From 2c4cd9698b4b993168071136de1ff34f6841866a Mon Sep 17 00:00:00 2001
From: lukas leufen <l.leufen@fz-juelich.de>
Date: Thu, 19 Mar 2020 08:09:44 +0100
Subject: [PATCH] removed slowest implementation
---
src/run_modules/post_processing.py | 42 ------------------------------
1 file changed, 42 deletions(-)
diff --git a/src/run_modules/post_processing.py b/src/run_modules/post_processing.py
index 0073f742..80d12fc4 100644
--- a/src/run_modules/post_processing.py
+++ b/src/run_modules/post_processing.py
@@ -60,9 +60,6 @@ class PostProcessing(RunEnvironment):
with TimeTracking(name="split (refac_1): create_boot_straps_refac_2()"):
self.create_boot_straps_refac_2()
self.bootstrap_skill_scores = self.calculate_bootstrap_skill_scores()
- with TimeTracking(name="split (refac): create_boot_straps_refac()"):
- self.create_boot_straps_refac()
- self.bootstrap_skill_scores = self.calculate_bootstrap_skill_scores()
with TimeTracking(name="merged: combined_boot_forecast_and_skill()"):
self.bootstrap_skill_scores = self.combined_boot_forecast_and_skill()
@@ -73,45 +70,6 @@ class PostProcessing(RunEnvironment):
# plotting
# self.plot()
- def create_boot_straps_refac(self):
- # forecast
- with TimeTracking(name="boot predictions"):
- bootstrap_path = self.data_store.get("bootstrap_path", "general")
- forecast_path = self.data_store.get("forecast_path", "general")
- window_lead_time = self.data_store.get("window_lead_time", "general")
- number_of_bootstraps = self.data_store.get("number_of_bootstraps", "general.postprocessing")
- bootstraps = BootStraps(self.test_data, bootstrap_path, number_of_bootstraps)
- for station in bootstraps.stations:
- with TimeTracking(name=station):
- logging.info(station)
- hist, label, station_bootstrap, length = bootstraps.get_generator_station_wise(station)
-
- # make bootstrap predictions
- bootstrap_predictions = self.model.predict_generator(generator=station_bootstrap(),
- steps=length,
- use_multiprocessing=True)
- if isinstance(bootstrap_predictions, list):
- bootstrap_predictions = bootstrap_predictions[-1]
- # get bootstrap prediction meta data
- bootstrap_meta = np.array(bootstraps.get_bootstrap_meta_station_wise(station))
- # save bootstrap predictions separately for each station and variable combination
- variables = np.unique(bootstrap_meta[:, 0])
- coords = None
- for boot in variables:
- # store each variable - station - combination
- ind = np.all(bootstrap_meta == [boot, station], axis=1)
- length = sum(ind)
- sel = bootstrap_predictions[ind].reshape((length, window_lead_time, 1))
- coords = (range(length), range(1, window_lead_time + 1))
- tmp = xr.DataArray(sel, coords=(*coords, [boot]), dims=["index", "ahead", "type"])
- file_name = os.path.join(forecast_path, f"bootstraps_{boot}_{station}.nc")
- tmp.to_netcdf(file_name)
- # store also true labels for each station
- labels = bootstraps.get_labels(station).reshape((length, window_lead_time, 1))
- file_name = os.path.join(forecast_path, f"bootstraps_labels_{station}.nc")
- labels = xr.DataArray(labels, coords=(*coords, ["obs"]), dims=["index", "ahead", "type"])
- labels.to_netcdf(file_name)
-
def create_boot_straps_refac_2(self):
# forecast
with TimeTracking(name="boot predictions"):
--
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