Convert the class into a YAML object.

Add an example config file and demonstrate its usage in ex_ml_pipeline.ipynb.

README.md

@@ -27,7 +27,7 @@ To install:
    ipython kernel install --user --name=straw2analysis
    ```
 
-2. Provide an .env file to be used by `python-dotenv` which should be placed in the top folder of the application 
+2. Provide a file called `.env` to be used by `python-dotenv` which should be placed in the top folder of the application 
    and should have the form:
    
    ```

config/environment.yml

@@ -15,6 +15,7 @@ dependencies:
   - psycopg2
   - python-dotenv
   - pytz
+  - pyyaml
   - seaborn
   - scikit-learn
   - sqlalchemy

exploration/ex_ml_pipeline.py

@@ -18,6 +18,7 @@
 import datetime
 import os
 import sys
+import yaml
 
 import seaborn as sns
 from sklearn import linear_model
@@ -156,20 +157,17 @@ lin_reg_proximity.score(
 from machine_learning import pipeline
 
 # %%
-ml_pipeline = pipeline.MachineLearningPipeline(
-    labels_questionnaire="PANAS", data_types="proximity"
-)
+with open('../machine_learning/config/minimal_features.yaml', 'r') as file:
+    sensor_features = yaml.full_load(file)
 
 # %%
-ml_pipeline.get_labels()
-
-# %% tags=[]
-ml_pipeline.get_sensor_data()
+sensor_features.set_sensor_data()
 
 # %%
-ml_pipeline.aggregate_daily()
+sensor_features.get_sensor_data("proximity")
 
 # %%
-ml_pipeline.df_full_data_daily_means
+sensor_features.calculate_features()
 
 # %%
+sensor_features.get_features("proximity", "all")

machine_learning/config/minimal_features.yaml

@@ -0,0 +1,5 @@
+--- !SensorFeatures
+grouping_variable: date_lj
+data_types: [proximity]
+feature_names: all
+participants_usernames: [nokia_0000003]

machine_learning/pipeline.py

@@ -1,6 +1,7 @@
 import datetime
 
 import pandas as pd
+import yaml
 from sklearn.model_selection import cross_val_score
 
 import participants.query_db
@@ -8,7 +9,9 @@ from features import esm, helper, proximity
 from machine_learning import QUESTIONNAIRE_IDS, QUESTIONNAIRE_IDS_RENAME
 
 
-class SensorFeatures:
+class SensorFeatures(yaml.YAMLObject):
+    yaml_tag = u'!SensorFeatures'
+
     def __init__(
         self,
         grouping_variable,