🎨 format yaml files (some had no last blank line)

tutorial/config/data/random_continuous.yaml

@@ -5,15 +5,16 @@ defaults:
 
 # FEEL FREE TO EDIT BELOW
 
-raw_data_path: data/              # where raw data is stored
-interim_data_path: interim_data_cont/  # where intermediate files will be stored
-results_path: results_cont/     # where result files will be placed
+raw_data_path: data/ # where raw data is stored
+interim_data_path: interim_data_cont/ # where intermediate files will be stored
+results_path: results_cont/ # where result files will be placed
 
-sample_names: random.continuous.ids  # names/IDs of each sample, must appear in the
-                                # other datasets
+sample_names:
+  random.continuous.ids # names/IDs of each sample, must appear in the
+  # other datasets
 
-categorical_inputs: []  # no categorical inputs
+categorical_inputs: [] # no categorical inputs
 
-continuous_inputs:   # a list of continuous datasets
+continuous_inputs: # a list of continuous datasets
   - name: random.continuous.proteomics
-  - name: random.continuous.metagenomics
+  - name: random.continuous.metagenomics

tutorial/config/data/random_small.yaml

@@ -5,16 +5,17 @@ defaults:
 
 # FEEL FREE TO EDIT BELOW
 
-raw_data_path: data/              # where raw data is stored
-interim_data_path: interim_data/  # where intermediate files will be stored
-results_path: results/            # where result files will be placed
+raw_data_path: data/ # where raw data is stored
+interim_data_path: interim_data/ # where intermediate files will be stored
+results_path: results/ # where result files will be placed
 
-sample_names: random.small.ids    # names/IDs of each sample, must appear in
-                                  # the other datasets
+sample_names:
+  random.small.ids # names/IDs of each sample, must appear in
+  # the other datasets
 
-categorical_inputs:               # a list of categorical datasets
+categorical_inputs: # a list of categorical datasets
   - name: random.small.drugs
 
-continuous_inputs:                # a list of continuous datasets
+continuous_inputs: # a list of continuous datasets
   - name: random.small.proteomics
   - name: random.small.metagenomics

tutorial/config/experiment/random_continuous.yaml

@@ -2,4 +2,4 @@
 
 defaults:
   - override /data: random_continuous
-  - override /task: random_continuous__id_assoc_ttest
+  - override /task: random_continuous__id_assoc_ttest

tutorial/config/experiment/random_continuous__tune.yaml

@@ -18,5 +18,5 @@ hydra:
     params:
       task.batch_size: 10 #10, 20
       task.model.num_hidden: "[250]"
-      task.model.num_latent:  100, 200, 220 
-      task.training_loop.num_epochs: 200
+      task.model.num_latent: 100, 200, 220
+      task.training_loop.num_epochs: 200

tutorial/config/task/random_continuous__id_assoc_bayes.yaml

@@ -1,21 +1,20 @@
-
 defaults:
   - identify_associations_bayes
 
 batch_size: 10
 
 num_refits: 10
 
-target_dataset: random.continuous.proteomics 
+target_dataset: random.continuous.proteomics
 target_value: plus_std
 save_refits: True
 
 model:
   num_hidden:
-    - 100 
-  num_latent: 50 
+    - 100
+  num_latent: 50
   beta: .0001
-  dropout: .1 
+  dropout: .1
 
 training_loop:
   lr: 1e-4

tutorial/config/task/random_continuous__id_assoc_ks.yaml

@@ -1,13 +1,12 @@
-
 defaults:
   - identify_associations_ks_schema
 
 batch_size: 10
 
-num_refits: 10 
+num_refits: 10
 sig_threshold: 0.05
 
-target_dataset: random.continuous.proteomics 
+target_dataset: random.continuous.proteomics
 target_value: plus_std
 save_refits: True
 
@@ -16,7 +15,7 @@ model:
   continuous_weights: ${weights:${data.continuous_inputs}}
   num_hidden:
     - 100
-  num_latent: 50 
+  num_latent: 50
   beta: 0.1
   dropout: 0.1
   cuda: false
@@ -38,4 +37,4 @@ training_loop:
 perturbed_feature_names:
   - proteomics_3
 target_feature_names:
-  - metagenomics_9
+  - metagenomics_9

tutorial/config/task/random_continuous__id_assoc_ttest.yaml

@@ -3,9 +3,9 @@ defaults:
 
 batch_size: 10
 
-num_refits: 10 
+num_refits: 10
 
-target_dataset: random.continuous.proteomics 
+target_dataset: random.continuous.proteomics
 target_value: plus_std
 save_refits: True
 
@@ -17,8 +17,8 @@ num_latent:
 
 model:
   num_hidden:
-    - 100 
+    - 100
 
 training_loop:
   lr: 1e-4
-  num_epochs: 200 
+  num_epochs: 200

tutorial/config/task/random_continuous__latent.yaml

@@ -13,4 +13,4 @@ model:
 
 training_loop:
   lr: 1e-4
-  num_epochs: 200
+  num_epochs: 200

tutorial/config/task/random_small__id_assoc_bayes.yaml

@@ -1,4 +1,3 @@
-
 defaults:
   - identify_associations_bayes
 

tutorial/config/task/random_small__id_assoc_ttest.yaml

@@ -1,19 +1,18 @@
-
 defaults:
   - identify_associations_ttest
 
-batch_size: 10  # number of samples per batch in training loop
+batch_size: 10 # number of samples per batch in training loop
 
-num_refits: 5 #10 is the default  # number of times to refit (retrain) model
+num_refits: 5 # 10 is the default  # number of times to refit (retrain) model
 
-target_dataset: random.small.drugs  # dataset to perturb
-target_value: 1                     # value to change to
-save_refits: True                   # whether to save refits to interim folder
+target_dataset: random.small.drugs # dataset to perturb
+target_value: 1 # value to change to
+save_refits: True # whether to save refits to interim folder
 
-model:         # model configuration
-  num_hidden:  # list of units in each hidden layer of the VAE encoder/decoder
+model: # model configuration
+  num_hidden: # list of units in each hidden layer of the VAE encoder/decoder
     - 1000
 
-training_loop:    # training loop configuration
-  lr: 1e-4        # learning rate
-  num_epochs: 40  # 40 is the default # number of epochs
+training_loop: # training loop configuration
+  lr: 1e-4 # learning rate
+  num_epochs: 40 # 40 is the default # number of epochs