Improve column names of daily summary

Author: aidanacquah

src/actinet/utils/eval_utils.py

@@ -7,16 +7,9 @@
 from scipy import stats
 from sklearn.metrics import accuracy_score, f1_score, cohen_kappa_score, balanced_accuracy_score, confusion_matrix
 import warnings
-
 warnings.simplefilter("ignore", UserWarning)
 
-ACTIVITY_LABELS_DICT = {
-    'sleep': 'Sleep',
-    'sedentary': 'Sedentary Behaviour',
-    'light': 'Light Activity',
-    'moderate-vigorous': 'Moderate-Vigorous Activity'
-}
-ACTIVITY_LABELS = list(ACTIVITY_LABELS_DICT.keys())
+from actinet.utils.utils import ACTIVITY_LABELS_DICT, ACTIVITY_LABELS
 
 
 class DivDict(dict):

src/actinet/utils/summary_utils.py

@@ -1,7 +1,7 @@
 import pandas as pd
 from pandas.tseries.frequencies import to_offset
 import numpy as np
-from actinet.utils.utils import infer_freq
+from actinet.utils.utils import infer_freq, ACTIVITY_LABELS_DICT
 
 
 def impute_missing(data, extrapolate=True):
@@ -203,10 +203,10 @@ def _total_hrs(x, min_wear=None, dt=None):
 
     daily = data.resample('D')\
                 .agg(_total_hrs, min_wear=min_wear_per_day, dt=dt)\
-                .rename(columns={label: f"{label.capitalize()}(hours)" for label in labels})
+                .rename(columns={label: f"{ACTIVITY_LABELS_DICT[label]}(hours)" for label in labels})
     daily_adj = data_adjusted.resample('D')\
                              .agg(_total_hrs, min_wear=min_wear_per_day, dt=dt)\
-                             .rename(columns={label: f"{label.capitalize()} Adjusted(hours)"
+                             .rename(columns={label: f"{ACTIVITY_LABELS_DICT[label]} Adjusted(hours)"
                                                 for label in labels})
 
     summary = pd.concat([daily, daily_adj], axis=1)

src/actinet/utils/utils.py

@@ -2,11 +2,19 @@
 import re
 import numpy as np
 import pandas as pd
-from scipy import stats
 from scipy.interpolate import interp1d
 from typing import Union
 
 
+ACTIVITY_LABELS_DICT = {
+    'sleep': 'Sleep',
+    'sedentary': 'Sedentary Behaviour',
+    'light': 'Light Activity',
+    'moderate-vigorous': 'Moderate-Vigorous Activity'
+}
+ACTIVITY_LABELS = list(ACTIVITY_LABELS_DICT.keys())
+
+
 def infer_freq(t):
     """Like pd.infer_freq but more forgiving"""
     tdiff = t.to_series().diff()