From 65ce7e7e72fdcfea4e4d7192909e11e1addcaa4d Mon Sep 17 00:00:00 2001
From: Alexander Minges <alexander.minges@hhu.de>
Date: Thu, 14 Apr 2016 14:04:18 +0200
Subject: [PATCH] calculate adjusted r-squared

---
 analyze-cli.py          |  7 ++++++-
 libkinetics/__init__.py | 26 ++++++++++++++++----------
 2 files changed, 22 insertions(+), 11 deletions(-)

diff --git a/analyze-cli.py b/analyze-cli.py
index 9658172..73fd447 100755
--- a/analyze-cli.py
+++ b/analyze-cli.py
@@ -267,6 +267,7 @@ def main():
     # grab fitting window from provided arguments
     fitting_window = (args.start, args.end)
     
+    # scaling of axes in kinetics plot
     if args.log_x:
         logx = args.log_x
     else:
@@ -276,17 +277,21 @@ def main():
         logy = args.log_y
     else:
         logy = False
-    
+        
+    # suppress calculation of Michaelis-Menten kinetics
     if args.no_michaelis:
         no_mm = args.no_michaelis
     else:
         no_mm = False
 
+    # do Hill kinetics
     if args.hill:
         do_hill = args.hill
     else:
         do_hill = False
 
+    # perform global fit of kinetic function(s) to all replicates
+    # instead of their means
     if args.replicates:
         fit_to_replicates = args.replicates
     else:
diff --git a/libkinetics/__init__.py b/libkinetics/__init__.py
index 0be8752..6a8922b 100644
--- a/libkinetics/__init__.py
+++ b/libkinetics/__init__.py
@@ -82,22 +82,28 @@ class Replicate():
          ) = stats.linregress(x_for_fit, y_for_fit)
 
         r_squared = r_value ** 2
+        
+        n = len(x_for_fit[0]) #  number of observations
+        k = 2  # independent variables: slope and intercept
+        
+        # calculcate adjusted R²
+        adj_r_squared = r_squared - (1 - r_squared) * k/(n - k - 1)
+        
         conc = '{} {}'.format(self.owner.concentration,
                               self.owner.concentration_unit)
 
         self.logger.info('Linear fit for {} #{}:'.format(conc, self.num))
-        if r_squared < 0.9 and r_squared > 0.7:
-            msg = '    r-squared: {} < 0.9; Check fit manually!'
-            self.logger.warning(msg.format(round(r_squared, 4)))
-        elif r_squared < 0.7:
-            msg = '    r-squared: {} < 0.7; Linear fit probably failed!'
-            self.logger.warning(msg.format(round(r_squared, 4)))
-        else:
-            msg = '    r-squared: {}'
-            self.logger.info(msg.format(round(r_squared, 4)))
+        if adj_r_squared < 0.9 and adj_r_squared > 0.7:
+            msg = '    adjusted R² < 0.9; Check fit manually!'
+            self.logger.warning(msg.format(round(adj_r_squared, 4)))
+        elif adj_r_squared < 0.7:
+            msg = '    adjusted R² < 0.7; Linear fit probably failed!'
+            self.logger.warning(msg.format(round(adj_r_squared, 4)))
+            
+        self.logger.info('    R²/adjusted R²: {}/{}'.format(round(r_squared, 4), round(adj_r_squared, 4)))
         self.logger.info('    slope: {}'.format(slope))
         if slope < 0:
-            self.logger.info('    Slope is negative. Will use absolute '
+            self.logger.info('    → Slope is negative. Will use absolute '
                              'value for further calculations!')
         self.logger.info('    intercept: {}'.format(slope))