From e2db8acb132a6774a3d8db53597c6e30bf86fc8b Mon Sep 17 00:00:00 2001
From: Manos <manos@delkappa.com>
Date: Fri, 24 Sep 2021 13:26:48 +0200
Subject: [PATCH] code: Goal thresholds

---
 code/parse_hue.py | 33 ++++++++++++++++++++++++++++++++-
 1 file changed, 32 insertions(+), 1 deletion(-)

diff --git a/code/parse_hue.py b/code/parse_hue.py
index 3228000..5f237a8 100644
--- a/code/parse_hue.py
+++ b/code/parse_hue.py
@@ -35,7 +35,7 @@ def main(args):
   '''
     Load data
   '''
-  # Get consumption data from previous parsing
+  # Get consumption data [timestamp, consumption] from previous parsing
   cons_data = lmdk_lib.load_data(args, 'cons')
   if cons_data.size == 0:
     # Consumption [dt, hr, kwh]
@@ -61,6 +61,37 @@ def main(args):
       print('[Error: %s]' %(e))
     # Save to results
     lmdk_lib.save_data(args, np.array(cons, np.float32), 'cons')
+  '''
+    Find thresholds for goals.
+    0.2: 0.30
+    0.4: 0.23
+    0.6: 0.15
+    0.8: 0.13
+  '''
+  # {goal: theta}
+  lmdk = {}
+  # Percentage of landmarks
+  goal = [.2, .4, .6, .8]
+  # Find max consumpton to start from
+  theta = max(cons_data[:, 1])
+  cons_data_cur = np.copy(cons_data)
+  # Find thetas for each goal
+  for g in goal:
+    print('Looking for %.1f... ' %(g), end='', flush=True)
+    while theta > 0:
+      # Reduce threshold gradually
+      theta -= .01
+      # Find data below the current theta
+      cons_data_cur = cons_data_cur[cons_data_cur[:, 1] < theta]
+      # Calculate the percentage of landmarks
+      diff = (len(cons_data) - len(cons_data_cur))/len(cons_data)
+      # Check if it is close enough to what we need
+      if abs(diff - g)/g < .05:
+        print('%.2f' %(theta))
+        lmdk[g] = theta
+        # Continue with the next goal
+        break
+
 
 
 '''