centre
+ * min_max
+ * log
### mean and std estimation
@@ -256,14 +258,16 @@ class DefaultDataHandler(AbstractDataHandler):
If mean and std are not None, the default data handler expects this parameters to match the data and applies
this values to the data. Make sure that all dimensions and/or coordinates are in agreement.
+
+ ### min and max given
+ If min and max are not None, the default data handler expects this parameters to match the data and applies
+ this values to the data. Make sure that all dimensions and/or coordinates are in agreement.
"""
sp_keys = {k: copy.deepcopy(kwargs[k]) for k in cls._requirements if k in kwargs}
- transformation_dict = sp_keys.get("transformation", None)
- if transformation_dict is None:
+ if "transformation" not in sp_keys.keys():
return
- if isinstance(transformation_dict, dict): # tuple for (input, target) transformation
- transformation_dict = copy.deepcopy(transformation_dict), copy.deepcopy(transformation_dict)
+ transformation_dict = ({}, {})
def _inner():
"""Inner method that is performed in both serial and parallel approach."""
--
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