modfied examples

examples/plot_scale/boadkh/README.md

@@ -25,14 +25,14 @@ job scripts contains `_gpu` computations run on GPU.
 The following crop combinations are rotated:
 - Winter wheat and clover
 - Winter wheat and corn
-- Winter wheat and winter rape
-- Winter wheat, clover and corn
-- Winter wheat, sugar beet and corn
-- Winter wheat, winter grain pea and winter rape
 - Summer wheat and winter wheat
 - Summer wheat, clover and winter wheat
-- Summer wheat, winter wheat and corn
+- Winter wheat, clover and corn
 - Summer wheat, winter wheat and winter rape
+- Winter wheat and winter rape
+- Summer wheat, winter wheat and corn
+- Winter wheat, winter grain pea and winter rape
+- Winter wheat, sugar beet and corn
 
 The name of the folder contains the considered crop combinations. Each folder contains a file that describes the crop rotation in `crop_rotation.csv`.
 

examples/plot_scale/boadkh/svat_crop/submit_jobs_muellheim.sh

@@ -0,0 +1,9 @@
+#!/bin/bash
+
+cd ~/roger/examples/plot_scale/boadkh/svat_crop
+
+FILES="$PWD/svat_crop_muellheim_*_slurm.sh"
+for f in $FILES
+do
+  sbatch --partition=single $f
+done

examples/plot_scale/boadkh/svat_crop/svat_crop.py

@@ -8,7 +8,7 @@
 from roger.cli.roger_run_base import roger_base_cli
 
 @click.option("--location", type=click.Choice(["singen", "azenweiler", "unterraderach", "muellheim", "freiburg", "ihringen", "altheim", "kirchen", "maehringen", "heidelsheim", "elsenz", "zaberfeld", "kupferzell", "stachenhausen", "oehringen"]
-), default="freiburg")
+), default="ihringen")
 @click.option("--crop-rotation-scenario", type=click.Choice(["summer-wheat_clover_winter-wheat", "summer-wheat_winter-wheat", 
                                                              "summer-wheat_winter-wheat_corn", 
                                                              "summer-wheat_winter-wheat_winter-rape", "winter-wheat_clover",

examples/plot_scale/reckenholz/svat_crop_monte_carlo/dotty_plots.py

@@ -47,11 +47,11 @@ def main(tmp_dir):
                 ax[i, j].set_xlabel("")
                 ax[i, j].set_ylabel("")
                 if metric_var in ["KGE_q_ss"]:
-                    ax[i, j].set_ylim((0.0, 0.3))
+                    ax[i, j].set_ylim((0.1, 0.5))
                 elif metric_var in ["r_theta"]:
                     ax[i, j].set_ylim((0.6, 0.9))
                 elif metric_var in ["E_multi"]:
-                    ax[i, j].set_ylim((0.5, 0.8))
+                    ax[i, j].set_ylim((0.4, 0.6))
 
                 # best parameter set for individual evaluation metric at specific storage conditions
                 df_params_metrics_sc1 = df_params_metrics.copy()
@@ -89,11 +89,11 @@ def main(tmp_dir):
                 ax[i, j].set_xlabel("")
                 ax[i, j].set_ylabel("")
                 if metric_var in ["KGE_q_ss"]:
-                    ax[i, j].set_ylim((0.0, 0.3))
+                    ax[i, j].set_ylim((0.1, 0.5))
                 elif metric_var in ["r_theta"]:
-                    ax[i, j].set_ylim((0.6, 0.9))
-                elif metric_var in ["E_multi"]:
                     ax[i, j].set_ylim((0.5, 0.8))
+                elif metric_var in ["E_multi"]:
+                    ax[i, j].set_ylim((0.4, 0.6))
 
                 # best parameter set for individual evaluation metric at specific storage conditions
                 df_params_metrics_sc1 = df_params_metrics.copy()

examples/plot_scale/reckenholz/svat_monte_carlo/dotty_plots.py

@@ -47,11 +47,11 @@ def main(tmp_dir):
                 ax[i, j].set_xlabel("")
                 ax[i, j].set_ylabel("")
                 if metric_var in ["KGE_q_ss"]:
-                    ax[i, j].set_ylim((0.0, 0.3))
+                    ax[i, j].set_ylim((0.1, 0.5))
                 elif metric_var in ["r_theta"]:
-                    ax[i, j].set_ylim((0.5, 1.0))
-                elif metric_var in ["E_multi"]:
                     ax[i, j].set_ylim((0.5, 0.8))
+                elif metric_var in ["E_multi"]:
+                    ax[i, j].set_ylim((0.4, 0.6))
 
                 # best parameter set for individual evaluation metric at specific storage conditions
                 df_params_metrics_sc1 = df_params_metrics.copy()
@@ -89,11 +89,11 @@ def main(tmp_dir):
                 ax[i, j].set_xlabel("")
                 ax[i, j].set_ylabel("")
                 if metric_var in ["KGE_q_ss"]:
-                    ax[i, j].set_ylim((0.0, 0.3))
+                    ax[i, j].set_ylim((0.1, 0.5))
                 elif metric_var in ["r_theta"]:
-                    ax[i, j].set_ylim((0.5, 1.0))
-                elif metric_var in ["E_multi"]:
                     ax[i, j].set_ylim((0.5, 0.8))
+                elif metric_var in ["E_multi"]:
+                    ax[i, j].set_ylim((0.4, 0.6))
 
                 # best parameter set for individual evaluation metric at specific storage conditions
                 df_params_metrics_sc1 = df_params_metrics.copy()