🐛 go back old config indentation (and model configuration)

- rerun in codespace for inspection

project/config/alzheimer_study/config.yaml

@@ -6,74 +6,70 @@ fn_rawfile_metadata: https://raw.githubusercontent.com/RasmussenLab/njab/HEAD/do
 cuda: False # use GPU?
 file_format: csv # intermediate file formats
 split_data: # for 01_01_split_data.ipynb -> check parameters
-      FN_INTENSITIES: https://raw.githubusercontent.com/RasmussenLab/njab/HEAD/docs/tutorial/data/alzheimer/proteome.csv
-      sample_completeness: 0.5
-      feat_prevalence: 0.25
-      column_names:
-            - protein groups
-      index_col: 0
-      meta_cat_col: _collection site
-      meta_date_col: null # null if no date column, translated to None in Python
-      frac_mnar: 0.25
-      frac_non_train: 0.1
+    FN_INTENSITIES: https://raw.githubusercontent.com/RasmussenLab/njab/HEAD/docs/tutorial/data/alzheimer/proteome.csv
+    sample_completeness: 0.5
+    feat_prevalence: 0.25
+    column_names:
+        - protein groups
+    index_col: 0
+    meta_cat_col: _collection site
+    meta_date_col: null  # null if no date column, translated to None in Python
+    frac_mnar: 0.25
+    frac_non_train: 0.1
 models:
-      - Median: # name used for model with this configuration
-              model: Median # model used
-      - CF:
-              model: CF # notebook: 01_1_train_{model}.ipynb will be 01_1_train_CF.ipynb
-              latent_dim: 50
-              batch_size: 1024
-              epochs_max: 100
-              sample_idx_position: 0
-              cuda: False
-              save_pred_real_na: True
-      - DAE:
-              model: DAE
-              latent_dim: 10
-              batch_size: 64
-              epochs_max: 300
-              hidden_layers: "64"
-              sample_idx_position: 0
-              cuda: False
-              save_pred_real_na: True
-      - VAE:
-              model: VAE
-              latent_dim: 10
-              batch_size: 64
-              epochs_max: 300
-              hidden_layers: "64"
-              sample_idx_position: 0
-              cuda: False
-              save_pred_real_na: True
-      - KNN:
-              model: KNN
-              neighbors: 3
-              file_format: csv
-      - KNN5:
-              model: KNN
-              neighbors: 5
-              file_format: csv
+    - Median: # name used for model with this configuration
+          model: Median # model used
+    - CF:
+          model: CF # notebook: 01_1_train_{model}.ipynb will be 01_1_train_CF.ipynb
+          latent_dim: 50
+          batch_size: 1024
+          epochs_max: 100
+          sample_idx_position: 0
+          cuda: False
+          save_pred_real_na: True
+    - DAE:
+          model: DAE
+          latent_dim: 10
+          batch_size: 64
+          epochs_max: 300
+          hidden_layers: "64"
+          sample_idx_position: 0
+          cuda: False
+          save_pred_real_na: True
+    - VAE:
+          model: VAE
+          latent_dim: 10
+          batch_size: 64
+          epochs_max: 300
+          hidden_layers: "64"
+          sample_idx_position: 0
+          cuda: False
+          save_pred_real_na: True
+    - KNN:
+          model: KNN
+          neighbors: 3
+          file_format: csv
 NAGuideR_methods:
-      - BPCA
-      - COLMEDIAN
-      - IMPSEQ
-      - IMPSEQROB
-      - IRM
-      - KNN_IMPUTE
-      - LLS
-      # - MICE-CART > 1h20min on GitHub small runner
-      # - MICE-NORM ~ 1h on GitHub small runner
-      - MINDET
-      - MINIMUM
-      - MINPROB
-      - MLE
-      - MSIMPUTE
-      - MSIMPUTE_MNAR
-      - PI
-      - QRILC
-      - RF
-      - ROWMEDIAN
-      # - SEQKNN # Error in x[od, ismiss, drop = FALSE]: subscript out of bounds
-      - SVDMETHOD
-      - TRKNN
-      - ZERO
+    - BPCA
+    - COLMEDIAN
+    - IMPSEQ
+    - IMPSEQROB
+    - IRM
+    - KNN_IMPUTE
+    - LLS
+    # - MICE-CART > 1h20min on GitHub small runner
+    # - MICE-NORM ~ 1h on GitHub small runner
+    - MINDET
+    - MINIMUM
+    - MINPROB
+    - MLE
+    - MSIMPUTE
+    - MSIMPUTE_MNAR
+    - PI
+    - QRILC
+    - RF
+    - ROWMEDIAN
+    # - SEQKNN # Error in x[od, ismiss, drop = FALSE]: subscript out of bounds
+    - SVDMETHOD
+    - TRKNN
+    - ZERO