diff --git a/mlair/run_modules/post_processing.py b/mlair/run_modules/post_processing.py
index ff74da37ed9706d9674bf773249c84e4e1e7424b..a633dec1d65244aacb531d7dc1f94c8e2931d29c 100644
--- a/mlair/run_modules/post_processing.py
+++ b/mlair/run_modules/post_processing.py
@@ -21,7 +21,6 @@ from mlair.model_modules.linear_model import OrdinaryLeastSquaredModel
from mlair.model_modules import AbstractModelClass
from mlair.plotting.postprocessing_plotting import PlotMonthlySummary, PlotClimatologicalSkillScore, \
PlotCompetitiveSkillScore, PlotTimeSeries, PlotBootstrapSkillScore, PlotConditionalQuantiles, PlotSeparationOfScales
-from mlair.plotting.preprocessing_plotting import PlotStationMap, PlotAvailability, PlotAvailabilityHistogram
from mlair.run_modules.run_environment import RunEnvironment
@@ -325,23 +324,6 @@ class PostProcessing(RunEnvironment):
except Exception as e:
logging.error(f"Could not create plot PlotConditionalQuantiles due to the following error: {e}")
- try:
- if "PlotStationMap" in plot_list:
- if self.data_store.get("hostname")[:2] in self.data_store.get("hpc_hosts") or self.data_store.get(
- "hostname")[:6] in self.data_store.get("hpc_hosts"):
- logging.warning(
- f"Skip 'PlotStationMap` because running on a hpc node: {self.data_store.get('hostname')}")
- else:
- gens = [(self.train_data, {"marker": 5, "ms": 9}),
- (self.val_data, {"marker": 6, "ms": 9}),
- (self.test_data, {"marker": 4, "ms": 9})]
- PlotStationMap(generators=gens, plot_folder=self.plot_path)
- gens = [(self.train_val_data, {"marker": 8, "ms": 9}),
- (self.test_data, {"marker": 9, "ms": 9})]
- PlotStationMap(generators=gens, plot_folder=self.plot_path, plot_name="station_map_var")
- except Exception as e:
- logging.error(f"Could not create plot PlotStationMap due to the following error: {e}")
-
try:
if "PlotMonthlySummary" in plot_list:
PlotMonthlySummary(self.test_data.keys(), path, r"forecasts_%s_test.nc", self.target_var,
@@ -372,22 +354,6 @@ class PostProcessing(RunEnvironment):
except Exception as e:
logging.error(f"Could not create plot PlotTimeSeries due to the following error: {e}")
- try:
- if "PlotAvailability" in plot_list:
- avail_data = {"train": self.train_data, "val": self.val_data, "test": self.test_data}
- PlotAvailability(avail_data, plot_folder=self.plot_path, time_dimension=time_dim,
- window_dimension=window_dim)
- except Exception as e:
- logging.error(f"Could not create plot PlotAvailability due to the following error: {e}")
-
- try:
- if "PlotAvailabilityHistogram" in plot_list:
- avail_data = {"train": self.train_data, "val": self.val_data, "test": self.test_data}
- PlotAvailabilityHistogram(avail_data, plot_folder=self.plot_path, station_dim=iter_dim,
- history_dim=window_dim)
- except Exception as e:
- logging.error(f"Could not create plot PlotAvailabilityHistogram due to the following error: {e}")
-
def calculate_test_score(self):
"""Evaluate test score of model and save locally."""
diff --git a/mlair/run_modules/pre_processing.py b/mlair/run_modules/pre_processing.py
index f59a4e89ced738c9198619ec0d117df2edf3ee93..3c2670aadf06c99b4d2491a9d5cc885dd605421b 100644
--- a/mlair/run_modules/pre_processing.py
+++ b/mlair/run_modules/pre_processing.py
@@ -18,6 +18,7 @@ from mlair.helpers import TimeTracking, to_list, tables
from mlair.configuration import path_config
from mlair.helpers.join import EmptyQueryResult
from mlair.run_modules.run_environment import RunEnvironment
+from mlair.plotting.preprocessing_plotting import PlotStationMap, PlotAvailability, PlotAvailabilityHistogram
class PreProcessing(RunEnvironment):
@@ -67,6 +68,7 @@ class PreProcessing(RunEnvironment):
self.split_train_val_test()
self.report_pre_processing()
self.prepare_competitors()
+ self.plot()
def report_pre_processing(self):
"""Log some metrics on data and create latex report."""
@@ -327,6 +329,54 @@ class PreProcessing(RunEnvironment):
else:
logging.info("No preparation required because no competitor was provided to the workflow.")
+ def plot(self):
+ logging.info("Run plotting routines...")
+
+ plot_list = self.data_store.get("plot_list", "postprocessing")
+ time_dim = self.data_store.get("time_dim")
+ window_dim = self.data_store.get("window_dim")
+ target_dim = self.data_store.get("target_dim")
+ iter_dim = self.data_store.get("iter_dim")
+
+ train_data = self.data_store.get("data_collection", "train")
+ val_data = self.data_store.get("data_collection", "val")
+ test_data = self.data_store.get("data_collection", "test")
+ train_val_data = self.data_store.get("data_collection", "train_val")
+ plot_path: str = self.data_store.get("plot_path")
+
+ try:
+ if "PlotStationMap" in plot_list:
+ if self.data_store.get("hostname")[:2] in self.data_store.get("hpc_hosts") or self.data_store.get(
+ "hostname")[:6] in self.data_store.get("hpc_hosts"):
+ logging.warning(
+ f"Skip 'PlotStationMap` because running on a hpc node: {self.data_store.get('hostname')}")
+ else:
+ gens = [(train_data, {"marker": 5, "ms": 9}),
+ (val_data, {"marker": 6, "ms": 9}),
+ (test_data, {"marker": 4, "ms": 9})]
+ PlotStationMap(generators=gens, plot_folder=plot_path)
+ gens = [(train_val_data, {"marker": 8, "ms": 9}),
+ (test_data, {"marker": 9, "ms": 9})]
+ PlotStationMap(generators=gens, plot_folder=plot_path, plot_name="station_map_var")
+ except Exception as e:
+ logging.error(f"Could not create plot PlotStationMap due to the following error: {e}")
+
+ try:
+ if "PlotAvailability" in plot_list:
+ avail_data = {"train": train_data, "val": val_data, "test": test_data}
+ PlotAvailability(avail_data, plot_folder=plot_path, time_dimension=time_dim,
+ window_dimension=window_dim)
+ except Exception as e:
+ logging.error(f"Could not create plot PlotAvailability due to the following error: {e}")
+
+ try:
+ if "PlotAvailabilityHistogram" in plot_list:
+ avail_data = {"train": train_data, "val": val_data, "test": test_data}
+ PlotAvailabilityHistogram(avail_data, plot_folder=plot_path, station_dim=iter_dim,
+ history_dim=window_dim)
+ except Exception as e:
+ logging.error(f"Could not create plot PlotAvailabilityHistogram due to the following error: {e}")
+
def f_proc(data_handler, station, name_affix, store, **kwargs):
"""